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THE IMPACT OF THE PERCEPTION
OF THE WORK ENVIRONMENT
ON EMPLOYEE TURNOVER INTENTION A quantitative study investigating the effects of
the perception of elements of the work environment
on employee’s intention to leave their organization
Wageningen University and Research
Student R.J.J. (Rob) de Leeuw
Student number 950712508070
Study program Management, Economics and Consumer studies
Specialization Management studies
Thesis code BMO-80436
Supervisor Dr. H.B. Kok
First examiner Dr. H.B. Kok
Second examiner Maria Annosi
Date of submission 22 November 2020
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ABSTRACT
Objectives The objectives of this study are to provide theoretical insights into the relationship
between the perception of elements of the physical work environment and
employees’ turnover intention and give recommendations about the design of
elements of the work environment to decrease employee turnover intention.
Methods This study uses a mixed method design. Starting with a literature study, four
theoretical sub-research questions are answered. Based on this theoretical
framework the conceptual framework is developed and multiple hypotheses are
formulated. Thereafter, the three empirical sub-research questions are answered.
Structural Equation Modelling (SEM) is used to test the hypotheses. This analysis
was conducted in R studio, using a sample size of 192 employees active in the
financial sector in the Netherlands.
Results The factor analysis results in seven factors from the perceived work environment:
(1) layout, (2) air quality, (3), lighting, (4) cleanliness, (5) equipment, (6) furniture
and (7) signs. The SEM analysis shows that both job satisfaction ( = -.409), p <
.01) and affective commitment ( = -.303, p < .01) have a significant negative
relationship with turnover intention. No significant direct relationships are found
between the perception of the defined elements of the work environment and
turnover intention. The mediation analysis shows that job satisfaction mediates the
relationship between turnover intention and both the perception of the layout ( =
-.320, p < .01) and the equipment ( = -.367, p < .01). Furthermore, affective
commitment mediates the relationship between the perception of equipment and
turnover intention ( = -.252, p < .05).
Conclusions Concluding, the current study shows a relationship between both job satisfaction
and turnover intention, and affective commitment and turnover intention.
Additionally, job satisfaction is found to mediate the relationship between the
perception of the layout and turnover intention, as well as between the perception
of the equipment and turnover intention. The relationship between the perception
of the equipment and turnover intention is also mediated by affective commitment.
Nevertheless, no evidence is found for any direct relationships between the
perception of elements of the work environment and employee turnover intention.
Besides the perception of the layout and the equipment, other elements of the work
environment do not have a significant relationship with one of the two mediators
and thus no other mediating effects are found. Therefore, more research is needed
to find more underlying factors in organizations that determine job satisfaction,
affective commitment and turnover intention.
Keywords: Facility design, turnover intention, perception, physical work environment.
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PREFACE
This report is the result of my master thesis project, which is part of the Master of Science degree
in Management, Economics and Consumer studies at the Wageningen University.
Finishing this report means finalizing my student life and the start of a new phase! The past six years I was able to delve into a broad range of topics at several universities. I had the honour to spent five months in Canada during my minor in 2017 and finished my first master’s degree in Tilburg in 2019. The past year I have dived into the depths of the physical work environment and employee behaviour and attitudes. I have spent weeks learning how to code in R and understanding the ins and outs of structural equation modelling. At times, it was a mental struggle, but I kept challenging myself and kept working. However, the fact that you are currently reading this marks the end of this journey. I am looking forward starting a new phase in life and start working. It is time to bring my developed skills and knowledge into practice, and I am very excited to say that I may start as trainee at FrieslandCampina in Leeuwarden. A huge opportunity and a very challenging next step in my life!
Via this way I would like to express my gratitude to my supervisor Herman Kok. Herman, you provided me with the necessary feedback, but at the same time also gave me the freedom and time to find solutions on my own. This was a big part of my learning process during my thesis. Subsequently, I would like to thank Maria Annosi for her feedback. Especially at the start and the end you provided me with some substantive feedback on my work. Lastly, I would like to thank my parents. Especially the last couple of months were quite intense, when the three of us were working from home. But your support and the creative breaks between my writing kept me going till the end. Thank you! For the readers of this report, I hope you find it interesting and enjoy reading it. Rob de Leeuw Wageningen, November 2020
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CONTENTS
ABSTRACT ........................................................................................................................ ii
PREFACE .......................................................................................................................... iii
CONTENTS ....................................................................................................................... iv
LIST OF TABLES & FIGURES ......................................................................................... vi
LIST OF ABBREVIATIONS ............................................................................................. vii
1 INTRODUCTION ............................................................................................................. 1
1.1 PROBLEM STATEMENT ............................................................................................ 2
1.2 RESEARCH QUESTIONS .......................................................................................... 4
1.3 RESEARCH FRAMEWORK ....................................................................................... 4
1.4 RESEARCH OUTLINE ............................................................................................... 5
2 THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION........ 6
2.1 WORK ENVIRONMENT ............................................................................................. 6
2.2 EMPLOYEE TURNOVER INTENTION .................................................................... 15
2.3 WORK ENVIRONMENT AND EMPLOYEE TURNOVER INTENTION.................... 17
2.4 CONCEPTUAL FRAMEWORK AND HYPOTHESES .............................................. 21
3 METHODS ..................................................................................................................... 24
3.1 LITERATURE STUDY .............................................................................................. 24
3.2 CONSTRUCTS ......................................................................................................... 24
3.3 QUESTIONNAIRE .................................................................................................... 26
3.4 SAMPLE AND SETTING .......................................................................................... 27
3.5 DATA ANALYSIS ...................................................................................................... 28
4 RESULTS ...................................................................................................................... 30
4.1 CHARACTERISTICS OF RESPONDENTS ............................................................. 30
4.2 PRELIMINARY DATA ANALYSIS ............................................................................ 31
4.3 DESCRIPTIVE STATISTICS .................................................................................... 31
4.4 EXPLORATORY FACTOR ANALYSIS .................................................................... 37
4.5 CONFIRMATORY FACTOR ANALYSIS .................................................................. 39
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4.6 STRUCTURAL EQUATION MODEL ........................................................................ 42
4.7 HYPOTHESES TESTING ......................................................................................... 44
5 CONCLUSION & DISCUSSION ................................................................................... 49
5.1 CONCLUSION .......................................................................................................... 49
5.2 DISCUSSION ............................................................................................................ 50
5.3 LIMITATIONS ............................................................................................................ 53
5.4 IMPLICATIONS & RECOMMENDATIONS............................................................... 54
REFERENCES ................................................................................................................. 56
APPENDICES ................................................................................................................... 68
APPENDIX 1 – Research framework ...................................................................................... 68
APPENDIX 2 – Questionnaire ................................................................................................. 69
APPENDIX 3 – Original constructs and their source............................................................... 82
APPENDIX 4 – Additional output Chapter 4 ............................................................................ 84
APPENDIX 5 – R coding ......................................................................................................... 91
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LIST OF TABLES & FIGURES
Table 1 Types of workplaces and their description
Table 2 Coding of the demographic variables
Table 3 Characteristics and demographics of the respondents
Table 4 Means, standard deviations, and minimum- and maximum scores for all the items
Table 5 Means, standard deviations and correlations of variables
Table 6 KMO and Bartlett’s test
Table 7 Factor analysis: measurement model
Table 8 Total variance explained: measurement model
Table 9 Fit measures
Table 10 Validity and reliability measures
Table 11 Fit measures structural model
Table 12 Percentage of variance explained in structural model
Table 13 Results hypotheses 1-6
Table 14 Results hypothesis 7 and 8
Table 15 Job satisfaction as mediator between perception of layout and turnover intention
Table 16 Job satisfaction as mediator between perception of equipment and turnover
intention
Table 17 Affective commitment as mediator between perception of equipment and
turnover intention
Table 18 Job satisfaction as mediator: 9a, 10a, 11a1, 11a2 12a, 13a1, 13a2 and 14a
Table 19 Affective commitment as mediator: 9b, 10b, 11b1, 11b2 12b, 13b1, 13b2 and 14b
Table 20 Included constructs and their source
Table 21 Correlation table, top left
Table 22 Correlation table, bottom left
Table 23 Correlation table, bottom right
Table 24 EFA: Perception of elements of the work environment
Table 25 EFA: Job satisfaction, Affective commitment and Turnover intention
Table 26 Correlation table latent variables
Table 27 Test for discriminant validity (AVE > squared correlation of latent variables)
Table 28 Relationship perception of the work environment and affective commitment
Table 29 Relationship perception of the work environment and job satisfaction
Figure 1 Research framework
Figure 2 Three environmental dimensions and the discussed underlying elements
Figure 3 Conceptual framework
Figure 4 Hypothesized model
Figure 5 Measurement model
Figure 6 Results structural equation model
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LIST OF ABBREVIATIONS
AVE Average Variance Extracted
CFA Confirmatory Factor Analysis
CFI Comparative Fit Index
CI Confidence Interval
CR Composite Reliability
EFA Explanatory Factor Analysis
GFI Goodness of Fit Index
HBO Hoger Beroepsonderwijs
MBO Middelbaar Beroepsonderwijs
PCA Principal Component Analysis
RMSEA Root Mean Square Error of Approximation
SEM Structural Equation Model
SRMR Standardized Root Mean Square Residual
TLI Tucker-Lewis Index
WO Wetenschappelijk Onderwijs
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1 INTRODUCTION
"Clients do not come first. Employees come first.
If you take care of your employees, they will take care of the clients."
–
Richard Branson
(founder of the Virgin Group)
The fast-changing economy, increased competition, and growing pressure on organizations to
perform leads to growing importance among companies to develop employee retention strategies
(Cloutier, Felusiak & Pemberton-Jones, 2015). Retaining employees, and thus human capital, can
give organizations a significant competitive advantage (Ramlall, 2003). When an employee
voluntarily leaves, the organization unintentionally loses human capital — skills and knowledge —
which has been directly linked with the loss of competitive advantage (Hatch & Dyer, 2004; Luthans
& Youssef, 2004).
However, the impact of employee turnover on organizations even extends beyond losing human
capital and competitive advantage. Many studies link employee turnover to several direct and
indirect costs. For example, increased recruitment and training costs, lower levels of job
satisfaction, employee morale and even customers’ perception of service quality of the organization
(Cheng & Brown, 1998; Clark-Rayner & Hartcourt, 2000; Cho, Johanson, & Guchait, 2009; Memon,
Salleh, Baharom, & Harun, 2014). Additionally, Dess and Shaw (2001) find that employee turnover
puts more pressure on workforce planning and results in a drain on management time.
Employees switching jobs is often due to dissatisfaction with wages (Borghans & Golsteyn, 2011)
or they want to increase their human capital by gathering more knowledge at another company,
because the more knowledge they possess, the more they will get paid (Gius, 2003). Many past
studies on turnover intention, therefore, focused on the effects of compensations and rewards,
training and development (Samuel & Chipunza, 2009; Das & Baruah, 2013), autonomy and
empowerment (Mehta, Kurbetti & Dhankar, 2014). On the other hand, according to Vischer (2008),
the sense of belonging, which is measured through the appropriation of space (Davis & Altman,
1976), needs further study because of its essential link with the turnover intention. A sense of
belonging (appropriation) is identified as an outcome measure of environmental studies
(Sundstrom & Sundstrom, 1986). If employees have the feeling that they do not belong to an
organization, their intention to leave the organization (i.e., turnover intention) will increase. The
turnover intention, being ‘the conscious and deliberate wilfulness to leave the organization’ (Tett &
Meyer, 1993, p. 262), proves to be one of the best predictors of actual turnover (Griffeth, Hom &
Gaertner, 2000; Van Dick et al., 2004; Trimble, 2006). This link can be explained by the Theory of
Reasoned Action as described by Ajzen and Madden (1986). According to this theory, behavioural
intention determines an individual’s behaviour. The more an individual shows a particular intention
CHAPTER 1 – INTRODUCTION
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to a specific behaviour, the more likely they are to act on this behaviour. Interestingly, multiple
studies show that employee behaviour is affected by the work environment (Peters and O’Connor,
1980; Blumberg and Pringle, 1982; Peters, O’Connor, & Eulberg, 1985; Olson and Borman, 1989;
Carnevale, 1992; Bitner, 1992; Niles and Harris-Bowlsbey, 2002; Kyriakidou and Ozbilgin, 2004).
For example, in the study of Carnevale (1992) is explained how the work environment is perceived
and result in a sense of the place. This sense of a place, the perception of the environment, is
related to individual attitudes and behaviours. These include employee satisfaction and
performance (Carnevale, 1992). Another example is the study of Bitner (1992). In her study, she
explains how the perception of the environment functions as a stimulus that results in internal
responses. These internal responses of the employee can be cognitive, emotional and
physiological and in turn result in an external response in the form of behaviour. This can be
approach or avoidance behaviour towards the environment (Bitner, 1992; Mehrabian & Russell,
1974). The study of Bitner (1992) is based on previous findings from the study of Mehrabian and
Russell (1974). In their study, they focus on the emotional internal response as a result of the
stimulus; the environment. Similarly, they conclude that this internal response can result in
approach or avoidance behaviour. This behaviour represents the desire among employees (not) to
stay longer in a particular environment (Bitner, 1992; Mehrabian and Russell, 1974). Additionally,
employees can feel (dis)satisfied with the environment and feel (not) affiliated to the environment
in which they work (Bitner, 1992). However, these studies do not focus on the long run. It is not
said that this avoidance behaviour, as a result of an internal response to an environment, results
in turnover intention and actual turnover. However, the study of Carnevale (1992) suggest that
satisfaction with the physical work environment is associated with turnover intention.
Overall, a better understanding of how the work environment affects employees can help managers
to make well-informed decisions when (re-) designing the work environment (Kok, Mobach, &
Omta, 2015). Additionally, having a better understanding of how elements of the work environment
affect turnover intention allows organizations to improve elements in their work environment and
reduce the direct and indirect costs associated with employee turnover.
1.1 PROBLEM STATEMENT
The consequences of employee turnover can be far-reaching. Not only is employee turnover
related to many direct costs, but also many indirect costs. An example would be the loss of human
capital, to which the loss of competitive advantage is linked (Hatch & Dyer, 2004; Luthans &
Youssef, 2004). But also, the costs related to recruitment, selection and training of new employees
are tremendous (Chang, Wang & Huang, 2013). Yet, the number of empirical studies that examine
the causes and antecedents of turnover intention are limited (Mor Barak, Nissly & Levin, 2001).
Understanding the causes and antecedents of turnover intention is relevant because it will help
employers to reduce turnover rates. This knowledge helps the employers to focus on effective
factors that they can control to reduce turnover intentions and actual turnover as a consequence.
These factors can be for example the nature of the work process, but can also be the worker
characteristics, or the work environment (Mor Barak, Nissly & Levin, 2001; Blankertz & Robinson,
1997). In their review and meta-analysis, Mor Barak, Nissly and Levin (2001) distinguish three
major categories of turnover antecedents that emerge from empirical studies. These three
categories are demographic factors, professional perceptions, and organizational conditions. The
demographic factors can be both work-related (e.g., tenure) and personal (e.g., age or gender).
Professional perceptions include for example job satisfaction and organizational affective
commitment (Tett & Meyer, 1993). Lastly, the organizational conditions are for example the level
of social support, organizational hierarchy, but also physical comfort. Physical comfort is the
perceived comfort of the ‘built’ elements of the work environment (Mor Barak, Nissly & Levin, 2001).
CHAPTER 1 – INTRODUCTION
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A very similar categorization was given by Steil, Floriani and Bello (2019) in their systematic review
on antecedents of turnover intention. Similarly, as Mor Barak, Nissly and Levin (2001), they
distinguish three categories of antecedents. Namely, personal, occupational and environmental
antecedents.
This last group, the work environment, including physical comfort, has been studied to a certain
extent during the past decades. Most of these studies focused on how the perception of the work
environment can affect the behaviour of its occupants (e.g., Bitner, 1992; Mehrabian and Russell,
1974; Carnevale, 1992; Carlopio, 1996). For example, in the study of Bitner (1992) explains how
the perception of an environment can result in avoidance behaviour among employees. However,
the environment Bitner studied is the service environment (e.g., a store) and not an office
environment, and avoidance behaviour towards the work environment and not necessarily towards
the job itself. Additionally, various studies concentrated on the physical work environment and their
relationship with various attitudes as the outcome variable. For example, employee job satisfaction
(Moos, 1994; Carlopio, 1996), employee productivity (Clements-Croome & Baizhan, 2000; Sarode
& Shirsath, 2014) and employee commitment (McGuire & McLaren, 2009; Carlopio, 1996).
However, these studies do not test for the direct effect of the work environment on turnover
intention. The few studies that did examine the direct relationship between work environment and
turnover intention did not examine the effects of individual elements of the physical environment,
but instead focused on the work environment as a whole and even included elements of the non-
physical environment in their work environment construct (e.g., Santoni & Harahap, 2018;
Kurniawaty, Ramly & Ramlawati, 2019). Additionally, Carlopio (1996) postulates that elements of
the physical work environment might have certain effects on employee behaviour and attitudes,
including job satisfaction and employee turnover intention. Furthermore, Ashkanasy, Ayoko and
Jehn (2014) proposed a new framework based on their literature about the physical work
environment and its effect on employee behaviour and attitudes. This framework proposes a link
between the physical work environment and turnover intention. Whereas, they have reasons to
suggest that elements of the physical work environment result in affective reactions that then lead
to judgment-driven behaviours. As an example of judgment-driven behaviour, they give actual
turnover. They suggest that future research should focus on these effects of elements of the
physical work environment on employee behaviour and attitudes, including turnover intention.
Based on these findings, it would be interesting to study these relationships, to see whether the
perception of elements of the physical work environment affects an employees’ intention to leave
their organization, or in other words their turnover intention. In this study, it is important to take into
account previous antecedents of turnover intention, including the demographic factors and
professional perceptions such as job satisfaction and affective commitment, as described in the
meta-review of Mor Barak, Nissly and Levin (2001).
The primary purpose of this study is to provide clarification on this topic by examining the
relationship between the perception of elements of the work environment and three employee
outcome variables: organizational affective commitment, job satisfaction, and turnover intention,
while controlling for several demographic variables. Exploring what perceptible elements of the
physical work environment affect employee turnover intention will not only fill this knowledge gap
but will also help organizations to circumvent the negative effects that are related to employee
turnover. Thus, the managerial relevance of examining the effects of the perception of elements of
the work environment on turnover intention, is that it will help managers to introduce strategies
concerning the work environment that reduce turnover intention. An improved work environment
will help to retain valuable employees and result in less direct and indirect costs related to employee
turnover.
CHAPTER 1 – INTRODUCTION
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The objectives of this study are twofold:
1. Provide theoretical insights into the relationship between the perception of elements of
the work environment and employees’ turnover intention;
2. Give recommendations about the design of elements of the work environment to
decrease employee turnover intention.
1.2 RESEARCH QUESTIONS
The central research question is derived from the research objective mentioned before. The central research question of the study is:
To what extent is the perception of elements of the work environment related to employee
turnover intention?
Several sub-research questions are formulated to answer this central research question. A
distinction is made between theoretical- and empirical research questions.
Theoretical research questions:
1. What are the elements of the work environment that can be perceived, and how can these
elements be operationalized?
2. What defines turnover intention and how can it be measured?
3. Which elements of the work environment can affect employee turnover intention?
4. What are, apart from elements of the work environment, additional aspects that may spark
employee turnover intention?
Empirical research questions:
5. How do employees evaluate different elements of their work environment?
6. How do employees evaluate their turnover intention?
7. What are the effects of the perception of elements of the work environment on employee
turnover intention?
1.3 RESEARCH FRAMEWORK
Figure 1 represents the research framework giving a clear overview of all steps taken in this study
to achieve the research objectives.
The first part of this research consists of the theoretical phase, during which the relevant literature
is discussed. This phase focuses on answering the theoretical research questions as formulated in
paragraph 1.2. The conceptual framework presented at the end of this phase provides insight into
how different types of objective data can be collected. It gives an overview of the included
constructs and how these constructs can be related. Based on this, several hypotheses are
developed and then tested in the second part of this study.
The empirical phase consists of the data collection using a questionnaire. This data is used to
answer empirical research questions. Finally, the analytical phase presents the findings and
provides conclusions and recommendations based on theoretical and empirical research. Several
findings, limitations and recommendations are discussed at the end of this study.
CHAPTER 1 – INTRODUCTION
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Figure 1
Research framework
1.4 RESEARCH OUTLINE
The remainder of the study consists of four parts. Chapter two discusses the work environment and
employee turnover intention. It ends with the hypotheses and conceptual framework. The third
chapter describes the research methodology and its research design. It furthermore explains the
sample and setting, measurement, and analysis. The fourth chapter presents the results of the
study, after which chapter five contains the conclusion and discussion.
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2 THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
By reducing employee turnover, organizations can save a lot of direct and indirect costs (Memon
et al., 2014). Improving the work environment may be an effective way to reduce employee turnover
intention since the work environment affects employee behaviour (Bitner, 1992). Therefore, this
literature study investigates how the perception of elements of the work environment affects
behaviour and how this may affect turnover intentions. The outcomes of this study indicate how the
perception of elements of the work environment and turnover intention are related and results in
the conceptual framework.
The first paragraph elaborates on the work environment and discusses the relevant literature. The
second paragraph discusses the theory on employee turnover intention, and the third paragraph
discusses the relation between both concepts. These three paragraphs answer the first four sub-
research questions. Finally, in the last paragraph, the conceptual framework is presented and
explained.
2.1 WORK ENVIRONMENT
The past century there has been a shift in the economy from manufacturing sectors working from
factories, towards more service and knowledge-based industries based in office environments (Van
Meel, 2000; Haynes, 2008). Whereas a century ago most employees worked in factories,
nowadays most employees spend their time working in an office environment. Formerly, people
saw the work environment as a passive setting for work, but nowadays people acknowledge that
the office environment can be a tool- and active support for employees to get their job done
(Newsham, 1997; Vischer, 2008).
Until recently, most office environments were designed according to a 19th century model of work.
Within this design, the focus was on performing rather than thinking, and the work environment was
often very uniform, and the occupation was standardized (Vischer, 2008). However, the
developments in information technology during the last decades allowed employees to work
anytime and anywhere (Van Meel, 2000; Vischer, 2008). This development resulted in new ways
of working, which enabled employees to choose where and when they want to work, depending on
the task they have at hand (Dooley, 2017).
Nowadays, the office environment is not conceptualized as a passive setting, but instead as a tool
to help employees getting their work done and offering employees active support in their work
(Newsham, 1997). This shift resulted in a growing interest in how employees behave as a function
of their work environment, which resulted in multiple studies recognizing employee behaviour is
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
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impacted by elements of the work environment (Peters and O’Connor, 1980; Peters et al., 1985;
Olson and Borman, 1989; Kyriakidou and Ozbilgin, 2004).
2.1.1 Types of work environment
In the past, multiple studies tried to categorize the workplace based on characteristics of the
environment. This categorization is often based on the functional and architectural characteristics
of the workplace. The layout is a common characteristic on which workplaces are distinguished.
One of the older categorizations is that of Ahlin and Westlander (1991) who identified three types
of workplaces: (1) cell-office; (2) combi-office; and (3) open-plan office. Van Meel (2000) uses a
very similar categorization. He distinguished four types of workplaces in his study. Similar to Ahlin
and Westlander, he identified the cell-, combi-, and open-plan office. However, he also added the
category ‘landscape office’, which are large open areas with an arbitrary layout of the furniture in
the large open area. This categorization differs from the open-plan office, which he described as
an open space in which many people can work in a very structured layout of the desks.
In their pervasive study, Danielsson and Bodin (2008) divided the workplace over seven categories.
Table 1 contains a description of these categories.
Table 1
Types of workplaces and their description
Type of workplace Description
Cell-office Single person office
Shared-room office 2-3 persons sharing an office
Open-plan offices
Small open-plan office 4-9 persons sharing an office
Medium open-plan office 10-24 persons sharing an office
Large open-plan office 24+ persons sharing an office
Flex-office No individual workstation. Often open plan, but not a defining feature.
Combi-office No strict spatial definition. Sharing facilities.
This categorization is based on the degree of openness of the workplace, the number of persons
in the room, and whether employees have their workspace (Danielsson & Bodin, 2008). However,
more elements distinguish work environments from each other. Elements of the physical
environment that have proven to affect its occupants. For example, ambient conditions or the signs
in the work environment (Bitner, 1992; Elsbach & Pratt, 2007; Al Horr et al., 2016).
Before these elements are discussed in more detail, it is necessary to have a clear understanding
of what is understood as the physical work environment.
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
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2.1.2 Physical work environment
Important to note is the difference made between the physical environment and other work
environments such as the social- or the purely natural environment (Elsbach & Pratt, 2007). Where
the social environment is described as the social structures and norms in the workplace, and the
natural environment as the surroundings entirely constructed by nature, the physical environment
consists of all the material objects and stimuli that employees encounter and interact with
(Carnevale, 1992; Sundstrom, Bell, Busby, & Asmus, 1996). These objects and stimuli can be
arranged in many ways, resulting in the different types of workplaces as described above (e.g.,
cell-office and open-space office plans). Examples of these objects and stimuli are the equipment,
furnishing, layout and ambient conditions such as air quality or noise (Elsbach & Pratt, 2007).
Organizations often combine more than one type of workplace and the workplaces, and the
elements of these, are subject to change (Vischer, 2007). These changes in physical environment
range from small-scale (e.g., adding new furniture) to large-scale (e.g., moving to a new building).
While each design element has its positive and negative implications, managers often need to
make trade-offs, in the design of the physical work environment, between the different objects and
their arrangements, to come to the best physical work environment for each situation. This trade-
off also depends on the financial resources available and a good understanding of the needs and
wishes of the employees concerning the design elements of the workplace (Elsbach & Pratt, 2007).
2.1.3 Design elements of workplace
Elsbach and Pratt (2007, p.184) distinguish four design elements of the physical environment.
These four elements are: “(1) enclosures and barriers in workspaces; (2) adjustable work
arrangements, equipment, and furnishings; (3) personalisation of workspaces, including the display
of well-known symbols; and (4) nature-like ambient surroundings, including natural light, presence
of plants, wood interiors, views of nature, and natural aromas.” Whereas Elsbach and Pratt
distinguish four design elements of the physical environment, Al Horr et al. (2016) identify eight
physical environmental factors that affect occupants in their extensive literature review that includes
over 300 papers. The eight factors that they identify are (1) Indoor air quality; (2) Thermal comfort;
(3) Lighting and daylighting; (4) Noise and acoustics; (5) Office layout; (6) Biophilia and views; (7)
Look and feel; and (8) Location and amenities. In their review, Al Horr et al. (2016) emphasize that
these eight physical factors do interact with each other and have some crossover. One of the
examples they give is the interaction between daylighting and the thermal state of the office.
Referring to Lyons, Arasteh and Huizenga (2000), they explain how windows absorb and transfer
a significant amount of solar radiation into the indoor environment. The main difference between
the study of Elsbach and Pratt (2007) and Al Horr et al. (2016) is that Al Horr and colleagues split
the 4th design element of Elsbach and Pratt, the nature-like ambient surroundings, in multiple
smaller design elements. In their study, Al Horr and colleagues identify the elements ‘indoor air
quality’, ‘thermal comfort’, ‘lighting and daylighting’, ‘noise and acoustics’, and ‘biophilia and views’,
which are compromised in the element ‘nature-like ambient surroundings’ by Elsbach and Pratt.
As explained by Al Horr et al. (2016), these elements of the physical environment interact with each
other. Bitner (1992) explains something similar in her study. She describes how people respond to
their environments holistically. Based on the total configuration of all discrete stimuli, people
respond to the environment. These stimuli come from the different dimensions of the environment
that they perceive. Bitner (1992) identifies three different environmental dimensions, namely: (1)
Ambient conditions; (2) Spatial layout and functionality; and (3) Signs, symbols and artefacts.
These three ways of categorizing the physical environment by Elsbach and Pratt, Al Horr et al., and
Bitner, have many similarities. Each of the eight categories defined by Al Horr and colleagues can
be placed under one of the dimensions as defined by Bitner. Furthermore, the four categories
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
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Elsbach and Pratt distinguish, are very similar to those of Bitner. The main difference between both
categorizations is that Elsbach and Pratt split the spatial layout and functionality dimensions in
“enclosures and barriers in workplaces” and “adjustable work arrangements, equipment, and
furnishing”.
As these three studies made clear, there is a complex mix of physical environmental elements that
can affect its occupants’ behaviour. However, all three studies show very similar categorizations,
that are all covered within the three dimensions of Bitner (1992): ambient conditions, spatial layout
and functionality, and signs, symbols and artefacts. This thesis continuous using Bitner’s (1992)
definition of the environmental dimensions of the physical work environment. The next paragraph
explains these three dimensions in more detail and discusses the elements within these dimensions
that can be perceived by the employees. These paragraphs explain how the work environment can
function a stimulus that triggers an individual's internal response, which subsequentially results in
a behavioural response.
2.1.4 Servicescape model of Bitner (1992)
Bitner (1992) defines three environmental dimensions in her servicescape model. These
dimensions, and the elements they contain, together result in the perceived environment and form
the stimulus. The three environmental dimensions are (1) ambient conditions, (2) spatial layout and
functionality, and (3) signs, symbols and artefacts. The second and third dimensions are commonly
referred to as ‘interior layout and design’ (Brauer, 1992), or as Bitner (1992) labels them ‘the built
environment’. This built environment can be controlled to a large extent by management, in contrast
to the ambient conditions, which are more difficult to control (Wakefield & Blodgett, 1996).
The first dimension, the ambient conditions, are those factors of the environment that affect the five
senses and include lighting, temperature, air quality, scent, colour and noise (Bitner, 1992).
According to Bitner, multiple studies showed that these conditions could either enhance or decline
the performance of occupants within this physical environment. Spatial layout of the physical
environment is described by Bitner (1992, p. 66) as “the ways in which machinery, equipment, and
furnishings are arranged, the size and shape of those items, and the spatial relationships among
them”. How well these items can facilitate performance and goal accomplishment is referred to by
the term ‘functionality’. Finally, the last environmental dimension is signs, symbols and artefacts,
which is described by Bitner (1992) as items in the physical office environment that are particularly
important for forming the first impression and give occupants implicit cues about the norms and
rules for behaviour in the place. These items function as signals that communicate about the place
to its users (Bitner, 1992). According to the literature review of Mari and Poggesi (2013), that
includes 92 classical studies on the servicescape, most of the articles about the servicescape focus
on the first two dimensions of Bitner (1992): the ambient conditions and spatial layout and
functionality. The signs, symbols and artefacts dimensions often get less attention in the literature.
The next section will discuss the elements included in these dimensions in more detail, to get a
better idea of what can be perceived in the environment.
2.1.5 Ambient conditions
As explained in the previous paragraph, ambient conditions are elements of the environment that
affect the five senses and include lighting, temperature, air quality, scent, colour, sound and
biophilia (Bitner, 1992). The next paragraphs will give a short description of these elements and
their effects on the occupants of the work environment.
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Lighting
A distinction can be made between two types of lighting, namely daylight and artificial light. Both
have an effect on employees’ satisfaction and productivity in an office environment (Alrubaih et al.,
2013; Sivaji, Shopian, Nor, Chuan, & Bahri, 2013; Al Horr et al., 2016). Humans need light in their
life, as it is a regulator of their performance and their physiology (Aries, 2005; Al Horr et al., 2016).
Office employees are dependent on the available daylight or artificial lighting, while they spend
most of their time indoors. Previous studies found that organizations that focus on the amount of
daylight in their offices and optimize these amounts will have higher employee productivity and less
absenteeism (Browning & Romm, 1995; Fay, Rea & Figueiro, 2002). Additionally, the amount of
daylight is related to the thermal state of the office. Windows absorb solar radiation into the office,
which affects the thermal state of the office (Al Horr et al., 2016). This change in the thermal state
of the office affects the employees’ perception of indoor air quality as well. As De Dear and Brager
(2002) found, the decrease in temperature in the office results in a better perceived indoor air
quality.
Temperature
Multiple studies found how temperature affects work performance (e.g., Seppänen & Fisk, 2006;
Wargocki et al., 2008). These studies showed how the performance of employees decreases when
the temperature is above 23-24 °C. The ambient temperature of the work environment has a
significant role in defining the thermal comfort of the employees in this environment (Al Horr et al.,
2016). However, it is essential to note that the optimum temperature for optimal productivity differs
per tasks and function (Huizenga, Abbaszadeh, Zagreus, & Arens, 2006; Tanabe, Nishihara, &
Haneda, 2007).
The temperature can also affect employees in a purely physiological way (Bitner, 1992). For
example, when it is too cold, people start to shiver, or when it is too hot, they start to perspire.
These physical responses may cause dissatisfaction with a particular environment (Bitner, 1992).
These effects of temperature and the resulting thermal comfort on occupant’s satisfaction and
productivity is supported by multiple studies (e.g., Tanabe et al., 2007, Djongyang, Tchinda &
Njomo, 2010, Lan, Wargocki & Lian, 2011)
Indoor air quality
Indoor air quality has an impact on both the productivity of the employees and their satisfaction. An
improved air quality will increase the productivity and performance of the employees (Wyon, 2004;
Al Horr et al., 2016). Additionally, an improved indoor air quality results in improved health of the
employees and increased job satisfaction (Wargocki, Wyon, Baik, Clausen, & Fanger, 1999;
Lagercrantz et al., 2000; Wargocki et al., 2008). Furthermore, Milton, Glencross and Walters (2000)
found in their study that the indoor air quality has a significant effect on the short-term sick leave.
Worse indoor air quality will result in more short-term sick leaves.
Scent / Odour
The indoor air quality can also affect the scent within the building. Too little fresh air can make the
room smell stuffy. The scent within an environment can affect its occupant’s health and mood
(Diego et al., 1998; Nicell, 2009), as well as their performance (Basevitch et al., 2011). For example,
Schweitzer, Gilpin and Frampton (2004) found that smelly scents can stimulate stress, whereas a
pleasant scent can reduce blood pressure. Thus, the scent within an environment can affect
occupants both physiologically as psychologically.
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Noise and Acoustics
Noise can be defined as a sound that is perceived unpleasant by the users and is a significant
source of dissatisfaction with the office environment (Bitner, 1992; Sundstrom, Town, Rice, Osborn,
& Brill, 1994; Al Horr et al., 2016). Increased noise levels result in reduced performance according
to the findings of Witterseh, Wyon and Clausen (2004). Noise or bad acoustics in an office
environment also affects the productivity and job satisfaction of employees (Sundstrom et al., 1994;
Banbury and Berry, 2005). For employees to work efficiently, a certain degree of noise control is
required. The design of the office environment should take into account this noise control, while
bad acoustics results in inefficient employees and employees that are dissatisfied with their work
environment (Balazova, Clausen, Rindel, Poulsen, & Wyon, 2008; Frontczak et al., 2012).
Colours
The colours used in an environment affects the emotional state of the people in it. Different colours
result in different psychological responses (Mahnke, 1996). For example, cold colours (blue, green
and purple) have a calming effect, while warm colours (yellow, orange and red) have an arousing
effect (Ou, Luo, Woodcock, & Wright, 2004; Küller, Ballal, Laike, Mikellides, & Tonello, 2006). Thus,
the colours used in an environment have a psychological effect on the people in this environment.
Additionally, the colour schemes used in an office environment can affect employee performance
and productivity (Öztürk, Yilmazer, & Ural, 2012). The right colour will bring the employee in the
right mood which will encourage productivity and will result in better-performing employees
(Kamaruzzaman & Zawawi 2010; Kamarulzaman, Saleh, Hashim, Hashim, & Abdul-Ghani, 2011).
Biophilia
Biophilia is the tendency of humans to seek connection with nature and other forms of life (Wilson,
1984). Humans are highly responsive to forms of nature and its processes and patterns (Nabhan,
St Antoine, Kellert, & Wilson, 1993). Multiple studies found that bringing greenery or natural
elements inside an office has a positive effect on the productivity and satisfaction of employees
(Heerwagen & Orians, 1986; Grinde & Patil, 2009; Heerwagen, 2009). Additionally, indoor greenery
is found to be negatively related with the stress of the occupants (Al Horr et al., 2016) and it
improves the indoor air quality (Lohr, Pearson-Mims, & Goodwin, 1996). Even the passive viewing
of natural elements through windows has a positive effect on the productivity of occupants of the
room (Al Horr, 2016) and results in reduced stress levels (Chang & Chen, 2005). Furthermore,
Elzeyadi (2011) found that the presence of biophilia in offices reduces absenteeism rates of
employees. Overall, the inclusion of biophilia in office environments has a positive effect.
2.1.6 Spatial layout and functionality
The spatial layout and functionality dimensions exist of fixed and semi-fixed elements, while the
dimension ‘ambient conditions’ exists of mostly non-fixed elements (Rapoport, 1982). The fixed
and semi-fixed elements of the work environment that are included in this study are spatial layout
and functionality, equipment and furniture. In addition to the spatial layout and functionality, privacy
will be discussed. Because privacy is seen as a direct consequence of the spatial layout.
Layout & Functionality
The layout of a building refers to how all the objects in the environment are placed. These objects
include the furnishing and equipment. Important factors are the size and shape of these objects,
but also the location in the environment is important (Bitner, 1992). The functionality of these
objects is determined by how well these objects facilitate the performance and achievement of
goals (Bitner, 1992). When a layout is sufficient and functioning, it will provide convenience and will
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make the use of the environment more pleasurable (Wakefield & Blodgett, 1996; Siu, Wan & Dong,
2012). On the other hand, if the layout does not match the work process, it can negatively affect
the occupant’s level of well-being. For example, when occupants have to fulfil a complex task, they
will be dissatisfied with a layout that causes distraction from other occupants (Al Horr et al., 2016).
Furthermore, Preiser, White and Rabinowitz (1988) found that the spatial layout affects occupant’s
behaviour. A good layout will allow occupants to access all spaces conveniently and will result in
satisfaction with the environment (Mustafa, 2017).
Privacy
Closely related to the layout of an office environment is the privacy that comes with a particular
layout. When the office layout causes too many people to be in the same space, a sense of
crowding can arise (Dilani, 2008). In her research, Aubert-Gamet (1997) showed that layout is
strongly related to the sense of crowding and thus with the perceived privacy.
Marquardt, Veitch and Charles (2002, p. 8) define privacy as “the degree to which one’s social
interactions are regulated”. Privacy is subdivided into several types, including visual privacy, sound
privacy (O’Neill & Carayon, 1993; Kim & de Dear, 2012) and privacy from distractions (O’Neill,
1994; Marquardt, Veitch and Charles, 2002).
As described in paragraph 2.1, several office types can be distinguished (Danielsson & Bodin,
2009). They describe in their study how the level of privacy decreases as the openness of the office
increases. The more open the office, the more people are in the same space, the easier it becomes
to get disrupted visually or auditorily. Most privacy is perceived in the cell-offices, while the levels
of distraction and interruptions are the lowest in these types of offices. The level of satisfaction with
the amount of privacy depends on the task at hand (Al Horr et al., 2016).
Enclosures & Barriers
Closely related to the spatial layout and the privacy of the work environment, are the enclosures
and barriers in the physical work environment. Examples of closures and barriers are hallways,
doors, walls, partitions, cubicles or other things that “buffer workers from each other and from
ambient disturbances” (Elsbach & Pratt, 2007, p. 4). The differences between the office types as
described in paragraph 2.1 depend to a large extent on the closures and barriers in the physical
work environment. For example, the open plan-office has only a few closures and barriers, whereas
the cell-office has many (Maher & von Hippel, 2005). When the physical work environment has
fewer closures and barriers, the privacy ratings will be lower (Oldham & Rotchford, 1983) and the
overall satisfaction with the physical environment will be lower (Brill, 1984). Oldham, Kulik and
Stepina (1991) found that a high degree of enclosures and barriers increases the satisfaction and
performance on simple tasks. However, it reduces the satisfaction and performance of those
employees working on complex tasks. On the other hand, Sundstrom, Burt and Kamp (1980) found
that employees prefer the privacy that comes with more enclosures when working on complex and
routine tasks.
Equipment & Furniture
As Bitner (1992) describes, the equipment must facilitate performance and the accomplishment of
goals. Besides its need for task performance, equipment and furniture are one of the main points
of interaction between employees and their physical environment (Carlopio, 1996). Furniture and
equipment are closely linked to the layout of the building. The layout of equipment and furniture in
the work environment can have a major impact on the occupant’s ability to achieve their goals and
complete their tasks (Bitner, 1992).
Ellickson and Logsdon (2002) found in their study a significant relationship between the perception
of equipment and overall job satisfaction. Additionally, Carlopio and Gardner (1992) found that
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13
furniture that can be adapted to individual physical characteristics, often called ergonomic furniture,
is perceived as more pleasurable and result in improved satisfaction with the work environment.
O’Neill’s (1994) research shows very similar results. He describes in his study how the adjustability
of all kinds of furniture, to meet the physical needs of its users, results in increased environmental
satisfaction. For example, the perceived comfort of a chair is increased if it is adjustable (O’Neill,
1994). The study of Makhbul (2013) shows that poor ergonomic furniture has its consequences. In
his study, he found that workplaces with poor ergonomic furniture lowers the productivity of its
occupants and also has a significant effect on their well-being.
In general, the quality of furniture and equipment in offices have a positive effect on the perceived
comfort of, and general satisfaction with, the physical office environment (Marquardt, Veitch &
Charles, 2002).
2.1.7 Signs, Symbols and Artefacts
The third environmental dimension that is described by Bitner (1992) are the signs, symbols and
artefacts in the physical office environment. As she describes in her paper, these items are
essential for forming the first impression and giving occupants implicit cues about the norms and
rules of the environment. These items consist mainly of semi-fixed elements.
According to Bitner (1992), signs and symbols encompass explicit and implicit elements. These
elements are used to communicate information to the employees and directing their behaviour.
Additionally, these elements can be used to communicate the organizational culture to the
employees (Siu, Wan & Don, 2012). Signs are the most direct way to communicate the meaning of
a place and conveying the norms and expected behaviour to employees (Bitner, 1992).
Another important element for communicating the organizational culture are artefacts. Artefacts are
those items in an environment that communicate about the place and its culture to its users (Bitner,
1992). Examples of artefacts are the presence of artworks, personal objects of the employees, the
quality of the materials used for construction, ceremonies, dress codes, and the language used.
Bang (1995) identifies four different categories of artefacts, namely: (1) behavioural expressions;
(2) verbal expressions; (3) material expressions; and (4) structural expressions. Bjerke, Ind and De
Paoli (2007) mention in their paper that there are potential relations between artefacts that express
the organizational culture and the motivation and satisfaction of employees. Additionally, Gagliardi,
Clegg, Hardy and Nord (1999) claim that artefacts impact the behaviour of employees.
2.1.8 Operationalization of the perception of the work environment
Based on the framework of Bitner (1992), the last paragraphs described three dimensions that can
be distinguished in the work environment and the elements within each dimension. An overview of
these three dimensions and all the underlying elements that have been discussed in this chapter
can be found in Figure 2. As Bitner (1992) explains in her study, it is the subjective and holistic
perception of these elements of the work environment that result in an internal response within the
employee. This holistic perception is based on a fusion of all aspects of the environment. However,
each perception may have different outcomes on the employees (Bitner, 1992). Perception is “the
process of experiencing organized and interpreted information extracted from sensations” (Jacobs,
2006, p. 122). This organized information from the environment enters the human body through
the five senses and helps us to understand and interact with the environment. More specifically,
environmental perception is often defined as “awareness of, or feelings about, the environment,
and the act of apprehending the environment by the senses” (Zube, 1984, p. 7). Information about
how employees perceive their work environment can inform managers about the employees’
concerns about the environment and gives information about probable responses to environmental
conditions (Zube, 1984).
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There are several ways of measuring perception. A good way to measure the perception of the
environment is by using self-reported measures such as a Likert Scale (Brown, 2011). Using a
Likert scale, one is able to measures the different perceived environmental qualities and results of
individual respondents
Figure 2
Three environmental dimensions (Bitner, 1992) and the discussed underlying elements
This study focuses on the perceptible elements of the work environment. Some elements, such as
gasses and infrasound are imperceptible. These imperceptible elements of the environment are
not included in this study. The perceptible elements of an environment can be divided into three
dimensions (Bitner, 1992). Several studies used these three dimensions as a starting point for
building their construct measuring the work environment (e.g., Wakefield & Blodgett, 1996). This
construct has shown to be reliable in several studies (e.g., Han & Ryu, 2009; Siu, Wan & Dong,
2012). This construct exists of six scales which contains a total of 30 elements of the work
environment. These items are measured on a five-point Likert scale, ranging from strongly disagree
(1) to, strongly agree (5). The six scales are layout, space, ambient conditions, the functionality of
equipment and furniture, cleanliness, and signs. The scales layout, space, and functionality refer
to the spatial layout and functionality dimensions. The ambient conditions scale covers the
dimension that is named likewise, and the cleanliness is included in this dimension as well. Finally,
the signs scale is related to the signs, symbols and artefacts dimension. Together these six scales
give a comprehensive view of how the ‘built physical work environment’ is perceived. The model
does not contain the whole perceptible environment, whereas this would result in a construct that
was too large. A selection was made to keep the length of the survey short to minimize the response
bias caused by boredom and monotony (Schmitt, Ford & Stults, 1986), but still covers elements
within all three dimensions.
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2.1.9 Conclusion – Paragraph 2.1
As described in the previous paragraphs, the primary purpose of a work environment is to support
occupants to get their work done, perform and be productive, to achieve the organizational goals
(Newsham, 1997; Vischer, 2008). Multiple studies have shown that the work environment can be
an efficient tool to steer employee behaviour (Peters and O’Connor, 1980; Peters et al., 1985;
Olson and Borman, 1989; Kyriakidou and Ozbilgin, 2004). Both Bitner (1992) and Mehrabian and
Russel (1974) explain in their studies how the behaviour of occupants can be influenced by the
work environment. They explain how the perception of elements of the environment can influence
several internal responses that affect the occupant’s behaviour and attitude.
Multiple studies divide the work environment into different categories based on the number of
employees in a room and whether employees have their workspace or not. A conventional
categorization is that of Danielsson and Bodin (2008). In their study, they divide the work
environment into seven different types of offices. However, besides this categorization based on
the number of persons in a room, more elements distinguish work environments. Elements of the
environment that have proven to affect its occupants (Bitner, 1992; Elsbach & Pratt, 2007; Al Horr
et al., 2016). As Rapoport (1982) explains, these elements can be fixed, semi-fixed or non-fixed.
Bitner (1992) divides these elements into three environmental dimensions, namely: (1) ambient
conditions, (2) spatial layout and functionality, and (3) signs, symbols and artefacts. Examples of
ambient conditions are the lighting, temperature, air quality, scent, colours and noise in the physical
office environment. When considering the spatial layout and functionality, which consists of fixed-
and semi-fixed elements, interesting factors are the layout itself and the privacy that comes with it.
The layout and associated privacy also depend on the number of walls and barriers. Additionally,
biophilia is an interesting element in the work environment that has its effects on employees.
Finally, the signs, symbols and artefacts play an important role in communicating the organizational
values to employees and steering their behaviour (Gagliardi, Clegg, Hardy & Nord, 1999; Bjerke,
Ind & De Paoli, 2007; Siu, Wan & Don, 2012).
These different elements of the environment can be perceived via the five senses. Perception is
described as “the process of experiencing organized and interpreted information extracted from
sensations” (Jacobs, 2006, p. 122). This organized information helps us to understand and interact
with the environment. Our environmental perceptions are our feelings about the environment and
our understanding of the environment via our senses (Zube, 1984). A good way of measuring
perception is by the use of self-reported scales, for example Likert scales (Brown, 2011). Using a
Likert scale, the employees in the environment can rate the different elements of their environment.
There are a lot of elements of the work environment that can be perceived and that have shown to
affect its occupant. These elements can be placed under one of the dimensions as described by
Bitner (1992). An existing construct measuring the perception of elements of an environment, and
that has shown to be reliable, is the construct of Wakefield and Blodgett (1996). This construct
covers the three dimensions (Bitner, 1992) of the environment that can be perceived, but at the
same time is not too long, to prevent bias caused by boredom and monotony (Schmitt, Ford &
Stults, 1986).
2.2 EMPLOYEE TURNOVER INTENTION
Intentions are often the best predictors for actual behaviour (Igbaria & Greenhaus, 1992). Multiple
studies found that the same applies to turnover intention, which has shown to be one of the best
predictors of actual turnover (Griffeth, Hom & Gaertner, 2000; Van Dick et al., 2004; Trimble, 2006).
Organizations that know the causes of turnover intentions can prevent this intention to become
reality (Campion, 1991).
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Many researchers studied the concept of turnover intention, resulting in a lot of different, but very
similar, definitions of the concept. For example, Watrous, Huffman and Pritchard (2006) define
turnover intention as the thoughts of employees to voluntarily quit their job. Bothma and Roodt
(2013, p. 2) define the intention to leave the organization as ‘... an individual’s behavioural intention
or conation to leave the employ of the organization.’ Another very similar, and often used definition
of turnover intention is the definition of Tett and Meyer (1993, p. 262): ‘… the conscious and
deliberate wilfulness to leave the organization’. This last definition of Tett and Meyer (1993) is the
definition used in this study.
In the literature, several categories of turnover are distinguished. The categorization that is often
made consists of three types, namely: a) involuntary and voluntary turnover, b) functional and
dysfunctional turnover, and c) controllable and uncontrollable turnover (Mathis & Jackson, 2011).
The distinction between voluntary and involuntary turnover is based on whether the employee
decides for himself to leave (voluntary) or if he is dismissed (involuntary) by the company (Stumpf
& Dawley, 1981). In other words, voluntary turnover is the employee’s decision to leave the
organization, whereas involuntary turnover is the decision of the employer to end the employment
(Shaw, Delery, Jenkins & Gupta, 1998). The distinction between functional and dysfunctional
turnover depends on whether the employee leaving the organization is beneficial for the employer
or not. Dysfunctional turnover is when the employee wants to leave the organization while the
employer wants to retain the employee. Functional turnover is when the employee wants to leave
the organization, and the employer does not care whether the employee stays or not (Dalton,
Krackhardt & Porter, 1981). The third distinction is between controllable and uncontrollable
turnover, or in other words, avoidable and unavoidable turnover (Abelson, 1987). Controllable
turnover is the case of employee turnover that could have been avoided, for example, through a
raise or a promotion. On the other hand, uncontrollable turnover are these cases in which the
organization could not have done anything to avoid the turnover: the turnover was unavoidable for
example when the employee quits, following a husband who needs to move (Dalton et al., 1981;
Abelson, 1987).
Companies are deliberately trying to avoid voluntary and dysfunctional turnover because of the
substantial cost that is related to these types of employee turnover. These include the costs of loss
of productivity, recruitment, training, loss of continuity, and many more (Koh & Goh, 1995). In order
to reduce these costs related to employee turnover, the right retention strategies should be adopted
that reduce employee turnover intention (Das & Baruah, 2013). Employee retention strategies are
crucial for organizations, while it allows organizations to develop interventions that can reduce
turnover intention and actual turnover, and subsequently prevent the direct and indirect costs
related to turnover (Nedd, 2006). Osteraker (1999) divides employee retention strategies into three
dimensions; the social-, mental-, and physical dimension. The social dimension suggests that
employees are affected by the interaction with other people, both external and internal. The mental
dimension refers to the characteristics of the work, and the physical dimensions are the working
conditions and the pay, both of which can affect employee retention (Osteraker, 1999).
2.2.1 Measure turnover intention
Actual turnover can be easily measured by counting the historical turnover data; however, the
turnover intention is harder to measure. In order to measure the turnover intention, a scale is
required that measures employees’ intentions. Often the intention to leave the organization is
sparked by employee job attitude combined with job alternatives (Mitchell et al., 2001). Traditional
studies about turnover intention, therefore, often tested the attitudinal constructs job satisfaction
and organizational affective commitment (Griffeth & Hom, 1995). These two constructs will be
elaborated on at the end of this chapter. Nevertheless, some studies include a construct that
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17
directly measures employee turnover intention. For example, the study of Mitchell and colleagues
(2001) or the study of Hom, Griffeth and Sellaro (1984). Both measured employee turnover
intention with three items. The construct used in both studies is an adapted version of the original
construct of Mobley, Horner and Hollingsworth (1978). Earlier studies on the turnover intention
often relied on one-item measures, which showed to be less reliable (Miller, Katerberg & Hulin,
1979; Mobley 1982). The aggregation of multiple items helps to cancel out a part of the random
error around an individual’s true score. However, it does add to the length of the questionnaire.
Although, with three items instead of one, this is not a constraint. These three items are often
phrased as follows (Mobley et al., 1978):
(1) “I often think of leaving the organization”.
(2) “I intend to look for a new job within the next year”; and
(3) “If I could choose again, I would not work for this organization”.
These - or very similar - items are often used to measure employee turnover intention and show
high internal consistency and is considered reliable (Mitchell et al., 2001).
2.2.2 Conclusion – Paragraph 2.2
As is described at the start of these paragraphs about turnover intention, intentions have shown to
be a good predictor for actual behaviour, including the intention to leave an organization as the
predictor of actual turnover (Griffeth, Hom & Gaertner, 2000). Many researchers studied the
concept of turnover intention. The definition that is often used, and which is used in this study, is
the definition of Tett and Meyer, who define the intention to leave the organization (i.e., turnover
intention) as ‘the conscious and deliberate wilfulness to leave the organization’ (Tett & Meyer, 1993,
p. 262). Several categorizations are made within the broader concept of turnover intention. Often
the distinction is made between:
(1) involuntary and voluntary turnover;
(2) functional and dysfunctional turnover; and
(3) controllable and uncontrollable turnover (Mathis & Jackson, 2011).
Organizations focus on the controllable, voluntary and dysfunctional turnover. These are the cases
of turnover that they can control and during which an employee decides to leave that will harm the
functioning of the organization. In order to reduce employee turnover, retention strategies are
essential for organizations. The reasons why employees stay might not be the exact reverse of the
reasons why they leave, but they are related. The right interventions, for example, in the work
environment, can reduce employees’ turnover intention (Nedd, 2006; Reitz & Anderson, 2011).
Lately, most studies measure turnover intention, using a self-reporting measure that consists of
multiple items. The three items to measure turnover intention, as phrased by Mobley and
colleagues (1978), have been used a lot and has proven to be a reliable scale and will therefore
be used in this study (Mitchell et al., 2001).
2.3 WORK ENVIRONMENT AND EMPLOYEE TURNOVER INTENTION
Most of the studies about the work environment and its effects on turnover intention focus on the
non-physical (or non-built) work environment. Examples of these are studies focusing on the effects
of the organizational structure and climate (Hong & Kaur, 2008), the reward system (Jauhar, Ting,
Rahim & Fareen, 2017), the managerial style (Dixon & Hart, 2010) or the human resource practices
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18
on turnover intention (Garcia-Chas, Neira-Fontela & Castro-Casal, 2014). Additionally, a lot of
research about the work environment and turnover intention focuses on nurses, health- and social
workers (Flinkman, Leino-Kilpi & Salanterä, 2010; Chan et al., 2013). There are some studies that
study the effect of the built or physical work environment on employee turnover intention. Most of
these studies test for the effects of the work environment as a whole and also include elements of
the non-physical work environment in their work environment construct (e.g., Kurniawaty, Ramly &
Ramlawati, 2019; Santoni & Harahap, 2018).
An interesting study about the physical work environment and turnover intention is the study of the
American Society of Interior Designers (ASID) in which 663 participants were given carte blanche
at the start to make a list of those factors that affect their decision to accept or leave a job. In total,
21 per cent of the participants stated the physical workplace as the number one factor. When the
participants were explicitly asked whether the physical environment in which they work would affect
their decisions to leave, a total of 51 per cent of the participants said it would (Earle, 2003).
Another example of a study that examined the effect of the physical work environment on employee
turnover intention is the study of Kurniawaty, Ramly and Ramlawati (2019). In their study, they use
100 employees from a Malaysian bank to test the relationships between the work environment and
intention to leave the organization. Additionally, they also test the mediating effect of job satisfaction
in this relation. Based on their regression analysis, they conclude that there is a significant negative
relationship between work environment and turnover intention ( = -.177, p < .01). These findings
suggest that those employees who are more positive about their work environment as a whole are
less likely to leave their organization. Furthermore, they found a significant positive relationship
between work environment and job satisfaction ( = .216 p < .01), and a significant negative
relationship between job satisfaction and turnover intention ( = -.195, p < .01). These findings
suggest that those employees who are more satisfied are less likely to leave their organization.
Included in their construct for work environment are ambient conditions such as lighting, air
circulation and temperature, but also available equipment and furniture is incorporated in their work
environment construct (Kurniawaty, Ramly & Ramlawati, 2019). Besides these elements from the
physical work environment, they also included several non-physical elements in their work
environment construct. Examples of these elements are good relationships with superiors and co-
workers.
In 1994, Montgomery, Heubach, Weimer and Heerwagen did a pre-post study of a laboratory that
was renovated. They were able to track the turnover rates the year before and the year after the
renovation. The renovation included the heating, ventilation and air conditioning system, the spatial
layout and aesthetic upgrades. The study showed significant differences in turnover rate pre and
post-renovation. The turnover rate decreased by 60% in the year after the renovation compared
with the years before the renovation (Heerwagen, 2000).
Another study that examined the effect of the work environment on both job satisfaction and
intention to leave the organization, is the study of Santoni and Harahap (2018). They gathered data
among 260 employees working in the plastic industry of household appliances in Jakarta. The
results of their analysis show a significant negative relationship between the work environment and
turnover intention ( = -.220, p < .01). Included in their work environment construct were the layout,
space provided, lighting, air conditions, furniture and equipment. However, there were also several
non-physical work environment elements included in the work environment construct. For example,
the organizational values and work security (Santoni & Harahap, 2018).
As far as known, no studies examined the effects of signs, symbols and artefacts in the physical
work environment on turnover intention. Despite the fact the important role signs, symbols and
artefacts in communicating organizational values and steering employee behaviour and attitudes
(Bitner, 1992; Siu, Wan & Don, 2012). This propound lack of research is in line with the conclusion
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
19
of Mari and Poggesi (2013) in their literature review. They conclude that the effects on behaviour
and attitudes of the third dimension of Bitner (1992), the signs, symbols and artefacts, is less
studied than the other two dimensions. However, as Bitner (1992) explains, it forms an important
dimension of the work environment and affects occupant’s behaviour. Therefore, it is included in
this study.
Concerning cleanliness of the work environment, Vos et al., (2018) conclude in their literature
review about perceived cleanliness, that cleanliness is a requirement for a good physical working
condition, among other conditions such as lighting, adequate equipment and furniture. They
describe the perceived cleanliness of an environment as an important ambient condition. Overall,
they conclude that the perceived cleanliness has a noteworthy influence on the behaviour of the
occupant of the environment. However, they do encourage more research on perceived cleanliness
and its effect on occupants. As far as known, no studies examined the direct effect of perceived
cleanliness on employee turnover intention. Despite this, there is general agreement about the
importance of cleanliness of an environment (Vos et al., 2018). This becomes clear in the studies
that examined the relationship between cleanliness and employee commitment (e.g., Hanaysha,
2016; Aydogdu & Asikgil, 2011; Applebaum, 2008) and employee job satisfaction (e.g.,
Ikartrinasari, Prayogo, Ariyanti, 2018; Balouch & Hassan, 2014; Ayim Gyekye, 2005). One study
was found that had cleanliness included in their physical work environment construct. This study of
Ikatrinasari, Prayogo and Ariyanti (2018) found a significant positive relationship between
perceived work environment and job satisfaction = .461 p < .01). More interestingly, they found a
significant correlation between the indicator for cleanliness and intention to leave the organization.
This suggests an important relationship between the cleanliness of the environment and turnover
intention.
2.3.1 Other factors that spark turnover intention
Besides elements of the physical work environment, several other factors can spark employee
turnover intention. In their literature review, Das and Baruah (2013) give a whole list of factors that
are related to turnover intention. They conclude that this list can be reduced to two crucial factors,
namely the lack of affective commitment and job satisfaction. Both factors are the result of the list
of underlying factors (Mobley et al., 1979). This list contains factors such as compensation, rewards
and recognition, the opportunity for growth, work environment, participation in decision-making,
work-life balance, work environment, training and development, leadership, and job security (Das
& Baruah, 2013; Boxall, Macky & Rasmussen, 2003). For example, when the compensation level
is perceived as too low, the employee tends to be less satisfied and committed. Similar relations
are found between compensation level and affective organizational commitment (Vandenberghe &
Tremblay, 2008). In their study, they also found a significant negative relationship between both
commitment and turnover intention, and job satisfaction and turnover intention. In their review
paper, Strachota and colleagues (2003) conclude that job dissatisfaction is cited as a major cause
of employee turnover intention. Other reviews of the literature on the relationship between job
satisfaction and turnover intention consistently report a negative relationship between both (Tett &
Meyer, 1993; Hellman, 1997; Porter & Steers, 1973; Mobley, Griffeth, Hand & Meglino, 1979;
Coomber & Barriball, 2007). Similarly, multiple studies report a negative relationship between
affective commitment and turnover intention (Tett & Meyer, 1993; Aydogdu & Asikgil, 2011; Chang,
1999; Lew, 2009).
Interestingly, several studies show relationships between the physical work environment and
employee job satisfaction and affective commitment. For example, Danielsson and Bodin (2008)
studied the differences in job satisfaction based on office type. Another example is the study of
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
20
Leder et al. (2016). In this study, the effects of the built office environment on employee satisfaction
was analysed. This analysis showed that several elements of the work environment have a
significant positive effect on employee satisfaction. A final example of a study that examines the
relationship between the physical work environment and job satisfaction is the study of Al Horr and
colleagues (2016). In their extensive literature review, they explain that the findings of multiple
surveys showed that employees are dissatisfied with the ‘open-plan’ office. Reasons for this
dissatisfaction are distractions, noise, and lack of privacy that comes with this work environment
design and the corresponding layout.
There are also several studies that examined the effects of the physical work environment on
commitment. For example, McGuire and McLaren (2009) confirm in their study the significant
positive relationship between the physical work environment and employee commitment (β = 0.53,
p < 0.01). Previous studies of for example Weiss (1999) and Wise (1987) had similar results.
Overall, providing adequate facilities to employees will result in greater employee commitment,
including affective commitment (McGuire & McLaren, 2009).
Besides job satisfaction and affective commitment, several demographic variables that have shown
to covary with turnover intention. These variables are the employee’s gender, age and
organizational tenure (Arnold & Feldman, 1982; Cotton and Tuttle, 1986; Gregersen and Black,
1992; Lee et al., 2004; Mitchell et al., 2001). For example, the findings of Arnold and Feldman
(1992) suggest that employees that work longer for an organization (high tenure) have a lower
turnover intention. Additionally, they found a negative relationship between age and turnover
intention, suggesting that the older an employee gets, the less intended they are to leave the
organization. Similar results were found in the study of Mobley et al. 1979. Arnold and Feldman
(1982) also found a significant correlation between gender and turnover intention. Their findings
suggest that females are more likely to leave an organization than males. Similar results were found
by Marsh and Mannari (1977). Furthermore, Cotton and Tuttle (1978) mention in their meta-
analysis and review about employee turnover literature that the educational level correlates with
turnover intention. Their meta-analysis produces highly significant results (p < .005), indicating a
positive correlation between educational level and turnover intention. Suggesting that higher
educated employees have a higher intention to leave their organizations.
2.3.2 Conclusion – paragraph 2.3
Multiple studies examined the effects of the work environment on employee turnover intentions.
Most of these studies focused on the non-physical work environment and focused for example on
the effects of organizational structure and climate (Hong & Kaur, 2008), the reward system (Jauhar,
Ting, Rahim & Fareen, 2017), the managerial style (Dixon & Hart, 2010) or the human resource
practices on turnover intention (Garcia-Chas, Neira-Fontela & Castro-Casal, 2014). However, there
are a few studies that examined the effects of the physical work environment on turnover intention.
Findings of these studies suggest effects of the layout (Montgomery et al., 1994; Santoni &
Harahap, 2018), space (Santoni & Harahap, 2018), furniture and equipment (Kurniawaty, Ramly &
Ramlawati, 2019), cleanliness (Ikatrinasari, Prayogo & Ariyanti, 2018) and ambient conditions
(Kurniawaty, Ramly & Ramlawati, 2019; Montgomery et al., 1994; Santoni & Harahap, 2018) on
employee turnover intention.
So far, no academics incorporated signs in their research on the effects of the perceived work
environment on employee turnover intention. Despite the considered importance of signs in
steering employee behaviour and attitudes (Siu, Wan & Don, 2012). According to Bitner (1992),
the signs, symbols and artefacts form an important dimension in the perception of an environment
that cannot be ignored in examining the effects of the perceived environment on its occupant’s
behaviour and attitudes. Therefore, this study not only focuses on the layout, space, ambient
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
21
conditions, functionality of equipment and furniture, and cleanliness. But also includes the
perception of the signs in the office environment.
Besides the physical work environment, there are several other factors that might spark employee
turnover intention. Das and Baruah (2013) conclude that this list can be brought down to two crucial
factors that comprise most of the underlying factors. These two factors are employee job
satisfaction and organizational affective commitment. Both job satisfaction and affective
commitment have consistently shown to be negatively related to employee turnover intention
(Aydogdu & Asikgil, 2011). The work environment is one of the underlying factors of both employee
job satisfaction and affective commitment (Das & Baruah, 2013). Several studies on the physical
work environment found significant positive relationships between the physical work environment
and job satisfaction (e.g., Leder et al., 2016). Similarly, several studies found a significant
relationship between the physical work environment and affective commitment (e.g., McGuire &
McLaren, 2009).
Besides the work environment, job satisfaction and affective commitment, academics found several
demographic factors that covary with turnover intention. The most important ones are gender, age,
organizational tenure and educational level (Cotton and Tuttle, 1986; Arnold & Feldman, 1982).
2.4 CONCEPTUAL FRAMEWORK AND HYPOTHESES
Many researchers try to find the essential determinants of employee turnover intention. Knowledge
about these determinants helps them to develop managerial implications that helps them to lower
employee turnover intention, resulting in fewer problems and costs related to high turnover rates
(Arshadi & Shahbazi, 2013).
As explained before, there are several elements of the work environment that can be perceived
and have effects on occupant behaviour and attitudes (Bitner, 1992). As explained in paragraph
2.3, a few studies suggest relationships between the work environment and employee turnover
intention. Findings of these studies suggest effects of the layout (Montgomery et al., 1994; Santoni
& Harahap, 2018), space (Santoni & Harahap, 2018), the functionality of furniture and equipment
(Kurniawaty, Ramly & Ramlawati, 2019), cleanliness (Ikatrinasari, Prayogo & Ariyanti, 2018) and
ambient conditions (Kurniawaty, Ramly & Ramlawati, 2019; Montgomery et al., 1994; Santoni &
Harahap, 2018) on employee turnover intention. Based on these findings the following hypotheses
are formulated, suggesting that the more positive the employee’s perception of the element of the
work environment, the less they are intended to leave their organization.
1. Employee’s perception of the layout of their work environment is negatively related to
their turnover intention.
2. Employee’s perception of the space of their work environment is negatively related to
their turnover intention.
3. Employee’s perception of the functionality of equipment and furniture of their work
environment is negatively related to their turnover intention.
4. Employee’s perception of the cleanliness of their work environment is negatively related
to their turnover intention.
5. Employee’s perception of the ambient conditions of their work environment is negatively
related to their turnover intention.
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
22
6. Employee’s perception of the signs of their work environment is negatively related to
their turnover intention.
There are several factors besides the work environment that can spark an employee turnover
intention. These factors can be brought down to two crucial factors that have consequently shown
to have a significant negative relationship with turnover intention. These factors are job satisfaction
and affective commitment (Das & Baruah, 2013; Tett & Meyer, 1993; Aydogdu & Asikgil, 2011).
Both factors have shown to be the consequence of several underlying factors such as
compensation, rewards and recognition, the opportunity for growth, work environment, participation
in decision-making, work-life balance, work environment, training and development, leadership,
and job security (Mobley et al. 1979). Validating the relationship between turnover intention and
both job satisfaction and affective commitment is an important step in our model that is presented
at the end of this paragraph. Therefore, the following hypotheses are formulated:
7. Job satisfaction is negatively related to employee turnover intention
8. Affective commitment is negatively related to employee turnover intention
Besides the hypothesized direct effect of the perception of elements of the work environment on
turnover intention, there is also a hypothesized indirect effect through the mediating variables job
satisfaction and affective commitment. Both factors are expected to be negatively related to
turnover intention. Additionally, based on findings in previous studies, it can be expected that the
perceptions of several elements of the work environment are positively related to job satisfaction
and affective commitment (e.g., McGuire & McLaren, 2009; Leder et al., 2016). These relationships
can be explained by the framework of Bitner (1992). In her study, she explains how the perception
of an environment results in a response within the occupants of the environment. This internal
response can be affective and attitudinal and can include feelings of satisfaction and commitment
(Mehrabian & Russell, 1974). This internal response results in a behavioural response of the
occupant (Bitner, 1992; Mehrabian & Russell, 1974). Interestingly, the internal responses such as
job satisfaction and affective commitment have been linked to turnover intention (Aydogdu &
Asikgil, 2011). Therefore, it is hypothesized that the relationship between the perception of the
previously defined elements of the work environment and turnover intention is mediated by both
(a) job satisfaction and (b) affective commitment. This led to the following hypotheses:
9a. Job satisfaction mediates the relationship between employee’s perception of the layout
and their turnover intention.
9b. Affective commitment mediates the relationship between employee’s perception of the
layout and their turnover intention.
10a. Job satisfaction mediates the relationship between employee’s perception of space
and their turnover intention.
10b. Affective commitment mediates the relationship between employee’s perception of
space and their turnover intention.
11a. Job satisfaction mediates the relationship between employee’s perception of the
functionality of equipment and furniture and their turnover intention.
11b. Affective commitment mediates the relationship between employee’s perception of
the functionality of equipment and furniture and their turnover intention.
CHAPTER 2 – THEORY ON WORK ENVIRONMENT & EMPLOYEE TURNOVER INTENTION
23
12a. Job satisfaction mediates the relationship between employee’s perception of the
cleanliness and their turnover intention.
12b. Affective commitment mediates the relationship between employee’s perception of
the cleanliness and their turnover intention.
13a. Job satisfaction mediates the relationship between employee’s perception of the
ambient conditions and their turnover intention.
13b. Affective commitment mediates the relationship between employee’s perception of
the ambient conditions and their turnover intention.
14a. Job satisfaction mediates the relationship between employee’s perception of the signs
and their turnover intention.
14b. Affective commitment mediates the relationship between employee’s perception of
the signs and their turnover intention.
Literature has indicated that the demographic variables age, gender, organizational tenure and
educational level can covary with turnover intention (Arnold & Feldman, 1982; Cotton & Tuttle,
1978). Therefore, these variables are included in the conceptual framework.
Based on the theoretical framework presented in the previous paragraphs, the conceptual
framework is designed as presented in Figure 3. The conceptual model shows the hypothesized
relationships between perceptible elements of the work environment – the independent variables
– and employee intention to leave the organization, the dependent variable. Additionally, the
conceptual model includes job satisfaction and affective commitment as mediating variables,
because of its hypothesized relationship with both the perception of elements of the work
environment and employee turnover intention.
Figure 3
Conceptual framework
24
3
3 METHODS
This study conducts quantitative research. This quantitative data is gathered using a questionnaire.
In this chapter is explained how the questionnaire is designed; how the data is gathered; and how
this data is analysed. First, a short description of the process behind the literature findings is given,
where after the constructs and the questionnaire are discussed. After that, the sampling method
and the data analysis is explained. This chapter also sheds a light on the reliability and validity of
this study, the used methods and included constructs. A complete overview of the research
framework can be found in Appendix 1.
3.1 LITERATURE STUDY
The main focus of the literature study is to describe the relationship between the perception of
elements of the work environment and an employee turnover intention to answer the theoretical
research questions. Before the relationship between both is studied, the two topics are discussed
separately. Literature for both topics is gathered using the search engines of Scopus and Google
Scholar. To optimize the searches, Boolean operators (AND, OR), double quotations marks (“...”)
and wildcards (? and *) are used. Additionally, the papers need to be in English and be peer-
reviewed. The snowballing method is used to find additional relevant articles. Relevant references
that are included in the found articles are also included in this study. The literature study results in
a theoretical framework and several hypotheses that form the basis of the quantitative part of this
study.
3.2 CONSTRUCTS
A questionnaire is developed based on the identified constructs during the literature study. This
questionnaire gathers data about how employees perceive their work environment, their attitude
towards their job and their behavioural intentions. The constructs that are included in the
questionnaire are job satisfaction, affective commitment, intention to leave the organization, and
the perception of the work environment. The next couple of paragraphs gives a more detailed
overview of the included constructs. The original constructs can be found in Table 20, Appendix 3.
3.2.1 Job Satisfaction
The five items measuring job satisfaction are based on the job satisfaction scale developed by
Brayfield and Rothe (1951). Multiple scholars have confirmed the validity and reliability of this scale
(e.g., Lambert, Hogan and Griffin, 2007; Hochwarter et al., 2003; Ilies and Judge, 2002). These
five items are scored on a Likert scale consisting of five categories of disagreement-agreement
(Brayfield and Rothe, 1951). A higher score indicates higher job satisfaction.
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25
3.2.2 Affective Commitment
The included items measuring affective commitment are based on the three-component model of
organizational commitment of Allen and Meyer (1990). This construct exists of a total of 24 items
and is divided into three parts: normative-, affective- and continuance commitment. Each part
consists of eight items that can be scored on a five-point Likert scale from strongly disagree (1) to,
strongly agree (5). A higher score indicates stronger employee commitment.
This paper specifically focuses on the affective commitment of employees because this component
can be seen as the core of organizational commitment (Mercurio, 2015; Samudi, Slambolchi, &
Mobarakabadi, 2016). Moreover, multiple studies have shown that this component predicts
employee behaviour better than the two other components (Meyer, Paunonen, Gellatly, Goffin, &
Jackson, 1989; Tett & Meyer, 1993). Affective commitment is defined as “the degree to which an
individual is psychologically attached to an employing organization through feelings such as loyalty,
affection, warmth, belongingness, fondness, pleasure, and so on” (Jaros, Jermier, Koehler &
Sincich, 1993 p. 954). It describes the employees’ emotional bond to the organization (Chang,
1999) and their desire to stay with the organization (Allen and Meyer, 1990).
The reliability and validity of the organizational commitment scale of Allen and Meyer (1990) has
been confirmed by many scholars (e.g., Kehoe & Wright, 2010; Meyer, Stanley, Herscovitch, &
Topolnytsky, 2002; Hackett, Bycio & Hausdorf, 1994)
3.2.3 Turnover Intention
The turnover intention scale of Mitchell et al. (2001) exists of three items that are used to measure
the intention to leave the organization. These three items are scored on a five-point Likert scale
from strongly disagree (1) to, strongly agree (5). This scale was validated by several scholars (e.g.,
Takawira, Coetzee & Schreuder, 2014; Halbesleben & Wheeler, 2008). An example of a statement
from the turnover intention scale is ‘Do you intend to leave the organization in the next 12 months?’’.
3.2.4 Perception of Work Environment
The 29 items measuring the perception of the work environment are adapted from Wakefield and
Blodgett (1996). This construct exists of six parts: layout (Lay), space (Spa), ambient (Amb), the
functionality of equipment and furniture (Fun), cleanliness (Cle), and signs (Sig). One single item
is added to measure the holistic perception of the work environment. All items are measured on a
five-point Likert scale from strongly disagree (1) to, strongly agree (5). Similar constructs for
measuring the perception of the work environment as the ones used in the study of Wakefield and
Blodgett (1996) has shown excellent reliability and validity (e.g., Wakefield & Baker, 1998; Han &
Ryu, 2009; Siu, Wan & Dong, 2012).
3.2.5 Demographic variables
Several items measuring demographic variables are included because scholars found that these
can covary with employee turnover intention. These variables are gender, age and organizational
tenure (Cotton and Tuttle, 1986; Gregersen and Black, 1992; Lee et al., 2004; Mitchell et al., 2001).
Additionally, Arnold and Feldman (1982) observed a relationship between the level of education
and employee turnover. Therefore, a question regarding the respondents’ educational level is also
included in the questionnaire.
The coding of the Demographic variables can be found in Table 2. For the variables age, tenure,
hours and education, a higher score indicates more years, more time or higher education.
CHAPTER 3 – METHODS
26
Table 2
Coding of the demographic variables
Demographic variable Answer Code
Gender Male 1 Female
2
Age 0-17 years 1 18-29 years 2 30-39 years 3 40-49 years 4 50-59 years 5 60+ years
6
Highest Education Level Lagere school 1 Middelbare school 2 MBO 3 HBO 4 WO
5
Weekly Hours 0-8 hours 1 9-16 hours 2 17-27 hours 3 25-32 hours 4 33-40 hours 5 40+ hours
6
Organizational Tenure 0-5 years 1 6-10 years 2 11-15 years 3 16-20 years 4 21-25 years 5 25+ years 6
3.3 QUESTIONNAIRE
Data describing employees’ perception of elements of their work environment and their turnover
intention is needed to test the previously described hypotheses. A questionnaire is conducted to
collect this data. The constructs and items in the questionnaire are based on the theoretical
framework, as presented in chapter 2 and explained in paragraph 3.2. The questionnaire consists
of two main parts. The first part consists of items measuring turnover intention, perception of the
work environment, employee satisfaction and employee affective commitment. The second part
consists of demographic questions, designed to gather information about the gender, age,
educational level and organizational tenure of the respondent. All the items in the first part are
measured on a five-point Likert scale, ranging from “1 = strongly disagree; 2 = disagree; 3 = neutral;
4 = agree; 5 = strongly agree”.
The questionnaire is accessible online via a link for all employees of the participating organizations.
All respondents get the same questions, and all items appear in the same order for each
respondent. All questions in the questionnaire are mandatory. However, the respondent is able to
stop the questionnaire at any time, resulting in an incomplete questionnaire. Only completed
CHAPTER 3 – METHODS
27
questionnaires are considered valid and are included in the study. Based on the pilot study, it is
expected that employees are able to complete the questionnaire within ten minutes.
3.3.1 Pilot questionnaire
Before the questionnaire was distributed, it was first tested during a pilot among six participants to
make sure it was free of errors and that the questions were interpreted correctly. Additionally, the
pilot gave an idea of how long the actual survey takes. Some questions were rephrased a bit if they
were considered as unclear. Furthermore, the order of the different topics was changed. In the
original questionnaire, the respondents needed to answer the demographic questions first. In the
final questionnaire, these demographic questions are answered at the end. This decision aimed to
make people more honest in giving their opinion and intention when they have not yet shared their
personal details.
Finally, the facility manager of one of the locations had some remarks. These remarks focused on
the information at the start of the questionnaire. Based on these remarks, the privacy statement
was rewritten to suit the wishes of the participating companies better. Additionally, the introduction
of the questionnaire was rewritten to give respondents a better idea of what to expect.
3.3.2 Final questionnaire
The final questionnaire exists of 54 items divided over three broad categories: 32 items about the
work environment, 16 items about the work itself and finally six demographic items. The full
questionnaire can be found in Appendix 2. The average time to complete the questionnaire was 7
minutes and 52 seconds. Furthermore, respondents could send remarks via the mail. Only one
respondent sent an email, which was about the exclusion of questions regarding “office gardens”.
3.4 SAMPLE AND SETTING
People from the same sector - the financial sector - and working in the same work environment -
same office location - were targeted using purposive sampling. A total of seven local organizations
active in the financial sector were approached simultaneously. The contact person, often the local
director or facility manager, were asked whether they were willing to distribute the questionnaire
among their employees. The targeted organizations were found within the researchers’ network
and consisted of local banking and accounting offices. Of the seven targeted offices, a total of four
were willing to participate.
The targeted population existed of approximately 675 employees working at four different locations
of companies active in the financial sector. A total of 242 employees started the questionnaire
between the 2nd and 29th of January 2020. This number resulted in an initial response rate of
around 36%. Of these 242 questionnaires started, a total of 215 questionnaires were completed
(88,84%). In the biggest office (A) approximately 485 employees are working, of whom 162 finished
the questionnaire (33,40%). In the second office (B), a total of 68 employees are working. Of these
68 employees, 30 employees completed the questionnaire (44,12%). At the third office (C), a total
of 55 employees are working of whom 17 completed the questionnaire (30.91%). The fourth office
(D) has a total of 63 employees, of whom six completed the questionnaire (9,52%). Besides the
fourth office, these response rates can be considered as normal if we compare them to the findings
of Baruch and Holtom (2008). They analyse 1607 published studies in their review and found an
average response rate of 35.7% with a standard deviation of 18.8% for studies that utilize data
collected from organizations.
CHAPTER 3 – METHODS
28
3.5 DATA ANALYSIS
Before the data is analysed, all incomplete data is omitted from the dataset. The gathered
quantitative data is analysed using the Lavaan package in R Studio. Structural Equation Modelling
(SEM) is used to analyse structural relationships between the measured variable ‘turnover
intention’ and latent (unobserved) variables that are inferred from the observed variables. The
coding used in R can be found in Appendix 5. SEM is the technique of choice to obtain significant
information about the determinants for the participants’ perception (Hair, Sarstedt, Hopkins &
Kuppelwieser, 2014). This study uses SEM to find the latent variables within the work environment
that affect the employee’s perception of the environment. SEM enables the simultaneous
estimation of a system of structural equations, the goodness of fit, and the total effects (Hair,
Anderson, Tatham & Black, 1998). Therefore, SEM is seen as an excellent method for testing
causal models.
Following the process described by Anderson and Gerbing in 1988, an analysis plan is designed
to test the hypothesis. The model that is tested consists, like most behavioural research, of
variables that are not directly measurable, also known as latent variables (Churchill, 1979; Hair et
al., 1998). According to Hox, Moerbeek and van de Schoot (2017), SEM is the best-suited model
for analysing a model that contains latent variables. The SEM analysis consists of two steps, two
separate models: the measurement model and the structural model.
The first step is the measurement model. The items included in the questionnaire are analysed to
assess the construct reliability and measurement validity of the model. Explanatory- and
Confirmatory Factor Analyses (EFA & CFA) are used to put the observed independent variables
into factors (Hair et al., 1998). It is assumed within the factor analysis that a set of underlying latent
variables can explain the covariances between the set of observed variables. During the EFA, there
is no hypothesis about the relationship between the latent variables and observed variables and
the number of underlying latent variables. The model is arbitrary: all variables will load on all factors.
Additionally, for each factor, one loading is fixed to one, to give the latent variable an interpretable
scale in both analyses.
EFA is conducted, using a principal component analysis to see whether the included items fall
under the predefined constructs that are based on previous studies. As the name already says, the
EFA is exclusively exploratory, which means that there is no prior specification of the number of
factors. A maximum likelihood estimation is used to specify the number of underlying factors and
to test the goodness of fit. Items that have a corrected item-total correlation of less than .5 are
eliminated from the scales (Koufteros, 1999). Additionally, a Cronbach alpha higher than .7 for
established scales and .6 for new scales is desired (Churchill, 1979). However, according to
Anderson and Gerbing (1988), EFA does not result in an exact test of un-dimensionality.
Additionally, the EFA does not give an explicit test statistic for the assessment of the discriminant
and convergent validity. This is given in the CFA.
In SEM, the hypothesized model is specified before the analysis is started, based on previous
findings and theories. After the model is defined, the factor loadings and (co)variances are
estimated. A statistical chi-square test is conducted to test how well the hypothesized model fits
the data. If the chi-square is significant, the model is rejected, and a better model needs to be
found. This is done by removing paths and parameters from the model.
The confirmatory analysis is done after the exploratory analysis. This analysis involves the
specification and estimation of the parameters in the hypothesized model of the factor structure. A
set of latent variables (factors) will account for the covariances among the set of observed variables
in this model (Koufteros, 1999). The path diagram of this model is presented in a figure in the results
chapter. The observed variables in this model are represented by squares and the latent variables
CHAPTER 3 – METHODS
29
by circles. A causal effect of the latent variable on the observed variable is represented by an arrow
from a latent variable to an observed variable.
Multiple fit indices will be used to assess the model fit of the CFA and SEM. These include root
mean square error of approximation (RMSEA), Bentler-Bonett Normed fit index (NFI), comparative
fit index (CFI), and Chi-square.
Additionally, mediation analysis is conducted to test for indirect effects of the perception of elements
of the work environment on turnover intention. This analysis tests whether the effect of the
independent variable on the dependent variable is mediated by another variable. The mediators in
this study are job satisfaction and affective commitment. The mediation analysis consists of several
steps. First, the total direct effect is measured. This is the direct effect of the independent variable
on the dependent variable. Without any interference of the mediator. The relation between both
variables does not necessarily have to be significant to continue with the next step (Bollen, 1989;
Hayes, 2017). Second, the effect of the independent variable on the mediating variable is tested.
This effect needs to be significant to establish mediation. Third, the combined effect of the
independent variable and the mediating variable on the dependent variable is tested. This step
confirms whether the mediator has a significant effect on the dependent variable or not, while
controlling for the independent variable. To be in place as a mediator, the mediator must explain
more of the variance in the dependent variable than the independent variable does. If the
independent variable during this third step is not significant, but the mediating variable is, there is
complete mediation. There is an incomplete mediation when both the effect of the independent
variable and the mediating variable on the dependent variable are significant. In this case, there is
another effect of the independent variable on the dependent variable, which does not go through
the included mediator. During these steps bootstrapping is used to become more confident of the
findings. The model is bootstrapped 1.000 times. I.e. The model is recalculated 1.000 times, using
randomly drawn subsamples from the data (Rucker, Preacher, Tormala & Petty, 2011; Rosseel,
2012). The R coding used for different models can be found in Appendix 5.
30
4
4 RESULTS
This chapter presents the results of this study and starts with the respondents’ characteristics, the
preliminary data analysis and the descriptive statistics. Hereafter, the exploratory and confirmatory
factor analyses are presented. Then the structural equation model is conducted, and finally, the
hypotheses are tested.
4.1 CHARACTERISTICS OF RESPONDENTS
In total, 215 employees from four offices and two organizations completed the whole questionnaire.
The characteristics of these respondents can be found in Table 3. The number of males and
females participating were almost equally split, with a total of 108 males and 107 females. Most of
the respondents were working in the large open-plan office, namely a total of 122 (56,7%). Most of
the respondents are between 40-49 years old (37,2%). However, also a large share of the
respondents is aged between 30-39 years and 50-59 years. Furthermore, most respondents work
five days per week, and almost all respondents work at least four days, or as measured between
25-32 or 33-40 hours. Additionally, a total of 125 respondents finished an HBO study and another
34 finished a university degree. Finally, most of the respondents, a total of 51 (23,7%), worked for
more than 25 years for the same organization. On the other hand, a total of 45 employees (20,9%)
just started working for their organization.
Table 3
Characteristics and demographics of the respondents
Questions/options Number of responses Percentage
Office Type (n=215) Cell-Office (1 person) 4 1,9% Shared-room office (2-3 persons) 3 1,4% Small open-plan office (4-9 persons) 16 7,4% Medium open-plan office (10-24 persons) 35 16,3% Large open-plan office (24+ persons) 122 56,7% Flex office 31 14,4% Combi office 4 1,9% Office location (n=215) Location A 162 75,4% Location B 30 14,0% Location C 17 7,9% Location D 6 2,8% Gender (n=215) Male 108 50,2% Female 107 49,8%
CHAPTER 4 – RESULTS
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Age (n=215) 18-29 years 22 10,2% 30-39 years 44 20,5% 40-49 years 80 37,2% 50-59 years 58 27,0% 60+ years 11 5,1% Educational level Lagere school 0 0,0% Middelbare school 8 3,7% MBO 48 22,3% HBO 125 58,2% WO 34 15,8% Working hours 0-8 hours 0 0,0% 9-16 hours 4 1,9% 17-24 hours 8 3,7% 25-32 hours 52 24,2% 33-40 hours 126 58,6% 40+ hours 25 11,6% Organizational tenure 0-5 years 45 20,9% 6-10 years 30 14,0% 11-15 years 31 14,4% 16-20 years 30 14,0% 21-25 years 28 13,0% 25+ years 51 23,7%
4.2 PRELIMINARY DATA ANALYSIS
Data were prepared and screened using the procedures as recommended by Kline (1997). For
those questionnaires that missed a single answer variable mean imputation was used.
Questionnaires which had more missing answers were deleted from the dataset and excluded from
the analysis. Furthermore, univariate outliers were identified as those with standardized scores
more than three standard deviations from the mean. Additionally, multivariate outliers were
identified using Mahalanobis distance (Hair, Anderson, Tatham & Black, 1998). A total of 22
univariate outliers and one multivariate outlier were found and deleted. The remaining sample used
for analysis numbered 192 cases.
4.3 DESCRIPTIVE STATISTICS
A total of 192 complete questionnaires were included in this study. These 192 respondents
answered a total of 29 items related to the six predefined elements of their work environment. They
scored these items on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Additionally,
they also completed a total of 16 items considering their affective commitment, job satisfaction and
turnover intention. The mean scores of all these items are presented in the fourth column of Table
4. This gives a good overview of how the employees evaluate the perception of different elements
of their work environment and how they evaluate their turnover intention.
Overall, the items for perceived layout and cleanliness of the office environments were scored the
highest. Primarily, the accessibility of the toilets due to the layout (Lay3) and the perceived
cleanliness of the canteen (Cle2) was scored high (the exact description of the items can be found
in Appendix 2). The mean scores for the intention to leave the organization items were low,
CHAPTER 4 – RESULTS
32
indicating that on average, the respondents did not consider leaving their organization. The three
highest scores were given to the items ‘I find my work pleasant’ (Sat1), ‘Time flies at work’ (Sat2),
and ‘The layout of our office environment makes it easy to access the toilets’ (Lay3). Suggesting
high levels of job satisfaction and a positive perception of the layout. The scores for the other items
measuring the perception of the layout are also relatively high.
The three lowest scores were given to the three items measuring intention to leave the organization
(Int1, Int2 and Int3). Suggesting an overall low turnover intention among the respondents. The three
items measuring the perception of the work environment with the lowest scores are ‘The amount
of plants in my office environment is pleasant’ (Amb7), ‘I have enough privacy at my workplace’
(Spa2), and ‘The temperature in my work environment is comfortable’ (Amb1). These low scores
suggest some issues with the ambient conditions, as well as with the privacy due to the perception
of the space within the office environment.
Looking at the average evaluation of the different elements of the work environment, the employees
evaluate the perception of the layout of their work environment the highest (M = 4.16, SD = .60).
Thereafter, the perceived cleanliness is evaluated the highest with a mean of 4.05 and a standard
deviation of .57. Overall, the perception of the ambient conditions had the lowest scores (M = 3.05,
SD = .97). The perception of the signs was evaluated slightly better (M = 3.16, SD = .89). The two
other perceived elements of the work environment, ‘space’ and ‘functionality of equipment and
furniture’ were evaluated above average with mean scores of 3.48 (SD = .70) and 3.51 (SD = .95)
respectively.
Overall, the employees evaluated their intention to leave their organization relatively low (M = 2.06,
SD = .93). All three the items measuring the intention to leave the organization were scored very
similarly, with mean scores of 2.02, 2.16 and 2.02. The second item, ‘feel to leave the organization
within 12 months’ was evaluated slightly higher, however, this is only a minor difference.
Table 4
Means, standard deviations, and minimum- and maximum scores for all the items (N=192)
Group
Item
code Measure Mean SD Min Max
Ambient
conditions Amb1 Temperature 2.70 1.14 1 5
Amb2 Air quality 2.85 1.04 1 5
Amb3 Scent 3.39 .73 1 5
Amb4 Music/Sounds 2.77 1.02 1 5
Amb5 Daylight 3.48 .92 1 5
Amb6 Artificial light 3.51 .85 1 5
Amb7 Biophilia 2.65 1.07 1 5
Average 3.05 .97
Cleanliness
Cle1 Toilets 3.94 .75 2 5
Cle2 Canteen 4.11 .47 3 5
Cle3 Stair- and hallways 4.08 .48 3 5
Cle4 Overall 4.05 .59 3 5
CHAPTER 4 – RESULTS
33
Average 4.05 .57
Affective
Commitment Com1 Stay with organization 3.58 .88 2 5
Com2 Talk about organization
with others 3.58 .74 1 5
Com3 Share the organization’s
problems 2.77 .87 2 5
Com4 Potential feeling of
attachment 2.76 .88 1 5
Com5 Feel part of the family 3.35 .91 1 5
Com6 Emotional attachment 3.51 .89 1 5
Com7 Personal meaning 3.35 .79 2 5
Com8 Feelings of attachment 3.66 .83 1 5
Average 3.32 .85
Functionality
of equipment and Fun1 Availability of equipment 4.08 .63 2 5
furniture Fun2 Advancement of equipment 3.48 .90 1 5
Fun3 Quality of equipment 3.65 .89 1 5
Fun4 Comfort of furniture 3.14 1.16 1 5
Fun5 Quality of furniture 3.22 1.16 1 5
Fun6 Arrangement of furniture 3.50 .98 1 5
Average 3.51 .95
Intention to Leave
the organization
Int1 Plan to leave within 12
months 2.02 .92 1 5
Int2 Feel to leave within 12
months 2.14 .99 1 5
Int3 Will to leave organization
within 12 months 2.02 .87 1 5
Average 2.06 .93
Layout
Lay1 Reach the reception 4.20 .64 2 5
Lay2 Reach the meeting rooms 4.07 .66 2 5
Lay3 Reach the toilets 4.32 .52 3 5
Lay4 Reach the canteen 4.05 .67 2 5
Lay5 Move through building 4.17 .52 3 5
Average 4.16 .60
Job Satisfaction
Sat1 Pleasantness of work 4.24 .66 2 5
Sat2 Felt duration of the workday 4.34 .55 3 5
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34
Sat3 Satisfaction with job 3.94 .67 2 5
Sat4 Enthusiasm 4.09 .56 2 5
Sat5 Satisfaction with work 4.00 .64 2 5
Average 4.12 .62
Signs
Sig1 Quantity 3.16 .90 1 5
Sig2 Visibility 3.12 .89 1 5
Sig3 Understandability 3.23 .86 1 5
Sig4 Usefulness 3.12 .89 1 5
Average 3.16 .89
Space
Spa1 Personal space to work 4.06 .67 2 5
Spa2 Privacy at workspace 2.68 1.06 1 5
Spa3 Close to relevant
colleagues 3.90 .76 2 5
Spa4 Not too close to others 3.27 .31 1 5
Average 3.48 .70
Table 5 show the correlations for the variables and constructs that were included in this study (see
Appendix 4, table 21, 22 and 23 for full correlation tables). The table shows the following significant
correlations between turnover intention and some independent variables:
- Turnover intention and perception of the space, -.148, p < .05; - Turnover intention and job satisfaction, r = -.401, p < .01; - Turnover intention and affective commitment, r = -.457, p < .01.
None of the control variables showed any correlation with turnover intention. However, there were
several significant correlations between the different perceived elements of the work environment.
Additionally, all the perceived elements of the work environment showed a significant correlation
with job satisfaction (p < .01). Furthermore, both the perception of space and the perceived
functionality of the furniture and equipment are significantly correlated to affective commitment (p
< .01). Additionally, the perceived cleanliness is significantly correlated to affective commitment at
p < .05. The effects size of these significant correlations can be considered as medium because
the correlation coefficient is around .30 (Field, 2013).
Other interesting significant correlations are between gender and both perceived ambient
conditions and perceived functionality of equipment and furniture. The significant negative
correlation between gender and perception of ambient conditions (r = -.263, p < .01) suggest that
overall female score their perception of the ambient conditions lower than males. Similarly, the
significant negative correlation between gender and perceived functionality of equipment and
furniture (r = -.201, p < .01) suggest that females are likely to have a lower perception of the
functionality of equipment and furniture. A significant correlation with a small effect size (Field,
2013) exists between the control variable organizational tenure and the perception of the signs (r
= .144, p < .05). This positive correlation suggests that people who work longer for an organization
have a more positive perception of the signs.
CHAPTER 4 – RESULTS
35
Table 5
Means, standard deviations and correlations of variables
Mean Std. Dev.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 Layout 4.16 0.49
2 Space 3.48 0.57 .226**
3 Ambient 3.05 0.61 .205** .481**
4 Functionality 3.51 0.72 .327** .449** .479**
5 Cleanliness 4.05 0.47 .278** .276** .268** .379**
6 Signs 3.16 0.86 .164* .329** .302** .219** .175*
7 Satisfaction 4.12 0.47 .301** .260** .231** .304** .256** .209**
8 Commitment 3.32 0.55 0.10 .226** 0.13 .228** .177* 0.02 .434**
9 Intention 2.06 0.89 -0.04 -.184* 0.00 -0.02 0.01 -0.01 -.401** -.457**
10 Gender 1.48 0.51 0.01 -0.01 -.263** -.201** -0.10 -0.02 -0.08 -0.04 0.01
11 Age 3.98 1.06 -0.04 -0.12 0.07 0.00 -0.09 0.06 0.01 0.04 0.00 0.03
12 Education 3.85 0.73 0.09 -0.01 0.11 0.11 0.02 0.02 0.04 0.03 -0.12 -.258** -0.10
13 Hours 4.73 0.78 0.03 -0.08 -0.06 -0.03 0.02 0.02 0.08 0.02 -0.06 -.478** -0.06 .263**
14 Tenure 3.52 1.88 0.02 -0.03 -0.01 -0.06 -0.03 .144* 0.09 0.13 -0.05 .240** .596** -.247** -.193**
Notes: N=192. ** Correlation significant at the 0.01 level (2-tailed). * Correlation significant at the 0.05 level (2-tailed).
CHAPTER 4 – RESULTS
36
Figure 4
Hypothesized model
CHAPTER 4 – RESULTS
37
4.4 EXPLORATORY FACTOR ANALYSIS
The hypothesized model, as can be seen in Figure 4, consist of nine latent (unobserved) variables.
These variables are labelled as Layout (Lay), Space (Spa), Ambient conditions (Amb), Functionality
of equipment and furniture (Fun), Cleanliness (Cle), Signs (Sig), Job Satisfaction (Sat), Affective
Commitment (Com), and Turnover Intention (Int). The first six variables are exogenous
(independent), and the last three are endogenous (dependent). The model consists of four
constructs, namely the perception of the work environment, job satisfaction, affective commitment
and intention to leave the organization. These four constructs were based on previous research to
enhance validity. Principal component analysis (PCA) is conducted with orthogonal rotations
(varimax) on the 16 items for job satisfaction, affective commitment, and turnover intention, and for
the 29 items measuring the perception of the work environment (Appendix 4, Table 24 and 25).
The Kaiser-Meyer-Olkin measure verifies the sampling adequacy for the analysis, KMO = .80
(‘good/great’ according to Field, 2013). Bartlett’s test of sphericity χ² (595) = 4731.38, p < .001,
indicated that correlations between items is sufficiently large for PCA (Table 6).
Table 6
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
0.80
Bartlett’s Test of Sphericity
Approx. Chi-Square 4731.38 df 595 Sig. 0.00
The maximum likelihood factor analysis with a cut-off point of .50 and the Kaiser’s criterion of
eigenvalues greater than 1 (see Field, 2013) yielded a ten-factor solution as the best fit for the data,
accounting for 77.89% of the variance. Some items were excluded pairwise to purify the scales.
Items were excluded if their loadings were too low or if they were not loading on a single specific
factor (Koufteros, 1999). The results of this EFA are presented in Table 7 and 8.
The original factor ‘ambient conditions’ was split in two different factors: ‘indoor air quality’ and ‘air
temperature’ loaded on one factor, which can be called ‘indoor air’, with an eigenvalue of 1.12,
accounting for 3,38% of the variance. The item ‘scent’ was deleted to purify the newly created
factor. Furthermore, the items ‘artificial lighting’ and ‘natural lighting’ loaded on another factor with
an eigenvalue of 1.00, accounting for 3.01% of the variance. This factor is labelled as ‘lighting’. The
hypothesized factor ‘functionality of equipment and furniture’ was also split into two factors. The
items ‘availability of equipment’, ‘advancement of equipment’, and ‘quality of equipment’ loaded on
one factor with an eigenvalue of 1.48, accounting for 4.50% of the variance. This factor can be
labelled as ‘equipment’. The items ‘comfort of furniture’, ‘quality of furniture’, and ‘arrangement of
furniture’ loaded on another factor with an eigenvalue of 1.83, accounting for 5.53% of the variance.
This factor is labelled as ‘furniture’. The two items, ‘privacy at workspace’ and ‘not too close to
others’, that were supposed to measure the perception of the space also loaded on this newly
created factor ‘furniture’. However, after inspection of both items, it was decided that both did not
measure the same underlying factor as the three previously mentioned items. Thus, these two
items were excluded from further analysis.
CHAPTER 4 – RESULTS
38
Table 7
Factor Analysis: Measurement Model
Factor
Dimension Items
1 2 3 4 5 6 7 8 9 10
Pleasantness of work
0.579
Job
satisfaction
Enthusiasm
0.844
Satisfaction with work
0.846
Feel part of the ‘family’
0.747
Affective
commitment
Emotional attachment
0.847
Personal meaning
0.717
Feelings of attachment
0.667
Plan to leave
0.943
Intention to
leave the
organization
Feel to leave
0.902
Will to leave
0.942
Reach reception
0.775
Layout
Reach meeting rooms
0.796
Reach toilets
0.763
Reach canteen
0.780
Move through building
0.848
Air temperature
0.861
Air quality Air quality
0.869
Daylight
0.880
Lighting Artificial light
0.868
Availability of equipment
0.831
Equipment Advancement
0.765
Quality of equipment
0.747
Comfort of furniture
0.820
Furniture
Quality of furniture
0.832
Arrangement of furniture
0.772
Canteen
0.842
Cleanliness
Stair- and hallways
0.879
Overall
0.783
Quantity 0.954
Signs
Visibility 0.964
Understandability 0.943
Usefulness
0.966
Extraction Method: Principal Component Analysis. 10 components extracted.
CHAPTER 4 – RESULTS
39
Table 8
Total Variance Explained: Measurement Model
4.5 CONFIRMATORY FACTOR ANALYSIS
A measurement model was estimated, using the maximum likelihood estimation method. This
estimation was done to refine all measures for the structural model. This measurement model
consists of the ten factors and 32 items, which resulted from the EFA (Figure 5). The results of this
factor analysis showed excellent fit to the data (χ2 = 545,17 df = 419 p < .001, χ2 /df = 1,301, root-
mean-square error of approximation [RMSEA] = .040, comparative fit index [CFI] = .971, goodness
of fit index [GFI] = .989, standardized root-mean-square residual [SRMR] = .048, Tucker-Lewis
Index [TLI] = .965). All of these fit measures satisfy the fit thresholds as defined by Schreiber and
colleagues (2006) as can be seen in Table 9.
Table 9
Fit measures
Fit measure The general rule for acceptable data (Schreiber et al., 2006) Outcome CFA
χ2 /df ≤ 2 1,301 RMSEA < .06 .040 SRMR ≤ .08 .048 TLI ≥ .95 .965 GFI ≥ .95 .989 CFI ≥ .95 .971
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Component Total
% of
Variance
Cumul
ative
%
Total
% of
Variance
Cumul
ative
%
Total
% of
Variance
Cumul
ative
%
1 7.14 21.65 21.65
7.14 21.65 21.65
3.85 11.68 11.68
2 4.06 12.31 33.96
4.06 12.31 33.96
3.43 10.38 22.06
3 3.22 9.74 43.70
3.22 9.74 43.70
2.87 8.70 30.76
4 2.54 7.69 51.39
2.54 7.69 51.39
2.84 8.62 39.38
5 2.02 6.11 57.50
2.02 6.11 57.50
2.54 7.69 47.07
6 1.83 5.53 63.03
1.83 5.53 63.03
2.45 7.41 54.48
7 1.48 4.50 67.53
1.48 4.50 67.53
2.20 6.66 61.14
8 1.31 3.97 71.50
1.31 3.97 71.50
2.07 6.27 67.41
9 1.12 3.38 74.88
1.12 3.38 74.88
1.78 5.41 72.82
10 1.00 3.01 77.89
1.00 3.01 77.89
1.67 5.07 77.89
11 0.74 2.25 80.14
Extraction Method: Principal Component Analysis
CHAPTER 4 – RESULTS
40
Figure 5
Measurement model
CHAPTER 4 – RESULTS
41
For the included factors, the Cronbach’s alpha estimates were between .776 and .979 and can be
considered as reliable (Table 10). A factor is considered as reliable as there Cronbach’s Alpha
score is above .70 (Nunnally, 1978).
Furthermore, the validity of the construct was tested using the factors loadings within the
constructs, average variance extracted (AVE) and the correlation between the constructs. The
outcomes of these tests can be found in Table 10. As can be seen in this table, all standardized
factors loadings were reasonably high, ranging from .579 to .966. These loadings indicate that the
constructs have convergent validity (Anderson & Gerbing, 1984). Additionally, AVE for every factor
exceeds the cut-off of .50, as suggested by Hair et al. (1998). Moreover, all AVE values were higher
than the squared correlation between constructs (Appendix 4, Table 26 and 27), indicating
adequate discriminant validity for all factors.
Regarding the construct validity, the composite reliability (CR) was calculated for each construct.
The CR scores for each construct exceeded the desired threshold of .70 (Bagozzi and Yi, 1988).
Therefore, construct validity is assured.
Table 10
Validity and reliability measures
Factor Item code
Item total
correlation
Standardized factor
loadings AVE CR
Cronbach's
Alpha
Layout
Lay1 0.647 0.775 0.629 0.868 0.865
Lay2 0.691 0.796
Lay3 0.675 0.763
Lay4 0.674 0.780
Lay5 0.805 0.848
Indoor Air Amb1 0.731 0.861 0.748 0.809 0.843
Amb2 0.731 0.869
Equipment
Fun1 0.586 0.831 0.611 0.776 0.806
Fun2 0.729 0.765
Fun3 0.696 0.747
Lighting Amb5 0.636 0.880 0.764 0.774 0.776
Amb6 0.636 0.868
Furniture
Fun4 0.822 0.820 0.654 0.831 0.866
Fun5 0.844 0.832
Fun6 0.594 0.772
Cleanliness
Cle2 0.700 0.842 0.698 0.836 0.841
Cle3 0.779 0.879
Cle4 0.666 0.783
Signs
Sig1 0.936 0.954 0.916 0.977 0.979
Sig2 0.965 0.964
Sig3 0.925 0.944
Sig4 0.961 0.966
Job
satisfaction
Sat1 0.499 0.579 0.588 0.752 0.794
Sat4 0.679 0.844
Sat5 0.760 0.846
CHAPTER 4 – RESULTS
42
4.6 STRUCTURAL EQUATION MODEL
Structural equation modelling was conducted using the maximum likelihood estimation method to
assess the proposed conceptual model. The outcomes of this test revealed that the model fits the
data reasonably well (χ2 = 532,69 df = 425, p < .001, χ2 /df = 1.253, RMSEA = .036, CFI = .975,
GFI = .990, SRMR = .036, TLI = .971). All of these fit measures satisfy the fit thresholds as defined
by Schreiber and colleagues (2006) as can be seen in Table 11.
Table 11
Fit measures structural model
Fit measure
The general rule for acceptable data
(Schreiber et al., 2006)
Outcome CFA
χ2 /df ≤ 2 1,253 RMSEA < .06 .036 SRMR ≤ .08 .052 TLI ≥ .95 .971 GFI ≥ .95 .990 CFI ≥ .95 .975
This proposed model was compared with an alternative model. In this alternative model, the direct
relationships between the factors concerning the work environment and turnover intention were
deleted. The results showed that this model also fits the data reasonably well (χ2 = 545,66 df =
432, p < .001, χ2 /df = 1.263, RMSEA = .037, CFI = .974, GFI = .990, SRMR = .058, TLI = .970).
This model did not show any significant differences with the hypothesized structural model ((∆χ2 =
12.77, ∆df = 7, p > .05). Thus, deleting these direct paths from the six factors of the work
environment to employee turnover intention did not significantly change the model fit. Therefore,
the proposed model was kept for further analyses.
An SEM analysis was conduct based on the proposed model to test the hypotheses. The parameter
estimates between the variables in the model were estimated, and step by step, all insignificant
paths (p>.05) were eliminated. During each step, the least significant path was omitted. Eventually,
this resulted in the deletion of 11 paths. The model fit of this most parsimonious model was: χ2 =
565,67 df = 436, p < .001, χ2 /df = 1.297, RMSEA = .039, CFI = .970, GFI = .990, SRMR = .065,
TLI = .966. Figure 6 shows this parsimonious model with all the included significant standardized
regression coefficients.
Affective
commitment
Com5 0.565 0.747 0.559 0.757 0.779
Com6 0.654 0.847
Com7 0.603 0.717
Com8 0.524 0.667
Turnover
intention
Int1 0.940 0.943 0.863 0.949 0.960
Int2 0.898 0.902
Int3 0.917 0.942
CHAPTER 4 – RESULTS
43
Figure 6
Results Structural Equation Model
Note: the figure shows a significant positive relation between the perception of Equipment and Intention to Leave. This relation contradicts with the
hypothesized negative relation between both constructs.
** p < .01
CHAPTER 4 – RESULTS
44
Table 12
Percentage of variance explained in structural model
Variable R2
Turnover intention .246 Job Satisfaction .173 Affective Commitment .104
Overall, the model portrayed in Figure 6 explains 24.6 percent in variance in employee turnover
intention, 17.3 percent of variance in job satisfaction, and 10.4 percent of variance in affective
commitment (Table 12).
4.7 HYPOTHESES TESTING
The formulated hypotheses were tested based on the proposed structural model (Figure 5, p.
40). Some initial hypotheses needed to be deleted or reformulated and split after the factor
analysis. Hypotheses 2, 10a and 10b, which hypothesized that the perception of space was
related to turnover intention (2) and that this relation is mediated by job satisfaction (10a) and
affective commitment (10b), were deleted. Because the factor perception of space was not
included as a factor in the proposed structural model.
Furthermore, hypotheses 3, 11a and 11b, which were related to the perception of ambient
conditions, were split into six new hypotheses (3a, 3b, 11a1, 11a2, 11b1 and 11b2). Hypotheses
3a, 11a1 and 11b1 hypothesize that there is a negative relation between the perception of the
indoor air and turnover intention (3a), and that this relation is mediated by job satisfaction (11a1)
and affective commitment (11b1). Whereas, hypothesis 3b, 11a2 and 11b2 hypothesize that
there is a relation between the perceived lighting and turnover intention (3b), and that this
relation is mediated by job satisfaction (11a2) and affective commitment (11b2).
Similarly, the three hypotheses (5, 13a and 13b) related to the perceived functionality of
equipment and furniture were split into six new hypotheses (5a, 5b, 13a1, 13a2, 13b1 and 13b2).
Hypotheses 5a, 13a1 and 13b1 hypothesize that there is a negative relation between the
perception of equipment and turnover intention (5a), and that this relation is mediated by job
satisfaction (13a1) and affective commitment (13b1). Whereas, hypothesis 5b, 13a2 and 13b2
hypothesize that there is a relation between the perception of furniture and turnover intention
(5b), and that this relation is mediated by job satisfaction (13a2) and affective commitment
(13b2).
The parameter estimates, which were assessed using the maximum likelihood estimation
method, can be found in Table 13 and 14. These tables also indicate whether the associated
hypotheses are supported. The results of the structural equation model, with the significant
standardized path coefficients, are presented in Figure 6 on the previous page.
CHAPTER 4 – RESULTS
45
Table 13
Results hypotheses 1-6
Hypothesis Hypothesized path z p Result
1 Perception of layout
→ Turnover intention .025 .257 .797
Not supported
2 Perception of space
→ Turnover intention - - - -
3a Perception of indoor air
→ Turnover intention (.011) (.096) .924
Not supported
3b Perception of Lighting
→ Turnover intention .071 .771 .441
Not supported
4 Perception of cleanliness
→ Turnover intention .150 1.754 .079
Not supported
5a Perception of equipment
→ Turnover intention .258 2.718 .007
Not supported
5b Perception of furniture
→ Turnover intention (.091) (.859) .390
Not supported
6 Perception of signs
→ Affective Commitment .000 .002 .999
Not supported
Table 14
Results hypothesis 7 and 8
Hypothesis Hypothesized path z p Result
7 Job satisfaction
→ Turnover intention (.409) (4.605) .000 Supported
8 Affective commitment
→ Intention to Leave (.303) (3.207) .001 Supported
Hypothesis 7 was supported, indicating that employee turnover intention was a negative
function of job satisfaction. The relationship between job satisfaction and turnover intention was
negative and significant ( = -.409, p < .01). Additionally, hypothesis 8 was supported, indicating
that turnover intention was a negative function of affective commitment. There is a significant
negative relationship between affective commitment and turnover intention ( = -.303, p < .01)
4.7.1 Mediation analysis
A mediation analysis is conducted to test the formulated mediation hypotheses. This analysis
tests whether job satisfaction and/or affective commitment mediates the relationship between
the perception of the different defined elements of the work environment and employee turnover
intention. As the structural equation model in Figure 6 (p.43) shows, there are two perceived
elements of the work environment that have a significant relationship with one or more of the
potential mediators. The perception of equipment is significantly related to both job satisfaction
( = .301, p < .01) and affective commitment ( = .398, p < .05). Additionally, the perception of
the layout shows a significant relation to job satisfaction ( = .274, p < .01). These are the paths
labelled with a1, a2 and a3 in Table 15, 16 and 17. These paths need to be significant in order
to have a potential mediating effect. All the other perceived elements of the work environment
are excluded from this mediation analysis, whereas they did not have a significant relationship
with one or more of the mediators (Appendix 4, Table 28 and 29).
CHAPTER 4 – RESULTS
46
Table 15
Job satisfaction as mediator between perception of the layout and turnover intention
Relation Label se z p CI. Lower
CI. Upper
Layout →
Job Satisfaction a1 .274 .086 3.190 .001 .124 .467
Job Satisfaction →
Turnover intention b1 (1.167) .230 (5.083) .000 (1.679) (.763)
Layout →
Turnover intention c1 .251 .189 1.328 .184 (.089) .624
Layout →
Job Satisfaction →
Turnover intention
a1*b1 (.320) .101 (3.174) .002 (.549) (.151)
Layout +
Job Satisfaction →
Turnover intention
Total (.069) .177 (.390) .697 (.416) .282
Table 16
Job satisfaction as mediator between perception of equipment and turnover intention
Relation Label se z p CI. Lower
CI. Upper
Equipment →
Job satisfaction a2 .301 .109 2.756 .006 .125 .562
Job satisfaction →
Intention b2 (1.218) .216 (5.650) .000 (1.680) (.827)
Equipment →
Turnover intention c2 .426 .223 1.912 .056 .076 .967
Equipment →
Job satisfaction →
Turnover intention
a2*b2 (.367) .140 (2.625) .009 (.725) (.155)
Equipment +
Job satisfaction →
Turnover intention
Total .059 .211 .282 .778 (.317) .492
Table 17
Affective commitment as mediator between perception of equipment and turnover intention
Relation Label se z p CI. Lower
CI. Upper
Equipment →
Affective commitment a3 .398 .160 2.480 .013 .113 .742
Affective commitment
→ Turnover intention b3 (.633) .145 (4.359) .000 (.918) (.381)
Equipment →
Turnover intention c3 .293 .218 1.342 .180 (.066) .779
Equipment →
Affective commitment
→ Turnover intention
a3*b3 (.252) .115 (2.193) .028 (.524) (.073)
Equipment + Affective commitment
→ Turnover intention
Total .041 .214 .191 .848 (.335) .499
CHAPTER 4 – RESULTS
47
Layout did not show a significant direct relation to turnover intention ( = .189, p = .184). On
the other hand, equipment did show a significant direct relation to turnover intention ( = .426,
p < .01). This direct path is labelled as ‘c’ in the Tables 15 and 17. This direct effect does not
necessarily have to be significant to have a mediation effect. The third step in mediation
analysis consists of the combined effect of the independent variable and mediating variable on
the dependent variable. This resulted in a significant combined effect of layout and job
satisfaction on turnover intention ( = -.320, p < .01). This effect is labelled as a1*b1 in Table
15. Similarly, the combined effect of equipment and affective commitment on turnover intention,
which is labelled as a2*b2, is significant ( = -.320, p < .01). Furthermore, a significant combined
effect of equipment and affective commitment on turnover intention was found ( = -.252, p <
.05). As can be seen in Table 17, this path is labelled a3*b3.
To summarize, the effect of perception of equipment on employee turnover intention was
completely mediated via both job satisfaction (hypothesis 9a) and affective commitment
(hypothesis 13a1). As can be seen in Table 18 and 19, the regression coefficient between both
mediators and employee turnover intention was significant. The indirect effect via job
satisfaction was -.367 and the indirect via affective commitment was -.252. The significance of
this indirect effect was tested using bootstrapping procedures. Unstandardized indirect effects
were computed for each 1.000 bootstrapped samples. The 95% confidence interval was
computed by determining the indirect effects at the 2.5th and 97.5th percentiles. This resulted
for the indirect effect of perception of equipment on turnover intention, via job satisfaction, in a
confidence interval (ci) that ranged from -.725 and .155. This indirect effect of = -.367 was
significant (p < .01). Similarly, the indirect effect of perception of equipment on turnover intention
via affective commitment was found to be significant ( = -.252, p < 0.05). Finally, the perception
of the layout had a significant indirect effect on turnover intention via the mediating variable job
satisfaction ( = -.320, p < 0.01). This is also a complete mediation, because there is no
significant relation between the perception of the layout and turnover intention, but there is a
significant indirect effect via job satisfaction. This result supports hypothesis 13b1. These
findings are summarized in Table 18 and 19. These tables also indicate whether the associated
hypotheses are supported.
Table 18
Job satisfaction as mediator: hypotheses 9a, 10a, 11a1, 11a2 12a, 13a1, 13a2 and 14a
Hypothesis Hypothesized path z p Result
9a Perception of layout + Job satisfaction
→ Turnover intention (.320) (3.174) .002 Supported
10a Perception of space + Job satisfaction
→ Turnover intention - - - -
11a1 Perception of indoor air + Job satisfaction
→ Turnover intention (.066) (1.493) .136
Not supported
11a2 Perception of Lighting + Job satisfaction
→ Turnover intention (.066) (1.203) .229
Not supported
12a Perception of cleanliness + Job satisfaction
→ Turnover intention (.167) (1.860) .063
Not supported
13a1 Perception of equipment + Job satisfaction
→ Turnover intention (.367) (2.625) .009 Supported
13a2 Perception of furniture + Job satisfaction
(.078) (1.851) .064 Not supported
CHAPTER 4 – RESULTS
48
→ Turnover intention
14a Perception of signs + Job satisfaction
→ Affective Commitment (.035) (1.134) .257
Not supported
Table 19
Affective commitment as mediator: hypotheses 9b, 10b, 11b1, 11b2 12b, 13b1, 13b2 and 14b
Hypothesis Hypothesized path z p Result
9b Perception of layout + Affective commitment
→ Turnover intention (.023) (.399) .690
Not supported
10b Perception of space + Affective commitment
→ Turnover intention - - - -
11b1 Perception of indoor air + Affective commitment
→ Turnover intention .024 .722 .470
Not supported
11b2 Perception of Lighting + Affective commitment
→ Turnover intention .013 .271 .786
Not supported
12b Perception of cleanliness + Affective commitment
→ Turnover intention (.080) (1.088) .272
Not supported
13b1 Perception of equipment + Affective commitment
→ Turnover intention (.252) (2.135) .033 Supported
13b2 Perception of furniture + Affective commitment
→ Turnover intention (.035) (.964) .335
Not supported
14b Perception of signs + Affective commitment
→ Turnover intention .023 .856 .392
Not supported
Besides hypothesis 7 and 8, the three other hypotheses that were supported are hypothesis
9a, 13a1 and 13b1. Hypothesis 7 concerned the mediating effect of job satisfaction in the
relationship between the perception of layout and turnover intention. The mediation analysis
did confirm this hypothesized mediating effect of job satisfaction ( = -.320, p < .01). Similarly,
hypothesis 13a1 is confirmed: job satisfaction mediates the relationship between perception of
the equipment and turnover intention ( = -.367, p < .01). Finally, affective commitment
mediates the relationship between the perception of the equipment and turnover intention ( =
-.252, p < .01). Based on this finding, hypothesis 13b1 is confirmed.
The other hypotheses were all rejected. No significant mediation effects were found between
the perception of the other defined elements of the work environment and turnover intention.
The results did show a significant relation between the perceived functionality of the equipment
and turnover intention ( = .208, p < .01), however, this relation was hypothesized (5a) to be
negative but turned out to be positive. Therefore, this hypothesis is not supported.
49
5
5 CONCLUSION & DISCUSSION
This chapter starts with the conclusion, whereafter in the second part the results are discussed.
In this discussion, the findings are discussed and are compared with the literature. Additionally,
I will reflect on some notable results. Thereafter, the limitations of this study are presented.
Finally, some recommendations and implications are given.
5.1 CONCLUSION
This study aims to shed a light on the relationship between the perception of elements of the
work environment and employee turnover intention to provide theoretical insights and give
recommendations. To get a clear and structured solution to this objective, seven sub-research
questions are formulated, which are answered in the theoretical and empirical parts of this
study. Using the findings presented in the theoretical framework and the results of the empirical
research, the next paragraph answers the main research question. The main research question
is:
To what extent is the perception of elements of the work environment related to
employee turnover intention?
To answer this question, this study looked into the direct and indirect effects of the perception
of different elements of the work environment on employee turnover intention. Based on the
results, there are no direct effects of the perception of the different elements of the work
environment and turnover intention. Hence, no support was found for the hypotheses 1-6.
Thus, it can be concluded that employee turnover intention is not directly related to the
perception of the defined elements of the work environment, including the perception of the
layout, indoor air, lighting, cleanliness, equipment, furniture, and signs.
In line with previous studies, and the related hypotheses in this study, job satisfaction fully
mediates the relationship between the perception of the layout and turnover intention ( = -
.320, p < .01). This supports hypothesis 9a. Subsequently, job satisfaction also fully mediates
the relationship between the perception of the equipment and turnover intention ( = -.367, p <
.01). Thereby supporting hypothesis 13a1. Furthermore, hypothesis 13b1 is supported. The
relationship between the perception of the equipment and turnover intention is found to be
mediated by employee affective commitment ( = -.252, p < .01).
These findings suggest that the perception of elements of the work environment does not have
any direct relationship to employee turnover intention. Or in other words, altering the elements
of the work environment that are included in this study will not likely result in other levels of
turnover intention. However, the perception of the equipment and the layout do have a positive
effect on employee job satisfaction, and higher levels of job satisfaction results in a lower
turnover intention. A positive perception of the equipment will also result in higher levels of
affective commitment, which results in a lower turnover intention. Therefore, it would be
interesting for organizations to focus on the layout of their offices and the equipment they
provide their employees. A layout that makes it easy for employees to get to the places where
CHAPTER 5 – CONCLUSION & DISCUSSION
50
they need to be, will be perceived as more positive. Additionally, the availability, quality and
advancement of the equipment are important for a more positive perception of the equipment.
In conclusion, this study explored the relationships between the perception of several elements
of the work environment and employee turnover intention. It gained and understanding of this
relationship and added to the literature. Based on the findings, it can be concluded that the
equipment in the office environment plays an important role. A more positive perception of the
equipment results in higher levels of employee job satisfaction and affective commitment. The
results of this study do confirm the previously found negative relationship between both job
satisfaction and turnover intention, and affective commitment and turnover intention. In other
words, higher levels of employee job satisfaction and affective commitment result in a lower
employee turnover intention. Additionally, the results show a mediating effect of job satisfaction
in the relationship between both the perception of the layout and turnover intention, and the
perception of the equipment and turnover intention. These findings suggest that both the
perception of the layout and the equipment have a significant positive effect on job satisfaction
and in turn job satisfaction has a significant negative effect on turnover intention. Additionally,
affective commitment mediates the relationship between the perception of the equipment and
turnover intention. Overall, the equipment can be considered as a very important element in
the work environment because of its positive effects on both employee job satisfaction and
affective commitment. Resulting in lower employee turnover intention via these two mediators.
5.2 DISCUSSION
The purpose of this discussion is to evaluate the research process and the results of this study
in light of existing literature. Additionally, some personal findings and ideas are put forward. The
main objectives of this explorative study were to provide empirical insights into the relationship
between the perception of elements of the work environment and employee turnover intention
and to give recommendations on the design of elements of the work environment to decrease
employee turnover intention.
To reach these objectives, this study investigated the relationships between the perception of
several elements of the work environment and job satisfaction, affective commitment, and
turnover intention. More specifically, based on the theoretical part it was hypothesized that a
more positive perception of the layout, space, ambient conditions, cleanliness, signs, or the
functionality of the equipment and furniture, result in a lower turnover intention. Additionally, it
was expected that this relationship between the perception of elements of the work environment
and turnover intention was mediated by job satisfaction and affective commitment. For
example, employees that perceive their equipment as more positive will have higher job
satisfaction, resulting in a lower turnover intention.
However, the results show that the effects of the perception of the elements of the work
environment on employee turnover intention are small and insignificant. Based on the stimuli-
organism-response model of Mehrabian and Russell (1974) it was expected that the perceptible
elements of the environment can function as a stimulus, resulting in a behavioural response via
an internal emotional response, including certain intentions. That intention determines
behaviour is explained by the Theory of reasoned action (Ajzen & Madden, 1986). However,
none of the perceived elements showed to have a significant effect on turnover intention in this
study. This might be caused by the fact that this study focuses on the perception of individual
elements of the work environment instead of the work environment as a whole. As Bitner (1992)
explains in her study, it is the holistic perception of the environment that functions as the stimuli
that result in an internal and behavioural response. Several studies found that the perception
of the work environment affects employee turnover intention (e.g., Santoni & Harahap, 2018;
Kurniawaty, Ramly & Ramlawati, 2019). These studies combined the perception of multiple
elements of the work environment in one construct and some studies even included non-
CHAPTER 5 – CONCLUSION & DISCUSSION
51
physical elements of the work environment in their work environment construct. These studies
showed that the combined perception of multiple elements in one factor affects employee
turnover intention. As explained, this explorative study tested for the effect of individual
elements, to get to the root causes of turnover intention caused by the physical work
environment, based on the stimuli-organism-response model (Mehrabian & Russell, 1974). But
based on the results, it can be concluded that none of the elements included in this studied has
a significant direct effect on turnover intention.
A contribution of this study is that it confirms the previously found negative relationships
between both job satisfaction and turnover intention, and affective commitment and turnover
intention. In other words, employees who have higher job satisfaction or affective commitment
will have a lower turnover intention. These findings are in line with the findings of Aydogdu and
Asikgil (2011), and once again emphasize the importance of both job satisfaction and affective
commitment in relationship to employee turnover intention.
Other notable findings are the mediating effects of both job satisfaction and affective
commitment in the relationship between the perception of the equipment and turnover intention.
Additionally, job satisfaction mediates the relationship between the perception of the layout and
employee turnover intention. These findings tie well with previous studies wherein the
perception of elements of the work environment has been related to employee job satisfaction
and affective commitment (e.g., McGuire & McLaren, 2009; Leder et al., 2016) and the
expected relationship between these two variables and turnover intention (Aydogdu & Asikgil,
2011). However, when comparing our results to those of older studies, it must be pointed out
that in older studies there was not tested for mediating effects. Both described relationships
were found in separate studies. This study combines both previously found relationships and
the results provide evidence for these hypothesized mediating effects.
Nevertheless, mediating effects were only found in these three relationships. The perception of
the other elements of the work environment did not have an indirect effect via one of the two
included mediating variables: job satisfaction and affective commitment. Although the
employees are less likely to leave the organization when they have higher levels of job
satisfaction and affective commitment. It could therefore be argued that there are other factors
than the physical work environment that result in higher levels of job satisfaction and affective
commitment. Examples that are given in other studies are organizational culture (Lund, 2003),
salary (Parvin & Kabir, 2011) and managerial style (Lok & Crawford, 2004). Further research
should investigate if any other factors function as a mediator in the relationship between the
perception of the work environment and turnover intention. One could think of other emotional
internal organisms as a response to the environmental stimuli as mediating variables. One
could speculate that, for example, employee wellbeing or organizational identification can
mediate the relationship between the perception of elements of the work environment and
employee turnover intention.
Another remarkable finding is that perception of the equipment is positively related to turnover
intention. This finding suggests that when employees perceive the equipment as more positive,
they have a higher turnover intention. Based on the literature framework, it was hypothesized
that a more positive perception of the equipment would result in a lower turnover intention
(Kurniawaty, Ramly & Ramlawati, 2019). However, the results show exactly the opposite. A
potential explanation for this finding could be that employees who perceive the equipment as
more positive might feel that they lose autonomy in their job. Whereas a positive evaluation of
the equipment indicates that there is a diverse range of advanced equipment that is of high
quality. Employees might get the feeling that the equipment is starting to do their work, resulting
in a loss of autonomy. Brey argued in his study in 1999 that new technologies in the work
environment can threaten employee autonomy. This feeling of loss of autonomy has been
CHAPTER 5 – CONCLUSION & DISCUSSION
52
linked to turnover intention in several studies (e.g., Kim & Stoner, 2008; Dysvik & Kuvaas, 2013;
Galletta, Portoghese & Battistelli, 2011). This study did not include feeling of autonomy as a
variable. But for future studies, this would be an interesting variable to include and see whether
similar results are found.
On the other hand, this study also showed the importance of the availability, advancement and
quality of the equipment. The perception of the equipment showed to be positively related to
both employee job satisfaction and affective commitment. This is in line with the findings of
previous studies. As van Meel (2000) and Vischer (2008) explain in their study, the
developments in information technology, resulting in better equipment, allowed employees to
work anytime and anywhere. Equipment that facilitates performance and goal accomplishment
will be perceived as more positive. Employees can feel supported in their work by the
functionality of their equipment (Bitner, 1992). These findings suggest a fine line considering
the perception of the equipment. Equipment that is perceived as positive results in higher levels
of job satisfaction and affective commitment, which will lead to lower turnover intention. But
equipment that is perceived as positive is probably taking away job autonomy, resulting in
higher turnover intention. Future studies should confirm whether job autonomy mediates this
relationship between the perception of the equipment and turnover intention.
This suggestion of adding job autonomy to the model is in line with another outcome that
deserves some attention. The outcome of concern is the percentage of variance explained in
turnover intention by the structural model (around 25 percent). This score suggests that other
factors affect the amount of turnover intention that the employees reported. As was mentioned
before, several studies investigated the antecedents of turnover intention. These studies found
how several demographic aspects such as age, tenure, gender and educational level influence
employee turnover intention (Arnold & Feldman, 1982). But besides the demographic factors,
which are included in this study, researchers found several other factors that influence
employee turnover intention. Examples of these factors are the organizational structure and
climate (Hong & Kaur, 2008), the reward system (Jauhar, Ting, Rahim & Fareen, 2017), the
managerial style (Dixon & Hart, 2010) or the human resource practices (Garcia-Chas, Neira-
Fontela & Castro-Casal, 2014). Based on the study of Das and Baruah (2013), job satisfaction
and affective commitment were considered as the most important factors influencing turnover
intention and therefore included in this study. But as the total variance explained suggests,
there are other factors that explain the variation in turnover intention. This study did not include
any other factors, whereas this would result in many constructs about which data needed to be
collected with the questionnaire. A selection was made to keep the length of the questionnaire
short to minimize the response bias caused by boredom and monotony (Schmitt, Ford & Stults,
1986). This selection included the perceptible elements of the work environment and the
mediating variables that were considered the most important based on the literature framework.
Another interesting note to make is that this study again did not find any significant relationship
between the perception of the signs and either one of the outcome variables. Previous studies
already mentioned that the effects of signs are minimal. Most of the studies focus on the other
two dimensions of Bitner (1992). Signs were included in this study as an element, despite these
suggestions of the limited effect, because it is considered as an important part of the work
environment according to Bitner (1992). Once again, no significant effect of the perception of
signs on emotional- and behavioural outcome variables was found. Based on this finding man
can question the importance of signs in a work environment because it remains unclear to what
extent it affects employees.
Finally, it is interesting to note that none of the included control variables had a significant
relationship with turnover intention. Based on previous studies, it was expected that females
would score higher on turnover intention than males. This expectation was based on the meta-
CHAPTER 5 – CONCLUSION & DISCUSSION
53
review of Arnold and Feldman (1982). The results of this study however showed that there was
no difference in turnover intention between males and females. Both groups were well
represented in the sample. The review of Arnold and Feldman might be based on outdated
results. Future studies should point out whether the difference in turnover intention between
males and females have diminished. Additionally, age, educational level and organizational
tenure did not have any significant effect on turnover intention. Concerning the educational
level, the current sample might not have a sufficient spread. Most of the employees included in
the sample have the same educational level. Additionally, it could be that the control variables
age and organizational tenure are of less importance in the financial sector as a predictor of
turnover intention. But the insignificance of these control variables does not necessarily impact
the conclusions based the test for the relationship between the perception of elements of the
work environment and employee turnover intention.
5.3 LIMITATIONS
A first limitation of this study is that there is not tested if there are any differences in perception
between the four different offices that participated in this study. However, most of the
employees (80.4%) works in an open-plan type of office, in which most of the environmental
elements will be, to a certain extent, the same.
Another potential limitation could be that personality traits of the respondents are not included
in the analysis. As the study of Jeswani and Dave (2012) showed, some personality traits can
have a significant impact on the intention to leave the organization. Similar results were found
by Zimmerman (2008). This effect is not controlled for in this study and might be interesting to
include in further study. However, the control variables that were included in the study did not
show any significant relationship with the dependent variable, although the fact that this was
expected. Including personality traits as control variable does not necessarily have to result in
a significant effect.
Next to that, the result might be biased to some extent due to the fact that the respondents
have given the socially desired answers. Especially, for the questions about their intention to
leave, but also, about their commitment and satisfaction. Various steps have been taken to
minimize this bias. Anonymous processing of the results was promised to all respondents at
the start of the questionnaire. Additionally, the more personal demographic questions were
asked at the end of the questionnaire, after the respondents had already filled in the questions
about their intention to leave the organization.
A fourth potential limitation might be that a single questionnaire containing self-reported
measures is used to gather the data. This might result in a distortion in the tested relationship
among the constructs by the effect of common method bias (Spector et al., 2019). Harman’s
single factor score was conducted to test whether common method bias was a concern in this
study. In this test, all items that measure the latent variables are loaded on a single factor.
Common method bias does not affect the data if the total explained variance of this one factor
is less than 50% (Podsakoff, MacKenzie, Podsakoff, 2012). The results of this test show that
the items measuring the latent variables in this study explain 19.45% of the total variance.
Therefore, common method bias is not a concern in this study. However, future studies could
also focus on testing the model using other sources of information and focus on more objective
behavioural outcomes, such as actual turnover levels.
Fifth, this study used a questionnaire which was distributed among local offices of firms active
in the financial sector, to circumvent any potential differences between sectors. One limitation
of this method however is that it might impact the generalizability of this study, because it is
uncertain whether the findings hold for other sectors. Future studies could strengthen the
findings in this study by addressing a larger sample. This would result in a more reliable and
stable view. Additionally, to make the findings more generalizable, the sample could exist of
organizations from multiple sectors. This would help to filter out potential extraneous variables
that have an effect on employee turnover intention.
CHAPTER 5 – CONCLUSION & DISCUSSION
54
A final limitation of this study also concerns the generalizability. The sampling method used for
this study was convenience sampling. This resulted in an unequal distribution of the
respondents among educational level and office types. The sample used in this study over-
represents the open-plan type of office and employees with HBO as their highest educational
level. Interesting would be to see whether the results are the same for lower educated
employees or in other office types.
5.4 IMPLICATIONS & RECOMMENDATIONS
Based on the findings of the literature study and the results of the empirical study several
managerial implications and recommendations for further research can be given.
First, as far as the researcher knows, the effects of the perception of individual elements of the
work on employee turnover intention have been barely researched. Most studies researched
the relationship between the perception of the work environment as a whole and employee
turnover intention. These studies also included elements of the non-physical work environment
in their work environment construct. Therefore, this study provides new and additional insights
into the field of research related to the physical work environment. Overall, this study provides
evidence for the relationship between the perception of the equipment and turnover intention
via both mediating variables job satisfaction and affective commitment. In contrast to the study
of Kurniawaty, Ramly and Ramlawati (2019) that measure the effect of the work environment
as a whole on turnover intention and include the perception of the equipment, among others,
in a single factor. Therefore, this study strengthens the body of evidence of the relationship
between perception of the equipment and turnover intention. Similarly, this study provides
evidence that the relationship between the perception of the layout and turnover intention is
completely mediated via job satisfaction. Previous studies did not assess this isolated effect of
the perception of the layout but instead included it in one factor named ‘work environment’
(Santoni & Harahap, 2018). These findings suggest that the equipment and layout play an
important role within the work environment if we look at its relationship to turnover intention.
Managers that want to decrease the turnover intention among their employees by adapting the
physical work environment should therefore focus on both the equipment and layout of their
office environment. Finally, in line with previous findings (see Aydogdu & Asikgil, 2011), this
study provides evidence for the negative relationship between job satisfaction and turnover
intention, and affective commitment and turnover intention. Stressing the importance of high
levels of job satisfaction and affective commitment, whereas it results in lower employee
turnover intention. For managers this means that, concerning the physical work environment,
they should focus on the equipment and the layout because of its positive relationship with job
satisfaction and affective commitment. But as is suggested in the discussion, managers should
be aware that these two elements in combination with job satisfaction and turnover intention
only explain around 25 percent of the variance in turnover intention.
Secondly, an interesting trade-off that should be made when deciding whether changes in the
work environment help lower the turnover intention is between the costs and the benefits.
Organizations are deliberately trying to avoid turnover intentions because of the direct and
indirect costs related to employee turnover (Koh & Goh, 1995). However, changes in the layout
of the work environment can be quite rigorous and costly. If changes in the layout of the current
environment are not possible, it would require a new office to create an environment in which
the layout is perceived as more positive. Questionably remains whether the benefits of these
change outweigh the related costs. Besides the costs of turnover intention, there are a lot of
other factors that should be included in the decisions about whether to redesign the
environment. These can include the effects on performance, productivity, wellbeing, and
amount of sick leave. This cost-benefit analysis would be an interesting topic for further study.
CHAPTER 5 – CONCLUSION & DISCUSSION
55
Furthermore, further research is required to see whether similar results can be found for
employees working in other sectors than the financial sector. Additionally, it would be interesting
to see whether there are any differences between office types. In the literature part a light was
shed on potential differences between office types, but it was outside the scope of this study to
test for these differences in the empirical part of this study.
Additionally, an interesting focus for further study would be to investigate whether there are any
other variables that mediate the relation between the perception of the work environment and
employee turnover intention. This study focused on two other factors that spark turnover
intention, but there are several other factors that might spark turnover intention. Factors that
can be mediators in the relationship between the perception of elements of the work
environment and turnover intention. For example, salary (Nawaz & Pangil, 2016), autonomy
(Kim & Stoner, 2008) or leadership style (Liu et al., 2013).
Finally, interesting to mention is that all the data was collected before the start of the Covid-19
pandemic. So, during the data collection all the participant were still working mostly in their
offices. The whole “working from home” situation was not yet a thing. This new work situation
might impact the perception of employees of the work environment. For example, most
employees will be more critical towards the indoor air quality in their offices and also the
perception of layout might have been changed with all the routing. Time will tell whether these
changes are just temporarily or will remain.
However, in these times of working from home, organizations can break with ways of working
from the past that were suboptimal. Organizations have the time to rethink and redesign their
office environments based on facts. A return to a well-designed office environment can result
in more satisfied and committed employees that are less likely to leave the organization. The
results of this study can be a first step in the right direction; however, I am well aware that there
is still a lot of elements of the work environment that can be further studied. One of the
respondents mentioned in the comment section, she was very dissatisfied with their open-plan
office (“kantoortuin”). The working from home during the Covid-19 pandemic refuelled this
public discussion about the future of the open plan office (e.g., NRC, 2020; AD, 2020).
Additionally, newspapers are reporting increasing complaints about the lack of ergonomic
workstations at home, resulting in more back pains (Trouw, 2020). Right now, we have to decide
for the future of the design of our office environments and relevant knowledge about the effects
of elements of the work environment is crucial for these design decisions. Because one thing
is certain: the physical environment impacts its occupants!
56
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APPENDICES
APPENDIX 1 – Research framework
APPENDICES
69
APPENDIX 2 – Questionnaire
_________________________________________________________________________________
Start of Block: Introductie
Geachte deelnemer,
Graag nodig ik u uit om deel te nemen aan mijn afstudeeronderzoek. Dit onderzoek richt zich op het
effect van uw werkomgeving op uw tevredenheid en intentie om werkzaam te blijven voor uw
werkgever.
Dit onderzoek bestaat uit 4 korte onderdelen en duurt ongeveer 10 minuten. De vragen gaan over uw
primaire werkgever en hebben betrekking op uw eigen werkplek(ken).
Leest u alstublieft de hiernavolgende instructies voordat u de vragenlijst invult:
1. U wordt verzocht de vragen zélf, dus zonder overleg met anderen, in te vullen.
2. De vragenlijst vraagt naar uw mening, u kunt dus nooit een fout antwoord geven!
3. Sta niet te lang stil staan bij de vragen, maar kruis het antwoord aan dat het eerst in u opkomt.
4. Sommige vragen worden nogmaals op een andere manier gesteld om de betrouwbaarheid van
de vragenlijst te verhogen.
5. Het invullen van deze vragenlijst zal ongeveer 10 minuten in beslag nemen.
Anonimiteit
Uw deelname is geheel anoniem en, door de software die ik gebruik, ook niet te herleiden naar
individuen. De geaggregeerde data zal enkel worden gebruikt voor mijn onderzoek. Los van dat de
gegevens anoniem zijn, ga ik vanzelfsprekend vertrouwelijk om met de gegenereerde data.
Toestemmingsverklaring
Met het geven van uw toestemming verklaart u deze persoonsgegevens vrijwillig te hebben verstrekt.
U heeft het recht om de gegeven toestemming ook weer in te trekken. De door u verstrekte
persoonsgegevens zullen uitsluitend voor het doel worden gebruikt waarvoor u deze heeft verstrekt. U
heeft het recht op inzage, verwijdering, correctie of beperking van de verwerking van
persoonsgegevens, alsmede het recht om bezwaar te maken en het recht op
gegevensoverdraagbaarheid. Https://www.wur.nl/nl/over-wageningen/integriteit-en-privacy.htm
Let op: er is geen sprake van een absoluut recht voor betrokkenen. Dat zal telkens per situatie en
ingeroepen recht moeten worden afgewogen. Wanneer de verwerking noodzakelijk is voor de
uitvoering van een wettelijke taak of algemeen belang (bijvoorbeeld: archivering in algemeen belang,
wetenschappelijk of historisch onderzoek of statistiek) dan bestaat het recht om niet genoemd te
willen worden niet.
Door rechtsonder op “→” te drukken gaat u akkoord met de hierboven genoemde
voorwaarden.
Alvast hartelijk bedankt voor uw medewerking aan het onderzoek!
Met vriendelijke groet,
Rob de Leeuw
Mijn onderzoek voer ik uit onder supervisie van de leerstoelgroep 'Business Management &
Organization' aan de Wageningen Universiteit. Indien u een klacht heeft, kunt u deze indienen bij
WUR via [email protected]. Ook kunt u een klacht indienen bij de Autoriteit Persoonsgegevens. Meer
APPENDICES
70
informatie kunt u vinden op www.autoriteitpersoonsgegevens.nl. Heeft u vragen, dan kunt u terecht bij
de Functionaris Gegevensbescherming van WUR via [email protected].
Meer informatie over de verwerking van persoonsgegevens kunt u vinden op www.wur.nl/privacy
End of Block: Introductie
Start of Block: Werkomgeving
Office type
Onderstaand vindt u de beschrijving van 7 verschillende type werkplekken. Geeft u aan op welk type
werkplek u het meest werkzaam bent.
o Een gesloten ruimte waar ik alleen werk
o Een gesloten ruimte waar ik met 1 of 2 andere collega's werk
o Een open werkplek met 4 tot 9 mensen in één ruimte
o Een open werkplek met 10 tot 24 mensen in één ruimte
o Een open werkplek met meer dan 24 mensen in één ruimte
o Ik heb geen vaste werkplek, want ik werk op verschillende werkplekken (flexplek)
o Ik ben voornamelijk werkzaam buiten mijn eigen werkplek (projectruimten, vergaderzalen, klant bezoeken)
APPENDICES
71
Layout
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee oneens (1)
Oneens (2) Neutraal (3) Eens (4) Sterk mee eens (5)
De indeling van ons gebouw maakt het
gemakkelijk de receptie te bereiken
o o o o o
De indeling van ons gebouw maakt het
gemakkelijk om de
vergaderruimtes te bereiken
o o o o o
De indeling van ons gebouw maakt het
gemakkelijk de toiletten te bereiken
o o o o o
De indeling van ons gebouw maakt het
gemakkelijk om de kantine te
bereiken
o o o o o
Over het geheel genomen maakt de indeling van
ons gebouw maakt het
gemakkelijk om te komen waar
u wilt
o o o o o
APPENDICES
72
Space
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Ik heb voldoende
ruimte op mijn werkplek
o o o o o Ik heb
voldoende privacy op mijn
werkplek o o o o o
Ik zit dicht bij de collega's met wie ik
moet samenwerken
o o o o o
Ik zit niet te dicht op mijn
collega's o o o o o
APPENDICES
73
Ambient
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
De temperatuur op uw werkplek is comfortabel o o o o o
De luchtkwaliteit op uw werkplek is goed o o o o o De geur in ons
gebouw is aangenaam o o o o o De
achtergrondmuziek/het achtergrondgeluid is
passend o o o o o
De hoeveelheid daglicht is aangenaam o o o o o
De hoeveelheid kunstlicht is aangenaam o o o o o
De hoeveelheid (kamer)planten is
prettig o o o o o
APPENDICES
74
Functionality
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
De apparatuur die ik nodig
heb is beschikbaar
op mijn werkplek
o o o o o
De apparatuur die
beschikbaar is op mijn
werkplek is geavanceerd
o o o o o
De apparatuur die
beschikbaar is op mijn
werkplek is van kwaliteit
o o o o o
Het meubilair op mijn
werkplek is comfortabel
o o o o o Het meubilair
op mijn werkplek is van kwaliteit
o o o o o Het meubilair
op mijn werkplek is
logisch ingedeeld
o o o o o
APPENDICES
75
Cleanliness
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Mijn kantoor onderhoudt
schone toiletten
o o o o o Mijn kantoor onderhoudt een schone
kantine o o o o o
Mijn kantoor onderhoudt
schone gangen,
trappen en uitgangen
o o o o o
Over het algemeen is mijn kantoor
schoon o o o o o
APPENDICES
76
Signs
De volgende stellingen hebben betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u
het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Er is voldoende
bewegwijzering in ons kantoor
aanwezig
o o o o o
De bewegwijzering
is duidelijk zichtbaar
o o o o o De
bewegwijzering is begrijpelijk o o o o o
De bewegwijzering
maakt het makkelijk alles
te vinden
o o o o o
Holistic
De volgende stelling heeft betrekking op uw werkplek. Hierbij kunt u aangeven in welke mate u het
hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Over het geheel ben ik tevreden met mijn werkplek
o o o o o
End of Block: Werkomgeving
Start of Block: Uw werk
APPENDICES
77
Satisfaction
De volgende stellingen hebben betrekking op uw ervaringen op het werk en uw gevoelens bij uw
werk. Hierbij kunt u aangeven in welke mate u het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Ik vind mijn werk nogal
onaangenaam o o o o o Elke dag op
werk lijkt alsof het nooit eindigt
o o o o o Ik ben redelijk tevreden met mijn huidige
baan o o o o o
De meeste dagen ben ik enthousiast
over mijn werk o o o o o
Ik vind echt plezier in mijn
werk o o o o o
APPENDICES
78
Commitment
De volgende stellingen hebben betrekking op uw ervaringen op het werk en uw gevoelens bij uw
werk. Hierbij kunt u aangeven in welke mate u het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Ik zou graag de rest van mijn
carrière bij deze organisatie
willen doorbrengen
o o o o o
Ik vind het leuk om mijn
organisatie te bespreken met
mensen van buitenaf
o o o o o
Ik heb echt het gevoel dat de
problemen van deze organisatie van mijzelf zijn
o o o o o
Ik denk dat ik gemakkelijk net zo gehecht zou kunnen raken
aan een andere organisatie als
ik aan deze organisatie ben
o o o o o
Ik voel me niet als "deel van de familie" binnen mijn organisatie
o o o o o Ik voel me niet
"emotioneel verbonden" met deze organisatie
o o o o o Deze
organisatie heeft veel
persoonlijke betekenis voor
mij
o o o o o
Ik voel me niet sterk verbonden
met mijn organisatie
o o o o o
APPENDICES
79
Intention
De volgende stellingen hebben betrekking op uw ervaringen op het werk en uw gevoelens bij uw
werk. Hierbij kunt u aangeven in welke mate u het hiermee eens dan wel oneens bent.
Sterk mee
oneens Oneens Neutraal Eens
Sterk mee eens
Ik ben van plan de
organisatie in de
komende 12 maanden te
verlaten
o o o o o
Ik heb het gevoel dat ik de komende 12 maanden
de organisatie wil verlaten
o o o o o
Ik zal de organisatie
in de komende 12
maanden verlaten
o o o o o
End of Block: Uw werk
Start of Block: Algemene informatie
A1 Wat is uw geslacht?
o Man
o Vrouw
o Anders
APPENDICES
80
A2 Hoe oud bent u?
o 0-17 jaar
o 18-29 jaar
o 30-39 jaar
o 40-49 jaar
o 50-59 jaar
o 60 jaar of ouder
A3 Wat is uw hoogst voltooide opleiding?
o Lagere school
o Middelbare school
o Middelbaar Beroeps Onderwijs (MBO)
o Hoger Beroeps Onderwijs (HBO)
o Wetenschappelijk Onderwijs (WO)
o Anders, namelijk: ________________________________________________
A5 Hoeveel uur per week werkt u gemiddeld voor uw bedrijf?
o 0-8 uur
o 9-16 uur
o 17-24 uur
o 25-32 uur
o 33-40 uur
o 40+ uur
APPENDICES
81
A5 Hoeveel jaar bent u al werkzaam voor uw bedrijf?
o 0-5 jaar
o 6-10 jaar
o 11-15 jaar
o 16-20 jaar
o 21-25 jaar
o 25+ jaar
A6 Wat is de naam van uw bedrijf en in welke plaats bevindt uw kantoor zich?
________________________________________________________________
End of Block: Algemene informatie
Start of Block: Afsluiting
Slot
Dit wat het einde van dit onderzoek. Dank u wel voor uw deelname!
Mocht u nog op- en of aanmerkingen hebben of nog een vraag hebben over het doel van mijn
onderzoek, dan kunt u mailen naar: [email protected]
Met vriendelijke groet,
Rob de Leeuw
End of Block: Afsluiting
APPENDICES
82
APPENDIX 3 – Original constructs and their source
Table 20
Included constructs and their source
Construct Category Item
Source
Job Satisfaction (JS) JS1: I consider my job as rather unpleasant JS2: Each day of work seems like it never ends JS3: I feel fairly satisfied with my present job JS4: Most days I am enthusiastic about my work JS5: I find real enjoyment in my work
Brayfield and Rothe (1951)
Organizational Commitment (OC) Affective commitment OC1: I would be very happy to spend the rest of my career with this
organization OC2: I enjoy discussing my organization with people outside it OC3: I really feel as if this organization’s problems are my own OC4: I think that I could easily become as attached to another organization
as I am to this one (R) OC5: I do not feel like ‘part of the family’ at my organization (R) OC6: I do not feel ‘emotionally attached’ to this organization (R) OC7: This organization has a great deal of personal meaning for me OC8: I do not feel a strong sense of belonging to my organization (R)
Allen & Meyer (1990)
Intention to Leave (IL) IL1: Do you intend to leave the organization in the next 12 months? IL2: How strongly do you feel about leaving the organization within the next
12 months? IL3: How likely is it that you will leave the organization in the next 12
months?
Mitchell et al. (2001)
Perception of Work Environment (PWE) Layout LAY1 The facility layout makes it easy to access the reception LAY2 The facility layout makes it easy to access the meeting rooms LAY3 The facility layout makes it easy to access the toilets LAY4 The facility layout makes it easy to access the canteen LAY5 Overall, the facility layout makes it easy to get to where you want to Space SPA1 I have enough space in my workplace SPA2 I have sufficient privacy in my workplace SPA3 I am close to the colleagues I have to work with SPA4 I am not too close to my colleagues. Ambient AMB1 The temperature in the facility is comfortable AMB2 The air quality in the facility is good AMB3 The background music/sound is appropriate AMB4 The odour in the facility is pleasant AMB5 The lighting in the facility is adequate AMB6 The lighting in the facility is easy on eye AMB7 Overall, the ambient condition of the facility makes it comfortable to
Wakefield and Blodgett (1996)
APPENDICES
83
stay inside Functionality FUN1 Electronic equipment that you need is available in the facility FUN2 Electronic equipment offered by this facility is technologically
advanced FUN3 The facility offers high performing electronic equipment FUN4 The furniture in my facility is comfortable FUN5 The furniture in my facility is of quality FUN6 The furniture in my facility is logically arranged Cleanliness CLE1 The facility maintains clean restrooms CLE2 The facility maintains clean lunch areas CLE3 The facility maintains clean walkways and exits CLE4 Overall, the facility is kept clean Signs and symbols SS1 There is sufficient signage in the facility SS2 The signage in the facility is large enough to be seen SS3 The signage in the facility is easy to be understood SS4 The signage in the facility makes it easy to find your way Holistic environment H1 Overall, I am satisfied with my work environment
APPENDICES
84
APPENDIX 4 – Additional output Chapter 4
Table 21
Correlation table, top left
Lay1 Lay2 Lay3 Lay4 Lay5 Spa1 Spa2 Spa3 Spa4 Amb1 Amb2 Amb3 Amb4 Amb5 Amb6 Amb7 Fun1 Fun2 Fun3 Fun4 Fun5 Fun6
Lay1 1.00
Lay2 .578** 1.00
Lay3 .517** .520** 1.00
Lay4 .488** .538** .556** 1.00
Lay5 .590** .659** .671** .682** 1.00
Spa1 .302** .252** .292** .214** .347** 1.00
Spa2 0.09 .144* 0.00 0.07 0.05 .210** 1.00
Spa3 -0.01 -0.02 0.01 0.09 0.08 0.05 0.01 1.00
Spa4 0.13 .192** 0.11 0.07 0.13 .442** .508** -0.08 1.00
Amb1 0.08 0.04 0.10 0.01 .142* .338** .212** 0.01 .299** 1.00
Amb2 .148* 0.14 .167* 0.07 .205** .223** .176* 0.01 .286** .731** 1.00
Amb3 0.10 0.12 0.14 0.06 0.13 .221** .284** 0.05 .323** .459** .557** 1.00
Amb4 0.09 .148* .150* 0.01 .145* 0.05 .385** 0.06 .267** 0.11 0.14 .312** 1.00
Amb5 .176* 0.04 0.10 .166* .145* .184* 0.13 0.08 .189** .194** .148* .172* .181* 1.00
Amb6 .169* 0.09 0.14 .178* .204** .260** 0.14 0.10 .253** .258** .255** .318** .216** .636** 1.00
Amb7 0.06 0.09 -0.01 0.07 0.02 0.13 .277** 0.05 .246** .211** .345** .371** .231** .208** .278** 1.00
Fun1 0.12 .266** .307** .164* .327** .237** 0.03 0.05 0.08 .165* .155* .184* 0.10 0.07 0.11 0.01 1.00
Fun2 .196** .309** .196** 0.14 .293** .223** .190** 0.02 .181* .154* .203** .237** .261** 0.06 0.12 .166* .562** 1.00
Fun3 .158* .229** .218** .150* .267** .261** .182* 0.05 .195** .273** .232** .219** .220** 0.08 .160* 0.14 .515** .690** 1.00
Fun4 .244** .249** .186** 0.14 .238** .419** .288** -0.10 .404** .406** .397** .337** .182* .157* .224** .243** .278** .422** .428** 1.00
Fun5 .196** .291** .189** .162* .243** .381** .284** -0.09 .384** .418** .409** .358** .150* .142* .190** .232** .271** .432** .497** .879** 1.00
Fun6 0.07 .160* .170* 0.12 .160* .379** .302** 0.07 .456** .312** .298** .371** .238** .204** .221** .294** .149* .308** .328** .562** .590** 1.00
** Correlation significant at the 0.01 level (2-tailed)
* Correlation significant at the 0.05 level (2-tailed)
APPENDICES
85
Table 22
Correlation table, bottom left
Lay1 Lay2 Lay3 Lay4 Lay5 Spa1 Spa2 Spa3 Spa4 Amb1 Amb2 Amb3 Amb4 Amb5 Amb6 Amb7 Fun1 Fun2 Fun3 Fun4 Fun5 Fun6
Cle1 0.11 0.07 .223** .151* .147* .330** .176* -0.06 .338** .202** .192** 0.13 0.10 0.09 0.11 0.08 .199** .198** .277** .312** .312** .291**
Cle2 0.13 .197** .346** .350** .265** .313** -0.03 -0.04 0.11 .145* .155* .160* -0.02 0.10 0.09 -0.04 .290** .142* .198** .231** .284** .230**
Cle3 0.13 .164* .269** .245** .193** .307** 0.00 -0.06 .171* .199** .203** .189** -0.05 0.12 0.13 0.07 .236** .160* 0.12 .250** .286** .200**
Cle4 .252** 0.07 .241** .166* .196** .349** 0.12 -0.06 .290** .318** .329** .225** 0.03 .170* .182* .184* 0.13 0.10 .161* .265** .284** .277**
Sig1 0.07 .178* 0.05 0.10 .190** .150* .263** 0.04 .259** .186** .144* .267** .200** .175* .142* .145* 0.06 .166* 0.10 .185* .210** .168*
Sig2 0.14 .201** 0.06 0.13 .204** .154* .334** 0.04 .276** .201** .150* .249** .231** .172* 0.13 .176* 0.08 .169* 0.11 .216** .203** 0.13
Sig3 0.06 .166* 0.09 0.09 .179* 0.14 .283** 0.06 .291** .201** .157* .269** .258** .161* 0.10 .157* 0.12 .157* .148* .192** .200** .171*
Sig4 0.08 .192** 0.07 0.11 .226** .146* .287** 0.06 .264** .178* .151* .255** .274** .169* 0.14 .168* 0.09 .180* 0.12 .176* .187** .163*
Sat1 .172* .144* .205** .163* .277** .252** 0.08 0.02 .169* .195** .161* 0.11 0.07 .146* .220** -0.01 .245** .254** .223** .223** .247** .187**
Sat2 .238** .197** .276** .183* .289** .259** .171* -0.04 .236** .193** 0.12 .212** 0.10 .180* .285** 0.05 .225** 0.14 .172* .220** .220** .225**
Sat3 0.09 0.12 0.08 0.12 0.13 0.04 0.14 .152* -0.01 0.03 0.05 .185* 0.11 -0.01 0.02 0.07 .159* .159* .159* -0.01 0.02 .243**
Sat4 .170* .184* .191** .184* .237** 0.11 .243** 0.13 0.06 0.14 0.08 0.12 0.12 0.09 .158* 0.13 .144* .154* .189** 0.07 0.11 .159*
Sat5 .230** .225** .158* .256** .253** .171* .240** 0.06 0.10 0.12 0.06 0.11 .168* 0.09 0.13 0.08 .221** .246** .257** .148* .184* .201**
Com1 0.07 .203** 0.11 0.08 .171* .200** .175* .163* 0.11 0.12 0.07 0.10 .156* 0.04 .142* 0.14 0.10 0.11 0.11 0.09 .147* .204**
Com2 0.06 .199** 0.08 0.03 0.14 0.09 .222** 0.08 0.10 0.12 0.14 0.10 0.13 0.03 0.04 0.07 0.06 0.07 .220** .149* .243** 0.14
Com3 -0.04 -0.05 -0.04 -0.13 -0.12 0.01 0.14 -0.02 .176* 0.11 .142* 0.13 0.10 -0.01 0.00 .162* -0.04 0.10 0.11 .162* .207** .216**
Com4 -0.01 -0.03 -0.08 -0.01 -0.06 0.03 0.04 0.07 0.03 -0.06 -0.03 -0.04 0.02 -0.02 0.00 0.09 -0.09 -0.07 -0.06 -0.03 0.03 -0.02
Com5 0.12 0.08 .163* 0.02 0.09 0.10 0.07 0.03 0.03 0.00 -0.01 -0.01 0.12 -0.08 -0.05 -0.04 .199** 0.12 0.13 0.08 0.10 0.04
Com6 0.11 0.04 .146* 0.01 0.10 .179* 0.03 -0.03 0.05 0.05 0.01 0.05 0.14 -0.01 0.08 -0.09 .200** 0.09 .207** 0.12 .197** 0.07
Com7 0.06 0.10 0.10 0.04 0.04 0.05 0.14 0.08 0.13 0.08 0.05 .159* .299** -0.03 0.01 0.09 0.08 0.08 0.12 0.12 .174* .143*
Com8 0.01 0.07 0.10 0.06 0.08 0.12 .198** 0.06 0.12 0.02 -0.02 .175* 0.12 -0.09 0.02 0.01 0.11 0.11 .143* 0.13 .186** 0.14
Int1 0.03 -0.07 -0.01 -0.01 -0.03 -0.14 -.150* -0.04 -0.13 -0.03 0.08 0.04 -.146* 0.07 0.02 0.02 -0.07 0.07 0.02 -0.01 -0.05 -0.08
Int2 -0.01 -0.01 0.01 -0.03 -0.02 -0.08 -.178* -0.08 -0.09 -0.01 0.08 0.07 -0.14 0.04 0.03 -0.01 -0.03 0.07 0.01 0.01 -0.01 -0.08
Int3 -0.05 -0.08 -0.04 -0.06 -0.08 -.146* -0.14 -0.01 -.143* -0.07 0.03 0.01 -0.08 0.07 0.01 -0.03 -0.04 0.09 0.00 -0.02 -0.06 -0.07
** Correlation significant at the 0.01 level (2-tailed)
* Correlation significant at the 0.05 level (2-tailed)
APPENDICES
86
Table 23
Correlation table, bottom right
Cle1 Cle2 Cle3 Cle4 Sig1 Sig2 Sig3 Sig4 Sat1 Sat2 Sat3 Sat4 Sat5 Com1 Com2 Com3 Com4 Com5 Com6 Com7 Com8 Int1 Int2 Int3
Cle1 1.00
Cle2 .486** 1.00
Cle3 .449** .724** 1.00
Cle4 .553** .570** .665** 1.00
Sig1 0.11 .145* 0.12 0.13 1.00
Sig2 0.12 .168* 0.13 .178* .932** 1.00
Sig3 0.14 .206** 0.12 .173* .879** .921** 1.00
Sig4 0.11 .155* 0.13 .148* .928** .951** .916** 1.00
Sat1 .273** .268** .249** .200** .238** .227** .250** .226** 1.00
Sat2 .189** .296** .247** .160* .157* .162* .161* .148* .684** 1.00
Sat3 -0.03 .171* .160* 0.05 0.13 0.12 0.13 0.14 .220** .267** 1.00
Sat4 0.10 0.12 0.09 0.04 0.09 0.12 0.11 0.09 .412** .482** .488** 1.00
Sat5 .198** .229** .203** 0.11 .146* .174* 0.13 0.14 .522** .538** .475** .778** 1.00
Com1 0.05 0.04 0.06 -0.06 0.10 0.09 0.10 0.09 .256** .334** .232** .416** .446** 1.00
Com2 .174* 0.11 0.03 0.03 0.06 0.05 0.07 0.07 .230** .282** .151* .395** .387** .367** 1.00
Com3 .230** 0.07 0.03 0.09 0.00 0.03 -0.01 0.03 0.05 0.11 0.09 0.12 0.11 .194** .297** 1.00
Com4 0.04 -0.04 -0.03 -0.02 -0.07 -0.05 -0.11 -0.11 0.05 .160* 0.07 .171* .204** .340** .229** .256** 1.00
Com5 .215** .190** 0.14 0.13 -0.07 -0.07 -0.06 -0.07 .201** .284** 0.05 .352** .334** .276** .235** 0.14 .268** 1.00
Com6 .219** .175* 0.11 0.08 -0.04 -0.05 -0.04 -0.04 .256** .241** 0.01 .257** .305** .257** .322** .207** .304** .623** 1.00
Com7 .240** 0.10 0.05 0.02 0.10 0.09 0.09 0.07 0.14 .214** 0.10 .310** .344** .428** .393** .312** .440** .435** .491** 1.00
Com8 .145* 0.13 0.08 -0.03 0.06 0.02 0.03 0.04 .186** .256** .161* .222** .245** .331** .352** .232** .330** .357** .483** .415** 1.00
Int1 -0.03 -0.01 0.06 0.06 -0.02 -0.01 -0.01 0.01
-
.208**
-
.370** -.177*
-
.342**
-
.376**
-
.508**
-
.257** -0.06
-
.350**
-
.254**
-
.246**
-
.302**
-
.327** 1.00
Int2 -0.03 0.02 0.09 0.03 -0.02 -0.03 -0.03 -0.01
-
.250**
-
.365**
-
.192**
-
.390**
-
.412**
-
.484**
-
.278** -0.07
-
.369**
-
.267**
-
.240**
-
.310**
-
.292** .895** 1.00
Int3 -0.05 -0.02 0.05 -0.02 0.00 -0.01 0.01 0.03
-
.219**
-
.378** -0.14
-
.328**
-
.349**
-
.467**
-
.263** -0.04
-
.342**
-
.215**
-
.218**
-
.295**
-
.337** .922** .865** 1.00
** Correlation significant at the 0.01 level (2-tailed)
* Correlation significant at the 0.05 level (2-tailed)
APPENDICES
87
Table 24
EFA: Perception of elements of the work environment
Item
code Items
Factor Dimension
1 2 3 4 5 6 7
Lay1 Reach reception
0.784
Layout
Lay2 Reach meeting rooms
0.796
Lay3 Reach toilets
0.757
Lay4 Reach canteen
0.778
Lay5 Move through building
0.854
Amb1 Air temperature
0.820
Ambient
conditions
Amb2 Air quality
0.883
Amb3 Scent
0.645
Amb4 Music/Sounds
Amb5 Daylight
0.773
Amb6 Artificial light
0.773
Amb7 Biophilia
Fun1 Availability of equipment
0.763
Functionality
of equipment
and furniture
Fun2 Advancement of equipment
0.823
Fun3 Quality of equipment
0.802
Fun4 Comfort of furniture
0.557
Fun5 Quality of furniture
0.522
Fun6 Arrangement of furniture
0.595
Cle1 Toilets
0.689
Cleanliness
Cle2 Canteen
0.822
Cle3 Stair- and hallways
0.838
Cle4 Overall
0.787
Sig1 Quantity 0.939
Signs Sig2 Visibility 0.955
Sig3 Understandability 0.936
Sig4 Usefulness 0.957
APPENDICES
88
Spa1 Personal space to work
Space
Spa2 Privacy at workspace
0.709
Spa3 Close to relevant colleagues
Spa4 Not too close to others
0.741
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
A Rotation converged in 7 iterations.
Table 25
EFA: Job satisfaction, Affective commitment and Turnover intention
Item
code Items
Factor
Dimension 1 2 3
Sat1 Pleasantness of work
0.736
Job
satisfaction
Sat2 Felt duration of the workday
0.716
Sat3 Satisfaction with job
0.625
Sat4 Enthusiasm
0.782
Sat5 Satisfaction with work
0.813
Com1 Stay with organization
Com2 Talk about organization with others
0.508
Affective
commitment
Com3 Share the organization’s problems
0.531
Com4 Potential feeling of attachment
0.534
Com5 Feel part of the family
0.658
Com6 Emotional attachment
0.766
Com7 Personal meaning
0.743
Com8 Feelings of attachment
0.630
Int1 Plan to leave within 12 months 0.935
Intention to
leave the
organization
Int2 Feel to leave within 12 months 0.900
Int3 Will to leave within 12 months 0.929
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization
A Rotation converged in 5 iterations.
APPENDICES
89
Table 26
Correlation table latent variables
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1. Layout 1 2. Indoor Air 0.10 1 3. Lighting 0.14 0.27** 1 4. Equipment 0.25** 0.24** 0.15* 1 5. Furniture 0.27** 0.43** 0.26** 0.43** 1 6. Cleanliness 0.19** 0.26** 0.2** 0.21** 0.35** 1 7. Signs 0.19** 0.17* 0.22** 0.2** 0.22** 0.15* 1 8. Job satisfaction 0.29** 0.08 0.15* 0.27** 0.23** 0.21** 0.18** 1 9. Affective commitment 0.07 0.05 -0.04 0.19** 0.16* 0.10 -0.02 0.31* 1 10. Turnover intention -0.07 -0.04 0.05 0.00 -0.06 0.02 0.01 -0.37** -0.36** 1
** Correlation significant at the 0.01 level (2-tailed)
* Correlation significant at the 0.05 level (2-tailed
Table 27
Test for discriminant validity (AVE > squared correlation of latent variables)
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. AVE
1. Layout 1 0.629
2. Indoor air 0.010 1 0.748
3. Lighting 0.020 0.073 1 0.611
4. Equipment 0.063 0.058 0.023 1 0.764
5. Furniture 0.073 0.185 0.068 0.185 1 0.654
6. Cleanliness 0.036 0.068 0.040 0.044 0.123 1 0.698
7. Signs 0.036 0.029 0.048 0.040 0.048 0.023 1 0.916
8. Job satisfaction 0.084 0.006 0.023 0.073 0.053 0.044 0.032 1 .0588
9. Affective commitment 0.005 0.003 0.002 0.036 0.026 0.010 0.000 0.096 1 0.559
10. Turnover intention 0.005 0.002 0.003 0.000 0.004 0.000 0.000 0.137 0.130 1 0.863
90
Table 28
Relations between perception of elements of the work environment and affective commitment
Hypothesized path Coefficient (std. all) Z-value P(>|Z|) Mediation step 1
Layout
→ Affective commitment .038 .381 .703 Not supported
Space
→ Affective commitment - - - -
Indoor air
→ Affective Commitment (.079) (.798) .425 Not supported
Lighting
→ Affective commitment (.019) (.189) .850 Not supported
Cleanliness
→ Affective commitment .140 1.534 .125 Not supported
Equipment
→ Affective commitment .273 2.952 .003 Supported
Furniture
→ Affective Commitment .152 1.241 .215 Not supported
Signs
→ Affective Commitment (.096) (1.117) .264 Not supported
Table 29
Relations between perception of elements of the work environment and job satisfaction
Path Coefficient (std. all) Z value P(>|Z|) Mediation step 1
Layout
→ Job satisfaction .228 2.512 .012 Supported
Space
→ Job satisfaction - - - -
Indoor air
→ Job satisfaction (.067) (.672) .501 Not supported
Lighting
→ Job satisfaction .055 .625 .532 Not supported
Cleanliness
→ Job satisfaction .130 1.485 .137 Not supported
Equipment
→ Job satisfaction .278 2.951 .003 Supported
Furniture
→ Job satisfaction (.050) (.432) .665 Not supported
Signs
→ Job satisfaction .081 1.022 .307 Not supported
APPENDICES
91
APPENDIX 5 – R coding
Measurement model library(lavaan) library(haven) library(dplyr) Thesis_data <- read_sav("/Users/robdeleeuw/Desktop/DATA Master thesis/Final Final dataset.sav") ### model description Sem.Model <- ' Layout=~Lay1+Lay2+Lay3+Lay4+Lay5 IndoorAir=~Amb1+Amb2 Lighting=~Amb5+Amb6 Equipment=~Fun1+Fun2+Fun3 Furniture=~Fun4+Fun5+Fun6 Cleanliness=~Cle2+Cle3+Cle4 Signs=~Sig1+Sig2+Sig3+Sig4 Satisfaction=~Sat1+Sat4+Sat5 Commitment=~Com5+Com6+Com7+Com8 Intention=~Int1+Int2+Int3 Lay1 ~~ Sig2 ### structural paths Intention ~ Age + Education + Gender + Hours + Tenure + Commitment + Satisfaction + Layout + IndoorAir + Lighting + Equipment + Furniture + Cleanliness + Signs Satisfaction ~ Layout + IndoorAir + Lighting + Equipment + Furniture + Cleanliness + Signs Commitment ~ Layout + IndoorAir + Lighting + Equipment + Furniture + Cleanliness + Signs ' fit <- sem(Sem.Model,data=Thesis_data,std.lv=TRUE, missing="fiml") inspect(fit,'r2') fitmeasures(fit,c("gfi","agfi","nfi","cfi","rmsea","srmr","tli")) summary(fit, standardized=TRUE) coef(fit) parameterestimates(fit) fitted(fit) Structural model library(lavaan) library(haven) library(dplyr) Thesis_data <- read_sav("/Users/robdeleeuw/Desktop/DATA Master thesis/Final Final dataset.sav") ### model description Sem.Model <- ' Layout=~Lay1+Lay2+Lay3+Lay4+Lay5 IndoorAir=~Amb1+Amb2 Lighting=~Amb5+Amb6 Equipment=~Fun1+Fun2+Fun3 Furniture=~Fun4+Fun5+Fun6 Cleanliness=~Cle2+Cle3+Cle4 Signs=~Sig1+Sig2+Sig3+Sig4 Satisfaction=~Sat1+Sat4+Sat5 Commitment=~Com5+Com6+Com7+Com8 Intention=~Int1+Int2+Int3 Lay1 ~~ Sig2
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### structural paths Intention ~ Commitment + Satisfaction + Equipment Satisfaction ~Layout + Equipment Commitment ~ Equipment ' fit <- sem(Sem.Model,data=Thesis_data,std.lv=TRUE, missing="fiml") inspect(fit,'r2') fitmeasures(fit,c("gfi","agfi","nfi","cfi","rmsea","srmr","tli")) summary(fit, standardized=TRUE) coef(fit) parameterestimates(fit) fitted(fit) Structural model – including insignificant paths of control variables library(lavaan) library(haven) library(dplyr) Thesis_data <- read_sav("/Users/robdeleeuw/Desktop/DATA Master thesis/Final Final dataset.sav") ### model description Sem.Model <- ' Layout=~Lay1+Lay2+Lay3+Lay4+Lay5 IndoorAir=~Amb1+Amb2 Lighting=~Amb5+Amb6 Equipment=~Fun1+Fun2+Fun3 Furniture=~Fun4+Fun5+Fun6 Cleanliness=~Cle2+Cle3+Cle4 Signs=~Sig1+Sig2+Sig3+Sig4 Satisfaction=~Sat1+Sat4+Sat5 Commitment=~Com5+Com6+Com7+Com8 Intention=~Int1+Int2+Int3 Lay1 ~~ Sig2 ### structural paths Intention ~ Age + Education + Gender + Hours + Tenure + Commitment + Satisfaction Satisfaction ~ Layout + Equipment Commitment ~ Equipment ' fit <- sem(Sem.Model,data=Thesis_data,std.lv=TRUE, missing="fiml") inspect(fit,'r2') fitmeasures(fit,c("gfi","agfi","nfi","cfi","rmsea","srmr","tli")) summary(fit, standardized=TRUE) coef(fit) parameterestimates(fit) fitted(fit)
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Table 6
Significant paths structural model, including insignificant control variables
Regression Estimate () Z-value p (<.05)
Intention ~ Age .011 .121 .904 Education (.197) (1.785) .074 Gender (.054) (.306) .760 Hours (.024) (.214) .831 Tenure (.009) (.174) .862 Commitment (.303) (3.168) .002* Satisfaction (.410) (4.571) .000* Equipment .258 2.718 .007* Satisfaction ~ Layout .228 2.509 .012* Equipment .278 2.951 .003* Commitment ~ Equipment .273 2.965 .003*
Mediation analysis – test for indirect effects library(knitr) library(lavaan) library(psych) library(MBESS) Thesis_data <- read_sav("/Users/robdeleeuw/Desktop/DATA Master thesis/Final Final dataset.sav") model <- ' # Latent variables Layout=~Lay1+Lay2+Lay3+Lay4+Lay5 IndoorAir=~Amb1+Amb2 Lighting=~Amb5+Amb6 Equipment=~Fun1+Fun2+Fun3 Furniture=~Fun4+Fun5+Fun6 Cleanliness=~Cle2+Cle3+Cle4 Signs=~Sig1+Sig2+Sig3+Sig4 Satisfaction=~Sat1+Sat4+Sat5 Commitment=~Com5+Com6+Com7+Com8 Intention=~Int1+Int2+Int3 # Covariance Lay1 ~~ Sig2 Satisfaction ~~ Commitment' # outcome model Intention ~ c*IndependentVariable+ b*MediatingVariable + other independent variable(s) + control variables # mediator model MediatingVariable ~ a*IndependentVariable + other independent variable(s) # indirect effect IndirectEffect := a*b # total effect total := c + a*b
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fit <- sem(model, data=Thesis_data, se = "bootstrap", bootstrap = 1000) summary(fit, fit.measures=TRUE, standardize=TRUE, rsquare=TRUE) parameterestimates(fit, boot.ci.type = "bca.simple", standardized = TRUE) %>% kable()