volume xxviii number 1-2 spring/summer 2016web.pdf · mahmoud nourayi, loyola marymount ... jason...

Volume XXVIII Number 1-2 Spring/Summer 2016

The JMI in Brief

Article Abstracts ................................................................................................................. 5

Main Articles

The Value-Creating Role of Firm Capabilities: Mapping Relationships

Among Absorptive Capacity, Ordinary Capabilities, and Performance ......... 9 Joshua J. Daspit, Derrick E. D’Souza, and Lisa A. Dicke

The Impact of Positive Organizational Phenomena and Workplace

Bullying on Individual Outcomes .................................................................. 30 Pamela Lutgen-Sandvik, Jacqueline N. Hood, and Ryan P. Jacobson

Managerial Control in Mergers of Equals: The Role of Political Skill ................................................................................................... 50

Rich Devine, Bruce T. Lamont, and Reginald J. Harris Formal or Informal Mentoring: What Drives Employees to Seek

Informal Mentors? .......................................................................................... 67 Daniel T. Holt, Gergana Markova, Andrew J. Dhaenens, Laura E. Marler, and Sharon G. Heilmann

Cynicism Across Levels in the Organizations ................................................... 83

Matrecia S. L. James and John C. Shaw Acquiring Emotional Sea Legs: Navigating Joy and

Sadness in Ethical Decisions ............................................................................... 101 Sukumarakurup Krishnakumar and Maria Evglevskik

Journal of Managerial Issues Statement of Purpose The purpose of the Journal of Managerial Issues is to contribute to the advancement of business knowledge by publishing high-quality basic and applied research across the functional areas of business. Its primary goal is to disseminate the results of new and original scholarly activity to a broad audience consisting of university faculty, business executives, consultants, and government managers. The Journal also acts as a bridge between the academic and business communities. Subscriptions The Journal of Managerial Issues is published quarterly (spring, summer, fall, winter). Subscriptions are $95/year for individuals and $115/year for institutions. International subscriptions are $190/year. Please make check payable to “PSU/Journal of Managerial Issues” and send it to the address below, attention Ms. Irene Robinson. Manuscripts Manuscripts submitted for consideration are welcome. Send an e-mail file attachment to [email protected]. To help defray the administrative costs, a payment of $100 (for up to 25 pages, $30 for every page over 25 to cover extra production costs) will be due if your article is accepted for publication. This is not a submission fee. There is no charge if your paper is not accepted for publication in JMI. See Manuscript Style Guide (inside back cover) for additional requirements. Copyright Information Authorization to photocopy articles from this journal, free of charge, and without securing permission, as permitted by Sections 107-108 of the United States Copyright Law, is given by the Journal of Managerial Issues. Copies beyond that permitted by Sections 107-108 may be made provided the base fee per copy is paid to the Copyright Clearance Center, 222 Rosewood Dr., Danvers, MA 01923 (508-750-8400). For those organizations that have been granted a photocopy license by CCC, a separate system of payment has been arranged. This consent does not extend to copies made for general distribution, for advertising or promotional purposes, creation of new works, or resale. Send Correspondence to: Eric G. Harris, Editor-in-Chief Journal of Managerial Issues Pittsburg State University, 1701 S. Broadway, Pittsburg, KS 66762 E-mail: [email protected] E-mail submissions to [email protected] Phone: 620-235-4575; FAX: 620-235-4572 (http://www.journalofmanagerialissues.com) ISSN 1045-3695 Copyright @ 2016 by Pittsburg State University

Journal of Managerial Issues Volume XXVIII Number 1 - 2 Spring/Summer 2016

Editor-in-Chief: Eric G. Harris; Assistant Editor: Irene Robinson; Consulting Editors: Donald Baack, Stephen Horner,

Sang-Heui Lee, and Lynn M. Murray Founder and Editor-in-Chief -- 1989-2008: Charles C. Fischer

http://www.journalofmanagerialissues.com

Editorial Policy

The Journal of Managerial Issues seeks to publish the highest quality empirical, theoretical, and methodological papers in business research. The overriding criterion for publication of a manuscript in the JMI is the knowledge readers will gain about the theory of organizations and business practice. The JMI is intended to foster research from a variety of business school and related disciplines. As such, the JMI is open to and encourages a wide range of emerging methods, conceptual approaches, and substantive problem areas within the domain of business behavior.

Articles published are not necessarily the opinions of the JMI, the editors, or Pittsburg State University. Statements by authors appearing in the Journal are the exclusive responsibility of the authors themselves. Authors are allowed to express their opinions so as to encourage and stimulate a free flow of ideas.

Each paper submitted to the JMI is processed as follows: 1. Receipt of the manuscript is acknowledged promptly by a letter from the Editor.

An initial screening is made by the editors to determine the suitability of the article. Key factors considered are the quality of the research methodology, the ability to communicate to university faculty and business leaders, and, most important, the potential contribution to the advancement of knowledge directly related to the theory of organizations and business practice.

2. Assuming the manuscript is suitable for consideration by the JMI, it is assigned to two (or more) “external” referees, according to its functional and methodological content. Manuscripts are “double-blind” reviewed by referees selected by the Editor.

3. Each referee provides a careful evaluation of the manuscript, makes a recommendation to the Editor, and supplies comments for the author.

4. The Editor appraises the reviews and makes a decision regarding publication of the article. Every effort is made to obtain prompt reviews and make early decisions regarding publication or suggested revision of the manuscript.

Circulation includes university faculty and administrators, collegiate and public libraries, business executives, and government managers.

(1)

EDITORIAL REVIEW BOARD

Industry and Government Linda Boise, Legacy Health Systems

University Accounting Edward Douthett, Jr., George Mason

University Timothy J. Fogarty, Case Western Reserve

University Hubert D. Glover, Drexel University Robert Kee, University of Alabama Kenneth Lambert, University of Memphis Claire Latham, Washington State

University Mahmoud Nourayi, Loyola Marymount

University Eric Press, Temple University Walter A. Robbins, University of Alabama Finance Thomas H. Eyssell, University of Missouri-

St. Louis Stephen Ferris, University of Missouri-

Columbia George Gallinger, Arizona State University George G. Kaufman, Loyola University of

Chicago Suk Hun Lee, Loyola University of Chicago R. Charles Moyer, University of Louisville Edward D. Zychowicz, Hofstra University Management

Behavioral Donald Baack, Pittsburg State University Mark Bolino, University of Oklahoma Debra R. Comer, Hofstra University Jennifer M. George, Rice University J. David Johnson, University of Kentucky Scott Lester, University of Wisconsin – Eau

Claire Laura Marler, Mississippi State University Terence R. Mitchell, University of

Washington Tina L. Robbins, Clemson University

Bret L. Simmons, University of Nevada Howard L. Smith, Pacific University Kenneth R. Thompson, DePaul

University

International Myria Watkins Allen, University of

Arkansas Rajan Chandran, Temple University Meredith Downes, Illinois State University Lee A. Graf, Illinois State University Bruce T. Lamont, Florida State University Jenice Prather-Kinsey, University of

Alabama at Birmingham Kathleen Rehbein, Marquette University Malika Richards, Penn State University-

Berks

Legal and Social Environment Christine Fogliasso, Pittsburg State

University Robert L. Holbrook, Jr., Ohio University Tammy Hunt, UNC-Wilmington Fred A. Jacobs, Georiga State University Paula Rechner, Texas State University –

San Marcos S. S. Samuelson, Boston University Lee P. Stepina, Florida State University G. Stephen Taylor, Mississippi State

University Lori L. Wadsworth, Brigham Young

University

Human Resource Management Wendy R. Boswell, Texas A&M University Joseph Broschak, University of Arizona M. Ronald Buckley, University of

Oklahoma Nancy E. Day, Univ. of Missouri-Kansas

City Angelo S. DeNisi, Tulane University Helen I. Doerpinghaus, University of

South Carolina Gerald R. Ferris, Florida State University

(2)

Editorial Review Board(continued)

Dwight D. Frink, University of Mississippi Jeffrey H. Greenhaus, Drexel University Wayne A. Hochwarter, Florida State

University Nancy Johnson, University of Kentucky K. Michele Kacmar, Texas State University Brian Klaas, University of South Carolina Howard J. Klein, The Ohio State

University Douglas McCabe, Georgetown University Lawrence H. Peters, Texas Christian

University Kira Reed, Syracuse University Jason D. Shaw, Honk Kong Polytechnic Scott A. Snell, University of Virginia Patrick M. Wright, Cornell University

Production/Operations

Arnold Barnett, MIT Farzaneh Fazel, Illinois State University Lawrence Fredendall, Clemson University Hélène Giroux, HEC Montréal Nancy Lea Hyer, Vanderbilt University Manoj Malhotra, University of South

Carolina Joseph Martinich, University of Missouri -

St. Louis Marc Schniederjans, University of

Nebraska-Lincoln

Strategy and Policy Allen C. Amason, Georgia Southern

University Diana Bilimoria, Case Western Reserve

University Aaron Buchko, Bradley University Charles M. Byles, Virginia Commonwealth

University Derrick D’Souza, University of North

Texas David Noble, University of Connecticut John A. Pearce II, Villanova University

Terrence Sebora, University of Nebraska –

Lincoln Chamu Sundaramurthy, San Diego State

University Ellen Weisbord, Pace University Management Information Systems John R. Carlson, Baylor University J. N. D. Gupta, University of Alabama-

Huntsville Anita Lee-Post, University of Kentucky-

Lexington David Paper, Utah State University Marion G. Sobol, Southern Methodist

University Mohan Tanniru, Southern Methodist

University Michael P. Thompson, Brigham Young

University Marketing Gerald Albaum, The University of New

Mexico Rolph E. Anderson, Drexel University J. Scott Armstrong, University of

Pennsylvania Rosemary J. Avery, Cornell University James S. Boles, Georgia State University Isabella Cunningham, University of Texas

at Austin C. Anthony di Benedetto, Temple

University Jule B. Gassenheimer, Rollins College Mark Johlke, Bradley University Keun S. Lee, Hofstra University James H. Martin, John Carroll University Ajay Menon, Colorado State University Paul Murphy, John Carroll University John Sherry Jr., University of Notre Dame David Stewart, Loyola Marymount

University R. Dale Wilson, Michigan State University

(3)

CCongratulations

to our founder and friend

DDr. Charles C. Fischer

on your Retirement from

Pittsburg State University

JMI Founder and Editor-in-Chief

(1989-2008)

(4)

108

132

The JMI in Brief

Volume XXVIII Number 1 - 2 Spring/Summer 2016

MAIN ARTICLES The Value-Creating Role of Firm Capabilities: Mapping Relationships among Absorptive Capacity, Ordinary Capabilities, and Performance ...................... 9

Joshua J. Daspit, Derrick E. D’Souza, and Lisa A. Dicke Various capabilities exist within the firm, yet how capabilities are configured to deliver firm value remains to be fully understood. To this end, the relationship between firm-level absorptive capacity, one type of dynamic capability, and ordinary capabilities is examined. Absorptive capacity is hypothesized to create value by exploiting knowledge via ordinary capabilities. Using a sample of firms in the software industry, a positive relationship is found between absorptive capacity and ordinary capabilities. Further, absorptive capacity is found to be positively related to three types of ordinary capabilities: customer, alignment, and operational capabilities. The findings extend current understanding of how capabilities are configured and how knowledge is leveraged to create firm value.

The Impact of Positive Organizational Phenomena and Workplace Bullying on Individual Outcomes ...................................................................... 30

Pamela Lutgen-Sandvik, Jacqueline N. Hood, and Ryan P. Jacobson

Positive organizational environments are increasingly being studied as important for positive organizational and individual outcomes. However, focusing exclusively on the positive aspects of an environment may mask the impact of negative behaviors, such as workplace bullying, on these same outcomes. The current study has two central goals. The first is to explore the expected positive effects of positive interpersonal work experiences and perceived organizational virtuousness on three vital outcomes: the intent to leave jobs, mental health quality, and stress levels related to work. The second goal involves going beyond simply looking at positive phenomena to also examining how the presence of workplace bullying may moderate (reducing) the expected beneficial effects of positive organizational variables on these outcomes. Results indicate that, as expected, higher levels of positive individual treatment were associated with lower stress levels, lower turnover intentions, and higher levels of self-reported mental health. Higher levels of organizational virtuousness were associated with lower turnover intentions, but this variable did not predict stress levels or mental health. As expected, the prevalence of workplace bullying behavior was found to be positively related to turnover intentions and to higher stress, and negatively related to mental health. Furthermore, the results indicate that workplace bullying moderates the relationship between the positive organizational factors and

(5)

the three outcome variables. When bullying levels were low, these positive organizational factors tended to have beneficial effects on the workplace outcomes examined in this study. However, these beneficial effects tended to decrease as levels of bullying in the organization increased.

Managerial Control in Mergers of Equals: The Role of Political Skill ....................................................................................................50

Rich Devine, Bruce T. Lamont, and Reginald J. Harris

The present research contributes to the existing literature on top management teams (TMTs) and mergers and acquisitions (M&A) by applying power and status theory to theoretically delineate how chief executive officer (CEO) power and political skill determine which firm will emerge the controlling partner in mergers of equals transactions. The study posits that the more powerful and politically skilled CEOs will emerge as the controlling managers. The results generally support study predictions on political skill, though the less powerful CEOs are more likely to emerge as the leader of the new firm. Both the expected and surprising results are discussed in the context of future research on mergers of equals (MOE) events.

Formal or Informal Mentoring: What Drives Employees to Seek Informal Mentors? ...........................................................................................67

Daniel T. Holt, Gergana Markova, Andrew J. Dhaenens, Laura E. Marler, and Sharon G. Heilmann

In organizations with formal mentoring programs, employees may still seek out informal mentors outside of their assigned mentors. This study examines factors that drive protégés to turn from their formal mentors to supplementary informal mentors. Using data from three sources, protégés relying on formal mentors versus informal mentors were compared, finding that leader-member exchange (LMX), perceived similarity, contact time, and the status of the formal mentor were significantly related to the protégé’s decision to select an informal mentor. There was no evidence that protégé performance affected a protégé’s decision to identify an informal mentor. Implications for practice and future research are also discussed.

Cynicism Across Levels in the Organization .........................................................84

Matrecia S. L. James and John C. Shaw

The current study examines the interactive relationship of politics perceptions and psychological contract violation on cynicism targeted at individuals in three hierarchical levels of an organization. Cynicism is characterized as a negative work attitude that develops as a result of perceived

3

(6)

192malfeasance of the agent or entity. Such a negative attitude can be directed at the organization as a whole and/or the individuals in the organization. Using a sample of 360 employees drawn from a southern school district, politics perceptions was positively related to cynicism towards upper-level management, immediate supervisors, and co-workers. Results also showed interactive effects of politics perceptions and psychological contract violation on cynicism only directed towards upper-level management. Specifically, for those perceiving higher levels of psychological contract violations, politics perceptions was associated with higher cynicism scores only directed towards upper-level management. Implications of these findings, strengths and limitations, and practical implications are provided.

Acquiring Emotional Sea Legs: Navigating Joy and Sadness in Ethical Decisions ........................................................................... 102

Sukumarakurup Krishnakumar and Maria Evglevskik

When positive and negative emotions such as joy and sadness are elicited during an ethical decision-making process (EDM), individuals use their emotion regulation ability (ERA) to better manage these emotions, and by doing so, make better ethical decisions. In this experimental study, effects of incidental joy, elicited from the context, and integral sadness, elicited from the ethical dilemma, are investigated with respect to the ability with which individuals manage such emotions. Results show that when the ethical scenario elicited less integral sadness, the effect of joy on ethical decision-making was influenced by the emotion regulation ability of the decision-makers. In high-ERA decision-makers, joy lead to better ethical decisions, whereas in low-ERA decision-makers, joy lead to poorer ethical decision-making. This moderating effect of ERA on joy was not seen in ethical scenarios with intense integral sadness. These results show that when the intensity of integral sadness is high, the role of ERA can be limited. Limitations and implications of the findings are also discussed.

1

(7)

JOURNAL OF MANAGERIAL ISSUES Vol. XXVIII Number 1 - 2 Spring/Summer 2016: 9-29

JOURNAL OF MANAGERIAL ISSUES Vol. XXVIII Number 1-2 Spring/Summer 2016

The Value-Creating Role of Firm Capabilities: Mapping

Relationships among Absorptive Capacity, Ordinary Capabilities, and Performance1

Joshua J. Daspit Assistant Professor of Management

Mississippi State University [email protected]

Derrick E. D’Souza Professor of Management

University of North Texas Derrick.D’[email protected]

Lisa A. Dicke

Professor, Department of Public Administration University of North Texas

[email protected]

Research related to capabilities in general, and dynamic capabilities in particular, is one of the most active areas of scholarship in management and has much promise as an area of study (Di Stefano et al., 2014; Helfat and Winter, 2011). Capabilities are developed from deeply embedded routines within the firm and have been singled out as the primary functions crucial for firm survival (Prahalad, 1993; Winter, 2000). The majority of research in this area focuses on two important classes of capabilities: dynamic capabilities and ordinary capabilities (Teece, 2014). Each type of capability is noted for

1 Acknowledgements: The authors wish to thank Divesh Ojha, Michael Breazeale, and Robert Moore for their insightful comments and suggestions on earlier versions of this manuscript. Additionally, Xueni (Judy) Dong is appreciated for research assistance. Editor Eric Harris and Assistant Editor Irene Robinson are thanked for their support during the review process, and the feedback received from two anonymous reviewers is also appreciated. Portions of this research were funded by the Department of Management at the University of North Texas College of Business.

(9)

VALUE-CREATING ROLE OF FIRM CAPABILITIES


its value-creating benefits; however, limited investigations examine how these classes of capabilities work together to create firm value and deliver performance returns.

To understand how capabilities are configured within the firm, the relationship between one type of firm-level dynamic capability, absorptive capacity, and ordinary capabilities is examined. Absorptive capacity (ACAP) is the capability of the firm to acquire, assimilate, transform, and exploit new knowledge toward commercial ends (Cohen and Levinthal, 1990; Zahra and George, 2002). Firms with refined knowledge management capabilities, such as ACAP, are better equipped to obtain and extract value from external knowledge resources (Argote, 1999), adapt to change, and enhance their competitive advantage. ACAP is noted to influence firm performance (Cohen and Levinthal, 1990; Todorova and Durisin, 2007; Zahra and George, 2002), as well as other firm outcomes including innovation (Huang et al., 2015; Leal-Rodríguez et al., 2014), corporate entrepreneurship (García-Morales et al., 2014), market responsiveness (Chang et al., 2013), new products (George et al., 2001), product development (Stock et al., 2001), and financial outcomes (George et al., 2001). The nature of these findings suggests that ACAP is essential in creating firm value and altering firm outcomes, although, the means through which this value creation occurs remains less clear.

For the firm to successfully compete in a dynamic marketplace, the capability to understand the marketplace is necessary to ensure the firm remains in congruence with the environment. ACAP is a dynamic capability that enables the firm to obtain new, external knowledge, yet once the knowledge exists within the firm, internal capabilities are required to exploit the knowledge and create value. Without internal mechanisms (capabilities) to leverage new knowledge, the value of obtaining new insights is marginalized. Therefore, this study hypothesizes that knowledge entering the firm via ACAP is exploited via internal ordinary capabilities, and through ordinary capabilities, firm value is created and performance affected.

After hypothesizing a broad relationship between ACAP and ordinary capabilities, a finer-grained perspective is used to more closely examine the relationship between ACAP and three types of ordinary capabilities (i.e., customer, alignment, and operational). An analysis of data from a sample of firms in the software industry suggests that ordinary capabilities serve an intermediary role in the ACAP-performance relationship, and ACAP has a positive relationship with each type of ordinary capability (i.e., customer, alignment, and operational capabilities). Thus, results suggest that firms exploit new knowledge via ordinary capabilities.

The findings of this investigation offer several contributions to the existing research on firm capabilities. First, insights extend prior findings that ACAP is directly related to firm performance by demonstrating that value is created via ordinary capabilities. Second, this investigation offers new insight into the manner in which ACAP relates to ordinary capabilities by finding that ACAP has a positive relationship with each type of ordinary capability. Third, although several studies have examined various classes of capabilities, few studies simultaneously investigate how multiple classes of capabilities (i.e., dynamic and ordinary) are configured in relation to firm performance. Overall, the findings offer a more comprehensive understanding of capability value-creation, noting how firm-level capabilities work together to influence performance.

10

DASPIT, D’SOUZA, AND DICKE


THEORETICAL FRAMEWORK AND HYPOTHESES

Capability-Based Perspective

A capability is a high-level routine, or collection of routines, that offers managers the ability to create commercial output (Winter, 2000). Capability-based research evolved from the resource-based perspective and acknowledges the need for firm resources to remain flexible given the ever-changing environment (Schreyögg and Kliesch-Eberl, 2007). That is, capability research seeks to understand how firms dynamically configure their resources for competitive advantage. Firm competitive advantage is primarily obtained via two classes of capabilities: dynamic capabilities and ordinary capabilities (Teece, 2014).

Ordinary capabilities exist to generate value that the firm delivers to its customers (Winter, 2003), thus representing the “value-creating engine” of the firm. Taking a latent action perspective (Di Stefano et al., 2014), researchers have argued that dynamic capabilities may be viewed as capabilities that allow the firm to shape and integrate ordinary capabilities, such that the firm’s value-creating engine is constantly aligned with the dynamics of the competitive environment (Teece et al., 1997; Winter, 2000). Teece notes that dynamic capabilities, “. . . enable an enterprise to profitably build and renew resources and assets that lie both within and beyond its boundaries, reconfiguring them as needed to innovate and respond to (or bring) changes in the market and in the business environment more generally” (2014: 332). Given its capability to integrate, build, and reconfigure ordinary capabilities in response to environmental changes, ACAP has been deemed to be one such dynamic capability through which competitive advantage is obtained (Zahra and George, 2002).

Absorptive Capacity (ACAP)

Firms seek and use new knowledge to meet the changing demands of a dynamic environment. ACAP is the capability of the firm to acquire, assimilate, transform, and exploit new knowledge for commercial purposes (Cohen and Levinthal, 1990; Zahra and George, 2002). The acquisition component of ACAP acknowledges the firm’s ability to actively scan the environment and obtain new, potentially valuable, knowledge (Liao et al., 2003). Once the knowledge is acquired, the firm assimilates (synthesizes and understands) the new knowledge (Zahra and George, 2002). The knowledge is then transformed and stored for future use, and the knowledge is ultimately exploited.

The components of ACAP collectively create value and are related to performance outcomes (Daspit and D’Souza, 2013); yet, the means through which new knowledge is exploited by the firm to achieve desired performance remains to be understood. Zahra and George (2002) hypothesize that exploitation should logically be embedded in routines that allow the firm to leverage existing capabilities. Hence, exploitation is suggested to represent the firm’s ability to incorporate knowledge into its internal operations. Flatten et al. (2011) posit that exploitation refers to the firm’s ability to improve and expand existing competencies and routines. In all, researchers generally acknowledge exploitation as a viable and necessary component of ACAP, yet a comprehensive explanation of how the exploitation of knowledge occurs is largely absent.

11



To this end, the current conceptualization of ACAP is extended to suggest that once knowledge is acquired, assimilated, and transformed, the exploitation of the knowledge occurs via a different class of capability. ACAP, a dynamic capability, is suggested to exploit new knowledge via the ordinary capabilities of the firm. This is in line with prior research (e.g., Flatten et al., 2011) suggesting that the exploitation of new knowledge is leveraged through changes made to the existing internal operations and systems associated with the ordinary capabilities of the firm.

The Exploitation Role of Ordinary Capabilities

The broad relationship between dynamic capabilities and ordinary capabilities is acknowledged in the strategic management literature (Di Stefano et al., 2014; Teece, 2014). Pavlou and El Sawy (2011) show that dynamic capabilities influence operational capabilities in the context of new product development, and Zahra et al. (2006) offer conceptual arguments to support the relationship between dynamic capabilities, ordinary capabilities, and firm performance. Zott (2003) uses dynamic modeling techniques to demonstrate how the cost and use of dynamic capabilities influence performance via operational routines (i.e., via ordinary capabilities). Broadly, research suggests an interconnectedness among dynamic capabilities, ordinary capabilities, and firm performance.

Given that ACAP is a type of dynamic capability, a similar interconnectedness is hypothesized to exist between ACAP, ordinary capabilities, and firm performance. Several scholarly studies offer evidence of statistically significant relationships between ACAP and firm performance (e.g., Liao et al., 2007; Schreyögg and Kliesch-Eberl, 2007; Fosfuri and Tribó, 2008; Volberda et al., 2010; Lewin et al., 2011). However, only a few investigations attempt to understand the means through which ACAP leverages knowledge for the benefit of the firm (see Tu et al., 2006). Kostopoulos et al. (2011) find that ACAP is not directly related to a firm’s financial performance, but rather, that the firm’s innovation capability mediates this relationship. These studies suggest a value-creating role for ordinary capabilities.

ACAP is responsible for enabling the firm to obtain new, external knowledge regarding market changes. However, simply having exposure to valuable external knowledge is not sufficient to ensure a competitive advantage; the firm must have internal capabilities that enable the synthesis and application of the knowledge to create value (Jansen et al., 2005). ACAP is a dynamic capability of the firm (Zahra and George, 2002), and Teece acknowledges that dynamic capabilities are “higher-level activities that can enable an enterprise to direct its ordinary activities toward high-payoff endeavors.” (2014: 328) Thus, as new knowledge is obtained via the “higher-level activities” associated with absorptive capacity, the knowledge must then be leveraged via “ordinary activities” to leverage the benefit.

In summary, prior literature acknowledges a relationship between ACAP and firm performance. However, once new knowledge enters the firm, it does not directly alter firm performance. The new knowledge must first be leveraged into value-enhancing products and services, and it is through such exploitation of the new knowledge that firm performance is altered. Here, ordinary capabilities are posited to act as a

12



transducer2 that allows the firm to leverage the new knowledge that has been acquired, assimilated, and transformed by the firm’s ACAP, thereby enabling the creation of products and services valued by the customer and influencing firm performance. Insights from capability literature are extended to suggest that new knowledge obtained via ACAP creates value through relationships with ordinary capabilities in the firm. Therefore, ordinary capabilities are hypothesized to have a mediating role in the relationship between ACAP and firm performance.

Hypothesis 1: Ordinary capabilities mediate the relationship between ACAP and

firm performance.

Relationships between ACAP and Types of Ordinary Capabilities

Now that a broad relationship among ACAP, ordinary capabilities, and performance is established, a more detailed perspective is taken to understand the relationships between ACAP and each type of ordinary capability. Winter (2003) refers to ordinary capabilities as the capabilities governing “how we earn a living now” in the firm (Winter, 2003: 992) giving such capabilities a central role in the basic functions of the firm. To conceptualize the various types of ordinary capabilities within the firm, a review of capability literature was conducted,3 and three general types of ordinary capabilities are acknowledged to exist: customer, alignment, and operational. These three types of ordinary capabilities are not specific to a functional area in the firm; rather, each exists at the firm-level and spans across functional areas. The hypothesized relationships between ACAP and each type of ordinary capability are developed below.

ACAP and customer capability. The customer capability represents the firm’s ability to build customer relationships to (a) obtain knowledge from the firm’s stakeholders and become aware of both current and future demand patterns (Treacy and Wiersema, 1993) and (b) respond in a timely manner to the customer, thereby realizing market demands (Hall, 1992, 1993; Kaplan and Norton, 2006; Roberts and Grover, 2012). Prior studies suggest a positive relationship between ACAP and the customer capability may exist. Welsch et al. (2001), for example, find that knowledge acquisition—one component of ACAP—is positively related to the firm’s responsiveness and ability to adapt to changing consumer demands. Further, in an investigation of Taiwanese financial service

2 “Transducer” is a commonly used term in the scientific literature. It is derived from “transduction,” which represents the process of converting one form of energy to another. Thus, in genetics, a virus can be viewed as the transducer that transfers DNA from one bacterium to another. In electro-mechanical systems, a motor represents a transducer that converts electrical energy from a source into mechanical energy (torque) at the point of use. It is important to note that in both cases transduction does not require physical contact between the source and the user. In the case of the current study, ordinary capabilities act as the transducer that converts the new knowledge into customer value that is ultimately reflected in the firm’s performance. 3 To conduct the review of ordinary capabilities, a literature search was conducted to identify published capability frameworks from journals including: Academy of Management Journal; Academy of Management Perspectives; Academy of Management Review; Administrative Science Quarterly; Entrepreneurship, Theory & Practice; Family Business Review; International Journal of Management Reviews; Journal of Business Venturing; Journal of Engineering and Technology Management; Journal of Management; Journal of Management Studies; Long Range Planning; Research Policy; Strategic Entrepreneurship Journal; Strategic Management Journal; and Technovation.

13



companies, Chen and Ching (2004) find that the ACAP of a firm influences customer relationship management practices.

Prior insights are extended to suggest that knowledge acquired, assimilated, and transformed via the firm’s ACAP affects the customer capability. ACAP influences the market responsiveness of the firm (Chang et al., 2013), which is an outcome affected by the customer capability. As new knowledge is obtained and understood, insights may be leveraged to enhance the firm’s ability to respond to customers in an effective and expedited manner. Thus, given that knowledge acquired and utilized by a firm likely enhances the ability of the firm to anticipate and respond to customer needs, ACAP positively relates to the customer capability of the firm.

Hypothesis 2: ACAP is positively related to the customer capability.

ACAP and alignment capability. The alignment capability allows the firm to

mobilize and combine knowledge (Lenz, 1980) to make continuous product and/or process improvements ( akar and Ertürk, 2010) that align the value creating engine with market needs. This capability offers the firm a logical, incremental pathway (Duncan, 1972) to align knowledge from existing customer or operational capabilities.

Weeks and Thomason (2011) examine the relationship between ACAP and firm improvement, and the authors demonstrate how the relationship improves by altering the configuration of human capital dedicated to ACAP. Measures of R&D are occasionally used as a proxy for ACAP (e.g., Lane and Lubatkin, 1998), and Li (2011) finds that investment in R&D is positively related to incremental innovative change. Prior studies support the existence of a relationship between ACAP and product/process adjustments (e.g., Liao et al., 2007). When firm-level change is necessary, the extent to which a firm acquires and leverages external knowledge likely enhances the capability of the firm to make incremental improvements and enhance capability alignment. Thus, the external knowledge acquisition and integration capabilities that create the firm’s ACAP are exploited to alter the incremental changes specific to the alignment capability of the firm.

Hypothesis 3: ACAP is positively related to the alignment capability.

ACAP and operational capability. The operational capability is the firm’s ability to

allocate resources and share common processes in a cooperative manner (Kaplan and Norton, 2006; Crossan et al., 2009). This collection of routines allows a firm to respond to market demands by implementing customized practices that result in desired products or services. The operational capability is commonly embedded in value-creation activities associated with manufacturing, service, purchasing, sales, distribution, and similar activities.

Levinthal and March (1993) highlight the relationship between knowledge exploitation and firm efficiency, noting that through the use of new knowledge acquired, the firm can refine internal value-creating processes. Thus, the authors conceptually link ACAP with the operational capabilities of the firm. At a higher level of abstraction, Cepeda and Vera (2007) find support for the influence of dynamic capabilities on operational capabilities among information technology and communication industries in Spain. Furthermore, Tanriverdi (2005) examines new knowledge acquisition

14



capabilities and suggests that such capabilities influence cross-unit synergies, a component of the firm’s operational capability. Overall, operational efficiency is enhanced through the utilization of the firm’s ACAP (Malhotra et al., 2005), which suggests a positive relationship between ACAP and the operational capability.

Hypothesis 4: ACAP is positively related to the operational capability.

METHOD

Data Collection and Sample

Prior to the data collection for the main study, a panel of experts reviewed items in the survey instrument to ensure their applicability to both product and service-oriented firms. A key informant approach, in which top managers were identified, was used to collect data (Kumar et al., 1993), and data collection began with a pilot study. In the pilot study, the research team tested the updated instrument with a sample of top executives from firms in the software industry. After reviewing their responses, the research team made minor refinements to the survey instrument to ensure contextual appropriateness.

The research team obtained firm names and contact details from a dataset acquired from a leading industry database provider and collected data for the study using an Internet-based survey administered to top-level managers of firms in the software industry. The research design was crafted using Dillman’s (1978, 2007) total design method for survey methodologies. All firm leaders were contacted via email, and following the deletion of undeliverable addresses and unsubscribe requests, a total of 3,926 unique firms were included in the survey. In all, 322 responses were received, yielding a response rate of 8.20%. Of the responses received, 151 responses were usable for the analysis. Nearly half of the firms (44.60%) reported to be fewer than ten years old with the average firm having 106.57 employees. Of respondents that reported their position, the majority were top managers or chief executives (90.0%) with others more closely identifying with other positions of leadership (e.g., chairman, founder). Approximately 72% of respondents had at least five years of professional experience in their current firm. Common Method and Non-Response Biases

Prior to survey administration, proactive measures were included in the survey design to act as procedural controls of common method bias (Podsakoff et al., 2003). Additionally, the questionnaire included a marker variable to further minimize the presence of common method bias (Lindell and Whitney, 2001). Results of Harman’s single factor test suggested that common method bias was not likely to confound the interpretation of results.

To examine non-response bias, early and late respondents were compared (Armstrong and Overton, 1977). Specifically, data from the earliest and latest 25 percent of respondents were examined for reported differences in performance, levels of ordinary capabilities, and levels of ACAP. No significant difference was found between respondents for any assessed value.

15



Measures

All measures were assessed using previously validated scales adapted to fit the context of this study. ACAP was measured using a scale developed by Jansen et al. (2005) and included assessments of the acquisition, assimilation, and transformation dimensions. Customer capabilities were measured using a scale adapted from Jayachandran et al. (2004), and alignment capabilities were measured using Liao et al.’s (2007) scale. For operational capabilities, a scale developed by Wu et al. (2010) was used. See Table 1 for an overview of constructs, dimensions, definitions, and sample items.

Because the sampled firms are primarily privately held entities, relative measures of performance were used (e.g., García-Morales et al., 2014). This approach minimizes the hesitation of managers and reduces the likelihood of inaccurate data. Managers were asked to rate the net profit (as a percentage of sales) and the overall performance of the firm compared to other firms in the industry. As with other items in the questionnaire, responses to these items were provided on a Likert scale ranging from 1 (strongly disagree/worse than other firms) to 5 (strongly agree/much better than other firms).

Control Variables

To minimize the variance experienced by external factors, control variables were included. First, the size of a firm relates to how the firm utilizes knowledge and engages in innovation. Specifically, smaller firms are generally more innovative than larger firms (Nootebloom et al., 2007). Hence, firm size was measured as the number of employees in the firm for the most recent year end.

Second, research suggests that established firms—firms with more time to develop and refine capabilities—have an advantage over younger firms that are in the process of developing and refining capabilities related to knowledge processing and innovation (Nootebloom et al., 2007). Therefore, a control variable was included to account for the firm’s age. Third, a measure of industry change was included to account for the variation of perceived environmental dynamism across firms (Li and Liu, 2014). Even though all firms sampled are from the software industry, firms may perceive the dynamism within the industry differently, and thus respond in accordance with their perception. To control for industry dynamism, respondents were asked to report the extent to which they perceived the technology in the industry was changing.

16



Tab

le 1

C

onst

ruct

s, D

efin

itio

ns, a

nd S

ampl

e It

ems

Con

stru

ct

(wit

h de

fini

tion

)D

imen

sion

(w

ith

defi

niti

on a

nd r

elia

bili

ty)

Sam

ple

Item

Abs

orpt

ive

Cap

acit

y A

dyn

amic

cap

abili

ty

that

ena

bles

the

firm

to

acqu

ire,

ass

imila

te,

tran

sfor

m, a

nd e

xplo

it

new

kno

wle

dge

for

com

mer

cial

pur

pose

s (C

ohen

and

Lev

inth

al,

1990

; Zah

ra a

nd G

eorg

e,

2002

)

Acq

uisi

tion

: The

firm

’s c

apab

ility

to id

entif

y an

d ac

quir

e ex

tern

al k

now

ledg

e (Z

ahra

and

Geo

rge,

200

2)

( =

0.7

7)

Our

firm

has

freq

uent

inte

ract

ions

wit

h ot

her

firm

s to

acq

uire

new

kno

wle

dge

(Jan

sen

et a

l.,

2005

)

Ass

imil

atio

n: T

he fi

rm’s

cap

abili

ty to

ana

lyze

, pro

cess

, in

terp

ret,

and

unde

rsta

nd e

xter

nal k

now

ledg

e (Z

ahra

an

d G

eorg

e, 2

002)

( =

0.8

1)

We

are

quic

k to

rec

ogni

ze s

hift

s in

our

mar

ket

(e.g

., co

mpe

titi

on, r

egul

atio

n, d

emog

raph

y)

(Jan

sen

et a

l., 2

005)

Tra

nsfo

rmat

ion:

The

firm

’s c

apab

ility

to c

ombi

ne

exis

ting

kno

wle

dge

with

new

ly a

cqui

red

and

assi

mila

ted

know

ledg

e (Z

ahra

and

Geo

rge,

200

2) (

= 0

.72)

Our

em

ploy

ees

reco

rd a

nd s

tore

new

ly

acqu

ired

kno

wle

dge

for

futu

re r

efer

ence

(J

anse

n et

al.,

200

5)

Ord

inar

y C

apab

ilit

y L

ower

-ord

er c

apab

ilitie

s th

at e

nabl

e th

e pe

rfor

man

ce o

f bas

ic

firm

func

tion

s ne

cess

ary

to a

ccom

plis

h co

re fi

rm

task

s (T

eece

, 201

4)

Cus

tom

er C

apab

ilit

y: T

he fi

rm’s

cap

abili

ty to

sat

isfy

cu

stom

er n

eeds

thro

ugh

effe

ctiv

e an

d qu

ick

resp

onse

s (J

ayac

hand

ran

et a

l., 2

004)

( =

0.7

7)

Whe

n w

e fin

d th

at c

usto

mer

s w

ould

like

us

to

mod

ify

a pr

oduc

t/ser

vice

, the

dep

artm

ents

in

volv

ed m

ake

conc

erte

d ef

fort

s to

do

so

(Jay

acha

ndra

n et

al.,

200

4)

Ali

gnm

ent C

apab

ilit

y: T

he fi

rm’s

cap

abili

ty to

alig

n pr

oced

ures

to a

chie

ve p

rodu

ct a

nd/o

r pr

oces

s im

prov

emen

ts (

akar

and

Ert

ürk,

201

0; L

iao

et a

l.,

2007

) ( =

0.8

3)

We

ofte

n tr

y di

ffer

ent p

roce

dure

s to

spe

ed u

p th

e re

aliz

atio

n of

the

firm

’s g

oals

(Lia

o et

al.,

20

07)

Ope

rati

onal

Cap

abil

ity:

The

firm

’s c

apab

ility

to

conf

igur

e op

erat

iona

l res

ourc

es b

y im

plem

entin

g cu

stom

ized

and

sha

red

prac

tices

(Kap

lan

and

Nor

ton,

20

06; W

u et

al.,

201

0) (

= 0

.85)

Our

ope

ratio

ns p

roce

ss h

as b

een

mod

ified

to

gain

uni

que

posi

tions

in th

e m

arke

t (W

u et

al.,

20

10)

17



RESULTS

Measurement Models

Analyses were conducted using AMOS Version 21 and SPSS Version 22. Table 2 presents the means, standard deviations, intercorrelations, and coefficient alpha reliabilities for the study. A confirmatory analysis was conducted first to examine the higher-order constructs associated with Hypothesis 1. Namely, customer capability, alignment capability, and operational capability were modeled using a single latent factor of ordinary capability, and the latent factors of ACAP, ordinary capability, and performance were allowed to correlate. The higher-order model indicated proper fit ( 2 [38, n = 151] = 59.98, p < 0.05; CFI = 0.96; RMSEA = 0.06; SRMR = 0.05), and all factor estimates were significant and greater than 0.50, with the exception of the acquisition factor, which was significant but loaded slightly below the recommended level (standardized estimate = 0.47).

A second measurement model was examined to assess the model fit for subsequent hypotheses (H2-H4). The second model included the latent variables of ACAP, customer capability, alignment capability, operational capability, and performance. The analysis indicated that this five-factor model fit the data well ( 2 [34, n = 151] = 57.98, p < 0.01; CFI = 0.96; RMSEA = 0.07; SRMR = 0.04). Similar to the previous model, all items significantly loaded onto their respective factors, with the exception of the acquisition factor (standardized estimate = 0.47). Table 3 details the factor loadings, construct reliabilities, and average variances extracted for each construct.

Structural Models

Hypothesis 1 suggests ordinary capabilities mediate the relationship between absorptive capacity and firm performance. Thus, to examine the paths and structure of the higher-order relationships, a three-factor model, which included ACAP, a latent construct of ordinary capabilities, and performance, was used. To test for mediation, Baron and Kenny’s (1986) three conditions for examining mediation were used with Brown’s (1997) recommendations for testing mediation in a structural model. First, absorptive capacity was significantly related to the mediator of ordinary capabilities (p < 0.001; = 0.91). Second, the mediator of ordinary capabilities was significantly related to firm performance (p < 0.001; = 0.71). Last, the previously significant relationship between absorptive capacity and performance was no longer significant (p = 0.72; = -0.11) when the additional relationships were added. The final structural mediation model is presented in Figure 1 and has an appropriate fit ( 2 [99, n = 151] = 128.90, p < 0.05; CFI = 0.96; RMSEA = 0.05; SRMR = 0.05), thereby supporting Hypothesis 1.

18



Tab

le 2

D

escr

ipti

ve S

tati

stic

s an

d C

orre

lati

on M

atri

x

Con

stru

ct

M

SD

1 2

3 4

5 6

7 8

1. A

bsor

ptiv

e ca

paci

ty

3.67

0.

54

0.84

a

2. O

pera

tion

al

capa

bilit

y 3.

76

0.61

0.

53**

0.

85a

3. A

lignm

ent

capa

bilit

y 3.

61

0.56

0.

60**

0.

59**

0.

83a

4. C

usto

mer

ca

pabi

lity

4.04

0.

49

0.39

**

0.53

**

0.51

**

0.77

a

5. P

erfo

rman

ce

3.39

0.

74

0.42

**

0.48

**

0.43

**

0.42

**

0.70

a

6. F

irm

age

b 2.

69

1.10

-0

.05

0.02

-0

.06

-0.0

9 -0

.01

7. N

umbe

r of

em

ploy

ees

106.

57

335.

01

-0.0

1 -0

.10

0.04

0.

01

0.04

0.

07

8. I

ndus

try

perc

epti

on

4.28

0.

72

0.19

* 0.

08

0.13

0.

14

0.18

* 0.

14

-0.0

4

9. M

arke

r 2.

36

0.79

-0

.23*

* -0

.17*

-0

.15

-0.0

9 -0

.13

0.01

-0

.08

-0.0

2

Not

e: a

Cro

nbac

h’s c

orre

latio

nal c

oeffi

cien

t; b F

irm

age

was

mea

sure

d us

ing

clus

tere

d ag

e gr

oups

; **

= p

< 0

.01;

* =

p <

0.0

5

19



Table 3 Factor Loadings, Construct Reliabilities, and Average Variances Extracted

Absorptive Capacity

Customer Capability

Alignment Capability

Operational Capability

Performance

Acquisition 0.47

Assimilation 0.79

Transformation 0.75

Response Speed 0.85 Response

Expertise 0.69

Product Alignment 0.78

Process Alignment

0.76

Cooperation 0.68

Customization 0.80

Net Profit 0.68 Generalized

Performance 0.79

CRa 0.72 0.75 0.75 0.70 0.70 AVEb 0.47 0.60 0.60 0.55 0.54

Note: a Construct reliability (CR); b Average variance extracted (AVE)

Given the mediating role of ordinary capabilities, further analyses were conducted to assess the relationship between ACAP and each type of ordinary capability. To assess these relationships, a five-factor model was examined, which included ACAP, customer capability, alignment capability, operational capability, and firm performance. The fit indices suggest the structural model fit is appropriate ( 2 [90, n = 151] = 124.54, p < 0.01; CFI = 0.96; RMSEA = 0.05; SRMR = 0.05). Hypothesis 2 states that ACAP positively relates to customer capability, and results suggest this relationship is positive and significant ( = 0.76; p < 0.001). The relationship between ACAP and alignment capability is positive and significant ( = 0.97; p < 0.001), thereby supporting Hypothesis 3. Last, Hypothesis 4 is supported, which suggests that ACAP positively relates to operational capability ( = 0.95; p < 0.001).

Furthermore, although not directly hypothesized but assumed in Hypothesis 1, the influence on firm performance was examined. The relationship between operational capability and firm performance is found to be partially significant ( = 0.58; p < 0.06) while the alignment capability ( = -0.02; p > 0.05) and customer capability ( = 0.19; p > 0.05) do not significantly relate to firm performance. Thus, operational capability is the sole ordinary capability with a partially significant direct relationship to firm performance, which offers additional insight into the relationships between ordinary capabilities and performance. Figure 2 graphically displays these relationships.

20



Not

es: C

ontr

ol v

aria

bles

and

mar

ker

vari

able

s inc

lude

d in

ana

lysis

but

elim

inat

ed fr

om g

raph

ical

mod

el fo

r cl

arity

; **

* =

p <

0.0

01, *

* =

p <

0.0

1, *

= p

< 0

.05

Perfo

rman

ce

Figu

re 1

H

ighe

r-O

rder

Rel

atio

nshi

p be

twee

n A

bsor

pti

ve C

apac

ity

and

Per

form

ance

: T

he M

edia

ting

Rol

e of

Ord

inar

y C

apab

ilit

ies

21



Not

es: C

ontr

ol v

aria

bles

and

mar

ker

vari

able

s inc

lude

d in

ana

lysis

but

elim

inat

ed fr

om g

raph

ical

mod

el fo

r cl

arity

; *

** =

p <

0.0

01, *

* =

p <

0.0

1, *

= p

< 0

.05,

† =

p <

0.1

0

Ord

inar

y C

apab

ilitie

s

Acq

uisi

tion

Ass

imila

tion

Tran

sfor

mat

ion

Figu

re 2

A

bsor

ptiv

e C

apac

ity

Val

ue C

reat

ion

via

Ord

inar

y C

apab

ilit

ies

22



DISCUSSION

Results of the study suggest that ACAP and ordinary capabilities are related, and more specifically, ordinar performance relationship. These findings help to extend knowledge of firm capabilities, and the results offer evidence to support the transductive role of ordinary capabilities. Additionally, ACAP was found to positively relate to each type of ordinary capability: customer, alignment, and operational. This exploration of the relationship between two classes of capabilities (i.e., dynamic and operational) advances understanding of how firm capabilities work together to alter firm performance in the software industry. Research Implications

Scholarly work (e.g., Zahra and George, 2002; Volberda et al., 2010) notes ACAP is positively related to firm outcomes, suggesting that ACAP creates value for the firm; however, the means through which value is created within the firm remains less clear. This study offers insight into the relationship between ACAP and ordinary capabilities, noting that ordinary capabilities are the value-creating capabilities through which knowledge is exploited. The conceptual development and empirical examination herein highlights the relationship between absorptive capacity and each type of ordinary capability and finds that ordinary capabilities mediate the relationship between ACAP and performance.

Second, this research extends the contributions in a parallel stream of organizational capability research by providing empirical support for the existence of a relationship between one type of dynamic capability (i.e., ACAP) and ordinary capabilities (Collis, 1994; Winter, 2000). Further, the findings (a) support a broader call to include the ordinary capabilities construct in research relating dynamic capabilities and firm performance and (b) supports prior research (e.g., Helfat and Peteraf, 2003; Martelo et al., 2013) that suggests dynamic capabilities may not have a direct relationship with firm performance, rather, other classes of firm capabilities may mediate the relationship.

Third, scholars have noted critical shortcomings in organizational capability research. Dosi et al. (2000) note that growth of the capability research stream has experienced developmental challenges with many studies conducted at a high level of abstraction. In addition, Kusunoki et al. (1998) note that prior research employs a construct-level operationalization of ordinary capabilities, and few studies examine ordinary capabilities as a multi-dimensional construct. This investigation represents an attempt to begin a scholarly dialogue that addresses such limitations of capability research. The study deploys a multi-dimensional operationalization of ordinary capabilities and finds a positive relationship between ACAP and each of the three ordinary capability dimensions.

Fourth, a more detailed analysis was conducted to examine relationships between ACAP and each type of ordinary capability. In this finer-grained analysis, only operational capabilities are found to directly relate to firm performance (neither alignment capabilities nor customer capabilities were significantly related to performance). Even though this relationship is partially significant (p < 0.10), the finding points to an interesting future area of research: examining the relationship among the types of ordinary capabilities, and how each relates to varied forms of firm

23



outcomes. Given these and other insights, future studies are necessary to further investigate how ordinary capabilities work together, and with other classes of capabilities, to create value and influence performance.

Managerial Implications

While the findings of this study advance ACAP and capability-related scholarship, implications to advance the practice of management are also noted. For managers of firms in dynamic environments (similar to those of the software industry), investments to enhance the ACAP of the firm are likely to result in enhanced ordinary capabilities. As an example, managers may participate in professional organizations to obtain the latest information on industry trends and forecasted changes, have active bi-directional relationships with customers, and engage with stakeholders to enhance knowledge acquisition. Kindström et al. (2013) note that, given their unique access, front-line personnel should have appropriate training to recognize potentially valuable knowledge and opportunities when interacting directly with the customer. Further, once a firm obtains knowledge, the firm must come to understand the new knowledge (e.g., use cross-functional groups to filter and/or generate ideas) and subsequently store newly acquired knowledge (e.g., codification via repositories, such as knowledge databases and/or process manuals, or in tacit form via human capital networks).

For managers, recognizing the capabilities associated with obtaining new knowledge (e.g., absorptive capacity) and exploiting the value from the knowledge (e.g., ordinary capabilities) provides a framework for diagnosing and refining sources of competitive advantage. For example, Pugh and Dixon (2008) illustrate how Intel Service Solutions—the consulting division of Intel—used a knowledge harvest program wherein knowledge was systematically acquired, circulated to the various departments and units, and applied to create and promote future products and services. Using a similar harvest approach, managers may systematically identify areas where new knowledge is needed, acquire the new knowledge, and ensure the knowledge is shared with the appropriate functional units so the full value of the knowledge can be leveraged. A strategic approach, wherein knowledge is systematically leveraged, is likely to yield performance returns.

Limitations and Future Research

Although this study offers an enhanced understanding of how ACAP creates firm value, the investigation has limitations. First, the study consists of firms in the software industry. The software industry is highly dynamic and a context commonly used for the study of knowledge transfer and firm capabilities. While significant relationships are found between absorptive capacity and ordinary capabilities, future studies are encouraged to determine if the noted relationships manifest similarly beyond the software industry in, for example, industries that are less dynamic and more mature.

Second, this study is restricted by a limited variable bias, given that another class of capabilities (e.g., strategic capabilities) has been theoretically linked to those investigated in this study. The scope of this investigation was limited to two classes of capabilities—namely, dynamic capabilities (ACAP) and ordinary capabilities—owing to the prior claims that dynamic and ordinary capabilities are the primary classes of firm capabilities (Teece, 2014). Given Ortega’s (2010) suggestion of the possibility of

24



combinatorial influences among the three classes of firm capabilities, future efforts to operationalize the “metaphysical strategic insights” (Collis, 1994) of strategic capabilities will help extend this stream of research.

Third, the acquisition component of ACAP demonstrated a slightly lower-than-expected factor loading when evaluating the measurement models. While this was not uncommon given the sample size and model complexity, researchers are encouraged to examine the measurement approaches for assessing ACAP. This study utilized a measure derived from Jansen et al. (2005), yet other measurement scales exist (e.g., see the scale by Flatten et al., 2011). Future studies are encouraged to continue refining the measurement of ACAP and also consider including a more comprehensive operationalization of the exploitation component.

Finally, the research design presents inherent limitations. The data were collected at a single point in time; thus, claims that dynamic capabilities are causally related to ordinary capabilities or performance should be made cautiously. Findings from the study by Lisboa et al. (2011) suggest that an extension of the current hypothesized model may have an influence on current and future firm performance given their finding that exploitative capabilities relate to current performance while explorative capabilities influence future performance. Future longitudinal studies have the opportunity to explicate the recursive relationship between the various types of capabilities and performance. Lin and Wu (2014) find that dynamic learning capabilities (e.g., ACAP) mediate the relationship between valuable firm resources and performance. Hence, assessing capabilities using data from multiple time periods will provide an improved understanding of causal interrelatedness among these constructs and will shed light onto the knowledge processes internal to the firm.

CONCLUSION

Capability-related questions are central to, and among the most complex, in strategic management research (Helfat and Peteraf, 2009). Although capability-specific research has existed for some time, much remains to be understood about how capabilities of various classes work together. To this end, an attempt is made to understand how ACAP, a dynamic capability, exploits new knowledge and creates firm value. Empirical results demonstrate that ordinary capabilities act as transducers that convert new knowledge into value-creating options for the firm, thereby influencing firm performance. Introducing ordinary capabilities into the research conversation on ACAP offers an improved understanding of how the ACAP of a firm leverages new knowledge while offering insights on how firms renew or re-configure their value-creating processes.

References

Argote, L. 1999. Organizational Learning: Creating, Retaining, and Transferring Knowledge. Boston, MA: Kluwer Academic.

25



Armstrong, J. S. and T. S. Overton. 1977. “Estimating Nonresponse Bias in Mail Surveys.” Journal of Marketing Research 14: 396-402.

Baron, R. M. and D. A. Kenny. 1986. “The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations.” Journal of Personality and Social Psychology 51: 1173-1182.

Brown, R. L. 1997. “Assessing Specific Mediational Effects in Complex Theoretical Models.” Structural Equation Modeling: A Multidisciplinary Journal 4: 142-156.

akar, N. and A. Ertürk. 2010. “Comparing Innovation Capability of Small and Medium-Sized Enterprises: Examining the Effects of Organizational Culture and Empowerment.” Journal of Small Business Management 48(3): 325-359.

Cepeda, G. and D. Vera. 2007. “Dynamic Capabilities and Operational Capabilities: A Knowledge Management Perspective.” Journal of Business Research 60(5): 426-437.

Chang, S., Y. Gong, S. Way, and L. Jia. 2013. “Flexibility-Oriented HRM Systems, Absorptive Capacity, and Firm Innovativeness and Market Responsiveness.” Journal of Management 39(7): 1924-1951.

Chen, J. and R. K. H. Ching. 2004. “An Empirical Study of the Relationship of IT Intensity and Organizational Absorptive Capacity on CRM Performance.” Journal of Global Information Management 12(1): 1-17.

Cohen, W. M. and D. A. Levinthal. 1990. “Absorptive Capacity: A New Perspective on Learning and Innovation.” Administrative Science Quarterly 35(1): 128-152.

Collis, D. J. 1994. “How Valuable are Organizational Capabilities?” Strategic Management Journal 15: 143-152.

Crossan, M. M., M. J. Rouse, J. N. Fry, and J. P. Killing. 2009. Strategic Analysis and Action (7th ed.). Toronto: Prentice Hall.

Daspit, J. J. and D. E. D’Souza. 2013. “Understanding the Multi-Dimensional Nature of Absorptive Capacity.” Journal of Managerial Issues 25: 299-316.

Di Stefano, G., M. Peteraf, and G. Verona. 2014. “The Organizational Drivetrain: A Road to Integration of Dynamic Capabilities Research.” Academy of Management Perspective 28(4): 307-327.

Dillman, D. A. 2007. Mail and Internet Surveys: The Tailored Design Method. New York: John Wiley and Sons, Inc.

————. 1978. Mail and Telephone Surveys: The Total Design Method. New York: John Wiley and Sons, Inc.

Dosi, G., R. R. Nelson, and S. G. Winter. 2000. The Nature and Dynamics of Organizational Capabilities. New York: Oxford University Press.

Duncan, R. B. 1972. “Characteristics of Organizational Environments and Perceived Environmental Uncertainty.” Administrative Science Quarterly 17(3): 313-327.

Flatten, T. C., A. Engelen, S. Zahra, and M. Brettel. 2011. “A Measure of Absorptive Capacity: Scale Development and Validation.” European Management Journal 29: 98-116.

Fosfuri, A. and J. A. Tribó. 2008. “Exploring the Antecedents of Potential Absorptive Capacity and its Impact On Innovation Performance.” Omega: The International Journal of Management Science 36: 173-187.

García-Morales, V. J., M. T. Bolívar-Ramos, and R. Martín-Rojas. 2014. “Technological Variables and Absorptive Capacity’s Influence on Performance through Corporate Entrepreneurship.” Journal of Business Research 67(7): 1468-1477.

26



George, G., S. A. Zahra, K. K. Wheatley, and R. Khan. 2001. “The Effects of Alliance Portfolio Characteristics and Absorptive Capacity on Performance: A Study of Biotechnology Firms.” The Journal of High Technology Management Research 12(2): 205-226.

Hall, R. 1993. “A Framework Linking Intangible Resources and Capabilities to Sustainable Competitive Advantage.” Strategic Management Journal 14(8): 607-618.

————. 1992. “The Strategic Analysis of Intangible Resources.” Strategic Management Journal 13(2): 135-144.

Helfat, C. E. and M. A. Peteraf. 2009. “Understanding Dynamic Capabilities: Progress along a Developmental Path.” Strategic Organization 7(1): 91-102.

———— and M. A. Peteraf. 2003. “The Dynamic Resource-Based View: Capability Lifecycles.” Strategic Management Journal 24(10): 997-1010.

———— and S. G. Winter. 2011. “Untangling Dynamic and Operational Capabilities: Strategy for the (N)ever Changing World.” Strategic Management Journal 32(11): 1243-1250.

Huang, K.-F., K.-H. Lin, L.-W. Wu, and P.-H. Yu. 2015. “Absorptive Capacity and Autonomous R&D Climate Roles in Firm Innovation.” Journal of Business Research DOI: 10.1016/j.jbusres.2014.05.002

Jansen, J. J. P., F. A. J. Van Den Bosch, and H. W. Volberda. 2005. “Managing Potential and Realized Absorptive Capacity: How Do Organizational Antecedents Matter?” Academy of Management Journal 48(6): 999-1015.

Jayachandran, S., K. Hewett, and P. Kaufman. 2004. “Customer Response Capability in a Sense-and-Respond Era: The Role of Customer Knowledge Process.” Journal of the Academy of Marketing Sciences 32(3): 219-233.

Kaplan, R. S. and D. P. Norton. 2006. “How to Implement a New Strategy without Disrupting Your Organization.” Harvard Business Review (March): 100-109.

Kindström, D., C. Kowalkowski, and E. Sandberg. 2013. “Enabling Service Innovation: A Dynamic Capabilities Approach.” Journal of Business Research 66(8): 1063-1073.

Kostopoulos, K., A. Papalexandris, M. Papachroni, and G. Ioannou. 2011. “Absorptive Capacity, Innovation, and Financial Performance.” Journal of Business Research 64(12): 1335-1343.

Kumar, N., L. W. Stern, and J. C. Anderson. 1993. “Conducting Interorganizational Research Using Key Informants.” Academy of Management Journal 36(6): 1633-1651.

Kusunoki, K., I. Nonaka, and A. Nagata. 1998. “Organizational Capabilities in Product Development of Japanese Firms: A Conceptual Framework and Empirical Findings.” Organization Science 9(6): 699-718.

Lane, P. J. and M. Lubatkin. 1998. “Relative Absorptive Capacity and Inter-Organizational Learning.” Strategic Management Journal 19(5): 461-477.

Leal-Rodríguez, A. L., J. A. Ariza-Montes, J. L. Roldán, and A. G. Leal-Millán. 2014. “Absorptive Capacity, Innovation and Cultural Barriers: A Conditional Mediation Model.” Journal of Business Research 67(5): 763-768.

Lenz, R. T. 1980. “Strategic Capability: A Concept and Framework for Analysis.” Academy of Management Review 5(2): 225-234.

Levinthal, D. A. and J. G. March. 1993. “The Myopia of Learning.” Strategic Management Journal 14(Special issue: Winter): 95-112.

Lewin, A. Y., S. Massini, and C. Peeters. 2011. “Microfoundations of Internal and External Absorptive Capacity Routines.” Organization Science 22(1): 81-98.

27



Li, D. and J. Liu. 2014. “Dynamic Capabilities, Environmental Dynamism, and Competitive Advantage: Evidence from China.” Journal of Business Research 67(1): 2793-2799.

Li, X. 2011. “Sources of External Technology, Absorptive Capacity, and Innovation Capability in Chinese State-Owned High-Tech Enterprises.” World Development 39(7): 1240-1248.

Liao, J., H. Welsch, and M. Stoica. 2003. “Organizational Absorptive Capacity and Responsiveness: An Empirical Investigation of Growth-Oriented SMEs.” Entrepreneurship Theory and Practice 28(1): 63-85.

Liao, S., W. C. Fei, and C. C. Chen. 2007. “Knowledge Sharing, Absorptive Capacity, and Innovation Capability: An Empirical Study of Taiwan’s Knowledge-Intensive Industries.” Journal of Information Science 33(3): 340-359.

Lin, Y. and L. Wu. 2014. “Exploring the Role of Dynamic Capabilities in Firm Performance under the Resource-Based View Framework.” Journal of Business Research 67(3): 407-413.

Lindell, M. K. and D. J. Whitney. 2001. “Accounting for Common Method Variance in Cross-Sectional Research Designs.” Journal of Applied Psychology 86(1): 114-121.

Lisboa, A., D. Skarmeas, and C. Lages. 2011. “Innovative Capabilities: Their Drivers and Effects on Current and Future Performance.” Journal of Business Research 64(11): 1157-1161.

Malhotra, A., S. Gosain, and O. A. El Sawy. 2005. “Absorptive Capacity Configurations in Supply Chains: Gearing for Partner-Enabled Market Knowledge Creation.” MIS Quarterly 29(1): 145-187.

Martelo, S., C. Barroso, and G. Cepeda. 2013. “The Use of Organizational Capabilities to Increase Customer Value.” Journal of Business Research 66(10): 2042-2050.

Nootebloom, B., W. Van Haverbeke, G. Duysters, and A. van den Oord. 2007. “Optimal Cognitive Distance and Absorptive Capacity.” Research Policy 36(7): 1016-1034.

Ortega, M. J. R. 2010. “Competitive Strategies and Firm Performance: Technological Capabilities’ Moderating Roles.” Journal of Business Research 63(12): 1273-1281.

Pavlou, P. A. and O. A. El Sawy. 2011. “Understanding the Elusive Black Box of Dynamic Capabilities.” Decision Sciences 42(1): 239-273.

Podsakoff, P. M., S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff. 2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” Journal of Applied Psychology 88(5): 879.

Prahalad, C. K. 1993. “The Role of Core Competencies in the Corporation.” Research Technology Management 36(6): 40-47.

Pugh, K. and N. M. Dixon. 2008. “Don’t Just Capture Knowledge—Put it to Work.” Harvard Business Review May: 21-22.

Roberts, N. and V. Grover. 2012. “Investigating Firms’ Customer Agility and Firm Performance: The Importance of Aligning Sense and Respond Capabilities.” Journal of Business Research 65(5): 579-585.

Schreyögg, G. and M. Kliesch-Eberl. 2007. “How Dynamic Can Organizational Capabilities Be? Towards a Dual-Process Model of Capability Dynamization.” Strategic Management Journal 28(9): 913-933.

Stock, G. N., N. P. Greis, and W. A. Fischer. 2001. “Absorptive Capacity and New Product Development.” The Journal of High Technology Research 12(1): 77-91.

28



Tanriverdi, H. 2005. “Information Technology Relatedness, Knowledge Management Capacity, and Performance of Multibusiness Firms.” MIS Quarterly 29(2): 311-334.

Teece, D. J. 2014. “The Foundations of Enterprise Performance: Dynamic and Ordinary Capabilities in an (Economic) Theory of Firms.” Academy of Management Perspectives 28(4): 328-352.

————, G. Pisano, and A. Shuen. 1997. “Dynamic Capabilities and Strategic Management.” Strategic Management Journal 18(7): 509-533.

Todorova, G. and B. Durisin 2007. “Absorptive Capacity: Valuing a Reconceptualization.” Academy of Management Review 32(3): 774-786.

Treacy, M. and F. Wiersema. 1993. “Customer Intimacy and Other Value Disciplines.” Harvard Business Review 71: 84-93.

Tu, Q., M. A. Vonderembse, T. S. Ragu-Nathan, and T. W. Sharkey. 2006. “Absorptive Capacity: Enhancing the Assimilation of Time-Based Manufacturing Practices.” Journal of Operations Management 24(5): 692-710.

Volberda, H. W., N. J. Foss, and M. A. Lyles. 2010. “Absorbing the Concept of Absorptive Capacity: How to Realize Its Potential in the Organization Field.” Organization Science 21(4): 931-951.

Weeks, M. R. and S. Thomason. 2011. “An Exploratory Assessment of the Linkages between HRM Practices, Absorptive Capacity, and Innovation in Outsourcing Relationships.” International Journal of Innovation Management 15(2): 303-334.

Welsch, H., J. Liao, and M. Stoica, 2001. “Absorptive Capacity and Firm Responsiveness: An Empirical Investigation of Growth-Oriented Firms.” 2nd Annual USASBE/SBIDA Conference: An Entrepreneurial Odyssey. Orlando, FL.

Winter, S. G. 2003. “Understanding Dynamic Capabilities.” Strategic Management Journal 24(10): 991-995.

————. 2000. “The Satisficing Principle in Capability Learning.” Strategic Management Journal 21: 981-996.

Wu, S. J., S. A. Melnyk, and B. B. Flynn. 2010. “Operational Capabilities: The Secret Ingredient.” Decision Sciences 41(4): 721-754.

Zahra, S. A. and G. George. 2002. “Absorptive Capacity: A Review, Reconceptualization, and Extension.” Academy of Management Review 27(2): 185-203.

————, H. J. Sapienza, and P. Davidsson. 2006. “Entrepreneurship and Dynamic Capabilities: A Review, Model and Research Agenda.” Journal of Management Studies 43(4): 917-955.

Zott, C. 2003. “Dynamic Capabilities and the Emergence of Intraindustry Differential Firm Performance: Insights from a Simulation Study.” Strategic Management Journal 24(2): 97-125.

29



The Impact of Positive Organizational Phenomena and Workplace Bullying on Individual Outcomes

Pamela Lutgen-Sandvik Director, NDSU Communication Research & Training Center

Associate Professor of Organizational Communication North Dakota State University

[email protected]

Jacqueline N. Hood Creative Enterprise Endowed Professor – Department of Organizational Studies

University of New Mexico [email protected]

Ryan P. Jacobson

Assistant Professor – Department of Organizational Studies University of New Mexico

[email protected]

Rarely are positive organizational scholarship (POS) (Cameron et al., 2003b) and

counterproductive workplace behavior (CWB) (Fox and Spector, 2005) coupled in the same research study or theory. POS believes there needs to be a focus on the positive in organizational research versus the negative approach that has been the tradition (Baumeister et al., 2001; Sekerka et al., 2014). However, there is reason to believe that even in the face of positive organizational features, if workplace bullying is present, the beneficial outcomes associated with positive features may be lost or at least diminished (Baumeister et al., 2001; Dutton and Glynn, 2008). From this perspective, in order to best understand and enrich human and organizational life, researchers should continue to study problems and their potential solutions, but do so in tandem with others who are studying human thriving in the absence of, or despite, problems.

The current study has two central goals. One of the purposes of the study is to explore the effect of positive interpersonal work experiences and perceived

(30)

LUTGEN-SANDVIK, HOOD, AND JACOBSON


organizational virtuousness on three vital individual and organizational outcomes: stress levels related to work, perceptions of mental health quality, and the intent to leave jobs. Importantly for this purpose, however, is going beyond simply looking at positive phenomena but also looking at the moderating effect of workplace bullying on these outcomes. Workplace bullying has significant negative consequences for individuals and organizations (e.g., Malinauskiene and Einarsen, 2014; Finne et al., 2011; Loerbroks et al., 2015) and can often escalate into what is becoming of significant concern in organizations, workplace violence (Mayhew and Chappell, 2007). It will be argued that although positive phenomena are valuable goals for a wide variety of reasons, if workers are also targeted with negative, hostile messages and behaviors, positive dynamics can be negated or at least weakened.

LITERATURE REVIEW

Positive Organizational Scholarship

The organizational literature has traditionally taken a problem-focused approach (Sekerka et al., 2014), in which researchers attempt to address deficits in organizations and to bring organizations to some state of normalcy rather than attempting to cultivate strengths (Cooperrider and Godwin, 2012). Positive organizational scholarship (POS) conceptualizes and studies what is or could be “good” in organizations—how organizations and their members might thrive, what leads to thriving, what thriving leads to, and how thriving might be increased. POS “is concerned with the study of especially positive outcomes, processes, and attributes of organizations and their members…. [, that which is] exceptional, virtuous, life-giving, and flourishing” (Cameron et al., 2003a: 4, 5). POS and positive organizational behavior are relatively young fields (Cameron et al., 2003b; Luthans, 2002) still calling for empirical work to test its nascent assumptions (Cameron and McNaughtan, 2014).

POS focuses on issues including but not limited to perceived organizational virtuousness (Cameron et al., 2004), upward spirals in organizations (Fredrickson, 2003), and narratives of compassion (Frost et al., 2000). Empirical work suggests that these phenomena are associated with positive organizational outcomes and, more importantly, positive human outcomes (Cameron and McNaughton, 2014). Compassion, for example, can provide supportive spaces for persons suffering loss or trauma in their personal lives and also “may be a factor in both attracting and retaining staff” (Frost et al., 2000: 38). The effects of such positive organizational processes appear promising for enriching human life, both inside and outside of organizations. The effects of two particular arenas of positive organizational phenomena are explored: positive individual treatment and organizational virtuousness.

Positive individual treatment. Positive individual treatment at work is comprised of the interpersonal and task interactions at work that represent the positive side of workplace experiences. It includes interpersonal positivity such as having others treat your feelings as important and treat you with respect and dignity (Keashly et al., 1994), as well as task-related positivity such as having others ask for your opinion and give your suggestions serious consideration (Lutgen-Sandvik, 2003). Indeed, positive experiences engender positive emotions that “can reverberate through other organizational members across interpersonal transactions with customers, … [and] fuel optimal organizational functioning” (Fredrickson, 2003: 163).

31

POSITIVE ORGANIZATIONAL PHENOMENA AND BULLYING


The interpersonal aspects of work have alternately been called maintenance (Meisenbach and McMillan, 2006), group-building, process, (Beebe and Masterton, 2009), and relational (Keyton, 1999) communication and behavior. Closely related is the presence of social support at work, interactions such as feeling safe saying what one believes or being told one is enjoyable to work with. Such social support at work is associated with lower turnover intentions, and lower depression levels (Thorsteinsson et al., 2014). Others’ appreciation for an individual’s efforts can make their endeavors feel worthwhile and, as an added bonus, open up creative channels in previously unrecognized directions (Fredrickson, 2000). Social support and friendships at work and, thus, social capital decreases workers’ intention to leave (Feeley et al., 2008).

Positive workplace experiences are determinants of workplace morale (Hart, 1994), affirmative quality of life (Hart et al., 1995), and work commitment (Meyer et al., 1998). Workplace morale and commitment are positively associated with job satisfaction which is negatively associated with intention to leave (Fried et al., 2008). Moreover, an affirmative or positive quality of life includes positive perceptions of one’s mental health (Rice et al., 1992). Further, positive experiences evoking positive emotion are also associated with lower stress levels (Fredrickson et al., 2000), as are positive communicative interactions at work (Lutgen-Sandvik and McDermott, 2008b).

Organizational virtuousness. Positive interpersonal treatment at work is associated with what Bright and colleagues call virtuous in organizations—the “behavior of individuals in organizational settings that helps people flourish as human beings” (2006: 252). However, organizational virtuousness, or “virtuousness through organizations relates to the enablers in organizations that foster and perpetuate virtuousness” (Bright et al., 2006: 252); however, “virtuousness through organizations has rarely been examined” (Cameron and Caza, 2013: 678). Organizational virtuousness is determined by workers’ perceptions of the presence or absence of the manifestations of virtuousness—crucial perceptions given that “the organizational context in which people work is more important than the work itself in determining psychological outcomes” (Hart et al., 1995: 150).

Virtuousness also positively affects human beings, contributing to human flourishing and thriving (Cameron and Caza, 2013). Finally, organizational virtuousness “extends beyond mere self-interested benefit ... [it] creates social value that transcends the instrumental desires of the actor” (Cameron et al., 2004: 769). Virtuousness is the “aggregates or virtues, acting in combination, which manifests itself as behaviors, processes, and routines in organizational settings” (Cameron and Winn, 2012). Manifestations of organizational virtuousness include characterizations of the organization as a whole, usually, but not always, as it manifests in workers’ specific divisions, departments, or workgroups. This could include perceptions of organizational trustworthiness, compassion, virtue, and honor.

Studies of individual virtuousness have found that it is negatively associated with employee turnover (Cameron et al., 2004) and positively associated with social capital and affiliative behavior (Cameron and Caza, 2013), which are factors associated with workers’ mental health (Baum, 1999). Virtuousness serves both as “self-reinforcing spirals, and a buffering function that strengthens and protects organizations from traumas such as downsizing” (Cameron et al., 2004: 766). Organizational virtuousness, measured as compassion, integrity, forgiveness, trust, and optimism, moderated the effects of downsizing on productivity efficiency and customer claims (Gittell et al., 2006).

32



Virtuous organizations and their members serve to better society in some way, and benefiting others may protect employees against a variety of risks, including stress leading to burnout (Grant and Campbell, 2007). Individual virtuousness also enhances flexibility and resilience, solidarity and commitment, and perceived efficacy or effectiveness (Cameron and Caza, 2013; Cameron et al., 2004). From these it can be extrapolated that organizational virtuousness is, at least indirectly, negatively related to workplace stress and voluntary turnover and positively associated with the quality of employees’ mental health.

Workplace Bullying and Bullying Degree

Workplace bullying is a constellation of hostile messages and abusive behaviors persistently targeted at one or more persons in work settings. It is patterned behavior comprised by numerous hostile actions and interactions (e.g., verbal abuse and public humiliation coupled with social ostracism, work obstruction, and destructive gossip) (Lutgen-Sandvik, 2008). Bullying is more often than not escalatory, starting with occasional subtle, indirect insults or rude remarks and growing to more egregious, frequent types of humiliation, criticism, or verbal abuse (Magee et al., 2015; Salin, 2003). In fact, workplace bullying is a potential precursor of workplace violence (Mayhew and Chappell, 2007), of growing concern in today’s workplace. Although persons outside the organization can bully organizational members (e.g., customers, patients), workplace bullying research is concerned with aggression by organizational members targeted at other members (Rayner et al., 2002). Considerable research substantiates the negative effects of bullying, both on targets and non-bullied witnesses (Lutgen-Sandvik et al., 2007; Magee et al., 2015).

Adult bullying at work is an extreme stressor for those targeted and is linked to serious negative mental health affects including the symptoms of post-traumatic stress disorder (Malinauskiene and Einarsen, 2014), mental distress (Finne et al., 2011), depression (Loerbroks et al., 2015), and suicidal ideation/suicide (Leymann, 1990). Clearly bullying is negatively related to the quality of workers’ mental health (Finne et al., 2011; Magee et al., 2015). Additionally, workplace bullying is positively associated with intention to leave, both for targets and for witnesses (Rayner et al., 2002; Simons, 2008). When workers are treated with respect, dignity, and work in a positive psychological climate, they are less likely to spend their time thinking about leaving or actually looking for another job. Stress levels are also directly related to bullying; bullying witnesses and targets report significantly higher stress levels than non-affected workers (Lutgen-Sandvik et al., 2007).

An extensive body of psychological research exists pointing to the power of negative events (Baumeister et al., 2001). As such, it is anticipated that even in the face of positive phenomena, workplace bullying will influence the effects of positivity. It has been proposed that workplace bullying can affect and is affected by the organizational culture (Hood and Logsdon, 2008; Logsdon et al., 2007). What is more, organizations are typically more complex than being simply employee-abusive (Lutgen-Sandvik and McDermott, 2008a) or virtuous/positive (Bright et al., 2006). Rather, it is likely that both negative and positive interpersonal interactions and organizational qualities coexist.

It is fruitful to conceptualize bullying on a continuum of negativity degree, rather than something that is present or absent. Given the overwhelming body of research that suggests bad is stronger than good (Baumeister et al., 2001), the degree of workplace

33



negativity will moderate the effects of positive workplace phenomena. As such, the following hypotheses are examined:

Hypothesis 1a: Positive individual treatment and organizational virtuousness are

negatively related to work stress, holding age and sex constant. Hypothesis 1b: Bullying is positively related to work stress, holding positive

organizational treatment, organizational virtuousness, age, and sex constant. Hypothesis 2a: Positive individual treatment and organizational virtuousness are

positively related to mental health, holding age and sex constant. Hypothesis 2b: Bullying is negatively related to mental health, holding positive

organizational treatment, organizational virtuousness, age, and sex constant. Hypothesis 3a: Positive individual treatment and organizational virtuousness are

negatively related to intent to leave, holding age and sex constant. Hypothesis 3b: Bullying is positively related to intent to leave, holding positive

organizational treatment, organizational virtuousness, age, and sex constant. Hypothesis 4a: Bullying moderates the relationship between organizational

virtuousness and work stress, such that the effects are weaker when higher levels of bullying are present.

Hypothesis 4b: Bullying moderates the relationship between positive individual treatment and work stress, such that the effects are weaker when higher levels of bullying are present.

Hypothesis 5a: Bullying moderates the relationship between organizational

virtuousness and mental health, such that the effects are weaker when higher levels of bullying are present.

Hypothesis 5b: Bullying moderates the relationship between positive individual treatment and mental health, such that the effects are weaker when higher levels of bullying are present.

Hypothesis 6a: Bullying moderates the relationship between organizational

virtuousness and intent to leave such that the effects are weaker when higher levels of bullying are present.

Hypothesis 6b: Bullying moderates the relationship between positive individual treatment and intent to leave such that the effects are weaker when higher levels of bullying are present.

METHOD

Data Collection and Sample

The current study was conducted via an online survey administered through Survey Monkey (www.surveymonkey.com) and using a sampling service coupled with online advertisements to draw U.S. workers to the survey. The sampling procedure included sending recruiting messages by email to individuals who have volunteered to participate

34



in web-based research through the StudyResponse project, a paid sampling service of Syracuse University. Emails linked respondents to the Survey Monkey site.

The StudyResponse project facilitates sampling for many university studies and, as such, is not a collaborator or subcontractor in this study. The service simply sends an electronic message with a link to the study’s online survey posted with Survey Monkey to panelists who have agreed to participate in online social science research. The service protects participant identity; participants are identified by a unique, anonymous ID, which they enter when beginning the survey. Equal sampling of men and women was requested as was a request to limit sampling to persons working in the U.S. After recruitment was completed and data collected, the service sent a database to the researchers containing participant ID numbers and demographic characteristics (age, gender, ethnicity, education level, work situation, and occupation). For an in-depth explanation of the sampling service, see studyresponse.com.

In total, 2,846 U.S. workers responded to the survey fully enough for data analysis. StudyResponse sent email requests to 5,000 potential participants and followed up that request twice, at seven and fourteen days post-contact. Of those sampled, 2,421 StudyResponse participants completed the survey for a response rate of 48.4%. The other 398 came to the survey through online advertisements; 27 did not provide information regarding how they came to the survey. Of the total respondents, 1,234 were male (43.4%) and 1,603 female (56.3%). Participants’ mean age was 42 (range 18-84, SD 10.6). (StudyResponse supplied sex, age, and other demographics.)

Their occupational distribution is similar to distribution reported by U.S. Department of Labor (Department of Labor, 2014) in the areas of retail/wholesale, real estate, government, professional/scientific, construction, utilities, other services, arts/recreation, and administrative support. The sample somewhat over-represents the occupations of finance/insurance, information, management, and education, and under-represented in the occupations of mining/natural resources, manufacturing, accommodation/food service, health/social services, and transportation. Thus, like other online survey formats, the sample is somewhat biased toward white-collar professionals.

Measures

The hypotheses required the measurement of a number of concepts: positive individual treatment factors, organizational virtuousness, bullying degree, and three outcome variables: intent to leave, stress level, and mental health.

Positive individual treatment. The first variable assessed was respondents’ positive personal experiences—interpersonal interactions at work that represented the positive side of workplace experiences—using an index that included eleven items from past research by Keashly et al. (1994), e.g., “Praised for your accomplishments,” “Treated as an equal,” and “Included in joking,” as well as nine items from past research by Lutgen-Sandvik (2003), e.g., “Your suggestions are given serious consideration,” “Treated with respect and dignity,” and “Felt safe in saying what you thought.” Respondents were asked to rate their level of agreement with statements regarding how they were personally treated where they worked during the last six months. Response categories for each positive individual treatment act ranged from 5, strongly agree to 1, strongly disagree. Cronbach’s alpha for the scale was 0.97

35



Organizational virtuousness. The second variable examined was perceived organizational virtuousness from Cameron and colleague’s (2004) work—the positive organizational factors associated more with an overall organizational culture than with an individual’s personal treatment. Reliability for the five factors of organizational virtuousness in Cameron et al.’s (2004) work ranged from 0.84 to 0.90. Respondents were asked to rate their level of agreement with statements regarding the organization where they worked during the last six months. Response categories ranged from 5, strongly agree to 1, strongly disagree.

Unlike Cameron et al.’s (2004) five factor analysis (optimism, trust, compassion, integrity, forgiveness), data in this study suggested one factor related to overall perceptions of organizational virtuousness. The organizational virtuousness scale included 15 items such as: “Honesty and trustworthiness are hallmarks of this organization,” “People trust the leadership in this organization,” and “We are optimistic that we will succeed, even when faced with major challenges.” Cronbach’s alpha for this variable was 0.96.

Bullying degree. A third variable assessed was personally experienced degree of negativity using Lutgen-Sandvik et al.’s (2007) construct of bullying degree—a continuous measure representing the cumulative variables of bullying duration, intensity (number of negative acts reported), and frequency (negative acts reported weekly or more often). The negative acts forming the basis of bullying degree were drawn from the Negative Acts Questionnaire (Einarsen and Hoel, 2001), the most commonly used measure of workplace bullying. The NAQ measures the intensity and frequency of 24 behaviorally-termed negative acts over the past six months without specifically referring to “bullying.” Previous studies using the NAQ have demonstrated an internal consistency as measured by Cronbach’s alpha of 0.84 to 0.92 (Einarsen and Hoel, 2001; Einarsen and Raknes, 1997; Mikkelsen and Einarsen, 2001); Cronbach’s alpha was 0.95 in this study. NAQ items include “had information withheld that affected your performance,” “had insulting/offensive remarks made about you,” and “been shouted at or targeted with spontaneous anger (or rage).” Response categories for each negative act were: 0 never, 1 occasionally (less than monthly); 2 monthly; 3 weekly, and 4 daily. As such, “a mid-range bullying degree score could reflect two different possibilities: a high number of negative acts at a relatively low frequency or a limited number of negative acts at a relatively high frequency. For example, for a respondent reporting five negative acts monthly (intensity = 5) and eight negative acts weekly/daily (frequency = 8) over the past six months (duration = 6), the bullying degree score would be calculated as 5 + 8 + 6 = 19” (Lutgen-Sandvik et al., 2007: 847).

Outcome variables: intent to leave, workplace stress, mental health quality. Positive and negative organizational variables were examined in relation to their impact on three outcome variables: intent to leave, stress level at work, and mental health quality. Intent to leave was measured by two items with which respondents were asked to rate their level of agreement: “I often think of finding another job,” and “I am currently looking for another job.” Reliability for the two items as measured by Cronbach’s alpha was 0.90. For both items, response choices ranged from 5, strongly agree to 1, strongly disagree. Stress level and mental health were assessed using single-item measures. Stress was measured by asking respondents to rate their “stress level at work;” response choices ranged from 5, high stress to 1, little or no stress. Respondents’ perceptions of the quality of their mental

36



health was measured by asking them to rate their level of mental health. Response choices ranged from 5, excellent to 1, poor.

Single-item measures of stress level and mental health were used because ample scholarship suggests that single-item measures are significantly associated with multiple-item measures of the same construct (Cunny and Perri, 1991; Loo, 2002; Wanous et al., 1997). Research has found that single-item measures correlate with multiple-item indexes of job satisfaction (Nagy, 2002; Wanous et al., 1997), work-related stress and health (Hasson and Arnetz, 2005), and health-related quality of life (Cunny and Perri, 1991). In addition, as single-item measures are shorter, more efficient, and may encompass more of the construct under analysis (Nagy, 2002), the single-item approach was well suited for these purposes.

RESULTS

Preliminary Analyses

Table 1 presents the means, standard deviations, and intercorrelations of study variables. As expected, the three outcome variables were significantly intercorrelated. In regard to control variables, age was significantly related (negatively) to turnover intentions but not to work stress or mental health quality. Sex was significantly related to work stress and mental health (females reported higher levels of work stress and lower levels of mental health quality than males), but not turnover intentions. In regard to hypothesis-relevant variables, organizational virtuousness and positive individual treatment were positively related, as expected, and each was significantly related to the three outcome variables. Bullying was negatively related to both organizational virtuousness and positive individual treatment, as anticipated, and was significantly related to the three outcome variables. Hierarchical Regression Analyses

To test Hypotheses 1a-b (work stress), a hierarchical regression analysis was performed in which control variables (respondent age and sex) were entered in step 1, organizational virtuousness and positive individual treatment were entered in step 2, and bullying was entered in step 3 (see Table 2). The combined effect of control variables in step 1 was significant, F(2, 2125) = 7.256, p = 0.001. Respondent sex emerged as the only significant individual predictor in this step. Supporting H1a, the addition of positive organizational variables in step 2 significantly improved model prediction,

F(2, 2123) = 100.450, p < 0.001. Respondent sex and positive individual treatment emerged as significant individual predictors in step 2. Supporting H1b, the addition of bullying in step 3 significantly improved model prediction, F(1, 2122) = 67.401, p < 0.001. The overall model explained 12% of the variance in work stress.

37



Tab

le 1

D

escr

ipti

ve S

tati

stic

s an

d B

ivar

iate

Cor

rela

tion

s

Var

iabl

e M

SD

1

2 3

4 5

6 7

1. W

ork

Stre

ss

3.50

1.

13

2. M

enta

l Hea

lth

Qua

lity

3.47

1.

01

-0.1

1**

3. T

urno

ver

Inte

ntio

ns

2.67

1.

31

0.30

**

-0.

14**

4. A

ge

41.5

0 10

.47

-0.0

1 0.

02

-0.1

1**

5. S

ex

0.37

0.

48

-0.0

8**

0.0

5* 0.

02

0.2

8**

6. O

rgan

izat

iona

l V

irtu

ousn

ess

3.70

0.

83

-0.1

7**

0.17

**

-0.

37**

0.

05*

0.0

2

7. P

ositi

ve I

nter

pers

onal

T

reat

men

t 3.

58

0.86

-0

.29**

0.

23**

-

0.51

**

-0.0

1 0

.00

0.6

3**

8. B

ully

ing

8.21

8.

77

0.27

**

-0.

16**

0.

34**

-

0.05

* -0

.02

-0.4

1**

-0.4

1**

Not

e. N

= 2

128.

Sex

cod

ed 0

= fe

mal

e, 1

= m

ale.

* p <

0.0

5. *

*p <

0.0

1.

38



Tab

le 2

H

iera

rchi

cal R

egre

ssio

n R

esul

ts f

or W

ork

Stre

ss

St

ep 1

St

ep 2

St

ep 3

Pre

dic

tor

B

SE B

B

SE

B

B

SE B

Con

stan

t 3.

52**

* 0.

10

4.87

***

0.15

4.

17**

* 0.

17

Age

0

.00

0.00

0

.00

0.00

0.

00

0.00

Sex

-0.2

0***

0.05

-0

.20**

* 0.

05

-0.1

9 0.

05

Org

aniz

atio

nal V

irtu

ousn

ess

0.0

3 0.

04

0.1

0* 0.

04

Posi

tive

Int

erpe

rson

al T

reat

men

t

-0

.40**

* 0.

04

-0.3

4 0.

04

Bul

lyin

g

0

.02**

* 0.

00

R2

0.

01

0.

09

0.

12

F R

2

7.2

6**

10

0.45

***

67

.40**

*

Not

e. N

= 2

128.

* p <

0.0

5, **

p <

0.0

1, **

* p <

0.0

01.

39



The same analytical strategy was used to test Hypotheses 2a-b (mental health quality; see Table 3). The combined effect of control variables in step 1 was not significant, F(2, 2125) = 2.824, p = 0.060. Respondent sex emerged as the only significant individual predictor in this step. Supporting H2a, the addition of positive organizational variables in step 2 significantly improved model prediction, F(2, 2123) = 58.703, p < 0.001. Respondent sex and positive individual treatment emerged as significant individual predictors in step 2. Supporting H2b, the addition of bullying in step 3 significantly improved model prediction, F(1, 2122) = 8.509, p < 0.001. The overall model explained 6% of the variance in mental health quality.

Tab

le 3

H

iera

rchi

cal R

egre

ssio

n R

esul

ts f

or M

enta

l Hea

lth

Qua

lity

Step

1

Step

2

Step

3

Pre

dic

tor

B

SE B

B

SE

B

B

SE B

Con

stan

t 3.

40**

* 0.

09

2.36

***

0.15

2

.59**

* 0.

15

Age

0

.00

0.00

0

.00

0.00

0.

00

0.00

Sex

0.10

* 0.

05

0.10

* 0.

05

0.1

0* 0.

05

Org

aniz

atio

nal

Vir

tuou

snes

s

0

.06

0.03

0.

04

0.03

Posi

tive

Inte

rper

sona

l T

reat

men

t

0.

23**

* 0.

03

0.2

1***

0.03

Bul

lyin

g

-0

.01**

0.

00

R2

0.

00

0.

06

0.

06

F R

2

2.82

58.7

0***

8.

51**

Not

e. N

= 2

128.

* p <

0.0

5, **

p <

0.0

1, **

* p <

0.0

01.

40



Finally, the same analytical strategy was used to test Hypotheses 3a-b (turnover intentions; see Table 4). The combined effect of control variables in step 1 was significant, F(2, 2125) = 16.924, p < 0.001. Both respondent age and sex emerged as significant individual predictors in this step. Supporting H3a, the addition of positive organizational variables in step 2 significantly improved model prediction, F(2, 2123) = 385.579, p < 0.001. Respondent sex, age, organizational virtuousness, and positive individual treatment emerged as significant individual predictors in step 2. Supporting H3b, the addition of bullying in step 3 significantly improved model prediction, F(1, 2122) = 52.450, p < 0.001. The overall model explained 30% of the variance in turnover intentions.

Tab

le 4

H

iera

rchi

cal R

egre

ssio

n R

esul

ts f

or T

urno

ver

Inte

ntio

ns

St

ep 1

St

ep 2

St

ep 3

Pred

icto

r B

SE

B

B

SE B

B

SE

B

Con

stan

t 3.

29**

* 0

.12

6.2

2***

0.15

5

.59**

* 0.

17

Age

-0

.02**

* 0

.00

-0.0

2***

0.00

-0

.02**

* 0.

00

Sex

0.14

* 0

.06

0.15

**

0.05

0.

15**

0.

05

Org

aniz

atio

nal

Vir

tuou

snes

s

-0

.11**

0.

04

-0.0

5 0.

04

Posi

tive

Inte

rper

sona

l T

reat

men

t

-0

.71**

* 0.

04

0.6

5***

0.04

Bul

lyin

g

0

.02**

* 0.

00

R2

0

.02**

*

0.28

0.30

F R

2

16.9

2

385.

58**

*

52.4

5***

Not

e. N

= 2

128.

* p <

0.0

5, **

p <

0.0

1, **

* p <

0.0

01.

41



Moderation Analyses

All moderation hypotheses were tested using Hayes and Matthes’ (2009) MODPROBE macro for SPSS. Two regression equations were estimated for each of the three outcome variables that examined: (a) the interaction between bullying and organizational virtuousness, and (b) the interaction between bullying and positive individual treatment. For work stress, the interaction between bullying and organizational virtuousness was not significant, b < 0.01, SE < 0.01, p = 0.276, failing to support Hypothesis 4a. The interaction between bullying and positive individual treatment was also not significant for work stress, failing to support Hypothesis 4b, b = -0.01, SE < 0.01, p = 0.093.

Supporting Hypothesis 5a, the interaction between bullying and organizational virtuousness was significant in the equation predicting mental health quality, b = -0.02, SE < 0.01, p < 0.001. Simple slopes tests indicated that the effect of bullying on mental health quality was significant at the mean of organizational virtuousness, b = -0.01, SE < 0.01, p < 0.001, as well as at 1 SD below the mean, b = -0.01, SE < 0.01, p = 0.008, and at 1 SD above the mean, b = -0.02, SE < 0.01, p < 0.001. As expected, as bullying levels increased, the beneficial effects of organizational virtuousness on mental health quality were reduced (see Figure 1). Hypothesis 5b was also supported by the data, as the interaction between bullying and positive organizational treatment was also significant, b = -0.01, SE < 0.01, p = 0.035. The effect of bullying on mental health quality was significant at the mean of positive individual treatment, b = -0.01, SE < 0.01, p < 0.001, as well as at 1 SD above the mean, b = -0.02, SE < 0.01, p < 0.001. The effect of bullying was not significant at 1 SD below the mean of positive organizational treatment, b = -0.01, SE < 0.01, p = 0.076. As with organizational virtuousness, these results indicate that the beneficial effects of positive individual treatment on mental health quality are reduced as bullying levels increase (see Figure 1).

42



Figure 1 Interaction between Bullying and Organizational Virtuousness

Predicting Mental Health Quality

Supporting Hypothesis 6a, the interaction between bullying and organizational

virtuousness was significant in the equation predicting turnover intentions, b = 0.01, SE < 0.01, p = 0.002. Simple slopes tests indicated that the effect of bullying on turnover intentions was significant at the mean of organizational virtuousness, b = 0.03, SE < 0.01, p < 0.001, as well as at 1 SD below the mean, b = 0.03, SE < 0.01, p = 0.008, and at 1 SD above the mean, b = 0.04, SE = 0.01, p < 0.001. These results indicate that, as expected, the beneficial role of organizational virtuousness in reducing turnover intentions decreased as levels of bullying increased (see Figure 2). Hypothesis 6b was also supported by the data, as the interaction between bullying and positive organizational treatment was also significant, b = -0.01, SE < 0.01, p < 0.001. The effect of bullying on turnover intentions was significant at the mean of positive individual treatment, b = 0.02, SE < 0.01, p < 0.001, as well as at 1 SD below the mean, b = 0.02, SE < 0.01, p < 0.001, and at 1 SD above the mean, b = 0.04, SE < 0.01, p < 0.001. As predicted, the beneficial effects of positive organizational treatment in decreasing turnover intentions were reduced as bullying levels increased (see Figure 2).

1.0

2.0

3.0

4.0

5.0

14.10 21.15 28.20 35.25 42.30

Men

tal H

ealt

h Q

uali

ty

Bullying

Organizational Virtue (-1 SD)

Organizational Virtue (Mean)

Organizational Virtue (+1 SD)

43



Figure 2

Interaction between Bullying and Positive Organizational Treatment Predicting Mental Health Quality

DISCUSSION

The results of the study indicate that stress level and turnover intentions are negatively related to positive individual treatment, with mental health positively associated with positive individual treatment. Higher levels of perceived organizational virtuousness were associated with lower turnover intentions, but this variable did not predict stress levels or mental health. Bullying behavior was positively related to turnover intentions and to higher stress, and negatively related to mental health. Furthermore, the results indicate that workplace bullying moderates the relationship between the positive organizational factors and the three outcome variables. When bullying levels were low, these positive organizational factors tended to have beneficial effects on the workplace outcomes examined in this study. However, these beneficial effects tended to decrease as levels of bullying in the organization increased.

Baumeister et al.’s (2001) review of literature convincingly argues that negative phenomena, in many ways, have stronger effects than do positive. This study’s findings

1.0

2.0

3.0

4.0

5.0

14.10 21.15 28.20 35.25 42.30

Men

tal H

ealt

h Q

uali

ty

Bullying

Positive Organizational Treatment (-1 SD)

Positive Organizational Treatment (Mean)

Positive Organizational Treatment (+1 SD)

44



support that claim since bullying tempered the positive effects of positive organizational variables on individual outcomes. Even with a virtuous culture, primarily positive individual treatment, having a bully in the work group can have significant negative effects on employees. As Cameron and colleagues (2004; 2014) argue, organizational virtuousness can have a buffering effect on negative behaviors in the workplace, but it does not eliminate the need for managerial action to eliminate harmful work behaviors such as bullying.

The sample size was large and, in principle, large sample sizes can produce statistically significant findings even when effect sizes are relatively small. However, it is not believed that this applies to the results obtained here. The predictor variables in the three hierarchical regression analyses performed explained 12%, 6%, and 30% of the variance in work stress, mental health quality, and turnover intentions, respectively. As these are complex and multiply determined outcomes that are affected by an array of person-level, situation-level, and organization-level variables, it is felt that the results of these analyses demonstrate effects that are indeed practically significant and make an important contribution to the literatures on these work outcomes.

Implications for Research and Practice

The dialogue between positive organizational scholarship and counterproductive workplace researchers is in the early stages. To consider organizations in their complexity, research needs to consider both of these perspectives. This means future research should explicitly explore positive and negative phenomena in tandem, like Hart and colleagues’ (1995) police officer study or Lutgen-Sandvik and McDermott’s (2008b) look at the effects of positive and negative communication in work organizations.

Additionally, negative and positive phenomena do different things in organizations. Emotions are a good example. Positive emotions foster approach behavior, encourage engagement with the external environment (e.g., taking part in activities) and “broaden people’s momentary thought-action and repertoires, widening the array of thoughts and actions that come to mind” (Fredrickson, 2005: 122, emphasis in original). Negative emotion, on the other hand, restricts or narrows an individual’s “momentary thought-action repertoire by calling to mind an urge to act in a particular way” (Frederickson, 2005: 122) (e.g., retaliate or seek escape when aggressed against). As such, measuring how negative and positive phenomena affect the same variables might be less useful than determining which aspects of organization life are most strongly affected by each of these. Future research might also examine different categories of outcomes (e.g., creativity, problem-solving, innovation), which could prove useful in determining which outcomes are more strongly affected by positive phenomena and which by negative phenomena.

As in studies of interpersonal relationships (Gottman, 1999), positive and negative behaviors in organizations appear to be independent rather than opposite ends of a continuum (Dutton and Glynn, 2008). Both can be present, and in varying degrees. As such, managers attempting organizational interventions should assess the presence and degree of negativity while building the desired positive organizational dynamic inherent to appreciative inquiry (AI) or other positively-based approaches. Positive approaches to organizational interventions, such as AI, must also take into consideration the presence of persistent aggression. Otherwise the negative dynamics can, at best,

45



decrease the hoped-for positive outcomes or, at worst, nullify those positive outcomes. This means developing hybrid intervention approaches such as a “balanced approach” (Cady and Caster, 2000: 79) or Egan’s (cited in Egan and Lancaster, 2005) Appreciative Action Research Model, combining the best of the positive-focused AI and the more problem-focused Action Research.

Further, there seems little doubt that organizations should work toward building positive environments marked by constructive, supportive relationships among members as well as organizational virtuousness as a manifested cluster of cultural features. Organizations must, at the same time, actively work to eliminate workplace bullying in order to build a positive, ethical environment for employees (Hood and Logsdon, 2008) that fosters beneficial individual and organizational outcomes.

References Baum, F. 1999. “Social Capital: Is it Good for Your Health? Issues for a Public Health

Agenda.” Journal of Epidemiology and Community Health 53: 195-196. Baumeister, R. F., E. Bratslavsky, C. Finkenauer, and K. D. Vohs. 2001. “Bad is Stronger

than Good.” Review of General Psychology 5(4): 323-370. Beebe, S. A. and J. T. Masterton. 2009. Communicating in Small Groups: Principle and

Practice (9th ed.). Boston, MA: Allyn & Bacon. Bright, D. S., K. S. Cameron, and A. Caza. 2006. “The Amplifying and Buffering Effects

of Virtuousness in Downsized Organizations.” Journal of Business Ethics 64(3): 249-269.

Cady, S. H. and M. A. Caster. 2000. “A DIET for Action Research: An Integrated Problem and Appreciative Focused Approach to Organizational Development.” Organization Development Journal 18(4): 79-93.

Cameron, K. S., D. Bright, and A. Caza. 2004. “Exploring the Relationships between Organizational Virtuousness and Performance.” The American Behavioral Scientist 47(6): 766-789.

———— and A. Caza. 2013. “Virtuousness as a Source of Happiness in Organizations.” Chapter in The Oxford Handbook of Happiness. Eds. S. A. David, I. Boniwell, and A. C. Ayers. Oxford: Oxford University Press: 676-692.

————, J. E. Dutton, and R. E. Quinn. 2003a. “Foundations of Positive Organizational Scholarship.” Chapter in Positive Organizational Scholarship: Foundations of a New Discipline. Eds. K. S. Cameron, J. E. Dutton and R. E. Quinn. San Francisco, CA: Berrett-Koehler. pp. 3-13.

————, ————, and ————. Eds. 2003b. Positive Organizational Scholarship. San Francisco, CA: Berrett-Koehler.

———— and J. McNaughtan. 2014. “Positive Organizational Change.” The Journal of Applied Behavioral Science 50(4): 445-462.

———— and B. Winn. 2012. “Virtuousness in Organizations.” Chapter in The Oxford Handbook of Positive Organizational Scholarship. Eds. K. Cameron and G. M. Spreitzer. Oxford: Oxford University Press. pp. 231-243.

46



Cooperrider, D. and L. Godwin. 2012. “Positive Development: Innovation-Inspired Change in an Economy and Ecology of Strengths.” Chapter in The Oxford Handbook of Positive Organizational Scholarship. Eds. K. Cameron and G. Spreitzer. Oxford, UK: Oxford University Press. pp. 737-750.

Cunny, K. A. and M. Perri. 1991. “Single-Item versus Multiple-Item Measures of Health-Related Quality of Life.” Psychological Reports 69(1): 127-130.

Department of Labor, U. S. 2014. “Occupational Employment Statistics.” Retrieved 9/30, 2015, from http://www.bls.gov/oes/current/oes_stru.htm.

Dutton, L. E. and M. A. Glynn. 2008. “Positive Organizational Scholarship.” Chapter in Handbook of Organizational Behavior. Eds. C. Cooper and J. Barling. Thousand Oaks, CA: Sage.

Egan, T. M. and C. M. Lancaster. 2005. “Comparing Appreciative Inquiry to Action Research: OD Practitioner Perspectives.” Organization Development Journal 23(2): 29-49.

Einarsen, S. and H. Hoel. 2001. “The Negative Acts Questionnaire: Development, Validation and Revision of a Measure of Bullying at Work.” Paper presented at the 10th European Congress on Work and Organisational Psychology, Prague.

———— and B. I. Raknes. 1997. “Harassment at Work and the Victimization of Men.” Violence and Victims 12(3): 247-263.

Feeley, T. H., J. Hwang, and G. A. Barnett. 2008. “Predicting Employee Turnover from Friendship Networks.” Journal of Applied Communication Research 36(1): 56-73.

Finne, L. B., S. Knardahl, and B. Lau. 2011. “Workplace Bullying and Mental Distress – A Prospective Study of Norwegian Employees.” Scandinavian Journal of Work, Environment & Health 37: 276-287

Fox, S. and P. Spector. (Eds.). 2005. Counterproductive Work Behavior. Washington, DC: American Psychological Association.

Fredrickson, B. L. 2005. “Positive Emotions.” Chapter in Handbook of Positive Psychology. Eds. C. R. Snyder and S. J. Lopez. New York: Oxford University Press. pp. 120-134.

————. 2003. “Positive Emotions and Upward Spirals in Organizations.” Chapter in Positive Organizational Scholarship. Eds. K. S. Cameron, J. E. Dutton, and R. E. Quinn. San Francisco, CA: Berrett-Koehler. pp. 163-175.

————. 2000. “Cultivating Positive Emotions to Optimize Health and Well-Being.” Prevention and Treatment 3: 1-25.

————, R. A. Mancuso, C. Branigan, and M. M. Tugade. 2000. “The Undoing Effect of Positive Emotions.” Motivation and Emotion 24: 237-258.

Fried, Y., A. Shirom, S. Gilboa, and C. L. Cooper. 2008. “The Mediating Effects of Job Satisfaction and Propensity to Leave on Role Stress-Job Performance Relationships: Combining Meta-Analysis and Structural Equation Modeling.” International Journal of Stress Management 15(4): 305-328.

Frost, P. J., J. E. Dutton, M. C. Worline, and A. Wilson. 2000. “Narratives of Compassion in Organizations.” Chapter in Emotion in Organizations. Ed. S. Fineman. Thousand Oaks, CA: Sage. pp. 25-45.

Gittell, J. H., K. Cameron, S. Lim, and V. Rivas. 2006. “Relationships, Layoffs and Organizational Resilience: Airline Industry Responses to September 11.” Journal of Applied Behavioral Science 42(3): 300-329.

Gottman, J. 1999. “Predicting Divorce among Newlyweds from the First Three Minutes of Marital Conflict Discussions.” Family Process 38: 293-301.

47



Grant, A. M. and E. M. Campbell. 2007. “Doing Good, Doing Harm, Being Well and Burning Out: The Interactions of Perceived Prosocial and Antisocial Impact in Service Work.” Journal of Occupational and Organizational Psychology 80: 665-691.

Hart, P. M. 1994. “Teacher Quality of Work Life: Integrating Work Experiences, Psychological Distress and Morale.” Journal of Occupational and Organizational Psychology 67(2): 109-132.

————, A. J. Wearing, and B. Headey. 1995. “Police Stress and Well-Being: Integrating Personality, Coping and Daily Work Experiences.” Journal of Occupational and Organizational Psychology 68(2): 133-156.

Hasson, D. and B. B. Arnetz. 2005. “Validation and Findings Comparing VAS vs. Likert Scales for Psychosocial Measurements.” The International Electronic Journal of Health Education 8: 178-192.

Hayes, J. F. and J. Matthes. 2009. “Computational Procedures for Probing Interactions in OLS and Logistic Regression: SPSS and SAS Implementations.” Behavior Research Methods 41(3): 924-936.

Hood, J. N. and J. M. Logsdon. 2008. “Organizational Culture Impacts on Presented Forms of Unethical Bullying Behavior.” Proceedings of the International Association of Business and Society. Tampere, Finland.

Keashly, L., L. M. Trott, and L. M. MacLean. 1994. “Abusive Behavior in the Workplace: A Preliminary Investigation.” Violence and Victims 9(4): 341-357.

Keyton, J. 1999. “Relational Communication in Groups.” Chapter in The Handbook of Group Communication Theory and Research. Eds. L. Frey, D. S. Gouran, and M. S. Poole. Thousand Oaks, CA: Sage. pp. 192-222.

Leymann, H. 1990. “Mobbing and Psychological Terror at Workplaces.” Violence and Victims 5(1): 119-126.

Loerbroks, A., M. Weigl, J. Li, J. Glaser, C. Degen, and P. Angerer. 2015. “Workplace Bullying and Depressive Symptoms: A Prospective Study among Junior Physicians in Germany.” Journal of Psychosomatic Research 78: 168-172.

Logsdon, J. M., J. N. Hood, and M. Detry. 2007. “Bullying in the Workplace: Challenges to Preserving an Ethical Organization.” Proceedings of the International Association for Business and Society. 67-71.

Loo, R. 2002. “A Caveat on Using Single-Item versus Multiple-Item Scales.” Journal of Managerial Psychology 17: 68-75.

Lutgen-Sandvik, P. 2008. “Intensive Remedial Identity Work: Responses to Workplace Bullying Trauma and Stigma.” Organization 15(1): 97-119.

————. 2003. “An Exploratory Study of U.S. Workplace Bullying.” Paper presented at the National Communication Association Annual Conference, Miami Beach, FL (paper available upon request).

———— and V. McDermott. 2008a. “The Constitution of Employee-Abusive Organizations: A Communication Flows Theory.” Communication Theory 18(2): 304-333.

———— and V. McDermott. 2008b. “The Good, the Bad, and the Ugly: Negative and Positive Workplace Communication’s Effect on Work-Related Outcomes.” Paper presented at the Western States Communication Association, Denver/Boulder, CO (paper available upon request).

48



————, S. J. Tracy, and J. K. Alberts. 2007. “Burned by Bullying in the American Workplace: Prevalence, Perception, Degree, and Impact.” Journal of Management Studies 44(6): 837-862.

Luthans, F. 2002. “The Need for and Meaning of Positive Organizational Behavior.” Journal of Organizational Behavior 23: 695-706.

Magee, C., R. Gordon, L. Robinson, S. Reis, P. Caputi, and L. Oades. 2015. “Distinct Workplace Bullying Behaviors and Sleep Quality: A Person-Centred Approach.” Personality and Individual Differences 87: 200-205.

Malinauskiene, W. and S. Einarsen. 2014. “Workplace Bullying and Post-Traumatic Stress Symptoms among Family Physicians in Lithuania: An Occupation and Region Specific Approach.” International Journal of Occupational Medicine and Environmental Health 27(6): 919-932.

Mayhew, C. and D. Chappell. 2007. “Workplace Violence: An Overview of Patterns of Risk and the Emotional Stress Consequences on Targets.” International Journal of Law and Psychiatry 30: 327-339.

Meisenbach, R. J. and J. J. McMillan. 2006. “Blurring the Boundaries: Historical Developments and Future Directions in Organizational Rhetoric.” Communication Yearbook 30: 99-141.

Meyer, J. P., P. G. Irving, and N. J. Allen. 1998. “Examination of the Combined Effects of Work Values and Early Work Experiences on Organizational Commitment.” Journal of Organizational Behavior 19(1): 29-52.

Mikkelsen, E. G. and S. Einarsen. 2001. “Bullying in Danish Work-Life: Prevalence and Health Correlates.” European Journal of Work and Organizational Psychology 10(4): 393-413.

Nagy, M. S. 2002. “Using a Single-Item Approach to Measure Facet Job Satisfaction.” Journal of Occupational & Organizational Psychology 75: 77-86.

Rayner, C., H. Hoel, and C. L. Cooper. 2002. Workplace Bullying: What We Know, Who is to Blame, and What Can We Do? London: Taylor & Francis.

Rice, R. W., M. R. Frone, and D. B. McFarlin. 1992. “Work-Nonwork Conflict and the Perceived Quality of Life.” Journal of Organizational Behavior 13(2): 155-168.

Salin, D. 2003. “Ways of Explaining Workplace Bullying: A Review of Enabling, Motivating and Precipitating Structures and Processes in the Work Environment.” Human Relations 56(10): 1213-1232.

Sekerka, L. E., D. R. Comer, and L. N. Godwin. 2014. “Positive Organizational Ethics: Cultivating and Sustaining Moral Performance.” Journal of Business Ethics 119: 435-444.

Simons, S. 2008. “Workplace Bullying Experienced by Massachusetts Registered Nurses and the Relationship to Intention to Leave the Organization.” Advances in Nursing Science 31(2): E48-E59.

Thorsteinsson, E. B., R. F. Brown, and C. Richards. 2014. “The Relationship between Work-Stress, Psychological Stress and Staff Health and Work Outcomes in Office Workers.” Psychology 5(10): 1301-1311.

Wanous, J. P., A. E. Reichers, and M. J. Hudy. 1997. “Overall Job Satisfaction: How Good are Single-Item Measures?” Journal of Applied Psychology 82: 247-252.

49



Managerial Control in Mergers of Equals:

The Role of Political Skill

Rich Devine Doctoral Candidate

Florida State University [email protected]

Bruce T. Lamont

Thomas L. Williams Eminent Scholar of Strategy and Entrepreneurship Jim Moran Institute Director of Research

Florida State University [email protected]

Reginald J. Harris

Doctoral Candidate Florida State University

[email protected]

Academics across disciplines have long explored research regarding how power and status dynamics determine organizational outcomes (Child, 1972; Salancik and Pfeffer, 1974; Pfeffer and Salancik, 1978; Pfeffer, 1981; Richmond et al, 1983; Finkelstein and Hambrick, 1990; Abrahamson and Park, 1994; Thye, 2000). In mergers and acquisitions, scholars have examined how the struggle for power influences top management team (TMT) turnover (Walsh, 1988), acculturation (Nahavandi and Malekzadeh, 1988), pursuit of market power (Chatterjee, 1991), integration decisions (Haspeslagh and Jemison, 1991), and in the context of mergers of equals (MOE), how they can be better managed.

MOE involve the merging of two large, related firms of similar size (Ellis et al., 2009). They require significant strategic and operational restructuring in order to blend the two involved legacy firms (Haspeslagh and Jemison, 1991). To do so, the retention and cooperation of TMTs is needed from both firms in order for the merger to be successful. This is done to foster the cooperation of key employees in blending the firm

(50)

DEVINE, LAMONT, AND HARRIS


and recognizing cross-organizational synergies (Graebner, 2004). However, MOE are predicated on a false premise that both firms will emerge equal partners in the new combination. Yet, that is rarely if ever true (Brew, 2014). As a result of the “friendly” merger transaction, the firms will often take on a combined company name, relocate headquarters, and reconfigure management to represent equal stakes in the new company. Through preliminary discussions, the firms’ respective chief executive officers (CEOs) and TMTs will broker shared power agreements to distribute control. However, MOE oftentimes becomes a euphemism for the power struggles that subsequently ensue.

Following the consummation of MOE, it often becomes clear that any equality was in name only. Executive infighting develops as each party to the exchange pursues their own firm agendas, ideals, and initiatives. Furthermore, it becomes clear that equality was never truly part of either firm’s intent as the more dominant management team can emerge quite rapidly. For example, chairman of DaimlerChrysler, Jurgen Schrempp, later contended that he always saw Chrysler as being simply a division of Daimler and that a shared stake in the company was never his vision. This was evidenced by the exodus of Chrysler’s managers along with their prompt replacement with German counterparts (Landler, 2005). Similarly, misrepresentation prior to the AOL-Time Warner merger of equals led to a power struggle that helped provoke shareholder value destruction totaling over $200 billion. This led to the sell-off of AOL by Time Warner several years later (Davidoff, 2009; Perez-Pena, 2009).

Using power and status theory, this study contends that political skill and power differences between the merging firms’ CEOs predict who prevails as the controlling party. Power is defined as a property of a social relationship, where one party holds authority over another (Emerson, 1962). Power allows those who hold it (e.g., CEOs) to assign directives and mobilize resources toward desired objectives. Conversely, political skill is a relatively static personality trait. It is defined as an individual’s ability to understand others and use this knowledge to act in a manner that benefits personal and organizational objectives (Ferris, Treadway et al., 2005). This type of social savvy is ideal in group settings, allowing individuals to accomplish goals in a seamless matter that fosters cooperation (Ferris et al., 2007).

In focusing on political skill, this study aims to evaluate political skill at the organizational level and answer the call of recent research to focus on specific dimensions of political skill (Ferris et al., 2012; Kimura, 2014). Accordingly, the study focuses on two of its four dimensions that extant work suggest are particularly important to managerial effectiveness, social astuteness and networking ability (Ferris, Treadway et al., 2005; Kimura, 2014). This study contends that politically skilled and powerful CEOs are best at managing the uncertainty arising in large-scale merger integration. The uncertainty includes commonly occurring cultural clashes (Weber and Schweiger, 1992) as well as arguments over incongruent company visions (Zaheer et al., 2003). Powerful and politically skilled CEOs are better able to manage conflict (Smith et al., 2009) and, as this study submits, better positioned to be effective in merger integration.

Power and social dynamics often become complicated amidst executive interactions in merger integration. Particularly, MOE involve management teams of similar status (from firms of the same size and business) with no clear deference patterns, and an implied shared governance agreement that brings further confusion to the MOE setting. With clear deference patterns, it is rather straightforward as to who is in control. Managers will defer to those executives of higher status whenever there are conflicts or

51

MANAGERIAL CONTROL IN MERGERS OF EQUALS


disagreements (Pocock, 1976; Gould, 2003), which are inevitable in a complex merger setting. However, in MOE, it is never clear who is in charge due to the proclaimed equality of the two firms. Without a clear organizational leader or direction, power and politics come into play to determine which CEO and management team will prevail. In MOE, it is difficult for anything substantive to be accomplished unless a singular group uses their influence to provide direction when disagreements arise. To successfully integrate, an emergent power group from either of the legacy firms needs to take control and unify the firm in a specific direction. It is because of this social deference problem that power dynamics become important in MOE. Therefore, this paper identifies how differences across the political skill and power of the two CEOs influences the ability of either to gain control of the new combined firm.

This research contributes to the literature on executive power (Hambrick and Mason, 1984; Pitcher and Smith, 2001; Casciaro and Piskorski, 2005) and mergers of equals (Shrivastava, 1986; Olie, 1994; Meyer, 2001; Ellis and Lamont, 2004; Zaheer et al., 2003; Ellis et al., 2009; Drori et al., 2011) by theoretically delineating how power and political skill differences between the CEOs determine MOE outcomes. The MOE context is one of unclear deference patterns, but also one where emergent control is required for synergies to be realized. While there have been no applications of political skill in strategy research, it may be particularly appropriate in MOE integration. In doing so, this study sets the stage for its theoretical development. Specifically, there is one theoretical and empirical contribution from this research. The study explains how power and political skill differences between the two firms’ CEOs pre-merger predict which team emerges with control in the contested context of MOE, and data is brought to bear on the study’s predictions in this novel context.

THEORETICAL BACKGROUND AND DEVELOPMENT

Power theory is important to understanding how politics interact to influence organizational outcomes (Pfeffer, 1981). In mergers and acquisitions (M&A), disagreements and cultural clashes are quite common (Weber, 1996; Stahl and Voigt, 2008). Conflict materializes with respect to idea incongruity (Zaheer et al., 2003), high rates of TMT turnover (Weber and Schweiger, 1992; Krug and Aguilera, 2005), and employee shirking (Shapiro et al., 1995). Too much conflict among management is, of course, detrimental to firm productivity, and MOE are not unlike “normal” M&A in this regard (Amason and Sapienza, 1997). However, MOE provide a unique context of M&A where the focus can be directed on the dynamics of the power struggle between similarly positioned executives.

During MOE integration, it is not long before previously hidden agendas of the top executives involved become known. Power agreements quickly unravel and the new organization may be led in directions other than those that were originally agreed. For those who are tactful with power or political skill, it is of little consequence to renege on prior promises (Appelbaum et al., 2000). For example, incongruence in company visions or managerial motives often contribute to cultural clashes. While cultural clashes are damaging in “normal” acquisitions (Lodorfos and Boateng, 2006), they are intensified in MOE. This results from each firm’s desire to maintain its identity (Zaheer et al., 2003). The colloquialism “merger of equals,” confers emphasis upon the merger being a friendly combination of equal partners, which may itself escalate expectations. Despite

52



this, firms continue to engage in these mergers under the pretense of shared interest and value creation that they hope will result.

Research also highlights the political nature of these mergers, with work on MOE suggesting that CEOs preserve their own career trajectories at the expense of shareholder payouts (e.g., trading shareholder premiums for shared control in the combined firm; Wulf, 2004). In the prominent case of the Daimler-Chrysler merger, one of Chrysler’s largest shareholders filed suit against Daimler claiming shareholders were purposely duped for Daimler manager gains. If Daimler had planned to takeover Chrysler from the beginning, then Chrysler shareholders were denied their due premiums as a result of the “MOE” (Garsten, 2000). Though each situation is different, it brings awareness to how CEOs leverage power, political skill, and influence in different ways.

Power and political skill research has shown the effectiveness of individuals who possess these qualities in organizational settings (Ferris et al., 2007; Pfeffer, 1981). Politically skillful leaders (e.g., CEOs) are more adept in managing stressful situations (Perrewé et al., 2000), soliciting higher approval from others (Treadway et al., 2007), and are influential in the workplace (Treadway et al., 2004). In addition to the bases of power in leadership (French and Raven, 1959), political skill is an additional form of social influence that can make other power bases more effective (Ferris et al., 2007). Powerful leaders (e.g., CEOs) are equipped to enact organizational changes and affect firm performance (Combs et al., 2007). Political skill confers the interpersonal finesse to manage impressions, which is important to fostering the cooperation and coordination necessary to MOE. As such, this study expects that both power and political skill will be vital to determining which firm will emerge with control of the new combined firm. The conception of MOE as mergers without clear deference patterns allows for framing the MOE event as a situation in which CEO and firm characteristics are important in predicting the merger outcome. This study contributes to present research by elaborating the role of political skill and power in merger integration and does so by focusing on the unique context of MOE events.

HYPOTHESES

CEO Power and Firm Control

CEOs possess power apart from the influence their firm provides (Haynes and Hillman, 2010). Power refers to the relational influence of the CEO with regard to colleagues and subordinates, apart from political savviness. The form considered in this study is structural power, as this relates to the CEO’s ability to orchestrate change within, at least, their own firm. Structural power is defined as the hierarchical power that the CEO holds by way of position(s) in the organizational structure, particularly with regard to the board of directors. Concentrated power allows those at the top immense influence over organizational outcomes (Simon, 1945). Structural power is enhanced when board members are beholden to the CEO, the CEO’s tenure is longer than the board members, and when the CEO is also board chairman. In this regard, the relative power of the CEO varies across organizations and is firm specific. Structural power confers legitimacy that is particularly important to shepherding resources and influence within the organization to bring about control during uncertainty. It is the study’s expectation that CEOs will differ in their organizational effectiveness based on the power they hold in their own

53



organizations (Salancik and Pfeffer, 1974). Prior research supports the idea that power is important to predicting who will emerge and lead during merger integration (Epstein, 2004). Accordingly, this study expects that CEO power will be relevant in predicting the outcomes of MOE events:

Hypothesis 1. The CEO’s power will be positively related to their respective firm

prevailing.

Political Skill and Firm Control

Previously stated, MOE transactions require high levels of cooperation on behalf of the two firms involved. During merger integration, organizational deference patterns become unclear (Epstein, 2004). In these situations, it is expected that differences across management teams will become magnified. As a result, this study contends that political savviness on behalf of organizational leadership (e.g., CEOs) is important to reconciling these merger difficulties. In doing so, the study examines each CEO’s political skill. Political skill is a concept that has largely been studied within organizations in the organizational behavior literature (Ferris et al., 2007; Kimura, 2014). Political skill is a multi-dimensional construct that encompasses four distinct dimensions of an individual’s personality, including social astuteness, apparent sincerity, interpersonal influence, and networking ability (Ferris et al., 2005). Political skill has also been linked to a number of positive group level and intra-organizational outcomes (Ahearn et al., 2004; Perrewé et al., 2000; Treadway et al., 2007). In examining political skill of CEOs, the study seeks to further the understanding of social influence at the inter-organizational level. Furthermore, the study expects political skill to be a practically and theoretically relevant predictor of effectiveness in MOE events.

Political skill has been shown to be a predictor of increased team performance (Ahearn et al., 2004). Highly politically-skilled individuals are thought to be at an advantage in influencing subordinates, colleagues, and superiors (Treadway et al., 2007). Furthermore, individuals possessing high levels of political skill are thought to be capable of tactfully managing the impressions of those around them (Harris et al., 2007). This is valuable to exacting favorable organizational outcomes. Accordingly, the current study expects that the political skill of the CEO will be important to predicting which firm prevails in MOE events. Particularly, the focus is on the two dimensions of social astuteness and networking ability. Social astuteness is generally conceptualized as an individuals’ ability to understand others, sense hidden motives, favorably present themselves, influence others, as well as interpret body language that others convey (Ferris, Davidson et al., 2005). Networking ability generally refers to an individual’s ability to build relationships, develop connections, as well as proactively seek out such connections and meaningfully use them to advance reputational position (Ferris, Davidson et al., 2005). Correspondingly, recent research has called for dimensional analysis of political skill (Kimura, 2014), and has also specifically pointed to the importance of social astuteness and networking ability in predicting performance (Shi et al., 2011; Munyon et al., 2015). In the settings that MOE events provide, having a higher relative aptitude in relation to the skills that social astuteness and networking ability encompass would put CEOs at an advantage in exacting their preferred outcome. Individuals scoring high on these dimensions are often perceived as being able to effectively lead (Douglas and Ammeter, 2004). As a result, others will defer to such

54



individuals and look to those who are socially adept and reputationally secure to direct organizational initiatives and outcomes (Liu et al., 2007). Subsequently, this study expects these dimensions of political skill to be instrumental to MOE outcomes, thus:

Hypothesis 2a: The CEO’s social astuteness will be positively related to their

respective firm prevailing. Hypothesis 2b: The CEO’s networking ability will be positively related to their

respective firm prevailing.

METHODS

The primary source for the sample comes from an extensive search of the LexisNexis database. The search terms, “Mergers of Equals,” “Merger of Equals,” “MOEs,” and “MOE” were used. Through a comprehensive perusal of press releases, two researchers independently identified 190 unique sets of mergers of equals, comprising 381 firms. After outlining the initial sample and confirming the respective MOE outcomes through latter press releases and SEC Edgar proxy statements, 114 merger sets with complete supporting data were identified. Other data were collected from COMPUSTAT, with some executive information coming from BusinessWeek listings and SEC proxy statements. The archival data was collected in 2014 and the final dataset includes 228 unique firms with merger events that occurred within the time period starting in 1989 and ending in 2011. These data consist of publicly-traded firms across all industries, with a mean total sales value of $12.9 billion.

Dependent Variables

The dependent variable is a categorical variable that indicates which of the respective firms’ TMTs ultimately prevailed or “won” control of the merged firm three years post-deal. This variable was assessed by evaluating the congruence of five indicators: (1) CEO retention, a categorical variable indicating whether the CEO stayed with the merged firm three years out; (2) TMT retention, a count of executives listed on the firms’ annual proxy statement report three years after the deal who were originally listed as being with the respective firm one year pre-merger; (3) Firm relocation, observance of the location where the newly merged firm became established; (4) Firm name, observance of the effective name change from the former names of the pre-merged firms; and, (5) Board member retention, a count of how many board members from each of the pre-merged firms were still with the merged firm three years post-merger. The three year timeline was chosen since it often takes a significant amount of time for the dynamics of any power and political motivations to unfold. Three years allows for the retroactive evaluation of who won control based on the five indicators. The firms were coded with either a “0” or a “1” indicating which firm won or lost and was independently assessed by two researchers relative to the established criteria. Across the two raters, the inter-rater reliability was greater than 0.90 and there was complete consensus based on the objective criteria for which firm won in all but a few cases. In these few cases, greater weight was assigned to the importance of CEO retention, executive retention, and firm re-location. This allowed for informed assessments, given that CEO and team retention most closely underpin the theorizing.

55



Independent Variables

Political skill. CEO political skill is measured by focusing on two of the four focal political skill dimensions. Specifically, social astuteness and networking ability, which are believed to be relevant to managerial effectiveness and MOE events (Haspeslagh and Jemison, 1991; Ferris, Davidson et al., 2005; Kimura, 2014). Social astuteness was measured by tracking the career progression of CEOs from the start of their careers to their present positions. Research by Treadway et al. (2007) found subordinate political skill favorably influenced supervisors’ job evaluations. While Ferris, Davidson et al. (2005) suggested that social astuteness may be the most valuable to influencing others’ perceptions of performance. Accordingly, it is reasonable to expect that social astuteness can be tapped by evaluating progression through job promotions. Social astuteness was evaluated with respect to: (1) time it took from start of career to obtaining first executive position; (2) time it took from start of career to obtaining first CEO position; (3) time from first executive position to first CEO position; and, (4) time spent within the current company before obtaining the CEO position. Networking ability was assessed by measures believed to capture a CEO’s ability to build connections. Specifically, networking ability was measured through the CEO’s number of: (1) board committees; (2) outside directorships; (3) nonprofit directorships; and, (4) executive titles held. Exploratory factor analysis (principal axis factoring with oblimin rotation) was used to analyze the factor structure since the political skill items are believed to be correlated (Ferris, Davidson et al., 2005). Through factor analysis on the eight referenced items believed to comprise dimensions of political skill, some of the indicators were dropped to arrive at a parsimonious result. Through the analysis, a two-factor structure emerged with eigenvalues at 1.648 and 1.270 with 33% and 25% of the variance explained for social astuteness and networking ability, respectively. For social astuteness, time to first executive position and time to first CEO position loaded highly on the first factor (0.929 and 0.589). The indicators for networking ability; outside directorships, nonprofit directorships, and executive titles, displayed strong loadings on a second factor (0.405, 0.524, and 0.292). Accordingly, the indicators were standardized and factor base scores were created for variables representing social astuteness and networking ability.

CEO power. Indicators of CEO structural power were used to capture this variable. Following Haynes and Hillman (2010), the study examined: (1) ratio of nonaffiliated directors to total company directors; (2) ratio of directors who began their tenure after the CEO to the total company directors; and, (3) CEO duality (i.e., if the CEO also served as board chairman). From conducting exploratory factor analysis on the three indicators (principal axis factoring with varimax rotation), a two factor structure emerged with eigenvalues at 1.28 and 1.05 (41.6% and 35.1% variance explained). The indicators for ratio of nonaffiliated directors to total company directors and ratio of directors who began their tenure after the CEO to the total company directors loaded on the first factor (0.50 and 0.54) and CEO duality loaded on the second factor (0.46). The indicators for the first factor were standardized and combined to create a variable for CEO structural power. The indicator for CEO duality was included in the analysis as a separate single-item variable. It is considered a measure of power if the CEO additionally holds the position of board chairman. As such, to control for its influence it is coded as a dummy variable with “1” representing CEOs who held the additional position.

56



Control Variables

Firm size. The size of the respective pre-merged firms was calculated by taking the three-year average of the firm’s total assets pre-merger. Since each firm represented a case in the sample and due to MOE transactions being between companies of similar size, relative size was not considered to be a viable indicator. Board size. A count of the number of directors that each firm’s board had one year prior to the merger. Firms with a larger number of board members may be able to exact more influence in the combined firm post-acquisition. Board tenure. The average number of years that each firm’s board members held their position one year prior to the merger. Longer tenured board members are believed to hold more “board capital” and potentially to build up greater access to resources and social connections over the course of their careers. TMT and board equity holdings. The percentage of total company shares held by firms’ respective top executives and board members one year prior to the merger. Firms with greater ownership stake at risk are more vested in the proceedings of the acquisition pre, during, and post-deal. CEO equity holdings. The percentage of total equity holdings for the focal firm that the CEO held one year prior to the merger. Debt to asset ratio. The ratio of the three-year average long-term debt divided by the firm’s three-year average total assets. Firms carrying a relatively higher amount of debt could be left more vulnerable before and during the merger process. TMT tenure. The tenure of the respective TMTs was calculated based on the average time executives had spent with the company as of one year pre-merger. Prior performance. Performance of each of the respective firms was calculated by determining the three-year average of their return on assets prior to the merger (Harrison et al., 1991; Ellis et al., 2011). Since mergers of equals involve firms nested within the same industry, their relative performance pre-merger was uncorrected for industry averages.

ANALYSIS AND RESULTS

To conduct appropriate analyses, some of the factor structures were explored and

the data was analyzed using SPSS 22.0. These data were analyzed by employing binary logistic regression in SPSS; results are reported in the following section. Log transformations were taken for the variables firm size, board ownership percentage, CEO ownership percentage, and debt to asset ratio in order to correct for non-normal distributions. In assessing the variance inflation factors (VIF) none of the variables had a VIF greater than 2.988, which is well below the recommended cut-off point. Additionally, the signs of the parameter estimates remained stable across the models.

The descriptive statistics as well as the bivariate correlations for the variables in the full model are reported in Table 1. Preliminarily, there are many significant correlations amidst the variables. However, none displays any significant bivariate correlations with the dependent variable (winner-loser). Unstandardized regression coefficients along with their standard errors are reported in Table 2. Model 1 shows the coefficients for the baseline model that includes the study’s control variables. For model 2, the focal independent variables were included to find that Hypothesis 2a (p < 0.01) and Hypothesis 2b (p < 0.05) receive support. Hypothesis 2a argues that socially astute CEOs are best positioned to prevail in a MOE situation. As social astuteness increases by one, there is a 0.25 increase in the log-odds of the CEO’s firm prevailing. Stated differently, for a one unit increase in social astuteness the odds are 1.29 greater for the

57



CEO’s firm to prevail. The positive and significant coefficient suggests that these CEOs are apt to gain control after the merger event. In Hypothesis 2b, the study similarly argues that CEO networking ability will be positively related to prevailing in the MOE, which is found to be positive and significant (p < 0.05). Likewise, for every one unit increase in networking ability, there is a 0.17 increase in the log-odds of the CEO’s firm prevailing (or a 1.19 times larger odds increase). Although Hypotheses 2a (p < 0.01) and 2b (p < 0.10) received support in the model, Hypothesis 1 did not receive support in the predicted direction. Interestingly, had there been a prediction for the negative effect of CEO power there would have been a significant result (p < 0.10) for both indicators for power (structural power and CEO duality). This could mean that while the CEO may be powerful, such CEOs are more likely to bring a set of demands coupled with a potentially coercive approach that does not go over well with the high level of cooperation needed between sets of also powerful top executives. To address other possible interpretations, the study tested for an interaction effect between power and political skill as an ad hoc analysis. However, support was not found for this alternative model.1 Overall, Hypotheses 2a and 2b were supported, while Hypothesis 1 was not supported. The findings emphasize the importance of political skill in interpersonal contexts.

1 Thanks to an anonymous reviewer for suggesting this possibility and the need to address it.

58



Tab

le 1

D

escr

ipti

ve S

tati

stic

s an

d C

orre

lati

ons

Var

iabl

es

Mea

n s.

d.

1 2

3 4

5

1.

Win

ner-

Los

er

0.50

0.

50

2.

B

oard

siz

e10

.61

4.38

0.

07

3.

Boa

rd t

enur

e 7.

69

3.57

-0

.01

0.08

4.

Soci

al a

stut

enes

s -0

.04

1.81

0.

09

-0.1

8* -0

.16*

5.

Net

wor

king

abi

lity

-0.3

6 1.

96

0.03

0.

15*

-0.0

3 -0

.08

6.

T

MT

ten

ure

8.56

5.

86

-0.1

0 0.

13

0.34

**

0.01

-0

.08

7.

Stru

ctur

al p

ower

0.

01

1.56

0.

03

0.46

**

0.14

* -0

.12†

0.18

* 8.

Fi

rm s

ize

7.59

2.

32

-0.0

0 0.

66**

0.

05

-0.0

7 0.

28**

9.

Boa

rd o

wne

rshi

p %

0.

40

1.90

-0

.08

-0.0

9 0.

01

-0.0

5 0.

03

10.

CE

O o

wne

rshi

p %

0.

03

0.08

-0

.07

-0.2

7**

-0.0

3 0.

03

-0.1

2† 11

. D

ebt t

o as

sets

rat

io

0.15

0.

14

-0.0

5 -0

.05

-0.1

1 -0

.06

0.28

**

12.

Prio

r pe

rfor

man

ce

-0.0

2 0.

25

0.02

0.

19**

0.

15*

-0.0

6 0.

02

13.

CE

O d

ualit

y

0.62

0.

49

-0.0

8 0.

17*

-0.0

8 -0

.05

0.25

**

N =

193

. † p <

0.1

0, * p

< 0

.05,

** p

< 0

.01.

(tw

o-ta

iled

test

)

59



Tab

le 1

(con

’t)

Des

crip

tive

Sta

tist

ics

and

Cor

rela

tion

s V

aria

bles

6

7 8

9 10

11

12

1.

Win

ner-

Los

er

2.

B

oard

siz

e

3.

Boa

rd t

enur

e

4.

Soci

al a

stut

enes

s

5.

Net

wor

king

abi

lity

6.

T

MT

ten

ure

7.

St

ruct

ural

pow

er

-0.0

1

8.

Fi

rm s

ize

0.12

0.

47**

9.

Boa

rd o

wne

rshi

p %

-0

.08

-0.1

0 -0

.08

10.

CE

O o

wne

rshi

p %

-0

.07

-0.3

6**

-0.2

5**

0.13

†

11.

Deb

t to

asse

ts r

atio

-0

.05

-0.0

2 0.

24**

-0

.20**

-0

.03

12.

Prio

r pe

rfor

man

ce

0.16

* 0.

19

0.37

**

-0.0

2 -0

.07

0.15

*

13.

CE

O d

ualit

y

-0.0

3 -0

.05

0.22

**

-0.0

3 0.

02

0.20

**

-0.0

4 N

= 1

93. † p

< 0

.10,

* p <

0.0

5, **

p <

0.0

1. (t

wo-

taile

d te

st)

60



Table 2 Results for Logistic Regression

Model I Model II

Variables B / s.e. B / s.e.

Intercept 0.06 (0.85) 0.19 (0.94)

Control

Firm size -0.04 (0.12) -0.08 (0.13)

Board ownership % 3.50 (2.51) 2.41 (2.59)

CEO ownership % -3.71 (3.53) -3.40 (3.66)

D/A ratio -0.38 (1.23) -0.57 (1.30)

Board size 0.05 (0.05) 0.10 (0.06)*

Board tenure 0.02 (0.05) 0.06 (0.06)

TMT tenure -0.04 (0.03)† -0.07 (0.04)*

Prior performance -0.43 (0.67) 0.50 (0.71)

Independent

Social astuteness — 0.25 (0.11)**

Networking ability — 0.17 (0.10)*

CEO duality — 0.53 (0.40)

Structural power — -0.18 (0.15) Cox and Snell R

square 0.04 0.10

Nagelkerke R square 0.05 0.13

Model ² 6.23 16.48

Log-likelihood 213.12 202.88 Overall correct

classifications % 55.30

61.60

n = 159. † p < 0.10, * p < 0.05, ** p < 0.01. (one-tailed test)

DISCUSSION

Through a review of press accounts and the sparse literature on MOE, this study aimed to consider the role of CEO political skill and power in determining MOE outcomes. In considering MOE events, this study portrays how status deference creates a situation in which social influence (e.g., political skill and power) affects merger outcomes. Status deference amongst TMTs creates a setting (e.g., MOE) which is primed for a power struggle between the respective firms. Recognizing the status similarities between the firms and their TMTs, the study relies on power and status theory to determine how CEO political skill and power affect power dynamics in the context of MOE events. Focusing on the unique situation which MOE provide, the study describes

61



how CEO characteristics are likely to influence who prevails. In doing so, the study predicts how CEO political skill and power influence MOE transactions. Furthermore, this study is one of the first to examine how political skill affects power dynamics within M&A contexts.

In examining how CEO political skill provides an advantage in MOE transactions, this study contributes to theory on power and status as well as the rich literature on CEO behavior. Essential to the depiction of MOE as scenarios in which power dynamics are likely to play out is the idea of status deference. Status deference suggests that managers of lower status will defer to those of higher status, thereby providing clear leadership. There are no clear status differences between the CEOs in MOE. As a result, there are often times blurred lines as to who is exactly in control; and it can be difficult to unify the firm in a definitive direction. In order for the newly combined firm to accomplish anything substantive, it is necessary for someone to come forward to establish clear strategy initiatives and properly guide the firm (Pfeffer, 1981). By controlling for situational aspects (i.e., firm size and performance) and group level characteristics (i.e., tenure and board size), this study examined the importance of CEO political skill and power in influencing which CEO prevails.

This study contributes to the extant literature on CEO behavior by explaining how power manifests in the context of MOE. Power and politics in organizations are complex (Pfeffer and Salancik, 1978; Pfeffer, 1981). However, in the context of MOE, this study more definitively discerns how top executive characteristics affect organizational outcomes (Finkelstein, 1992) by examining the direction of who wins. As a result, CEO influence is better examined in MOE contexts. Furthermore, it is interesting to consider that CEO political skill may be a better predictor of resource access and social capital than CEO power.

Politically skilled individuals exact considerable influence on a number of outcomes in organizations (Ferris et al., 2007). While politically skilled leaders effect important outcomes (Ahearn et al., 2004), this study shows the importance of political skill relative to CEO power. This may be attributable to political skill simply being more important than power, power working against a CEO, or the winning firm potentially having better governance mechanisms. A well-managed firm pre-deal is likely to influence the CEO’s efficacy during merger events. An additional explanation is that power can often denote autonomy (Adams et al., 2005), which is likely to be ineffective in MOE where cooperation of power individuals is necessary. The research topics for the future are numerous.

There arises several implications worthy of consideration from the review of power dynamics that occur following MOE transactions. First, CEO political skill has an influence on inter-organizational outcomes, and it would be interesting to examine this argument in other contexts (other than MOE). However, power dynamics are complex and MOE events provide a unique setting for study. A key supposition is that a setting is created where deference patterns are unclear and a struggle to leverage power progresses as a result. Although, acquisitions may also be contentious regardless of clear deference patterns (Weber, 1996). Retained managers and employees often experience dissatisfaction with sudden changes in management, company direction, and organizational climate (Walsh, 1989). This makes it difficult for acquisitions to be cleanly executed even under “normal” assumptions, which underscores how power dynamics become confounded in MOE. In this regard, political skill offers better explanatory

62



power. Specifically, politically skillful individuals do not need to be at the node of power (e.g., CEOs and top executives) to effect meaningful outcomes. When politically skilled individuals are in these positions, they are able to produce favorable outcomes for themselves as well as manage others more effectively.

This study has considered ways in which CEO political skill and power manifest in the context of MOE and future research should continue to investigate these merger events that hold high stakes for multiple stakeholders. Despite being relatively infrequent merger events, they typically involve large firms (of great value) within related industries. This implies that there are a large number of stakeholders with a vested interest in the combined firm’s success. As such, it is important to understand MOE events. It is also important to understand how to better ensure the cooperation and retention of key individuals to allow for effective acquisition integration. To meet this goal, it may require a future reconsideration of the shared power agreements for MOE. Clearly drafting and monitoring a desired course of action (and succession) for the firm during and post integration could prove beneficial. In following, future research should consider how contract agreements affect MOE and whether there is a pattern for success that depends on firm choice of underwriters (Higgins and Gulati, 2003). With retention and cooperation imperative to MOE success, future research may wish to examine how “time to exit” for key executives may be correlated with firm performance.

References

Abrahamson, E. and C. Park. 1994. “Concealment of Negative Organizational Outcomes: An Agency Theory Perspective.” Academy of Management Journal 37: 1302-1334.

Adams, R. B., H. Almeida, and D. Ferreira. 2005. “Powerful CEOs and Their Impact on Corporate Performance.” Review of Financial Studies 18: 1403-1432.

Ahearn, K. K., G. R. Ferris, W. A. Hochwarter, C. Douglas, and A. P. Ammeter. 2004. “Leader Political Skill and Team Performance.” Journal of Management 30: 309-327.

Amason, A. C. and H. J. Sapienza. 1997. “The Effects of Top Management Team Size and Interaction Norms on Cognitive and Affective Conflict.” Journal of Management 23: 495-516.

Appelbaum, S. H., J. Gandell, H. Yortis, S. Proper, and F. Jobin. 2000. “Anatomy of a Merger: Behavior of Organizational Factors and Processes Throughout the Pre-During-Post-Stages (part 1).” Management Decision 38: 649-662.

Brew, A. 2014, June 5. “Why Corporate Mergers of Equals Almost Never Work.” Retrieved from http://www.forbes.com/sites/forbesleadershipforum/2014/06/05/why-corporate-mergers-of-equals-almost-never-work/

Casciaro, T. and M. J. Piskorski. 2005. “Power Imbalance, Mutual Dependence, and Constraint Absorption: A Closer Look at Resource Dependence Theory.” Administrative Science Quarterly 50: 167-199.

Chatterjee, S. 1991. “Gains in Vertical Acquisitions and Market Power: Theory and Evidence.” Academy of Management Journal 34: 436-448.

Child, J. 1972. “Organizational Structure, Environment and Performance: The Role of Strategic Choice.” Sociology 6: 1-22.

63



Combs, J. G., D. J. Ketchen, A. A. Perryman, and M. S. Donahue. 2007. “The Moderating Effect of CEO Power on the Board Composition–Firm Performance Relationship.” Journal of Management Studies 44: 1299-1323.

Davidoff, S. M. 2009, February, 17. “The Return of the Mergers of Equals.” Retrieved from http://dealbook.nytimes.com/2009/02/17/the-return-of-the-merger-of-equals/

Douglas, C. and A. P. Ammeter. 2004. “An Examination of Leader Political Skill and Its Effect on Ratings of Leader Effectiveness.” The Leadership Quarterly 15: 537-550.

Drori, I., A. Wrzesniewski, and S. Ellis. 2011. “Cultural Clashes in a “Merger of Equals”: The Case of High Tech Start Ups.” Human Resource Management 50: 625-649.

Ellis, K. M. and B. T. Lamont. 2004. “‘Ideal’ Acquisition Integration Approaches in Related Acquisitions of Equals: A Test of Long-Held Beliefs.” Advances in Mergers and Acquisitions 3: 81-102.

–––––––, T. H. Reus, and B. T. Lamont. 2009. “The Effects of Procedural and Informational Justice in the Integration of Related Acquisitions.” Strategic Management Journal 30: 137-161.

–––––––, T. H. Reus, B. T. Lamont, and A. L. Ranft. 2011. “Transfer Effects in Large Acquisitions: How Size-Specific Experience Matters.” Academy of Management Journal 54: 1261-1276.

Emerson, R. M. 1962. “Power-Dependence Relations.” American Sociological Review 27: 31-41.

Epstein, M. J. 2004. “The Drivers of Success in Post-Merger Integration.” Organizational Dynamics 33: 174-189.

Ferris, G. R., S. L. Davidson, and P. L. Perrewé. 2005. Political Skill at Work: Impact on Work Effectiveness. Mountainview, CA: Davies-Black Publishing.

–––––––, D. C. Treadway, R. L. Brouer, and T. P. Munyon. 2012. “Political Skill in the Organizational Sciences.” Politics in Organizations: Theory and Research Considerations Eds. G. R. Ferris and D. C. Treadway. New York, NY: Routledge/Taylor and Francis. pp. 487-529.

–––––––, D. C. Treadway, R. W. Kolodinsky, W. A. Hochwarter, C. J. Kacmar, C. Douglas, and D. Frink. 2005. “Development and Validation of the Political Skill Inventory.” Journal of Management 31: 126-152.

–––––––, D. C. Treadway, P. L. Perrewé, R. L. Brouer, C. Douglas, and S. Lux. 2007. “Political Skill in Organizations.” Journal of Management 33: 290-320.

Finkelstein, S. 1992. “Power in Top Management Teams: Dimensions, Measurement, and Validation.” Academy of Management Journal 35: 505-538.

––––––– and D. C. Hambrick. 1990. “Top-Management-Team Tenure and Organizational Outcomes: The Moderating Role of Managerial Discretion.” Administrative Science Quarterly 35: 484-503.

French, J. R. and B. Raven, 1959. “The Bases of Social Power.” Chapter in Studies in Social Power. Ed. D. Cartwright. Ann Arbor, MI: Institute for Social Research.

Garsten, E. 2000, December, 27. “DaimlerChrysler: What Went Wrong?” Retrieved from http://money.cnn.com/2000/12/27/europe/chrysler_outlook/

Gould, R. V. 2003. Why do Networks Matter? Rationalist and Structuralist Interpretations. Oxford, UK: Oxford University Press.

Graebner, M. E. 2004. “Momentum and Serendipity: How Acquired Leaders Create Value in the Integration of Technology Firms.” Strategic Management Journal 25: 751-777.

64



Hambrick, D. C. and P. A. Mason. 1984. “Upper Echelons: The Organization as a Reflection of Its Top Managers.” Academy of Management Review 9: 193-206.

Harris, K. J., K. M. Kacmar, S. Zivnuska, and J. D. Shaw. 2007. “The Impact of Political Skill on Impression Management Effectiveness.” Journal of Applied Psychology 92: 278.

Harrison, J. S., M. A. Hitt, R. E. Hoskisson, and R. D. Ireland. 1991. “Synergies and Post-Acquisition Performance: Differences versus Similarities in Resource Allocations.” Journal of Management 17: 173-190.

Haspeslagh, P. C. and D. B. Jemison. 1991. Managing Acquisitions: Creating Value through Corporate Renewal. New York, NY: The Free Press.

Haynes, K. T. and A. Hillman. 2010. “The Effect of Board Capital and CEO Power on Strategic Change.” Strategic Management Journal 31: 1145-1163.

Higgins, M. C. and R. Gulati. 2003. “Getting off to a Good Start: The Effects of Upper Echelon Affiliations on Underwriter Prestige.” Organization Science 14: 244-263.

Kimura, T. 2014. “A Review of Political Skill: Current Research Trend and Directions for Future Research.” International Journal of Management Reviews.

Krug, J. A. and R. Aguilera. 2005. “Top Management Team Turnover in Mergers and Acquisitions.” Advances in Mergers and Acquisitions 4: 123-151.

Landler, M. 2005, July, 29. “Shake-up at Daimler Chrysler.” Retrieved from http://www.nytimes.com/2005/07/29/business/shakeup-at-daimlerchrysler.html?_r=0

Liu, Y., G. R. Ferris, R. Zinko, P. L. Perrewé, B. Weitz, and J. Xu. 2007. “Dispositional Antecedents and Outcomes of Political Skill in Organizations: A Four-Study Investigation with Convergence.” Journal of Vocational Behavior 71: 146-165.

Lodorfos, G. and A. Boateng. 2006. “The Role of Culture in the Merger and Acquisition Process: Evidence from the European Chemical Industry.” Management Decision 44: 1405-1421.

Meyer, C. B. 2001. “Allocation Processes in Mergers and Acquisitions: An Organizational Justice Perspective.” British Journal of Management 12: 47-66.

Munyon, T. P., J. K. Summers, K. M. Thompson, and G. R. Ferris. 2015. “Political Skill and Work Outcomes: A Theoretical Extension, Meta Analytic Investigation, and Agenda for the Future.” Personnel Psychology 68: 143-184.

Nahavandi, A. and A. R. Malekzadeh. 1988. “Acculturation in Mergers and Acquisitions.” Academy of Management Review 13: 79-90.

Olie, R. 1994. “Shades of Culture and Institutions in International Mergers.” Organization Studies 15: 381-405.

Perez-Pena, R. 2009, May, 28. “Time Warner Backs AOL Spinoff.” Retrieved from http://www.nytimes.com/2009/05/29/business/media/29warner.html

Perrewé, P. L., G. R. Ferris, D. D. Frink, and W. P. Anthony. 2000. “Political Skill: An Antidote for Workplace Stressors.” The Academy of Management Executive 14: 115-123.

Pfeffer, J. 1981. Power in Organizations. Marshfield, MA: Pitman. ––––––– and G. R. Salancik. 1978. The External Control of Organizations: A Resource

Dependence Perspective. New York, NY: Harper & Row. Pitcher, P. and A. D. Smith. 2001. “Top Management Team Heterogeneity: Personality,

Power, and Proxies.” Organization Science 12: 1-18. Pocock, J. G. 1976. “The Classical Theory of Deference.” The American Historical Review

81: 516-523.

65



Richmond, V. P., J. P. Wagner, and J. C. McCroskey. 1983. “The Impact of Perceptions of Leadership Style, Use of Power, and Conflict Management Style on Organizational Outcomes.” Communication Quarterly 31: 27-36.

Salancik, G. R. and J. Pfeffer. 1974. “The Bases and Use of Power in Organizational Decision Making: The Case of a University.” Administrative Science Quarterly 19: 453-473.

––––––– and –––––––. 1978. “A Social Information Processing Approach to Job Attitudes and Task Design.” Administrative Science Quarterly 23: 224-253.

Shapiro, D. L., R. J. Lewicki, and P. Devine. 1995. “When do Employees Choose Deceptive Tactics to Stop Unwanted Organizational Change?: A Relational Perspective.” Research on Negotiation in Organizations 5: 155-184.

Shi, J., Z. Chen, and L. Zhou. 2011. “Testing Differential Mediation Effects of Sub-Dimensions of Political Skills in Linking Proactive Personality to Employee Performance.” Journal of Business and Psychology 26: 359-369.

Shrivastava, P. 1986. “Postmerger Integration.” Journal of Business Strategy 7: 65-76. Simon, H. A. 1945. Administrative Behavior. Cambridge, UK: Cambridge University

Press. Smith, A. D., D. A. Plowman, D. Duchon, and A. M. Quinn. 2009. “A Qualitative Study

of High-Reputation Plant Managers: Political Skill and Successful Outcomes.” Journal of Operations Management 27: 428-443.

Stahl, G. K. and A. Voigt. 2008. “Do Cultural Differences Matter in Mergers and Acquisitions? A Tentative Model and Examination.” Organization Science 19: 160-176.

Thye, S. R. 2000. “A Status Value Theory of Power in Exchange Relations.” American Sociological Review 65: 407-432.

Treadway, D. C., W. A. Hochwarter, G. R. Ferris, C. J. Kacmar, C. Douglas, A. P. Ammeter, and M. R. Buckley. 2004. “Leader Political Skill and Employee Reactions.” The Leadership Quarterly 15: 493-513.

–––––––, G. R. Ferris, A. B. Duke, G. L. Adams, and J. B. Thatcher. 2007. “The Moderating Role of Subordinate Political Skill on Supervisors’ Impressions of Subordinate Ingratiation and Ratings of Subordinate Interpersonal Facilitation.” Journal of Applied Psychology 92: 848.

Walsh, J. P. 1988. “Top Management Turnover Following Mergers and Acquisitions.” Strategic Management Journal 9: 173-183.

–––––––. 1989. “Negotiations and Their Impact upon Target Company Top Management Turnover.” Strategic Management Journal 10: 307-322.

Weber, Y. 1996. “Corporate Cultural Fit and Performance in Mergers and Acquisitions.” Human Relations 49: 1181-1202.

––––––– and D. M. Schweiger. 1992. “Top Management Culture Conflict in Mergers and Acquisitions: A Lesson from Anthropology.” International Journal of Conflict Management 3: 285-302.

Wulf, J. 2004. “Do CEOs in Mergers Trade Power for Premium? Evidence from ‘Mergers of Equals’.” Journal of Law, Economics, and Organization 20: 60-101.

Zaheer, S., M. Schomaker, and M. Genc. 2003. “Identity versus Culture in Mergers of Equals.” European Management Journal 21: 185-191.

66



Formal or Informal Mentoring: What Drives Employees

to Seek Informal Mentors?

Daniel T. Holt Associate Professor


Gergana Markova

Associate Professor Wichita State University

[email protected]

Andrew J. Dhaenens Graduate Teaching Assistant


Laura E. Marler

Associate Professor Mississippi State University

[email protected]

Sharon G. Heilmann Professor

Wright State University [email protected]

Broadly speaking, a mentoring relationship occurs when a more experienced,

senior employee (mentor) takes an active interest in and encourages a less experienced, junior employee (protégé) by providing support, direction, and feedback regarding career plans and personal development (e.g., Eby et al., 2008; Ragins and Kram, 2007). Mentoring is thought to be beneficial for all involved. For protégés, mentoring has been positively related to increased job satisfaction, greater promotion possibilities,

(67)

FORMAL OR INFORMAL MENTORING


opportunities for increased pay, higher self-esteem, and a heightened sense of professional competence (cf., Allen et al., 2004). For mentors, the positive feelings generated by playing a key role in a protégé’s development can lead to more productive work and greater commitment (Chun et al., 2012). In addition, mentors may feel that their identification of and support for up-and-coming stars will increase their own chances for further advancement (Kram, 1988). Several have suggested that the organization benefits as well, as mentoring increases the speed with which protégés learn and reduces the likelihood that protégés will leave the organization voluntarily (e.g., Dulebohn et al., 2012; Scandura and Viator, 1994).

Because of the positive effects of mentoring, many organizations, including 71% of the Fortune 500 (Bridgeford, 2007), have adopted formal mentoring programs in the hopes of cultivating meaningful developmental relationships. These formal programs develop mentoring relationships through the assistance of the organization, establishing guidelines that outline how the relationships are formed and the roles and responsibilities for those involved (Burke and McKeen, 1989). While well intended, as mentoring becomes more formal, research suggests that the level of interaction as well as the quality of information shared decreases (Johnson and Anderson, 2009), resulting in fewer long-term advantages for protégés, mentors, and organizations when compared to mentoring relationships that develop naturally and voluntarily, based on perceived competence and interpersonal comfort (e.g., Chao et al., 1992; Eby et al., 2007; Ragins and Cotton, 1999; Underhill, 2006). In cases where formal mentoring is less than fully effective, protégés often seek an additional informal mentor to realize those benefits that are not being gained as part of the formal program.

Despite this understanding, little is known about the specific conditions that lead a protégé with a formal mentor to supplement that relationship by finding his or her own informal mentor (cf., Allen et al., 2006). This study sheds light on this by empirically examining factors that lead a protégé to look for an informal mentor. Specifically, using multi-source data, the dynamics of the mentor-protégé relationship are captured by examining the quality of leader-member exchange, the amount of work-related contact time, and the similarity between the formal mentor and the protégé. Additionally, protégé performance is investigated as a predictor of the identification of an informal mentor. In doing so, this study responds to recent calls for work that extends researchers’ understanding of what actually occurs in mentoring relationships that affects the cultivation of a positive relationship whether it be formal or informal (Eby et al., 2013; Weinberg and Lankau, 2011). A better understanding of the reasons protégés seek informal mentors, especially when they already have an assigned mentor available, extends knowledge with regard to what makes a mentoring relationship positive so that more effective, high-quality mentoring programs can be facilitated.

This phenomenon is examined in a unique context, the U.S. Air Force. As part of the organization’s formal mentoring program, a mentor is described as “a trusted counselor or guide” with directives placing the primary responsibility for this activity on supervisors (U. S. Air Force Policy Directive 36-34, 2000: 1). The organization believes that appointing supervisors as formal mentors has several benefits including frequent mentor–protégé interaction and the mentors’ ability to share job-specific expertise. At the same time, junior members (protégés) are encouraged to identify informal mentors outside of their supervisor, providing a unique opportunity to examine a protégé’s decision to supplement a formal mentoring relationship.

68

HOLT, MARKOVA, DHAENENS, MARLER, AND HEILMANN


FORMAL MENTOR-PROTÉGÉ RELATIONSHIP Relationship Quality and Mentoring

When junior employees have access to a formal mentoring program but can choose an informal mentor, the quality of the relationship with their formal mentor likely determines whether or not junior employees choose an informal mentor. Given that the formal mentor in the system being examined is a direct supervisor (a practice common in formal programs; Allen et al., 2008; Ragins et al., 2000), leader member exchange (LMX) represents the quality of the working relationship that the formal mentor has with each subordinate (or, protégé). High-quality LMX, which indicates the subordinate is working with the supervisor to take on greater roles and responsibilities, comes about as a result of repeated high levels of performance that facilitate trust, motivation, and mutual respect (Liden and Graen, 1980). This high-quality relationship results in reduced turnover, increased performance, higher organizational commitment, and better career progression (Dulebohn et al., 2012). As suggested by Scandura and Schriesheim (1994), high LMX would motivate a protégé to maintain the formal mentoring relationship and entrust his or her career choices to the senior person. On the other hand, low LMX occurs when subordinates only fulfill the exact obligations of their contract with little interest in expanding their roles. Low LMX can result from poor job performance but can also be a result of a relationship that has not yet matured, such as the one between a supervisor and a newly-hired subordinate. Provided a relationship has developed, when LMX is low, subordinates may disconnect from their supervisor and therefore never fully realize their potential in the organization (Graen and Uhl-Bien, 1995). Thus, low LMX suggests that trust and respect are lacking; as a result, the protégé is likely to seek advice and social support outside of the formal mentor (Scandura and Schriesheim, 1994). Consistent with the theoretical underpinnings of LMX theory, it is hypothesized that:

Hypothesis 1: Junior members who report having low LMX with their formal

mentor are more likely to identify an informal mentor. Work-related Contact Time and Mentoring

As mentoring refers to a relationship between two organizational members, it stands to reason that the time spent cultivating the relationship would influence the satisfaction with the relationship as well as the outcomes that are derived. Kram (1988) suggested that mentoring relationships evolve through stages as trust and confidence in one another are built; the more time a mentor and a protégé spend together, the more quickly trust and confidence develop. Mentors in formal mentoring programs, however, report less motivation to fully invest their time and effort. Johnson and Anderson (2009) indicate that the more formalized a mentoring program becomes the less likely mentors are to fully participate. Ensher and Murphy (1997) found that the time summer interns spent with their mentors had a significant impact on their perceived satisfaction with their mentor and the amount of contact time was significantly correlated to protégés’ and mentors’ intentions to continue their relationships. In a similar vein, employees who spend more time with their formal mentors would be less likely to perceive a need to seek informal mentoring. In fact, studies indicate that the amount and frequency of

69



contact time between members of mentoring relationships have positive impacts on the relationships, members’ perceived similarity, and the protégé’s performance (e.g., Dansereau et al., 1975; Liden and Graen, 1980; Turban and Jones, 1988). Therefore, if the formal mentor spends too little time with a protégé, the employee would likely seek mentoring elsewhere. Thus, it is hypothesized that:

Hypothesis 2: Less work-related contact time with a formal mentor will be associated

with junior member’s identification of an informal mentor. Similarity and Mentoring

Traditionally, informal mentoring relationships come about as part of a shared attraction between a protégé and mentor because of recognized similarities (Ensher and Murphy, 1997; Ensher et al., 2002; Riordan, 2000). One concern with formal mentoring programs, therefore, is that a quality relationship might not be created without a certain amount of similarity between assigned members. In formal relationships, mentors may not be assigned protégés with whom they have things in common, in which case perceived differences between the mentor and protégé could negatively affect the potential outcomes of the relationship (Ensher and Murphy, 1997). Multiple studies have suggested that personal characteristics like race and gender play a key role in the development and subsequent success of mentoring relationships (e.g., Burke, 1984; Ensher and Murphy, 1997; Feldman et al., 1999; Noe, 1988; Thomas, 1990). These results are consistent with the similarity-attraction paradigm which states that people who have a great deal in common report stronger feelings of attraction toward one another (Byrne, 1971). In fact, Chao et al. (1992) suggest that it takes much longer to develop a meaningful relationship when it does not emerge out of mutual admiration. In examining dyads of same and differing races, Ensher and Murphy (1997) found that perceived similarity was significantly correlated to liking, satisfaction, and intention to continue the relationship as reported by both mentors and protégés. Hence, the similarity (perceived or actual) between a formal mentor and junior member would likely influence the junior member’s selection of an informal mentor. Because dissimilarity can negatively impact interpersonal relationships (Ragins, 1997), a lack of similarity may inhibit the willingness of formal mentors to fully engage in mentoring functions and may diminish the desire of the protégé to seek the formal mentor’s help. Thus, it is hypothesized that:

Hypothesis 3: Less similarity between a formal mentor and a junior member will be associated with the junior member identifying an informal mentor.

PROTÉGÉ PERFORMANCE

The relationship between job performance and mentoring type has been one of the

most studied aspects of mentoring. In many studies, performance is viewed as an outcome variable (e.g., Allen et al., 2004) rather than a possible predictor of mentoring (e.g., Eby et al., 2013). Nonetheless, an employee’s performance likely determines whether or not he or she will seek out an informal mentor. Because mentoring can be an intensive process, it reasons that both formal and informal mentors would be highly selective in choosing a protégé (Green and Bauer, 1995). Intuitively, a high-performing

70



individual would certainly command the attention of others who have a desire to mentor. On the other hand, formal and informal mentors may distance themselves from potential protégés who are performing poorly as they may present a risk to the mentors’ reputation. Previously, perceptions of risk have been used to gauge how a potential mentor feels about the potential negative impact of a particular protégé on his or her own career (Ragins and Scandura, 1994). Research shows a significant negative correlation between costs and intentions to mentor. Findings from Green and Bauer’s (1995) longitudinal study suggest that high-performing employees receive greater mentoring from their advisors than their low-performing counterparts. As a result, the mentoring relationship with a formal mentor who is also a supervisor may suffer for the junior employees who have low performance. Moreover, when performance is low, the junior member may consider that mentoring is ineffective regardless of the involvement of the formal mentor and seek additional help. It would be reasonable to expect that employees with poor performance ratings may perceive lower quality interactions with formal mentor and seek another mentor. It should be noted, however, that seeking an informal mentor by a poor performing member does not necessarily mean that the informal mentor would accept the responsibility. If aware of the performance, a sought after informal mentor would likely share the same reservations the formal mentor has. Thus, it is hypothesized that:

Hypothesis 4: Junior members with low supervisor-rated performance will be more

likely to state they have an informal mentor.

METHOD

Participants and Procedures

Data were collected from three groups of participants: supervisors who were appointed as formal mentors through policy directives, junior Air Force members (i.e., Lieutenants or Captains) considered their protégés, and individuals identified by the junior members as informal mentors. All participants were assigned to the same Air Force center. To collect the data from these groups, three different questionnaires were used. Consistent with previous studies in measuring informal and formal mentoring relationships (e.g., Ensher and Murphy, 1997; Kram, 1988), questionnaire packages were addressed to “The formal mentor of [Name of the junior member].” These packages included: (a) cover letter, (b) a copy of the formal mentor’s questionnaire, and (c) a sealed package that was to be forwarded to junior member (i.e., protégé). The cover letter explained the research purpose, assured confidentiality, and requested that the formal mentor complete the survey based on his or her relationship with the junior member listed and forward the remaining package to that member. Each junior member’s package included a separate cover letter that assured confidentiality, his or her survey, and a package that could be forwarded to whomever he or she considered a mentor (i.e., informal mentor). The letter also assured the junior members that their formal mentors were not aware of the informal mentor survey so they felt no pressure to identify these individuals as mentors.

In all, data were collected from 338 supervisors, 224 of their protégés, and 75 informal mentors. Supervisors were active duty military members or civil service employees. The typical military supervisor in the sample was a 41-year-old, white male,

71



with over 10 years in the current position, supervising nearly 50 individuals. The typical civilian supervisor in the sample was a 49-year-old, white male with 14 years in the current position, supervising over 25 individuals. Of the protégés responding, the typical participant was a married white male, with a little over one year in the current position, and 3.5 years working within the Air Force. Informal mentors were either senior military officers or senior civil servants. On average, the senior military officers had more than 10 years working in their current occupation and were 40 years old. The civilian employees who were identified as informal mentors averaged 12.5 years of experience.

Measures Included in Formal Mentor, Informal Mentor, and Protégé Questionnaires

Work-related contact time. Consistent with previous research (e.g., Ensher and Murphy, 1997), nine open-ended items were used to reflect work-related contact time (in hours per week) referring to the average amount of time formal or informal mentors and their protégés spend in direct contact with each other. An example formal mentor item is “In an average week, how much time do you spend coming in contact with this subordinate at work?” An example junior member item is “In an average week, how much time does your mentor spend coming in contact with you at work?” The score was created by summing the response for each item. Coefficient alpha was 0.88 for the junior members (n = 224) and 0.84 (n = 338) for the formal mentor.

Similarity. Respondents indicated which of 13 items they shared with the other member of the relationship to reflect the extent to which participants perceived their formal mentor, informal mentor, or protégé as similar (Gibson, 1998). Similarity characteristics included age, marital status, and anticipated career path. Junior members completed the similarity measure in regard to whom they considered their mentor whether that be formal or informal. Formal and informal mentors completed the similarity index in regard to their protégé and the similarity index was computed by adding the number items each member selected (Gibson, 1998). Measures Included in Formal Mentor Questionnaire Only

Performance. Supervisors rated the performance of their subordinates on three dimensions (Gibson, 1998): interpersonal effectiveness, dedication to their job, and overall job performance. First, interpersonal effectiveness was assessed relative to the subordinate’s peers within the unit and measured using a seven-point Likert-type scale with four items (coefficient alpha = 0.93 for n = 331). The scale ranged from “Much below average” to “Much above average.” An example item was “Compared with others, how effective is this officer in helping others who need it?” Second, supervisors rated their subordinate’s dedication to their job as compared to peers (coefficient alpha = 0.92 for n = 331). Job dedication was measured with four items rated on a five-point Likert-type scale ranging from “Not at all likely” to “Exceptionally likely.” An example item is “Compared with others, how likely is it that this officer would persist to overcome obstacles to complete a task?” Third, overall job performance was measured with three items on a seven-point scale anchored with a “High” (7-6), “Medium” (5-3), and “Low” (2-1). An example item is “Contributes to unit effectiveness.” The overall performance score was calculated by averaging the three items and the reliability coefficient alpha was

72



0.95 (n = 332). Finally, an overall performance rating was created by averaging the responses of all three sub-scales with a coefficient alpha for the scale of 0.94.

Measures Included in Protégé Questionnaire Only

Leader-member exchange. Scandura and Graen’s (1984) six-item scale was used to measure leader-member exchange. LMX was measured on a seven-point scale ranging from “Strongly Disagree” (1) to “Strongly Agree” (7). An example item was “My supervisor recognizes my potential” with reliability coefficient of 0.87 (n = 191).

Identification of an informal mentor. This variable was determined dichotomously with the question “Is your mentor also your supervisor?”

RESULTS

In Table 1, descriptive statistics as well as correlations among study variables are

presented. The hypotheses were tested by comparing two groups of junior members – those who identified their supervisor as their mentor (i.e., a formal mentor) and those who identified an informal mentor. Results are presented in Table 2. In Hypothesis 1, a junior member who identified an informal mentor was expected to report low LMX (as reported by the protégé) between the formal mentor and him or herself. The findings indicated that the two groups of junior members reported significantly different LMX. While all of the officers reported a high-quality exchange relationship on average, those officers who recognized their supervisor as their mentor appeared to have a more positive exchange relationship with their supervisors than those officers who had identified an informal mentor. Thus, Hypothesis 1 was supported.

In Hypothesis 2, a junior member who identified an informal mentor was expected to report less work-related contact time between a mentor and him or herself. Examining junior members’ reports, those who identified their supervisors as their mentors reported significantly higher contact time than those service members that identified informal mentors. Examining the supervisors’ responses, those supervisors who were identified by their subordinates as mentors reported higher contact time with their subordinates than did their fellow supervisors whose subordinates had identified an informal mentor, although the differences were not as statistically significant. Thus, Hypothesis 2 was partially supported.

In Hypothesis 3, the similarity between the supervisor and the junior member would be associated with the junior mentor choosing the supervisor as a mentor rather than choosing an informal mentor. Examining reports from supervisors and junior members, there were significant differences in perceived similarity among those who relied on their formal mentor in comparison to those who chose an informal mentor. To assess actual similarity, an index was created. The index was based upon demographic information and measured what characteristics each junior member had in common with his or her supervisor (e.g., gender, ethnic background, source of commissioning, age, education, and marital status). The results for the Similarity (Actual) index were in the hypothesized direction but the differences were not significant (F = 1.76, p = 0.19). Therefore, Hypothesis 3 was supported for perceived similarity only.

73



Tab

le 1

D

escr

ipti

ve S

tati

stic

s an

d C

orre

lati

ons

for

Stud

y D

ata

Fact

or

N

M

SD

1 2

3 4

5 6

7 8

1. L

eade

r-M

embe

r E

xcha

nge

191

5.28

1.

00

(0.8

7)

2. W

ork-

rela

ted

Con

tact

Tim

e1 22

4 23

.33

44.7

8 0.

15*

(0.8

8)

3. W

ork-

rela

ted

Con

tact

Tim

e2 33

8 40

.29

44.6

3 0.

25**

0.

25**

(0

.83)

4. S

imila

rity

1 22

4 2.

33

2.74

0.

13

0.41

**

0.15

* --

5. S

imila

rity

2 33

8 3.

42

1.84

0.

18*

0.02

0.

23**

0.

22**

--

6. S

imila

rity

(A

ctua

l)

224

2.40

0.

86

-0.0

1 0.

01

0.06

0.

09

0.3

2**

--

7. F

orm

al M

ento

r St

atus

3 33

6 0.

54

0.50

-0

.14

-0.0

7 -0

.20*

* -0

.05

-0.2

7**

-0.1

4 --

8. P

erfo

rman

ce

323

5.22

0.

82

0.28

**

0.15

0.

26**

0.

11

0.2

2**

0.0

7 -0

.03

(0.9

4)

Not

e. A

lpha

coe

ffic

ient

s fo

r m

ulti-

item

sca

les

are

repo

rted

in p

aren

thes

es a

long

the

diag

onal

. Tw

o-ta

iled

test

s. *

p <

0.0

5; *

* p

< 0

.01

1 Jun

ior

mem

ber

(i.e.

, pro

tégé

);

2 For

mal

men

tor

of th

e ju

nior

mem

ber

3 1

=C

ivili

an, 0

=M

ilita

ry

74



Tab

le 2

C

ompa

riso

n be

twee

n th

e Fo

rmal

and

Inf

orm

al M

ento

rshi

p G

roup

Fo

rmal

Men

tor

Info

rmal

Men

tor

AN

OV

A T

est

Stat

isti

cs

Mea

sure

N

M

SD

95%

Con

fide

nce

Inte

rval

for

Mea

n N

M

SD

95

% C

onfi

denc

e In

terv

al fo

r M

ean

F p

Low

er

Upp

er

L

ower

U

ppe

r

Lea

der-

Mem

ber

Exc

hang

e 55

5.

71

0.74

5.

51

5.91

82

5.

20

1.04

4.

97

5.43

9.

910.

002

Wor

k-re

late

d C

onta

ct T

ime1

57

57.2

1 55

.48

42.4

9 71

.93

94

20.9

0 42

.65

12.1

6 29

.63

20.4

1<

0.00

1

Wor

k-re

late

d C

onta

ct T

ime2

45

54.1

2 55

.83

37.3

5 70

.89

63

38.7

2 37

.53

29.2

7 48

.17

2.94

0.08

9

Sim

ilari

ty1

57

4.18

2.

06

3.63

4.

72

94

2.97

2.

96

2.36

3.

57

7.32

0.00

8

Sim

ilari

ty 2

45

3.91

2.

04

3.30

4.

52

63

3.08

1.

69

2.65

3.

50

5.34

0.02

3

Perf

orm

ance

44

5.

34

0.71

5.

13

5.56

60

5.

25

0.79

5.

04

5.45

0.

410.

525

1 Jun

ior

mem

ber

(i.e.

, pro

tégé

) 2 F

orm

al m

ento

r of

the

juni

or m

embe

r

75



In Hypothesis 4, low levels of junior member performance, as reported by the supervisor, would be associated with the officers’ selection of an informal mentor other than the supervisor. Protégés who relied on their formal mentor had an average performance level of 5.34 while those who had an informal mentor had a performance level of 5.25. Results indicated that the junior member’s performance ratings did not significantly differ whether they identified their supervisor or another informal mentor. Therefore, Hypothesis 4 was not supported.

Supplementary Analyses

While the U.S. Air Force, employing military and civilians, may be a generalizable context to examine mentoring relationships, an additional similarity factor comes into play. In the current Air Force structure and according to the mentoring requirements outlined in formal instructions, it is common for civil servants to supervise and mentor military members. Similar to concerns about gender or ethnicity, a formal mentor’s status (i.e., military or civilian) might have a considerable impact on the trust established and strength of the relationship between the mentor and protégé. In line with this hypothesis, junior members with civilian formal mentors were expected to report an informal mentor more frequently than those with military formal mentors. To test this, a 2 test was conducted. Results indicated that junior members with civilian supervisors were more likely to select an informal mentor ( 2 = 9.51, p < 0.01).

Additionally, a logistic regression analysis was used to evaluate the effect of each independent variable on the dependent variable (i.e., identifying an informal mentor). Significant results of the regression analysis are presented in Table 3. The results further confirmed the earlier finding, that high-quality LMX is negatively related to the likelihood that a junior member will seek an informal mentor. This result provided additional support for the hypothesis that junior members who perceive themselves as more similar to their supervisors are less likely to identify an informal mentor. These results provided additional support that junior members whose supervisors have military status are less likely to select another person as a mentor.

Table 3 Summary of Logistic Regression Analysis Predicting

Identification of Informal Mentor

Variable SE Wald df Odds ratio

p

Leader-Member Exchange -0.769 0.300 6.596 1 0.463 0.01

Formal Mentor Status1

1.674 0.479 12.220 1 5.332 <0.001

Similarity2 -0.216 0.101 4.563 1 0.805 0.033

1. 1= Civilian, 0=Military 2. Junior member (i.e., protégé)

76



DISCUSSION

This study examined mentoring relationships to determine what characteristics might lead protégés to select informal mentors in addition to or in place of their formal mentors. The U.S. Air Force provided a fitting setting to study this issue because mentoring roles are formally assigned; yet, junior members are encouraged to develop informal mentoring relationships with others whom they find helpful. The members involved in this study were assigned to one of the Air Force’s largest acquisition centers dedicated to the design, development, and procurement of aeronautical systems. In addition, it focuses on innovation facilitating the rapid transition of technology into systems and exploring the development and retention of a high performance work force. Due to the technical nature of the organization, the majority of respondents were science and engineering professionals, many with advanced degrees. Like other professional service firms, these members operate in a system where their performance is evaluated at discrete periods of time. Those that are deemed to have the potential for advancement are selected for promotions in rank and those that are not compete for advancement at a later time. At some point, those that are not selected are required to leave the organization. This system provided a unique opportunity to study mentorship as it is critical to these members’ success.

As expected, the quality of the relationship reported (as measured through LMX) between a formal mentor and protégé was related to the individual’s decision to seek an informal mentor. That is, when LMX was low, the junior member was much more likely to find an additional mentor. With regards to LMX theory, it is possible that the protégés who recognize their supervisor as their mentor are members of the “in group” or have attained a “high level exchange.” These individuals would likely realize the benefits of a greater level of influence with and from their supervisor through the mentoring activities that they receive (Graen and Uhl-Bien, 1995). In contrast, those employees with low-quality exchanges may have become part of the “out group” with their supervisors not finding either a reason or time to fully develop them as protégés. While being part of an out-group is generally viewed negatively, this may not be a serious concern given that members who reported low-quality exchanges with supervisors were able to receive mentoring vis-à-vis an alternate route—informal mentoring.

Additionally, differences were observed in time spent participating in “mentoring functions” by informal and formal mentors. For those in a formal mentoring relationship, the time spent with their mentor was far greater than those in an informal mentoring relationship. This might suggest that the junior members who identify informal mentors under-report contact time because mentoring is taking place unknown to the protégé. It could also indicate that the less frequent exchanges with informal mentors may be so content rich that much less time is required in order for an informal mentor to effectively provide key support—an interesting issue that warrants further study. Supervisors indicated that they did not spend as much time with those subordinates that had informal mentors, suggesting that supervisors who are not spending as much time with their subordinates may not be allowing a positive relationship to evolve and develop within the formal mentoring program. Alternatively, these supervisors may dedicate less time to mentoring the subordinate because they may not feel needed as mentoring is already being provided to the subordinate from other sources.

77



In addition, similarity as reported by both the junior members and the supervisors was associated with less likelihood of seeking another mentor. The data also indicate that perceived similarity, rather than actual similarity, matters in determining the choice of mentor and mentoring behavior. This finding is consistent with the findings of Turban et al. (2002) on the mentoring doctoral students receive. When mentoring is confined to a strict formal relationship, it could easily be viewed as an expected action, causing the protégé to expect a greater amount of mentoring from the mentor. However, if a junior member in a mentoring dyad considers the mentoring actions to be informal, then the same formal mentor might prove more successful. In short, formal mentors should be encouraged to try to develop relationships with their protégés with a more natural exchange. Interestingly, a strong correlation (r = 0.4) was found between work-related contact time from the junior member’s perspective and similarity with the mentor as reported by the junior member. This finding is consistent with Turban and Jones (1988) who suggested that contact between junior and senior members in any developmental relationship leads to greater perceptions of similarity. From the supervisor’s perspective, it seemed that a higher level of similarity with a subordinate was related to the subordinate considering him or her a mentor. From the junior member’s perspective, it seemed that an informal mentor could be effective despite having a lesser degree of similarity than was required of a formal mentor. This might also suggest that informal mentoring pairs had commonalities which were not measured.

No significant differences were identified with regard to protégé performance as hypothesized. Several things may explain this finding. First, it might be intuitive that supervisors may rate their employees that they perceive as protégés more highly–as supervisors may view the performance ratings as a reflection of their abilities as supervisors and mentors. These potentially “inflated” ratings may prevent full examination of the degree to which performance affects or is affected by mentoring. Alternatively, informal mentors who are being sought by those performing more poorly may not agree to serve as mentors because of performance concerns. A factor the methods used would not detect. Regardless, these findings hint that organizational leadership can focus on teaching the benefits of mentoring and what it takes to facilitate effective mentoring and then allow junior employees to find potential mentors that best suit their needs such that their learning and performance improves.

These findings should offer some insights for practitioners. As organizations become committed to formal mentoring programs, leaders should consider ways to better build those mentoring relationships. Additionally, the results offer some advice on how to foster a better mentoring culture outside of the formal program and encourage the informal mentoring that often supplements a formal relationship. One of the most important discoveries of the analysis was the relationship between LMX and mentoring. While mentoring is often conceptualized as a somewhat confusing conglomeration of coaching, role modeling, friendship, sponsorship, and counseling (Kram, 1988), leader-member exchange is a more easily understood model of improved interactions. Supervisors seeking “higher level” exchanges with their subordinates can make an effort to influence their employees by increasing “job latitude, influence in decision-making, open and honest communications, support of the member’s actions, and confidence in and consideration for the member” (Dansereau et al., 1975: 50). One important aspect of good leader-member exchange and mentoring is the frequency, quality, and amount of contact time between the members of a particular mentoring

78



relationship. The amount of contact time certainly plays an important role in establishing high-quality exchanges and opportunities for effective mentoring. Additionally, increased contact time has shown to be an important factor in increasing perceived similarity between individuals. These increased perceptions of similarity play an important role in satisfaction with a supervisor or mentor, as well as increased clarity of work roles for subordinates (Turban and Jones, 1988).

While this study may take a step toward closing the recognized knowledge gap between formal and informal mentoring, it also has several limitations that may lead to the identification of several future areas of study. First, this study only examined formal mentors who also served as the protégés’ supervisor. Like other mentoring, Scandura and Schriesheim (1994) define supervisory mentoring as the extra-organizational commitment and investment a supervisor makes to a protégé’s long-term development accomplished by the sharing of values, knowledge, and experience. Still, supervisory mentors differ from other formal mentors and, while many formal mentoring programs have supervisors act as mentors, this practice is not universal. As a positive, supervisors have structured opportunities to observe their protégés and are in an organizationally sanctioned position to protect and provide protégés with positive exposure. This advantage may be countered as supervisors must allocate their time across several individuals when they have multiple subordinate-protégés, making it likely to only provide career support to protégés whose characteristics enable them to fulfill their motivations and organizational obligations.

This shortcoming has been suggested within the field of mentoring research as the true effects mentoring have been discussed. In their meta-analysis of mentoring outcomes for protégés, Allen et al. (2004) found a positive correlation between mentoring and career outcomes, but their effect sizes were notably small (e.g., Mwr = 0.12 for compensation). Part of this is likely due to the fact that the majority of the people who serve as a mentor to a protégé (even when a formal mentor is not in a supervisory role) also, to some degree, determine the protégé’s career-related outcomes. Hence, mentoring might simply be a self-fulfilling prophecy with the individuals who are mentored by senior organizational members being rewarded by the same senior members. One improvement might be to measure career-related outcomes longitudinally with pre-mentoring and post-mentoring measures provided by an impartial evaluator. In addition, the field of subjective career outcomes still provides a great deal of potential future studies.

The relationship between mentoring and LMX is interesting and future studies should investigate how the two concepts work together as part of overall developmental relationships in the workplace. One contribution and practical implication is that supervisors acting as formal mentors can improve their mentoring relationships by engaging in positive LMX behaviors such as working with subordinates on areas in which they could expand their job-related contributions. This would in turn provide short-term career benefits for the subordinate in the form of performance appraisals (Scandura and Schriesheim, 1994). In fact, Scandura and Graen (1984) found that individuals could improve their LMX skills and significantly improve the job satisfaction and job performance of employees with whom they previously had low-quality exchanges. Further, the relationship between mentor-protégé similarity and contact time has vast possibilities as the two concepts have been linked to positive outcomes for mentors, protégés, and organizations (Ensher and Murphy, 1997; Turban and Jones,

79



1988). Finally, this study demonstrates that many protégés recognize more than one person as their mentor. Particularly within the organization, it would be interesting to further investigate the dynamics between protégés and their multiple mentors, especially as it relates to what roles are filled by each mentor and how each mentor might feel about the presence of an additional mentor.

As mentoring has been positively linked to employee performance, satisfaction, and intentions to stay, it makes sense that organizations look to capitalize upon these benefits by encouraging mentoring relationships. As this movement has grown, the use of formal mentoring relationships to foster positive development has also increased. Better understanding the factors that drive protégés to seek informal mentoring while formal mentors are available will help organizations to improve their formal mentoring programs and more successfully encourage informal mentoring. This study highlighted some of these factors with the results notably suggesting that teaching the concepts of LMX to formal and informal mentors could foster better interactions between junior and senior members.

References

Allen, T. D., L. T. Eby, and E. Lentz. 2006. “The Relationship between Formal Mentoring Program Characteristics and Perceived Program Effectiveness.” Personnel Psychology 59: 125-153.

————, L. T. Eby, K. E. O’Brien, and E. Lentz. 2008. “The State of Mentoring Research: A Qualitative Review of Current Research Methods and Future Research Implications.” Journal of Vocational Behavior 73(3): 343-357.

————, ————, M. Poteet, E. Lentz, and L. Lima. 2004. “Career Benefits Associated with Mentoring for Protégés: A Meta-Analysis.” Journal of Applied Psychology 89: 127-136.

Bridgeford, L. C. 2007. “Mentoring Programs Still Have a Place in the 21st Century.” Employee Benefit News 21: 16.

Burke, R. J. 1984. “Mentors in Organizations.” Group and Organization Studies 9: 253-272.

———— and C. A. McKeen. 1989. “Developing Formal Mentoring Programs in Organizations.” Business Quarterly 53: 76-79.

Byrne, D. 1971. The Attraction Paradigm. New York: Academic Press. Chao, G. T., P. M. Walz, and P. D. Gardner. 1992. “Formal and Informal Mentorships:

A Comparison on Mentoring Functions and Contrast with Nonmentored Counterparts.” Personnel Psychology 45: 619-636.

Chun, J. U., J. J. Sosik, and N. Y. Yun. 2012. “A Longitudinal Study of Mentor and Protégé Outcomes in Formal Mentoring Relationships.” Journal of Organizational Behavior 33(8): 1071-1094.

Dansereau, F., G. Graen, and W. J. Haga. 1975. “A Vertical Dyad Linkage Approach to Leadership within Formal Organizations: A Longitudinal Investigation of the Role Making Process.” Organizational Behavior and Human Performance 13: 46-78.

Dulebohn, J. H., W. H. Bommer, R. C. Liden, R. L. Brouer, and G. R. Ferris. 2012. “A Meta-analysis of Antecedents and Consequences of Leader-Member Exchange:

80



Integrating the Past with an Eye toward the Future.” Journal of Management 38(6): 1715-1759.

Eby, L. T., T. D. Allen, S. C. Evans, T. Ng, and D. L. DuBois. 2008. “Does Mentoring Matter? A Multidisciplinary Meta-Analysis Comparing Mentored and Non-Mentored Individuals.” Journal of Vocational Behavior 72(2): 254-267.

————, ————, B. J. Hoffman, L. E. Baranik, J. B. Sauer, S. Baldwin, M. A. Morrison, K. M. Kinkade, C. P. Maher, S. Curtis, and S. C. Evans. 2013. “An Interdisciplinary Meta-analysis of the Potential Antecedents, Correlates, and Consequences of Protégé Perceptions of Mentoring.” Psychological Bulletin 139(2): 441-476.

————, J. E. Rhodes, and T. D. Allen. 2007. “De nition and Evolution of Mentoring.” The Blackwell Handbook of Mentoring: A Multiple Perspectives Approach. Oxford, UK: Blackwell.

Ensher, E. A., E. J. Grant-Vallone, and W. D. Marelich. 2002. “Effects of Perceived Attitudinal and Demographic Similarity on Protégés’ Support and Satisfaction Gained from Their Mentoring Relationships.” Journal of Applied Social Psychology 32: 1407-1430.

———— and S. E. Murphy. 1997. “Effects of Race, Gender, Perceived Similarity, and Contact on Mentor Relationships.” Journal of Vocational Behavior 50: 460-481.

Feldman, D. C., W. R. Folks, and W. H. Turnley. 1999. “Mentor-Protégé Diversity and its Impact on International Internship Experiences.” Journal of Organizational Behavior 20: 597-611.

Gibson, S. 1998. “An Evaluation of Characteristics and Practices Associated with Effective Mentoring within the United States Air Force.” Master’s Thesis. Air Force Institute of Technology.

Graen, G. and M. Uhl-Bien. 1995. “Relationship-based Approach to Leadership: Development of Leader-Member Exchange (LMX) Theory of Leadership Over 25 Years: Applying a Multi-Level Multi-Domain Perspective.” The Leadership Quarterly 6: 219-247.

Green, S. and T. Bauer. 1995. “Supervisory Mentoring by Advisers: Relationships with Doctoral Student Potential, Productivity, and Commitment.” Personnel Psychology 48: 537-562.

Johnson, W. B. and G. Anderson. 2009. “How to Make Mentoring Work.” U.S. Naval Institute Proceedings April: 26-32.

Kram, K. E. 1988. Mentoring at Work: Developmental Relationships in Organizational Life. Lanham, MD: University Press of America.

Liden, R. C. and G. Graen. 1980. “Generalizability of the Vertical Dyad Linkage Model of Leadership.” Academy of Management Journal 23: 451-465.

Noe, R. A. 1988. “An Investigation of the Determinants of Successful Assigned Mentoring Relationships.” Personnel Psychology 41: 457-479.

Ragins, B. R. 1997. “Diversified Mentoring Relationships in Organizations: A Power Perspective.” Academy of Management Review 22(2): 482-521.

———— and J. L. Cotton. 1999. “Mentor Functions and Outcomes: A Comparison of Men and Women in Formal and Informal Mentoring Relationships.” Journal of Applied Psychology 84(4): 529-550.

81



————, J. L. Cotton, and J. S. Miller. 2000. “Marginal Mentoring: The Effects of Type of Mentor, Quality of Relationship, and Program Design on Work and Career Attitudes.” Academy of Management Journal 43(6): 1177-1194.

———— and K. E. Kram. 2007. The Handbook of Mentoring at Work: Theory, Research, and Practice. Thousand Oaks, CA: Sage Publications.

———— and T. A. Scandura. 1994. “Gender Differences in Expected Outcomes of Mentoring Relationships.” Academy of Management Journal 37: 957-971.

Riordan, C. M. 2000. “Relational Demography within Groups: Past Developments, Contradictions, and New Directions.” Research in Personnel and Human Resource Management 19: 131-173.

Scandura, T. A. and G. B. Graen. 1984. “Moderating Effects of Initial Leader-Member Exchange Status on the Effects of a Leadership Intervention.” Journal of Applied Psychology 69: 428-436.

———— and C. Schriesheim. 1994. “Leader-Member Exchange and Supervisor Career Mentoring as Complementary Constructs in Leadership Research.” Academy of Management Journal 37: 1588-1602.

———— and R. E. Viator. 1994. “Mentoring In Public Accounting Firms: An Analysis of Mentor-Protégé Relationships, Mentorship Functions, and Protégé Turnover Intentions.” Accounting, Organizations and Society 19(8): 717-734.

Thomas, D. 1990. “The Impact of Race on Manager’s Experiences of Developmental Relationships (Mentoring and Sponsorship): An Intra-Organizational Study.” Journal of Organizational Behavior 11: 479-492.

Turban, D. B., T. W. Dougherty, and F. K. Lee. 2002. “Gender, Race, and Perceived Similarity Effects in Developmental Relationships: The Moderating Role of Relationship Duration.” Journal of Vocational Behavior 61: 240-262.

———— and A. P. Jones. 1988. “Supervisor-Subordinate Similarity: Types, Effects, and Mechanisms.” Journal of Applied Psychology 73: 228-234.

Underhill, C. 2006. “The Effectiveness of Mentoring Programs in Corporate Settings: A Meta-Analytical Review of the Literature.” Journal of Vocational Behavior 68(2): 292-307.

U.S. Air Force. 2000, June 1. “Air Force Mentoring Program.” Air Force Policy Directive 36-34.

Weinberg, F. J. and M. J. Lankau. 2011. “Formal Mentoring Programs: A Mentor-centric and Longitudinal Analysis.” Journal of Management 37: 1527-1557.

82



Cynicism Across Levels in the Organization

Matrecia S. L. James Associate Dean & Graduate Director

Jacksonville University [email protected]

John C. Shaw Assistant Professor

Jacksonville University [email protected]

Organizational cynicism is rampant throughout the modern workplace (Dean et al.,

1998; Neves, 2012; Chiaburu et al., 2013). Prior research (Dean et al., 1998) has described cynicism as negative work attitude that develops as a result of perceived malfeasance of the perceived agent or entity that can be targeted at individuals in the organization or the company as a whole. Causes of cynicism include prevalent characteristics of the work environment such as high levels of executive compensation, poor organizational performance, and harsh layoffs (Andersson and Bateman, 1997; Brandes et al., 2008). The consequences of cynicism should not be understated. Kim et al. (2009) found that cynicism was negatively associated with self-assessed job performance. Andersson and Bateman (1997) showed that cynicism relates negatively to intentions to perform organizational citizenship behaviors. Furthermore, meta-analytic results confirm that such attitudes lead to important workplace outcomes such as decreased job satisfaction and organizational commitment and increased turnover intentions (Chiaburu et al., 2013). Cynical attitudes also have negative effects for the attitude holder. For example, Johnson and O’Leary-Kelly (2003) found that those individuals who expressed the strongest cynicism also reported the highest levels of emotional exhaustion. Despite these findings, there is still a lack of a more comprehensive understanding of cynicism.

The purpose of the present study is to address this gap in the current knowledge base. First, although a great deal of research has linked cynicism to various antecedents (see Chiaburu et al., 2013), scholars have devoted little attention to the effect of politics perceptions on cynicism. However, one study predicted and tested the positive

(83)

CYNICISM ACROSS LEVELS IN THE ORGANIZATION


relationship between perceptions of politics and cynicism (see Bashir and Nasir, 2013). Given that organizational politics is prevalent in virtually all work environments, it is critically important for organizations to attend to factors, such as perceptions of politics that contribute to the development of cynicism.

Second, it would be informative to expand the scope of cynicism research to include the direction of its target. Much of the previous research conceptualized cynicism as an affective state that encompasses perceptions of all organizational activities and agents (Chrobot-Mason, 2003). However, it is conceivable that employees hold more (or less) cynical attitudes toward particular targets (proximal supervisors versus distal executives). Scholars have devoted limited attention to the target specificity of cynicism (for exceptions see Lipset and Schnieder, 1983; Kanter and Mirvis, 1989; Andersson and Bateman, 1997). Yet this is an important issue to understand because perceived cynicism can have serious organizational implications. More studies are needed to further explore this issue.

Lastly, this paper explores the impact of psychological contract violation on existing relationships within organizations. Each employee works within an organization with a certain set of expectations referred to as a psychological contract (Robinson and Rousseau, 1994). When these expectations are not met, a psychological contract violation occurs (Robinson and Rousseau, 1994) resulting in a negative emotional response (Tomprou et al., 2015). Moreover, following a psychological contract violation, employees engage in considerable cognitive effort to scrutinize the environment (Parzefall and Coyle-Shapiro, 2011; Tomprou et al., 2015). Specifically, employees are attentive to current levels of organizational politics because it functions as a technique that employees use to make attributions for the way in which they are treated by the organization (Kiewitz et al., 2009). That is, employees that perceive high levels of politicking in their workplace are more likely to assume that the psychological contract violation signals that the organization does not care for their well-being or value their contributions. In light of the above information, psychological contract violation may be an important moderator that could exacerbate or mitigate the negative effects of perceived politics on cynicism.

In sum, the objective of this study is to further the understanding of the ill effects of perceived organizational politics on cynicism directed towards employees in three distinct levels of the organization and explore possible variations in the moderating effects of psychological contract violation. The authors review the literature on cynicism, perceived organizational politics, and psychological contract violation, and develop a set of hypotheses which are tested with a sample of full-time workers.

CYNICISM LITERATURE

There are several definitions of organizational cynicism in the existing literature.

Reichers et al. (1997) maintained that organizational cynicism is a negative attitude that develops as a result of perceived malfeasance of the agent or entity. Dean et al. (1998: 345) defined organizational cynicism as “a negative attitude toward one’s employing organization, comprising three dimensions: (1) a belief that the organization lacks integrity; (2) negative affect toward the organization; and (3) tendencies to disparaging and critical behaviors toward the organization that are consistent with these beliefs and affect.” Other researchers such as Wilkerson adopted this definition and broadened the

84

JAMES AND SHAW


target of organizational cynicism by including “[organizational] procedures, processes, and management.” (2002: 533) Such a negative attitude can be directed at the organization as a whole and/or the individuals in the organization. Bedeian defined the construct as “an attitude resulting from a critical appraisal of the motives, actions, and values of one’s employing organization.” (2007: 11) More recently, researchers (Chiaburu et al., 2013) suggest that cynicism encompasses the individual’s affective state and behavioral tendencies toward the organization. In general, cynicism is viewed as a negative work attitude, an aspect of individuals that may change over time (Dean et al., 1998), distinct from stable personality traits such as negativity and trait cynicism (Bommer et al., 2005). In addition, cynicism is an attitude that can relate to multiple objects and generalize from one object to another (Bateman et al., 1992; Andersson, 1996). Therefore, cynicism is conceptualized as broader in scope than other attitudes such as job satisfaction, because it relates to a more diverse set of objects or foci (Andersson, 1996).

The existing cynicism literature recognizes the importance of, and concentrates on, understanding the nature and processes by which cynicism develops. As such, the study of organizational cynicism focuses mainly on the development of normative models that include contributing factors (e.g., Andersson, 1996; Abraham, 2000). Most of the factors identified by past research are universal in that they contribute to an overall cynical attitude towards the organization. Although some factors may indeed be general and affect cynicism toward virtually all organizational employees, others may only affect cynicism toward individuals in certain hierarchical levels of the organization. In addition, the source of cynicism may be uniquely related to the target of that cynicism.

Researchers (e.g., Kanter and Mirvis, 1989; Andersson and Bateman, 1997) have identified industry-level and business environmental factors such as workforce reduction and organizational performance as causes of cynicism. Additionally, a small number of organizational characteristics have been investigated in cynicism studies. Managerial incompetence, limited voice, and discourteous interpersonal treatment have been conceptually linked to organizational cynicism (Andersson, 1996). Other organizational characteristics that have been empirically examined as antecedents to cynicism are perceptions of organizational politics, organizational justice, perceived organizational support, and psychological contract violation (Johnson and O’Leary-Kelly, 2003).

THEORY AND HYPOTHESES

Politics Perceptions as a Predictor of Cynicism

Organizational politics are an inherent part of all organizations and have long been an area of considerable interest to scholars, practitioners, and the general public (Chang et al., 2009; Atinc et al., 2010; Ferris and Hochwarter, 2011). Organizational politics can be described as schemes that promote an individual’s self-interests at the expense of other individuals, groups, or the organization as a whole (Mintzberg, 1983, 1985). Ferris et al. maintained that the perception of organizational politics “involves an individual’s attribution to behaviors of self-serving intent, and is defined as an individual’s subjective evaluation about the extent to which the work environment is characterized by co-workers and supervisors who demonstrate such self-serving behavior.” (2000: 90) That is, perceptions of organizational politics consist of an individual’s interpretations of the extent to which co-workers and supervisors engage in political behaviors and create an

85



environment characterized by such behaviors (Gandz and Murray, 1980). This definition is consistent with Lewin’s (1936) notion that individuals are largely guided by their perception of reality rather than by objective reality.

An important stream of research has focused on the link between a person perceiving the workplace as political and various job-related attitudes and behaviors (Ferris and Hochwarter, 2011; Hochwarter et al., 2004). For example, Ferris and colleagues (Ferris at al., 1989; Ferris at al., 2002) found that there were several possible reactions to politics perceptions such as increased job anxiety, increased intent to withdraw, decreased job satisfaction, and decreased perceived organizational support. Parker at al. (1995) found that when employees work in an environment that they perceive to be pervaded by individuals looking out for themselves, they are likely to become distrustful, skeptical, and distant. Because the overall integrity of the organization is compromised by perceptions of politics (Dean et al., 1998), everyone in the organization becomes the target of suspicion. Additionally, the negativeness associated with the conditions of a political environment is expected to contribute to negative emotions such as contempt and distress that have been associated with cynical attitudes. Hence, it is hypothesized:

Hypothesis 1: Perceptions of organizational politics will be positively associated

with cynicism towards co-workers. Hypothesis 2: Perceptions of organizational politics will be positively associated

with cynicism towards immediate supervisors. Hypothesis 3: Perceptions of organizational politics will be positively associated

with cynicism towards upper-level management.

Interactive Effects of Perceptions of Politics and Psychological Contract Violations

Psychological contract has emerged as an important framework for understanding the perceptions and reactions to the complex employment relationship (Braekkan, 2012). Rousseau describes psychological contract as “an individual’s beliefs regarding the terms and conditions of a reciprocal exchange agreement between the focal person and another party.” (1989: 123) These contracts are not always fulfilled. When breached, the emotional or affective response an employee may have is referred to as a psychological contract violation (Rousseau, 1995). According to the conceptualization of psychological violation, employees experience a strong emotional experience, typically in the form of distress and anger, due to the perception that the terms of their psychological contracts have not been adequately fulfilled (Robinson and Rousseau, 1994; Morrison and Robinson, 1997; Robinson and Morrison, 2000).

When a psychological contract violation has occurred, employees seek out additional information to form evaluative judgments. Theoretically, social information processing (SIP) theory (Salanick and Pfeffer, 1978) suggests that employees respond to cues provided by the social environment to construct and interpret reality. Thus, the social contextual environment, such as information communicated by coworkers, observations of coworkers’ behavior, and interactions with agents of the organization, provides employees with information about how they should perceive and respond to a psychological contract violation. That is, in addition to perceiving and reacting to an objective workplace reality, employees’ responses are also influenced by a reality that is partly constructed from social contextual information (Rosen et al., 2009). When the

86

JAMES AND SHAW


social context is highly political, it creates the impression that the organization has failed to fulfill obligations, explicit or implicit, contained in the psychological contract because organizational agents are engaged in self-serving behavior. In other words, a psychological breach has occurred. In contrast, when perceived politics is low, it creates the general impression that the organization continues to fulfill their promised obligations, which leads to a greater likelihood of not perceiving a psychological breach.

There is a general consensus among researchers that psychological contract violation is a factor capable of interacting with other individual variables to impact organizational outcomes. For example, researchers (Rousseau, 1995; Morrison and Robinson, 1997) have argued that the interaction between a psychological contract violation and individual cognitive assessments of the organization context surrounding the breach would predict the strength of the emotional and behavioral reactions subsequent to a violation. Indeed, Kickul et al. (2001) found a three-way interaction between contract breach, procedural justice, and interactional justice on anticitizenship behavior.

Past research provides evidence that politics perceptions are a predictor of various negative outcomes (e.g., Ferris and Judge, 1991; Kacmar and Baron, 1999). Aselage and Eisenberger (2003) claim that when applied to organizations’ social exchange accounts, the efforts carried out on behalf of the organization are enhanced to the degree that the organization is believed to be willing and able to give back desirable resources. Believing that organizational members are acting in a self-serving manner is likely to alter this social exchange.

Similarly, employee-organization psychological contracts comprise subjective beliefs concerning an exchange agreement (Rousseau, 1995). A major component of psychological contracts is the person’s belief that an agreement is mutual and involves a set of beliefs about what both employee and employer are to receive and to give in return for the other’s contribution (Levinson et al., 1962; Paul et al., 2000). Because organizations do not have a life of their own, it is posited that exchange agreements are perceived to exist between employees and upper-level managers who represent the organization. Therefore, it is argued that the impact of perceived politics is augmented by perceived psychological contract violations.

In summary, it is believed that when organizations fail to fulfill one or more psychological contract obligations, employees will most likely blame those who are in control of the organization. Furthermore, psychological contract violation is believed to result in emotional, attitudinal, and behavioral responses (McLean Parks et al., 1994). Some of these responses manifest themselves in the form of anger, resentment, frustration, hopelessness (Robinson and Rousseau, 1994), and/or loss of trust in the organization (Robinson, 1996) and its representatives. Dean et al. (1998) also identified employee cynicism as an additional outcome. Because upper-level managers occupy critical managerial positions in the hierarchy and are critical players of organizational politics, the negativity related to psychological contract violations and perceptions of organizational politics are expected to interact to predict cynicism towards individuals in the upper hierarchical level of the organization. As such, the following hypothesis is proposed:

87



Hypothesis 4: Psychological contract violation will moderate the relationship between perceptions of organizational politics and cynicism towards upper-level management.

METHOD

Participants

A total of 1,000 surveys were delivered to employees in 17 schools of the participating school district in the southeastern region of the United States. Responses were obtained from 360 of these individuals (36% response rate).

Of the 360 respondents, 78.9% were female, 18.1% were male, and 3.1% did not respond to this question. The racial composition of the sample was 17.8% African American, 1.1% Asian, 0.3% Hispanic, 75.3% White, and 1.9% Other. Additionally, 49.9% of the respondents were teachers, 45.6% were non-instructional staff members, and 4.7% did not respond to this question.

Demographic information obtained from the school district represented by this sample, indicates that 76.9% of the employees were female and 23.1% were male. Of the total number of workers, 18% are African American, 4% Hispanic, 2% Indian, and 76% White. Additionally, the district-wide employee pool is composed of 51% teachers and 49% non-instructional staff.

Measures

Perceived organizational politics. A six-item scale by Hochwarter et al. (2003) was used to measure perceptions of organizational politics. The items in this scale were developed to tap politics perceptions at work. A five-point response format with strongly disagree (1) and strongly agree (5) as endpoints is utilized. The coefficient alpha for this scale was 0.92.

Psychological contract violation. A global measure developed by Robinson and Morrison (2000), which assesses employees’ perceptions of how well their psychological contracts have been fulfilled by their organization, was used to measure psychological contract violation. The measure contained five items with responses on a five-point scale (1 = strongly disagree, 5 = strongly agree). Robinson and Morrison (2000) reported a Cronbach alpha for this scale of 0.92. In this study, the internal consistency for the scale was 0.86.

Cynicism. In order to measure the distinctiveness of cynicism towards others in the organization, three scales were developed to tap cynicism towards upper-level management, immediate supervisors, and co-workers. To ensure that the same aspects of cynicism towards people in the previously identified levels of the organization were captured, the same three items were simply reworded to identify the specific target of the cynical attitude. The following is a list of the items used: “It is hard to be hopeful at work because people at the highest levels in this school district have such bad attitudes;” “It is hard to be hopeful at work because people one level above me have such bad attitudes;” “It is hard to be hopeful at work because my co-workers have such bad attitudes.” The reliability for the measure of cynicism towards upper-level management was 0.63. The measure of cynicism towards immediate supervisors had an alpha of 0.69 and the measure of cynicism towards co-workers had an alpha of 0.66. All three

88

JAMES AND SHAW


measures used a five-point response scale (1 = strongly disagree, 5 = strongly agree). Although these reliabilities are relatively low, these measures were designed for the current study. This is acknowledged in the limitations section that follows. See the Appendix for a complete list of items.

Control variables. Affective disposition was measured using the 20-item Positive and Negative Affect Scale (PANAS, Watson et al., 1988), using a five-point response format ranging from very slightly or not at all (1) to extremely (5).

Additionally, based on existing organizational cynicism research (Andersson, 1996), this study gathered data to control for trust, age, gender, education, race, tenure, position, and organization/school effects in the last section of each survey (Schwab, 1999).

Data Analysis Techniques

Hypotheses 1-3 were tested by using hierarchical regression analysis. In the first step, the demographic variables (i.e., age, gender, educational level, race, tenure, and position), organization, affective disposition (i.e., negative and positive affect), and trust were entered as controls. The predictor variable was entered in step 2.

Hypothesis 4 was tested by hierarchical moderated regression analyses. Specifically, moderated regression analyses are conducted to determine the influence psychological contract violation on the relationships between perceptions of organizational politics and cynicism towards individuals in various levels of the organization (i.e., co-workers, immediate supervisors, and upper-level management). In the first step, the demographic variables (i.e., age, gender, educational level, race, tenure, and position), organization, affective disposition (i.e., negative and positive affect), and trust were entered as controls. The predictor variables were entered in step 2. A t-test of the 3 and

F-test of the R2 were used to test the interaction effect. Significance was indicated by a significant beta weight for the interaction term (Tate, 1998) or a significant increase in the variance explained (Cohen and Cohen, 1983; Tate, 1998) in the third step.

RESULTS

The means, standard deviations, intercorrelations, and internal consistency for the

measures used are reported in Table 1. Both predictors were significantly related to each of the dependent variables. Additionally, negative affect, positive affect, and trust were significantly related to the dependent variables. Negative affect was positively related to cynicism at each level in the organization, whereas positive affect and trust were negatively related to cynicism towards individuals in all three hierarchical levels. Finally, the correlation between the predictors was moderate (r =0.33, p 0.01).

89



Tab

le 1

D

escr

ipti

ve S

tati

stic

s, C

orre

lati

ons,

and

Rel

iabi

lity

Coe

ffic

ient

s

Var

iabl

es

Mea

n s.

d.

1 2

3 4

5 6

7 1.

Cyn

icis

m to

war

ds U

pper

- le

vel M

anag

emen

t 2.

81

0.68

(0

.63)

2.C

ynic

ism

tow

ards

Mid

dle

Man

agem

ent

2.54

0.

70

0.54

**

(0.6

9)

3.C

ynic

ism

tow

ards

Co-

wor

kers

2.

44

0.67

0.

46**

0.

62**

(0

.66)

4.Pe

rcep

tion

s of

O

rgan

izat

iona

l Pol

itic

s 3.

11

0.89

0.

39**

0.

36**

0.

46**

(0

.92)

5.Ps

ycho

logi

cal C

ontr

act

Vio

lati

ons

2.36

0.

72

0.37

**

0.42

**

0.44

**

0.33

**

(0.8

6)

6.O

rgan

izat

ion/

Scho

ol

- -

0.03

0.

09

0.10

0.

11*

0.01

7.

Ten

ure

15

.85

8.60

0.

04

0.01

-0

.08

0.03

0.

03

-0.0

3

8.A

ge

45.2

9 9.

04

-0.0

2 -0

.01

-0.1

0 -0

.01

-0.0

1 -0

.03

0.67

**

9.R

ace

- -

-0.0

3 -0

.23*

* -0

.17*

* -0

.10

-0.1

5**

-0.1

6**

-0.0

5 10

.Gen

der

- -

0.05

0.

07

-0.0

1 0.

00

-0.0

1 -0

.14*

* 0.

14**

11

.Pos

ition

-

- 0.

00

0.10

0.

02

-0.0

2 0.

04

0.04

0.

07

12.E

duca

tion

3.00

1.

25

0.02

-0

.14*

-0

.13*

-0

.02

-0.1

0 0.

00

0.28

**

13.N

egat

ive

Aff

ect

1.63

0.

64

0.30

**

0.27

**

0.30

**

0.26

**

0.26

**

0.03

-0

.03

14.P

ositi

ve A

ffec

t 3.

69

0.59

-0

.16*

* -0

.27*

* -0

.24*

* -0

.10*

-0

.30*

* 0.

02

0.03

15

.Tru

st

3.24

0.

92

-0.4

7**

-0.2

5**

-0.2

6**

-0.3

2**

-0.3

4 0.

02

-0.0

6 a V

alue

s al

ong

the

diag

onal

rep

rese

nt r

elia

bilit

y co

effic

ient

s *

p 0

.05,

**

p 0

.01

90

JAMES AND SHAW


Tab

le 1

(con

t’d)

Des

crip

tive

Sta

tist

ics,

Cor

rela

tion

s, a

nd R

elia

bili

ty C

oeff

icie

nts

Var

iabl

es

Mea

n s.

d.

8 9

10

11

12

13

14

1.C

ynic

ism

tow

ards

Upp

er-

leve

l Man

agem

ent

2.81

0.

68

2.C

ynic

ism

tow

ards

M

iddl

e M

anag

emen

t 2.

54

0.70

3.C

ynic

ism

tow

ards

Co-

wor

kers

2.

44

0.67

4.Pe

rcep

tion

s of

O

rgan

izat

iona

l Pol

itic

s 3.

11

0.89

5.Ps

ycho

logi

cal C

ontr

act

Vio

lati

ons

2.36

0.

72

6.O

rgan

izat

ion/

Scho

ol

- -

7.

Ten

ure

15

.85

8.60

8.A

ge

45.2

9 9.

04

9.

Rac

e -

- -0

.01

10.G

ende

r -

- 0.

16**

0.

05

11

.Pos

ition

-

- 0.

17**

-0

.14*

* -0

.04

12.E

duca

tion

3.00

1.

25

0.18

**

0.17

**

-0.0

6 -0

.15*

*

13.N

egat

ive

Aff

ect

1.63

0.

64

-0.1

6**

-0.0

5 -0

.04

-0.0

9 -0

.01

14.P

ositi

ve A

ffec

t 3.

69

0.59

0.

10

0.03

0.

05

0.02

0.

12*

-0.3

1**

15

.Tru

st

3.24

0.

92

-0.0

3 0.

09

-0.1

0 -0

.02

0.07

-0

.15*

* 0.

16**

a V

alue

s al

ong

the

diag

onal

rep

rese

nt r

elia

bilit

y co

effic

ient

s *

p 0

.05,

**

p 0

.01

91



Hypotheses 1-3 were tested using a series of hierarchical regressions. Table 2 presents the results of these tests. In step 1, control variables (organization, tenure, age, race, gender, position, education, NA, PA, and trust) were entered, followed by perceptions of organizational politics at the second level.

These hypotheses tested the impact of perceptions of organizational politics on cynicism towards co-workers (Hypothesis 1), cynicism towards the immediate supervisors (Hypothesis 2), and cynicism towards upper-level management (Hypothesis 3). When entered in the second step, the perceptions of organizational politics measure explained 6% of the variance in cynicism towards upper-level management ( R2 =0.06,

F = 29.11, p 0.001), 6% of the variance in cynicism towards immediate supervisors ( R2 = 0.06, F = 28.71, p 0.001), and 12% of the variance in cynicism towards co-workers ( R2 = 0.12, F = 56.11, p 0.001).

As can be seen in Table 2, perceived organizational politics emerged as a significant predictor of cynicism towards co-workers ( = 0.29, p 0.001), cynicism towards immediate supervisors ( = 0.22, p 0.001), and cynicism towards upper-level management ( = 0.21, p 0.001). These results indicate that perceptions of organizational politics were significantly and positively related to cynicism across hierarchical levels of the organization. Therefore, Hypotheses 1-3 were supported.

Table 2 Results of Hierarchical Regression Analysis

of Workplace Outcomes on Cynicism

Independent Variables Cynicism towards

Co-workers

Cynicism towards

Immediate Supervisors

Cynicism towards

Upper-level Management

Step 1: Controls School 0.00 0.00 0.00 Tenure 0.00 0.00 0.00 Age 0.00 0.00 0.00 Race -0.05* -0.10** 0.02 Gender 0.01 0.11 0.05 Position 0.01 0.05t 0.01 Education -0.02 -0.03 0.04 NA 0.11* 0.14* 0.12* PA -0.10 t -0.15* 0.02 Trust -0.07* -0.09* -0.28*** Step 2: Perceptions of

Organizational Politics 0.29*** 0.22*** 0.21***

R2 0.30 0.28 0.34 R2 0.12 0.06 0.06 F 56.11*** 28.71*** 29.107***

a Beta Weights are reported for the final step (n = 334) t p 0.10, * p 0.05, ** p 0.01, *** p 0.001

92

JAMES AND SHAW


To test Hypothesis 4, three separate moderated hierarchical regression analysis were used. All control variables were entered in step 1. In step 2, perceptions of organizational politics and psychological contract violation were entered. Finally, the interaction term for perceptions of organizational politics and psychological contract violation was entered in step 3.

Table 3 Results of Hierarchical Moderated Regression Analysis

Independent Variables Cynicism towards

Upper-level Management Step 1: Controls School 0.00 Tenure 0.00 Age 0.00 Race 0.03 Gender 0.05 Position 0.01 Education 0.04t NA 0.11* PA 0.07 Trust -0.26*** Step 2: Main Effects Perceptions of Organizational Politics 0.39*** Psychological Contract Violations 0.44** Step 3: Interactive Effects Perceptions of Organizational Politics

Psychological Contract Violation -0.09*

R2 0.37 R2 0.01 F 4.40*

a Beta Weights are reported for the final step (n = 334) t p 0.10, * p 0.05, ** p 0.01, *** p 0.001

Hypothesis 4 tested whether cynicism towards individuals in the various hierarchical

levels of the organization was differentially influenced by perceptions of organizational politics because of psychological contract violation experiences. Only one moderated relationship was found. Table 3 gives these results. A significant interactive effect of perceptions of organizational politics and psychological contract violation on cynicism towards upper-level management was detected ( = -0.09, R2 = 0.01, p 0.05). Slope difference tests were conducted to assess whether the slope of the moderated lines differed significantly from zero. Results indicated that the slope of the line when the moderator was low ( = 0.29, p 0.01) and when the moderator was average ( = 0.25, p 0.001) was significantly different from zero. However, the slope of the line when the moderator was high was not significant. The interaction is illustrated in Figure 1.

93



Figu

re 1

T

he M

oder

atin

g E

ffec

t of P

sych

olog

ical

Con

trac

t Vio

lati

on o

n th

e R

elat

ions

hip

betw

een

Per

cept

ions

of

Org

aniz

atio

nal P

olit

ics

and

Cyn

icis

m to

war

ds U

pper

-lev

el M

anag

emen

t

94

JAMES AND SHAW


DISCUSSION

A primary objective of this study was to explore the interactive effects of

psychological contract violation and perceptions of organizational politics in determining cynicism towards co-workers, immediate supervisors, and upper-level organizational managers. The results showed that psychological contract violation moderated the relationship between politics perceptions and cynicism towards upper-level management, but not the relationships between perceptions of organizational politics and individuals in less powerful positions. Based on this, it is evident that people are able to make a distinction between organizational agents and those who simply work for the organization. Upper-level management is viewed as the agents who personify the organization and are responsible for fulfilling contractual agreements. Thus, when violated, those in the higher ranks of the organization become the targets of increased cynicism.

Further, the moderating effects of psychological contract violation can be viewed as an indication that employees are sensitive to whether or not specific individuals were involved in perceived contractual transgressions. Cynicism towards those believed to be at fault, in this case, upper-level managers, may be one way to immediately express disappointment, frustration, and even anger at the organization for failing to make good on its promises. Consequently, when psychological contract violations are experienced in political workplace environments, cynicism towards upper-level management is derived from a dual source. However, the illustration of the interaction and slope analysis results suggest that when psychological contract violation is high, its effects overpower the effects of perceptions of organizational politics, resulting in high levels of cynicism towards upper-level management even when politics perception are low. Likewise, increases in politics perceptions have little effect on cynicism towards upper-level management when violations are high. On the other hand, the non-significant interaction between politics perceptions and psychological contract violations on cynicism towards employees in the other two organizational levels suggests that psychological contract violation does not have the same effect on cynicism relationships across vertical organizational boundaries.

There are a number of notable strengths of this study. First, this study provides evidence to substantiate the claim that cynicism in organizations is a specific attitude directed at certain targets within the workplace. Findings further indicate that the environmental source of cynicism have varying effects on different targets. Also, a number of control variables were included in the data analysis to rule out as many alternative explanations as possible. By controlling for demographics, organization (school) effects, affective disposition, and trust, the most conservative test of hypothesized relationships was employed. Limitations and Future Research

Despite the contributions of the study, there are some limitations. The first involves the homogeneity of the sample that is made up of employees from a public school district. This potentially limits the generalizability of the results. While the authors purposefully set out to study this population, future research should seek to implement samples from a diverse range of organizations and industries across both private and

95



public sectors in order to investigate whether the same relationships exists in other types of organizations. Exploring the impact of organizational structure and characteristics of the industry that have the potential to interact with perceptions of politics to predict cynicism might be fruitful in providing contextual insight related to embedded factors that affect employee attitudes. This would also address a limitation of this study by increasing generalizability.

It is also important to note that the cross-sectional data prevents any supposition of causality. Future studies that employ longitudinal designs to better measure causality are encouraged. Additionally, since data related to all of the study variables was collected at the same time, common method variance could be an issue (Podsakoff and Organ, 1986). However, any indication of common method variance bias will not necessarily affect results or conclusions (Spector, 2006). Moreover, the statistically significant interaction provides support for the notion that common method bias did not influence the observed relationships (Evans, 1985).

Another limitation is that only one predictor and one moderator variable were explored, and the only distinction made among employees was the hierarchical level of their position. In particular, future studies may look at different variables and make different distinctions within the organization in order to gain further insight related to the specificity of cynicism in organizations. In order to further explicate cynicism in the workplace, and specifically build a better understanding of cynical attitudes that permeate the work environment, additional attention could focus on identifying factors that interact with perceptions of politics to shape employee cynicism among those who work together on a regular basis. Understanding these kinds of organizational elements might prove useful in creating and managing workplace relationships and collaborations among peers and immediate dyadic relationships. Future work that further refine the measures of cynicism are also encouraged.

CONCLUSION

From a managerial perspective, the findings suggest that perceptions of politics can facilitate the spread of cynicism throughout the organization. Although the effects of politics are powerful enough to permeate boundaries within the organization, there are a number of things managers can do to manage political situations. For instance, adhering to formal guidelines and procedures, providing clear and timely feedback, and allowing employee participation are a few antidotes that can reduce perceptions of politics and thereby combat cynicism at one of its main sources. It is also important for upper-level managers to recognize that they are being held accountable for the broken promises of the organization. Employees often take psychological contract violations personally and have strong reactions to this form of betrayal (Johnson and O’Leary-Kelly, 2003). This study further indicates the main target of negative reactions associated with psychological contract violation is upper-level management. In order to preserve the reputation of the organization, reduce negative attitudes towards upper management, and protect the social exchange relationships between employees and the organization, it is strongly suggested top management take steps to clearly communicate what is expected of employees and what the organization will provide in return.

This study represents a first step towards an enriched understanding of the uniqueness of cynicism in organizations. By explicitly investigating differences in

96

JAMES AND SHAW


cynicism across distinct organizational levels, this research was able to provide support for the notion that not all cynicism is the same, and convincing evidence that cynicism towards one person or group of persons at work does not necessarily imply cynicism towards everyone in the organization. This perspective suggests a stimulating and potentially prolific direction for future research.

Appendix

Cynicism towards Others at Work

Items in Each Scale Cynicism towards Upper-level Management ( = 0.63)

Most people at the highest levels in this organization will think that things will get better instead of worse.

It is hard to be hopeful at work because people at the highest levels in this organization have such bad attitudes.

Efforts to make improvements are recognized by people at the highest levels in this organization.

Cynicism towards Immediate Supervisors ( = 0.69) Most people one level above me will think that things will get better instead of

worse. It is hard to be hopeful at work because people one level above me have such

bad attitudes. Efforts to make improvements are recognized by people one level above me.

Cynicism towards Co-workers ( = 0.66) Most of my co-workers will think that things will get better instead of worse. It is hard to be hopeful at work because my co-workers have such bad attitudes. Efforts to make improvements are recognized by my co-workers.

References

Abraham, R. 2000. “Organizational Cynicism Bases and Consequences.” Genetic, Social and General Psychology Monographs 126: 269-292.

Andersson, L. 1996. “Employee Cynicism: An Examination Using a Contract Violation Framework.” Human Relations 49: 1395-1418.

———— and T. S. Bateman. 1997. “Cynicism in the Work Place: Some Causes and Effects.” Journal of Organizational Behavior 18: 449-470.

Aselage, J. and R. Eisenberger. 2003. “Perceived Organizational Support and Psychological Contracts: A Theoretical Integration.” Journal of Organizational Behavior 24: 491-509.

97



Atinc, G., M. Darrat, B. Fuller, and B. W. Parker. 2010. “Perceptions of Organizational Politics: A Meta-Analysis of Theoretical Antecedents.” Journal of Managerial Issues 22: 494-513.

Bashir, S. and M. Nasir. 2013. “Breach of Psychological Contract, Organizational Cynicism and Union Commitment: A Study of Hospitality Industry in Pakistan.” International Journal of Hospitality Management 34:61-65.

Bedeian, A. G. 2007. “Even If the Tower Is ‘Ivory,’ It Isn’t ‘White:’ Understanding the Consequences of Faculty Cynicism.” Academy of Management Learning & Education 6: 9-32.

Bommer, W. H., G. A. Rich, and R. S. Rubin. 2005. “Changing Attitudes about Change: Longitudinal Effects of Transformational Leader Behavior on Employee Cynicism about Organizational Change.” Journal of Organizational Behavior 26: 733-753.

Braekkan, K. F. 2012. “High Performance Work Systems and Psychological Contract Violations.” Journal of Managerial Issues 24: 277-292.

Brandes, P., S. L. Castro, M. S. L. James, A. D. Martinez, T. A. Matherly, G. R. Ferris, and W. A. Hochwarter. 2008. “The Interactive Effects of Job Insecurity and Organizational Cynicism on Work Effort Following a Layoff.” Journal of Leadership & Organizational Studies 14: 233-247.

Chang, C., C. C. Rosen, and P. E. Levy. 2009. “The Relationship between Perceptions of Organizational Politics and Employee Attitudes, Strain, and Behavior: A Meta-Analytic Examination.” Academy of Management Journal 52: 779-801.

Chiaburu, D. S., A. C. Peng, I. Oh, G. C. Banks, and L. C. Lomeli. 2013. “Antecedents and Consequences of Employee Organizational Cynicism: A Meta-Analysis.” Journal of Vocational Behavior 83: 181-197.

Chrobot-Mason, D. L. 2003. “Keeping the Promise: Psychological Contract Violations for Minority Employees.” Journal of Managerial Psychology 18: 22.

Cohen, J. and P. C. Cohen. 1983. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum.

Dean, J. W. Jr., P. Brandes, and R. Dharwadkar. 1998. “Organizational Cynicism.” Academy of Management Review 22: 341-352.

Evans, M. G. 1985. “A Monte Carlo Study of the Effects of Correlated Method Variance in Moderated Multiple Regression Analysis.” Organizational Behavior and Human Decision Processes 36: 305-32.

Ferris, G. R., G. Adams, R. W. Kolodinsky, W. A. Hochwarter, and A. P. Ammeter. 2002. “Perceptions of Organizational Politics: Theory and Research Directions.” Chapter in The Many Faces of Multi Level Issues. Eds. F. J. Yammarino and F. Dansereau. Oxford, UK: Elsevier Science/JAI Press. pp. 179-254.

————, G. Harrell-Cook, and J. H. Dulebohn. 2000. “Organizational Politics: The Nature of the Relationship between Politics Perceptions and Political Behavior.” Chapter in Research in the Sociology of Organizations. Eds. S. B. Bacharach and E. J. Lawler. Stamford, CT: JAI Press. Pp. 89-130.

———— and W. A. Hochwarter. 2011. “Organizational Politics.” Chapter in APA Handbook of Industrial and Organizational Psychology, Vol 3: Maintaining, Expanding, and Contracting the Organization. Ed. S. Zedeck, 435-459. Washington, DC: American Psychological Association.

———— and T. A. Judge. 1991. “Personnel/Human Resources Management: A Political Influence Perspective.” Journal of Management 17: 447-488.

98

JAMES AND SHAW


————, G. S. Russ, and P. M. Fandt. 1989. “Politics in Organizations.” Chapter in Impression Management in the Organization. Eds. R. A. Giacalone and P. Rosenfeld. Hillsdale, NJ: Lawrence Erlbaum. pp. 143-170.

Gandz, J. and V. Murray. 1980. “The Experience of Workplace Politics.” Academy of Management Journal 23: 237-251.

Hochwarter, W. A., M. L. James, D. Johnson, and G. R. Ferris. 2004. “The Interactive Effects of Politics Perceptions and Trait Cynicism on Work Outcomes.” Journal of Leadership and Organizational Studies 10: 44-57.

————, C. Kacmar, P. L. Perrewé, and D. Johnson. 2003. “Perceived Organizational Support as a Mediator of the Relationship between Politics Perceptions and Work Outcomes.” Journal of Vocational Behavior 63: 438-456.

Johnson, J. and A. O’Leary-Kelly. 2003. “The Effects of Psychological Contract Breach and Organizational Cynicism: Not All Social Exchange Violations are Created Equal.” Journal of Organizational Behavior 24: 627-647.

Kacmar, K. M. and R. A. Baron. 1999. “Organizational Politics: The State of the Field, Links to Related Processes, and an Agenda for Future Research.” Chapter in Research in Personnel and Human Resources Management. Ed. G. R. Ferris. Stamford, CT: JAI Press. pp. 1-39.

Kanter, D. L. and P. H. Mirvis. 1989. The Cynical Americans. San Francisco, CA: Jossey-Bass.

Kickul, J. R., G. Neuman, C. P. Parker, and J. Finkl. 2001. “Settling the Score: The Role of Organizational Justice in the Relationship between Psychological Contract Breach and Anticitizenship Behavior.” Employee Responsibilities and Rights Journal 13: 77-93.

Kiewitz, C., S. L. D. Restubog, T. Zagenczyk, and W. A. Hochwarter. 2009. “The Interactive Effects of Psychological Contract Breach and Organizational Politics on Perceived Organizational Support: Evidence from Two Longitudinal Studies.” Journal of Management Studies 46: 806-834.

Kim, T., T. S. Bateman, B. Gilbreath, and L. M. Andersson. 2009. “Top Management Credibility and Employee Cynicism: A Comprehensive Model.” Human Relations 62: 1435-1458.

Lewin, K. 1936. Principles of Topological Psychology. New York: McGraw-Hill. Levinson, H., C. Price, K. Munden, H. Mandl, and C. Solley. 1962. Men, Management

and Mental Health. Cambridge, MA: Harvard Press. Lipset, S. M. and W. Schnieder. 1983. The Confidence Gap: Business, Labor, and Government

in the Public Mind. New York: The Free Press. McLean Parks, J. and D. L. Kidder. 1994. “Till Death Us Do Part . . .: Changing Work

Relationships in the 1990s.” Chapter in Trends in Organizational Behavior. Eds. C. L. Cooper and D. M. Rousseau. New York: Wiley. pp. 112-133.

Mintzberg, H. 1985. “The Organization as Political Arena.” Journal of Management Studies 22: 133-154.

————. 1983. Power In and Around Organizations. Englewood Cliffs, NJ: Prentice-Hall. Morrison, E. and S. Robinson. 1997. “When Employees Feel Betrayed: A Model of How

Psychological Contract Violation Develops.” Academy of Management Review 22: 226-256.

Neves, P. 2012. “Organizational Cynicism: Spillover Effects on Supervisor-Subordinate Relationships and Performance.” The Leadership Quarterly 23: 965-976.

99



Parker, C., R. Dipboye, and S. Jackson. 1995. “Perceptions of Organizational Politics: An Investigation of Antecedents and Consequences.” Journal of Management 5: 891-912.

Parzefall, M. and J. A-M. Coyle-Shapiro. 2011. “Making Sense of Psychological Contract Breach.” Journal of Managerial Psychology 26: 12-27.

Paul, R. J., B. P. Niehoff, and W. H. Turnley. 2000. “Empowerment, Expectations, and the Psychological Contract: Managing the Dilemmas and Gaining the Advantages.” The Journal of Socio-Economics 29: 471-486.

Podsakoff, P. M. and D. W. Organ. 1986. “Self-reports in Organizational Research: Problems and Prospects.” Journal of Management 12: 531-544.

Reichers, A. E., J. P. Wanous, and J. T. Austin. 1997. “Understanding and Managing Cynicism about Organizational Change.” Academy of Management Executive 11: 48-59.

Robinson, S. L. 1996. “Trust and Breach of the Psychological Contract.” Administrative Science Quarterly 41: 574-599

———— and E. W. Morrison. 2000. “The Development of Psychological Contract Breach Violation: A Longitudinal Study.” Journal of Organizational Behavior 21: 525-546.

———— and D. M. Rousseau. 1994. “Violating the Psychological Contract: Not the Exception but the Norm.” Journal of Organizational Behavior 15: 245-259.

Rosen, C. C., C. Chang, R. E. Johnson, and P. E. Levy. 2009. “Perceptions of Organizational Context and Psychological Breach: Assessing Competing Perspectives.” Organizational Behavior and Human Decision Processes 108: 202-217.

Rousseau, D. M. 1995. Psychological Contracts in Organizations: Understanding Written and Unwritten Agreements. Thousand Oaks, CA: Sage.

————. 1989. “Psychological and Implied Contracts in Organizations.” Employee Responsibilities and Rights Journal 2: 121-139.

Salanick, G. R. and J. Pfeffer. 1978. “A Social Information Processing Approach to Job Attitudes and Task Design.” Administrative Science Quarterly 23: 224-252.

Schwab, D. P. 1999. Research Methods for Organizational Studies. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

Spector, P. E. 2006. “Method Variance in Organizational Research: Truth or Urban Legend?” Organizational Research Methods 9: 221-232.

Tate, R. 1998. An Introduction to Modeling Outcomes in the Behavioral and Social Sciences. Edina, MN: Burgess Publishing.

Tomprou, M., D. M. Rousseau, and S. D. Hansen. 2015. “The Psychological Contracts of Violation Victims: A Post-Violation Model.” Journal of Organizational Behavior 36: 561-581.

Watson, D., L. Clark, and A. Tellegen. 1988. “Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scale.” Journal of Personality and Social Psychology 54: 465-490.

Wilkerson, J. M. 2002. “Organizational Cynicism and its Impact on Human Resource Management.” Chapter in Human Resources Management: Perspectives, Context, Functions, and Outcomes. Eds. G. R. Ferris, M. R. Buckley, and D. B. Fedor. Upper Saddle River, NJ: Prentice Hall

100



Acquiring Emotional Sea Legs:

Navigating Joy and Sadness in Ethical Decisions

Sukumarakurup Krishnakumar Associate Professor

North Dakota State University [email protected]

Maria Evglevskikh

MBA North Dakota State University

[email protected]

In spite of trainings, warnings, and punitive measures, ethical scandals seem to prevail, if not increase in the corporate world (De Cremer and Lemmich, 2015). This points to the complexity underlying the process of ethical decision-making (EDM), which is defined as the process of perceiving, judging, and choosing a morally appropriate decision (Treviño et al., 2006). Studies show that ethical issues are prevalent in workplaces and employees can harbor unethical behavioral tendencies. In a recent report which asked more than 1200 business professionals from a wide variety of occupations, one out of three people said that they have been aware of unethical behavior at the workplace, and one out of every four people suggested that they would exploit private information to make money if they knew they would not be caught or arrested (Alton, 2015). In response to such ethical concerns, companies have attempted to enact compliance-related policies and procedures, which may not have had the intended prevention effect on managerial EDM (De Cremer and Lemmich, 2015).

On a different note, evidence shows that employees engage in positive, ethical behaviors in light of temptations to act unethically. There are examples of such prosocial and ethical behaviors as returning large amounts of cash that were lost by customers (e.g., Lacitis, 2013; Pike, 2015) and whistleblowing (Philpott, 2015). These examples show that ethical dilemmas, defined as moral decision-situations in which the choices are not clear for the decision-maker, are complex. These examples also show that the decisions made in response to such dilemmas can be more or less ethical depending on a plethora of individual and situational factors. The increased complexity, in some ways,

(101)

ACQUIRING EMOTIONAL SEA LEGS


distinguishes generic business decision-making processes (e.g., choosing the right investments) from ethical decision-making processes (e.g., reporting unethical behavior to authorities) by its reliance on morality, which is inherently an emotional construct for decision-makers (Manfrinati et al., 2013; Shenhav and Greene, 2014). The presence and influence of emotions, thus, makes it imperative that their influences on EDM are studied.

Emotions are inevitable actors in the ethical decision-making process. Primarily, ethical dilemmas have been shown to induce tension or negative affect prior to or during the decision-making process (Guzak, 2015). Emotions elicited directly from a decision-maker’s target or a situation that directly concerns the decision are called integral emotions (Schmeichel and Inzlicht, 2013). Therefore, in most ethical decision scenarios, integral emotions are negatively valenced due to the inherent conflicts involved in an ethical dilemma. Even so, emotions are not just elicited from the dilemmas, but also from the context in which such ethical scenarios exist. From a practical perspective, organizations have been working towards implementing positively oriented policies and procedures generally as well as with respect to ethical decision-making (Meyer, 2015). Such a focus on positive contextual aspects are evident in recent work in positive psychology, where the elicitation of positive emotions are being studied. Organizations are especially interested in such positive emotions because it can lead to greater employee well-being (Hart et al., 2015), lesser turnover (Siu et al., 2015) and better ethical decisions (Dietz and Kleinlogel, 2014). Implementation of positive policies and procedures potentially elicits positive emotions—ones that are not necessarily connected to an ethical dilemma that may arise at work. Such emotions elicited from the general context and not connected to the target or the decision-situation at hand are called incidental emotions (Schmeichel and Inzlicht, 2013). Both incidental and integral emotions are operationalized as state emotions as opposed to dispositional or trait affect in this study.

In this paper, the role of such emotions on the EDM process is elucidated using experimental procedures. The main purpose of this paper is not to differentiate or to compare the sources of integral and incidental emotions, but to study how these emotions, which can be diverse in their valences, can overlap and perhaps affect each other in the context of EDM. Because different emotions are involved, the role of emotion regulation ability (ERA), defined as the ability of individuals to effectively process and regulate emotions, is also examined in relation to EDM.

ETHICAL DECISION-MAKING AND EMOTIONS

Early history of studying decision-making through the prism of dual-process

frameworks seems to reflect the modern debate about the roles of cognition (or reason) and emotion in ethical decision-making (Strack and Deutsch, 2004). On the one hand, such philosophers as Hume (1888) have suggested that ethical decisions are based on sentiment. On the other hand, Socrates, Plato, and others cautioned people from infusing emotion into ethical decisions. Finally, Immanuel Kant (1785, c.f., Schnall et al., 2008) has discussed the role of emotions in ethical decisions as well. A dual process approach, similar to the classical “reflective” (thoughtful and rational) versus impulsive (sentiment/emotion driven) approach has also been suggested (Reynolds, 2006; Treviño et al., 2006). Even so, the history of EDM has mostly seen the dominance of the

102

KRISHNAKUMAR AND EVGLEVSKIKH


rationalist or cognitive paradigm in action until perhaps about a decade ago (Haidt, 2008). In the cognitive paradigm, the EDM process follows a four-stage sequence from the basic stage of moral awareness, followed by moral judgment, intentions, and results in the final step of ethical behavior or decision-making (Rest, 1986). This cognitive theory of EDM includes additional factors such as the intensity of the ethical issue at hand (Jones, 1991), the philosophical basis of decision intentions (Kujala et al., 2011), and the stages of moral development (Jones, 1991). Though the cognitive theory of EDM has been studied over several years, the role of emotions has not been extensively studied (Rogerson et al., 2011). More recently, there is increased interest in studying the role of emotions in ethical decision-making (e.g., Thiel et al., 2011).

Emotions play an important role in morality and ethical decision-making (Huebner et al., 2009). One of the first conceptual frameworks about the role of emotion in EDM was put forth by Gaudine and Thorne (2001). Their research suggested that positive emotion generally facilitates the EDM process. The role of negative emotions, though, was left unclear. The role of emotions was even more prominently featured in the affective-intuitive model highlighted in research by Haidt (2007, 2008) and others (e.g., Connelly et al., 2004; Horberg et al., 2011). Their research shows that emotions affect EDM in two ways. First, emotions elicited from the situation can direct individuals towards a more (or less) ethical choice. Here, emotions are more likely to be elicited from the ethical situation itself. Such emotions are called integral emotions. For example, a manager can be particularly discouraged to speak up against unethical practices because of fear and nervousness elicited from a particular ethical dilemma. Anger towards an unethical act which violates the norms, or fear of retribution for reporting an unethical act can facilitate or hinder ethical decision-making respectively (Henik, 2008). The direct and quick effect of emotions can also occur through such integral emotions as guilt and disgust. Haidt’s (2007) research has centered on the moral emotion of disgust, particularly as a factor in intuitively promoting more ethical choices because of gut level disgusted reactions to certain kinds of moral scenarios. As Haidt (2007) notes, a disgusting moral scenario can be repulsive to people on a gut level, and such repulsion because of guilt can guide individuals to a more ethical choice rather than a less ethical choice. Here emotion serves as a pointer, serving enough information in a more intuitive and instinctual manner to the decision-maker resulting in a more ethical rather than a less ethical decision. In sum, most of the above-mentioned research studies look at the influence of emotions elicited from the ethical decisions themselves.

Emotions that are unrelated to the ethical dilemma and are elicited from the general context, called incidental emotions, can also influence judgement and decision-making (Forgas, 1995). Such emotions, rather than pointing the decision-maker in a certain direction or towards a certain choice, can act through an indirect pathway—one in which they color or bias judgments. Research has examined how appraisals formed from different and unique emotions can color or promote certain kinds of moral judgments (Horberg et al., 2011; Keltner et al., 2006). Evidence indicates that emotions have domain or valence specific effects, emotion-specific effects, and embodiment effects. Here, the positivity or negativity of emotions could spill over into judgments, coloring them, and making individuals form more negative judgments when feeling a negative emotion such as sadness or form more positive judgments when they feel the positive emotion of joy. More recent research also shows that positive or negative emotions can help individuals to process information differently. Positive emotions such

103



as joy and awe can facilitate a more accommodative or a casual processing style, thereby helping individuals to use a wider range of information, often creatively, to make decisions (Fredrickson and Branigan, 2003; Mantel, 2005; Piff et al., 2015). In the context of EDM, this means that individuals are better able to see nuances involved in an otherwise unclear ethical dilemma. Research in broader domains support this notion, including studies with creativity (e.g., Shin, 2014) and decision-making (e.g., Isen, 2008). Thus, it is hypothesized that positive affect, such as joy will facilitate ethical decision-making because individuals are able to see broader and more diverse cognitive perspectives and thus examine and evaluate multiple criteria more effectively when they are feeling positive emotions.

Hypothesis 1: Joviality will facilitate ethical decision-making.

However, there is a potential for a contradictory finding. Although they facilitate divergent, broad, and accommodative thinking styles, positive emotions can also induce individuals to use heuristic and perhaps intuitive thinking styles when making ethical decisions. This can cause individuals to not consider important aspects of the ethical dilemma. For example, recent research shows that individuals who are experiencing positive incidental emotions tend to disregard the magnitude of consequences involved in their EDM process (Winterich et al., 2014). Such findings point to a possible role for the ability of decision-makers to process and use emotions more appropriately in their thought and judgment processes. The specific ability to regulate emotions for productive purposes is called emotion regulation ability. Such abilities have received increased attention more recently and are included under the broader domain of emotional intelligence (Mayer et al., 2008).

EMOTION REGULATION ABILITY

Emotions are ubiquitous and substantially relevant in organizational processes

especially in decision-making involving intense ethical dilemmas (Barsade et al., 2003). As more attention is being given to emotions and their roles in decision-making, findings have emerged showing the effect of abilities of decision-makers to process emotional information. Such abilities involving the accurate perception, thorough understanding, and effective management of emotions have been included as the three branches of the global construct of emotional intelligence (EI; Mayer and Salovey, 1997; Newman et al., 2010). The most applied of EI’s dimensions, management, operationalized here as emotion regulation ability (ERA), involves the ability to regulate emotions appropriately and effectively to achieve a productive purpose. High-ERA employees, because of their ability to change and modify emotions are better able to reduce emotions that hinder EDM and enhance emotions that can facilitate EDM. Research suggests that such an emotion regulation ability (ERA) helps individuals in making more ethical choices (Krishnakumar and Rymph, 2012). This could be because of the general ability of high-ERA individuals to process emotional information in a more productive and clearer manner. When an ethical dilemma presents difficult or grey choices which naturally include emotional stimuli, high-ERA individuals are able to use information from those emotional stimuli to guide them towards choices that are more effective and yet ethical. As shown earlier, EDM processes have been shown to be affected by both

104



incidental and integral emotions. Irrespective of the sources of emotions elicited before, during, and after the EDM process, ERA can play a significant role in regulating emotions in such a way as to maximize the ethicality of the decisions made. Therefore, in this study, ERA is expected to have a positive and direct effect on EDM, especially when the ethical dilemma is more intense and when it elicits more integral sadness (conceptual model depicted in Figure 1).

Figure 1 Theoretical model depicting the moderating effects of both Emotion

Regulation Ability and negative integral effect on the relationship between joy and ethical decision-making.

Hypothesis 2: High-ERA individuals will make more ethical choices than low-

ERA individuals when the EDM scenario is more intense and when it elicits more integral sadness than when the EDM scenario is neutral/elicits less integral sadness.

Furthermore, it is important to understand the nuances of the effects of emotions on different kinds of EDM scenarios. In Jones’s (1991) terms, this would be included under two factors: magnitude of consequences and proximity. Magnitude of consequences relate to the seriousness of the effects of a decision, whereas proximity refers to the closeness of the target involved in EDM. Some EDM scenarios elicit lesser amounts of integral affect (mostly negative, if any). As operationalized in this study, this may involve the act of reporting a neutral person to authorities for engaging in unethical behavior. Here, the lesser amount of integral affect may be produced due to a combination of lower magnitude of consequences and higher proximity. Other EDM scenarios can involve more tension or greater levels of integral negative affect. As operationalized in this study, this may involve the act of reporting a close friend to authorities for engaging in unethical behavior. In the former situation, any incidental emotion that the decision-maker feels carries over to the actual EDM scenario, whereas in the latter situation with a friend, the incidental emotions are likely to be affected or changed due to the integral affect produced by the EDM scenario itself. In this regard,

Integral Sadness (Elicited from the EDM scenario)

Ethical Decision-makingIncidental Joy

Emotion Regulation Ability

105



to the extent that the decision-maker is experiencing a positive incidental emotion, there is a potential for ignoring details involved in the ethical dilemma because here the emotion can be a distraction rather than a pointer to a more ethical path. As shown in recent work, individuals who are experiencing a substantial amount of positive emotions tend to take a faster, heuristic approach rather than a slower, more detailed or methodical approach to making decisions (Winterich et al., 2014). High-ERA decision-makers, through their ability to regulate emotions appropriately, will be able to control the effects of positive emotion by regulating the tendency to rely on excessive heuristic processing. Therefore, a positive emotion such as joy will enhance EDM in high-ERA individuals, but not in low-ERA individuals.

When the EDM scenario involves an ethical dilemma that has the potential to generate more negative emotions, such negative emotions can counteract the effect of any positive emotions present in the context (incidental) making the processing more detailed and methodical thereby reducing the potential role of ERA. In short, in a more sadness-evoking ethical dilemma, the role of ERA will be much limited as the individuals already are prone to detailed processing and careful decision-making. Integrating all of these possibilities, the following three-way moderation is hypothesized:

Hypothesis 3: There will be a three-way moderation involving incidental joy,

intensity of the integral sadness, and emotion regulation ability such that in a low integral sadness scenario, high-ERA individuals will make better ethical decisions as they experience more joy; whereas low-ERA individuals will make poorer ethical decisions as they experience more joy. This effect will not be seen in the high-integral sadness scenario.

METHOD

Sample

Undergraduate business students (N = 228) taking foundation courses in business at a medium-sized university in the Midwestern USA were invited to participate in this study of which 156 responded (response rate = 72.8%). Out of these respondents, 36% were female, 87.3% were Caucasian, and they had a mean age of 21.3 years. Most students (70.5%) worked full-time or part time, on average 19.8 hours per week. Participants received extra-credit for the study.

Procedure

The study consisted of a combination of survey and experimental design with one of the factors, intensity of integral sadness, being manipulated (high versus low intensity of integral sadness). Except for the intensity levels, other variables were continuous and measured through surveys. The study was divided into two parts to accommodate participants’ time limitations and decrease possibility of them losing interest and attention while taking a survey. All 156 students took the first part of the survey that included a measure of emotion regulation ability (measure described below). After approximately ten days, the second part was administered. This part included measures of state emotion (joy) and a version of the ethical decision-making scenario, based on

106



the experimental condition they were assigned. The full scenario and the modifications are described below. Participants were assigned to one of two experimental conditions based on the type of EDM scenario they saw. Approximately half of the participants were shown the un-manipulated EDM scenario and asked to make decisions (Sims, 1999). This un-manipulated EDM scenario was used to measure EDM with a scenario eliciting low intensity of integral sadness. The other random half of the respondents saw a modified EDM scenario which was manipulated to elicit more integral sadness. As described in Krishnakumar and Rymph (2012), the modification makes it such that it is harder for the decision-maker (respondent) to make a more ethical decision.

Measures

Emotion Regulation Ability. ERA was measured with MacCann and Roberts’ (2008) ability-based measure called Situational Test of Emotion Management (STEM). This measure includes 44 scenarios from the original measure that are divided into three main sections: 18 scenarios with anger content, 14 scenarios with sadness content, and 12 scenarios with fear content. Students received the questions in randomized order. A sample item is given below.

Darla is nervous about presenting her work to a group of seniors who might not understand it, as they don’t know much about her area. What action would be the most effective for Darla? (a) Be positive and confident, knowing it will go well. (b) Just give the presentation. (c) Work on her presentation, simplifying the explanations. (d) Practice presenting to laypeople such as friends or family.

A multiple-choice format was used and the items were scored using keys in the

supplement provided with MacCann and Roberts (2008). Adequate reliability ( = 0.63) was obtained, consistent with previous studies.

Incidental Joy. Incidental Joy was measured using eight items from the Positive Affect Negative Affect Schedule-Expanded version (PANAS-X) that included items such as happy, joyful, delighted, cheerful, excited, enthusiastic, lively, and energetic (Watson and Clark, 1999). Respondents were asked to report on how they felt during the last three days by rating the items on a Likert scale of 1 to 5 (very slightly or not at all – extremely; Cronbach’s = 0.94).

Ethical Decision-making. To measure ethical decision-making, a scenario developed and validated by Sims (1999) and modified by Krishnakumar and Rymph (2012) was used. The original and the modified versions were selected for two reasons. First, these measures consist of two versions of the same scenario: a low-integral sadness eliciting ethical scenario and high-integral sadness eliciting ethical scenario, depicting their potentials to elicit low and high levels of integral sadness respectively. The original scenario, also called the low-sadness scenario, presents respondents with a moral dilemma in a work-related setting where a respondent has to pick the best response/decision to the dilemma. Here, the respondent has to decide to either report or to not report “a coworker.” The following example shows the scenario with low integral sadness:

107



“You have recently learned that a co-worker has been violating one of your company’s policies on an ongoing basis. This violation is quite serious and would look very bad for your department if it were discovered. The co-worker has more seniority than you, and he/she is well respected in the company. You are unsure if his/her behavior is illegal, but you are sure it is not right.”

The respondents were then provided with the following choices:

1. “Say nothing.” 2. “Confirm the violation only if I was specifically asked by management.” 3. “Mention the violation to the co-worker only, hoping that it would stop.” 4. “Report the violation to my supervisor only, letting it drop after that.” 5. “Make sure that the violation was corrected, no matter how far I would have

to go.”

The above-mentioned scenario was modified by Krishnakumar and Rymph (2012) where the “coworker” was also described as a “close friend” of theirs and “the sole income provider” for his/her family. This high-integral sadness scenario is as follows:

“You have recently learned that a co-worker has been violating one of your company's policies on an ongoing basis. This violation is quite serious and would look very bad for your department if it were discovered. The coworker has more seniority than you, and he/she is well respected in the company. She/he is also a very close friend of yours. You are also aware that he/she is the sole income provider for his/her household. Hence, this could lead to emotional consequences. You are unsure if her/his behavior is illegal, but you are sure it is not right.”

The responses were exactly the same as described above for the low-integral sadness

scenario. Just as scored in the original measure, each item was scored from 1 = least ethical (i.e., choice 1 above: “Say nothing.”) to 5 = most ethical (choice 5 above: “Make sure that the violation was corrected, no matter how far I would have to go”).

The modification, highlighted in bold text, was shown to elicit more sadness as a result of the decision-making process as it involves reporting a close friend and sole income provider. The second reason for selecting this measure was because of the additional information rendered by the modifications done by Krishnakumar and Rymph (2012). When asking the respondents to make a choice from available alternatives, there could be a potential problem. For example, all five of the choices available may not be perceived as being favorable or ethical to respondents, and so they might have chosen a slightly more ethical decision from among a largely unfavorable set of choices. To circumvent this problem, Krishnakumar and Rymph (2012) added two additional items in order to estimate the strength of a participant’s decision. The first additional item asked respondents to estimate the percentage of times they would make each of the above-mentioned decisions given another chance. This had a fixed sum response option, where all of their percentage estimates for the decisions should combine to a 100%. The ethicality of their decision was determined by the percentage value associated with the most ethical choice (“Make sure that the violation was corrected, no

108



matter how far I would have to go.”). The second additional item asked the respondents to rate their confidence in each of the options presented. In this item, participants rated their strength of each choice using a Likert scale from 1 = least confident to 5 = most confident. This item was scored by choosing the confidence rating associated with the most ethical choice. To determine the overall EDM score, the three items (decision choice, percentage score of the most ethical choice, and the confidence rating of the most ethical choice) were standardized and combined to form a composite. The Cronbach’s alphas for the low-integral and high intensity measures were 0.74 and 0.75 respectively.

RESULTS

Tables 1a and 1b present zero-order correlations produced from the two groups:

low-integral sadness and high-integral sadness. The overall hypothesis that joy would predict EDM was partially supported since joy was positively (but non-significantly; r = 0.19) correlated with EDM in the low-integral sadness group whereas it was positively and significantly correlated with EDM in the high-integral sadness group (r = 0.29, p<0.01). Results also show that ERA was more positively related to EDM in the high-integral sadness EDM group (r = 0.22, ns) than the low-integral sadness EDM group (r = -0.06, ns), though the effects were not significant. To test for interactions, the PROCESS macro, developed and validated by Hayes (2013), was used. The moderated regression analyses done by the macro is primarily based on methods developed by Aiken et al. (1991). Thus, using the PROCESS macro, a moderated two-way regression analyses with unstandardized ERA as the predictor, the experimental EDM condition (low- versus high-integral sadness; coded as 1 and 2 respectively) as the moderator, and EDM as the dependent variable (composite, average of standardized items) was conducted to determine if the differences in the effects of ERA was statistically significant between the two EDM conditions. Results show that the effects of ERA was stronger in the high-integral sadness condition, although the coefficient of the interaction was not significant at the 0.05 level (BERA*Cond. = 2.27; t = 1.79, p = 0.08). Therefore, Hypothesis 2 was not supported.

To test the hypothesis that individuals with higher ERA will be able to navigate joy better especially in the low-integral sadness condition, more so than the high-integral sadness condition, a moderated moderation analyses or a three-way moderated regression analyses was conducted using the PROCESS macro (Hayes, 2013). This hypothesis was supported, because the coefficient of the triple interaction term (Joy*ERA*EDM-Condition) was significant (Table 2; B = -2.78, t = -1.98, p = 0.05). This moderation effect was plotted using previously established procedures (Aiken et al., 1991; Dawson and Richter, 2006; Figure 2). As seen in the graph, ERA was a significant factor in helping individuals experiencing joy to make better decisions when the low-integral sadness scenario was presented to them. In the low-integral sadness scenario, low-ERA individuals, when feeling more joy tended to make worse ethical decisions, whereas high-ERA individuals were able to make better ethical decisions as they felt more joyful. The PROCESS macro also computes regression coefficients for the interaction between ERA and joy in both experimental conditions separately. These results reveal that the interaction between joy and ERA was significant in the low-integral sadness condition (B = 1.85; t = 2.20, p = 0.05) whereas it was not significant in the

109



high-integral sadness condition (B = -0.93; t = -0.88, p =0.38). As confirmed by the graph, it is seen that both high-ERA and low-ERA individuals, when they felt more joyful in the high-integral sadness condition, were able to make better ethical decisions.

Tab

le 1

a Ze

ro-o

rder

cor

rela

tion

s be

twee

n va

riab

les

in th

e ra

ndom

sam

ple

that

was

ad

min

iste

red

the

low

-int

egra

l sad

ness

eth

ical

dil

emm

a

Mea

n SD

1

2 3

4 5

1 A

ge

21.5

1 2.

31

-

2 G

ende

r 1.

39

0.49

-0

.25*

-

3 Jo

y 2.

88

0.97

-0

.06

0.08

0.

94

4 E

mot

ion

Reg

ulat

ion

Abi

lity

0.51

0.

12

-0.1

6 0.

16

-0.1

4 0.

63

5 E

thic

al D

ecis

ion-

Mak

ing

-0.0

1 0.

81

0.16

-0

.07

0.19

-0

.06

0.74

N

otes

. *p

< 0

.05

Tab

le 1

b Ze

ro-o

rder

cor

rela

tion

s be

twee

n va

riab

les

in th

e ra

ndom

sam

ple

that

was

ad

min

iste

red

the

high

-int

egra

l sad

ness

eth

ical

dil

emm

a

Mea

n SD

1

2 3

4 5

1 A

ge

21.1

1 1.

52

-

2 G

ende

r 1.

36

0.48

-0

.11

-

3 Jo

y 3.

06

0.90

0.

01

0.15

0.

94

4 E

mot

ion

Reg

ulat

ion

Abi

lity

0.51

0.

10

-0.1

3 0.

24*

0.15

0.

63

5 E

thic

al D

ecis

ion-

Mak

ing

0.00

0.

82

-0.2

2 0.

17

0.29

**

0.22

0.

75

Not

es. *

p <

0.0

5, *

*p <

0.01

110



Tab

le 2

H

iera

rchi

cal r

egre

ssio

n an

alys

es s

how

ing

the

inte

ract

ion

effe

cts

of E

RA

and

In

tens

ity

on th

e re

lati

onsh

ip b

etw

een

Joy

and

ED

M

B

SE

t

p

Con

stan

t 8.

36

3.55

2.

36

0.02

Em

otio

n R

egul

atio

n A

bilit

y -1

5.83

6.

57

-2.4

1 0.

02

Joy

-2.4

5 1.

14

-2.1

5 0.

03

Joy*

Em

otio

n R

egul

atio

n A

bilit

y 4.

63

2.12

2.

18

0.03

Eth

ical

Con

ditio

n -5

.66

2.32

-2

.44

0.02

Joy*

Con

ditio

n 1.

60

0.76

2.

12

0.04

Em

otio

n R

egul

atio

n A

bilit

y*C

ondi

tion

10.0

4 4.

34

2.31

0.

02

Joy*

Em

otio

n R

egul

atio

n A

bilit

y*C

ondi

tion

-2

.78

1.41

1.

98

0.05

Ove

rall

Reg

ress

ion

Mod

el S

umm

ary

R

R2

2 F

dfl

Df2

p

0.33

3 0.

11

0.03

2.

34

7 13

6 0.

03

111



Figure 2

The moderation effects of emotion regulation ability and intensity condition on the relationship between joy and ethical decision-making.

DISCUSSION

There is a rich history of research that has looked at the effect of emotions on

decision-making. It is understood generally that individuals do rely on their emotions while making decisions (Greifeneder et al., 2011). However, only recently have researchers started to investigate the potential influence of emotions in ethical decision-making. In fact, some have even suggested that emotions or emotional intuitions, as opposed to rationality, play a more important role than rational mechanisms (Haidt, 2007). This study took a more nuanced look at the sources of emotions within the EDM context by investigating potential influences of incidental and integral emotions. Additionally, the study also sought to clarify the role of emotion regulation ability as a contingency in EDM.

Broadly, the results show the interaction effects of positive emotion (joy) and ERA on EDM in two conditions, low- and high-integral sadness ethical scenarios. ERA had a significant moderating influence on the effect of joy on EDM in the low-integral sadness ethical decision scenario. This showed that ERA helped temper the overall stimulating effect of joy. Because ERA is part of a broader emotional intelligence construct that involves both cognition and emotion, ERA is a very appropriate construct to be studied in the context of ethical decision-making. It has been debated whether ethical decisions can be made by an impulsive, automatic process or a more detailed and rational process (Strack and Deutsch, 2004). The results indicated that the interaction effects of joy and ERA were more important when the ethical dilemma was low in integral sadness. Previous research shows that individuals tend to not rely on their feelings when the

1

1.5

2

2.5

3

3.5

4

4.5

5

Low Joy High Joy

Eth

ical

Dec

isio

n-M

akin

g

(1) High ERA, HighIntensity(2) High ERA, LowIntensity(3) Low ERA, HighIntensity(4) Low ERA, LowIntensity

112



emotions elicited are less salient (Greifeneder et al., 2011). Research also indicates that integral emotions can act as “markers” of information for the decision-makers. This hypothesis is called the affect-as-information hypothesis. Sadness, for example, can mark information in an ethical dilemma, congruent with its negative valence (Clore et al., 2001). When lesser integral emotions are present, there appears to be no guiding mechanism that individuals could use to make better decisions (Garber et al., 1991). Therefore, when the integral sadness was in lower amounts (low-intensity scenario), decision-makers may have had more uncertainty regarding the choices, and thus ERA could have played a more significant role in guiding them to make more ethical decisions.

In the general decision-making domain, positive affect has been found to expand cognitions, making individuals use casual shortcuts and creative alternatives while making decisions (Fredrickson, 2001). Note that unlike sadness elicited from the decision situation itself, joy may act from the outside or contextually through its indirect effects by affecting the way individuals process information. Unlike integral sadness, incidental joy may not directly guide individuals to focus their attention and cognitions on a particular issue within the decision situation itself. Research does indicate that positive emotions have a non-specific activation and freeing effect on individuals. As individuals become cognitively freer due to more joyfulness, without proper reasoning and focus on the moral issue at hand, decision-makers could make careless choices. This was seen in individuals with low ERA especially in the low-integral sadness condition, where the ethical scenario involved “a coworker” instead of “a close friend” in the high-intensity condition. Again, even in the presence of increasing joyfulness, presence of integral sadness due to the reporting of a “close friend” seemed to have helped individuals more. When this integral sadness was not present, the increase in joyfulness made low-ERA individuals make poorer ethical decisions.

MANAGERIAL IMPLICATIONS

There are several implications for these findings. First, results related to the effects

of the incidental positive emotion of joy on ethical decision-making confirm some of the earlier findings about the facilitatory effects of positive affect on decision-making (Fredrickson, 2001; Isen, 2001). Increased joyfulness does help in EDM. However, joyfulness may not be an effective facilitator of EDM in situations that are not intense in eliciting the integral negative emotions typically associated with some of the ethical dilemmas, and when the decision-makers are low in their emotion regulation ability. Therefore training and/or selection procedures that help increase ERA would be helpful to organizations as it can help employees make better ethical decisions. Second, the facilitatory effect of incidental positive emotions supports the idea that an organizational culture that promotes a joyful work atmosphere can result in helping employees make better ethical decisions. Additionally, research has also suggested that negative emotions can promote unethical behavior or discourage positive ethical behavior. For example, fear can discourage a form of unethical behavior such as whistleblowing (Henik, 2008) and hostility can facilitate Machiavellian tendencies (Krishnakumar and Robinson, 2015). In short, organizations should strive to reduce negative emotions and increase positive emotions at work. Finally, the guiding role of integral sadness, and consequently the role of salience in ethical dilemmas can also be significant to organizations. In fact,

113



based on the findings, making the ethical dilemma more salient or intense actually helped individuals to use joyfulness in a more effective way to make better ethical decisions. Therefore, organizations should make the inherent tension associated with ethical dilemmas more salient, at least during training sessions.

LIMITATIONS

This study had several limitations. First, this study utilized a student sample. The

scenarios provided for measuring EDM were based on workplace situations; therefore, one would expect some level of inexperience within the student sample. However, the background data that were gathered about the sample indicate that more than 70 percent of the students worked full or, at least, part time, therefore leading one to believe that the majority of the sample had enough experience to assess the work-related scenarios presented in this study. Also, Sims (1999) has shown that the scenarios were effective in both student and employee samples. Second, only one ethical decision-making scenario was presented. There could be other scenarios where emotions could have different effects on the kinds of choices made by individuals. In spite of these limitations, the study contributes to the relatively nascent research area of emotions in ethical decision-making.

References Aiken, L. S., S. G. West, and R. R. Reno. 1991. Multiple Regression: Testing and Interpreting

Interactions. Sage. Alton, L. 2015. “Report: ‘Unethical Behavior’ Continues to Plague Financial Services

Industry.” Business Ethics Magazine. Barsade, S. G., A. P. Brief, and S. E. Spataro. 2003. “The Affective Revolution in

Organizational Behavior: The Emergence of a Paradigm.” In J. Greenberg (Ed.) Organizational Behavior: The State of the Science (2nd ed.). 3-52. Mahwah, NJ: Lawrence Erlbaum Associates Publishers.

Clore, G. L., K. Gasper, and E. Garvin. 2001. “Affect as Information.” J. P. Forgas (Ed) Handbook of Affect and Social Cognition. Mahwah, NJ: Lawrence Erlbaum Associates Publishers, xviii, 457 pp. (pp. 121-144).

Connelly, S., W. Helton-Fauth, and M. Mumford. 2004. “A Managerial In-Basket Study of the Impact of Trait Emotions on Ethical Choice.” Journal of Business Ethics 51(3): 245-267.

Dawson, J. F. and A. W. Richter. 2006. “Probing Three-way Interactions in Moderated Multiple Regression: Development and Application of a Slope Difference Test.” Journal of Applied Psychology 91(4): 917.

De Cremer, D. and B. Lemmich. 2015. “Compliance Alone Won’t Make Your Company Safe.” Harvard Business Review. Harvard Business Press.

Dietz, J. and E. P. Kleinlogel. 2014. “Wage Cuts and Managers’ Empathy: How a Positive Emotion Can Contribute to Positive Organizational Ethics in Difficult Times.” Journal of Business Ethics 119(4): 461-472.

114



Forgas, J. P. 1995. “Mood and Judgment: The Affect Infusion Model (AIM).” Psychological Bulletin 117: 39.

Fredrickson, B. L. 2001. “The Role of Positive Emotions in Positive Psychology: The Broaden-and-Build Theory of Positive Emotions.” American Psychologist 56(3): 218.

———— and C. Branigan. 2003. “Positive Emotions Broaden the Scope of Attention and Thought action Repertoires.” Cognition & Emotion 19(3): 313-332.

Garber, J., N. Braafladt, and J. Zeman. 1991. “The Regulation of Sad Affect: An Information-Processing Perspective." Chapter in The Development of Emotion Regulation and Dysregulation. Eds. J. Garber and K. A. Dodge. New York, NY: Cambridge University Press. pp. 208-240

Gaudine, A. and L. Thorne. 2001. “Emotion and Ethical Decision-Making in Organizations.” Journal of Business Ethics 31(2): 175-187.

Greifeneder, R., H. Bless, and M. T. Pham. 2011. “When Do People Rely on Affective and Cognitive Feelings in Judgment? A Review.” Personality and Social Psychology Review 15(2): 107-141.

Guzak, J. R. 2015. “Affect in Ethical Decision Making: Mood Matters.” Ethics & Behavior 25(5): 386-399.

Haidt, J. 2008. “The Emotional Dog and its Rational Tail: A Social Intuitionist Approach to Moral Judgment.” Chapter in J. E. Adler and L. J. Rips (Eds.) Reasoning: Studies of Human Inference and its Foundations. New York, NY: Cambridge University Press. 1024-1052.

————. 2007. “The New Synthesis in Moral Psychology.” Science 316(5827): 998-1002. Hart, P. M., P. Cotton, and C. E. Scollay. 2015. “Flourishing at Work: Improving

Wellbeing and Engagement.” In R. J. Burke, K. M. Page, and C. L. Cooper (Eds.) Flourishing in Life, Work and Careers: Individual Wellbeing and Career Experiences. Northampton, MA: Edward Elgar Publishing. pp. 281-312.

Hayes, A. F. 2013. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-based Approach. New York, NY: Guilford Press.

Henik, E. 2008. “Mad as Hell or Scared Stiff? The Effects of Value Conflict and Emotions on Potential Whistle-blowers.” Journal of Business Ethics 80(1): 111-119.

Horberg, E. J., C. Oveis, and D. Keltner. 2011. “Emotions as Moral Amplifiers: An Appraisal Tendency Approach to the Influences of Distinct Emotions upon Moral Judgment.” Emotion Review 3(3): 237-244.

Huebner, B., S. Dwyer, and M. Hauser. 2009. “The Role of Emotion in Moral Psychology.” Trends in Cognitive Sciences 13(1): 1-6.

Hume, D. 1888. Treatise on Human Nature. L. A. Selby-Bigge (Ed.). Isen, A. M. 2008. “Some Ways in Which Positive Affect Influences Decision Making and

Problem Solving.” Chapter in M. Lewis, J. M. Haviland-Jones, and L. F. Barrett (Eds.), Handbook of Emotions (3rd ed.). New York, NY: Guilford Press. pp. 548-573.

————. 2001. “An Influence of Positive Affect on Decision Making in Complex Situations: Theoretical Issues with Practical Implications.” Journal of Consumer Psychology 11(2): 75-85.

Jones, T. M. 1991. “Ethical Decision Making by Individuals in Organizations: An Issue-Contingent Model.” Academy of Management Review 16(2): 366-395.

Keltner, D., E. J. Horberg, and C. Oveis. 2006. “Emotions as Moral Intuitions.” Chapter in J. P. Forgas (Ed.) Affect in Social Thinking and Behavior. New York, NY: Psychology Press. pp. 161-175.

115



Krishnakumar, S. and M. D. Robinson. 2015. “Maintaining An Even Keel: An Affect-Mediated Model of Mindfulness and Hostile Work Behavior.” Emotion 15(5): 578-589.

———— and D. Rymph. 2012. “Uncomfortable Ethical Decisions: The Role of Negative Emotions and Emotional Intelligence in Ethical Decision-Making.” Journal of Managerial Issues 24(3): 339-362.

Kujala, J., A. M. Lämsä, and K. Penttilä. 2011. “Managers’ Moral Decision-Making Patterns Over Time: A Multidimensional Approach.” Journal of Business Ethics 100(2): 191-207.

Lacitis, E. 2013. “Hero with a $20,000 Heart: Walmart Worker Honored For Returning Cash Left In Cart.” The Seattle Times. Seattle, Washington.

MacCann, C. and R. D. Roberts. 2008. “New Paradigms for Assessing Emotional Intelligence: Theory and Data.” Emotion 8(4): 540-551.

Manfrinati, A., L. Lotto, M. Sarlo, D. Palomba, and R. Rumiati. 2013. “Moral Dilemmas and Moral Principles: When Emotion and Cognition Unite.” Cognition and Emotion 27(7): 1276-1291.

Mantel, S. P. 2005. “Choice or Perception: How Affect Influences Ethical Choices Among Salespeople.” Journal of Personal Selling & Sales Management 25(1): 43-55.

Mayer, J. D. and P. Salovey. 1997. “What is Emotional Intelligence?” In P. Salovey and D. J. Sluyter (Eds.) Emotional Development and Emotional Intelligence: Educational Implications. New York, NY: Basic Books. pp. 3-34

————, ————, and D. R. Caruso. 2008. “Emotional Intelligence: New Ability or Eclectic Traits?” American Psychologist 63(6): 503-517.

Meyer, M. 2015. “Positive Business: Doing Good And Doing Well.” Business Ethics: A European Review 24(Suppl 2): S175-S197.

Newman, D. A., D. L. Joseph, and C. MacCann. 2010. “Emotional Intelligence and Job Performance: The Importance of Emotion Regulation and Emotional Labor Context.” Industrial and Organizational Psychology-Perspectives on Science and Practice 3(3): 384-384.

Philpott, T. 2015. “USDA Whistleblowers Tell All–and You May Never Eat Bacon Again.” Mother Jones. February 27, 2015. http://www.motherjones.com/tom-philpott/2015/02/usda-whistleblowers-report-gross-condition-hog-slaughterhouses.

Piff, P. K., P. Dietze, M. Feinberg, D. M. Stancato, and D. Keltner. 2015. “Awe, The Small Self, and Prosocial Behavior.” Journal of Personality and Social Psychology 108(6): 883-899.

Pike, H. 2015. “Calgary Cab Driver Returns Lost Bag with More Than $10,000 Cash Inside.” Metro News. Calgary, Canada.

Rest, J. 1986. Moral Development: Advances in Research and Theory. New York, NY: Praeger. Reynolds, S. J. 2006. “A Neurocognitive Model of the Ethical Decision-Making Process:

Implications for Study and Practice.” Journal of Applied Psychology 91(4): 737-748. Rogerson, M. D., M. C. Gottlieb, M. M. Handelsman, S. Knapp, and J. Younggren. 2011.

“Nonrational Processes in Ethical Decision Making.” American Psychologist 66(7): 614-623.

Schmeichel, B. J. and M. Inzlicht. 2013. “Incidental and Integral Effects of Emotions on Self-Control.” In M. D. Robinson, E. Watkins, and E. Harmon-Jones (Eds.) Handbook of Cognition and Emotion. New York, NY: Guilford Press. pp. 272-290.

116



Schnall, S., J. Haidt, G. L. Clore, and A. H. Jordan. 2008. “Disgust as Embodied Moral Judgment.” Personality and Social Psychology Bulletin 34(8): 1096-1109.

Shenhav, A. and J. D. Greene. 2014. “Integrative Moral Judgment: Dissociating the Roles of the Amygdala and Ventromedial Prefrontal Cortex.” The Journal of Neuroscience 34(13): 4741-4749.

Shin, Y. 2014. “Positive Group Affect and Team Creativity: Mediation of Team Reflexivity and Promotion Focus.” Small Group Research 45(3): 337-364.

Sims, R. L. 1999. “The Development of Six Ethical Business Dilemmas.” Leadership & Organization Development Journal 20(4): 189-197.

Siu, O. L., F. Cheung, and S. Lui. 2015. “Linking Positive Emotions to Work Well-Being and Turnover Intention Among Hong Kong Police Officers: The Role of Psychological Capital.” Journal of Happiness Studies 16(2): 367-380.

Strack, F. and R. Deutsch. 2004. “Reflective and Impulsive Determinants of Social Behavior.” Personality and Social Psychology Review 8(3): 220-247.

Thiel, C., S. Connelly, and J. Griffith. 2011. “The Influence of Anger on Ethical Decision Making: Comparison of a Primary and Secondary Appraisal.” Ethics & Behavior 21(5): 380-403.

Treviño, L. K., G. R. Weaver, and S. J. Reynolds. 2006. “Behavioral Ethics in Organizations: A Review.” Journal of Management 32(6): 951-990.

Watson, D. and L. A. Clark. 1999. “The PANAS-X: Manual for the Positive and Negative Affect Schedule - Expanded Form.” http://ir.uiowa.edu/psychology_pubs/11

Winterich, K. P., A. C. Morales, and V. Mittal. 2014. “Disgusted or Happy, it is Not So Bad: Emotional Mini-Max in Unethical Judgments.” Journal of Business Ethics 130: 343-360.

117

Journal of Managerial Issues

Manuscript Style Guide

Manuscripts must conform to the following guidelines:

Typed papers should be double-spaced, 25 pages in length (maximum) and sent via e-mail to [email protected].

Footnotes are discouraged and should be put in the main text where possible.

Include a brief abstract (no more than 250 words) that presents the main points of the paper, three to five keywords must be supplied with the abstract.

Cite references in the body of the text – for example, (Smith, 1984b: 32; Pope, 2006; Mir et al., 2007). References should follow the following format for books: Bright, S. M. and M. Doud. 1999. New Marketing Developments. New York, NY: Holt, Rinehart, and Winston. For Journals: Jade, N. J. 2006. “The Choice among Debt, Equity and Convertible Bonds.” The Journal of Finance 29 (October): 139-51.

If in doubt, consult The Chicago Manual of Style. A more complete style guide is available upon request. Pittsburg State University Pittsburg, Kansas 66762

Pittsburg State University Journal of Managerial IssuesPittsburg, KS 66762

volume xxviii number 1-2 spring/summer 2016web.pdf · mahmoud nourayi, loyola marymount ... jason...

Documents