Tilburg University

Moving toward task virtuality in organizations

Orhan, Mehmet A.

Publication date:2016

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T I L B U R G U N I V E R S I T Y

Moving toward Task Virtuality in Organizations

PROEFSCHRIFT

ter verkrijging van de graad van doctor aan Tilburg University, op gezag

van de rector magnificus, prof.dr. E.H.L. Aarts, in het openbaar te verdedigen

ten overstaan van een door het college voor promoties aangewezen commissie

in de Ruth First zaal van de Universiteit

op maandag 21 maart 2016 om 14.15 uur

door

Mehmet Ali ORHAN

geboren op 07 oktober 1982 te Istanbul, Turkije.

Dit proefschrift is goedgekeurd door de promotoren:

prof.dr. John B. Rijsman

en

prof.dr.ir. Gerda M. van Dijk

Printed by: Carter\Reproplus – Prague

Copyright © 2015 Mehmet A. Orhan

ISBN: 978-80-260-9259-9

T I L B U R G U N I V E R S I T Y

Moving toward Task Virtuality in Organizations

PROEFSCHRIFT

ter verkrijging van de graad van doctor aan Tilburg University, op gezag

van de rector magnificus, prof.dr. E.H.L. Aarts, in het openbaar te verdedigen

ten overstaan van een door het college voor promoties aangewezen commissie

in de Ruth First zaal van de Universiteit

op maandag 21 maart 2016 om 14.15 uur

door

Mehmet Ali ORHAN

geboren op 07 oktober 1982 te Istanbul, Turkije.

iii

Promotiecommissie

Promotores: prof.dr. John B. Rijsman

prof.dr.ir. Gerda M. van Dijk

Overige leden: prof.dr. Petru L. Curşeu

prof.dr. John Goedee

prof.dr. Şule I. Özmen

prof.dr. Rens van Loon

prof.dr. Mark van Vugt

In the memory of my mother

Dr. K. Kâmuran Orhan

&

To my father

Prof. Dr. Osman Z. Orhan

v

ACKNOWLEDGEMENTS

The ‘acknowledgements’ section is one of the most important parts of a doctoral dissertation, not least because it is often the first and potentially the only section to be read by most. However, although not all doctoral dissertations are fun to read, this one was great fun to write. And even though my name appears as the single author of this dissertation, its completion was only possible with the encouragement and opportunities provided by the many people to whom I owe a great deal of gratitude.

Before writing the first sentences of this dissertation, I held the belief that ‘virtuality,’ both in organizational and educational settings, comes with significant limitations in counterpoint to its widely noted benefits. I considered any attempt aiming to replace face-to-face communication as futile and fruitless. My supervisor Prof. Rijsman solidified my beliefs. Ever since our first meeting, I have been amazed with the depth and breadth of the conversations we engaged in. With his vision, expertise, intelligence and constructive supervision, he became my role model. I wish I could continue to apprentice him, since I enjoyed listening to his lessons and experiences about many different topics during all our time together. His vast knowledge of the fields of social and organizational psychology, coupled with his dedication to instruction, is a major source of inspiration for me. The level of respect I have for him is incomparable, and no matter how many times I thank him, it will never suffice. If I could one day provide even a fraction of the support to my future students that Prof. Rijsman gave to me, I would consider myself very successful. Similarly, Prof. van Dijk’s positive attitude, support and guidance were remarkable. I am grateful for her invaluable suggestions throughout my research. In spite of her busy schedule, she made an enormous effort to always be there for me. I consider myself endlessly lucky for having found such a great fit with my supervisors. I could not have done it without them.

I am also indebted to the committee members. I would like to thank Prof. van Vugt and Prof. Özmen for accepting to be on my committee, and for

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their support. I am also grateful to Prof. Goedee and Prof. van Loon for their commitment to the ‘reflective practitioner’ approach besides their other challenging responsibilities; both inside and outside academia. I give special thanks to Prof. Curşeu for contributing to the improvement of the quality of studies in this dissertation. I also acknowledge Dr. Wm. Marty Martin from the Kellstadt Graduate School of Business of DePaul University in Chicago for supporting me since the beginning of my doctoral journey.

I would like also to express my gratitude to the university management and to Prof. Paul Post for being supportive in the establishment of the ‘Reflective Practitioners’ research group at Tilburg University. All involved friends, alumni and professors are wonderful examples of symbiosis—how research and leadership practice can get along. As such, they have all earned my deep appreciation.

Before this thesis assumed its final shape for submission, most of its chapters already passed through several checkpoints. I would like to extend my thanks to the editors Prof. Joseph Roberts (Administrative Sciences) and Prof. Jesús F. Salgado (Journal of Work and Organizational Psychology) and the five anonymous reviewers who helped ensure all academic standards for this study were met. Furthermore, I am indebted to Dr. Juliane M. Deacutis and Dr. Julie Spergel for their editorial corrections. If this thesis is readable, it is because of them. Nevertheless, I acknowledge that all remaining errors belong to me.

In academia, teaching is inseparable from research. Over the last two years, I was able to work with enthusiastic students with a profound interest in organizational psychology. Had I not met doc. PhDr. Milan Rymeš, CSc. and doc. PhDr. Ilona Gillernová, CSc. from the department of psychology in the famous Faculty of Arts at the Charles University in Prague, I would not have had the wonderful opportunity and privilege to teach at one of the oldest universities in Europe. I can therefore not thank them enough.

My journey would have been much more difficult had it not been for the support of many friends. First, I would like to thank to Dr. Deniz Baglan for his assistance on an almost daily basis. Whenever I had a methodological question, he was there to guide me; whenever I was discouraged, he emboldened me with his logical and analytical talks. The other sources of motivations include Kürşat Tayfur and Gökhan Arslan from Istanbul; Taşkın Aşan, Görkem and Bojana Yazıcıoğlu and Jan Gaszczyk from Prague; Eray Altılı from Belgium and Burak Malay from the Netherlands. All deserve credit for their support from the beginning to the completion of this dissertation.

But of course this process was not all rainbows and cherry blossoms. I faced many difficulties throughout this journey. Luckily, however, these difficulties taught me the invaluable and unforgettable lessons now dearer to me than anything else in my life. Occasionally, it was precisely these challenges that spurred me on more than anything else could. I am therefore extremely indebted to those who made these sometimes painful, sometimes joyful lessons clear to me. So many people have contributed meaningfully to my life and have helped me see things differently, and I thank you all.

Vážená babičko, jak jsem sliboval, tak konám. A je to tady. Konečně se mi podařilo úspěšně získat titul PhD. Doufám, že Vám to bude dělat stejnou radost jako to dělá mně. Upřímně jsem rád, že jsem dodržel slovo. A ještě navíc, dřive než jsem očekával, díky tomu, že jsem měl (asi) štěstí. Ale, nakonec člověk stejně nikdy neví jestli měl štěstí doopravdy... Velmi Vám děkuji za vaší důvěru.

Ve en nihayetinde ailem…Emekleri bende sonsuz olan annem ve anneannemin ruhlarını umarım şad edebilmişimdir. Ayrıca, babam Prof.Dr. Osman Z. Orhan, kardeşim Aylin Türe Orhan ve de Yard.Doç.Dr. Failatun Sarı Orhan’a desteklerinden dolayı minnet ve teşekkürlerimle...

Mehmet A. Orhan Dec 24, 2015

ix

MOVING TOWARD TASK VIRTUALITY IN ORGANIZATIONS

Table of Contents CHAPTER 1: INTRODUCTION ......................................................................................1

INTRODUCTION ......................................................................................................2

MOTIVATION OF THIS STUDY: DISCOVERY OF THE PROBLEM .............................2

SCOPE AND PURPOSE OF THE THESIS ..................................................................8

REFERENCES ....................................................................................................... 12

CHAPTER 2: RE-SEARCHING THE DEFINITION: A CRITICAL REVIEW OF THE VIRTUAL TEAM LITERATURE .................................................................................... 15

INTRODUCTION .................................................................................................... 17

PROBLEM STATEMENT ......................................................................................... 19

LITERATURE REVIEW ........................................................................................... 22

THE CONCEPT OF VIRTUALITY ......................................................................... 22

THEORETICAL APPROACHES TO VIRTUALITY .................................................. 26

METHODOLOGY ................................................................................................... 34

THE SCOPE OF REVIEW ................................................................................... 34

ANALYSES ......................................................................................................... 38

FINDINGS.............................................................................................................. 42

CITATION ANALYSES ........................................................................................ 44

CONTENT ANALYSES ........................................................................................ 49

DISCUSSION AND IMPLICATIONS ......................................................................... 54

GENERAL DISCUSSIONS................................................................................... 54

THEORETICAL DISCUSSION ............................................................................. 60

LIMITATIONS ..................................................................................................... 61

CONCLUSION ........................................................................................................ 62

REFERENCES ....................................................................................................... 64

APPENDIX ............................................................................................................. 87

CHAPTER 3: EXTENDING THE INDIVIDUAL LEVEL OF VIRTUALITY: IMPLICATIONS OF TASK VIRTUALITY IN VIRTUAL AND TRADITIONAL SETTINGS ............................ 89

INTRODUCTION .................................................................................................... 91

WHAT HAPPENED AT YAHOO IN 2013? ................................................................ 92

THE CONCEPT OF VIRTUALITY ............................................................................. 93

TASK VIRTUALITY EXPLAINED.............................................................................. 95

TASK VIRTUALITY AND YAHOO .......................................................................... 100

WHY TASK VIRTUALITY SHOULD MATTER ......................................................... 102

PRACTICAL IMPLICATIONS FOR MANAGERS ...................................................... 103

LIMITATIONS AND DIRECTIONS FOR FURTHER STUDIES .................................. 105

CONCLUSION ...................................................................................................... 106

REFERENCES ..................................................................................................... 109

CHAPTER 4: INVISIBLE, THEREFORE ISOLATED: COMPARATIVE EFFECTS OF TEAM VIRTUALITY WITH TASK VIRTUALITY ON WORKPLACE ISOLATION AND WORK OUTCOMES ............................................................................................................ 113

INTRODUCTION .................................................................................................. 115

THEORY AND HYPOTHESIS ................................................................................ 117

VIRTUALITY AND ISOLATION .......................................................................... 117

ISOLATION AND WORK OUTCOMES ............................................................... 121

PERFORMANCE AND SATISFACTION .............................................................. 122

TURNOVER INTENTION ................................................................................... 123

FURTHER HYPOTHESES ................................................................................. 124

METHODOLOGY ................................................................................................. 126

DATA COLLECTION AND SAMPLE ................................................................... 126

MEASURES ..................................................................................................... 127

FINDINGS............................................................................................................ 131

RESULTS ......................................................................................................... 131

DISCUSSION ....................................................................................................... 146

LIMITATIONS AND DIRECTIONS FOR FURTHER RESEARCH .............................. 148

PRACTICAL AND MANAGERIAL IMPLICATIONS ................................................... 149

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REFERENCES ..................................................................................................... 152

APPENDICES ....................................................................................................... 159

APPENDIX I. THE QUESTIONNAIRE ................................................................ 159

APPENDIX II. STATISTICAL DETAILS OF COMPARISONS FOR REGRESSION LINES PREDICTING STUDY CONSTRUCTS ...................................................... 164

APPENDIX III. RESULTS OF PATH ANALYSES WITH DIRECT AND INDIRECT EFFECTS ......................................................................................................... 170

CHAPTER 5: NARRATIVE VOICES ON CHALLLENGES OF TASK VIRTUALITY: A QUALITATIVE STUDY .............................................................................................. 175

INTRODUCTION .................................................................................................. 177

GENERAL METHODOLOGICAL DISCUSSION ...................................................... 178

METHODOLOGY AND DESIGN ............................................................................ 179

INTERVIEWEES’ BACKGROUNDS ....................................................................... 181

PERSONAL PROFILES ..................................................................................... 182

RESEARCH AND INTERVIEW QUESTIONS .......................................................... 185

CASES AND REFLECTED CHALLENGES OF TASK VIRTUALITY .......................... 186

LIMITATIONS ...................................................................................................... 206

CONCLUSION ...................................................................................................... 207

REFERENCES ..................................................................................................... 209

CHAPTER 6: CONCLUSION AND FINAL REFLECTIONS ........................................... 213

FINAL DISCUSSIONS........................................................................................... 214

SUMMARY OF FINDINGS .................................................................................... 216

MANAGERIAL IMPLICATIONS .............................................................................. 218

FINAL REFLECTIONS AND CLOSING REMARKS ................................................. 222

REFERENCES ..................................................................................................... 224

SUMMARY............................................................................................................... 226

ABOUT THE AUTHOR ............................................................................................. 227

List of Figures

Figure 1. Representative Workflow Diagram .................................................................5 Figure 2. Google Ngram Viewer Graph with the Word “virtual” ................................... 23 Figure 3. The Linear Measure of Virtuality ................................................................. 29 Figure 4. An Illustration of the Multiple Linear Measurement of Virtuality ................. 30 Figure 5. Word Cloud of the Definitions of Virtuality .................................................. 39 Figure 6. Word Cloud of Entered Codes ..................................................................... 42 Figure 7. Frequency Distribution of the Number of Dimensions Used in Each Definition ................................................................................................................................. 50 Figure 8. Venn Diagram for Highly Used Dimensions in Definitions ........................... 52 Figure 9. Venn Diagram: ICT & Geographic Dispersion & Minimal Face-to-Face Contact ..................................................................................................................... 53 Figure 10. Number of Articles Citing Temporary Lifespan – Project Work by Year ....... 56 Figure 11. Integrated Conceptual Model (Model 1).................................................... 125 Figure 12. Dimensional Impacts of Workplace Social Isolation (Model 2) .................. 125 Figure 13. Task Virtuality – Team Virtuality Regression ........................................... 132 Figure 14. Path Analyses of Integrated Structural Equation Model (Model 1) ............ 135 Figure 15. Interaction Effect of Task Virtuality on Perceived Performance – Turnover Intention Association ............................................................................................... 137 Figure 16. Path Analyses of Structural Equation Model for Dimensional Impacts of Workplace Social Isolation (Model 2) ........................................................................ 138 Figure 17. Regression Lines of Team Virtuality vs. Task Virtuality Predicting Study Variables ................................................................................................................. 142 Figure 18. Mapping Team Virtuality vs. Task Virtuality ............................................ 144 Figure 19. Regression Lines Predicting Workplace Social Isolation ........................... 164 Figure 20. Regression Lines Predicting Physical Isolation ......................................... 165 Figure 21. Regression Lines Predicting Informational Isolation ................................. 166 Figure 22. Regression Lines Predicting Job Satisfaction ........................................... 167 Figure 23. Regression Lines Predicting Perceived Performance ................................. 168 Figure 24. Regression Lines Predicting Turnover Intention ....................................... 169 Figure 25. Path Analyses of Model 1 ........................................................................ 170 Figure 26. Path Analyses of Model 2 ........................................................................ 172

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List of Tables

Table 1. Number of Articles Reviewed by Databases ................................................... 35 Table 2. List of Journals covered in the literature review ............................................ 37 Table 3. Sample Coding ............................................................................................. 38 Table 4. Labels and Structure of Coding .................................................................... 41 Table 5. Number of Articles Reviewed by Year ............................................................ 43 Table 6. Number of Reviewed Articles by the Domain of the Journal .......................... 43 Table 7. Coding of Journals' Subject Domains ........................................................... 44 Table 8. Most Cited References .................................................................................. 45 Table 9. Most Cited Definitions: ................................................................................. 47 Table 10. Descriptive Statistics of Dimensions Used for a Single Definition ................ 49 Table 11. Frequency Table of Dimensions Used in Definitions .................................... 51 Table 12. Mostly Cited Definitions: ............................................................................ 57 Table 13.The Complete List of Definition Citations Used in Reviewed Articles ............. 87 Table 14. Two dimensional framework of virtuality .................................................... 97 Table 15. Measurement Scales ................................................................................ 127 Table 16. Descriptive Statistics, Correlation Matrix and Reliability Statistics ............ 134 Table 17. Results of Hierarchical Regression Analysis .............................................. 140 Table 18. Results of Comparative Prediction of Team Virtuality vs Task Virtuality for the Tests of Hypotheses 7-12 ................................................................................... 140 Table 19. T-test Results of Differences within Groups .............................................. 143 Table 20. One-way ANOVA Test Results of Differences between Groups ................... 144 Table 21. Details of Regression Statistics for Workplace Social Isolation Prediction .. 164 Table 22. Details of Regression Statistics for Physical Isolation Prediction ................ 165 Table 23. Details of Regression Statistics for Informational Isolation Prediction ........ 166 Table 24. Details of Regression Statistics for Job Satisfaction Prediction .................. 167 Table 25. Details of Regression Statistics for Perceived Performance Prediction ........ 168 Table 26. Details of Regression Statistics for Turnover Intention Prediction .............. 169 Table 27. Details of Structural Equation Model 1 ..................................................... 170 Table 28. Details of Structural Equation Model 2 ..................................................... 172 Table 29. Details of Interviews ................................................................................. 181 Table 30. Summary of Background Profiles of Interviewees ...................................... 183

ABBREVIATIONS

CD Cultural diversity CMC Computer mediated communication EMEA Europe, Middle East, Africa F2F Face-to-face GD Geographic dispersion GVT Global virtual team ICT Information and communication tools ID International dispersion INFO_ISO Informational isolation INTT Interdependent tasks INDT Independent tasks JS Job satisfaction LF2F Lack of face-to-face contact MF2F Minimal face-to-face contact ND National dispersion NH No (previous) history OD Organizational dispersion PPERF Perceived performance PW Project work PHYS_ISO Physical isolation RB Rational boundaries SYNC Synchronicity TASKVIRT Task virtuality TD Temporal dispersion TEAMVIRT Team virtuality TL Temporary lifespan TURN_INT Turnover intention VT Virtual team WSI Workplace social isolation

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1

CHAPTER 1: INTRODUCTION

Chapter

1

2

INTRODUCTION

This thesis is the culmination of my personal reflections acquired through practical experiences in the corporate world over the last few years combined with the scientific studies that are stemmed from these reflections. Ever since immediately after graduation from university in 2006, when I began my career in the private sector, I have worked at the world’s largest and most admired companies, such as ExxonMobil & Electronic Arts, acquiring a great deal of invaluable practical experience. From witnessing daily interactions and activities of people working globally in various organizational settings, I went on to found my own invisible lab, where I tried to examine people’s behaviors at work and to link the existing organizational theories to our work practices. Due to the size and structure of operations, I had to deal with many dispersed colleagues across the world, even though I did not have any previous experience in virtual settings. Over the years, to understand better the dynamics of my secret lab, I tried to find some answers from the existing body of knowledge on virtual team research. On some occasions, I was satisfied with the empirical findings and conceptual studies. Other times, I struggled to understand the answers, which did not provide enough guidance and offered very little relevance. At some point, I realized that my real-life reflections had no one-to-one correspondence in the literature of management and organizational theories. Approximately six years later, with all of these observations having remained unaddressed in the literature, I came up with an idea how to connect these missing links. I therefore consider myself as lucky enough to have been able to detect a real-life research problem and to begin research that fills this gap with some practical implications in addition to theoretical contributions.

MOTIVATION OF THIS STUDY: DISCOVERY OF THE PROBLEM

In 2008, when I was assigned to a virtual project team in my first job at ExxonMobil, I couldn’t imagine that my learning experiences would eventually lead to a doctoral candidacy. In addition to my existing

3

responsibilities, the workload of the virtual project was quite challenging. Not only were the different nationalities, cultures, and time zones an issue, but the lengthy electronic communications and frequent travel were also very demanding. All of these challenges caused my growing interest in virtual team research. The more I read about it, the more I enjoyed it. And the more I found myself struggling with the difficult conditions of a virtual workplace, the greater the need to consult academic studies chiefly focused on discovering ways to increase virtual team effectiveness. At that time, I was also amazed by the number of articles written about virtual teams, as these structures were only beginning to become prevalent in organizations. The number of studies has been increasing every day; although new empirical findings with managerial and practical implications shed some light on virtuality, the distinct characteristics of virtual teams become ever more obfuscated. Once our virtual team progressed further in our project work, I personally faced many further challenges. The differences of social mechanisms in a virtual team environment compared to a traditional one ignited my curiosity about virtual team dynamics, particularly the person−environment fit in virtual settings. In those days, I had come to believe that there were certain types of personalities that align better with the requirements of virtual teamwork and can be more successful than others. Perhaps this meant that simply because of my personality, I did not fit in well with a virtual team setting. Or maybe my (social) skills were not wholly reflected in front of a computer screen as they would be in reality. It could be a personality-related issue or my cognitive style, as pointed out by Luse et al. (2013). Was my strong preference for face-to-face interactions over ICT-mediated ones a sign that I was not cut out for virtual work? Maybe there was something else… But I had no (definitive) answer.

A few years after, I changed jobs, and everything changed. There was a shift to a permanent virtual setting in another multinational company. In my previous role, my virtual team experience had been limited to the project work with which I was involved. This time, however, I had team members from all over Europe. Distances, different cultures, and time constraints rose to a more

4

challenging level than before. Although I had previous virtual teamwork experience, albeit to a lesser degree, I could not be happy with my performance. It was becoming obvious to me that I lacked the knowledge, skills and abilities to cope with the difficulties of a virtual environment. I began to believe that I did not belong there. When I read the Randstad report (2012) on the cultural differences in face-to-face contact over electronic communication, I was almost sure that there was a mismatch between virtual teamwork and my personality and cultural background. The report revealed that the majority of Turkish employees (more than 80% of the respondents) were in favor of face-to-face contact over phone or e-mail compared to other nations, which are indifferent to any mode of communication. Singapore, Norway and the US have a face-to-face communication preference of 56%, 57%, and 60%, respectively. I thought to myself: “I am Turkish, so that explains everything. Eureka!”

Soon after, however, I realized that there was something beyond the virtual teamwork that made my job challenging. And it was slightly more complicated. The chasm created between a virtual work setting and my nationality and culture could only explain so much, as my self-identification does not rely heavily on my Turkish background. Moreover, stereotyping is in no way part of my world view, so how could I accept it for myself? There had to be another reason why I was not satisfied with what I was doing. There had to be other factors behind my (not very strong) performance, even though I was consistently assessed as a good performer. It was around this time that I began thinking about how communication with non-face-to-face contacts has impacted the current business world more than anything else. I was only communicating with my team via electronic means. My team was composed of three members (regional risk managers) including me and one supervisor. Our team leader was Chris, a UK national working in the headquarters of our company in Geneva, Switzerland, managing the European risk organization. One of my teammates working in the Guilford office, Wayne, also a UK national, was mainly responsible for UK retailers. The other teammate, Sebastien, a French national working in our Lyon office, was in charge of the

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French retailers. And then there was me. A Turkish national working in the Prague office in Czech Republic, mainly responsible for German retailers. I had frequent online conferences, phone sessions and seemingly endless email traffic, either in German or English. Moreover, in the office, I pushed myself to communicate in Czech, although I was not really fluent at that time. This was in complete agreement with the discontinuities perspective provided by Chudoba and colleagues (2005), in which they aimed to measure the virtuality in teams. There were many more discontinuities in my new work practices and a higher dispersion of people I worked with. However, I had been experiencing another kind of discontinuity with all others involved in my job. I did not share the same office with the team members and colleagues with whom I had to confer. I was not using a language I was fully fluent in. Additionally, I observed dramatic differences from an organizational design point of view. I observed that my teammates had a pooled interdependence with the agents they work with (represented as circles 1 and 2 in Figure 1), whereas my task interdependence can be considered as an intensive one. On the other hand, all people involved in my job, were geographically dispersed in terms of being based at different sites; culturally diverse in their perspectives of work practices; and organizationally dispersed as they communicated via electronic tools. As our workflow within the team had a pooled/additive structure, we had a very limited interdependence within the team. Interdependence with others (colleagues, co-workers), however, was relatively high. The people I mostly worked with were separated from me, unlike how the work was set up for Wayne or Sebastien.

Figure 1. Representative Workflow Diagram Source: Adapted from Maynard et al. (2012)

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As risk managers, we were in charge of reporting monthly financial exposures and sales revenues, which required a great deal of collaboration with sales and accounting teams. In order to process reports and complete the tasks, I needed their input. Most of the time, I was among the last people informed about the required changes in reports. “Out of sight, out of mind” was a significant issue. I remember the occasions when I had to change the report several times during the course of one day, since several things had not been communicated to me by the German teams, or there were multiple changes required in the reports that had only been communicated right before the submission deadline. These were the most stressful days of the entire assignment, since I had many time constraints, and this pressure increased when these challenges were added into the working routine.

A few years after, I read the internal memo written by Marissa Mayer for Yahoo employees in February 2013. It was intended to be confidential, a for-company-use-only announcement, but it was leaked and quickly garnered public attention and controversy due to the cancellation of flexible working options, which is considered as a must-have benefit in technology companies. Her memo reads: “…To become the absolute best place to work, communication and collaboration will be important, so we need to be working side-by-side. That is why it is critical that we are all present in our offices. Some of the best decisions and insights come from hallway and cafeteria discussions, meeting new people, and impromptu team meetings… We need to be one Yahoo!, and that starts with physically being together.”1 She was partly right. In that note, I realized how important it was to be side by side with those you work with. This is was what I had been missing all along. But there was still an issue: I was not working from home. I was already in the office, just not the office where all my peers and other colleagues were located. Lack of face-to-face interaction with peers and colleagues that are not in my team had more 1 As reported in various newspapers, magazines etc. See for example: Thomson, Derek. (Feb 25, 2013). “Marissa Mayer is wrong: Working from home can make you more productive”. The Atlantic. Retrieved from: http://www.theatlantic.com/business/archive/2013/02/marissa-mayer-is-wrong-working-from-home-can-make-you-more-productive/273482/

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impact on my performance: More than my team members. I was sharing more information with those people, and I needed more information from them. And virtuality of my team has nothing to do with it. If we were a traditional team, sitting side by side with Sebastien and Wayne, and my job was still dependent on those others whom I do not physically interact, I would still feel the impacts and challenges of virtuality. I discovered then that one does not need to be on a virtual team to be impacted by virtuality. Nor does being a part of virtual team guarantee that virtuality will be experienced. As a result, the implication is that the effects of virtuality can still be experienced if other people outside the team are also geographically separated and can only be reached via electronic communication tools. I subsequently realized that virtuality should be treated as a job characteristic, although it is often referred to a team or organizational level construct (Hertel et al., 2005). Most of the issues clustered under the rubric of virtual team literature partly include the challenges that not only belong to virtual team settings. Virtuality in teams can also be partially responsible for challenges. I thus found an obvious reason to uncover the mystery, as the extent of virtuality in my own team had something to do with my existing work practices in the organization. This must be it, the reason why I felt more virtual than any other of my team members, and nothing felt real.

Since then, I recognized that there were two different worlds. All the scholarly studies on virtual teams mostly address issues exclusively within teams. The influence of virtuality sourced by the separation of team members are then further elaborated upon in those studies. On the other hand, all other interactions with others outside of teams were neglected. Lack of face-to-face communication was considered a real challenge for virtual team members. But how about for people working in traditional teams that had to communicate with others virtually? Is that not a challenge in and of itself, if others (customers, co-workers, suppliers, etc.) cannot be physically contacted? And, what about trust? When team members are distant from each other, building trust becomes more difficult. How about with customers when there is no physical contact? How can I trust suppliers if I do not know their

8

working practices? Moreover, in the literature, there are many other constructs associated with team virtuality such as isolation, connectedness, and organizational identification. However, we simply do not know how much individuals are affected by virtuality and how much of it specifically by team virtuality as opposed to task virtuality. Task virtuality is a concept that is introduced as the core of this research. It is a concept that relates virtuality to our jobs and tasks performed daily at the individual level instead of associating it with the team or organizational level concepts. This concept tries to answer the following question: How forceful is the impact of not being able to contact all others (that are both inside and outside of the team) in a face-to-face manner?

The related research questions designed for this thesis are the

following:

• How can we measure virtuality in a unique way that captures both interactions within a team, as well as those outside of the team?

• How can we compare these two types of virtuality in organizational settings?

• If there is a valid tool to measure the individual impacts of virtuality, can we measure organizational and behavioral outcomes with it?

• Will that measurement tool be able to predict organizational outcomes better than the tool for team virtuality?

• And how business practitioners experience virtualities and cope with the challenges, especially in relation to task virtuality, in organizations?

SCOPE AND PURPOSE OF THE THESIS

Ultimately, the purpose of this thesis is to answer the research questions in a systematic way as outlined in the previous section. In order to be able to do so, there are a few requirements that act as a scaffold for this

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thesis. First, there is a need to conceptually define the term “virtuality” as it is considered one of the most contentious terms in the literature. We thus need to examine how virtuality is defined and revisit its common characteristics, which will constitute the basis for the development of a means of measuring task virtuality.

This study introduces a theoretical concept called “task virtuality” and goes on to illustrate its impacts. Parameters for task virtuality are derived from definitions of virtuality appearing in existing management and organizational studies. To be able to understand all sides of the term, this book starts with a critical literature review outlining how the concept of virtuality in teams and organizations has been defined and described in past research. After the content analysis, Chapter 2 continues with a synthesis of the most commonly cited characteristics and dimensions of virtual teams by scholars. A discussion of why current virtual team research fails to reach a consensus on a single definition follows. Subsequently, several examples are provided to highlight why most of these definitions cannot be applied to all virtual team variations, describing the exceptions restricting applicability of these definitions. For this reason, a unique and universal definition of how virtuality in teams should be defined based on the gap observed in past research is proposed. The proposed definition that focuses on face-to-face contact is a common determinant of team virtuality as well as task frequency. This interpretation implies that the less face-to-face contact a team has, the more virtual characteristics it has depending on task frequency. As a result, this study expands the understanding of the team virtuality concept with a correct means of measuring that focuses not only on the lack of face-to-face communication, but also on the characteristics of team virtuality that can vary significantly.

Chapter 3 introduces the core of this thesis, namely, that the task virtuality of individuals in organizations is its own type of virtuality. Unlike previous definitions of virtuality, however, virtuality is here conceived as a characteristic belonging exclusively to individuals’ tasks rather than being

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present at the team level. Based on the proposed definition of team virtuality, which takes face-to-face contact into account, the task virtuality phenomenon in organizations becomes crucial to identifying virtuality since working in a virtual environment is no longer a characteristic unique to virtual team settings. Even employees working in traditional forms of organizational settings at corporate organizations interface with dispersed contacts, colleagues, clients, or suppliers via electronic tools. This implies that the challenges faced in virtual teams can also be shared by many employees, even if their team structure remains conventional. Similarly, employees working in virtual teams may possess fairly low task virtuality depending on the designed organizational structure. Therefore, Chapter 3 illustrates how task virtuality is relevant for the design of organizations. A proposed two-dimensional framework integrating both team and task virtuality elements in organizations not only allows the conceptualization of task virtuality, but also provides a practical guidance for managers to understand the factors leading to high task virtuality and to deal with the complexities that arise from task virtuality in organizations.

In the next section, Chapter 4, an empirical research study is designed to present an integrated model between workplace social isolation, work outcomes and turnover intention and to demonstrate the relations between organizational variables and task virtuality. Rhetorical and anecdotal evidence largely cover how human beings are isolated in the social context using more technological products and taking part in virtual communities (Turkle 2011; 2012). In organizational settings, virtual teams are found partly responsible for the isolation of a globalized workforce (Raghuram, et al., 2001; Mulki & Jaramillo, 2011). This study posits empirical evidence that task virtuality is a relevant and appropriate concept that explains workplace isolation and related work outcomes.

In social sciences, qualitative methods complement quantitative studies with storytelling (Jick, 1979). The triangulation method is also found to be a robust technique that improves validation of the investigated

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constructs and accuracy of judgments. Taking a holistic approach to corroborate the triangulation method, Chapter 5 presents a qualitative study, whereby the findings of semi-structured interviews are discussed.

Finally, Chapter 6 is a review of the body of research studies summarizing the findings. Under the light of results presented in Chapters 2−5, managerial and practical implications of task virtuality are discussed along with their theoretical relevance in the management and organizational psychology fields.

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REFERENCES

Chudoba, K. M., Wynn, E., Lu, M., & Watson-Manheim, M. B. (2005) How virtual are we? Measuring virtuality and understanding its impact in a global organization. Information Systems Journal, 15, 279-306.

Hertel, G., Geister, S., & Konradt, U. (2005), Managing virtual teams: A review of current empirical research. Human Resource Management Review, 15, 69-95.

Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24, 602-611.

Luse, A., McElroy, J. C., Townsend, A. M., & DeMarie, S. (2013). Personality and cognitive style as predictors of preference for working in virtual teams. Computers in Human Behavior, 29(4), 1825-1832.

Maynard, M. T., Mathieu, J. E., Rapp, T. L., & Gilson, L. L. (2012). Something(s) old and something(s) new: Modeling drivers of global virtual team effectiveness. Journal of Organizational Behavior, 33, 342-365.

Mulki, J. P., & Jaramillo, F. (2011). Workplace isolation: Salespeople and supervisors in USA. International Journal of Human Resource Management, 22(4), 902-923.

Raghuram, S., Garud, R., Wiesenfeld, B., & Gupta, V. (2001). Factors contributing to virtual work adjustment. Journal of Management, 27(3), 383-405.

Randstad. (2012). Personal contact preferred: Dealing with information overload, job satisfaction and mobility. Randstad Workmonitor Global Press Report, Wave 1.

Suh, A., Shin, K., Ahuja, M., & Kim, M. S. (2011). The influence of virtuality on social networks within and across work groups: A multilevel approach. Journal of Management Information Systems, 28(1), 351-386.

Turkle, S. (2011). Alone together: Why we expect more from technology and less from each other. New York: Basic Books.

Turkle, S. (2012, March 1). Sherry Turkle: Connected, but alone?. [Video file]. Retrieved from: http://www.ted.com/talks/sherry_turkle_alone_together/

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CHAPTER 2: RE-SEARCHING THE

DEFINITION: A CRITICAL REVIEW OF

THE VIRTUAL TEAM LITERATURE

Chapter

2

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Abstract:

The purpose of this study is to present a review of the scholarly literature on virtual teams and to redefine the key characteristics and features of ‘team virtuality’ and ‘virtual teams’. A literature review through content analyses was conducted using the Web of Science, ABI/Inform and EBSCO databases in order to comprehensively explore all definitions and characteristics of the concepts of ‘virtual team’ and ‘team virtuality’. A total of 265 articles published between 2006 and 2013 were analyzed, and the details of the content analyses are herein presented. The analyses reveal that the characteristics and definitions are often contradictory and rarely correspond, thereby attesting to a gap in the literature. With this study, we present a portrait that exposes the literature’s one-sided focus on a virtual team’s geographic dispersion and its dependency on electronic communication as the core sources of virtuality.

This study aims to unify the definitions and ultimately propose a new definition that helps to measure virtuality more comprehensively by addressing the gap observed in past research. This paper contributes to the literature incorporating the studies from the most extensive fields of research.

Keywords: Virtual teams, team virtuality, definition, literature review, content analysis

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INTRODUCTION

Over the last two decades, we have been living in an increasingly connected society, where we interact with each other at a much higher frequency, even though we no longer need to meet face to face. Today, business organizations are those mostly benefiting from the vast availability and accessibility of electronic communication tools; not only due to cost advantages, but also due to the greater flexibility offered by these new technologies (Bell & Kozlowski, 2002). Advancements in communication technologies have also allowed organizations to reorganize their work structures by outsourcing tasks and workforces to another corner of the world for cheaper and easier labor (Janssen & Joha, 2008; Curseu et al., 2008; Hertel et al., 2005; Kirkman et al., 2004; Montoya-Weis et al., 2001; Townsend et al., 1998, Lipnack & Stamps, 1997). The most common of these new work structures, “virtual teams” has now become an inseparable part of today’s business world (Vartiainen, 2006). With this monumental development, a great deal of scholarly attention was paid to virtual team research, quickly becoming one of the most popular topics in many different disciplines ranging from management to education, and from psychology to computer sciences. The different perspectives contributed a very rich and diverse input on the design, processes, leadership and outcomes associated with team virtuality. According to a 2002 study, Gartner, an information technology research and advisory firm, claimed that more than 60% of professional employees work in virtual teams worldwide (Martins et al, 2004; Kanawattanachai & Yoo, 2002). The consulting firm also estimated that by 2016 this number will reach 80% among global 2000 leading companies (Gartner, 2012). However, with the diversity of interdisciplinary approaches to the concept of “virtual teams”, the meaning of “virtuality” is treated differently. The consequent ambiguity means constructing a precise, comprehensive definition has become even more difficult. As of yet, there is still no universal understanding of what a virtual team is and how it should be defined (Gilson et al. 2015).

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When virtual teams first emerged, they were considered merely to be temporary task forces assigned to particular, short-term projects (Lipnack & Stamps, 1997 & 1999; Jarvenpaa & Leidner, 1999). Today, the virtuality concept for teams has expanded from its initial definition. While the novel approaches focus on a simplified measuring tool for the degree of virtuality (Hoch & Kozlowski, 2014; Maynard et al. 2012), the old definitions are still widely in use in current research literature. This study thus addresses this semantics issue still observed in the literature.

With the shift from the extensively studied “virtual teams” notion and its successor “virtuality in teams,” a general discrepancy can be observed: virtual teams are considered those with the highest level of virtuality (Hertel et al., 2005). The in-depth literature reviews enhanced our understanding of the implications brought about by virtual teams. However, this present study differs from previous literature reviews on virtual teams in a number of ways. Firstly, although the majority of literature reviews narrowed their focus to a small number of disciplines and limited their review scope to the major business, management, information systems, psychology, and communications journals (Martins et al., 2004; Gibson & Gibbs, 2006; Kirkman et al., 2012), the concept of virtuality is a multidisciplinary phenomenon (de Guinea, Webster, & Staples, 2012). Virtual teaming is a term and a practice widely used and written about in fields as divergent as engineering, library sciences, computer sciences, cybernetics, education, economics and industrial relations. Therefore, this review examines the issue of virtuality from a much broader perspective than has yet been undertaken. Secondly, the methodology used in this article was purposely objective, so elimination criteria based on subjective methods used in the past did not restrict the scope of this study. For example, unlike previous studies, articles were taken into account regardless of the number of citations they received and the reputation of the journals that published them. In order to obtain as many articles to review as possible, we utilized EBSCO, ABI/INFORM Global and Web of Science databases for an objective comparison. To observe trends and patterns of virtuality, the review years between 2006 and 2013 were

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analyzed. These new results from the wider review range have underscored the necessity of solidifying a universal definition of virtuality. While this study lays all existing definitions on the table, the proposed definition does not wipe the slate clean. Instead of creating additional confusion, this review aims to streamline the variations in the already existing definitions of virtual team research and summarize their common ground.

This chapter starts by providing a problem statement and outlining the historical development of the literature on virtuality. A description of the scope of the research, design of the review, and research conclusions follow. The final part of this chapter draws upon the entire thesis, tying up the various results and findings and discusses the implications.

PROBLEM STATEMENT

There has been a growing body of literature on virtual team research over the last 15 years. The existing research includes both empirical studies and theoretical approaches. However, the vastness of this empirical research has overshadowed the theoretical foundation and conceptualization required to understand what virtuality really means (Martins et al., 2004). As a result of this growing interest in virtual team studies, a number of characteristics and dimensions have been proposed by researchers. However, because there is still no consensus on an exact definition, this resulted in a long list of items that proved to be of little practical value or were irrelevant for our understanding of team virtuality (Maynard & Gilson, 2013; Hakonen & Lipponen, 2008; Gibson & Gibbs, 2006; Chudoba et al., 2005; Kirkman & Mathieu, 2005). Even though some scholars claim that a minimum level of consensus has been reached in defining a virtual team (Johnson et al., 2009; de Leede et al., 2008), this study posits that this conclusion is not sufficient and lacks clarity. In fact, the disagreement among researchers could hardly be stronger. To illustrate this disagreement, a series of clashing definitions is presented in the following. Whereas de Jong, Schalk & Curseu (2008, p.365) and Curseu & Wessel (2005, p.270), for instance, have noted that “most scholars agree that if a team mainly relies on technology in order to

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communicate, it can be called virtual,” remarking that location is not a dominant factor of virtuality, and Kirkman & Mathieu (2005) agree that geographical dispersion cannot be a determinant of team virtuality, Schweitzer and Duxbury (2010) identified this dispersion as the minimum requirement for team virtuality. Similarly, a significant number of researchers highlighted information and communication technologies (ICT) usage as a standalone determinant of virtual teams, as ICT is the most relevant dimension of virtuality (Johnson et al. 2009; Shekhar, 2006; Workman, 2007a; Ocker, 2007; Anderson et al. 2007; Brahm & Kunze, 2012). Shekhar (2006) associated increased ICT usage with non-face-to-face interaction, whereas Griffith and Neale (2001) empirically illustrated that the level of ICT usage is not dependent on geographical dispersion. As another example, some researchers argued that in spite of common team goals, tasks within a virtual team are independent (Ferreira et al., 2012a; Giaglis & Spinellis, 2012; Guzman et al., 2010; Olson-Buchanan et al., 2007; Davis & Khazanchi, 2007). It is further claimed that the tasks are independent in a virtual team, because predefined and well-structured tasks do not require collaborative coordination (Kratzer et al., 2006), whereas others claimed that interdependence is a distinctive character of a virtual team (Aiken et al., 2013; Turel & Zhang, 2010; Mitchell & Zigurs, 2009; Bosch-Sijtsema, 2007; Hambley et al., 2007a; Schiller & Mandviwalla, 2007; Kirkman et al., 2002). Although Purnanova and Bono (2009) designed a study comparing face-to-face teams to virtual project teams, whereby the lifespan is shorter and team membership is seen as temporal (Bell & Kozlowski, 2002), they drew general conclusions for virtual teams. Kimble (2011, p.7) exemplifies the inconclusive characteristics between all existing definitions as follows:

“The term virtual team can be applied to a number of different types of groups. Team membership may be relatively stable (e.g., in an established sales team) or change on a regular basis (e.g., in project teams). Members may be drawn from the same organization or from several different organizations (e.g., when projects involve consultants or external assessors). Team

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members may work in close proximity (e.g., in the same building) or geographically distantly (e.g., in different countries) and, similarly, team members may work at the same or at different times (e.g., depending on whether the team members are in the same time zone).”

As indicated by a few cited examples only, it can be deducted that virtual team research currently harbors conflicting definitions, clashing dimensions, and ungeneralizable conclusions and that, no clear boundaries have been drawn. In some cases, the confusion is so extreme that a number of researchers mistakenly went ahead and defined virtual teams as “a network group where team members from different cultures are temporarily gathered together for the period of a mission” (Chang et al., 2011), even though the belief in virtual teams’ temporary nature has long been outdated and it is acknowledged that cultural diversity has nothing to do with virtual teamwork, unless global virtual teams are in question. Likewise, Glücker & Schrott (2007) and Eom (2011) have made the same conclusion and consequently mixed the definition of virtual team with that of global virtual team, and added in “cultural diversity” as factor unique to virtual teams, as opposed to conventional teams, which is clearly false, naïve or even irresponsible to some extent. Therefore, amending these gaps observed in virtual team research and righting its wrongs has become imperative.

Based on the examples of contradiction and confusion provided, the following research questions have been formulated:

• How have ‘virtual teams’ / ‘team virtuality’ been defined

in the existing literature? • What is the extent of disagreement among researchers in

defining ‘virtual teams’ / ‘team virtuality’? • Is it possible to integrate all perspectives and to propose a

universal definition?

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While the existing definitions propose multiple dimensions such as geographic temporal, organizational dispersion, electronic communication, task interdependence, or even cultural diversity, the measurement of virtuality often requires fewer dimensions, since the operational definition differs from the theoretical propositions (Martins et al. 2004). Recently, the need for unity and cohesion in quantifying virtuality measurement has been cited in the literature by Gilson and colleagues (2015). Undoubtedly, the answers to these research questions will serve to align of the conceptualization, operationalization, and measurement of virtuality.

LITERATURE REVIEW

THE CONCEPT OF VIRTUALITY

There is a popular belief that the emergence of virtual teams was made possible with the widespread use of information communication technologies (Furst et al. 2004; Ganesh & Gupta, 2008; Bergiel et al., 2008). Although we can acknowledge that virtual team research gained popularity over the last few decades, the word “virtual” has a longer history than current virtual team research. To illustrate this, we applied the n-gram indexing tool available on the Internet. Though the Google Ngram corpus can be criticized for its limitations for complicated search queries (Roth, 2013), its advantages outperform its limitations for simplified (one-word) searches and their trending, because it is the largest and most functional text source available (Roth, 2014; Wang et al., 2010). Therefore, Google Ngram Viewer is used to show the trend of the use of the word “virtual” published books in English since the 1700s (See Figure 2). It is certainly not a new word. According to Longmans English Larousse edited by Watson (1968, p.1288), virtual is defined as “being something specified in essence or effect though not in name”.

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Figure 2. Google Ngram Viewer Graph with the Word “virtual”

Mackenzie (2006) and Massumi (2002) oppose the idea of virtuality referring to exclusively ICT-mediated interactions or something that is related to Internet, though today, the word “virtual” is commonly used interchangeably with other words referring to a state which involves either something that is online or related to some certain level of electronic communication and network, in addition to the Internet (Nyström & Asproth, 2013; O’Keefe & Chen, 2011). From a philosophical perspective, virtuality mainly refers to an abstract concept that signals a temporality and distance to reality (Styhre, 2006). The semantic meaning of virtuality is thus closely linked to an approximation of real existence (Shields, 2006). The underlying assumption about virtuality is that it provides similar experiences with real occurrences, as if they really exist or happen. In the organizational context, the attainment of team tasks is achieved in real terms without the physical formation of a team. However, a team is still a functioning social system (Curseu, 2006), but as these systems’ achievements are highly dependent on information exchange through electronic communication, the large body of the literature considers virtual equal to digital (Mackenzie, 2006; Massumi, 2002). As the Internet provided a digital platform and connected virtual communities, online social relations functioned as well as if they were real (Burt, 2009; Benson, 2007). As a result, with the increased usage of information communication technology tools, the term “virtual” has become a widespread phenomenon that attracted researchers in the social sciences to explore the social relations occurring online. There are also other alternative approaches to describing virtuality. Watson-Manheim and colleagues (2002) used the term

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virtuality to “describe changing work environments” (p. 191). However, this fundamental divergence in the inherent meaning of virtuality contributes to the plurality of the definitions at a very high level. Because these differences in semantic attributions are not aligned, it was no coincidence that virtual team research contained various different perspectives. Consequently, digital connections allowed millions of people to establish virtual relations with others at a distance.

On the other hand, throughout the history of civilization, human beings continuously attempted to communicate with others at a distance. There was an enormous evolution in the channels we use to communicate with others: from smoke signals, drums, pigeons, messengers, signal lamps, telegraphs, telephones, and faxes to today assortment of mobile technologies. One of the most frequently confused elements in the virtual team literature is how these flexible structures emerged and prevailed in today’s business organizations. In the past, people desired continuous connections with each other even when not collocated. International scientific collaboration networks, for instance, already existed in academe even before the Internet was discovered (Frame & Carpenter, 1979). Many overseas scientists collaborated on a project basis and co-authored many publications even without today’s possibilities of getting connected. Even before the widespread public use of the telephone, scientists shared their ideas and thoughts via letters, cooperated distantly, and published scientific papers with no regular face-to-face contact (cf. Einstein & Laub, 1908, 1909)2. Before electronic communication, military teams accomplished their operations via human messengers which were later succeeded by electrical telegraphs (Moss, 1987; Ess & Sudweeks, 2001). None of these teams could have interacted with each other face to face. Further examples can be cited to illustrate that geographically dispersed teams were in fact thriving even before digital communication. The Internet and related technologies only facilitated and accelerated the collaboration (Barker & Dickson, 1996). Despite many

2 Einstein, A., & Laub, J. (1908). Über die elektromagnetischen Grundgleichungen für bewegte Körper. Annalen der Physik, 331(8), 532-540.

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scholars still claiming that virtual teams and communities are the byproducts of the Internet and subsequent networked collaboration through ICT-mediated interactions (Rabby & Walther, 2003), this emergence was not creating but rather fostering older structures of long-distance business operations already in existence.

Although these early examples of virtual work show that the virtual team phenomenon is not a new concept, its theoretical conceptualization, evolution and widespread implementation in business organizations does have a relatively short history. It was the new technologies that allowed for synchronous communication at a cheaper and faster rate. The understanding of the current state of virtual teams, therefore, is that they are structures supported by information communication technologies. However, they are virtual teams (VT) not because of high ICT usage, but because of the lack of face-to-face communication possibilities. Thus, the second contribution of this theoretical study is to broaden the definitions of virtual teams by removing the dependency on the electronic communication and information technologies aspect.

The initial question about the virtual work asked by Handy (1995, p. 41) was “How do you manage people whom you don’t see?”. Unfortunately, the attempt to answer this question ended up blurring virtual team research with the irrelevant dimensions, conflicting definitions and inconsistent study designs that result in a deviation from its original direction (de Guinea et al., 2012). The present state of VT definitions does not capture all possible variations of virtual settings. In order to be able to answer the original research question directed by Handy, there is a need to synthesize the theoretical framework and propose new definitions of virtual teams and team virtuality for the reasons outlined above. In this paper, the literature is examined by raising the question of which dimensions and characteristics every team share and where they begin to diverge.

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THEORETICAL APPROACHES TO VIRTUALITY

A detailed scrutiny of the theoretical approaches to virtuality exposes that the nature of virtuality has changed over this last decade (Hosseini et al., 2015). Although Bell and Kozlowski (2002) supported the idea that virtual teams are distinct and unique forms against traditional teams, “virtual vs. traditional” dichotomy did not succeed in classifying teams because of its rigidity. Within this approach, hybrid structures were not represented, so there was a further need to elaborate on the phenomenon of VT. With the introduction of the degree of virtuality, the concept was considered to be a linear function. Nevertheless, even this approach has been found to be problematic because of the inconsistency of the dimensional constructs developed. This inconsistency stemmed from the fact that researchers could not agree what makes a team more virtual; more distance or more ICT use between team members or something else. The debate for the constructs’ relevance is still alive today. The context of virtuality has become a more complex issue, since the understanding of virtuality has been changed from linear to a continuous form. The continuum approach has allowed researchers to identify the relative differences between team structures by comparing the former constructs in question. This approach then transformed virtuality from being a one-dimensional to a multi-dimensional form. The postmodern approaches, conversely, have investigated the constructs of virtuality as assessing discontinuities rather than a continuum. Watson-Manheim et al. (2002) and later Chudoba et al. (2005) advocated the discontinuity approach, in which virtuality is considered as a distraction from traditional working practices in a team environment. Dixon and Panteli (2010, p. 1179) identified these distractions as “problems of communicating and interacting across a boundary” in contrast to regular, traditionally designed face-to-face teams. In the following section, these approaches are presented in detail with its theoretical development.

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Dichotomy Approach

In earlier virtual team research, virtual teams were considered a temporary structure due to its versatile nature. When the concept was first introduced, mainly project-based work teams with no common history as well as no common future were called virtual due to this temporality (Jarvenpaa & Leidner, 1999). This concept quickly became obsolete, as organizations started realizing that virtual teams could be used for permanent or longer term tasks in organizations; project-based work was therefore no longer a prerequisite of virtual teams. The trend of teaming up members in different geographical locations was a trend that took hold in the business world. Due to the transformation of virtual teams from project-based work into permanent functional tasks, companies did not see any reason not to reassign existing conventional team members in order to form new virtual teams. This meant that having no common history and no common future no longer had anything to do with VT. When distances became less important, more diverse virtual teams emerged. With the side effect of geographic dispersion, cultural diversity became an inevitable element to consider, and therefore, the term “global” virtual teams gained importance in the literature (Staples & Zaho, 2006; Powell et al., 2004; Maznevski & Chudoba, 2000). However, there were different approaches in defining global virtual teams. Is it global due to different cultures (Krumm et al. 2013), different nations (Gibson & Gibbs, 2006), or geographic dispersion (Pinjani & Palvia, 2013)? Because these variables cannot be consistent across the board, conclusions cannot be compared.

It is believed that geographical dispersion, “the most commonly noted boundary” in the literature (Martins et al., 2004), is the key defining characteristic of virtual teams, which distinguishes them from conventional face-to-face teams (Powell et al., 2004; Bell & Kozlowoski, 2002; Jarvenpaa & Leidner, 1999). Some researchers even argued geographical dispersion as a minimum requirement for the classification of virtual team characteristics (Zigurs & Khazanchi, 2008; Dubé & Paré, 2004). Kirkman and Mathieu (2005)

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were among the first researchers to note the theoretical limitations of existing virtual team definitions. They discussed the removal of geographical dispersion as the core characteristic of virtual teams. The justification was as follows: even conventional face-to-face teams exhibit some virtuality, thereby suggesting other indicators as determining virtuality. The source of virtuality arose from “the extent of use of virtual tools (1), the value of the information shared (2), and the synchronicity of team members (3)” (p.706). According to this three-dimensional model, every team could be assessed in terms of its virtuality. Before proposing the team virtuality concept, there was a belief that virtual teams were unique team structures (Bell & Kozlowski, 2002).

Continuum Approach

From Virtual Teams to Virtuality in Teams

The degree of virtuality plays a pivotal role in virtual team research (Dixon & Panteli, 2010). It is widely accepted that virtuality is a continuum, rather than an on-off mechanism, and in this continuum, each teams’ virtuality may vary (Hosseini et al., 2015; Shekhar, 2006; Gibson & Gibbs, 2006; Kirkman & Mathieu, 2005; Chudoba et al., 2005; Hertel et al., 2005; Martins et al., 2004; Shin, 2004). The traditional belief, articulated by Bell and Kozlowski (2002), initially identified virtual teams as unique structures different from traditional teams. However, this view shifted to a more flexible typology of virtuality with the continuum approach (Dixon & Panteli, 2010; Chudoba et al., 2005).

Although the dichotomy view evolved into the continuum approach, the initial attempts could not encompass many dimensions. Instead, the degree of face-to-face communications is considered as a determinant of the level of virtuality (Fiol & O’Connor, 2005; Martins et al., 2004; Griffith et al., 2003; Griffith & Neale, 2001). As a result, a linear continuity perspective has been dominant in determining the degree of virtuality, as shown in Figure 3. According to this perspective, fully virtual teams are the ones that lack face-to-face contact so the virtuality stems from an absence of physical interaction.

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By the same token, traditional teams’ full reliance on face-to-face contact allows for the management of group boundaries (Sundstorm, et al., 1990), as shared physical environment is a significant component for team effectiveness (Gibsom & Cohen, 2003).

Figure 3. The Linear Measure of Virtuality

When describing virtuality, further approaches that use linearity for other dimensions have been developed. For instance, Hinds and Bailey (2003) treat the virtuality as a function of locational distance. They argued that “members’ separation by distance forces to rely on technologies to mediate their communication and collaborative work.” (p. 616). Similarly, since the extent of ICT usage within teams play an important role in virtual teams, it also became a relevant dimension determining the level of virtuality (Martins et al., 2004; Kirkman & Mathieu, 2005).

For a detailed treatment, the development of constructs assisted researchers in identifying further impacts on virtuality. As a result of a combination of different dimensions, a multiple linear approach developed, leading to a more complex measuring and defining systems of virtuality in teams. Additional dimensions that are frequently cited in the literature include geographic dispersion, ICT usage, temporal dispersion, organizational dispersion, asynchronicity, culture, work practices, (Chudoba et al., 2005; Schweitzer & Duxbury, 2010; Dixon & Panteli, 2010; Malhotra & Majchrzak, 2012).

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Figure 4. An Illustration of the Multiple Linear Measurement of Virtuality

In measuring the level of virtuality, scholars proposed various dimensions to identify the differences and the characteristics which distinguish virtual teams from traditional ones (Bell & Kozlowski, 2002). Gibson and Gibbs (2006) reported that between 2000 and 2006, 80 of the 143 articles included at least three dimension defining virtual characteristics. Shin (2004) argued that teams become more virtual when dispersions in temporal, spatial, cultural, and organizational constructs increase. Kirkman and Mathieu (2005) associated teams’ virtuality positively with the number of boundaries (organizational and cultural boundaries, country, different time zones), the team size, and negatively with the proportion of co-located team members and level of task complexity. Chudoba and others (2005) suggested that identifying discontinuities that usually occurs in virtual team settings helps to determine the level of virtuality. They created a virtuality index assessing geographical, temporal, cultural, organizational and work-practical discontinuities. Likewise, Dixon and Panteli (2010, p.1179) focused on the discontinuities occurring in “physical location, time-zone difference, language and cultural differences, professional and organizational affiliation” to measure the degree of virtuality. Shekar (2006) identified the degree of virtuality by measuring the within-team ICT usage as a substitute for face-to-face communication. As in the previous attempts to define virtual teams, the definition of the ‘degree of virtuality in teams’ concept is also affected by various different suggestions in the literature. Due to the large number of studies focusing on ICT usage and geographic dispersion, as minimum

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requirements of virtuality as defined by some researchers (Cohen & Gibson, 2003; Gilson et al., 2015), these two distinct dimensions will be examined more closely in the next section, while other dimensions will be discussed after the findings of the literature review analyses are presented.

ICT Mediated Interaction

A significant number of research argued that virtual teams are considered virtual due to their dependency on information and telecommunication technologies (Glickson & Erez, 2013; Krumm et al. 2013; Maynard & Gilson, 2013; Kirkman & Mathieu, 2005; Martins et al., 2004; Powell et al., 2004; Gibson & Cohen, 2003; Jarvenpaa & Leidner, 1999; DeSanctis & Poole, 1997). Bergiel and colleagues (2008) argue that “virtual teams could not exist in their current guise without the advanced technological tools available today” (p.103).The extensive usage of ICT tools in virtual teams was considered a unique characteristic unlike in traditional teams (Kirkman et al., 2012; Chudoba et al. 2005, Gibson & Gibbs 2006). The most plausible reasoning behind this thought is that face-to-face communication has been replaced by these tools. While the differential impact of this substitution is not found significant via the experiments done by Fjermestad (2004), Rains (2005) asserted that ICT-mediated interactions promote equality and innovativeness in idea generation. These direct comparisons of traditional teams with virtual teams led scholars to focus on the technology-use dimension of virtual teams. Glikson and Erez (2012, p.22) defined virtual teams as “teams in which members coordinate and execute their work predominantly using computer mediated communication.” They further claim that members of virtual teams can be dispersed or co-located; geographic dispersion can therefore not be considered as a constitutive characteristic of virtual teams, which conforms to the view of Kirkman & Mathieu (2005). Penarroja and colleagues (2013) operationalized virtuality based on the media richness in communication. Videoconferencing is considered an element that can reproduce the qualities of face-face communication. Therefore, teams using videoconferencing are considered as

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having lower virtuality, whereas other types of communications over ICT tools, where the synchronicity is low and non-verbal cues are not available, are recorded as high virtuality. For some scholars, no matter how large the geographical separation of the members, the source of virtuality varies with the degree of the ICT use for work-related interactions (Kirkman & Mathieu, 2005; Curseu & Wessel, 2005; de Jong et al., 2008). Thus, the other dimensions (e.g. geographic locations) are irrelevant given the fact that ICT use is the dominant feature of virtuality.

Geographic Dispersion

While for some researchers ICT usage transforms a team from traditional to virtual, others believe geographic dispersion is the key determinant of virtuality (Bell & Kozlowski, 2002; Schweitzer & Duxbury, 2010; Blaskovich, 2008; Aiken et al., 2013; Klitmøller & Lauring, 2013; Peters & Manz, 2007; DeRosa, 2009; Martins et al., 2004; Ebrahim et al., 2009). ‘Dispersed teams’ are often used as a synonym for “virtual teams” due to the dispersed structure from the team-design point of view. This quality of teams facilitates ICT usage. Therefore, the increased use of ICT for inter-team communication is caused by geographical dispersion, since no other communication tool allows cheaper and more effective interaction (Brahm & Kunze, 2012; Geister et al, 2006; Hertel et al., 2005). Polzer and colleagues (2006) reported that increased ICT usage among members is likely to be observed among co-located members, if other members are geographically dispersed. Bell and Kozlowski (2002) explain the major difference between traditional and virtual team as follows: whereas in traditional teams ICT-mediated interaction is a complementary factor to face-to-face communication, in virtual teams, it is a substitute for face-to-face communication. Thus, the absence of proximal, physical interaction is often missing, which differentiates virtual teams from conventional ones. In relation to the spatial distance of team members, Bell and Kozlowski stated that it is “the absence of this proximal, face-to-face interaction between members of

33

virtual teams that makes them virtual and distinguishes them from more traditional teams” (2002, p.22).

Fiol and O’Connor (2005) highlighted that spatial dispersion of members does not indicate a direct relation with team virtuality. The condition of spatial distance to be considered as a characteristic of virtuality depends on its effects on face-to-face meetings. When the distance among members hinders face-to-face meetings, then it becomes a defining element. This implies that if members reside far from each other, but create chances to meet face-to-face for team tasks, then its impact on virtuality disappears.

The opponents of the view that geographic dispersion is a characteristic of team virtuality agree that it is at least an antecedent to the virtuality construct (Kirkman & Mathieu, 2005). However, when comparing the effect of virtuality on performance indicators such as team effectiveness, team cohesion, and other indicators, face-to-face teams are used as control groups (Fiol & O’Connor, 2005). Since virtual team members are often geographically dispersed and electronically connected, the impacts of virtuality remain ambiguous whether the difference is caused by geographic dispersion or electronic interaction (Gibson & Gibbs, 2006). This disagreement remains an issue in the conceptualization of virtuality (Gibson et al., 2014).

After thoroughly examining a very large portion of the existing studies on virtuality, it can be concluded that the synchronicity of communication can be influenced by the variation of the geographic dispersion, as this triggers temporal and organizational dispersion directly. Although most researchers conceptualized geographic dispersion as members’ separation in spatial proximities, Watson-Mannheim et al. (2002) and Chudoba et al. (2005) theorized it as a discontinuity that does not necessarily correlate with the relative spatial distance of members. The distances among members could be relatively small. However, if any discontinuity arises in locational presence among team members, which can include home-office or other flexible working arrangements, the team can still be highly virtual. Therefore, measuring geographic distances between members loses its importance if there exists a

34

discontinuity in co-presence. In the next section, the discontinuities approach is explored in detail.

Discontinuities Approach

Contrary to the continuum approach, the perspective presented by Watson-Mannheim et al. (2002; 2012) and Chudoba et al. (2005) responded to the dynamic and unconventional changes in the workplace. Today, work can be performed in various ways, times, locations and platforms. In their study, the authors propose that “post-bureaucratic work is characterized by discontinuities, meaning a lack of coherence or gaps in a pattern, either temporal or cross-sectional. These discontinuities may arise in the work itself, in the location and general context of the work, and in supervisory and inter-worker relationships” (Watson-Mannheim et al. 2002, p.9). Thus, these discontinuities are adopted as barriers that hinder traditional collaboration and a cohesive environment within conventional teams. As a result, when describing virtuality, the discontinuities approach treats virtuality as a sum of distracting conditions resulting from discontinuities rather than being a positive feature of teams. However, Dixon and Panteli (2010) claimed that the measure of virtuality by assessing virtual continuities, which are based on the balance between face-to-face and ICT-enabled communication, is more aptly suited than the discontinuities form of measurement.

METHODOLOGY

THE SCOPE OF REVIEW

The purpose of this review is to highlight the definitions used for team virtuality or virtual teams in general. The review was restricted to scholarly journal articles published between 2006 and 2013 so as not to skip the findings of Martins et al. (2004); Kirkman and Mathieu (2005); Gibson and Gibbs (2006), as they all proposed novel findings on the conceptualization of virtuality based on past research. However, a broader, more inclusive perspective was employed in the search, regardless of journal reputation and

35

number of citations. Since the focus of this study is the variation between definitions, it was necessary to examine as many articles as possible. The following search terms were used in the Web of Science, ABI/INFORM Global and EBSCO databases:

“Virtuality” “Virtual team” “Virtual teams” “Virtualness” “Virtual collaboration” “Dispersed teams”

The search uncovered 685 articles in total. After careful analyses, the duplicate articles, book reviews, conference and working papers, and other irrelevant items were removed, leaving 380 research articles. The content of articles was thus scanned and the definitions and/or defining characteristics of the search terms used were identified. In the end, 265 articles out of 380 were usable. Of the discarded articles, 76 had no definitions and 39 were irrelevant. Both English and German research articles were included.

Below, Table 1 shows the number of hits found, scanned and reviewed from the databases. Of all reviewed articles, 118 were from the Web of Science database, 129 were from EBSCO, and the remaining 18 were from the ABI/INFORM Global database. (See Table 2 for the complete list of journals covered in the review.)

Table 1. Number of Articles Reviewed by Databases ARTICLES

DATABASES Reviewed Scanned No. of Search

Results

Web of Science 118 154 234 EBSCO 129 202 365 ABI/INFORM Global 18 24 86

TOTAL 265 380 685

36

The Selection of Articles

First, at least one definition or a defining characteristic of virtuality had to appear in all articles accepted for review. When examining the definitions, a cited definition versus a newly proposed definition were carefully checked; only the proposed definition was used. Whenever both conceptual and operational definitions were present, the most relevant definition—the one complying with the design of study—was used. Otherwise, the cited references would be used as the working definition. The most important dimensions, characteristics and definitions exclusively provided for team virtuality and virtual teams were examined. Table 2 presents the full list of published articles and reviewed journals reviewed.

37

Table 2. List of Journals covered in the literature review

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L 26

5

38

ANALYSES

As this study was based on a qualitative dataset, a content analysis was conducted. For each definition analyzed, the data was recorded using MS Excel 2010. For all articles reviewed, author information, publication information, defined concept and selected definitions were recorded. Before moving to coding, all definitions and dimensions were copied separately. All reviews, checks and coding have been made manually. For improved accuracy, the articles have been reviewed twice, and coded accordingly. Below Table 3 demonstrates examples how coding has been performed.

Table 3. Sample Coding

Authors, Year (page. no)

Concept defined

Operational / Theoretical Definitions

Coding*

Martins et al., 2004 (p.808)

VT “whose members use technology to varying degrees in working across locational, temporal, and relational boundaries to accomplish an interdependent task”

ICT, GD, TD, RB,

INTT

Schiller & Mandviwalla, 2007 (p.13)

VT “(a) Members interact through interdependent tasks guided by common purposes (Lipnack & Stamps, 1997), (b) they use CMC or telecommunicationmedia substantially more than face-to-facecommunication (Anawati & Craig, 2006; Fiol& O’Connor, 2005; Griffith & Neale,2001), and (c) they are geographically dispersed fromeach other (Cohen & Gibson, 2003; Griffith &Meader, 2004).”

ICT, GD, MF2F,

INTT

Schweitzer & Duxbury, 2010 (p.272)

VT “In our opinion, geographic dispersion should be sufficient to warrant the term virtual team.”

GD

Guo et al., 2009 (p.1)

VT “groups of people engaged in a common organizational task through electronic information and communication technologies.”

ICT

*Note: Labels and structure of coding are provided in Table 4.

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Figure 5. Word Cloud of the Definitions of Virtuality

As a visual aid for understanding the semantic relations of virtuality, a word/tag cloud using the Wordle.net website was created for both the definitions quoted directly from articles and the coded labels based on these

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definitions. Even though they are not conclusive, visualization of qualitative data through word clouds are useful for the validation of previous studies’ findings and a way to isolate the key concepts of the contents (McNaught & Lam, 2010; Cui et al., 2010). Therefore, the use of clouds is more appropriate for preliminary checks, as the texts are preserved without any editing or coding (Wu et al., 2011). For this word cloud, 18,185 words were scanned and analyzed. The common English words and conjunctions (i.e., “the,” “and,” “but”) are removed automatically by the system’s algorithm. The size of each word proportionally illustrates the occurrences in the texts. Apart from the most frequently used words such as “virtual,” “team, “teams,” etc., the remaining words “technology,” “geographic/geographically” appeared as the most consistently used words in defining virtuality. The deeper level of analyses will be discussed in the structure of coding and the findings section of this study.

The Structure of Coding

When coding, several different dimensions with similar meanings were categorized as per the table below. The key criterion for coding was whether a distinctive character of a virtual team or virtuality has been referred to or not. For example, a common characteristic of any team is a shared purpose; it has therefore not been identified as a distinctive code. However, when it comes to what makes a virtual team unique, we further split minimal face-to-face contact from lack of face-to-face contact, as there is a meaningful difference in those definitions. In addition to these codes below, additional codes were also created (such as knowledge diversity, linguistic diversity, technology dispersion, etc.) where the occurrences are rare.

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Table 4. Labels and Structure of Coding

Code Labels Including

ICT ICT mediated interaction electronic communication, online interaction

GD Geographic dispersion spatial dispersion, locational dispersion,

different locations etc.

TD Temporal dispersion time dispersion, time-zone differences

OD Organizational dispersion different organizational membership

MF2F Minimal face-to-face-contact rare f2f meetings, limited encounters

INTT Interdependent tasks interdependent group

CD Cultural diversity cultural dispersion

TL Temporary lifespan temporary membership, no future

LF2F Lack of face-to-face-contact no physical contact, lack of personal contact, no chance to contact f2f

RB Relational boundaries no social cues, limited context cues

INDT Independent tasks independent individuals, no task coordination required

ID International dispersion different countries, worldwide dispersion

ND National dispersion diverse in national culture, cultural dispersion

SYNC Synchronicity (a)synchronicity, simultaneous work processes,

asynchronous responses, asynchronous communication

NH No previous history no past

PW Project work

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Figure 6. Word Cloud of Entered Codes

FINDINGS

In this section, the results of both citation analyses and content analyses are discussed. First, the distribution of publication years is categorized. Table 5 summarizes the distribution of articles. It can be concluded that the distribution of articles by years is fairly uniform. The majority of the reviewed articles come from publications that appeared in 2012 (n=38). The next in line were 37 articles from 2009 and 36 from 2010 constituting the highest number of publications reviewed in this study. The least number of articles is found as belonging to the year 2013 (n=23).

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Table 5. Number of Articles Reviewed by Year Year No. of Articles %

2006 33 12.5%

2007 30 11.3%

2008 34 12.8%

2009 37 14.0%

2010 36 13.6%

2011 34 12.8%

2012 38 14.3%

2013 23 8.7%

TOTAL 265

Table 6 illustrates the subject domains of the journals where the articles were published. Furthermore, it summarizes the fact that virtual team research attracted different domains, thereby leading to multidisciplinary research (Panteli & Chiasson, 2008).

Table 6. Number of Reviewed Articles by the Domain of the Journal

For the categorization of the subject domains of journals, we used the classification information based on the fields assigned by each database. When there were more than two fields attributed, the highest two ranking domains were matched. When the domain information on the databases was not available, we used the journal’s self-reported area of domain. According to the statistics, the highest number of research about virtual teams has been

BUS/MGT IS COMM PSY EDU CS SOCSCI ENG ECON PLAN ERGO ETH OTHER TOTAL

BUS/MGT 58

IS 33 25

COMM 3 4 14

PSY 42 - - 11

EDU 4 2 - - 9

CS - - - - - 6

SOCSCI 7 - - - - - 4

ENG 4 3 - - 3 - - 3

ECON 2 - - - - - - - 2

PLAN 1 - - - - - - - - 2

ERGO - - - 2 - - - - - - 3

ETH - - - - - - - - - - - 2

OTHER 3 4 1 1 - - - 1 - - - - 6

TOTAL 157 38 15 14 12 6 4 4 2 2 3 2 6 265

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conducted in the business/management domain with a total of 58 articles. Out of 265, there were 58 from pure business/management journals. The second largest number of articles reviewed was from the business/management and psychology fields. A total of 42 of the reviewed articles were from these categories. This is followed by 25 journals from the information sciences. In total, 157 journals were found under the business/management domain, where 99 were multidisciplinary coupled with business and management. While virtual team research has been published in numerous journals from various points of view, the total number of articles from the journals with pure domains is 145. The number of articles that were from multidisciplinary domains is 120. The coding of subject domains is explained in Table 7 below:

Table 7. Coding of Journals' Subject Domains Domain Code

Subject Domain Domain Code

Subject Domain

BUS/MGT Business/Management SOCSCI Social Sciences (General)

IS Information Science ENG Engineering

COMM Communication/Media Studies PSY Psychology (incl. Applied, Social, Educational and General)

CS Computer Science PLAN Planning and Development

ECON Economics ERGO Ergonomics

EDU Education ETH Ethics (Applied Ethics)

Note: Other includes Applied Sciences, Sociology, Medicine, Public Relations, Philosophy, Cultural Studies, Statistics, Industrial and Labor Relations, Accounting and Mathematics.

Further analyses are conducted to evaluate the content of the articles to investigate the approaches, definitions and dimensions cited in the articles. The following sections summarize the findings related with the content of the papers.

CITATION ANALYSES

While all articles were chosen regardless of how often they were cited, it is nevertheless relevant to this study to examine which definitions received more acceptance than others because higher citation numbers of a research signal its impact (Serenko & Dumay, 2015). For citation analyses, we scanned

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265 articles to identify how they defined and described team virtuality. Out of 265, only 152 articles (57.36%) used at least one cited reference for its definition. The remaining 113 articles (42.64%) either provided no reference or reported a self-constructed novel definition. Between the 152 articles using a forerunner’s definition, 249 different references from past research were cited. Below, the citations that appeared in more than two journal articles are illustrated. (n=149). The number of the frequently cited definitions (citation count >2) is identified as 19.

Table 8. Most Cited References

Citation Total Count

Citations Citation Total Count

Citations

Martins et al., 2004 17 Kirkman & Mathieu, 2005 7 Jarvenpaa & Leidner, 1999 17 Gibson & Cohen, 2003 4 Lipnack & Stamps, 2000 14 Malhotra et al., 2007 4 Powell et al., 2004 13 Jarvenpaa & Leidner, 1998 4 Bell & Kozlowski, 2002 12 Mowshowitz, 1997 3 Townsend et al., 1998 11 Griffith & Neale, 2001 3 Hertel et al., 2005 10 Cohen & Gibson, 2003 3 Lipnack & Stamps, 1997 9 Lipnack & Stamps, 1999 3 Maznevski & Chudoba, 2000 9 Kirkman et al., 2004 3

Duarte & Snyder, 1999 3

Total Count 149

Note: Citation frequency >2 is reported. The complete list of cited references is shown in the Appendix I.

The most commonly cited definitions were from Martins et al. (2004) and Jarvenpaa & Leidner (1999). Each had 17 occurrences in the reviewed articles. They are followed by Lipnack & Stamps (2000), Powell et al. (2004) and Bell & Kozlowski (2002) with 14, 13 and 12 occurrences respectively. Townsend et al. (1998) and Hertel et al. (2005), each appeared in more than 10 articles. The mostly cited references also included the definitions of same authors’ earlier contributions. The definitions form Lipnack and Stamps’s three studies (2000, 1999 and 1997) were cited in 26 later studies. Similarly, both works of Jarvenpaa & Leidner (1999, 1998) were referenced in 21 articles collectively. Finally, the direct definitions of Gibson & Cohen (2003) and Cohen & Gibson (2003) received a total of seven mentions in the reviewed

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articles. All citations detected in this literature review are presented in the Appendix I of this chapter.

Normative theory of science acknowledges that the contribution of past research within a certain field can be measured by analyzing the citing behavior of researchers (Small, 2010; Serenko & Dumay, 2015). For establishing a foundation built on previous research, the direct quotes most frequently used in defining virtual teams and subsequently virtuality are presented in Table 9. There are 13 studies3 that are relatively popular, constituting 49.43% of the definitions used in the reviewed articles.

3 In fact, Jarvenpaa & Leidner (1999) is the same article as Jarvenpaa & Leidner (1998), because in 1999, a special issue of Organization Science (Volume 10, Issue 6) was being published in conjunction with the Journal of Computer-Mediated Communication (Volume 3, Issue 4). Thus, the definitions form Jarvenpaa & Leidner (1999) and Jarvenpaa & Leidner (1998) are merged in Table 9.

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Table 9. Most Cited Definitions:

Authors, Year (page. no)

Concept defined

Definition

Martins et al., 2004 (p.808)

VT “whose members use technology to varying degrees in working across locational, temporal, and relational boundaries to accomplish an interdependent task”

Jarvenpaa & Leidner, 1999 (p.792); 1998

Global VT

“temporary, culturally diverse, geographically dispersed, electronically communicating work group”

Lipnack & Stamps, 2000 (p.18)

VT “a group of people who work interdependently with a shared purpose across space, time, and organizational boundaries using technology”

Powell et al., 2004 (p.7)

VT “groups of geographically, organizationally and/or time dispersed worker brought together by information and telecommunication technologies to accomplish one or more organizational tasks”

Bell & Kozlowski, 2002 (p.25)

VT “the key characteristics of virtual teams that distinguish them from conventional teams are (a) the spatial distance between team members that restrictsface-to-face communication and(b)the resulting use of technological communication to connectteam members”

Townsend et al., 1998 (p.17)

VT “groups or geographically and/or organizationally dispersed coworkers that are assembled using a combination of telecommunications and information technologies to accomplish an organizational task”

Hertel et al., 2005 (p.71)

VT “consists of (a) two or more persons who (b) collaborate interactively to achieve common goals, while (c) at least one of the team members works at a different location, organization, or at a different time so that (d) communication and coordination is predominantly based on electronic communication media.”

Lipnack & Stamps, 1997

VT "Unlike conventional teams, a virtual team works across space, time, and organizational boundaries with links strengthened by webs of communication technologies"

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Table 9. Most Cited Definitions (cont’d): Authors, Year (page. no)

Concept defined

Definition

Maznevski & Chudoba, 2000 (p.473 & p.474)

Global VT

“internationally distributed groups of people with an organizational mandate to make or implement decisions with international components and implications. They are typically assigned tasks that are strategically important and highly complex” & “Kristof et al. (1995) and Jarvenpaa and Leidner (1998) describe global virtual teams as culturally diverse and geographically dispersed. We add that global virtual teams are also global in their task”

Kirkman & Mathieu, 2005 (p.702)

Team Virtuality

“[is defined] using three dimensions: (a) the extent to which team members use virtual tools tocoordinate and execute team processes (including communicationmedia such as e-mail and videoconferencing and work tools suchas group decision support systems,(b) the amount of informational value provided by such tools, and(c) the synchronicity of team member virtual interaction.”

Gibson & Cohen, 2003 (p.4)

Team Virtuality

“To be considered virtual to some degree, a team must have the following three attributes: • It is a functioning team—a collection of individuals who areinterdependent in their tasks, share responsibility for outcomes,see themselves and are viewed by others as an intact social unitembedded in one or more social systems, and collectivelymanage their relationships across organizational boundaries(Hackman, 1987; Alderfer, 1977)*.• The members of the team are geographically dispersed.• The team relies on technology-mediated communications ratherthan face-to-face interaction to accomplish their tasks.”

Malhotra et al., 2007 (p.60)

VT “whose members are geographically distributed, requiring them to work together through electronic means with minimal, or in extreme circumstances, no face-to-face interaction”

*Note: Hackman, 1987 & Alderfer, 1977 are not included in the references section

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CONTENT ANALYSES

Unlike normative theory, social constructivist theory argues that citation analysis is not the best way to illustrate the theoretical development of a concept, because concepts socially evolve over time (Serenko & Dumay, 2015). Past research delivers evidence that authors are prone to cite studies that are published by well-known researchers or in reputable journals, which are not necessarily scientifically and theoretically the most reflective ones (de Villiers & Dumay, 2013). To overcome the biased inclination of citing behavior, a fair application of content analysis is considered a sensible way to objectively analyze social constructs.

The content analyses in this research start with shedding light on the descriptive nature of the dimensions used in the articles that attempted to define virtuality. Table 10 shows the detailed descriptive statistics. In order to define virtuality, the analyses indicate that the total number of dimensions counted is 779 in all 265 studies. This reveals the mean as 2.95 with a1.40 standard deviation. Out of 265 articles, 83 report one definition composed of two dimensions. Although a single dimension is adequate for 33 studies (12.45%), as many as nine separate dimensions for one definition are encountered in a single study.

Table 10. Descriptive Statistics of Dimensions Used for a Single Definition Statistic Value (Frequency) Percentage

Total Count of Dimensions 779 - Total Count of Definitions 265 100% Mean number of dimensions 2.95 - Standard deviation 1.40 - Mode 2 (83) 31.32% Max 9 (1) 0.38% Min 1 (33) 12.45%

In Figure 7, the frequency distribution of the number of dimensions used in one single definition is depicted. As discussed earlier, a definition composed of two distinct dimensions is the most popular one. Representing

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31.32% of the reviewed articles, 83 articles use a definition that consists of two distinct dimensions such as ICT dependence and geographic dispersion. Out of 265 reviewed studies, 67 articles (25.28%) use a combination of three dimensions, 45 (16.98%) use four and 24 (9.06%) use a version with five dimensions to define virtuality. Finally, 13 articles, which represent 4.91% of the study population, use six or more dimensions that characterize the virtuality concept.

Figure 7. Frequency Distribution of the Number of Dimensions Used in Each Definition

The content analysis reveals that 229 studies (86.42%) in this review considered ICT-mediated interaction as the major characteristic of virtuality. Out of these, 21 considered ICT-mediated interactions as the only determinant of virtuality, as they refer to no other related dimension. On the other hand, for nine studies, geographic dispersion (GD) is the only characteristic that distinguishes virtuality from traditional settings. GD is thus found to be another major dimension. A total of 208 articles (78.49%) used GD as a distinctive feature of virtuality, whereas three studies using a single dimension considered face-to-face contact to be the defining factor. Minimal face-to-face contact (MF2F) is used in 45 (16.98%) and lack of face-to-face contact (LF2F) is used in 22 articles (8.3%) as a distinguishing feature

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describing virtuality. Temporal dispersion (TD) and organization dispersion (OD) dimensions are among those very highly referred to, although only one article considers temporal dispersion as a stand-alone characteristic. TD is used as a typical construct in 75 cases (28.30%), whereas OD is used in 58 cases (21.89%). The frequencies of the remaining characteristics can be found in Table 11. In addition to the listed dimensions, “others” include “simultaneous work processes,” “knowledge intensive,” “information value,” “process informatization,” “technology dispersion,” “complex tasks,”, “agilities in functions, workplaces, competencies, work contracts, equipment, functional dependencies, and hierarchical dependencies”.

Table 11. Frequency Table of Dimensions Used in Definitions

Dimension

Total Frequency of Dimensions used in

Definitions Dimension

Total Frequency of Dimensions used in

Definitions ICT 229 (21) RB 14 GD 208 (9) SYNC 7 TD 75 (1) NH 6 OD 58 ID 4

MF2F 45 (2) ND 4 INTT 41 INDT 4 LF2F 23 (1) PW 3 CD 20 LD 2

TL 17 Others 19

Total Count of Dimensions 779 Note: Refer to Table 4 for the labels denoting dimensions.

As there are many dimensions considered vital to varying degrees, it is essential to visualize how these dimensions are incorporated to formulate a preferred definition. To begin, the four most frequently used dimensions were selected; ICT use, geographic dispersion, temporal dispersion and organizational dispersion. These particular dimensions are put under the microscope because there are 570 uses versus the total number of dimensions used, which is 779. With the Venn diagram in Figure 8, each dimension is presented as a unique set, where the numbers in the intersections denote the number of studies using the specific dimension.

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The definitions, which incorporate both ICT use and geographic dispersion, have the highest occurrences in this review: 178 (102+15+27+34). On the other hand, 102 cases included both geographic dispersion and ICT usage but they concluded that neither temporal dispersion nor organizational dispersion is a distinctive determinant that typifies virtuality. However, 34 articles reach the conclusion that both temporal dispersion and organizational dispersion are required when ICT usage and geographic dispersion are present in virtuality.

Figure 8. Venn Diagram for Highly Used Dimensions in Definitions

Though Martins and colleagues (2004) assert that geographic dispersion is the most commonly noted dimension, this content analysis reveals that the emphasis on geographic dispersion has been succeeded by ICT-mediated interactions. This finding, however, confirms the studies of Cohen & Gibson (2003), Gibson & Gibbs (2006), Stanko & Gibson (2009) and Gilson et al. (2015) that geographic dispersion and ICT-mediated interactions are the most frequently attributed characteristics of virtuality. By the same token, a closer look at the reviewed articles is taken after leaving out temporal and organization dispersion, another iteration of a Venn diagram (see Figure 9) is formulated to assess the impact of the face-to-face contact dimension.

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Out of the 178 articles containing both ICT and GD dimensions, 42 cases report lack or minimal face-to-face contact as the most defining characteristic.

Figure 9. Venn Diagram: ICT & Geographic Dispersion & Minimal Face-to-Face Contact

On the other hand, when the operational definition and the measurement of virtuality in the empirical studies is examined, results reveal that the level of face-to-face interaction appears more frequently. Of 265 studies, virtuality is measured in 94 studies (35.47%). Among these 94 studies, 78 (82.98%) either utilize the degree of face-to-face communication in their virtuality measures or assess face-to-face interactions as a control variable in the studies. This illustrates that the extent of face-to-face communication (or the lack thereof) determines the degree of virtuality, even though its presence in theoretical definitions is found to be less frequent.

Based on the content analyses presented in this section, the discussion section addresses the research questions set out in the introduction. The findings of these content analyses have suggested how virtuality can be defined and measured. With these findings, this study renders empirical evidence on how virtual team research has been evolving over the last few years, especially after virtuality is considered to be a multifaceted construct. In the discussion section, the implications for further research along with limitations of this study are presented.

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DISCUSSION AND IMPLICATIONS

GENERAL DISCUSSIONS

Independent or Interdependent Members?

The content analyses suggest that there is a mixed polarization in the structure of team members in virtual settings. While the majority of the literature addresses the tasks within a virtual team as composed of high member interdependence, with 41 articles emphasizing it as a dimension of virtuality (41/265, 15.47%), only four articles discussed that the tasks in a virtual team require no interdependence becaise members of a virtual team are necessarily rather independent (Kratzer et al., 2006; Davis & Khazanchi, 2007; Ferreira et al., 2012a; Giaglis & Spinellis, 2012). Kratzer and colleagues (2012) further argued that in the full condition, assigned tasks in a team are highly structured, so that no coordination is required by the members.

Giaglis and Spinellis (2012) cite Lipnack and Stamps (2000) definition of virtuality directly, but the word interdependent from the original definition is replaced with independent. This was likely unintentional. A higher percentage of reviewed studies agree on the fact that virtual team members are interdependent, and Maynard and colleagues (2012) go so far as to report a weak but significant relationship between member interdependence and virtuality in teams, thereby implying that the higher the interdependence, the higher the virtuality ceteris paribus. On the other hand, contrasting results are also present in earlier studies. The study of Rico and Cohen (2005) reveal that no significant relationship is found between team virtuality and interdependence. Therefore, the link between interdependence and team virtuality is loose, even though the definitions in this review often refer to in(ter)dependence. Based on these ambiguous results, it is difficult to suggest that either interdependence or independence is a distinguishing characteristic of team virtuality, even though interdependence is cited more frequently.

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Are Virtual Teams Temporary Structures?

The pioneering studies on virtual teams authored by Lipnack & Stamps (1997) and Jarvenpaa & Leidner (1999), even before virtual team research gained its popularity, classified virtual teams as temporary structures best suited for project work. At that time, the Internet was not widely utilized and its potential was not fully internalized by organizations. However, with the rapid advancement in technology—especially communication tools—both the nature and scope of organizations quickly transformed (Townsend et al., 1998; Montoya-Weiss et al., 2001; Bell & Kozlowski, 2002; Furst et al., 2004). The unexpected pace of technological developments, internal and external pressures for globalization, and networked structures added new flexibilities to organizations and virtual teams consequently became more prevalent and permanent in organizations (Busch, 2004). Despite the fact that the view of virtuality as a temporary, project-based structure was quickly superseded, subsequent studies on VT have cited these two definitions more than any other.

Unfortunately, some of the existing VT definitions still convey the same message. Overall, in this review, 20 studies (7.55%) associated temporary lifespan or a project basis as the defining characteristics of virtuality. The trend reached its peak with five studies in 2012, whereas no study with this feature is detected in studies published in 2010 (See Figure 10). Taking into account the mainstream tendency of scholarship to continue to cite seminal authors, it becomes evident that there is no growing body of research that persists in the characterization of these dimensions for virtuality. The conclusion can thus be drawn that temporary structures are no longer considered a distinctive feature of VT.

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Figure 10. Number of Articles Citing Temporary Lifespan – Project Work by Year

What Makes a Team Virtual: ICT-Mediated Interactions or Geographic Dispersion?

In this analysis, the concept of geographical dispersion includes both spatial and physical dispersion. One of the most cited dimensions in the literature along with ICT dependency is the geographical dispersion of team members, also referred to as spatial distance. Out of 265 articles, 208 noted geographical dispersion as a defining quality of virtual teams or team virtuality, and nine considered geographic dispersion as the single determinant of virtuality (See some of the conceptual definition and comments in Table 12). But the main question remains: What makes a virtual team virtual? Is it the frequency of the use of communication technologies, the richness or the variety of these communication tools, or geographical dispersion?

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Table 12. Mostly Cited Definitions:

Authors, Year (page. no)

Definition

Peters & Manz, 2007 (p.117)

“Virtual teams are comprised of members who are located in more than one physical location.”

Blaskovich, 2008 (p.29) “interdependent group members work together on a common task while they are spatially separated”

DeRosa, 2009 (p.17) “Virtual teams were defined as teams in which team members were geographically dispersed”

Reed & Knight, 2010b (p.19) “Whether, they are called virtual or distributed, the team members are not co-located; they can reside in different cities, states or countries.”

Schweitzer & Duxbury, 2010 (p.272)

“…geographic dispersion should be sufficient to warrant the term virtual team.”

Klitmøller & Lauring, 2013 (p.398)

“Virtual teams are based on individuals collaborating in geographically dispersed work groups and who may reside in different time zones and countries.”

Schweitzer and Duxbury (2010) identified geographical dispersion as a “sufficient warrant” of virtuality. This statement alone is open to discussion. The reason is spatial distance by itself cannot guarantee virtuality. If this were true, then we have to call every football team a virtual team, because the spatial distance between goalkeeper and forward player is usually greater than zero, unless they physically occupy the same point of coordinates. It is further claimed by Reed & Knight (2010b) and Klitmøller & Lauring (2013) that virtual team members may reside in different cities or countries, and so may the players of the football club Willem II in Tilburg. The Belgian players may reside in Belgium; Dutch players may live Tilburg, Breda, Den Bosch or in different cities in the Netherlands. While these counter-arguments may sound like an overstatement or an irrelevant criticism, when the definition only argues that spatial distance between members is a defining characteristic, measuring virtuality becomes problematic, because what eventually matters

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in virtual teams is that members experience the lack of face-to-face communication.

Kirkman and Mathieu (2005) claim that geographic dispersion cannot be a prerequisite for working virtually, because in today’s organizations, co-located members highly rely on electronic communication. The authors explicitly state that “a team with co-located members does not automatically preclude members from interacting virtually or even prevent the team from being highly virtual” (p.702). Therefore, the extent of ICT use is considered as a fundamental element in virtuality. The inference is that the more computer-mediated interactions, the higher the virtuality. As the outcomes of the content analyses advocate, 229 out of 265 studies follow this approach, with 21 being supportive for the extent of ICT use as the exclusive measurement of virtuality. Unsurprisingly, however, this approach could not escape criticism, either. In the early literature, Griffith and Neale (2001) expressed the diffusion of technologies into traditional teams as a usual practice. They articulated that, intrinsically, ICT facilitation is not a necessary form of communication. Fiol and O’Connor (2005, p. 20) advocate the view that “virtual teams may make no use of technology, and face-to-face teams may make great use of technology,” and thus they claim that ICT use cannot define virtuality by itself. They conclude the same for geographic/physical dispersion: it is also not a pre-requisite of virtuality.

Even though Schweitzer and Duxbury (2010) conceptually assert the spatial distance−virtuality relation, the operational measure of virtuality differs from this conceptual definition in their research because they also quantify the hours spent working virtually, which is based on electronic communication. The proposed formula of virtuality is calculated by total hours of virtual work over total hours spent for tasks. Though this aligns the measurement of virtuality with the general inclination of the literature, there are other problems associated with it. This measurement still misses how much information is shared and how critical information is during face-to-face contact between members. Measuring only hours may therefore not reflect the

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frequency of face-to-face contact and value of information shared. Kirkman and Mathieu (2005) thus propose synchronicity and information value on top of ICT use. According to this view, when team members share a great deal of information over ICT tools, that carries a high value of information required for coordination of tasks and communicate asynchronously, the team shows more virtual qualities.

On the other hand, if the informational value and synchronicity of members’ interaction are also the determinant of virtuality, then why would it be critical to use ICT-mediated tools, even if offline tools (such as hard-copy distribution of the physical documents) could perform the same job, where appropriate? The sharing of confidential and classified information in online platforms may not be a working practice in some organizations (Jarvenpaa & Staples, 2001; Julibert, 2008). As a result, distributed members of a team can share hardcopies of documents that have a high value of information, so a team can still score high in virtuality even if it never uses an ICT tool. Even with information on paper set before them, teamwork is still virtual becausee team members still lack face-to-face interaction.

In new organizational settings, ICT tools have replaced face-to-face communication (Ocker, 2007). However, the modality should not matter as long as face-to-face communication is missing. Velmurugan and colleagues (2010) lament virtual teams composed of members that “are not able to interact face-to-face” (p.145). Measuring the degree of virtuality, therefore, should be determined by the level of face-to-face interactions. There are other boundaries associated with virtuality; however, they have a rather moderating role in the impacts of virtuality rather than in the degree of it (Gilson et al., 2015). The consistency can be only reached if researchers identify face-to-face interaction as the core of virtuality discussions (Fiol & O’Connor, 2005). Integrating all existing dimensions is next to impossible since both diversity and disparity in the definitions of VT continue to grow in the literature. Therefore, there is a need to employ methods that converge all potential dimensions in one common denominator: the extent of face-to-face

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communication. It should be noted that neither geographic dispersion nor high ICT use eliminates opportunities to meet face to face. The primary challenge of virtual teams is the lack of social and non-verbal cues (Raghuram et al., 2001). The higher the chances to meet with team members face to face, the lower the chances to work virtually. Therefore, we support the view of researchers that “the extent of face-to-face contact among members [should be] the single defining feature of virtuality” among all other possible variations (Fiol & O’Connor, 2005, p. 18).

THEORETICAL DISCUSSION

According to the philosophy of science, definitions should define concepts that are in line with current practices and do not contradict them (Kithcer, 1980). Definitions enable the conceptualization of constructs that are involved in theory development. Alvesson and Karreman (2011) argued that even when there is an agreement on the conceptual foundation of certain social constructs, alternative suggestions to challenge the state of theories and their implications are needed. Given the debated nature of virtual team research, it is a must to explore the conceptualization of constructs that remained unclear. Virtuality itself, to date, is addressed from different angles, offering a variety of propositions that attempt to define it. This review illustrates that the equivocal nature of the past literature is also repeated between the years 2006 and 2013. Although some level of consensus can be observed based on the content analyses provided, the root of the problem has been uncovered. On the other hand, there is some convergence in the treatment of literature. Contrary to early assumptions, as argued by Bell & Kozlowski (2002), the distinction between virtual and traditional teams is not black and white. The established agreement among researchers proposes that virtuality varies in a continuum, where there are multiple dimensions. And most of the time, the core is composed of either geographic dispersion or ICT use, or both. Either case implies limited face-to-face interactions.

However, disagreements when it comes how to measure virtuality are polarized. While some researchers applies more complicated approaches

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assessing multiple dimensions (Chudoba et al., 2005; Trzcielinski & Wojtkowski, 2007), others prefer to employ more simplified methods (Fiol & O’Connor, 2005, Bierly et al., 2009). Against all difficulties of clashing and mismatched definitions, historically, the literature on virtual teams is established on a more solid foundation where researchers articulated that other than the extent of face-to-face communication, no other characteristics can define and measure the degree of virtuality (Griffith & Neale, 2001, Bell & Kozlowski, 2002; Martins et al., 2004). However, over time, for broadening our understanding of the term, other investigated factors have slowly become integral components of virtuality.

Gilson and colleagues (2015) reported a shortage of empirical studies that illustrate certain impacts of virtuality due to fact that researchers still struggle to agree on a mutual measure of virtuality. This study proposes an opportunity for the future: a unified methodological application will enable accurate comparisons and interpretations of managerial and practical findings affected by virtuality.

LIMITATIONS

As this research is composed of content analyses, scanned, reviewed and coded by myself as the sole author of this thesis, it is open to human error. Even though the review has been conducted thoroughly with the highest integrity, effort, and attention to detail, the reliability of this study could have been improved with a secondary coder, which could in turn allow for a confirmation of inter-coder reliability as a measure of the overall reliability and the quality of this study. On the other hand, given the large number of studies reviewed, the results can still provide meaningful insights to understand the current state and the direction of virtual team research. Other reviews usually take a holistic approach when studying virtuality that relates the findings to input, team processes and output perspectives (Martins et al., 2004; Ebrahim et al., 2009; Kirkman et al., 2012; Gibson et al., 2014; Foster et al.; 2015). However, since this review is exclusively concerned with the definitions and dimensions of virtuality, the data and findings can still be

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considered valid and reliable. Because content and citation analyses rely on qualitative data, the procedure for the coding of definitions is applied with a rather straightforward method, as discussed in the methodology section.

Another limitation can be related to the selection of academic databases. The data was obtained from prominent, mainstream social sciences databases. With open access journals becoming more popular, there is a growing trend toward publishing with them and, in turn, respect for online journals within the scholarly community is slowly gaining momentum (Acharya, 2014). Although this review is one of the most extensive studies on virtual teams, inclusion of other articles through Directory of Open Access Journal database could broaden the picture.

CONCLUSION

Three research questions were posited at the beginning of the chapter, and what followed was the blueprint of answering them. Given the extensive nature of the literature review covering the years between 2006 and 2013, the citation and content analyses presented here exhibited the varying treatment of definitions of virtuality in the literature. After considering different approaches and dimensional constructs, in addition to variations in the same dimensions, it became clear that constructing a single dimension that all research could agree upon is an unsurmountable challenge. But determining the common ground for virtuality measurement is a matter of urgency. A unified means of measuring, however, could only be developed by isolating the dimension shared by all of the definitions: the extent of face-to-face communication. However, the impacts of other dimensions cited for defining virtuality should also guide researchers to determining the moderating and mediating impacts of virtuality.

As discussed, taking the previously mentioned dimensions for granted as part of virtual teams does not tell the whole story: What about the traditional teams that may also possess these characteristics of virtuality to some extent? This study examined how the number of dimensions and

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boundaries defined in the literature varies significantly. Consequently, only a limited number of studies defined virtuality as deriving primarily from the lack of face-to-face interaction in physical settings. Geographic dispersion and ICT may be the causes of not being able to meet face-to-face, but they do not axiomatically mean that team members perpetually fail to meet face-to-face in order to complete their tasks. Any team can score high on a virtuality scale without being geographically dispersed and without using ICT. All it takes is for team members not to see each other.

In conclusion, if only ICT-mediated interactions with geographic dispersion could explain the virtual collaboration, neither military teams should have functioned nor researchers should have collaborated in the history. Media change when the technology advances. However, what does not change is the continuous attempt of human beings to communicate with others that cannot be contacted face to face. People may still prefer using old methods, even human messengers; or the newest ways to transfer letters (e.g. unmanned aerial vehicle known as drones). In either case, no ICT-mediated interaction will take place. Likewise, geographically dispersed people may arrange frequent face-to-face meetings, exchange ideas, make decisions. However, if two people next to each other have no chance or will to interact face to face, they should be considered as virtual.

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APPENDIX

Table 13.The Complete List of Definition Citations Used in Reviewed Articles5

5 The citations used in this table are for information purpose only. Only the articles that are explicitly referred in the study are included in the references section.

CitationTotal Count

CitationsCitation

Total Count

CitationsCitation

Total Count

CitationsJarvenpaa & Leidner, 1999 17 Watson-Manheim et al., 2002 2 Hyrkkanen et al., 2007 1Martins et al., 2004 17 Zigurs, 2003 2 Jones et al., 2005 1Lipnack & Stamps, 2000 14 Ahuja & Carley, 1998 1 Kanawattanachai & Yoo, 2002 1Powell et al., 2004 13 Anawati & Craig, 2006 1 Kankanhalli et al., 2006 1Bell & Kozlowski, 2002 12 Aubert & Kelsey, 2003 1 Kasper-Fuehrer & Ashkanasy, 2003 1Townsend et al., 1998 11 Avolio et al., 2001 1 Kimble et al., 2000 1Hertel et al., 2005 10 Axtell et al., 2004 1 Kirkman & Mathieu, 2007 1Lipnack & Stamps, 1997 9 Baba et al., 2004 1 Konradt & Hertel, 2002 1Maznevski & Chudoba, 2000 9 Berry, 2011 1 Kosslerand & Prestridge, 2004 1Kirkman & Mathieu, 2005 7 Brown, 1998 1 Kozlowski & Bell, 2003 1Gibson & Cohen, 2003 4 Cascio & Shurygailo, 2003 1 Kristof et al., 1995 1Jarvenpaa & Leidner, 1998 4 Cogburn & Levinson, 2003 1 Marchrzak et al., 2000 1Malhotra et al., 2007 4 Cogburn, 2002 1 Massey et al., 2003 1Cohen & Gibson, 2003 3 Coleman, 1997 1 Matlay, 2003 1Griffith & Neale, 2001 3 Crenier & Metes, 1995 1 Mohrman, 1999 1Kirkman et al., 2004 3 Cummings & Kiesler, 2008 1 Montoya-Weiss et al., 2001 1Duarte & Snyder, 1999 3 Cummings, 2004 1 Noble, 2004 1Lipnack & Stamps, 1999 3 Curseu & Wessel, 2005 1 O’Leary & Cummings, 2007 1Mowshowitz, 1997 3 DeSanctis et al., 1999 1 Pauleen, 2003 1Chinowsky & Rojas, 2003 2 Duarte & Snyder, 2001 1 Piccoli et al., 2004 1Chudoba et al., 2005 2 Dube & Pare, 2004 1 Powell et al., 2006 1Cramton, 2001 2 Dutton, 1999 1 Purvanova & Bono, 2009 1DeSanctis & Monge, 1999 2 Ebrahim et al., 2009 1 Riopelle et al., 2003 1DeSanctis & Poole, 1997 2 Edwards & Wilson, 2004 1 Sarker et al., 2003 1Driskell et al., 2003 2 Fichman-Shachaf, 2003 1 Schmidt et al., 2001 1Fiol & O'Connor, 2005 2 Fröhlich, 2006 1 Schweitzer & Duxbury, 2010 1Gibson & Gibbs, 2006 2 Gassmann & Von Zedtwitz, 2003 1 Shachaf, 2008 1Hambley et al., 2007 2 Gaudes et al., 2007 1 Stanko & Gibbs, 2009 1Hertel et al., 2004 2 Geister et al., 2006 1 Thompson & Coovert, 2003 1Jarvenpaa et al., 1998 2 Griffith & Meader, 2004 1 Warkentin et al., 1997 1Kirkman et al., 2002 2 Griffith et al., 2003 1 Webster & Staples, 2006 1Majchrzak et al., 2000 2 Hardin et al., 2007 1 Wong & Burton, 2000 1Piccoli & Ives, 2003 2 Henry & Hartzler, 1998 1 Zaccaro & Bader, 2003 1Townsend et al., 1996 2 Horwitz et al., 2006 1 Zhu & Zhou, 2006 1

Total Count 249

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CHAPTER 3: EXTENDING THE

INDIVIDUAL LEVEL OF VIRTUALITY:

IMPLICATIONS OF TASK VIRTUALITY

IN VIRTUAL AND TRADITIONAL

SETTINGS6

6 A similar version of this chapter has been published as an article on Administrative Sciences Vol.4(4) in 2014 under CC BY 4.0. Proper APA citation for published version:

Orhan, M.A. (2014). Extending the individual level of virtuality: Implications of task virtuality in virtual and traditional settings. Administrative Sciences, 4(4). 400-412.

Chapter

3

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Abstract:

Virtuality in organizations has usually been treated as a characteristic that is observed either at a team or organizational level. However, the penetration of new technologies into our lives has transformed the entire design of organizations and teams. Not only has the design of teams and organizations changed, but the context and design of our jobs have also been impacted. Today, even employees in traditional team settings use electronic communication tools to work with multiple dispersed contacts outside of their teams and organizations, such as colleagues, clients or suppliers, who do not share the same geographical location. With all of these changes, virtuality can no longer be considered as a concept that is exclusive to virtual team members. In today’s organizations, to some extent, everyone’s tasks involve non-face-to-face contacts, irrespective of team virtuality. It therefore becomes crucial to identify the task virtuality phenomenon in organizations. With this paper, the example of Yahoo! is used as a case study to illustrate how task virtuality can be relevant for the design of organizations. Additionally, the proposed two-dimensional framework integrates both team virtuality and task virtuality elements in organizations. This framework is novel in that it not only allows us how to conceptualize the task virtuality, but also provides practical guidance for managers to identify and understand the factors leading to high task virtuality and to deal with the resulting complexities.

Keywords: task virtuality, individual level of virtuality, team virtuality, organizational design

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INTRODUCTION

Communication with non-face-to-face contacts has been increasingly sophisticating our lives more than anything else. Today, we sell our products to customers we never physically see. We collaborate globally with peers and colleagues we never actually meet. When needed, we hire freelancers from a part of the world that we have actually never visited. We teach online classes, where we have no clear idea whether our students comprehend the subject or where they get stuck. Regardless of whether our teams or our organizations are virtual, the increased involvement of non-face-to-face contacts in our daily tasks has complicated how we deal with others.

Oldham, Hackman, and Stepina (1978) define ‘dealing with others’ as one of the core dimensions in their job characteristics model. It is described as “The degree to which the job requires the employee to work closely with other people in carrying out the work activities (including dealings with other organization members and with external organizational ‘clients.’)” (ibid. p.6). Since this model was developed, the way we deal with others has evolved significantly, both inside and outside of the organization. Organizations, teams and, consequently, jobs are becoming more virtual as we increasingly communicate and perform tasks with non-face-to-face contacts. Researchers have found distinct benefits and challenges of virtuality within organizations and, particularly, within teams. Previous studies have recognized that virtual team structures bring challenges, such as a lack of social cues, inexistence of socio-emotional linkages, limited social relations and a decreased sense of connectedness with others (Hill, Kang & Seo, 2014; Branson, Clausen, & Sung 2008; Townsend et al., 1998), in addition to ambiguity and difficulties in communication and coordination of work (Hill, Kang, Seo, 2014; D’Souza and Colarelli, 2010; Brahm & Kunze, 2012). One of the pioneering literature review studies in virtual team research reported negative psychological experiences among virtual collaborators, such as isolation due to the lack of face-to-face contact (Gibson & Gibbs, 2006). However, researchers have widely ignored another important form of virtuality: virtuality at an individual level (Arling &

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Subramani, 2011). As a result, we do not know much about the implications of individual virtuality, because the individual dimension still suffers from many misconceptions and unknowns. This situation brings the need to assess the individual level of virtuality more in detail, as the context and design of the tasks we perform become more virtual. Our proposed framework enables managers and practitioners to use the unique task virtuality perspective to assess their organizational design through the conceptualization of how task virtuality relates to team virtuality and how it differs from it.

In this paper, task virtuality, an individual level of virtuality, is introduced as a new concept that can be considered as a latent and important factor in organizations for organizational design practitioners. The practical relevance of this concept is explained through a real-life example faced at Yahoo! (hereinafter, Yahoo). With this article, it is argued that task virtuality can be observed even in non-virtual teams and conventional settings. We contend that even in a traditional workplace, one’s roles and tasks may involve a high degree of dependency on non-face-to-face contacts. As a result, increasing dependency on non-face-to-face contacts carries additional challenges for individual performance. Individuals, who have limited physical connection with their networks in knowledge extensive settings, consequently know less about their networks and the expertise of the network (Cross & Cummings, 2004). This situation discourages employees from collaborating and communicating with others that are not physically contacted. Thus, “out of sight, out of mind” could be perceived as a major challenge for many employees.

WHAT HAPPENED AT YAHOO IN 2013?

To address this challenge, in 2013, Yahoo’s Marissa Mayer released a confidential memo that called off the employees’ flexible remote-working option. It soon leaked to the public and sparked criticism from the press, as well as from the advocates of virtual team collaboration (Cairns, 2013). Its negative publicity was due to the fact that this move was perceived as hugely damaging to virtual team collaboration at Yahoo. This came at a time when

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empirical findings directly contradicted Marissa Mayer’s actions. As a reaction to Mayer, one of the early virtual team researchers, Lipnack (2013) shared the empirical findings based on Majchrzak and colleagues’ study (2004) that proved that co-location of team members was not a requirement for innovation and productivity. However, with off-site working, employees not only become separated from their team members, but also from their colleagues, co-workers, clients and potentially all others. Apparently, the implications of Mayer’s decision were beyond virtual teamwork. Several questions that need to be asked include whether the announcement’s purpose was to abandon virtual team work to better understand the difference between virtual team work and virtual collaboration. Was the memo saying that all team members have to share the same location? Did that mean Yahoo employees from California and New York offices could no longer setup virtual teams? Additionally, what about global virtual teams? Did the memo mean that all globally dispersed employees of Yahoo had to be located in one single office? Or did this decision have different impacts on virtual collaboration than most of those others think? It was not clear that the announcement alone captures the direct effects on virtual teams. The existing accounts fail to resolve the misconception of virtuality between the team and individual level. Therefore, before proceeding to examine task virtuality, it will be necessary to highlight the concept of virtuality.

THE CONCEPT OF VIRTUALITY

A virtual team is usually defined as a group of people, composed of members that are geographically dispersed and mostly dependent on electronic communication tools (Wilson et al., 2013; Ayoko, Konrad, & Boyle, 2012; de Guinea, Webster, & Staples, 2012; de Leede et al., 2008). With the advances of technology, global networks within and between organizations have become easier to establish. “Global virtual teams” are characterized as virtual teams whose members are dispersed around the globe (Scott, 2013). Virtual teams, whether global or not, have two common characteristics: First, the members lack face-to-face communication with each other, and second,

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the members largely depend on electronic communication tools (Wilson et al., 2013). However, over time, researchers have agreed on assessing team virtuality as a continuum rather than an on-off dichotomy, as the degree of virtuality of teams may differ based on the level of face-to-face communication and electronic communication usage (Hoch & Kozlowski, 2014). We therefore maintain that team virtuality is a concept that applies to most, if not all, organizations to some degree.

Besides team virtuality, the individual level of virtuality is considered as an extension of team virtuality (Suh et al., 2011, Arling & Subramani, 2011). The concept is defined as ‘the degree of to which an individual relies on computer mediated communication’ (Suh et al. 2011, p.355). Therefore, based on the current model, where individual virtuality is a subset of team virtuality, theoretically, one could say that the higher the team virtuality, the higher the individual level of virtuality, and vice versa. Although the current model is theoretically and logically sound, it does not accurately represent reality. This is due to the fact that the degree of the reliance on computer mediated communication is free from team virtuality. Therefore, we propose task virtuality as a new concept, since the reliance on computer mediated communication with non-face-to-face contacts can be high no matter what the team virtuality is.

Task virtuality can be defined as the level of coordination, collaboration and interaction required with non-face-to-face contacts on which an employee is dependent to complete assigned tasks. This definition challenges the directional relation between task and team virtuality, as we argue that task virtuality is not necessarily a direct outcome of team virtuality. This assumption consequently puts task virtuality out of the broader topic of team virtuality. While task virtuality can be a direct outcome of team virtuality, it should be considered as a distinct concept that every task possess. The determinant of this depends on how much non-face-to-face contacts are involved in assigned tasks. The next section clarifies task virtuality in detail.

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TASK VIRTUALITY EXPLAINED

A new way of working has evolved. With the involvement of ICT tools and flexible work arrangements, small geographical distances can become chasms, while large geographical distances can become closer. Therefore, we no longer assess geographical dispersion as a distracting condition in organizational design, as it is used to be (Kiesler & Cummings, 2002). Remote work arrangements, such as home-office and off-site working, enable the necessary environment for team flexibility, but team virtuality is only one aspect of this flexibility. We have experienced that organizations themselves have become more virtual; call center operations can be migrated from the U.S. to India or shared service centers can centralize certain functions covering worldwide operations. Teams become more virtual, either to capture the best talents around world or to serve in different geographies (Curseu et al., 2008). This new set of networked, non-face-to-face relations brought the need to assess the virtuality individuals encounter. Therefore, we discuss and position the task virtuality concept as a job characteristic that can be encountered in both virtual and non-virtual team settings with a two-dimensional framework illustrating the possible different formations of team virtuality and task virtuality.

Task virtuality has existed at the individual level in every form of organizational structure since the penetration of the Internet to the workplace, yet it does not exist in models of organizational design. Team virtuality has been the primary focus of these models, while the impacts of task virtuality have been ignored.

We propose that task virtuality can be identified and assessed using two criteria. First is the physical proximity to others, and second is the degree to which electronic communication tools are relied upon to collaborate, cooperate and interact with others to complete assigned tasks. Therefore, the key determinant of the task virtuality is how much the employee is dependent on the non-face-to-face contacts while completing assigned tasks. The higher interdependency of virtual team members will have a stronger impact on both

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team and task virtuality aspects, since each team member is dependent on others to coordinate their tasks virtually. For example, a virtual project team can be considered as an example of members with high task virtuality driven by team virtuality. The virtual team depends on the collaboration, cooperation and interaction of dispersed project team members, and the project success is highly dependent on each member’s input. On the other hand, members of a traditional team may have widely varied task virtuality profiles, which is not dependent on their co-location, but on other variables, such as the level of the dependency on the coordination, collaboration and interaction of work with non-face-to-face contacts. As a result, not only “dealing with others” becomes an important factor in the classical job characteristics model developed by Oldham and colleagues (1978), but also the nature of how these others (e.g., colleagues, clients, suppliers, etc.) are dealt with, contacted and interacted; whether virtually or face-to-face.

As we have discussed, task virtuality is not necessarily dependent on team virtuality. Different levels of task virtuality have different implications from an organizational management perspective and necessitate different management strategies. Higher team virtuality may influence organizational behaviors and attitudes, yet a high level of task virtuality may be ignored although fundamentally important. For example, the virtuality of a team may not be as important as task virtuality if team members perform tasks that require a high level of collaboration and interaction with others who are physically distant. In this instance, there will be a high dependency on non-physical co-workers and a resulting increase in the virtuality of the role and associated tasks. In this example, team virtuality alone may cause confusing conclusions if task virtuality is not examined. Therefore, we propose the following two-dimensional framework of virtuality in teams, capturing task virtuality in addition to team virtuality.

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Table 14. Two dimensional framework of virtuality

The degree of dependency on coordination/collaboration/interaction with

non-face-to-face contacts (both inside and outside of an organization,

including team members)

low high

The degree of face-to-face interaction with team members

high Low team virtuality Low task virtuality

Low team virtuality High task virtuality

low High team virtuality Low task virtuality

High team virtuality High task virtuality

PROPOSITION 1: A high degree of face-to-face contact with team members leads to low team virtuality, and a low degree of dependency on non-face-to-face contacts leads to low task virtuality.

Low team virtuality and low task virtuality is experienced in teams where all of the interactions, either within the team or outside, depend on face-to-face contact. Sports teams can be considered as the best example, as there is no virtuality in place. No particular attention to the task virtuality is required in the organizational design, because all ties in an employee’s network are dealt with face-to-face.

PROPOSITION 2: A high degree of face-to-face contact with team members leads to low team virtuality, and a high degree of dependency on non-face-to-face contacts leads to high task virtuality.

Low team virtuality and high task virtuality is the situation where, even though an employee is a member of a traditional face-to-face team, the role and related tasks require higher dependency on non-face-to-face contacts. One example would be a regular faculty member teaching only online classes. Special attention may be required, because the virtuality is not considered as an important element in the

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design of organizations, because it may not be observed at a team or organizational level. Similarly, employees working in global call centers can be considered as a well-fit example, since the virtuality of their teams is minimal considering that team members are co-located, yet their work is highly dependent on people who are contacted via electronic communication tools. Another factor that can influence high task virtuality in traditional team settings is horizontal information linkages that are connected via electronic communication tools. In this case, team virtuality would be irrelevant, because the high task virtuality is caused by the dependence on the collaboration/coordination and interaction with non-face-to-face contacts that are outside of the team.

PROPOSITION 3: A low degree of face-to-face contact with team members leads to high team virtuality, and a low degree of dependency on non-face-to-face contacts leads to low task virtuality.

High team virtuality and low task virtuality is the case where the members of a (globally) dispersed team are mainly responsible for the tasks that do not involve non-face-to-face work coordination. When no interdependency exists between team members and team members are responsible for their individual assigned tasks, the team virtuality will not have any direct impacts on the individual performance, if all other contacts are dealt with face-to-face, because the team will have control over its ties in its networks and have more insights about the expertise of other people with whom it collaborates (Barton & Bunderson, 2014; Cross & Cummings, 2004). A geographically structured sales team (with each individual having its own, independent regional field sales responsibilities) could be suitable as an example. Regional responsibilities are distributed to the team members who aim to achieve sales targets for their assigned regions, while they maintain face-to-face contacts with clients directly in the field.

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PROPOSITION 4: A low degree of face-to-face contact with team members leads to high team virtuality, and a high degree of dependency on non-face-to-face contacts leads to high task virtuality.

High team virtuality and high task virtuality can be experienced in two different ways. The first possible variation is in the situation where a geographically dispersed team performs tasks with a higher degree of interdependence. In this event, the dependency on the coordination of work automatically involves non-face-to-face contacts that are mainly team members.

Another variation could be one where team members have lower interdependencies, but their tasks involve a higher degree of dependency on coordination, collaboration and interaction with non-face-to-face contacts. The best example fitting the latter variation could be any employee remotely working (home-office) with the assumption that he/she is a member of a team and collaborating with others. As a result, off-site working not only increases the virtuality of teams, as team members lose face-to-face contact with each other, but it also raises task virtuality.

As outlined, higher task virtuality can be a result of team virtuality; however, this is not always the case. It is therefore critical for us to understand the related dynamics between task virtuality and team virtuality. In this way, we can predict the circumstances under which task virtuality becomes an important consideration.

One important thing to note is the instance of mixed team structures. If a virtual team consists of dispersed members whose job virtuality varies, then outcomes, such as performance, behaviors and attitudes, may differ, as well. In this instance, team virtuality is the same for all members in the team (Suh et al., 2011) yet task virtuality between members will differ. Consequently, this may create unequal working conditions between members who experience high levels of task virtuality and those who experience low

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levels of virtuality. This should be considered as another complexity in the job design. Addressing this complication entails understanding how this design may cause conflicting comparisons and inferences about individual performances, results and outcomes.

It can be argued that the individual level of virtuality is a condition that is not just dependent on team virtuality. We reasoned that this high task virtuality can be experienced by anyone whose tasks heavily include non-face-to-face contacts other than team members with whom the employee is dependent for completing assigned tasks.

Task virtuality is distinguished from other virtuality definitions in that it requires an assessment of the dependency on non-face-to-face contacts, including both team members and others that are inside and outside of the organization. Unlike previous studies investigating the individual level of virtuality, we extended the concept based on the discussion that co-located workers could also possess high individual task virtuality, if they are highly dependent on collaboration, cooperation and interaction with non-face-to-face contacts. Our main discussion in this paper is to challenge the existing conceptualization, which claims that individual virtuality is caused by team virtuality. However, we argue that a high level of team virtuality does not always determine the level of task virtuality. If the interdependence within team is low, the individual impacts of team virtuality will be minimal. Likewise, low team virtuality does not guarantee low task virtuality, if individuals’ tasks depend on collaboration, coordination and interaction with non-face-to-face contacts.

TASK VIRTUALITY AND YAHOO

Yahoo presents an interesting example illustrating the importance of both team and task virtuality, because their company is driven by virtuality in both respects. Therefore, with the above framework in mind, was Mayer right or wrong in her 2013 decision against flexible working? Many of the critics regarded her decision as damaging to virtual teamwork; however, their

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assessment did not fully consider the interactions between task and team virtuality. We consider Mayer’s decision to have both advantages and disadvantages.

To Mayer’s credit, there are disadvantages associated with task virtuality: When an employee works remotely, he/she not only becomes dispersed from team members, but also possibly detached from colleagues and co-workers. The objective of the decision made by Mayer was to enhance the communication and collaboration among Yahoo employees by sharing the office atmosphere with all colleagues from different departments at Yahoo. This objective sounds laudable enough, so why did her decision suffer from harsh criticisms? One possible reason is a misconception between team virtuality and task virtuality.

As discussed previously, task and team virtuality are not completely dependent on each other. Although Mayer’s memo directly referenced virtual team collaboration, we believe that this was meant to remove virtual teamwork from the organization and replace it with face-to-face interactions where appropriate. Her memo, however, may not remove team virtuality from the workplace, and as such, we would expect virtual collaboration to still remain vibrant within the company, especially across global teams. Employees in global virtual teams would undoubtedly continue collaborating with their team members via electronic communications tools out of necessity. We would expect her decision to influence the task virtuality of certain employees who will become co-located with some of their colleagues, peers and maybe team members. With this understanding, proponents of virtual teamwork may have been less critical of her decision, as she clearly did not intend to remove either virtual tasks or global virtual teams from the company.

However, it can be argued that calling this decision an execution warrant for virtual teams would be a careless critique. If there are global virtual teams, composed of members that are located in different places across the world, team members will still continue cooperating with their team mates distantly, as gathering all Yahoo employees around the world into one office

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space would neither be feasible nor rational. Additionally, this was not the real purpose of this decision either. Yet, the difference would be the following: the cancellation of flexible working arrangements would definitely have an impact on the employees’ task virtuality, if they will have more face-to-face interaction with their co-workers. Our translation of Mayer’s move is that task virtuality is experienced as a complexity in the work practices at Yahoo. The concrete objective of this decision is not to destroy virtual team collaboration, but to eliminate the challenges that had arisen from high task virtuality, encouraging employees to collaborate and coordinate their tasks in a more face-to-face setting, while maintaining the existing team structures that require virtual teams to function.

WHY TASK VIRTUALITY SHOULD MATTER

Virtuality is not only socially challenging, as outlined above, but requires employees with a specific set of skills, knowledge and abilities in order to be successful. Empirical evidence indicates that a conscientious work ethic is particularly important for cross-cultural collaboration in virtual teams (Krumm et al., 2013). The need for conscientious work is offset, however, by the fact that a lack of face-to-face communication and social interaction leads to less meaningful task associations, thus reducing the chances of conscientious work (Gibson et al., 2011). To avoid a negative environment, Curseu and colleagues (2008) proposed that initial face-to-face meetings can, in part, overcome this obstacle in an effort to develop trust and cohesion in the virtual teamwork. Initial face-to-face meetings could also enhance the establishing of trust and cohesion between employees (particularly ones with low team virtuality and high task virtuality) and other non-face-to-face collaborators.

Leading virtual teams is just as challenging as being an employee within virtual teams. Team leaders must make critical evaluations of virtual employees based on criteria that may in fact be highly influenced by task virtuality. This becomes a particular problem when each member of a virtual team may experience different levels of task virtuality in their jobs. In essence,

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performance reviews may be a more accurate reflection of the differences in the task virtualities of employees rather than employee diligence. For example, we cannot expect a very meaningful evaluation of sales figures between two salespeople on the same virtual team if one of them contacts customers face-to-face and the other sells over the phone. Therefore, fair evaluations and comparisons should consider only the design of tasks with comparable task virtualities.

These concepts shed light on the practicality of Mayer’s decision at Yahoo. Companies like Yahoo should recognize the challenges associated with virtuality, both at the team and task level, while being sensitive to the increasing importance of maintaining virtuality in all respects, from the global team level to the individual task level. Thus, we suggest that companies make an effort to incorporate appropriate measures in their organizational design, accounting for the task virtuality concept. Measures must consider the challenge of assessing employees’ task virtualities on a managerial level, the social challenges of high-task virtuality roles and the resulting organizational outcomes. If task virtuality is found as a distracting condition for collaboration and effective cooperation, managers could either consider restructuring the organizational design in a way that reduces individuals’ task virtualities or take similar actions as Mayer did.

PRACTICAL IMPLICATIONS FOR MANAGERS

As this paper discusses, task virtuality has implications from the selection to assessment of employees. Common misconceptions about the interactions between task and team virtuality lead even the most practiced managers to false conclusions, which can lead selection and assessment astray. To reiterate, those situations at the highest risk of mismanagement are those where the task virtuality of an individual is relatively high, even though the team’s virtual characteristics are low.

Managers may believe that a high level of task virtuality can only be associated with high team virtuality. Consequently, their selection of

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employees for a traditional team may be misguided if they seek candidates with strong knowledge, skills and abilities based solely on traditional tasks, while ignoring qualities relevant to virtual tasks. As we discussed, it is often the case that employees in traditional settings may also have a high level of task virtuality that requires communication, coordination and collaboration with non-face-to-face contacts. If, however, as in the Yahoo example, a company takes deliberate actions to reduce their employees’ task virtuality, focusing primarily on traditional skills rather than virtual ones is an appropriate action.

Due to the misconception between team virtuality and task virtuality, managers may consider how they train employees. Often, virtual team trainings are only provided to members that work in virtual teams. Yet, in today’s global organizations, everyone has to deal with non-face-to-face contacts. As a result, communication, culture, trust and conflicts can be problematic for conventional workers, as well as virtual ones. It is therefore reasonable that managers should also consider the impacts of task virtuality and determine the training needs of their staff accordingly in both virtual and traditional team settings. This would overcome the problems of virtual tasking, which are recognized in virtual teams, but latent in conventional teams. The two-dimensional framework illustrated here will provide a preliminary checkbox for managers to evaluate the design of their teams and organizations and coordinate the work and training requirements accordingly. As a result, managers can expect their performance comparisons and evaluations to become more meaningful.

Managers make an extraordinary effort to coordinate virtual team work, because they consider the challenges that virtual team members face to be critical. However, identifying these challenges for virtual teams is not sufficient, because it does not consider the consequences of task virtuality. By the same token, managers leading traditional team settings need to be aware of these challenges as task virtuality becomes more prevalent in organizations.

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Managers and practitioners can use this paper to reconsider the implications and challenges caused by task virtuality within conventional teams. Similarly, managers of virtual teams may use this paper to balance the performance expectations for their employees in complex situations where task and team virtualities interact, especially when individuals experience different levels of task virtualities. Whether managing virtual or traditional teams, task virtuality should be considered as an important factor in job and organization design, as it has clear implications in the obstacles and challenges faced with the communication and coordination of work.

LIMITATIONS AND DIRECTIONS FOR FURTHER STUDIES

Even though this study contributes to the literature with a new organizational concept, there are several limitations to address. First of all, the Yahoo case is presented as an illustrative example to highlight the importance and practical relevance of the task virtuality concept in organizations. By doing so, we discourse the distinction between team and task virtuality and refute a misconception that has been widely cited. Therefore, the interferences about the implications, in particular at Yahoo, reflect some common characteristics of the construct introduced contextually. While it is believed that cases are more appropriate methods when presenting conceptual analyses (George & Bennett, 2005), there is a certain need to extend the framework with appropriate models and hypotheses to test the existence and real implications of task virtuality. We acknowledge that the lack of data support is the main limitation that should be evaluated. Further research could overcome this limitation by integrating task virtuality with a distinctive measure that combines the degree of virtuality within teams, as well as within individuals’ network groups. Secondly, although this article focuses on virtuality at the individual level, future studies could evaluate the impacts of interdependence between agents in relation to task virtuality. Finally, we also acknowledge that there are various definitions and dimensions proposed in the literature that illuminate the virtuality concept, especially at the team level. Though some researchers particularly focused on discontinuities

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between team members’ spatial, temporal, organizational, cultural boundaries, technology use, differences in team members’ work practices (Chudoba et al., 2005; Lu et al., 2006) and linguistic differences (Dixon & Panteli, 2010), the task virtuality concept takes an approach to virtuality that relates the extent of virtual tool usage for coordinating, collaborating and/or interacting with non-face-to-face contacts in order to execute job processes (Hoch & Kozlowski, 2014; Maynard et al. 2012; Kirkman, & Mathieu, 2005). The perspective of discontinuities is highly relevant, as they not only occur at the team level, but also during the entire work process, which involves other parties, both inside and outside of the organizations. Unquestionably, assessing task virtuality from the perspective of discontinuities would add an invaluable contribution to the examination of the relations between task virtuality and other organizational/behavioral outcomes to uncover further implications for organizations.

CONCLUSION

The aim of the paper is to extend our conceptual understanding of individual level virtuality, the concept coined by Suh and colleagues (2011). According to this concept, individual level virtuality is an immediate result of team virtuality. This implies a directional relation between team virtuality and the individual level of virtuality. While our model of task virtuality captures the association between team and task virtuality, it further claims that team virtuality is not the only reason why individuals encounter tasks that require virtual collaboration with others.

Our proposed definition differentiates itself from team virtuality by taking all non-face-to-face contacts with whom one collaborates, interacts and coordinates into account, as well. These contacts can be colleagues, clients, suppliers and all other parties that a person is dependent on to complete individual tasks. However, task virtuality is not a concept that can be completely differentiated from team virtuality. As our definition concerns the dependency on all non-face-to-face contacts, including team members, it should include team members, as well. Therefore, the interdependency

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between agents (within team and within networks) is critical in assessing the degree of task virtuality.

If a virtual team is highly interdependent, where tasks are highly reciprocal, and no other parties are involved in members’ tasks, such as in pure virtual team projects, members will experience high task virtuality, since individiuals’ tasks cannot be separated from team tasks.

On the other hand, the distinction of our proposed definition from earlier approaches of individual virtuality is related with the fact that task virtuality cannot be separated by other non-face-to-face contacts if a higher level of interdependencies exists. For example, if the dependency within a virtual team is rather pooled, the interdependence within the team would be considered rather weak. As the tasks are rather individualized in such teams, team virtuality may not be the only determinant in task virtuality. The reason is that an individual could still experience high task virtuality, if higher dependency on other non-face-to-face contacts is in place, which can be measured by the level of coordination, collaboration and interaction required with other non-face-to-face contacts.

The two-dimensional virtuality framework proposed provides a tool that will help organization designers to assess individuals’ exposure to both team and task virtuality. Based on this framework, managerial guidelines are developed for the consideration of the organizational design of teams and of the tasks of individuals. From a managerial standpoint, task virtuality deserves more attention, as it is an inseparable part of today’s working environments. As a result, managers will be able to provide more relevant leadership and supervision according to the needs of the employees’ task virtuality, and they will be able to take more serious measures if task virtuality is found to be a distracting condition for collaboration in the organization, as Mayer did. Even though it is too early to tell at this stage whether task virtuality has a significant impact on organizational outcomes, it is certainly worth analyzing further. Either in virtual or in traditional team settings, task virtuality will play an important role as we depend more and

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more on ICT tools in our daily communications with others. The approach presented in this paper will regenerate the focus in organizational design, as this paper contributes to the literature by highlighting the fact that the challenges of and the exposure to virtual work could also be experienced in traditional settings.

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CHAPTER 4: INVISIBLE, THEREFORE

ISOLATED: COMPARATIVE EFFECTS OF

TEAM VIRTUALITY WITH TASK

VIRTUALITY ON WORKPLACE

ISOLATION AND WORK OUTCOMES7

7 A similar version of this chapter was submitted with the co-authors J.B. Rijsman and G.M. van Dijk. The manuscript has been conditionally accepted for publication (with minor changes) by the Journal of Work and Organizational Psychology (ISSN: 1576-5962).

Chapter

4

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Abstract:

The new standards of technological and flexible arrangements have made virtual work prevalent for almost everyone in all levels of an organization. Whether in a virtual or traditional setting, current working conditions allow anyone to collaborate, work and interact with others through electronic means of communication, thereby creating a lack of face-to-face contact. Even though the dynamics of virtuality have been widely elaborated at the team level, there are still many unknowns about the impacts of virtuality experienced at an individual level. This paper aims to shed light on the relationship between workplace social isolation, job satisfaction, perceived performance and turnover intention comparing individual responses to team virtuality and task virtuality. Our findings propose that there are statistically significant relations between individual task virtuality, workplace social isolation, satisfaction, perceived performance and turnover intention in organizations. The results also reveal that task virtuality is a better predictor than team virtuality in estimating workplace social isolation and turnover intention.

Keywords: task virtuality, team virtuality, workplace isolation, job satisfaction, turnover intention, perceived performance, social isolation, physical isolation, informational isolation

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INTRODUCTION

Technological integration in business has changed workplace dynamics over the last few decades. With the new forms of organizations and sub-units, both jobs and methods of communication have become more dependent on information technology. This shift has resulted in the drastic change of many facets of a variety of jobs in organizations. From an organizational design point of view, more flexible structures such as virtual teams have emerged (Curseu, Schalk & Wessel, 2008). However, numerous studies on behavioral perspectives have illustrated that greater technology dependence and consequently less face-to-face contact detrimentally impact work-related outcomes (Martins, Gilson & Maynard, 2004; Gibson & Gibbs, 2006). One recent study reported that jobs at the macro level in Europe have become more monotonous in the face of increasing technology involvement and intensity (Greenan, Kalugina & Walkowiak, 2014). At the micro level, in virtual settings where the dependency on technology is high and physical face-to-face contact is low, decreased job satisfaction, commitment, and identification as well as increased workplace social and physical isolation have been detected (Bartel, Wrzesniewski & Wiesenfeld, 2012; Mulki, Locander, Marshall, Harris & Hensel, 2008; Kurland & Egan, 1999). The evidence from previous studies has also shown that virtuality in teams detrimentally impacts the performance of both the team and the individual (Lu, Watson-Manheim, Chudoba & Wynn, 2006; Arling & Subramani, 2011; Schweitzer & Duxbury, 2010).

Since the focus of research has shifted from virtual teams to the virtuality in teams, greater attention has been paid to the impacts of virtuality in team settings (Dixon & Panteli, 2010; Hosseini, Zuo, Chileshe & Baroudi, 2015). By the same token, researchers have started studying the individual and behavioral effects influenced by virtuality (Arling & Subramani, 2011; Suh, Shin, Ahuja & Kim, 2011; Orhan, 2014). Social support and the need for affiliation are often considered the missing elements in virtual work settings (Wiesenfeld, Raghuram & Garud, 2001). Kenyon and colleagues’ study (2002)

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suggested that, due to the absence of physical, face-to-face contact, increased virtuality leads to a higher degree of social isolation. These findings are corroborated by the conclusion of Golden, Veiga and Dino (2008) that there is a negative correlation between isolation and the degree of face-to-face interactions. A recent experiment performed by Bloom and colleagues (2015) revealed that home-office applications, one of the most frequently used flexible working arrangements in organizations, appeared to be increasing individuals’ work performance. However, they also reported that working from home caused increased feelings of loneliness and worries that one’s performance was not visible. Visibility is a factor that plays a crucial role in both performance and job satisfaction (Allen & Griffeth, 2001). Jobs in virtual settings vary greatly in terms of visibility. In extreme virtuality contingencies, where no physical contact with others takes place, lack of visibility in addition to social, physical and informational isolation negatively impact work outcomes (Mulki & Jaramillo, 2011; Bartel et al., 2012). As a result, there is a need to distinguish individual exposure to the impacts of virtuality.

The majority of studies relating social isolation to virtuality, however, have focused on interactions within a team. Our knowledge about the impacts of virtuality outside of teams is therefore limited. When studying isolation, emphasis is mostly placed on the individual’s interactions with colleagues, supervisors and team members (Golden et al., 2008). One of the main reasons for this specificity is that virtuality is usually referred to as a team or organizational-level phenomenon. Given the design differences in organizations, the feelings of an employee who has no physical interaction with another person will not be the same as those of one having a certain level of interaction with people outside of the team. However, the nature of interactions beyond team members is often neglected. In contrast to previous studies, we investigated the role of face-to-face interaction with parties that are separate from team members, such as colleagues outside teams, clients or suppliers.

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THEORY AND HYPOTHESIS

VIRTUALITY AND ISOLATION

It has long been argued that virtuality in teams causes distinct challenges compared to traditional team settings, where co-workers are centralized in one location. One of the most apparent difficulties is the isolation of virtual employees because of the lack of frequent face-to-face contact with team members (Kirkman, Rosen, Gibson, Tesluk & McPherson, 2002; Furst, Reeves, Rosen & Blackburn, 2004; Hertel, Geister & Konradt, 2005; Malhotra, Majchrzak, & Rosen 2007; Shachaf, 2008; Mulki et al., 2008). On the other hand, due to differing approaches and definitions, “virtuality in organizations” is one of the last decade’s most highly debated concepts in organization research (Gilson, Maynard, Young, Vartiainen & Hakonen, 2014). The term “virtuality” is notoriously ambiguous because disagreements still exist as towhether electronic communication, geographic dispersion or other dimensions make a team more virtual (Schweitzer & Duxbury, 2010). Gibson and Cohen (2003) identified task interdependence as an important charactersitic of virtual teams, thus helping to create a distinction between virtual teams and other groups and network structures that also communicate via information and communication tools (ICT). Task interdependence is defined as “the extent to which an individual needs information, materials and support from others to be able to carry out his or her job” (Van der Vegt, Van de Vliert & Oosterhof, 2003; p. 717). Depending on the job, different task interdepencies result in a fluctuating mixture of interfaces with others. As a result, the degree of information received face to face or via electronic communication varies as well. The degree is critical from an organizational effectiveness point of view because task interdependence also affects employee performance (Ganesh & Gupta, 2010). Shekhar (2006) proposed a multidimensional virtuality measure that allows all potential technological interfaces with others to be taken into account, including customers, suppliers, and employees; all have an impact on the magnitude of virtuality. While this approach carries its own merits to evaluate virtuality

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from a broader perspective, it does not fully detect the actual influence of virtuality at the individual level. To illustrate with an example, let us consider a virtual team composed of salespeople working in the field. Since their task is to go out and sell to potential customers in their environment, face-to-face contact is required. Although the team is virtual, the impacts of virtuality will not be felt as heavily as it would be by a telesales representative. On the other hand, a call center agent working in a traditional team setting has more exposure to virtuality because customers are contacted via electronic means of communication. If task interdependence within a team declines, the virtuality of the team becomes a less critical element. Contrarily, if a task becomes more dependent on other parties contacted via communication tools, the virtuality becomes critical. Orhan (2014) introduced the task virtuality concept to address virtuality as a phenomenon that can be experienced by individuals not necessarily belonging to a virtual team. The ultimate determinant of task virtuality relies on the lack of face-to-face communication with all people on whom tasks are dependent. This approach identifies virtuality as a salient characteristic that can be present in all kind of jobs, if the tasks are contingent on non-face-to-face contact regardless if there is a team or another setup. We have therefore focused on the impacts of task virtuality on job outcomes and testing the hypotheses discussed in this section.

The extent of face-to-face interaction has a strong impact on the social support received in the workplace (Wiesenfeld et al, 2001; Marshall et al., 2007; Mulki & Jaramillo, 2011). Especially for virtual workers, lack of face-to-face contact creates threatening conditions that cause isolation in the workplace and subsequently detrimental effects on the well-being of employees (Wiesenfeld et al., 2001). Besides organizational disconnectedness, lack of informal socialization opportunities is found particularly problematic for virtual workers (Kurland & Egan, 1999; Raghuram, Garud, Wiesenfeld & Gupta, 2001). While increased face-to-face interactions promote individuals’ sense of social belongingness (Sacco & Ismail, 2014), lack of social support is associated with feelings of loneliness (Song, Zmyslinski-Seelig, Kim, Drent, Victor, Omori & Allen, 2014) and perceptions of isolation (Wiesenfeld et al.,

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2001). Based on the work of Marshall, Michaels and Mulki (2007), workplace social isolation can be defined as a “lack of satisfying friendship relationships or a lack of access to social networks in workplace” (p198-199). Although virtual workers are often considered to be “remote workers,” very few opportunities for contact with others occur. If a virtual employee sees colleagues every day in the office, even though they are not team members, feelings of social isolation will be considerably less than a home-office virtual worker, who is potentially without any contact whatsoever in the workplace, which is home. As the former carries the opportunities for and access to workplace friendships, the latter completely hinders them. Besides colleagues, direct contact with customers also provides social connections and friendship opportunities. As task virtuality is concerned with who is involved in delivering tasks and how much face-to-face contact is maintained, Hypothesis 1a (H1a) is thus suggested.

H1a: The degree of task virtuality is positively associated with workplace social isolation.

Workplace isolation is believed to be a multidimensional construct (Cooper & Kurland, 2002; Marshall et al, 2007; Bartel et al., 2012). The actual source of workplace isolation is caused by the physical distance. When people are not co-located, it thus follows that they are physically separated. This separation in turn makes coordination and collaboration more challenging. Even though Bartel and colleagues (2012) recognize physical isolation as the main difficulty of virtual working, they also acknowledge that working remotely with team members does not necessarily signal complete physical isolation as there may still be interactions with others such as suppliers or clients. On the other hand, this does not mean that physical contact with others cannot lead to physical isolation. Co-working spaces and shared offices have become a trend, primarily bringing virtual workers together (Waber, Magnolfi & Lindsay, 2014; Gandini, 2015).To overcome an individual’s sense of being separated, co-working spaces are considered remedies (Garrett, Spreitzer & Bacevice, 2014). However, research shows that physical isolation

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may still be experienced when all direct contacts are dispersed and there is no face-to-face contact in terms of performing work-related tasks (Morgan & Symon, 2002). This implies that task virtuality is at its maximum level when there are no face-to-face contacts] maintained with those whose informational and relational input is relevant. Thus, the following hypothesis is developed:

H1b: The degree of task virtuality is positively associated with physical isolation.

Another aspect of isolation in the virtual workplace is connected to employee perceptions of missing information and lacking access to key people involved in tasks (Marshall et al, 2007). Curseu et al. (2008, p.633) propose that “tacit knowledge transfer takes place through direct interactions.” The implication is that both knowledge and social context is somehow blurred when working apart, as nonverbal cues are lost during information transfer due to lack of face-to-face interaction (de Jong, Schalk & Curseu, 2008; Wang & Haggerty, 2009). Furthermore, remote team members are often overlooked in reporting and information-sharing chains. Therefore, when individuals are out of sight, they are mostly out of mind, thereby delaying task-related information to arrive, if not skipped entirely (McCloskey & Igbaria, 2003; Gajendran & Joshi, 2012). Golden et al. (2008, p.1413) stated that “some individuals can feel professionally isolated despite working alongside coworkers.” This usually occurs when individuals lack connections and access to resources, resulting in a failure to receive required information. While these implications have an impact on negative social feelings, when task-related information is missing, the likelihood of informational isolation feelings increases. Employees with the least face-to-face contact with others would ultimately feel the highest level of informational isolation, as they are more likely to be kept out of information loops (Rook, 1984; Wiesenfeld, Raghuram & Garud, 1999) and informal information exchange (Marshall et al., 2007; Golden et al., 2008). However, the negative effects are not only felt at the absence of face-to-face contact with team members. When contact with non-team members like customers or suppliers does not take place in person, then

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the clarity of information is always somewhat skewed; the perception of missing information and restricted access to key people is thus likely to increase. Hence, we suggest H1c to test the relationship between informational isolation and task virtuality.

H1c: The degree of task virtuality is positively associated with informational isolation.

ISOLATION AND WORK OUTCOMES

The levels of social contact and connectedness determine employees’ feelings of isolation at work (Wohlwill, 1974; Wiesenfeld et al., 1999). Harrington and Santiago (2006, p.1) remark that “social isolation occurs because of lack of interaction with people.”. When working remotely, physical distance and lack of social context cause dissatisfaction (Morgan & Symon, 2002). Hypothesis 2a is to be tested in order to estimate the impact of workplace social isolation on job satisfaction. Because physical separation reduces interfaces with others and consequently opportunities for making friendships, social isolation increases. Home-office workers often have no opportunities for physical contact with others. While Sims, Szilagyi and Keller (1976) did not find a direct association between job satisfaction and dealing with others and friendship opportunities, later studies supported that contact with others and friendship opportunities significantly influence satisfaction at work (Levin & Stokes, 1989; Maslach & Jackson, 1981; Morrison, 2004). The relationship between physical isolation and job satisfaction is to be tested through Hypothesis 2b.

H2a: Workplace social isolation has a negative impact on job satisfaction.

H2b: Physical isolation has a negative impact on job satisfaction.

Organizational justice theories propose that fair distribution of information among employees is as important as fair distribution of rewards (Colquitt, 2001). This also entails fair access to resources, including

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information and key contacts. When employees do not have this opportunity, the meaning and joy received from work will diminish identification with the organization and feelings of dissatisfaction may be experienced. To extend the findings of Marshall et al. (2007) and Mulki et al. (2008), Hypothesis 2c will be tested.

H2c: Informational isolation has a negative impact on job satisfaction.

In light of the existing body of literature on work outcomes and overall isolation in the workplace, we also argue that perceived performance is negatively affected by more isolation in the workplace. Previous studies confirm the relationship between isolation and a negatively affected perceived performance (Golden et al., 2001; Allen & Griffeth, 2001). Thus Hypotheses 3a, 3b and 3c are structured as follows:

H3a: Workplace social isolation has a negative impact on perceived performance.

H3b: Physical isolation has a negative impact on perceived performance.

H3c: Informational isolation has a negative impact on perceived performance.

PERFORMANCE AND SATISFACTION

One of the most trivial and complicated relationships in the organizational psychology domain is between performance and job satisfaction (Judge, Thoresen, Bono & Patton, 2001). This complication arises because the directionality is not always easy to determine. However, a significant amount of research suggests that performance follows satisfaction (Judge et al., 2001). According to Ryan and Deci (2000), self-determination theory also argues that individuals inherently possess growth needs, which allow them to continue to perform well, thus further constituting the grounds that lead to higher satisfaction. Moreover, researchers agree on the moderating effects of task characteristics when directionality goes from performance to satisfaction

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(Hackman & Lawler, 1971; Brass, 1981; Dubinsky & Skinner, 1984). The theory of Hackman and Lawler (1971) suggests that dealing with others creates social belongingness and friendship opportunities at work. Moreover, the social support is required for both relational and informational contexts on the job (Raghuram et al., 2001). When social connectedness is lost, the conditions for accomplishing tasks also disappear (Golden et al., 2008). The underlying assumption is that when individuals feel they perform better, they are more likely to value the outcomes of job, thereby encouraging them to achieve more. As such, the quality of communication at work and the nature of work are perceived as more satisfying because they are supportive for performance. Hypothesis 4 is formulated to test the relationship in the model.

H4: Perceived performance positively affects job satisfaction.

TURNOVER INTENTION

The relationship between turnover intention and job satisfaction remains one of the most studied areas in organizational psychology literature. (Tschopp, Grote & Gerber, 2014). Job satisfaction is considered to be a multidimensional construct composed of different facets (Fila, Paik, Griffeth & Allen, 2014). Spector (1985) identified various facets that are significantly correlated with turnover intention, which is the best predictor of voluntary quitting behavior (Griffeth, Hom & Gaertner, 2000). Certainly, the quality of communication is central to job satisfaction (Giri & Kumar, 2010). The lack of non-verbal and para-verbal cues and remote means make communication particularly challenging and consequently more vital in employee engagement (de Jong et al., 2008; Robbins, Judge, Millett & Boyle, 2013). It is commonly observed in virtual working environments that employees sometimes miss information required to perform tasks (Elron & Vigoda, 2003) and do not receive messages in a clear and timely manner (Walther, 1996). When these conditions occur, the quality of communication is negatively impacted. On the other hand, other conditions harmfully impacting the nature of work cause dissatisfaction, consequently leading to quitting behavior (Swider, Boswell & Zimmerman, 2011). Individuals performing monotonous jobs often find their

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roles less interesting and rate them as less satisfying (Chung & Ross, 1977; Fisher, 1993). Considering the implications of increased technology involvement (Greenan et al., 2014) and declined relational ties, coupled with reduced face-to-face contact with others (Massey, Montoya-Weiss & Hung, 2003), the potential of performing less complex and less interesting jobs becomes quite high. To confirm with the majority of studies testing the relation between job satisfaction and turnover intention, we formulated Hypothesis 5.

H5: The higher the job satisfaction, the lower the intention to leave the organization.

Another predictor of turnover intention is employee performance (Cohen, 1999). Past research examined the directionality of both dimensions’ association. When employees show poor performance, negative feelings result in a decision to leave (Jackofsky, 1984). The studies of McEvoy and Cascio (1987) also reveal that while good performers consider staying, poor performers consider leaving, thus confirming the negative association. Thus, Hypothesis 6 is developed to test the same relation.

H6: The lower the perceived performance, the higher the intention to leave the organization.

FURTHER HYPOTHESES

Given the comprehensive nature of task virtuality, it is further hypothesized that task virtuality is a better predictor than team virtuality in estimating physical isolation (H7), informational isolation (H8), workplace social isolation (H9), job satisfaction (H10), perceived performance (H11), as well as turnover intention (H12).

Two separate models are developed to test hypothesized associations. Figure 11 is the comprehensive conceptual model (Model 1) which integrates the constructs from an overall social isolation point of view. Model 2, on the other hand, tests the dimensional impacts of workplace social isolation,

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namely the impacts of physical isolation and informational isolation on job satisfaction and perceived performance (See Figure 12).

Figure 11. Integrated Conceptual Model (Model 1)

Figure 12. Dimensional Impacts of Workplace Social Isolation (Model 2)

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METHODOLOGY

DATA COLLECTION AND SAMPLE

In this study, the self-reported survey method is used to collect data for the constructs examined. A questionnaire was developed in the English language and prepared over the Internet using the Qualtrics survey tool of the Tilburg School of Humanities. An invitation message was sent to 908 prospective participants in several platforms facilitating convenience and snowball sampling (also known as chain referral sampling) methods. Snowball sampling is considered as an effective method when researching sensitive issues because it enables respondents to provide honest responses as participation requests chain through trusted referrals (Biernacki & Waldorf, 1981; Atkinson & Flint, 2001). In selection of the prospective respondents, we relied on the authors’ personal, extended personal and social networks which targeted employees who work in different organizational settings and asked them to refer to their colleagues to participate. The inclusion criterion solely depended on the employment condition of the participants. In total, 278 respondents completed the survey. Participants were of 41 different nationalities and reported 33 different countries of their workplaces. Other demographic information also asked of respondents included their highest educational attainment; type of organization they work for; role and position in that organization; and duration of service in the current role. Gender and age information were purposely not requested. Of the participants, 174 (62.6%) were working for a privately owned company, 39 (14%) for a publicly owned company, 14 (5%) for a non-profit organization, and 43 (15.5%) for a governmental organization/public sector. Eight participants indicated the type of organization as “other.” A total of 138 respondents (49.6%) reported that they perform managerial level jobs at the supervisory, departmental and upper management levels. Participants with at least an undergraduate level of education accounted for 83% of the entire sample. Finally, the average duration of employment was calculated as 61.39 months (>5years) with a standard deviation of 76.8 months (min=2 months, max=300 months).

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MEASURES

In this questionnaire, we asked respondents to evaluate their: isolation levels in the workplace; satisfaction levels; self-performance in the current position; and turnover intentions. We further asked for their assessment of to what extent their daily tasks depend on others and how much face-to-face interaction they have with those people. Table 15 exhibits the details of the items for each construct explored.

Table 15. Measurement Scales

Variables and items

Workplace Social Isolation

Physical Isolation I am isolated from others at work I often feel left out. I often miss having people around me. I often feel I am no longer close to anyone. I am separated from others whom I work with. I often miss engaging in work-related informal chats with others.

Informational Isolation I feel I miss a lot of information when I am not seeing people I work with. I often miss the opportunity to meet key people who I work with. I could resolve problems more quickly and effectively, if I had more chances to interact with face-to-face with others. Informal discussions with people are an important part of my work(dropped) Job Satisfaction I sometimes feel my job is meaningless. (R) Communications seem good within this organization. I do not feel that the work I do is appreciated. (R) My efforts to do a good job are seldom blocked. (R) I often feel that I do not know what is going on with the organization. (R) My work tasks are often not fully clear to me. (R) I enjoy being with others I work with. (dropped)

Perceived Performance How would you rate your overall performance at your current job?

Turnover intention How often have you seriously considered quitting your present job?

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Workplace Social Isolation – Job Satisfaction

To measure overall the workplace social isolation (WSI) construct, 10 items were selected and adapted from the original 65-item workplace isolation inventory developed by Marshall et al. (2007). Its conceptual development primarily aimed at virtual workers enabled the formation of two sub-dimensions: physical and informational isolation. The physical isolation scale (PHYS_ISO) included six items, such as “I am isolated from others at work” and “I often miss having people around me.” Respondents indicated their informational isolation (INFO_ISO) based on items such as “I feel I miss a lot of information when I am not seeing people I work with.” and “I often miss the opportunity to meet key people whom I work with”. One item was dropped because it failed to satisfy the desired loading level (>0.60). The reliability (Cronbach’s alpha) score for the composite isolation construct was 0.84. For physical isolation, the score was found to be 0.89, and 0.60 for informational isolation.

For the job satisfaction scale (JS), Spector’s (1985) Job Satisfaction Survey instrument is used. In particular, items from “nature of work” and “communication” facets are gathered to construct a combined satisfaction score. A seven-item scale is derived to measure the feelings of employees. The reported reliability scores (Cronbach’s alpha) for nature of work and communication were 0.78 and 0.71, respectively. The combined job satisfaction in our study yielded a reliability score of 0.80.

The level of agreement for isolation and satisfaction constructs is determined by six-point Likert-type scale (1=Strongly Disagree, 2=Disagree, 3=Somewhat Disagree, …, 6=Strongly Agree). An especially beneficial merit of using a six-point scale is that it increases the normality pattern in distributions (Leung, 2011). Another advantage of using a six-point scale in this study is to extract participants’ feelings explicitly by removing the neutrality option and avoiding it as an escape response (Wakita, Ueshima & Noguchi, 2012). Previous studies using a six-point scale for determining respondents’ agreement level of satisfaction and social isolation include

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Templer (2012); Zou, Ingram & Higgins (2015); Jeske & Santuzzi (2015) and Calvete, Orue & González-Diez (2013).

Turnover Intention – Perceived Performance

For turnover intention (TURN_INT) and self-rated performance (PPERF), single items are utilized with five-point scales. The use of single-item measures are accepted as appropriate, especially in the field of organizational behavior psychology, where respondents are asked to rate their feelings and attitudes (Fisher & To, 2012; Tong, 2010). Bergkvist (2015) also argued that with single-item measures, less boredom and quitting behavior was observed. For unidimensional and distinct constructs, such as turnover intention or perceived performance, single-item measures are widely used in the literature (Sandelands, Brockner & Glynn, 1988; Lambert, Hogan & Barton, 2001; White & Lehman, 2005). Turnover intention is assessed with the item “How often have you seriously considered quitting your present job?” as suggested by Spector, Dwyer & Jex (1988). The options for responses were coded as: 1=Never, … 5=Extremely Often. Perceived performance is measured with the item asking “How would you rate your overall performance at your current job?”. The choices of responses ranged from 1=Poor to 5=Excellent.

Degree of Virtuality (Task and Team Level)

Because there are various approaches to appraising the level of virtuality of a team, it is still a fervently debated topic (Gilson et al., 2015). Although there are contrasting approaches and divergent definitions of virtuality, a common factor of the measurement of this construct is the level of face-to-face interaction among team members, as a proxy of virtuality (Hakonen & Lipponen, 2007). To assess the level of team virtuality, we followed the same approach proposed by Rapp, Ahearne, Mathieu & Rapp, (2010); Maynard, Mathieu, Rapp & Gilson (2012); and Gajendran & Joshi (2012). The respondents were asked to indicate a percentage of how much face-to-face interaction they have with others. We categorized each group as follows: (1) team members: (2) colleagues, peers, co-workers other than team

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members; (3) clients, customers; (4) suppliers, business partners; and (5) others. The team virtuality score is determined by subtracting the indicated percentage for face-to-face communication with team members from 100. When an employee had no face-to-face interaction with team members, then the team virtuality score was recorded as 100. Task virtuality is operationalized as put forward by Orhan (2014). It is assessed with respect to the respondents’ level of virtual collaboration with the others on whom they depend for completing work-related tasks. To determine the level of task virtuality, respondents were asked to distribute a percentage out of 100 reflecting their interdependence among the five aforementioned categories (The total sum of all categories may not exceed 100%). Based on this scale, the task virtuality score was calculated as the sum of products of interdependence with groups of people and the corresponding non-face-to-face contact level with each group.

The formulas for the calculation of team virtuality and task virtuality scores are as follows:

𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑇𝑇𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 = (100 − 𝜑𝜑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇)

𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑇𝑇𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 = 𝜔𝜔𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(100 − 𝜑𝜑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇)

+ 𝜔𝜔𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝐶𝐶𝐶𝐶(100 − 𝜑𝜑𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝐶𝐶𝐶𝐶) + 𝜔𝜔𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝑇𝑇𝐶𝐶𝐶𝐶(100 − 𝜑𝜑𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝑇𝑇𝐶𝐶𝐶𝐶)

+ 𝜔𝜔𝑆𝑆𝐶𝐶𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑇𝑇𝐶𝐶𝐶𝐶�100 − 𝜑𝜑𝑆𝑆𝐶𝐶𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑇𝑇𝐶𝐶𝐶𝐶� + 𝜔𝜔𝑂𝑂𝐶𝐶ℎ𝑇𝑇𝐶𝐶(100 − 𝜑𝜑𝑂𝑂𝐶𝐶ℎ𝑇𝑇𝐶𝐶)

and,

𝜔𝜔𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 + 𝜔𝜔𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝐶𝐶𝐶𝐶 + 𝜔𝜔𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇𝑇𝑇𝐶𝐶𝐶𝐶 + 𝜔𝜔𝑆𝑆𝐶𝐶𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑇𝑇𝐶𝐶𝐶𝐶 + 𝜔𝜔𝑂𝑂𝐶𝐶ℎ𝑇𝑇𝐶𝐶 = 1

where

𝜑𝜑 indicates the percentage score of the self-reported level of face-to-face interaction ranging [0,100],

𝜔𝜔 indicates the self-reported weight of interdependence ranging [0,1].

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FINDINGS

RESULTS

The correlation matrix revealed that task virtuality has a significant correlation with all variables measured in this study at the 0.01 significance level. Moreover, the directions of relationships demonstrate that the directions of hypothesized models are confirmed. Task virtuality was found significantly and positively correlated with workplace social isolation (r=0.30, p<0.01); physical isolation (r=0.28; p<0.01); informational isolation (r=0.18, p<0.01) and turnover intention (r=0.21, p<0.01). Negative and significant associations are found between task virtuality and job satisfaction (r=-0.19, p<0.01) and perceived performance (r=0.22, p<0.01).

The relationship between team virtuality and task virtuality is also explored in this study. While team virtuality is included after a multiplication with the weighted score in task virtuality calculation, it also has a significant and positive relation with the other (r=0.33, p<0.01). However, even though it has been previously argued that individual virtuality is a direct result of team virtuality (Suh et al., 2011), Figure 13 shows that the relation is not unidirectional, thus confirming Orhan’s argument (2014). It can therefore be concluded that a causal relationship between team virtuality and task virtuality is not an inevitability. The illustration of scatter plots is imperative in this context because it represents extreme cases, data structures, and variations better than a simple regression method (Anscombe, 1973). Our sample revealed that 155 observations (55.76%) out of 278 are categorized under low−low and high−high combinations of team and task virtuality. The remaining 123 observations (44.24%) are classified either under low team−high task virtuality or high team−low task category. In this study, team virtuality can explain 11% of overall task virtuality for the entire sample (R2=0.103, β=0.326, p<0.01; n=278). The explanatory power of team virtuality increases (Adj. R2=0.160, β=0.408, p<0.01) when task virtuality is measured as high (task virtuality score≥50; n=146). When task virtuality is low (task

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virtuality score<50; n=132), the explanatory power of team virtuality decreases (Adj. R2=0.051, β=0.242, p<0.01).

Figure 13. Task Virtuality – Team Virtuality Regression

To evaluate the fitness of the model, both confirmatory and exploratory factor analyses are used. After determining the minimum loading criteria as above 0.6 for all items, both results of confirmatory and exploratory factor analyses are taken into account. Due to poor loadings, one item from the job satisfaction scale and one item from the informational isolation scale are dropped. For Model 1, integrating all dimensions, the calculated chi-square was 91.5, with 33 degrees of freedom (chi-square/df=2.77). The goodness of fit (GFI) is measured as 0.94, and comparative fit index (CFI) as 0.92. The root mean square error of approximation (RMSEA) is 0.080. For Model 2, the chi-square was measured as 240.3 with 111 degrees of freedom (chi-square/df=2.16). The GFI score for this model was found to be 0.91 and CFI was 0.93. The RMSEA result was 0.065. Both models indicated an acceptable fit for the testing of the hypotheses. In addition, based on exploratory factor analyses, all loadings found were above 0.60. The reliability analyses have also shown that workplace isolation, physical isolation, informational isolation

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and job satisfaction were acceptable measures. Excluding informational isolation, all Cronbach’s alpha measures were over 0.80. The alpha score computed for the three-item informational isolation scale was slightly over the moderate threshold of 0.60, which is still acceptable for the model. While larger internal consistency is desired in psychometric measures, the alpha score is still considered adequate when exceeding 0.60 (Robinson, Shaver & Wrightsman, 1991). The average variances extracted (AVE) for each construct measured were recorded over 0.50, thereby indicating that the convergent validities of measures are satisfied (Ward, Fischer, Lam & Hall, 2009). Further details of descriptive statistics are presented in Table 16.

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Tab

le 1

6. D

escr

ipti

ve S

tati

stic

s, C

orre

lati

on M

atri

x an

d R

elia

bili

ty S

tati

stic

s

1

2 3

4 5

6 7

8 9

10

Con

stru

cts

1. W

orkp

lace

Soc

ial I

sola

tion

[0

.84]

2. P

hys

ical

Iso

lati

on

0.94

**

[0.8

9]

3. I

nfo

rmat

ion

al I

sola

tion

0.

66**

0.

36**

[0

.60]

4. J

ob S

atis

fact

ion‡

-0

.54*

* -0

.47*

* -0

.43*

* [0

.80]

5.

Per

ceiv

ed P

erfo

rman

ce

-0.2

9**

-0.2

7**

-0.1

9**

0.29

**

6. T

urn

over

In

ten

tion

0.

36**

0.

31**

0.

28**

-0

.53*

* -0

.18*

*

7. T

ask

Vir

tual

ity

0.30

**

0.28

**

0.18

**

-0.1

9**

-0.2

2**

0.21

**

8. T

eam

Vir

tual

ity

0.16

* 0.

27**

-0

.15*

-0

.06

0.00

-0

.01

0.33

**

D

emog

raph

ics

9. E

duca

tion

leve

l -0

.02

-0.0

6 0.

08

0.03

-0

.01

0.13

* 0.

04

-0.1

3*

10.

Du

rati

on o

f se

rvic

e -0

.05

-0.0

7 -0

.10

0.02

0.

04

0.02

0.

00

0.10

0.

01

11

. Ty

pe o

f or

gan

izat

ion

0.

15*

0.18

**

0.02

-0

.10

-0.0

2 0.

01

-0.0

4 0.

10

0.01

0.

12*

Mea

n

2.74

2.

36

3.52

4.

13

3.82

2.

68

52.0

9 52

.56

61

.39

St.

Dev

. 0.

93

1.12

1.

05

1.04

0.

83

1.18

27

.03

35.1

0

76.8

0 A

vera

ge V

aria

nce

Ext

ract

ed

0.60

0.

65

0.56

0.

51

(n=2

78)

Not

es: C

ron

bach

’s a

lph

a re

liabi

lity

scor

es a

re in

dica

ted

diag

onal

ly in

bra

cket

s. *

* in

dica

tes

a si

gnifi

can

t co

rrel

atio

n a

t th

e 0.

01 le

vel.

*

indi

cate

s a

sign

ifica

nt

corr

elat

ion

at

the

0.05

leve

l. ‡ R

ever

se it

ems

on jo

b sa

tisf

acti

on s

cale

are

rec

oded

.

135

Structural Equation Models and Path Analyses

The direct effects in the model testing integration of task virtuality in respect to workplace social isolation, job satisfaction, perceived performance and turnover intention is shown in Figure 14. Based on the structural equation model conducted in AMOS 16, the paths have significant direct effects, which support all hypotheses, except for H6. While the expected negative effect between perceived performance and turnover intention is found, the path is not drawn for the model because its significance did not meet the minimum desired level of p<0.05. Thus, the model suggested the full mediation of perceived performance. The impact of perceived performance on job satisfaction was significant at the 0.05 level. The remaining effects were found significant at the 0.01 level. With this model, turnover intention can be estimated with R2=0.33.

Figure 14. Path Analyses of Integrated Structural Equation Model (Model 1)

Notes: **p≤0.01; *p<0.05, χ2=91.45, df=33, χ2/df=2.77, p<0.001; GFI=0.94, AGFI=0.90, CFI=0.92; RMR=0.90, SRMR=0. 05; RMSEA=0.080, CI90% [0.061– 0.100].

Structural equation models (SEM) expose the details of the hypotheses tested in this study. H1a is confirmed as task virtuality is significantly and positively associated with the effect size of 0.30 (p<0.01). The more task virtuality that is experienced, the more isolation that will be felt. This, of

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course, has multiple implications. First, an increase in social isolation in the workplace decreases job satisfaction. This effect is measured with the path coefficient of −0.56 (p<0.01), thereby supporting H2a. Similarly, social isolation has a negative impact on perceived performance. Validating H3a, the effect size is found to be −0.29 (p<0.01). Job satisfaction has the highest effect = −0.58 (p<0.01) in relation to turnover intention. As predicted with H5, satisfied individuals often consider staying on at their current jobs. Though H6 is not supported by the model, further analysis suggests an interesting finding. We conducted a regression to reveal the interactional effect of task virtuality on the relationship between perceived performance and turnover intention. Figure 15 presents the differences in interactional effects of task virtuality on perceived performance—turnover association. For individuals facing low task virtuality (n=132), perceived performance has a significant and positive effect (r=0.29, p<0.01). The same association for individuals with high task virtuality (n=146) cannot be observed (r=0.04, p=0.65). Pure task virtuality suggests lack of face-to-face interaction with all others that are somehow involved in daily tasks. This directly influences the visibility of individuals. When individuals’ performance can be assessed by other parties, higher visibility moderates the relationship between performance and turnover intention (Allen & Griffeth, 2001). Hence, the relationship between perceived performance and turnover intention appears to be as expected in H6 when an individual works in a low task virtuality setting. Conversely, when there are less chances for individual performance to be assessed by others, even weaker self-assessments do not influence the intention to leave. More explicitly, since visibility is missing in high task virtuality contexts, the real performances of individuals can be harder to measure or even deceiving. Therefore, even when there is a gap between real performance and perceived performance, individuals can hide this gap due to less visibility. Adversely, it may also imply that high performers can have as much intention to leave as low performers because performance assessments cannot be undertaken easily and objectively when they cannot be observed. Under such circumstances, perceived performance does not influence turnover intention.

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Notes: TaskLeve x Pperf Standardized β = 0.136 (t=2.282, p=0.023), R2 =0.019

Figure 15. Interaction Effect of Task Virtuality on Perceived Performance – Turnover Intention Association

To test the dimensional impacts of social isolation in the workplace, an additional model (Model 2) is tested through path analyses. Figure 16 represents the structural model diagram. As hypothesized with H1b and H1c, task virtuality is significantly and positively associated with physical isolation (r=0.30, p<0.01) and informational isolation (r= 0.26, p<0.01). The implication is that individuals working with dispersed contacts lack face-to-face communication. This has an influence not only on an individual’s feelings of physical isolation, but also on the exchange of information. Being unable to physically interact with key people at work gives the remote worker the feeling that some information is lost in communication. Information transfer also becomes challenging because individuals feel that information is missing when there is no physical contact with colleagues. As a result, feelings of loneliness and of missing information have a compound set of further impacts. Supporting H2b and H2c, physical isolation and informational isolation decrease job satisfaction, with computed negative effects of 0.36 and 0.58, respectively (p<0.01). The sense of being left out and not being able to

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engage in informal chats with others incite adverse feelings and affect job satisfaction (Mulki et al., 2008; Marshall et al., 2007). At the same time, missing opportunities for information exchange exert performance-related issues. Our study results also provide evidence that a lack of social support triggered by physical and informational isolation causes perceived performance to be affected negatively. Participants experiencing the impact of high virtuality indicated that they could perform better if they had more chances to have physical communication opportunities with others. Both H3b and H3c are supported by the data. The effect sizes of physical isolation and informational isolation on performance are found to be 0.22 and 0.19 respectively at the 0.01 significance level, indicating inverse relations. As a result, the model exposes that the higher the task virtuality, the higher the impacts on the sub-dimensions of social isolation in the workplace. These dimensions consequently deter feelings of satisfaction and performance at work.

Figure 16. Path Analyses of Structural Equation Model for Dimensional Impacts of Workplace Social Isolation (Model 2)

Notes: **p≤0.01, χ2=240.33, df=111, χ2/df=2.16, p<0.001; GFI=0.91, AGFI=0.88, CFI=0.93; RMR=0.56, SRMR=0.10; RMSEA=0.065, CI90%[0.054 – 0.076].

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Post-Hoc Analyses

To analyze relations further, we continued with post-hoc analyses to test Hypotheses 7–12. First, we conducted a four-step hierarchical regression analysis. Measurement variables are included in the regression equation as independent variables. The second step collated the demographic data. Team virtuality was subsequently added as the next step. In the final step, task virtuality was inserted. The details of the standardized beta coefficients and regression results corresponding to each step are shown in Table 17.

While in step 1 only the satisfaction variable is significant; education becomes the second independent variable significantly affecting the turnover intent in the following steps. A higher level of education leads to a higher level of intention to leave. In the first step, 29% of the variance of turnover intention is explained. With the introduction of the demographic part of data, the explained variance slightly increases to 30.1%. The highest level of adjusted R2 is obtained when task virtuality is added into the regression. The total explained portion of the variance of turnover intention is recorded as 31.2%.

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Table 17. Results of Hierarchical Regression Analysis Predicting Turnover Intention

Step Variable Step1 (β)

Step2 (β)

Step3 (β)

Step4 (β)

1 Physical isolation 0.054 0.076 0.082 0.067 Informational isolation 0.035 0.018 0.014 -0.006Job satisfaction -0.502** -0.511** -0.511** -0.509**Perceived performance -0.005 0.001 0.002 0.023

2 Education 0.130** 0.129** 0.118*Duration of service 0.036 0.037 0.034Type of organization -0.066 -0.065 -0.052

3 Team virtuality -0.016 -0.0594 Task virtuality 0.131*

Regression Results R2 0.300 0.321 0.322 0.335 R2 change 0.300 0.021 0.000 0.013 Adj. R2 0.290 0.304 0.301 0.312 F 28.942** 18.064** 15.763** 14.831** df 4, 270 7, 267 8, 266 9,265

**p≤0.01; *p≤0.05

For assessing predictive capacities of team virtuality and task virtuality, a two-step hierarchical regression is constructed. In this analysis, team and task virtuality turned into independent variables. While in step 1, the direct impacts of team virtuality (teamvirt) on the dependent variables (workplace social isolation, physical isolation, informational isolation, job satisfaction, perceived performance and turnover intention) are observed, task virtuality (taskvirt) is added in step 2. The results of comparative prediction of team virtuality vs. task virtuality are shown in Table 18.

Table 18. Results of Comparative Prediction of Team Virtuality vs Task Virtuality for the Tests of Hypotheses 7-12

Independent Variable

Hypothesis Dependent Variable Step1: teamvirt (R2)

Step2: taskvirt (R2)

ΔR2

H7 Physical Isolation (PHYS_ISO) 0.072** 0.115** 0.043 H8 Informational Isolation (INFO_ISO) 0.022* 0.081** 0.059 H9 Workplace Social Isolation (WSI) 0.025** 0.092** 0.067 H10 Job Satisfaction (JS) 0.003 0.036** 0.033 H11 Perceived Performance (PPERF) 0.000 0.056** 0.056 H12 Turnover Intention (TURN_INT) 0.000 0.048** 0.048

**p<0.01; *p<0.05

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According to the results of explained variances for each regression, team virtuality has a significant explanatory power on social isolation and its sub-dimensions. The level of significance for social isolation and physical isolation is 0.01, and for informational isolation, it is 0.05. On the other hand, task virtuality appears to be significantly interacting with each dimension. Relating to the hypotheses, the data did not support the claim that task virtuality is a better predictor of physical isolation than team virtuality (H7). Although both effects of team virtuality and task virtuality are significant, the incremental increase in the variance explained when task virtuality (4.3%) was added is smaller than the variance explained by team virtuality (7.2%). On the other hand, H8 is validated as an explained variance of workplace social isolation that increased from 2.5% to 9.2% when the task virtuality variable was inserted. Similarly, for informational isolation, task virtuality was better at predicting: the variance explained rose from 2.2% to 8.1% when task virtuality was added into the regression analysis. H9 is therefore supported by the data. The remaining hypotheses (H10 & H11 & H12) are also supported. For job satisfaction, in the first step, no significant explanatory power is provided by team virtuality. The second step increases the explained variance by 5.6% with the addition of the task virtuality variable into the equation. Finally, when team virtuality cannot predict perceived performance and turnover intention, task virtuality manages to explain variances of these variables 5.6% and 4.8%, respectively. Figure 17 also illustrates each regression line for the variables predicted by team and task virtualities. The statistical details and comparisons of regression lines are provided in Appendix II at the end of this chapter.

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Figure 17. Regression Lines of Team Virtuality vs. Task Virtuality Predicting Study Variables

To test the effect of each team and task virtualities, mean comparisons were also analyzed. Table 19 summarizes the t-test results of differences within groups. Based on these results, team virtuality is significantly associated with physical isolation (p<0.01) and overall social isolation in the

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workplace (p<0.05). Task virtuality, on the other hand, is found to significantly impact perceived performance and turnover intention at the 0.01 level and on the satisfaction, informational and social isolation levels at work.

Table 19. T-test Results of Differences within Groups Team Virtuality Task Virtuality

Variable Low (n=103)

High (n=175)

p-value Low (n=132)

High (n=146)

p-value

WSI 2.59 (0.86) 2.83 (0.96) 0.036** 2.60 (0.91) 2.87 (0.94) 0.016** PHYS_ISO 2.06 (1.00) 2.53 (1.15) 0.001*** 2.22 (1.11) 2.48 (1.12) 0.057* INFO_ISO 3.65 (1.05) 3.44 (1.04) 0.108 3.36 (1.06) 3.66 (1.02) 0.019** JS 4.09 (1.05) 4.16 (1.03) 0.564 4.29 (1.05) 3.99 (1.01) 0.016** PPERF 3.85 (0.77) 3.81 (0.86) 0.677 3.98 (0.77) 3.69 (0.86) 0.004*** TURN_INT 2.72 (1.19) 2.66 (1.17) 0.705 2.57 (1.16) 2.88 (1.17) 0.004***

Note: Scores represent means of each variable, and values in parentheses are standard deviations. ***p<0.01; **p<0.05; *p<0.1

In Figure 18, we visualize the categorical distinction of team virtuality and task virtuality. For each individual, two score pairs of team and task virtualities are positioned. Based on these pairs, we determined each individual’s category representing virtuality composition. Four categories were generated. The first category is comprised of individuals with low team virtuality and low task virtuality (LowTeamLowTask). The second category covered individuals with high team virtuality and low task virtuality (HighTeamLowTask). In the third category, we covered employees experiencing low team virtuality but high task virtuality (LowTeamHighTask). The last category contained the data with high team virtuality coupled with high task virtuality (HighTeamHighTask). According to this distinction, we found 56 people in the LowTeamLowTask category, 76 people in the HighTeamLowTask category, 47 people in the LowTeamHighTask category and 99 people in the HighTeamHighTask category.

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Figure 18. Mapping Team Virtuality vs. Task Virtuality

Table 20. One-way ANOVA Test Results of Differences between Groups Virtuality Type

LowTeam LowTask (n=56)

LowTeam HighTask

(n=47)

HighTeam LowTask (n=76)

HighTeam HighTask

(n=99)

Variable 1 2 3 4

F-Value‡ Sig. Pairwise Comparison

WSI 2.44 (0.780) 2.78 (0.913) 2.73 (0.974) 2.92 (0.949) 3.29** [1,4]** PHYS_ISO 1.88 (0.892) 2.28 (1.079) 2.48 (1.185) 2.57 (1.132) 5.23*** [1,3]** [1,4]** INFO_ISO 3.55 (1.077) 3.76 (1.026) 3.22 (1.028) 3.61 (1.018) 3.22** [2,3]** [3,4]* JS 4.16 (1.092) 4.00 (1.007) 4.39 (1.022) 3.99 (1.011) 2.46* [3,4]* PPERF 3.95 (0.672) 3.74 (0.871) 4.00 (0.833) 3.67 (0.857) 2.95** [3,4]* TURN_INT 2.55 (1.205) 2.91 (1.158) 2.41 (1.122) 2.86 (1.178) 3.01** [2,3]* [3,4]*

‡d.f.=3, 274; ***p≤0.01; **p≤0.05; *p≤0.1

In Table 20, the descriptive nature of variables for each category and analysis of variance (ANOVA) results are provided. The significant levels of pairwise comparisons are determined using the Scheffe and Games-Howell tests, where appropriate. The Games-Howell test shows robustness when unequal sample sizes are in place and the assumption of homogeneity of

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variance does not hold (Toothaker, 1993). When sample variances are regarded as homogeneous, Scheffe tests are taken into consideration.

The lowest social isolation score belongs to the first category that experiences low team−low task virtuality. The significant difference is found between the high team−high task virtuality group (F=3.29, p≤0.05). For physical isolation, the differences are found to be significant as well. Again, the lowest physical isolation is felt by people categorized in the LowTeamLowTask (F=5.23, p≤0.01). For both physical and social isolation constructs, individuals working in the high team−high task virtuality context felt loneliness the strongest. For the informational isolation construct, team virtuality appeared irrelevant because even people with low team virtuality felt high informational isolation, because the highest informational isolation is observed in groups with high task virtuality (F=3.22, p≤0.05). The results of pairwise comparison for job satisfaction and perceived performance yielded meaningful differences as well. The least satisfied and lowest rated performance observed in the group occurred when both team and task virtualities measured high. F-test measured for satisfaction is 2.46 (p≤0.1), and for perceived performance is 2.95 (p≤0.05). Significant differences are found within teams scoring high in team virtuality. When task virtuality is also high, given there is high team virtuality, employees feel significantly less satisfied and that they perform worse as compared to individuals with less task virtuality but with high team virtuality.

Finally, we conducted a mean comparison analysis of informational isolation in order to assess whether working in an international environment influences individuals’ feelings. Results show that for respondents who reported a different country of workplace from a country of birth or nationality, the feelings of information isolation were significantly higher (n=78, mean=3.73, st.dev=1.07) than those whose country of workplace is the same as their country of birth and nationality (n=200, mean=3.43, st.dev=1.03; p=0.029<0.05)

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DISCUSSION

Our models have resulted in a number of important personal and work-related outcomes by presenting empirical evidence as to how task virtuality triggers feelings of isolation in the workplace. The results of this study revealed that individual exposure to virtual tasks, which require interaction and interdependence with people in a face-to-face manner, determines the level of isolation at work. In alignment with the findings of previous studies (Wiesenfeld et al., 1999; Mulki et al., 2008; Golden et al., 2008), it has been demonstrated that increased face-to-face interaction is associated with lower degrees of isolation. On the other hand, in contrast to previous studies, our results have shown that a higher level of face-to-face interaction with team members only is not enough to explain isolation. Face-to-face interactions with all others, who have a direct impact on performance and whose input is required, are found significantly correlated with social, physical and informational isolation at work. For example, for a salesperson, being able to interact with clients in person can mean a great deal more than meeting with team members. Clients possess more useful information than team members and thus can make a difference in a salesperson’s performance. It is very difficult to predict which products should be offered and what the needs/wants/expectations of the client are when there is no face-to-face interaction. Although individual experience varies between employees, our study has nevertheless identified solid patterns: when individuals interact physically with those who are important for their tasks, they feel a sense of belongingness, receive social support, and find friendship opportunities (Wiesenfeld et al., 2001; Morrison, 2004; Mulki & Jaramillo, 2011). When employees are physically separated from others, they sense that they lack the resources necessary for performing tasks, they lose the shared social context (Cramton, 2001), and they feel socially isolated (Maslach & Jackson, 1981; Rook, 1984; Levin & Stokes, 1989). As a result, both meaning and pleasure obtained from a job and strong work performance are positively influenced, as discussed by Golden and colleagues (2008). It can thus be

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concluded that more satisfied employees prefer to stay with an organization, while those who are dissatisfied are more likely to choose to leave.

Published results in relation to the impacts of virtuality are infamously contradictory. From organizational and behavioral standpoints, in particular, the conclusions of studies vary enormously (Gilson et al., 2015). This is not a coincidence. Because the root causes of how virtuality influences individual feelings, perceptions and attitudes in organizations have not been taken into consideration, there can be very little consensus about team virtuality. Our study shows that the impacts of team virtuality do not reflect an individual’s feelings and attitudes in a one-to-one manner. In essence, virtuality of a team is concerned with the virtual work performed collectively with team members. With this study, however, the empirical evidence has reinforced the outlined concept of task virtuality as a valid phenomenon. This implies that team members are only a part of a larger community that employees work with. The experiences with virtuality may not be purely dependent on the level of team interactions. In contrast, lack of face-to-face interaction with others may complicate jobs and daily tasks of individuals and create conditions that could be considered challenges if they occur in teams. Therefore, when assessing virtuality, team virtuality remains a vague concept, maybe even irrelevant. If team members have little or no interdependence, then the virtuality of a team may not influence the variables explored in the literature. Task virtuality comprises overall exposure to the lack of face-to-face communication with all others concerned, not only team members (Orhan, 2014). It thus takes into account the impact of other players who have a stake in the tasks and in the jobs performed. Task virtuality as opposed to team virtuality allows the researcher to conceptualize the real implications and exposures to working conditions that involve electronic communication or geographical dispersion, or both. The contribution of our study is that virtual work with all others associated with the task can be tested via the proposed task virtuality measure. Specifically, this study distinguishes task virtuality from individual impacts of team virtuality and identifies it as a separate measure that allows

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for more accurate comparisons and contrasts of different virtuality conditions of individuals.

LIMITATIONS AND DIRECTIONS FOR FURTHER RESEARCH

This study, as many others, comes with limitations. The first suggestion for further research is to improve the interpretation of the results through comparison with alternative study designs. As the aim of this study was to measure organizational−psychological feelings, perceptions and attitudes, our design can be regarded appropriate. Nonetheless, there could be a need to cross-check self-reported scores versus (actual) peer/supervisor-rated scores particularly for task virtuality/team virtuality and performance components. This cross-referencing would enhance the validity of further studies, as well as the results of this study. Another limitation worth mentioning is the unequal sample sizes across different categories identified in this study. Even though significant differences are found between different types of virtuality combinations, the random nature of sampling had an impact on equal variance assumptions and related tests of ANOVA comparisons. Researchers can bear the categorical combination of virtuality types in mind so that the data collection can be made under different conditions in order to collect a more representative sample size in all categories; therefore, clustered sampling may be the most appropriate means to test the differences between groups. On the other hand, the advantage of the random sample used in this study can be seen as a factor that improves the generalizability of findings in various organizations. In fact, one of the purposes of the introduction of the task virtuality measure is that it enables a comparison with individual impacts of virtual work, although individuals are not necessarily the members of a virtual team.

As previously discussed in this study, co-working spaces and shared offices have become an increasingly common practice for virtual workers (Waber et al., 2014; Gandini, 2015), and they are considered a mechanism that can resolve the isolation problem of virtual workers (Garrett et al., 2014). On the other hand, our study only measured work-related interactions, so the

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interactions with individuals out of the work scope have been neglected. Co-working spaces and shared offices are interesting avenues to explore the isolation levels of individuals by comparing task virtualities versus non-work-related face-to-face interactions. Although research verified the impacts of (lack of) work-related face-to-face interactions on physical isolation (Morgan & Symon, 2002), the impacts of non-work-related face-to-face interactions are as of yet unclear.

Future studies are necessary for validating the exclusive findings of this study and are therefore strongly encouraged. Thus far, researchers investigated a series of relations affected by team virtuality. As such, only intra-team interactions have been measured for the individual impacts of the virtuality construct. Conversely, this study may propose as an alternative the measuring of overall virtuality that is linked to tasks. Thus, future research could consider using the task virtuality concept to replicate and validate previously studied and preconceived correlations that have already been found idiosyncratic to team virtuality.

Based on the study results, another interesting question arising is that whether working in a foreign environment has further impacts on other organizational and behavioral matters at the workplace. Working in a country other than a country of birth or nationality may translate into language barriers that influence the quality of information and knowledge transfer. Consequently, future studies may also focus on additional challenges that are not currently addressed in this study.

PRACTICAL AND MANAGERIAL IMPLICATIONS

This study also posits highly relevant and crucial insights for managers and organizational designers. Virtual working is generally perceived as inherent only to virtual teams. Nevertheless, this study presents a case that virtual team members performing tasks that do not require electronic communication, but necessitate face-to-face interactions with others (e.g. virtual salespeople interacting with clients) may feel less isolated even though

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they are virtual team members. On the other hand, traditional team members can still perform tasks that require virtual coordination or collaboration (e.g. call center agents) that can cause higher levels of isolation at work, even when co-located in the same space with other team members. Managers often ignore the implications and challenges of virtuality when employees are not working in virtual teams. However, this study shows the importance of task virtuality, which influences a number of important factors behind a desire to resign. The implication is that not only are employees in virtual teams impacted by virtuality, but also employees in traditional settings who perform virtual tasks.

In order to manage virtuality effectively, Maznevski and Chudoba (2000) highlighted the crucial role played by face-to-face meetings. Curseu et al. (2008) noted that physical, face-to-face encounters lead to the development of interpersonal trust. Interestingly, however, a significant number of employees at present perform tasks with people that they never meet. If the interdependence between those two parties is higher, then the difficulty in performing virtual tasks increases. As a result, higher isolation and increased feelings of being deprived of information and access to key people affect satisfaction received and performance shown. For effective functioning, virtual employees require specifically designed training that teaches them to overcome communication issues when they are not able to have physical interactions (Warkentin & Beranek, 1999; Malhotra et al., 2007). Likewise, the management of traditional employees, especially if they have restricted face-to-face interactions with others, should also provide training. Rosen, Furst and Blackburn (2006) concluded that there is an acute need for effective training programs particularly for virtual settings, as the skills required to perform in such an environment can differ vastly. Consequently, these skills need to be acquired by those who encounter the challenges of virtual work, no matter how their teams are designed (i.e. virtual or traditional).

Results show that the least social and physical isolation are experienced by those who have the most frequent face-to-face interaction with others (respondents categorized in LowTeamLowTask), while the highest social

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and physical isolation are experienced by people with high team virtuality – high task virtuality (respondents categorized in HighTeamHighTask). This group of people also perceived the least satisfaction and least self-performance. Thus, for managers, being able to offer social support and to create conditions that could increase identification to goals and organizations carry more importance for those highly isolated employees. In the end, turnover decisions are dependent on the factors that are explored in this study.

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APPENDICES

APPENDIX I. THE QUESTIONNAIRE

Dear Participant,

The aim of this questionnaire is to measure a number of organizational and behavioral issues in relation to the extent of face-to-face communication with others that are involved in your work-related tasks. The questionnaire is part of the study I am conducting at Tilburg University for my doctoral thesis. Your input will provide an incredible assistance in meeting the study goals.

Please be kindly reminded that the data you provide will be kept anonymous and confidential. No personal/private information is required to participate to this survey. Therefore, please read each question carefully and answer all questions as accurately as possible.

Thank you for your time and cooperation.

Mehmet A. Orhan

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Q1) When you perform your daily, work-related tasks, how much are you dependent on the interaction and input from this group of people below?

Your total should be equal 100%.

Q2) How much do you have a face-to-face interaction with this group of people below?

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Q3) The items below assess your perceptions about the work environment and the job you are currently performing. Please indicate to what extent do you agree or disagree with each of the following statements.

Q4) Please indicate your self-evaluation about your overall performance at your workplace.

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Q5) Please indicate your intention to leave your current job.

Q6) Please indicate the highest level of education completed.

Q7) Please indicate your position and employment status (Please tick only one box which applies the best).

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Q8) Please indicate the type of the organization you currently work.

Q9) Please indicate the duration of service in months in the current organization.

Q10) Please select your country of birth, citizenship and workplace. If you hold multiple nationalities, please select the one you identify most with.

We thank you for your time spent taking this survey.

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APPENDIX II. STATISTICAL DETAILS OF COMPARISONS FOR REGRESSION LINES PREDICTING STUDY CONSTRUCTS

Figure 19. Regression Lines Predicting Workplace Social Isolation

Table 21. Details of Regression Statistics for Workplace Social Isolation Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.296 Multiple R 0.160 R2 8.8% R2 2.5% Adj. R2 8.4% Adj. R2 2.2% Std. Error 0.890 Std. Error 0.920 N 278 N 278 ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 20.99 20.99 26.50 .000 Regression 1 6.10 6.10 7.21 .008 Residual 276 218.63 0.79 Residual 276 233.51 0.85 Total 277 239.62 Total 277 239.62 Unstandardized 95% CI Unstandardized 95% CI B Std.

Error t p LL UL B Std.

Error t p LL UL

Intercept 2.21 0.116 19.1 .000 1.98 2.44 Intercept 2.52 0.099 25.4 .000 2.33 2.72 taskvirt 0.01 0.002 5.2 .000 0.01 0.01 teamvirt 0.00 0.002 2.7 .008 0.00 0.01

Standardized β = 0.296 (t=5.148, p<0.001)

Standardized β = 0.160 (t=2.686, p=0.008)

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Figure 20. Regression Lines Predicting Physical Isolation

Table 22. Details of Regression Statistics for Physical Isolation Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.284 Multiple R 0.268 R2 8.1% R2 7.2% Adj. R2 7.7% Adj. R2 6.9% Std. Error 1.075 Std. Error 1.080 N 278 N 278

ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 27.98 27.98 24.2 .000 Regression 1 24.99 24.99 21.4 .000 Residual 276 319.04 1.16 Residual 276 322.03 1.17 Total 277 347.03 Total 277 347.03

Unstandardized 95% CI Unstandardized 95% CI

B Std. Error

t p LL UL B Std. Error

t p LL UL

Intercept 1.75 0.140 12.5 .000 1.47 2.02 Intercept 1.91 0.117 16.3 .000 1.68 2.14 taskvirt 0.01 0.002 4.9 .000 0.01 0.02 teamvirt 0.01 0.002 4.6 .000 0.00 0.01

Standardized β = 0.284 (t=4.919, p<0.001) Standardized β = 0.268 (t=4.628, p<0.001)

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Figure 21. Regression Lines Predicting Informational Isolation

Table 23. Details of Regression Statistics for Informational Isolation Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.180 Multiple R 0.148 R2 3.3% R2 2.2% Adj. R2 3.0% Adj. R2 1.9% Std. Error 1.031 Std. Error 1.037 N 278 N 278

ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 10.02 10.02 9.4 .002 Regression 1 6.69 6.69 6.2 .013 Residual 276 293.41 1.06 Residual 276 296.74 1.08 Total 277 303.43 Total 277 303.43

Unstandardized 95% CI Unstandardized 95% CI

B Std. Error

t p LL UL B Std. Error

t p LL UL

Intercept 3.15 0.134 23.4 .000 2.88 3.41 Intercept 3.75 0.112 33.4 .000 1.68 2.14 taskvirt 0.01 0.002 3.07 .002 0.00 0.01 teamvirt -0.00 0.02 -2.5 .013 -0.01 0.00

Standardized β = 0.182 (t=3.070, p=0.002) Standardized β = -0.148 (t=-2.495, p=0.013)

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Figure 22. Regression Lines Predicting Job Satisfaction

Table 24. Details of Regression Statistics for Job Satisfaction Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.190 Multiple R 0.057 R2 3.6% R2 0.3% Adj. R2 3.3% Adj. R2 0.0% Std. Error 1.201 Std. Error 1.039 N 278 N 278

ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 10.77 10.77 10.3 .001 Regression 1 0.96 0.96 0.9 .347 Residual 276 287.94 1.04 Residual 276 297.75 1.08 Total 277 298.71 Total 277 298.71

Unstandardized 95% CI Unstandardized 95% CI

B Std. Error

t p LL UL B Std. Error

t p LL UL

Intercept 4.51 0.133 33.9 .000 4.25 4.78 Intercept 4.22 0.112 37.6 .000 4.00 4.44 taskvirt -0.01 0.002 -3.2 .001 -0.01 0.00 teamvirt 0.00 0.002 -0.9 .347 -0.01 0.00

Standardized β = -0.190 (t=-3.213, p<0.001) Standardized β = 0.000 (t=0.002, p=0.999)

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Figure 23. Regression Lines Predicting Perceived Performance

Table 25. Details of Regression Statistics for Perceived Performance Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.224 Multiple R 0.000 R2 5.0% R2 0.0% Adj. R2 4.7% Adj. R2 -0.4%Std. Error 0.808 Std. Error 0.829N 278 N 278

ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 9.52 9.52 14.6 .000 Regression 1 0.00 0.00 0.00 .999 Residual 276 180.20 0.65 Residual 276 189.71 0.69 Total 277 189.81 Total 277 189.71

Unstandardized 95% CI Unstandardized 95% CI

B Std. Error

t p LL UL B Std. Error

t p LL UL

Intercept 4.18 0.105 39.7 .000 3.98 4.39 Intercept 3.83 0.090 42.7 .000 3.65 4.00 taskvirt -0.01 0.002 -3.8 .000 -0.01 0.00 teamvirt 0.00 0.001 0.00 .999 0.00 0.00

Standardized β = -0.224 (t=-3.818, p<0.001) Standardized β = 0.000 (t=0.002, p=0.999)

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Figure 24. Regression Lines Predicting Turnover Intention

Table 26. Details of Regression Statistics for Turnover Intention Prediction

taskvirt teamvirt Regression Statistics Regression Statistics

Multiple R 0.208 Multiple R 0.001 R2 4.3% R2 0.0% Adj. R2 4.0% Adj. R2 -0.4%Std. Error 1.154 Std. Error 1.180N 278 N 278

ANOVA ANOVA

df SS MS F p df SS MS F p

Regression 1 16.57 16.57 12.4 .000 Regression 1 0.00 0.00 0.00 .989 Residual 276 367.58 1.33 Residual 276 384.14 1.39 Total 277 384.14 Total 277 384.14

Unstandardized 95% CI Unstandardized 95% CI

B Std. Error

t p LL UL B Std. Error

t p LL UL

Intercept 2.21 0.150 14.7 .000 1.92 2.51 Intercept 2.68 0.128 21.1 .000 2.43 2.94 taskvirt 0.01 0.003 3.5 .000 0.00 0.01 teamvirt 0.00 0.002 -0.0 .989 0.00 0.00

Standardized β = 0.208 (t=3.527, p<0.001) Standardized β = -0.001 (t=-0.014, p=0.989)

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APPENDIX III. RESULTS OF PATH ANALYSES WITH DIRECT AND INDIRECT EFFECTS

Figure 25. Path Analyses of Model 1

Table 27. Details of Structural Equation Model 1

Standardized Regression Weights: (Group number 1 - Default model) Estimate SE C.R. P

WSI <--- TASKVIRT .296 .002 5.157 *** JS <--- WSI -.561 .078 -8.109 *** PPERF <--- WSI -.287 .051 -4. 986 *** JS <--- PPERF .125 .074 2.156 .031 TURN_INT <--- JS -.577 .078 -8.262 ***

Goodness of Fit Results Model RMR GFI AGFI PGFI

Default model .900 .942 .903 .565 Saturated model .000 1.000 Interdependence model 2.418 .491 .377 .401

Baseline Comparisons

Model NFI

Delta1 NFI

rho1 IFI

Delta2 TLI

rho2 CFI

Default model .886 .844 .924 .894 .923 Saturated model 1.000 1.000 1.000 Interdependence model .000 .000 .000 .000 .000

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Table 27. Details of Structural Equation Model 1 (Cont’d)

RMSEA Results Model RMSEA LO 90 HI 90 PCLOSE

Default model .080 .061 .100 .006 Interdependence model .246 .231 .261 .000

Direct vs Indirect Effects Standardized Direct Effects

Standardized Indirect Effects

TASKVIRT WSI PPERF JS TASKVIRT WSI PPERF JS WSI .296 - - - - - - - PPERF - -.287 - - -.085 - - - JS - -.561 .125 - -.177 -.036 - - TURN_INT - - - -.577 .102 .345 -.072 -

Total Effects Standardize Total Effects

TASKVIRT WSI PPERF JS WSI .296 - - - PPERF -.085 -.287 - - JS -.177 -.597 .125 - TURN_INT .102 .345 -.072 -.577

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Figure 26. Path Analyses of Model 2

Table 28. Details of Structural Equation Model 2

Standardized Regression Weights: (Group number 1 - Default model) Estimate SE C.R. P

PHYS_ISO <--- TASKVIRT .295 .003 4.745 *** INFO_ISO <--- TASKVIRT .261 .002 3.195 .001 JS <--- PHYS_ISO -.362 .055 -5.175 *** PPERF <--- PHYS_ISO -.222 .043 -3.583 *** JS <--- INFO_ISO -.579 .198 -4.621 *** PPERF <--- INFO_ISO -.193 .106 -2.556 .011

Goodness of Fit Results Model RMR GFI AGFI PGFI

Default model .561 .914 .881 .663 Saturated model .000 1.000 Interdependence model 2.281 .369 .290 .328

Baseline Comparisons

Model NFI

Delta1 NFI

rho1 IFI

Delta2 TLI

rho2 CFI

Default model .876 .848 .929 .912 .928 Saturated model 1.000 1.000 1.000 Interdependence model .000 .000 .000 .000 .000

RMSEA Results Model RMSEA LO 90 HI 90 PCLOSE

Default model .065 .054 .076 .016 Interdependence model .218 .210 .227 .000

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Table 28. Details of Structural Equation Model 2 (Cont’d)

Direct vs Indirect Effects Standardized Direct Effects

Standardized Indirect Effects

TASKVIRT INFO_ISO PHYS_ISO JS TASKVIRT INFO_ISO PHYS_ISO JS INFO_ISO .261 - - - - - - - PHYS_ISO .295 - - - - - - - JS - -.579 -.362 - -.258 - - - PPERF - -.193 -.222 - -.116 - - -

Total Effects Standardize Total Effects

TASKVIRT INFO_ISO PHYS_ISO JS INFO_ISO .261 - - - PHYS_ISO .295 - - - JS -.258 -.579 -.362 - PPERF -.116 -.193 -.222 -

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CHAPTER 5: NARRATIVE VOICES ON CHALLLENGES OF TASK VIRTUALITY: A QUALITATIVE STUDY

Chapter

5

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Abstract:

The aim of this study is to support and clarify the previous studies presented in this thesis with personal reflections and anecdotal evidences. Particularly, the challenges associated with task virtuality are elaborated in this chapter. The impacts of task virtuality on these challenges are examined through structured and semi-structured interviews. Five business practitioners participated in this research to identify the challenges they face. Each interview is presented as a unique case reflecting the experiences under different work settings.

The reflections of interviewees’ not only cross-check some of the findings of the qualitative study linking task virtuality to work outcomes, but they also develop an understanding in the differences between various task virtualities by exemplifying the varying conditions in work settings and their outcomes. The individual findings, summarized for each case, highlight the relations between task virtuality, satisfaction and performance. Limitations and practical implications are also presented in the end of this chapter.

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INTRODUCTION

Unlike traditional teams, virtual teams are considered that they face unique challenges, which make coordination and collaboration more difficult when employees lack face-to-face interactions with each other. Various studies have reported on the strategies and recommendations to overcome these challenges identified for virtual teams (Bergiel et al., 2008; Schumacher & Poehler, 2009). At the global scale, the challenges of virtual work are even more evident due to additional communication barriers and cultural issues (Oertig & Buergi, 2006). Moreover, knowledge sharing, process- and technology-related challenges add insult to injury (Rosen et al., 2007; Munkvold & Zigurs, 2007).

Against all aforementioned challenges, virtual working was a response to the environment as a natural adaptation in the organizational context, since globalization and technological adjustments became a must to remain efficient and competitive (Raghuram et al., 2001). Nevertheless, the human aspects of virtual teams constituted a series of hurdles for the effectiveness of virtual teams; because employees were having hard times to get adapted to the new conditions as the mode of interactions has dramatically changed (Nelson, 1990; Raghuram et al., 2003). The difficulties attached to establishing trust, shared organizational culture, identification with team and organization and social connectedness were recognized in the academic literature as some of the limitations of virtual working (Wiesenfeld et al., 2001; Piccoli & Ives, 2003; Rezgui et al., 2005; Fiol & O’Conner, 2005). Past research has shown that identification is a key factor determining both individual and group performance (Ellemers et al., 2004). However, performance is not always affected by the factors that are inherently present in teams with a high degree of virtuality. The empirical evidence obtained in Chapter 4 argues that in predicting individual performance, task virtuality plays a more critical role than task virtuality does.

This chapter supports the previous studies presented in this thesis with anecdotal evidences and personal reflections acquired after five separate

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interviews. Besides, the findings also suggest the variables uncovered in this thesis, which can potentially guide researchers for future studies. The aim of this chapter is to expose the virtuality-related views, feelings and perceptions of the practitioners who possess a background in multinational companies and have experience in dealing with dispersed contacts, though not necessarily in team settings. These reflections mostly highlight the challenges experienced in relation to task virtuality, which will help us to affirm the link between task virtuality and performance. While there are some certain similarities between the experiences of interviewees with my own, the variety of their nationality, culture, field of work, position, seniority, mode of work and educational background contributes to this study.

Chapter 5 sets out the section about the general methodological discussion and methodology employed in this paper. The next part, then, introduces the interviewees’ backgrounds, followed by the research and interview questions. Interviewees’ responses are quoted in the excerpts narrating their reflections on the challenges, which indicate the views, perceptions and feelings of each individual. The relevance of reflections is discussed in the conclusion section.

GENERAL METHODOLOGICAL DISCUSSION

This study is conducted to enrich the methodological triangulation of the thesis. Denzin (1970, p. 297) define triangulation as "the combination of methodologies in the study of the same phenomenon.". It is often used as a tool to cross-validate previous results obtained through other alternative methods (Jick, 1979; Bryman, 2003). Denscombe (2008) suggests that combining qualitative approaches with quantitative methodologies offers an option to researchers to generalize the findings of studies. As a further matter, Jack and Raturi (2006) praise the procedure of methodological triangulation particularly in management research as it proposes completeness, contingency and confirmation. The authors also argue that qualitative studies make complex concepts easier to understand bringing insights and evidences. Oftentimes, insights and evidences are obtained through interviews. According

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to Bleich and Pekkanen (2013), interviews play an important role that complements the validity and verifiability of the research studies in social sciences. With a literature review covering the years 1994–2003, Bryman (2006) reports that the interviews constitute the most frequently used method in the qualitative studies using the triangulation method in the domains of social sciences including management and organizational behavior fields. On the other hand, some researchers argue that the aim of using triangulation method with introducing additional methodological approaches is to complete the pieces of puzzles to gain a broader perspective rather than confirming with the previously found results (Creswell, 2003).

Mixed methods are believed to suit better for the knowledge claims made by pragmatists, whose worldviews focus on understanding problems employing pluralistic approaches (Feilzer, 2010). Unlike proponents of post-positivism, constructivism or advocacy, pragmatists deal with the root of the problem to offer solutions, so the importance of methods remains inferior (Creswell, 2003). As a result, methodological settings become more contextual and practice-oriented (Denscombe, 2008).

To develop an effective strategy for methodological triangulation, Jack and Raturi (2006) contend that the data collection and unit of analysis should be parallel with complementary studies. This ensures that adequacy of results can be reasoned. Furthermore, another requirement for designing a robust qualitative study is that selected methods should possess “complementary strengths and non-overlapping weaknesses” (p.351). Taking the pragmatic approach for the design of this study, we focus the relevant findings that allow us to understand the problem and reflect the real life experiences of corporate practitioners. In the next section, the details of methodology are presented.

METHODOLOGY AND DESIGN

In line with the recommendations for an effective research strategy, the unit of analysis is kept as the same as in previous studies. For this chapter, individuals are the unity of analysis. This study brings the voices of

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professionals who had a variety of organizational experience at the international level and experience varying degrees of virtuality. To comply with the second strategy highlighted, the directed interview questions aim to shed light on the challenges of virtuality and its relation to individuals’ isolation levels and performance without specifying any additional background about the previous studies conducted. This method allows establishing an approach that will complement the strengths of the quantitative study. Furthermore, neither the concept of virtuality nor the task virtuality phenomenon is explained until the interviews were finalized. The rationale was to understand how virtuality is understood in the operational setting in the corporate environment.

To determine the general framework of the interviews, the questions were prepared in a written form. However, while some of the questions remained stable, the interviews were developed with structured and semi-structured settings. However, as each individual’s organizational setting, design and experience differ, some of the questions were adjusted to the interviewees’ backgrounds and needs.

In the data collection process, again a mixed method is utilized. All five participants were interviewed with an initial face-to-face meeting. Then, one of them was also contacted over the phone for a follow-up, in-depth interview, while another respondent is requested to provide written answers to structured interview questions after the initial interview was taken place.

Each person’s responses are provided as a case for the unity of discussions and reflections. Whilst this method serves to present a cohesive and fluent story of each interviewee, it also helps to identify the fact that different organizational settings may lead to unique outcomes. This further allows readers to compare the similarities and differences of narrative voices depending on their personal experiences.

Verbatim transcripts have been provided back to interviewees after the audios of dialogues were recorded. The interviews with three people were held

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in Turkish language, while the remainders were interviewed in English. After the consents, corrections and confirmations, the transcripts in Turkish are translated into English. Finalized documents are used for this research. The further details of each interview process are provided in Table 29.

Table 29. Details of Interviews

Name Date of Interview Mode of Interview

Language of Interview

Method of Data Collection

Milena 29 May/10 June ‘15 F2F / Written Form English Unstructured/Structured Yaman 30 May ‘15 F2F Turkish Unstructured Gregor 09 June ‘15 F2F English Semi-Structured Hakan 10 June ‘15 F2F Turkish Semi-Structured Metin 11 June/15 June ‘15 F2F / Telephone Turkish Unstructured/Semi-Structured

Since the focus of our interviews is to identify challenges that are linked with the organizations and self, the reflections contain a mixture of positive and negative feedbacks. Therefore, preserving the privacy of individuals is rather appropriate in this study. As a result, the names of the interviewees and the companies they work for are not disclosed. Pseudo names are replaced with the people’s name, whereas the names of companies are still kept confidential. These names are Milena, Hakan, Gregor, Metin and Yaman. The next section reveals the information about interviewees’ profiles.

INTERVIEWEES’ BACKGROUNDS

In total, five people were selected for the interviews, whose backgrounds were considered to fit well to the framework of this study. All have either a previous or current experience in a multicultural, international organization. On average, they had around nine years of corporate, full-time work experience. The average age of interviewees is 32 with a standard deviation of 1.73 years. Four of them work in a different country than their birthplace and nationality, while one interviewee is local. Only two of them are able to speak the language at the native level where the work is located. All interviewed people possess at least a college level education.

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PERSONAL PROFILES

In this section, the details of interviewees’ educational and professional backgrounds are highlighted. The additional information provided will also help to understand the context of work they are currently performing. Table 30 summarizes the demographics and background profiles of interviewees.

Milena

Since 2005, Milena, a Serbian national, has been living in Czech Republic, where she first arrived to study for her doctoral studies in Slavic languages. Before having been employed as a communication and marketing specialist in one of the local banks in Prague, she worked as a freelancer web editor in one of the prominent, international broadcasting organization for more than seven years. She speaks Czech and English languages at the native level, in addition to her mother tongue Serbian.

Yaman

Yaman is from Istanbul. Studied industrial engineering in one of the top universities in Turkey, his advanced quantitative skills allowed him to secure a financial analyst position in a global company in Russia. After gaining some years of experience specializing in IT solutions for the finance department, he further pursued his graduate studies in economics and finance in Prague in tandem working full-time in another American company. Upon graduation, he transferred into a major, global consultancy firm, where he serves for mainly clients from the finance industry for their IT integration support in Europe.

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Tab

le 3

0. S

umm

ary

of B

ackg

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f In

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Nam

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ende

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Nat

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La

ngua

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Sp

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D

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Lang

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Mile

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F 33

G

radu

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Ser

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S

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Cze

ch,

En

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Yam

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33

Gra

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Turk

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Eng

lish

G

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Gre

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M

29

Gra

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C

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, E

ngl

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C

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-En

glis

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Hak

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M

32

Un

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Turk

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En

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Ger

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33

U

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Turk

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Eng

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E

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Nam

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ende

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f Pr

ofes

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Exp

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Plac

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33

8.5

Prag

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Ban

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& M

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33

11

Pr

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29

6

Prag

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Sen

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Ris

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Hak

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32

10

Prag

ue

Fina

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33

9

Prag

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IT

Sen

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Sal

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184

Gregor

Gregor, born Czech, moved to Prague in 2000 from his hometown for his studies. He completed his bachelor's degree in the Czech Republic and master's degree in Asia. Gregor, educated in finance, started off his career as an intern in Ireland, later moved back to the Czech Republic, where he resided and worked on various analytical assignments for a private bank and various small and medium-sized enterprises. He is currently employed as a senior risk analyst in a large, multinational company. Besides his native language of Czech, he speaks English fluently.

Hakan

Originally from a southern town of Turkey, Hakan works as a software developer in an IT company in Czech Republic. Before coming to Prague in 2007, he spent 1.5 years in Germany and Turkey. Previously, he has worked at several foreign and multinational IT companies as an engineer specialized in electronics and computers. However, his software development and coding experience exceeds 10 years. Currently, he works as a developer in a data driven micro financing company providing loans to households. Next to his native Turkish and advanced English, he has a beginner level of German language skills.

Metin

Coming from communication engineering background, Metin has gained an extensive business experience, which helped him to build a successful commercial career. After working over two years in the most reputable companies in their own industries, Metin has moved to the world’s one of the largest IT companies, working as a senior sales manager responsible for Europe, Middle East and Africa regions. In addition to his virtual team experience, he oversees a team that is composed of members who are located in two different continents. As of Fall 2015, Metin will be an MBA

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student in one of the top ranked management schools in the US. He is fluent in English in addition to his native Turkish.

RESEARCH AND INTERVIEW QUESTIONS

As the pragmatic approach is discoursed in the general methodological discussion section, the identification of the problem plays the most important part of this research. Therefore, the challenges in relation to task virtuality are explored. Three major research questions to be answered are:

• What are the experiences of practitioners about the challengesof task virtuality in their daily tasks?

• How critical is the role played by the dispersed contacts inrelation to individual performance?

• Does a higher level of task virtuality confirm the difficulty ofchallenges experienced?

On top of these research questions, the challenges associated with dispersed contacts, not only with team members, could indicate the validity of task virtuality concept; whether or not the reflections of business practitioners are appropriately mirrored in this thesis. The answers of interviewees correspond to these questions directed. In some cases, these questions were combined, but in total 5 common questions are identified. These are:

1) Please briefly elaborate your task and organizational design in yourcurrent job.

2) To what extent virtual teams is utilized in your organization?3) How is your current team / task environment?4) What is the balance between electronic communication and face-

to-face contact with your colleagues/clients/suppliers (others)?5) What are the challenges you personally experience in relation to

virtual work?

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Each interview presented as a case in the following section starting with the interview process details. Next, important pieces of interview responses are presented. Finally, a brief discussion with a summary of each case is supplied.

CASES AND REFLECTED CHALLENGES OF TASK VIRTUALITY

Milena’s Case

My first conversation with Milena was not actually intended or planned to be an interview. I know her for over 8 years and she is a very good friend of mine. When we met on a weekend, we were having chat about how things go and so on…

Then, I started asking some questions about her current job, and how she feels there in general. Milena used to work as a web editor covering several countries in Europe. Among main roles; she was in charge of writing, editing and posting short news and news stories, editing multimedia content on the website and managing social networks. I knew how busy she was when she worked as a freelancer at that time, but she was mostly working from home. Especially some of her weekends were like a nightmare. She sometimes had to work uninterruptedly for over 12 hours on Sundays. For example, when there was an election in a country, of which she was responsible for, she had to update web pages, news and relevant statistics to provide the most current information for readers. Although the organization she worked for was multinational, her department covered Balkan counties, so she had frequent calls and interactions over the Internet.

I was particularly curious how her relatively new job goes. Currently, she works as a communication and marketing specialist in a local bank. While she has to deal with some international contacts, her focus is rather local. It is an 8-to-5 job in a corporate setting, more formal, more organized; more bureaucratic. Her main roles are establishing and maintaining contacts with

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media, editing and writing content for company’s intranet page and webpage, brand management.

During our conversation, she was actually giving me valuable information that could be relevant and interesting for my thesis. Therefore, while I recorded some parts of our conversation afterwards, I invited her to provide her answers on a written form. Therefore, the interview process with Milena consists of the details from our initial conversation in addition to her responses to my structured, open-ended questions. I combine them to reflect the entire story.

Me: How do you compare the challenges of your previous jobs to the new one? In your previous job, you had a lot of interaction with dispersed contacts. Was it the main difficulty?

Milena: To be honest, it wasn’t a major difficulty for me. Probably, the main reason was I was talking to my native language with them. So, it is slightly easier when you communicate in your own language. On the other hand, for me they were like friends. Whenever I visited Belgrade to see my family, I always created chances to meet with them, socialize with them. So, we had already built some sort of friendly relation which helped me a lot in my job. Secondly, I was more autonomous when doing that job. I had clear responsibilities and I knew what the expectations are. I knew what I was supposed to do and things went really well. Moreover, I was constantly in touch via electronic communication (mail, chat, and phone) with my colleagues or superior. My job required my full attention and I didn’t have the time to think of social aspect of my job.

On the other hand, in my current job, I feel that I have less freedom (autonomy). But, this is due to the fact that this job has a very different set of requirements. I also believe that bureaucracy makes things less efficient. In my previous jobs, maybe strict deadlines and pressure made it work well. However, in my current job, it is not much result oriented, but its focus is process-oriented. (This means) it is more important to follow the rules rather

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than achieving results. On the other hand, in my previous job, my outcome was visible as soon as I delivered the job. And most of the times, there was a huge time pressure.

Me: How do you compare the challenges of your previous jobs to the new one?

Milena: In my opinion, both jobs are equally challenging but for different reasons. I would maybe find office environment more challenging because of working relations with colleagues and inability to focus on certain tasks. There are too many distractions in the office environment, unlike working from home.

On the other hand, I must admit that working face-to-face brings a lot of advantages, not only because of ease of communication but also because of speed of communication. When you send an urgent email, you know how urgent is the email and how fast the action is required. But this is not the same for the other person receiving email. Therefore, when you have chances to meet face to face, you may speed up processes.

As already mentioned, when I had face-to-face contacts with my colleagues when I was in Serbia, the face-to-face interaction solved many issues we have. Like previous misunderstandings, complexities etc. On the other hand, in my current job, I still haven’t met face-to-face many of my colleagues, although we work in the same building and we are in daily contact through emails or by phone. There is also no way to meet with them because for internal communications, I deal with hundreds of people. But their impact on my job can be considered as minimal. Therefore, my team tasks are more important for my own performance. But in my old job, I had a very small team, and I had no any other interactions with others. Maybe this is also a noteworthy challenge (that I have in my current job).

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Milena’s Case Summary

While our interview with Milena and her answers to written form was rather short, they revealed important aspects. First of all, the way how she identified the virtuality matches the definition discussed and proposed in Chapter 2. Neither geographic dispersion nor electronic communication can define virtuality, as confirmed by Milena’s case. She revealed that the possibility to obtain face-to-face contact may reduce the level of virtuality. As she implied, the frequent interactions with people via ICT-mediated tools increases her virtuality despite of working in the same building. In the same vein, friendships were established with colleagues in Serbia, because of her frequent visits. This may partially explain why she feels that things went well in her previous job.

Analyzing the current job environment of Milena, compared to the previous one, it can be concluded that the close proximity of colleagues in the office environment, and co-presence of her team enable to label her virtuality categorization as low team virtuality – low task virtuality. Besides the major challenges mentioned, Milena emphasized the merits of working in the office environment, as it allows face-to-face interactions with others. Moreover, Milena’s lack of explicit identification of perceived performance as a challenge support the view that low task virtuality leads to a higher satisfaction with the working conditions and own performance. As a result, stronger perceived performance is expected if employees experience a low level of task virtuality.

On the other hand, Milena’s answers suggest a set of variables that could allow further research to be developed on a solid basis. When measuring task virtuality, team and network size, linguistic differences, organization type (bureaucracy or flexible organization), autonomy and task complexity may impact the relations between isolation, satisfaction and performance outcomes. Specifically, less complex, straightforward tasks may reduce the interdependence to others (Tushman &. Nadler, 1978; van Vijfeijken et al., 2002), and therefore, the challenges associated with task virtuality diminish. As a result, more autonomous jobs lead to higher satisfaction levels (Weaver,

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1977) and therefore positively impact employee perceptions about their self-performance (Jung & Sosik, 2002).

Yaman’s Case

As introduced in the profile section, Yaman currently works as a business consultant in one of the global management and financial consultancy firm. The projects he has been taking so far mostly focused on the improvement and integration of IT systems that allow clients to manage cash flows, risk and returns. His clients mainly operate in the banking and finance industry. Corporate or national banks or other financial intermediaries are among the main players in this industry. The next section illustrates the details of our interview:

Me: Please let me know your regular day at work? How does it look like? Where do you work?

Yaman: As a business consultant, I always travel. This translates that if I spent 10 days in the office in a year, the remaining time I spent at my clients’ premises. Our projects’ life usually depends on the requirement of each client, but I can say that it takes minimum period of 6 months. I am covering Europe and so far I have provided services to main central banks in Europe and a few corporate banks.

Me: Are you the only business consultant when you are assigned to a project or you take this job as a team?

Yaman: It’s a bit more complicated than this. There is me and the team. But team changes in each project. However, the number of consultants changes as well. So, each project has its own manager, who is responsible for the entire management including the coordination of work. In August last year, I was assigned to a new project in Germany. I am the only business consultant in this project and I have a direct reporting relationship with the project manager. But sometimes, there are more consultants as well. Some of

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the consultants involved could be at the senior level. This means, they do not actively participate in clients’ site all times.

Me: In this new project, you work with your project manager as one single team?

Yaman: Kind of. Because, at the end of the day, I am responsible for everything that relates to day-to-day activities at work. I am the one who needs to understand what is exactly needed. Project managers often have no idea what specific requirements a client need. They deal with higher level stuff. They are accountable and liable from all operations I am doing, but they are not responsible. In addition to this, they cannot have any solid idea, because they do not work with me. I mean physically. Project managers do not relocate when the project changes, but consultants do. Sometimes, project managers can be assigned two different projects simultaneously, but consultants cannot do this, because they have to be physically present in the offices where the client is.

Me: This means you have an intensive work relationship with clients, right? And less intensive with your project manager… Do you also have another people involved in projects?

Yaman: Yes. For each project, you work for your client, as if you are employed by the client. So, obviously, you develop an intensive work relationship with them each time. Project managers need to know some details and they are not very much involved. And there are two analysts located in the UK, and sometimes they support me with reports and analyses. For example, when the project manager asks about the details of configurations performed for a specific period in my project, I need to get some additional reports from the European headquarters, so I could get back to him. But otherwise, there is no any other person involved in projects.

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Me: Do you experience any challenges while working with your project managers when you do not see them face-to-face? Or with the analysts supporting you?

Yaman: Not at all. What project managers mostly care are the reports and getting responses to their questions. The rest is not important that much. Even if we worked in the same place, I would still have to answers questions via email for documentation purposes. And it’s the same with the analysts.

Me: Do you believe that you could provide clients the same level of services if you worked distantly?

Yaman: Every bank uses different systems, apply different methodologies. Even the most simplistic calculations sometimes differ. The way how they integrate these calculations to their systems differ. If not impossible, it would be almost impossible to provide consulting at distant.

I seek constant advice from my clients, and I have to observe many, many things. I need to see how processes are developed; I also need to observe who does what and how. How the developed processes are operationalized? Are there any gaps? All these questions require clear answers. And without any clear answers, there will be no point in providing consultancy services. In addition to this, in consulting, you need to be present all the time. Both physically and mentally. You are perceived as a knowledgeable, expert person in the field. Clients respect you because you are there to help them, solve their problems. You could not provide any fraction of the credibility and strong impression by being away from client. Contrasting to my previous jobs, being a consultant also requires an ability to build a self-image and strong social relationships with clients. At distant, no one can do these things that easily.

Yaman’s Case Summary

According to Yaman’s responses, several shortcomings can be made. Based on his explanation of his work settings, the features of job expose a low level of task virtuality. As his projects tasks mainly depend on the information

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exchange between his clients, the interactions often incur face-to-face. On the other hand, the structure of project teams indicates some characteristics of virtuality. Off-site project managers, some degree of involvement of analysts from another location increases the level of virtuality in teams in which Yaman works. Therefore, it can be concluded that the challenges experienced do not cross to the boundaries stemmed from team virtuality. Contrary, the performance is dependent on his observations, and ability to offer solutions to the observed problems.

Moreover, in consulting jobs, self-identity plays a complementary role in the services provided because the source of expert power is supported up by the image (Wright, 2009; Handley et al., 2007). Representations of a strong image would be dubious when there is a lack of face-to-face interaction with clients. While the literature include contrasting findings, the studies by Voida and colleagues (2002) and Meyer (2003) praise face-to-face interactions for knowledge workers as brainstorming appears to be the most effective when physical interfaces encountered. What is more, Gargiulo et al. (2009, p. 299) state the following:

“Informal networks play an essential role in the performance of knowledge workers. These workers create value by acquiring, processing, and providing information to create solutions and address complex problems.”

Another interesting shortcoming worthwhile to make is that although Yaman works with clients and colleagues from different cultural background, he did not refer cultural differences as a challenge. Meriläinen et al. (2004) discuss the importance of cultural cohesion to draw attention towards the environmental fit between consultants and clients’ organizations. Achieving an outstanding organizational performance is possible only when consultants act like internal employees of clients (Chen, 2011). Thus, the importance of cultural fit cannot be neglected, since the level of face-to-face interactions mediates the identification with organization, perceived fit, work-based social support and knowledge transfer (Newman & Nollen, 1996; Wiesenfeld et al.,

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2001; Fiol & O’Connor, 2005; Bourgeois, 2012). However, as Yamazaki and Kayes (2004) argue that the performance results of consulting services on dominantly rely on consultants’ analytical skills rather than skills of establishing interpersonal relations.

Gregor’s Case

My interview with Gregor was based on questions about his organizational setup and the related challenges. But before that, I wanted him to briefly introduce about his role and team setup. The rest of the interview hereinafter is presented on an “as is” basis.

Gregor: I am a senior risk analyst working for a leading energy company. It’s been more than four years and five months in this current job. I am responsible for managing the portfolio of North American customers worth $17billion.

My team is composed of three analysts and one team manager. As analysts, we all manage our own portfolios. Since I am responsible for the North American business unit, my primary contacts are thousands of kilometers away from me.

Me: So you are co-located with your own team, but you have to deal with contacts away from you, right?

Gregor: Yes, but my functional manager is also away from me. He is located in the US with the rest of our top level-management. I have an administrative manager here in Prague.

Me: Does this mean that you have to deal with time differences when working?

Gregor: Yes, indeed.

Me: So, what other challenges do you personally face when working with dispersed contacts?

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Gregor: We already discussed time zone difference, so it is a real challenge. The US is a big country and there are several time zones. When I work with the companies on the east coast, it is a bit easier because when it’s after my lunch time, around 1pm, they are already in the office, so I basically have half a day to discuss issues with them. However, the companies on the west coast, when they get to the office, I am already about to leave the office so the requests have to wait for the next day.

Me: Does that mean that when you arrive in the office in mornings, you have some left over works to do from the previous day related to the companies in the west side?

Gregor: Yes, basically I have to deal with them immediately when I get to the office, if they are really urgent. I actually have another colleague, located in Canada, who deals with requests and he is my back-up who covers my responsibilities related to urgent cases when I am not in the office in the evening. But otherwise, I am responsible of all cases in 90% of the time.

Me: What other challenges do you face when working with dispersed contacts? Any misunderstandings or similar issues related to communication?

Gregor: I have to say that I used to work in a global portfolio before moving to this role, but my regional focus was EAME (Europe-Africa-Middle East) and I faced some more challenges when working with them as opposed to dealing with North Americans because US people are more straightforward in communication, I must say.

But of course, from time to time, there are some misunderstandings because sometimes emails are just not enough. I still prefer talking over the phone to solve issues. It is, however, not always possible. Emails are still an ideal tool for communicating and sometimes it has to be the only channel to discuss ideas, raise issues or deal with problems.

Me: How many Czechs do you have in your team? How is the structure of your current team? Where are they from, and what do they do?

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Gregor: Until recently, there were two other Czechs in my team, but after a very recent reorganization there is only one. My other team members are from Moldova and Belgium and our administrative manager is from the UK.

Me: Do you experience any trust related issues with your team members?

Gregor: No, I don’t think so because I know these people well. I physically see these guys, I meet them, go to lunch… And I somehow know what their baseline behaviors are. I know what to expect from them. I know their limits. I know how they feel when I see them.

Me: So, what about with people in the US? Or, your back-up in Canada?

Gregor: Ah, with the person in Canada, we usually chat, and we chat a lot. By chat I mean through Lync (chat application of Microsoft) via computers. With this program, we can partly express our emotions using emoji icons. We can really discuss our stuff with this tool. It is really fine. Despite the fact that we are distant from each other, we have been able to become closer to each other as colleagues. So, we trust each other.

Me: Do you only chat to share work related stuff or discuss work issues, or kind of everything?

Gregor: Everything. That actually helped us to build trust even though we have never seen each other. Because he’s my back-up, I see him as a part of my team, although from the administrative point of view, he is not. But, with my clients or other colleagues that I am working with or advising to, I wouldn’t have such a close relationship. First, it is because of the fact that we don’t interact so often. And second, when it comes to email communication, there has to be a certain level of professionalism. This also influences the fact that some feelings or messages like what they really want cannot be passed across completely, which means that these emails are not always so clear.

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And therefore, it sometimes takes a couple or more emails to get some further clarification on what the message is and therefore it is more difficult to get instant results.

Me: How do you evaluate your job? Do you think you perform a virtual or a traditional job? That means do you work more with your team members or more with colleagues located elsewhere?

Gregor: I would say more virtual, because in the traditional sense, there is not much work related cooperation. We don’t really cooperate. It is rather that we jointly accumulate and share knowledge as a center and provide centralized service. Yet, we do not discuss same issues, everyone has different issues. So, the common issues we really have are limited, although we have a common goal that is to provide services to our clients and colleagues.

Me: Is that because everyone in the team has a different portfolio and responsibilities?

Gregor: Yes. Everyone is responsible for his/her own portfolio for different regions. My share is North America, my other teammates have EMEA. Then we also have colleagues in Asia, who are responsible for Asian portfolios.

Me: When working with your dispersed colleagues in the US, do you ever feel that you miss some part of information? Do you think would it make sense if you worked in the US?

Gregor: Absolutely. For example today, in the evening, I had an urgent call. It was about moving some product through the pipeline. I was examining the optimization of logistics with our customer and I was asked to advise about the financial risk and exposure associated to this movement. However, I was not able to give them a quick feedback in such a short period of time. Simply because, it just takes some time to analyze financial reports, conduct the risk-exposure analysis and make financial decisions. As a result I was not

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able to give them a quick response, their reply, in return, was that they would find another solution and move the product through another customer. I told them that I could investigate whether it was feasible or not but asked for more time. Yet, the response I got was a bit cold – at least this is how I felt. Their reply was quite plain i.e. that they were going to move the product differently as they needed an alternative solution but they didn’t tell me any rationale. At that time, I didn’t actually understand whether they were disappointed because I couldn’t give them a quick response or whether it wasn’t an issue at all to go and find alternative solutions. I was completely emotionless and I really had no idea what the other person was thinking about this situation.

Gregor’s Case Summary

Gregor’s case is a typical representation of the situation, where he has low team virtuality and high task virtuality, as identified in Chapters 3 and 4. Although, administratively he and his team report to a single manager, who is co-located with them; functionally, each team member has own responsibilities associated with different regions and different points of contacts thereof. Gregor has been facing with the challenges of virtuality, although the team structure is rather conventional.

The examples he provided indicate that the interactions with others have impacts on Gregor’s own performance. Part of the challenge is the lack of face-to-face contact. On the other hand, Gregor was able to establish a strong relation with his colleague in Canada. The frequency of formal and informal use of electronic communication may also mediate the trust and isolation perceptions when working virtually. Montoya et al. (2009) present that the nature of organizations and tasks determine the level of communication over ICT tools. Even though frequency of communication is largely elaborated in the literature, the content of messages transmitted in this process in not identified. The frequency and informal nature of messages may signal the friendship opportunities, although they take place in virtual space. Therefore, trust can be established immediately, if the tools and environment allows both formal and informal idea – information exchanges (Hsu et al., 2007). As a

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result, the frequency and nature of ICT use may mediate the relationship between task virtuality and isolation at work.

On the other hand, the interview results indicate similar suggestions as previous ones. Apart from the most apparent challenge of lack of face-to-face interactions, time zone and cultural differences may escalate the difficulties experienced when working virtually. Additionally, Gregor’s reflections about the communication style differences between European and North American colleagues illustrate that the clarity of tasks are dependent on the information holders. However, his answer to the final question related to the recent difficulty he has experienced conveys that the lack of non-verbal messages are still an important element for a healthy feedback mechanism and beliefs about one’s own performance.

Hakan’s Case

Also discussed in the profile section, Hakan works as a software developer in an IT company in Prague, Czech Republic. His previous role was based in Germany. He has been involved in numerous projects varying in sizes. In his previous company, he assumed a global position, whose responsibilities include developing software at a very large IT corporation. He discussed about the difficulties he faced during coordinating and working in a highly virtual team, traditional teams and hybrid ones throughout his 10-year experience.

Hakan: In the last eight years, since I moved to Prague from Germany, I changed three jobs. In each company I worked for, the structures of teams differed. My first role in Prague was a small company, which had been taken over by one of the largest IT firms in the world. It was just a few months after I started working there and I became a part of a global team all of a sudden. After three years, I moved a very small software developing company, where I worked over 1 year. Following this, I returned back to my previous company but for a different role. That was even a more global position because it was related to research and development. And finally, I have been working in my

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current role almost for one year. So, I have some years of experience that I can compare the diversity of I observed in these different roles. I have worked in teams of 5 people sitting next to each other. I also worked in teams with more than 15 people that are distributed in several continents and times zones.

My experience with that team where we had more than 15 people in different continents is the most striking one. While we were working in Prague, as the lead coordinating team of the project, we had to deal with our team members in the US and India. The challenges included time zone differences and culture. From the cultural perspective, the way how we communicated varied dramatically. When we sent emails to our American team members, they were all short and to-the-point. For Indian team members, we had to include more details and instructions. Work practices also differed. How they followed up tasks was different. Our customer was located in Germany. That was the reason why we were leading that project because we could arrange all communication at more convenience due to proximity. Even though we were leading this project, the decision mechanism always seemed to stay within the US office. We have had very difficult times because team members in the US had modified a couple of settings in the software, which they failed to notify in timely manner. This had put us into a very challenging situation in front of the customer. And conversely, when we got an updated feedback from our customer, even though we promise to take care of the issue notified, we had to wait the action from the US office. In several occasions, we had to work at nights, because we had to coordinate the jobs in the US office more closely. These were major challenges I could highlight.

Me: And how is your current job? How do you compare it with your experience?

Hakan: My current company applies a methodology called agile. Based on this methodology, the company gives a special attention to bring the task forces together who share common goals. The idea of agile methodology is to be able to respond quickly. Also quick adjustments and adaptations are

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needed based on this approach. As a result, virtual teams may not be the best friends of agile approach, because it hinders quick response times of teams.

Me: How do you compare agile methodology to the traditional approaches? Can you give some examples?

Hakan: For example, if you want to sell a product or platform (software), there is a development time linked to this. Let’s say six months. In the traditional approach, you get back to your customer after you finalize the product, and make adjustments according to the feedback received. However, in the agile methodology, you split the tasks into categories so that you could be able to present some basics after the first two weeks. There is a lot of information exchange between customers and developers. Therefore, developers also need to communicate with each other more frequently. So, I work with a traditional team sitting with my co-developers in the same office. Every day, we organize quick meetings for discussing the progress of the ongoing project. The aim is to share continuous feedback within team. The same is also valid with customers. The quicker the feedback, the better the outputs. It also confirms whether you fully understood what is expected from the customers’ side.

Me: How did feedback mechanism work in your previous job, then when you were coordinating your virtual team members?

Hakan: Of course, it was much slower, because we were using waterfall model (a traditional model that is based on developing software in successive stages (Boehm, 1988)). Actually, the reason why I had to leave my previous job, because at the end management realized that waterfall model is not a suitable approach for software development. They decided to switch to agile methodology. The implication was the total redesigning of the software development team. As a result, virtual team structure disappeared and all members of the software development team are based in the US. So, other software development teams were shut down. This illustrates how critical is the face-to-face interaction in software development. Because it is often very

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challenging to convey your message in the email when there are lots of technical details involved. When you decide using chat option over the computer or talking over the phone to explain the issue, you have to sacrifice a meaningful period of time. When you use this time instead of working on coding, the quality of your output inevitably declines.

Hakan’s Case Summary

There are unique challenges associated with software development in the IT industry, especially when there are time differences and/or spatial distances between the members of teams. Therefore, the agile methodology is deliberated as a quick fix to these challenges, because more and more software developing firms started to implement this approach (Rangra & Gupta, 2013). Taber (2013, para. 3) concludes that “the closeness of collaboration between developers and users makes agile projects so cost-efficient and responsive”.

As Hakan’s reflections confirmed that proximity and synchronicity are critical elements in software development projects. This implies that teams cannot respond as quickly as possible when there are virtual organizational designs in place. The lack of face-to-face communication not only creates a barrier for within team interactions, but also it delays the response times back to customers. As a result, as per Hakan’s observation, the quality of end results is negatively impacted by these challenges. The redesign, which introduced the agile methodology in his previous company, caused several employees to lose their jobs because top management decided to form a face-to-face team that could both flexible and responsive. This case constitutes a well-suited example to the situation that when task interdependence within teams is high; task virtuality of teams gets high as well. Communication problems within team can be solved best if members of a team have chances to discuss, exchange ideas, and interact face-to-face.

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Metin’s Case

As discussed in the personal profiles section, Metin is a senior sales manager in a major IT company. His assigned area is composed of several countries in the EMEA region. He runs a team that is dispersed in two different continents; one in Prague, another in Dubai. The team in Prague consists of 8 sales representatives mostly from Eastern European countries including Czech Republic, Slovakia, Russia and Turkey. In Dubai, 6 representatives and their team leader, from African and Arabic countries, work together. I asked him to summarize the challenges he faces in leading a virtual team.

Metin: For me there are multiple challenges. Leading a virtual team is not an easy task for many reasons. Take team meetings (via teleconferences). We can’t even run efficient and effective team meetings. In our monthly sales meetings, we discuss several important issues. I try to deliver messages in an order; from the most important to the least. However, of course the urgency is not the same thing as importance. Unfortunately, my team in Dubai sometimes faces difficulties to reckon the urgency of tasks. Another example, when I assign the same task to these teams, I always experience a difference in the delivery times. The team in Dubai is the one that submits with a delay. For example, if my (immediate) manager sends a request or a report on an urgent matter, the team in Dubai again does not take the ownership or feel an immediate obligation to reply. This is not because they are poor performance. I could never say that. Contrary, their regular performance and commitment to tasks are much higher than those of my team in Prague. But they only have a barrier to perceive our immediate feelings or expectations. When I have a trouble with some certain report, my team in Prague tries their best to support me, whereas the team in Dubai often can’t comprehend what is needed. As a result, the team I manage is always quicker to respond and to understand what’s needed because they have the chance to observe things in person. They can see the tension and pressure. I totally believe in my own job, face-to-face interaction has a lot to do.

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Me: Could you please elaborate more on other differences between your employees in Prague and Dubai?

Metin: For me there are multiple challenges. Leading a virtual team is not an easy task for many reasons. But don’t get me wrong that I complain about my team in Dubai. In fact, they are more hard-working and more committed as I already mentioned. Let me give you an example, if the Prague team moves to Dubai, and they move here, I will have a higher challenge. Europeans are a bit more laid back. When it is 5PM, they leave the office, no matter how much work left. But maybe because of culture or other reasons, like the dynamics of job market such as the level of competition etc., the team in Dubai works until late hours. It is just like the standard. So, I wouldn’t able to manage my employees, if the setup will be other way around.

My previous comment on the differences was actually purely based on the comparison of interactions. I wanted to highlight the advantages of being together with my team in Prague.

Me: I assume you also have to work with other people who do not share the same location with you, as working in a global company. How much do you think they have an impact on your individual and team performances?

Metin: Extremely. It is impossible to ignore the impacts of others when they don’t share the same location with you. Sometimes, they have a direct influence. Let me explain you with another example. As being responsible for sales, I can tell you that the most crucial part of our job is to catch a new customer; to develop new businesses. You really have to try hard to convince a customer, persuade why we are better than our competitors etc. The level of competition in software sales is at margins. So, imagine that your performance, bonuses and future career depend on the amount of sales you make.

Only a few months ago, with a decision of top management, our contract department has been centralized. They are mitigated to India. That

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department does not exist in our offices anymore. You know this new trend of shared services centers. But this move has impacted our jobs dramatically. The old contract department could process new customer setups as short as two days maximum. Then, we were able to provide the software and required installments for our customers. But with this new change, it takes about two weeks on average. Some of our prospective customers have already given up working with us just because we were not able to quickly process the approval and creation of new contracts. For example, even if there is a minor issue with the customer creation process, the ping-pongs of emails with the new department both complicate and delay the issue. So, no matter how hard my team works, their performance largely relies on the new contract department. And as already mentioned, not being able to explain things face to face creates a huge barrier for us.

Metin’s Case Summary

Metin’s case paints a very clear picture on the impacts of dispersed contacts worked with. In global organizations, lack of face-to-face contact is a major source of a challenge because it often hinders the speed and clarity of communication and the effectiveness of end performance results of individuals and teams. When people outside of the teams or colleagues scattered around the world have a high degree of task interdependence with individuals, their input becomes more significant. The more people, whose interdependence is high, is interacted via ICT-mediated tools, the more problematic becomes the work, because our research suggested that it influences isolation perceptions and consequently satisfaction, performance and turnover intentions. The meaning and joy received from job declines if efforts are damaged by others who cannot be contacted face-to-face. As a result, employees consider alternative options outside their current roles and companies.

Similar to other discussions, the involvement of other cultures and the differences associated with culture appeared to be a relevant finding in this case as well. However, in this context we see the evidence that there has to be a fit between group and environment. As Metin, recognized, the team in

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Prague could not be managed so well, if they were located somewhere else. The group fit into environment is also crucial because empirical research suggested that some cultures are more inclined to interact via ICT-mediated tools (Randstad, 2012).

LIMITATIONS

There are several limitations associated with this research. The first one relates to the methodology itself. Interviews are often criticized for its limitation of representative nature which influences the reliability of qualitative sources (Creswell, 2007). This issue is addressed with the inclusion of interviewees from various backgrounds into the study. Even though there were some polarizations in some demographics, variations in work settings, educational backgrounds, exposure to virtuality and industries offer a pertinent diversity considering the aim and scope of this research.

Another limitation of qualitative studies, especially when an interview-based method is utilized, is that researcher bias. It is referred to researchers’ intention to prove themselves (Johnson, 1997). However, Bleich and Pekkanen (2013) argued that interviews can offer strong, respected evidences regardless of the limitations. This study should be evaluated in the light of previous studies presented in this thesis. A small number of sample size represented in this study may be critiqued as well. However, one should note that the reflections illustrated in this research do not seek a high level of validity, and therefore generalizability; but they propose unique cases. Small (2009) argued that case-based interference should focus on saturation rather than representation. The reflections of interviewees’ not only cross-check some of the findings of the qualitative study linking task virtuality to work outcomes, but they also develop an understanding in the differences between team and task virtualities by exemplifying the varying conditions in work settings. Therefore, personal stories only incorporate the practical aspects of the theoretically developed models, not offer a strict cause-effect relationship.

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Finally, some could contemplate the past relationships and shared histories and contexts with interviewees among limitations. Higher level of strength and closeness of past relations may cause answers to be inclined in a way that researchers want to hear. Shared histories and contexts have some influence on the similarities in experiences and therefore in reflections. Creswell (2007), however, advocates that open, frank and transparent response behaviors increase the quality of interviewees’ stories. Especially, when challenges of virtual work often involve negative work outcomes, failures and potential weaknesses at the individual and group level, acknowledging and transmitting them require a certain level of trust and interpersonal relation to be established a priori. As a result, the integrity and openness about the interviewees’ stories are safeguarded in this study.

CONCLUSION

The aim of this research is to achieve corroboration through the reflections of business practitioners as the final step in the triangulation approach. Each case presented empirical and anecdotal evidence that task virtuality plays a partial, sometimes significant, role in determining the performances of individuals and groups and accompanying challenges in the workplace. These evidences support the initial research questions addressed in the introduction part of this research. Specifically, besides testing the predictive power of task virtuality in determination of organizational outcomes with a quantitative dataset in the previous chapter, the cases in this chapter support the practical relation between the variables examined.

A closer look at the cases, the findings suggest that the extent of face-to-face interaction with others who are involved in delivering tasks not only determine the perceived performance of individuals and groups, but also the satisfaction of the work results, nature and communication aspects. One of the most frequently addressed challenges was that delays in communication originate the overall performance of sales teams or software developers. Spector’s study (1985) regarding the facets of satisfaction indicate that the quality of communications and interactions determine the fulfilment of

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employees. Au and Marks (2012) also report employees’ diminishing satisfaction and commitment levels when working virtually due to low identification. The reflections of Gregor, Metin and Hakan, who deal with dispersed contacts largely due to their work settings, prove that when higher task virtualities experienced at the individual level, the perceived performance and satisfaction from jobs and end results decline. In same token, Milena and Yaman’s experiences indicate a lesser extent of task virtuality, although Milena has a low level of team virtuality, and Yaman does high. As a result, for both of them, low task virtualities demonstrate comparatively higher levels of perceived performance and satisfaction from the job.

The implications of this study are the following. To strengthen the satisfaction received from the job and performance as an individual, organizational practitioners need to identify the needs of their structures and assess individuals’ task virtuality levels. The more challenging becomes the communication with others, whose collaborations and interactions are essential, the less satisfied become employees about the communication, environment and outputs. Therefore, their perceived performance is also negatively affected. As Wong and Burton (2000) note, performance declines are inevitable when there is no face-to-face interaction between employees when they perform highly interdependent tasks. Similarly, Kilduff and Brass’s findings (2010) show that the role played by task structures and network dependencies are critical in individual’s performance as well as in satisfaction. According to these findings, the authors recognize that friendship opportunities, which are dependent on the level of face-to-face interactions, should be taken into account when designing effective organizations.

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CHAPTER 6: CONCLUSION AND FINAL REFLECTIONS

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FINAL DISCUSSIONS

Since organizations have become more global, the structures in organizations have been transformed into more flexible units. With these changes, many new approaches have emerged in management practice. Among all others, virtuality in organizations received a growing attention in the last decade. Extensive amount of research confirmed the fact that virtuality plays a crucial role in organizations. Findings linked virtuality to a number of variables including organizational and behavioral outcomes. Ranging from team leadership to employee feelings, lack of face-to-face contact between people at the workplace resulted in fierce challenges that raised the barriers for organizational effectiveness.

Although the dynamics of virtual working have gained much traction, only a limited number of studies addressed the organizational and behavioral impacts of virtuality at the individual level. This thesis adds value to the literature by introducing the task virtuality concept and its impacts on work related behaviors and attitudes.

Task virtuality, first and foremost, is to be evaluated as an individual level construct. With this aim in mind, the gaps in the virtuality research provide further directions to this work. According to the existing virtual team literature, a linear and unidirectional relationship is suggested between team virtuality and the virtuality at the individual level (Suh et al., 2011). This implies that the source of virtuality can only vary with the level of team virtuality. The more virtuality in team, the higher the impacts of virtuality perceived at individual level. This thesis illustrates that the opposite can be true as well. Based on the conceptual definition proposed, and the empirical study conducted; individuals can experience a higher level of virtuality even in traditional team settings.

Recognizing “virtuality” as a concept that varies at the individual level, rather than at the team or organizational level enhances our understanding of employee feelings and perceptions in a more comparable and objective

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fashion. Previous studies could only assess the degree of virtuality in teams. These virtuality scores obtained for teams are assumed that the level of virtuality influences all members in the team equally ignoring individuals’ work practices. However, with the introduction of task virtuality, the extent of virtuality of each individual can be examined. Regardless of organizational settings, task virtuality indicates individuals’ virtuality, not teams.

The studies described in this thesis expose that task virtuality is an empirically existent but undiscovered phenomenon. This research also argues that the task virtuality concept has not only a theoretical relevance but as well as practical implications. To illustrate theoretical and practical relevance of this concept, four distinct but inter-related articles are presented in this thesis.

First of all, not every team is identical. Neither are the roles of individuals in a team: The nature of tasks differs. The number of people dealt differs. The way how these people are interacted differs. As a result, employees’ network and task structures influence the individual levels of virtuality experiences. Therefore, virtuality is not only sourced by team members but as well as by others. All others those are not interacted face to face. In order to look at from a broader perspective, capturing the impacts of entire task and network structures of individuals, task virtuality becomes an important concept to consider.

In order to manage the challenges associated with virtuality effectively, Maznevski and Chudoba (2000) highlight the crucial role played by face-to-face meetings. Curseu et al. (2008) support that physical, face-to-face encounters lead to the initial development of interpersonal trust in virtual teams. Interestingly, however, a significant number of employees today in organizations perform tasks with people that they never meet. They rely on information from people whom they never see. To be able to function effectively, virtual team members are provided training programs that alert the challenges (Warkentin & Beranek, 1999; Malhotra et al., 2007). Rosen, Furst and Blackburn (2006) conclude that effective training programs are essential

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especially for virtual settings, as the skills required to perform in such an environment differ vastly. On the other hand, virtual work has become a norm for global organizations. Consequently, these skills are needed to be acquired by those who encounter the challenges of virtual work, no matter how their teams are structured (i.e. virtual or traditional). Considering virtual team members are not the ones interacting virtually, there is also a need to address this issue from a broader perspective covering all interactions with others in organizations. Thus, the “task virtuality” concept is coined to be able to answer further questions related to the challenges.

To illustrate the impacts of task virtuality, and its distinction from team virtuality, different methods and approaches are utilized. The identified research questions are answered by the each set of findings or theoretical discussions of each study. The summary of study findings, followed by the practical and managerial implications, is discussed in the next section. Final reflections and closing remarks are also communicated in the end of this chapter.

SUMMARY OF FINDINGS

In this thesis, five major research questions are identified in relation to task virtuality. First question was: “How can we measure virtuality in a unique way that captures both interactions within a team, as well as those outside of the team?” To be able to uncover this question, there was a need to elaborate how virtuality has been conceptualized in the literature. Considering the equivocal approaches in the virtual team literature, a critical review has been performed. An extensive review covering years between 2006 and 2013, demonstrated that a unified measure for virtuality is an emergency. Whilst virtuality is considered as a multi-dimensional construct by the scholars, the review findings conclude that lack of face-to-face interaction is the most significant and defining characteristic for both conceptualization and measurement of virtuality. As a result, this literature review provided guidance how virtuality should be measured in order to capture the most important characteristic of virtual teams..

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To be able to answer the second question, “ How can we compare these two types of virtuality in organizational settings?”, a conceptual paper, published in Administrative Sciences, attempted to extend our understanding of individual level virtuality. In this chapter, in contrast to past research, it is asserted that virtuality experienced by individuals in organizational settings is not an immediate outcome of team virtuality. Thus, both similarities and differences between task virtuality and team virtuality are discussed. To illustrate the disparity of virtuality in teams and tasks, a two-dimensional virtuality framework proposed. Based on this framework, it is 2x2 matrix represented different combinations of team and task virtualities.

Chapter 4 represents the most crucial part of this thesis. To test the assertions made in Chapter 3, and to be able to answer two following research questions, an empirical, quantitative study is conducted. These questions are: “If there is a valid tool to measure the individual impacts of virtuality, can we measure organizational and behavioral outcomes with it” and “Will that measurement tool be able to predict organizational outcomes better than the tool for team virtuality?”. In this study, an integrated conceptual model is tested assessing the impacts of task virtuality on workplace social isolation, job satisfaction, perceived performance and turnover intention. Besides, the impacts of task virtuality on the sub-dimensions of workplace isolation, physical isolation and informational isolations are also tested. The effects of relations between variables are measured through path analyses using the structural equation modeling technique. Hierarchical regression models, which evaluate the comparative impacts of team virtuality and task virtuality, are also examined in this study. Furthermore, post hoc analyses are performed to compare the mean differences calculated between virtuality combinations. Most importantly, a quantitative measurement tool evaluating employees’ task virtualities was developed in Chapter 4. This tool enables to assess employees’ network contributing to the virtual work environment at the personal level. This also means that this tool assesses virtuality for everyone working in organizations regardless of team settings. Our models suggest that workplace social isolation, physical isolation and informational isolation can

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be caused by high levels of task virtualities of individuals. The data derived from task virtuality explain a larger proportion of isolation in the workplace whereas team virtuality remain insufficient. This implies that frequent face-to-face interaction with others of which an employee had higher task interdependence is a crucial determinant in job satisfaction, perceived performance and consequently turnover intention, as it diminishes workplace isolation socially, physically and informationally.

To enrich methodological diversity in triangulation, another qualitative study is presented in Chapter 5. This study supports the findings of previously presented studies with the anecdotal evidences enriched by five business professionals own reflections. The summaries of interview responses also confirm that the level of face-to-face interactions is a critical element which determines the challenges experienced in relation to virtuality. Narrative stories reflected by five business practitioners demonstrate that unique challenges are associated with the varying degrees of task virtuality. These challenges also relate to work outcomes such as perceived performance and satisfaction received from the communication and nature of job aspects. For employees with a high level of task virtuality, delays in communication and quality of performed tasks are perceived among the most frequently addressed challenges. In fact, they are considered as the major factors deteriorating performance of sales teams and software developing teams. On the other hand, in addition to validating the previous chapters’ findings; the practical evidences suggest additional key variables that would influence the challenges of virtualities. Particularly, reflected stories indicate that the impact of trust and cross-cultural working environment play a significant role in perceived performance and satisfaction feelings.

MANAGERIAL IMPLICATIONS

The findings obtained in this thesis address a series of managerial concerns linked to virtuality as much as they offer theoretical contributions. Being aware of the challenges caused by task virtuality is critical for managers to the success of teams and as well as individuals in organizations and any

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organization is no exception. Three major The implications can be emphasized by highlighting three major pillars that relate task virtuality to organizational design, leadership and performance evaluation.

The first managerial implication relates to the organizational design element. While virtual teams are given special attention for its coordination and facilitation for information sharing to maximize organizational effectiveness (Maznevski & Athanassiou, 2003), virtual aspects in traditional settings are often ignored. Managerial support, coordination and training requirements should be carefully analyzed for employees dealing with dispersed contacts regardless of team structures. As our studies demonstrate, an individual may face a high level of task virtuality against a low level of team virtuality. By the same token, a high level of team virtuality does not directly imply a high level of task virtuality. Thus, resources and technological arrangement should be made based on individual requirements. As a result, it is more important to identify employees who don’t see the people that they mostly collaborate with and depend on. These people may not be their team members only.

The second implication is that the empirical study findings suggest that the relationships between organization variables and task virtuality are stronger than those with team virtuality. For effective leadership, managers need to be able to understand the dynamics that influence employees’ feelings and perceptions. Based on the study presented in Chapter 4, task virtuality is found to affect employees’ workplace social isolation, job satisfaction, perceived performance and turnover intentions significantly. Results also show that the least social and physical isolation are experienced by those who have the most frequent face-to-face interaction with others (respondents categorized in LowTeamLowTask), while the highest social and physical isolation are experienced by people with high team virtuality – high task virtuality (respondents categorized in HighTeamHighTask). This group of people also perceived the least satisfaction and least self-performance. As an instant diagnosis, when employees lack face-to-face interaction with those

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who play the most critical roles in employees’ task interdependencies, they feel significantly more isolated, less satisfied with their jobs and performances. Moreover, they appear to be the first to leave the organization when compared with employees possessing high task virtuality (cf. Table 19). Therefore, for managers, being able to offer social support and to create conditions that could increase identification to goals and organizations carries more importance when the task virtualities of individuals are high. In the end, turnover decisions are dependent on the factors that are explored in this thesis. Task virtuality allows managers and organizational designers to assess the individual level of virtuality experienced by employees both in virtual and traditional team settings. Whenever isolation is detected at the individual level, the rectification of work settings or resources, social support and training may lead to increased satisfaction and performance and consequently reduced employee turnover (Furst, Blackburn, & Rosen, 1999; Beranek & Martz, 2005; Malhotra et al., 2007; Garrison et al., 2010; Hoch & Kozlowski, 2012).

As much as team members interact within teams by cooperating and accomplishing common tasks, they also compete with each other (Lin et al., 2010). Managers are responsible for providing fair tools and conditions to promote a fruitful environment for maximum individual and group performance within a team. Therefore, the design of organizations should be considered as a procedure which should be applied fairly. An unfair organizational design for team members, such as one having a high level, whereas another has a low level of task virtuality, may result in negative feelings because of unfair goal perceptions. Therefore, the evaluation of performance cannot be based on fair judgments since the conditions for each member differ. In order not to compare apples with oranges, task and network structures should be comparable when designing organizations, so that performance outcomes could be comparable as well. Designing each individual’s tasks appropriately and accordingly may not only increase the person-environment fit due to perceived equal justice in procedures (Kristof, 1996; Elovainio et al., 2002), but subsequently it can also provide a better

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mechanism that will enable comparable performance evaluation. As a result, task virtuality facilitates an important role in determining suitable more designs for organizations as well as fair goal settings and performance evaluations.

Probably, the most important findings of this research relate to the managerial implications. Since companies have started to become more global, the virtual settings in organizations have become a popular trend in organizations. Managers and organization designers often categorize teams according to their virtualities when they develop organizational structures. As a common practice, teams, which are considered more virtual, are provided supplementary training programs that familiarize members with the challenges of virtuality. In the same way, organizational consultancy firms specialized in virtual team dynamics engaged with organizations to overcome the difficulties of virtuality. On the other hand, traditional teams do not get such support even though some of the members in traditional teams require it. However, both qualitative and quantitative studies in this thesis indicate that the challenges that are considered unique for virtual teams can be experienced by anyone, not necessarily virtual team members only. By the same token, some of virtual team members don’t face these any of these challenges. The real question to be asked how much lack of face-to-face interaction has an impact on individual performance. What most matters is that whether or not jobs performed by individuals contain virtuality characteristics.

As a result, in order to increase effectiveness of individuals and organizations, managers should not only consider the extent of virtuality of their teams, but also analyze the extent of each employee’s individual level, task virtuality. There may not be a single, one-size-fits-all answer to the challenges of virtuality for every team member because each member could interface a different level of virtuality, depending on task and network structures. As a result, managers should also be careful in providing fair

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organizational tools and conditions that they can evaluate individual performances fairly.

FINAL REFLECTIONS AND CLOSING REMARKS

My aim with this thesis was to underline the differences between team virtuality and task virtuality. The studies reported in the thesis have challenged the underlying assumptions of virtual team research. From the beginning of discussions about the “virtuality” concept in the organizations science literature, it has been assumed that the impacts associated with a certain level of virtuality within a team are distributed to its members evenly. Therefore, the guiding principle of this thesis was to extend these previous assumptions by including more complex cases, which represent the real life practices in organizations,

The entire concept covered in this research is initially inspired by my personal reflections. The observations I have collected in the corporate world over 6 years determined the direction to this thesis. Particularly, the problems I experienced without clear answers in the scholarly literature encouraged me to take this journey.

Even though, the starting point of these studies is based on observations, I believe that I made the strongest effort to ground the foundations of all studies to be still solid, rigorous, academic and evidence-based. With a pragmatic approach, starting from a problem definition, the studies confirmed the gap in the literature. In addition to this, the underlying assumptions of virtuality are challenged through problematization of virtuality in this thesis. Sandberg and Alvesson (2011) contended that problematizations offer the opportunities to challenge existing theories. As Axel (1997) argued, critically grounded social practices and reflections enable new theories to be built, as reference points of the problems carry relevancies. Beyond gap spotting, implications and findings discussed also allow new research questions to be constructed to reflect further dimension related to task virtuality. Answering the research questions leads to new ones to arise.

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While I was able to find some of the answers which I initially triggered my curiosity, I have accumulated many new questions to study further.

On the other hand, this research posits virtuality in teams is not the only kind of virtuality that employees face in organizations. The findings in this study encompass two distinct research outcomes. First, this research proposes that task virtuality is an existent concept in organizations although it has not been detected before. Stemmed from team virtuality, task virtuality argues that it is a challenge by its own, since it concerns with the all contacts that are interacted virtually, not only with team members. Furthermore, it considers the impact of relative task interdependence of contacts working virtually. Second, it proves that the experienced virtuality at individual level is not a direct outcome of team virtuality. Our results argue that there is no unidirectional relationship between task virtuality and team virtuality.

In the light of findings, it would not be inaccurate to argue that it is time for organizational researchers and practitioners to move toward task virtuality to understand the broader impacts of virtuality at the individual level and address these challenges by analyzing unique situations of individuals in organizations. Technological advancements are evolving and keep penetrating into all areas of work that are used to be considered as traditional. Interactions between people turn out to be more electronic, since more and more people predominantly communicate using ICT-mediated tools in all sorts of organizations. This dominance of the technology in organizations potentially precipitate negative behavioral outcomes as workplace social relations, attachment and identification with jobs, satisfaction, meaningfulness and sense of achievement will be destructively impacted by automatization, mechanization and virtualization of works and work relations.

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REFERENCES

Axel, E. (1997). One developmental line in European activity theories. In M. Cole, Y. Engestrom, and O. Vasquez (Eds.), Mind, Culture, and Activity (pp. 128-146). Cambridge, UK: Cambridge University Press.

Beranek, P. M., & Martz, B. (2005). Making virtual teams more effective: improving relational links. Team Performance Management: An International Journal, 11(5/6), 200-213.

Curseu, P. L., Schalk, R., & Wessel, I. (2008). How do virtual teams process information? A literature review and implications for management. Journal of Managerial Psychology, 23(6), 628-652.

Elovainio, M., Kivimauki, M., Eccles, M., & Sinervo, T. (2002). Team climate and procedural justice as predictors of occupational strain. Journal of Applied Social Psychology, 32(2), 359-372.

Furst, S., Blackburn, R., & Rosen, B. (1999). Virtual team effectiveness: A proposed research agenda. Information Systems Journal, 9(4), 249-269.

Garrison, G., Wakefield, R. L., Harvey, M., & Kim, S. H. (2010). Exploring perceptions of ‘foreignness’ in virtual teams: Its impact on team member satisfaction and turnover intention. Asia Pacific Journal of Information Systems, 20(1), 101-125.

Hoch, J.E., & Kozlowski, S.W.J. (2014). Leading virtual teams: Hierarchical leadership, structural supports, and shared team leadership. Journal of Applied Psychology, 99(3), 390-403.

Hsu, M.H., Ju, T.L., Yen, C.H. & Chang, C.M. (2007). Knowledge sharing behavior in virtual communities: The relationship between trust, self-efficacy, and outcome expectations. International Journal of Human-Computer Studies, 65(2), 153-169.

Kristof, A. L. (1996). Person‐organization fit: an integrative review of its conceptualizations, measurement, and implications. Personnel Psychology, 49(1), 1-49.

Malhotra, A., Majchrzak, A., & Rosen, B. (2007). Leading virtual teams. The Academy of Management Perspectives, 21(1), 60-70.

Maznevski, M. L., & Athanassiou, N. A. (2003). Designing the knowledge-management infrastructure for virtual teams: Building and using social networks and social capital. In C. B. Gibson & S. G. Cohen (Eds.). Virtual Teams That Work: Creating Conditions for Virtual Team Effectiveness: (196-213). San Francisco: Jossey-Bass.

Maznevski, M. L., & Chudoba, K. (2000). Building space over time: Global virtual team dynamics and effectiveness. Organizational Science, 11(5), 473-492.

Montoya, M. M., Massey, A. P., Hung, Y. T. C., & Crisp, C. B. (2009). Can you hear me now? Communication in virtual product development teams. Journal of Product Innovation Management, 26(2), 139-155.

Rosen, B., Furst, S., & Blackburn, R. (2006). Training for virtual teams: An investigation of current practices and future needs. Human Resource Management, 45(2), 229-247.

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Sandberg, J., & Alvesson, M. (2011). Ways of constructing research questions: gap-spotting or problematization?. Organization, 18(1), 23-44.

Suh, A., Shin, K., Ahuja, M., & Kim, M. S. (2011). The influence of virtuality on social networks within and across work groups: A multilevel approach. Journal of Management Information Systems, 28(1), 351-386.

Warkentin, M., & Beranek, P. M. (1999). Training to improve virtual team communication. Information Systems Journal, 9(4), 271-289.

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SUMMARY

This book consists of four different studies. The purpose of the first study is to present a review of the scholarly literature on virtual teams and to redefine the key characteristics and features of ‘team virtuality’ and ‘virtual teams’. These characteristics of virtuality form the basis of task virtuality, a novel concept, coined with the second study in this book.

It is argued that with the penetration of new technologies into the workplace, virtuality has become an inseparable element of many kinds of jobs in today’s organizations. However, virtuality in organizations has usually been treated as a characteristic that is observed either at a team or organizational level, whereas the individual level impacts are often neglected.

The remaining two studies in this book highlight that the task virtuality concept cause several challenges and has significant effects on employees’ feelings and work related outcomes. The results presented in this book also reveal that task virtuality possesses a better predictive capacity than team virtuality when estimating workplace isolation, job satisfaction,

perceived performance and turnover intention.

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ABOUT THE AUTHOR

Before embarking on his doctoral research, Mehmet A. Orhan has worked as the financial planning and risk manager for Central and Eastern Europe at Electronic Arts in Prague. He started his career as a risk analyst at the European Downstream Treasury Center of Exxon Mobil Corporation after completing his undergraduate degree in economics and management at the University of London in association with the London School of Economics and Political Sciences. He holds an MBA from the Kellstadt Graduate School of Business of DePaul University in Chicago and an MSc in management from the Solvay Business School of the Vrije Universiteit Brussel in Belgium.

Currently, Mehmet teaches the work and organizational psychology class as a visiting lecturer in the Department of Psychology under the Faculty of Arts at the Charles University in Prague. He is a member of several professional associations including the Academy of Management, the International Association of Applied Psychology, the Society for Industrial & Organizational Psychology and the European Association of Work & Organizational Psychology.