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A new trend has recently emerged in organizational structures: the remote-only organization. These organizations operate without headquarters or main offices, and have all employees telecommute full-time. Traditional organizations keep an eye on these trends, and are unsure how to react. Full-time telecommuting is still very much an unknown phenomenon, and its results on firm-level outcomes are scarcely researched. One big concern for managers is the fact that full-time telecommuters can leave the organization by simply disappearing from the organization’s digital infrastructure, leading to uncertainty about their commitment. This study researched the effects of full-time telecommuting on organizational commitment, and examined the differences of commitment between full-time telecommuters and moderateand non-telecommuters. A three-dimension conceptualization of organizational commitment was used, which allowed for a more detailed look into the specific effects of the telecommuting intensities. This research gives managers detailed insights in whether or not to implement telecommuting in the organization, and provides the academic field with new insights regarding the telecommuting – organizational commitment relationship. Using a cross-sectional survey, resulting in 721 complete responses, data was collected to assess the organizational commitment for three categories of telecommuting intensity: nontelecommuting, moderate telecommuting and full-time telecommuting. The results show that full-time telecommuting is not worse, and in some cases better, for organizational commitment than non-telecommuting, and is comparable with moderate telecommuting. Therefore concluding that managers should not be afraid of a decrease in organizational commitment when implementing full-time telecommuting. From the results several other managerially relevant conclusions are drawn that improve on the insights of securing the organizational commitment for full-time telecommuters. First, it is important to harness the autonomy full-time telecommuting gives employees. Second, no extra internal social support is needed for full-time telecommuters. Thirdly, to expand on the previous point, infrequent physical meetings with co-workers do not have a positive influence on the commitment for full-time telecommuters. The two most important academic implications are that full-time telecommuting is distinct from the prior researched telecommuting intensities, and should therefore be accounted for in any future research involving telecommuting intensity, and that organizational commitment should not be treated as a singular dimension when relating to telecommuting intensity.
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Master Strategic Management
January 9
th
, 2020
Name: Wout Brink
Student Number: 2030914
ANR: U999980
Supervisor: Francis Park
Second reader: Joshua Eckblad
The effect of Telecommuting intensity on Organizational commitment
The Telecommuting Dilemma
1
Abstract
A new trend has recently emerged in organizational structures: the remote-only organization.
These organizations operate without headquarters or main offices, and have all employees
telecommute full-time. Traditional organizations keep an eye on these trends, and are unsure
how to react. Full-time telecommuting is still very much an unknown phenomenon, and its
results on firm-level outcomes are scarcely researched. One big concern for managers is the
fact that full-time telecommuters can leave the organization by simply disappearing from the
organization’s digital infrastructure, leading to uncertainty about their commitment.
This study researched the effects of full-time telecommuting on organizational commitment,
and examined the differences of commitment between full-time telecommuters and moderate-
and non-telecommuters. A three-dimension conceptualization of organizational commitment
was used, which allowed for a more detailed look into the specific effects of the
telecommuting intensities. This research gives managers detailed insights in whether or not to
implement telecommuting in the organization, and provides the academic field with new
insights regarding the telecommuting – organizational commitment relationship.
Using a cross-sectional survey, resulting in 721 complete responses, data was collected to
assess the organizational commitment for three categories of telecommuting intensity: non-
telecommuting, moderate telecommuting and full-time telecommuting.
The results show that full-time telecommuting is not worse, and in some cases better, for
organizational commitment than non-telecommuting, and is comparable with moderate
telecommuting. Therefore concluding that managers should not be afraid of a decrease in
organizational commitment when implementing full-time telecommuting. From the results
several other managerially relevant conclusions are drawn that improve on the insights of
securing the organizational commitment for full-time telecommuters. First, it is important to
harness the autonomy full-time telecommuting gives employees. Second, no extra internal
social support is needed for full-time telecommuters. Thirdly, to expand on the previous point,
infrequent physical meetings with co-workers do not have a positive influence on the
commitment for full-time telecommuters.
The two most important academic implications are that full-time telecommuting is distinct
from the prior researched telecommuting intensities, and should therefore be accounted for in
any future research involving telecommuting intensity, and that organizational commitment
should not be treated as a singular dimension when relating to telecommuting intensity.
2
Table of contents
1. Introduction ......................................................................................................................................... 4
1.1 Context .......................................................................................................................................... 4
1.1.1 Telecommuting ....................................................................................................................... 4
1.1.2 Organizational Commitment .................................................................................................. 5
1.1.3 Telecommuting – Organizational commitment relationship .................................................. 6
1.2 Relevance ...................................................................................................................................... 6
1.3 Problem statement ......................................................................................................................... 7
1.4 Research design ............................................................................................................................. 7
2. Literature review ................................................................................................................................. 8
2.1 Telecommuting .............................................................................................................................. 8
2.1.1 History .................................................................................................................................... 8
2.1.2 Definition ................................................................................................................................ 9
2.1.3 Predicting telecommuting ..................................................................................................... 10
2.2 Organizational commitment ........................................................................................................ 10
2.2.1 Definition .............................................................................................................................. 10
2.2.2 Effects ................................................................................................................................... 12
2.2.3 Antecedents .......................................................................................................................... 12
2.3 Telecommuting - Organizational commitment relationship ........................................................ 14
3. Hypothesis development ................................................................................................................... 16
4. Methodology ..................................................................................................................................... 21
4.1 Operationalization variables ........................................................................................................ 21
4.1.1 Dependent variable ............................................................................................................... 21
4.1.2 Independent variable ............................................................................................................ 21
4.1.3 Moderating and mediating variables .................................................................................... 22
4.1.4 Control variables .................................................................................................................. 22
4.1.5 Summary .............................................................................................................................. 23
4.2 Data collection ............................................................................................................................. 24
4.2.1 Sample .................................................................................................................................. 24
4.2.2 Survey ................................................................................................................................... 25
4.3 Analysis ....................................................................................................................................... 26
4.3.1 Datafile ................................................................................................................................. 26
4.3.2 Reliability ............................................................................................................................. 26
4.3.3 Models of analysis ................................................................................................................ 26
5. Results ............................................................................................................................................... 28
5.1 Reliability of measures ................................................................................................................ 28
5.2 Distribution of data ...................................................................................................................... 29
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5.3 Correlations Matrix ..................................................................................................................... 30
5.4.1 Results Hypothesis 1 ............................................................................................................ 31
5.4.2 Results Hypothesis 2 ............................................................................................................ 34
5.4.3 Results Hypothesis 3 ............................................................................................................ 36
5.4.4 Results Hypothesis 4 ............................................................................................................ 38
6. Discussion and implications .............................................................................................................. 41
6.1 Discussion ................................................................................................................................... 41
6.2 Managerial implications .............................................................................................................. 44
6.3 Academic implications ................................................................................................................ 45
6.4 Future research ............................................................................................................................ 45
6.5 Limitations................................................................................................................................... 46
References ............................................................................................................................................. 48
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1. Introduction
This study researched the effects of different telecommuting intensities on organizational
commitment. Recently, a new category of telecommuting intensity increased in prevalence:
full-time telecommuting. Results from a 2018 survey claim that full-time telecommuters have
less commitment, and are much less likely to remain at a company long-term (Schawbel,
2018). In addition, the telecommuting intensity – organizational commitment relationship has
not been previously researched using the extended three dimension conceptualization of
organizational commitment. Therefore, this study distinguishes full-time telecommuters from
moderate- and non-telecommuters, and researched their organizational commitment.
1.1 Context
1.1.1 Telecommuting
Telecommuting, used interchangeably with remote working or telework, among others, is
defined and conceptualized by Allen, Golden and Shockley (2015) as “employees that
substitute time typically spent in a central office with time spent working away from other
employees and do so for a portion of their regular work time”. Telecommuting has seen an
increase in popularity over the last decades (State of Remote Work, 2019; Future Workforce
Report, 2018; The Latest Remote Work Statistics, 2019). Advances in technology and
affordable rates for mobile connections have increased the availability of telecommuting for
workers worldwide (Allen, Golden and Shockley, 2015). Multiple studies have researched
telecommuting and found it advantageous for both employee and employer. Greater
productivity, lower absenteeism, better morale, reduced overhead costs and lower turnover are
a few of the advantages found (Hill et al., 1996; Bailey & Kurland, 1999; Nilles, 1994; Olson,
1987; Verbeke et al., 2008). However, this same research also uncovered challenges and
possible disadvantages for telecommuting; such as performance measurement, loyalty,
coordination and communication.
A new development in the area of telecommuting among knowledge workers, is the rise of the
so-called “remote only organization”. These organizations define themselves as having no
headquarters or main office, and hiring and working from all over the world (The Remote
Manifesto, 2015). These organizations function with virtual teams (Ferrazzi, 2014;
Malhotram, Majchrzak and Rosen, 2007), which are teams consisting of members who are
geographically dispersed and cross-functional. In addition, new technology and internet
infrastructure enables companies to maintain tighter controls over full-time telecommuters
(Kizza, 2007). These trends lead to an increased prevalence of full-time telecommuters. Full-
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time telecommuters list increased productivity, increased autonomy, less stress, lack of
commute and improved work-life balance as the main benefits of telecommuting full-time
(State of Remote Work, 2019; Future Workforce Report, 2018; The Latest Remote Work
Statistics, 2019; Global State of Remote Work, 2018). For companies, these positive factors
generally lead to happier employees, which in turn has a positive effect on performance
related outcomes (Iaffaldano & Muchinsky, 1985). In addition, employing full-time
telecommuters enables companies to hire employees without accounting for geographic
distances. Society itself also benefits from this trend due to reduced commuting, which leads
to less stress on the roads and infrastructure, and a reduction of combustion-based pollution.
At the early stages of telecommuting research, the intensity of telecommuting was not, or
barely taking into account, leading to conflicting results regarding the effect of telecommuting
intensity on firm-related outcomes (Crossan & Burton, 1993; Igbaria & Guimaraes, 1999;
Niles, 1994). It wasn’t until the mid-2000’s until telecommuting intensity was properly
distinguished (Allen, Golden & Shockley, 2015). Even then, the extent of intensity was
maximized to nearly full-time, thus not including the, now upcoming, full-time
telecommuting group (Allen, Golden & Shockley, 2015).
1.1.2 Organizational Commitment
The positive effects of a strong organizational commitment of employees are well known
(Steers, 1977; Buchanan, 1974). Although the research of Steers (1977) showed that
employee performance is generally not directly related to commitment, there are other studies
that indicated that organizational commitment of employees is positively related to prosocial
behavior and negatively related to turnover (O’Reilly & Chatman, 1986). It’s also well
researched that a strong organizational commitment has a positive influence on in-role
behaviors, and job satisfaction (Williams & Anderson, 1991). It can be concluded that a
strong employee organizational commitment is an added value to an organization, and
important for a manager to monitor. Organizational commitment has been conceptualized
many times by many different researchers (Becker, 1960; Buchanan, 1974; Mowday, Steers &
Porter, 1979; Allen & Meyer, 1990). This research will use the three-component
conceptualization and definition of organizational commitment first published by Allen and
Meyer (1990). Allen and Meyer define organizational commitment as “a psychological link
between the employee and his or her organization that makes it less likely that the employee
will voluntarily leave the organization” (Allen & Meyer, 1990).
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1.1.3 Telecommuting – Organizational commitment relationship
The effect of telecommuting on organizational commitment has been previously researched;
in 2006, Golden found a curvilinear relationship with telecommuting intensity on
organizational commitment (Golden, 2006). However, this research did not include full-time
telecommuters, and used a single-dimension definition for organizational commitment,
consisting of one survey-item.
The challenges for the telecommuting – organizational commitment relationship are further
examined and distilled in various studies. Multiple researchers found that telecommuting
leads to employee isolation, thus negatively affecting organizational commitment
(Wiesenfeld, Raghuram and Garud, 2001; Gainey, Kelley and Hill, 1991). However, more
recent research contrasts these previous findings; establishing a positive relation between
telecommuting and organizational commitment (Harker & MacDonnell, 2012). In addition,
Harker & MacDonnell (2012) found that this relation was stronger for younger workers,
suggesting that telecommuting may be a tool to attract younger talent.
The conflicting results from public surveys regarding the effects of full-time telecommuting
on organizational commitment, as well as lack of insights in this relationship from an
academic point of view, give managers little objective foundation whether or not to integrate
full-time telecommuting in their organization (Schawbel, 2018; Global State of Remote Work,
2018). This research aims to provide managers a definitive answer to this “Telecommuting
Dilemma”.
1.2 Relevance
This research contributes to the academic field by expanding on the telecommuting –
organizational commitment literature in three ways. First, this research includes full-time
telecommuters, and distinguishes this group with moderate intensity telecommuters, and non-
telecommuters. Second, this research uses the full measure of the three dimensions of
organizational commitment, as defined by Allen and Meyer (1990). Third, this research
includes moderating and mediating variables that are specifically relevant for the full-time
telecommuting group.
This research provides managerial relevance by demonstrating the effect of full-time
telecommuting on organizational commitment, allowing managers to decide whether or not it
is beneficial to employ this option within their own firm. In addition, this study provides
advice on factors that may influence organizational commitment when allowing full-time
telecommuting within the firm.
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1.3 Problem statement
Following the proper motivation for the research from an academic and managerial
perspective, the following problem statement was formulated: “What is the effect of full-time
telecommuting on employee organizational commitment?”.
1.4 Research design
To test the problem statement and subsequent hypotheses, a four-step approach was used:
1. Operationalization variables
a. Establishing the definition and characteristics of the variables of interest
2. Construction questionnaire
a. Theoretical justification for used measures
b. Adding additional items for control variables
3. Sample selection and preliminary data collection
a. Conduct preliminary analysis
b. Sample selection based on results preliminary analysis
4. Performing cross-sectional survey and data analysis
a. Distribution of survey via Qualtrics
b. Data analysis of results using descriptive- and inferential statistics
After the data analysis, conclusions are drawn regarding the hypotheses, and the academic-
and managerial implications are presented.
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2. Literature review
In this chapter, the constructs of organizational commitment and telecommuting are further
explored. An extensive review of the literature is presented. Furthermore, relevant theories to
the telecommuting – organizational commitment relationship are elaborated.
2.1 Telecommuting
2.1.1 History
Originally conceived by NASA engineer Jack Nilles in 1973 (Avery & Zabel, 2001),
telecommuting was the idea of moving the work to workers instead of the other way around.
This introduced the option for employees to work from a different location than the
organization’s (main) offices, for example from home. Sparked by the U.S. oil crisis, the main
concern was to reduce fuel and energy consumption by eliminating the need to commute
(Avery & Zabel, 2001). At the end of the 1970’s, companies such as IBM and Control Data
Corporation saw potential organizational advantages in the ability to telecommute, and started
hiring remote computer programmers (Avery & Zabel, 2001; Caldow, 2009). In addition,
telecommuting was seen as an option for managing work-life balances in case of family
responsibilities (Avery & Zabel, 2001).
The number of people telecommuting has grown extensively over the past decades. The U.S.
Census Bureau published a report which stated that the number of people telecommuting in
the U.S. increased 115 percent between 2005 and 2015 (U.S. Census Bureau, 2017). The
availability and feasibility of telecommuting is highly dependent on technological
developments (Kizza, 2007). Before high-speed internet was available around the world,
telecommuting was more challenging and less prevalent (Kizza, 2007). Now it is possible to
emulate the office environment from a remote location (Kizza, 2007). These external macro
conditions may alter research results, therefore it is of importance to retest previously
established relationships (Chang, Li, 2015; Ethiraj, Gambardella & Helfat, 2016).
A more recent trend is the increased prevalence of full-time telecommuting, and organizations
composed solely of full-time telecommuters (Global State of Remote Work, 2018). A
research conducted by Owl Labs on a global convenience sample of 3,028 workers showed
that 18% of respondents telecommuted full-time (Global State of Remote Work, 2018). A
2019 research conducted with a U.S. based convenience sample of 1,202 workers showed that
30% of respondents telecommuted full-time. Even though the samples are not academically
valid, other similar surveys report comparable results (State of Remote Work, 2019; Future
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Workforce Report, 2018; The Latest Remote Work Statistics, 2019). This is an indication of
increased prevalence of full-time telecommuting. The respondents on these surveys list work-
life balance, lack of commute, less stress, increased productivity and increased autonomy as
benefits of telecommuting full-time (State of Remote Work, 2019; Future Workforce Report,
2018; The Latest Remote Work Statistics, 2019; Global State of Remote Work, 2018).
The trend of full-time telecommuting gives managers a dilemma whether or not to incorporate
this in the organization. There are potential benefits to enabling full-time telecommuting,
however managers also list concerns and challenges. A 2019 case study examined the
transition of two tech-focused companies to full-time telecommuting (Eckhardt, Giordano,
Endter & Somers, 2019). These two companies faced significant challenges regarding the
technological infrastructure, building a relationship of trust with the employees, and
integrating the traditional organization with the new remote organization. Both companies
state that trust in the employee is essential, and both companies aimed to prevent social
isolation of their remote workforce, with mixed success.
2.1.2 Definition
A significant lack of an accepted definition of telecommuting, as well as lack of a
homogeneous term for the concept, makes reviewing existing literature on telecommuting
hard. In addition, the absence of worldwide high-speed internet and technological
developments in the time periods within which part of the literature was published makes it
challenging to determine modern day applicability of earlier research. In the literature,
different terms are used to indicate comparable definitions as telecommuting, such as
Distributed work (Dourish & Bly, 1992), Flexible work arrangements (Shockley & Allen,
2007), Remote work (Olson, 1983), Telework (Huws, Korte & Robinson, 1990) and Virtual
teams (Lipnack & Stamps, 1999). In a 2015 assessment of scientific findings regarding
telecommuting, Allen, Golden and Shockley established a singular definition for
telecommuting, and proposed to use the term telecommuting in all subsequent research
regarding the subject. In agreement with these statements, and for the sake of consistency, this
research will use the term telecommuting for all references to the subject.
In their research, Allen, Golden and Shockley distilled a singular definition for telecommuting
from all previous iterations of definitions of telecommuting. In this definition, individuals
who telecommute: substitute time normally spent in the office with time spent working away
from other employees, they do so for a few hours a week to nearly full-time, are part of a
larger organization, work principally within their home during telecommuting periods and use
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some form technology for communication and information in order to interact with other
members of the organization (Allen, Golden & Shockley, 2015).
Considering the large body of research condensed to form this definition, and its exhaustive
properties, this definition will partially fit this research. To make this definition suitable for
this research an important alteration must be made: instead of limiting telecommuting
intensity to nearly full-time, this research includes full-time telecommuting in its definition.
This will allow this research to break new grounds by examining this previously unexamined
group.
Distinguishing the maximized degree of telecommuting intensity; full-time telecommuting,
raises the question to what extent telecommuting intensity has been researched in prior
studies. Unfortunately, up until the mid-2000’s the extent of telecommuting was not explicitly
distinguished, which prohibits valid comparisons and caused inconsistent results (Crossan &
Burton, 1993; Igbaria & Guimaraes, 1999; Niles, 1994). It is evident that there is a difference
between an employee that telecommutes thirty hours a week and an employee that
telecommutes three hours a week. This difference, and thus the importance of the extent of
telecommuting intensity, has been established in numerous studies since 2005 where different
results were found for different extents of telecommuting intensity (Allen, Golden &
Shockley, 2015). This study will add to this base of research by researching the maximum
intensity of telecommuting: full-time, exclusive, telecommuting.
2.1.3 Predicting telecommuting
A few studies, mostly in the economic research fields, have aimed to predict the likelihood of
employees telecommuting, when made available by the employer (Singh, Paleti, Jenkins &
Bhat, 2013; Yen, 2000). Researchers have found several variables to predict the likelihood of
telecommuting. These variables are travel distance, age, education level, internet usage,
flexible working hours and household income (Singh, Paleti, Jenkins & Bhat, 2013). In
addition, openness to new experiences seem to influence the happiness and adaptability a
telecommuter experiences, and may influence a telecommuters decision to telecommute
(Anderson, Kaplan & Vega, 2015).
2.2 Organizational commitment
2.2.1 Definition
Various definitions of organizational commitment have been coined since first defined by
Becker in 1960 (Becker, 1960; Brown, 1969; Buchanan, 1974; Grusky, 1966; Hall, Schneider
11
& Nygren, 1970; Hrebiniak & Alutto, 1972; Kanter, 1968; Salancik, 1977; Sheldon, 1971;
Weiner & Gechman, 1977).
Even though these definitions have distinct differences, most have in common that
organizational commitment is considered as a single-dimension concept. The definitions
mostly focus on employee behavior, which are expressions of underlying commitment.
Mowday, Steers and Porter (1979, 1982) constructed a homogeneous definition of
organizational commitment, paired with a reliable measurement. In their research, Mowday,
Steers and Porter (1979, 1982) recognized two dimensions within organizational commitment:
the calculative dimension, which is focused on extrinsic motivations and sunk costs, and the
attitudinal dimension, which is characterized by the alignment of employee’s ambitions with
the organization’s goals and wishes (Becker, 1960). Mowday, Steers and Porter (1979, 1982)
defined organizational commitment as “the relative strength of an individual’s identification
with and involvement in a particular organization”. This definition and recognition of multiple
dimensions, which focuses on the active relationship of the employee in which it is willing to
contribute to the organization’s wellbeing, serves as a keystone for subsequent research and
conceptualization on organizational commitment (Allen & Meyer, 1990).
Based on these keystones, Allen and Meyer defined a three-component conceptualization of
organizational commitment (Allen & Meyer, 1990), namely: Affective commitment,
Continuance commitment and Normative commitment. Affective commitment encompasses
the emotional ties an employee has with the organization, and is measured through positive
work experiences. Continuance commitment consists on the perceived financial or social
costs and risks associated with leaving the organization. Normative commitment is focused on
the commitment that is based on a perceived moral obligation to commit to the organization.
As a whole, Allen and Meyer define organizational commitment as “a psychological link
between the employee and his or her organization that makes it less likely that the employee
will voluntarily leave the organization” (Allen & Meyer, 1990; Meyer & Allen, 1991; Meyer
& Allen, 1997).
The wide use within organizational research of this construct ensures a certain homogeneity
with other studies on organizational commitment, which facilitates comparison (Meyer,
Stanley, Herscovitch & Topolnytsky, 2002; Jaros, 2007; Solinger, van Olffen & Roe, 2008).
In addition the three dimensions and subsequent items are proven valid, reliable and
statistically sound as a measure of organizational commitment (Allen & Meyer, 1990; Meyer
& Allen, 1991; Meyer & Allen, 1997). Even though there are studies in which the three
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dimensions are highly correlated, some interdimensional differences could be hypothesized
when examining the relationship with telecommuting (Caykoylu, Egri, Havlovic & Bradley,
2011; Allen, Golden & Shockley, 2015). For example, telecommuting affects employee
affection for the organization through job satisfaction (Affective commitment), but is
insignificant for the costs of leaving an organization (Continuance commitment). On account
of this reasoning, the three-component conceptualization will be used as the definition, and
measurement, of organizational commitment in this research.
2.2.2 Effects
Several effects of organizational commitment have been studied. One significant consequence
of strong organizational commitment is its negative effect on employee turnover and turnover
intention (Meyer et al, 2002; Steers, 1977). In addition, a strong organizational commitment
enhances job satisfaction (Knoop, 1995; Testa, 1999; Yousef, 2000; Markovits, Davis, van
Dick, 2010; Vandenberg & Lance, 1992) and lowers absenteeism (Sagie, 1998). These
positive effects, as well as a direct effect of strong organizational commitment on job
performance, lead to higher job performance (Mathieu & Zajac, 1990; Riketta, 2002;
Freeman, 1977; Herzberg, 1957). These effects make organizational commitment a variable
of high interest to managers and organizations.
2.2.3 Antecedents
There are numerous antecedents for organizational commitment. Concerning this research it
will be important to distinguish the most relevant of these antecedents for the telecommuting
– organizational commitment relationship.
Job satisfaction
Job satisfaction is defined in Tett and Meyer’s meta-analysis of 1993 as “the affective
connection an employee has regarding its job in its entirety or with certain facets of the job”
(Tett & Meyer, 1993). Job satisfaction is influenced by employee empowerment and self-
determination (Spreitzer, 1995; Comm & Mathaisel, 2000). These studies showed that when
an employee feels more empowered and has an increase in self-determination, they are more
satisfied with their job.
Even though job satisfaction is an observed result of strong organizational commitment, it has
also been shown to be an effective, and important, antecedent for organizational commitment
(Caykoylu et al., 2011; Mayer & Schoorman, 1998; Blegen, 1993; Lu, While & Barriball,
2005; Porter, Steers, Mowday & Boulian, 1974; Mueller, Boyer, Price & Iverson, 1994). In
these studies, a higher job satisfaction lead to more committed employees. The important role
13
of job satisfaction in explaining organizational commitment, but also as the outcome of
organizational commitment shows a strong two-way interaction.
Organizational identification
The two-way interaction between organizational commitment and job satisfaction is
complimented by the explanatory value of organizational identification. Organizational
identification encompasses the extent of which an employee sees itself as part of the
organization (Dutton, Dukerich & Harquail, 1994). The three determining factors of
organizational identification are extent of contact between employee and organization,
visibility of organizational membership and the attractiveness of organizational identity
(Ashforth & Mael, 1989; Bhattacharya, Rao & Glynn, 1995). Of these determining factors,
extent of contact between an individual and the organization, is expected to be most relevant
to the telecommuting relationship, since this contact can be heavily influenced by the absence
of contact when not working in a central office.
Some researchers have found a positive relation of organizational identification to
organizational commitment (Balfour & Wechsler, 1996; Mottaz, 1988; Cheney & Tompkins,
1987; Chan, 2004), even suggesting that there is an overlap between commitment and
identification (Cheney & Tompkins, 1987). However, other research found that the two
concepts are distinct (Bullis & Bach, 1989; Chan, 2004), indicating a person may identify
with the organization without being committed. For example, an employee who identifies
with the company’s cause but not the organization itself. Conversely, an employee may be
committed to the organization, without identifying with its cause. For example a loyal account
manager that sells tobacco while disapproving smoking. Organizational identification also has
a two-way interaction effect with job satisfaction (Mael & Tetrick, 1992; van Dick, van
Knippenberg, Kerschreiter, Hertel & Wieseke, 2007), therefore organizational identification
adds to the two-way interaction of organizational commitment and job satisfaction, forming a
partial three-way interaction effect (van Dick et al., 2004).
Other
In addition to the concepts of job satisfaction and organizational identification as antecedents
for organizational commitment, there are numerous more tangible variables that have an
influence on organizational commitment. These are job characteristics such as type of position
(Cohen & Gattiker, 1994), where a higher position would lead to increased commitment. In
addition a weak, but positive effect was observed regarding tenure and organizational
commitment (Cohen, 1993).
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Furthermore, personal characteristics such as gender (Cramer, 1993; Mathieu & Zajac, 1990;
Mowday, Steers & Porter, 1982), level of education (Luthans, Baack & Taylor, 1987; Meyer
& Allen, 1997) and age (Cohen, 1993; Allen & Meyer, 1993) were found to have some degree
of influence on organizational commitment.
2.3 Telecommuting - Organizational commitment relationship
Several articles list one of the managers’ main concerns when implementing full-time
telecommuting as the lack of control over the employee, which requires a large amount of
trust from the manager in the employee (Nevogt, 2019; Miller, 2019; 7 Challenges of
Managing Remote Team, 2019). These concerns are amplified by a new phenomenon called
“Ghosting”. Ghosting is when an employee, or interviewee, suddenly breaks off all contact
and simply disappears from the organization’s radar, which is an increasing problem for
managers (Bolsu, 2018; What causes workplace ghosting?, 2018). Full-time telecommuting
makes it easier for employees to “Ghost” their employer, due to lack of physical contact,
being in a different country and geographic distance. Results from a 2018 survey paint a
similar picture, the author states that full-time telecommuters have lower organizational
commitment due to social isolation and lack of personal connection with the organization
(Schawbel, 2018). This begs the question if full-time telecommuters are less committed to
their organization, making the telecommuting – organizational commitment relationship even
more salient.
The relationship between telecommuting and organizational commitment has been previously
researched. A systematic review of eight studies showed a positive relationship between
telecommuting and organizational commitment, these studies did not account for extent of
telecommuting, nor did they distinct between the three dimensions of organizational
commitment (Martin & MacDonnell, 2012). In a 2006 study, Golden researched the effect of
extent of telecommuting on organizational commitment, and found that more telecommuting
leads to more organizational commitment (Golden, 2006). However, also in this study, only a
single-dimension construct of organizational commitment was used based on a single survey
question. In addition, the study did not include full-time telecommuters in the research.
Predictors of organizational commitment in the telecommuting relationship are mostly
comprised of relationships with co-workers, social support received and the autonomy
associated with telecommuting (Golden & Veiga, 2008; Madlock, 2013; Fay & Kline, 2011).
The effect of availability of telecommuting on job satisfaction has been established, results
from a meta-analysis of 28 studies showed a positive association of telecommuting with job
15
satisfaction (Gajendran & Harrison, 2007). Regarding the extent of telecommuting, a
curvilinear relationship was found, where the positive effect of telecommuting on job
satisfaction topped out at 15.1 hours of telecommuting per week (Golden & Veiga, 2005;
Golden, 2006). These studies explained this curvilinear relationship by theorizing a lack of
social interaction, which may offset other gains in job satisfaction caused by telecommuting
advantages such as autonomy gain (Golden & Veiga, 2005; Golden, 2006). Predictors of job
satisfaction relating to telecommuting are similar to on-site studies on job satisfaction, such as
job characteristics (Baker, Avery & Crawford, 2007). However, several factors seem more
important in the telecommuting context, such as the manager’s trust in the teleworker and
granted autonomy (Baker, Avery & Crawford, 2007). Autonomy was found to have a
mediating effect for the telecommuting relationship with job satisfaction and turnover intent
(Gajendran & Harrison, 2015). Higher intensity of telecommuting increased perceived
autonomy of the employee (Gajendran & Harrison, 2015).
Similar to job satisfaction, organizational identification can influence organizational
commitment (e.g. Chan, 2004). Several aspects that influence organizational identification are
available when working on-site, are not available when telecommuting (DeSanctis & Monge,
1999; Wiesenfeld, Raghuram & Garud, 2001). These aspects include means of supervision
and control, but also certain rituals and ceremonies. For telecommuters, seemingly
insignificant informal rituals such as water cooler conversation are absent, which significantly
influences the telecommuters satisfaction and organizational identification (Goldsborough,
2000; Nilles, 1994). This implies organizational identification is an important factor in the
telecommuting – organizational commitment relationship. This has not been explicitly
researched for full-time telecommuters, but it can be theorized that these effects carry over
and may even be emphasized for full-time telecommuters. Therefore, organizational
identification can serve as an important variable in the telecommuting – organizational
commitment relationship.
This research offers new insights in the telecommuting – organizational commitment
relationship by using the three-dimensional view of organizational commitment, which has
not been done before in this extent, and by analyzing the effects of full-time telecommuting
intensity on organizational commitment.
16
3. Hypothesis development
Prior research on the effect of telecommuting on organizational commitment reported results
for non-telecommuters to nearly full-time telecommuters (Allen, Golden & Shockley, 2015).
These studies report a curvilinear relationship, where more telecommuting leads to more
organizational commitment until after a certain point of increase, organizational commitment
drops again (Golden & Veiga, 2005; Golden, 2006).
Among the reasons for increased organizational commitment for telecommuters are an
employee’s perceived increase of autonomy, and trust from the manager when allowed to
telecommute, which in turn increases organizational commitment (Golden & Veiga, 2008;
Madlock, 2013; Fay & Kline, 2011). It can be speculated that for full-time telecommuting this
perceived increase in autonomy and trust from the manager may even be more amplified in
comparison with other modes of telecommuting, since full-time telecommuting implies less
tangible management control over the employee and more self-determination (Wiesenfeld,
Raghuram & Garud, 1999).
Reasons for the drop in organizational commitment levels were stated as lack of social
interaction and support, which negate the positive factors from telecommuting (Golden &
Veiga, 2008; Madlock, 2013; Fay & Kline, 2011). It can be theorized that an organization that
allows full-time telecommuting has mechanisms in place in order to negate the lack of social
interaction and support and thus experience a net benefit from the positive factors.
Further, prior research used a basic construct of organizational commitment, and did not
distinguish between dimensions of organizational commitment (Martin & MacDonnell, 2012).
There is a distinct difference between the three dimensions of organizational commitment,
and the effects of telecommuting on these dimensions may differ per dimension.
For the dimension of Continuance commitment, which is characterized by the need to remain
at an organization because of the costs of leaving (or lack of alternatives), it is expected the
extent of telecommuting to not have an influence on this dimension, since the cost of leaving
an organization may be the same for telecommuters as non-telecommuters.
Affective commitment (feelings of comfort and personal competence) and Normative
commitment (based on loyalty and repayment of favors) are mostly determined by drivers
which are in turn influenced by the extent of telecommuting offered to the employee, such as
increased trust and increased autonomy (Marique, Stinglhamber, Desmette, Caesens & De
17
Zanet, 2013). Therefore, it is expected that telecommuting intensity has an effect on these two
dimensions.
In sum, it is proposed that telecommuting intensity has a positive impact on two out of three
dimensions of organizational commitment. Because of likely negation of negative factors of
high telecommuting intensity, full-time telecommuting is expected to have similar
commitment to moderate telecommuting, instead of a curvilinear relationship. The
beforementioned reasoning leads to the following hypotheses:
H1a: Full-time telecommuting employees have higher Affective commitment compared to
non-telecommuting employees, and similar Affective commitment compared to moderate
telecommuting.
H1b: Full-time telecommuting employees have similar Continuance commitment compared to
non-telecommuting employees, and similar Continuance commitment compared to moderate
telecommuting employees.
H1c: Full-time telecommuting employees have higher Normative commitment compared to
non-telecommuting employees, and similar Normative commitment compared to moderate
telecommuting employees.
As previously stated, the positive relationship between telecommuting intensity and
organizational commitment is partially explained by an increase in trust from the manager,
and an increase in autonomy of the employee. When relating this effect to full-time
telecommuting, it could be theorized that this effect size increases proportionally with the
telecommuting intensity. Culminating to the largest effect size for full-time telecommuting.
The increase in trust and autonomy is best captured in the self-determination dimension
within the construct of employee empowerment (Spreitzer, 1995). Employee empowerment
itself is an explanatory dimension of job satisfaction (Spreitzer, 1995; Comm & Mathaisel,
2000). It has consistently been linked to an increase in job satisfaction and in turn
organizational commitment (Laschinger, Finegan, Shamian & Wilk, 2004; Tummers, van
Merode & Landeweerd, 2006; Iverson & Roy, 1994). Within employee empowerment there
are three dimensions (Spreitzer, 1995). Of these three dimensions self-determination is most
fitting for this research, since it encompasses the level of autonomy an employee has in
determining its work activities, and the level of trust an employee experiences from its
supervisor. Taking into account the important role of autonomy in job satisfaction, and
18
therefore in all dimensions of organizational commitment, it is expected for self-
determination to mediate the relationship to all dimensions of organizational commitment.
Therefore, the following is hypothesized:
H2: Self-determination acts as a partial mediator in the telecommuting – organizational
commitment relationship for all dimensions of organizational commitment
Eckhardt’s 2019 case study of two companies switching to full-time telecommuting showed
great concerns of the managers regarding social isolation of its full-time telecommuting
employees (Eckhardt, Giordano, Endter & Somers, 2019). As stated, a lack of social
interaction and social support are hypothesized to influence the full-time telecommuting –
organizational commitment relationship (Golden & Veiga, 2008; Madlock, 2013; Fay &
Kline, 2011). Similar to social interaction, social support influences organizational identity
and job satisfaction (Ashforth & Mael, 1989; Battacharya, Rao & Glynn, 1995;
Goldsborough, 2000; Nilles, 1994).
Social support is defined as “the degree to which individuals perceive that they have positive
social relationships with others in the workplace” (Wiesenfeld, Raghuram & Garud, 2001;
Aspinwall & Taylor, 1992; Wanberg & Banas, 2000).
Since full-time telecommuters have a certain spatial distance, the level of social support may
be perceived different. Especially since work-based social support is signified by individuals
in close proximity (Lim, 1996; Aspinwall & Taylor, 1992). Full-time telecommuters generally
lack work-based individuals in close proximity. Furthermore, a full-time telecommuter’s
relationship with its supervisor or co-worker may be more task-based, with a lack of informal
meetings. Task-based relationships may be beneficial for efficiency, but it can also mean the
employee may lack certain intrapersonal connections with managers and coworkers that can
give a sense of social support (Fay & Kline, 2011; Fay & Kline, 2012).
It is expected that a higher social support from within the company partially negates the
negative effects of full-time telecommuting. It is expected for social support to represent
meaningful relationships, thus influencing Affective commitment. Social support may
increase identification with the organization’s culture, which in turn increases Normative
commitment. In addition, having strong relationships with peers, supervisors and superiors
may represent certain sunk costs in these relationships, which may influence the cost of
leaving, and thus Continuance commitment.
19
Taking into account the positive influence social support has on organizational identification
and job satisfaction, and subsequently on organizational commitment, the following is
hypothesized:
H3: Social support has a positive interaction with Affective commitment, but no interaction
with Continuance and Normative commitment.
As stated previously, organizations that allow full-time telecommuting are expected to have
mechanisms in place to negate negative effects experienced by high-intensity telecommuters;
primarily lack of social support and social interaction. This research aims to understand how
these negative factors can be negated, and what role these negative factors play in the
telecommuting – organizational commitment relationship.
Even though there are more possibilities for social interaction with co-workers for
telecommuters in the digital age (Kizza, 2007), it is possible for a full-time telecommuter to
not physically meet any co-worker during its employment. This has not been factored in
during previous research, since non-telecommuters to nearly full-time telecommuters always
have a certain degree of physical face-time.
The extent of contact between an individual and the organization is one of the three
determining factors of organizational identification (Ashforth & Mael, 1989; Bhattacharya,
Rao & Glynn, 1995). For full-time telecommuters this contact can be neglected. Several
tangible markers of organizational identification are missing when never physically seeing
your co-workers (Pratt & Raphaeli, 1997).
In addition, lack of contact can lead to feelings of isolation and unhappiness, which
significantly influences job satisfaction (Goldsborough, 2000; Nilles, 1994).
Virtual face-time does not always fulfill this social interaction the same as physical face-time
(Riva, 1999; Okada, Maeda, Ichikawaa & Matsushita; 1994; Wellman, 1996). In addition,
several companies have indicated communication and social interaction is a challenge when
not meeting physically (Mazzitti & Sullivan, 2018; Disadvantages of Remote Work, 2018).
Thus, physical face-time can be of great importance in influencing organizational
identification and job satisfaction for full-time telecommuters, which in turn affects
organizational commitment.
Interaction between social support and physical face-time is expected, since more physical
face-time could increase the social support. However there are key differences between the
20
two constructs. Whereas physical face-time measures the presence of physical social
interactions with coworkers, social support measures the perceived quality of any interactions
with peers, superiors and the direct supervisor.
Physical face-time with coworkers is always present for non-, or moderate-telecommuters. It
is expected for physical face-time to have a positive effect on Affective commitment, since
that dimension captures this form of social contact. Therefore the following is hypothesized
only for the full-time telecommuting group:
H4: A higher frequency of physical face-time has a positive effect on Affective commitment for
full-time telecommuting employees, but not on Normative- and Continuance commitment.
Based on the hypotheses, The conceptual model is presented. The model includes
telecommuting intensity as the independent variable, with self-determination as a partial
mediator for the telecommuting intensity – organizational commitment relationship, and
social support as a moderator. There is also an expected direct effect for telecommuting
intensity on organizational commitment. The effect of frequency of physical face-time is only
hypothesized for full-time telecommuters, on Affective commitment.
Figure
1: Conceptual model
21
4. Methodology
In this section the research design of this study is elaborated, after which the methods of data
collection are presented, followed by the methods of analysis for this data.
This research has quantitative properties, and uses the four-step approach:
1. Operationalization variables
a. Establishing the definition and characteristics of the variables of interest
2. Construction questionnaire
a. Theoretical justification for used measures
b. Adding additional items for control variables
3. Sample selection and preliminary data collection
a. Conduct preliminary analysis
b. Sample selection based on results preliminary analysis
4. Performing survey and data analysis
a. Distribution of survey via Qualtrics
b. Data analysis of results using descriptive- and inferential statistics
4.1 Operationalization variables
The data was collected using a cross-sectional survey. In order to collect the correct data for
each relevant variable, the variables needed to be operationalized correctly for measurement
and analysis.
4.1.1 Dependent variable
Organizational commitment, as defined in the literature review, was measured with the three
dimensions of Allen and Meyer (1990). It was measured using eight survey items for each
dimension. These items have been previously extensively tested for reliability and validity,
and were shown sufficiently consistent (McGee & Ford, 1987; Nunnaly, 1978). In different
settings, the measure displayed convergent and discriminant validity (Karim & Noor, 2006;
Cohen, 1996; Dunham, Grube & Castaneda, 1994). Affective commitment was scored as a
mean of the eight items, and is named acmean in the datafile. The same was done for ncmean
(Normative commitment) and ccmean (Continuance commitment).
4.1.2 Independent variable
Telecommuting intensity, as defined in the literature review, was measured using three
categories: no telecommuting, full-time (exclusive) telecommuting and moderate
telecommuting for all values in between. These categories have a clear distinction between
22
intensities, which allows for a focus on the full-time telecommuting group for hypothesis four.
This study focused on categorical differences for hypotheses one, two and three, and on full-
time telecommuting for hypothesis four, therefore a detailed examination within the moderate
telecommuting group was outside the scope of this research. Whereas the categorical
distinction allowed for efficient analyzing of the full-time telecommuting group. The variable
regarding telecommuting intensity is named intensity in the datafile. The variable name non-
telecommute was used for non-telecommuters, moderate for moderate telecommuters and
exclusive for full-time telecommuters.
4.1.3 Moderating and mediating variables
Self-determination, as defined in the hypothesis development, was measured using three items
from the employee empowerment survey of Spreitzer (1995). These three items determine the
level of autonomy and self-determination an employee experiences and have previously been
positively tested for convergent and discriminant validity (Spreitzer, 1995). Self-
determination was scored using the mean of the three items, and is named selfdetmean in the
datafile.
Social support, as defined in the hypothesis development, was measured using three items
from Wiesenfeld, Raghuram and Garud (2001). These items measure the social support an
employee experiences from co-workers, supervisors and upper management and have been
formulated specifically for the organizational identification context. These have been named
socialpeers, socialsupervisor and socialsuperior, respectively. Social support was scored as
the mean of the three items, and is named socialsuppmean in the datafile. Alternatively, social
support can be treated independently for each item.
Physical face-time, defined as the frequency of physical meetings with co-workers, was
measured only for the full-time telecommuting group, since non-full-time telecommuters were
expected to have frequent physical face-time due to being present at an office at least once a
week. This measure included six categories, ranging from no face-time to face-time once a
week. This variable is named physical in the datafile.
4.1.4 Control variables
Control variables were distilled from the literature review, and were age, gender, position,
tenure, industry, income and education. These variables have been shown in previous
literature to have a possible influence on organizational commitment and are also expected to
have a degree of influence in this research, and therefore should be controlled for.
23
4.1.5 Summary
The definitions and characteristics of the relevant variables are captured in Table 1, below:
Variable Definition Measure Scale
Organizational
commitment
A psychological link between the employee
and his or her organization that makes it less
likely that the employee will voluntarily
leave the organization
Eight items as
statements on
each dimension,
24 total
7-point Likert:
"Strongly
disagree" to
"Strongly agree"
Telecommuting
intensity
Individuals who telecommute: substitute time
normally spent in the office with time spent
working away from other employees, they do
so for a few hours a week to full-time, are
part of a larger organization, work principally
within their home during telecommuting
periods and use some form technology for
communication and information in order to
interact with other members of the
organization.
Full-time telecommuting is defined as
“exclusively telecommuting all working
hours”
One item
Ordinal, three
categories: "No
telecommuting",
"Moderate
telecommuting",
"Full-time
telecommuting"
Self-determination
The level of autonomy an employee has in
determining its work activities and the level
of trust an employee experiences of its
supervisor
Three items
7-point Likert:
"Strongly
disagree" to
"Strongly agree"
Social support
The degree to which individuals perceive that
they have positive social relationships with
others in the workplace
Three
independent
items
7-point Likert:
"Strongly
unsupportive" to
"Strongly
supportive"
Physical face-time The frequency of physical meetings with co-
workers One item
Ordinal, six
categories
ranging from
"Never" to
"More than once
a week"
Control variables Various
Seven items on
personal
characteristics
Nominal and
ordinal scales
Table 1: Summary of definitions and characteristics relevant variables
24
4.2 Data collection
4.2.1 Sample
A preliminary survey and data analysis have been conducted in order to test the response rate
and the survey items. This preliminary survey tested two different samples. The first sample
was a collection of 49 companies that are self-defined as “remote-only”; these are companies
that employ forms of full-time telecommuting. These 49 companies had an estimated
minimum of 980 employees. This sample has been collected using the website
remoteonly.org, where companies can list themselves as proponents and enablers of full-time
telecommuting. The companies within the sample were approached via e-mail to participate in
the survey, the invitations were coupled with monetary incentives for both company and
participants. From this sample a response rate of two individual respondents was realized,
indicating a response rate of roughly 0,2%. Since this response rate was not sufficient or
encouraging for this research, alternative sampling methods had to be taken into account.
Considering the timeframe of this research, a convenience sample was deemed the best choice
for this research. There were different methods for convenience sampling to choose from.
When considering the dependence of full-time telecommuters on the internet, an online
convenience sample was more likely to collect data on all intensities of telecommuting than
offline convenience sampling (Kizza, 2007). There are several online platforms where so-
called “workers” complete online jobs, such as surveys, for monetary compensation.
Considering online convenience sampling, the online platform of Amazon Mechanical Turk
(MTurk) was chosen for this research due to existing studies on the reliability and validity of
the population on this platform (Paolacci & Chandler, 2014; Buhrmester, Kwang & Gosling,
2011). This research showed that MTurk has a demographic that is representative of internet
users, where most samples have met a certain standard of reliability (Paolacci & Chandler,
2014; Shapiro, Chandler & Mueller, 2013). In addition, by using this sampling platform, this
research will be able to contribute to a vast body of research already existing on the
platform’s population (Landers & Behrend, 2015).
To test the reliability for this research, a second preliminary survey of 379 respondents taken
on the MTurk platform, aimed to replicate the linear relationship of telecommuting and
organizational commitment. The MTurk platform verifies identity, so a worker can only
complete a survey once, and was rewarded $0,35 for completing the survey. This
compensation does not influence reliability but rather only the speed of data gathering
(Paolacci & Chandler, 2014; Buhrmester, Kwang & Gosling, 2011). The preliminary survey
25
ran on the MTurk platform indicated reliable results regarding extent of telecommuting on
organizational commitment. Prior results were replicated using an independent samples T-
test, where it was shown that absence of telecommuting lead to a lower organizational
commitment compared to when telecommuting was available. These results are consistent
with prior studies indicating a positive linear relationship between telecommuting extent and
organizational commitment, and can be found in Appendix 1 (Martin & MacDonnell, 2012).
This indicates a certain validity of the sample of MTurk for this research. Certainly, the
MTurk sample is a convenience sample and therefore not fully reliable or valid, however
taking into account the timeframe of this research, the low response rate of the original
sample and the results of the preliminary survey, MTurk is deemed sufficiently representative
and valid for this research, and therefore was used as the sample of choice for the main
survey. Thus, the sample used for this main study was a convenience sample of 750 MTurk
workers, who were awarded $0,25 each for participation in the survey.
4.2.2 Survey
The survey used in the data collection process consists of 42 items, the complete survey can
be found in Appendix 2. Nine items are based on personal characteristics. Three items are
used to determine the social support. Another three items are used to establish the level of
self-determination. Three items are used to determine the availability and extent of
telecommuting, and the frequency of physical face-time with a co-worker. Only respondents
that indicated to telecommute full-time received the question to assess physical face-time. In
order to measure organizational commitment a total of 24 items are used, eight items for each
dimension of organizational commitment. 11 questions of the organizational commitment
measurement are reverse coded. The survey was distributed through the Qualtrics platform,
which is a widely used platform for distributing online surveys (Ritter & Sue, 2007).
Item type
Number
of items
Control questions
9
S
ocial support
3
Self
-
determination
3
T
elecommuting intensity
3
O
rganizational commitment
24
Total
42
Table 2: Overview item types survey
26
4.3 Analysis
The data was analyzed using Stata analytical software, version 15.
4.3.1 Datafile
Prior to the analysis, the data file was operationalized. In addition to naming and labeling the
relevant variables, some data has been removed from the datafile. To comply with General
Data Protection Regulations all personal data that Qualtrics automatically collects, was
removed prior to the analysis. This means that IP-address information, e-mail addresses and
longitudinal and lateral coordinates were removed from the datafile.
4.3.2 Reliability
To test the reliability of the multi-item measures, a measurement of the Cronbach’s alpha was
done for each multi-item measure. This research didn’t use an arbitrary 0.7 cut-off value for
Cronbach’s alpha to determine internal consistency of the measure (Lance, Butts & Michels,
2006). Instead, each Cronbach’s alpha was assessed independently. Outlying alpha scores
were interpreted independently and assessed for internal consistency. Normality of data was
assessed, and accordingly the best model for testing the hypotheses was formed.
4.3.3 Models of analysis
Different statistical models and methods were used to test the hypotheses.
For hypotheses 1a, 1b and 1c, a baseline simple regression model was formulated and used to
test the levels of commitment among different levels of telecommuting intensity. For each
hypothesis, one regression was run. Additional robustness tests indicated whether the chosen
model was the best fit.
Hypothesis 2, which implies a partial mediating effect, was tested using the three-step method
for mediation by Baron and Kenny (1986). This test indicated if there is a mediation effect,
and wether this effect is full-mediation or partial-mediation. Step one was to do a simple
regression where telecommuting intensity predicts organizational commitment, similar to
hypothesis 1. In step two, the mediating variable self-determination was predicted by
telecommuting intensity using a simple regression. In step three, the mediator self-
determination predicted organizational commitment using a simple regression. In step four,
the full model was used for a multiple regression, where the mediator and independent
variable are added in the analysis. If mediation was confirmed, additional tests for mediation
were done, such as Sobel test and the Monte Carlo Method for Assessing mediation, to further
establish the effect (Selig & Preacher, 2008; Sobel, 1982).
27
Hypothesis 3, which proposes a moderation effect, was tested using a simple baseline
regression, where the interaction terms that represent the moderating effect were included.
This is done for each separate dimension of organizational commitment. Before reporting the
results, the full model including all three moderators, combined with each telecommuting
intensity, were tested for multicollinearity. There is a risk of collinearity since social support
experienced may be similar across the distinct telecommuting intensities. For example, a
language barrier may influence all items of social support, regardless of telecommuting
intensity. Therefore the social support interaction variables are expected to not be
independent. The extent of multicollinearity was tested using a variance inflation factor (VIF).
This measure indicates the multiple a coefficient experiences than it would have been if the
variable was linearly independent. Generally, a rule of thumb is used where if the VIF
exceeds a score of 10, multicollinearity may be severe enough to influence the results
(O’Brien, 2007). However, this rule of thumb needs to be interpreted in context and can’t
serve as sole argumentation for multicollinearity problems. In the case of multicollinearity
and difficulties to distinct between telecommuting intensities, a subsample analysis where
each intensity is regressed on each dimension of organizational commitment, is deemed the
best fit.
Hypothesis 4, which tests the effect of extent of physical face-time on organizational
commitment for full-time telecommuters, was tested using a simple regression for each
dimension of organizational commitment, and was further inspected for all levels of physical
face-time intensity using a one-way ANOVA. Since the sample is nonrandom, selection bias
may influence the results for OLS models. For hypothesis 4, this was tested using a Heckman
correction model to account for possible sample selection bias for full-time telecommuting
intensity, which in turn may increase statistical causality (Certo, Busenbark, Woo &
Semadeni, 2016). Previous research indicated certain predictor variables of telecommuting
intensity (Singh, Paleti, Jenkins & Bhat, 2013; Yen, 2000). In this Heckman model, the
availability of telecommuting, travel distance to workplace, age, education and income, were
used to predict the likelihood of a respondent telecommuting full-time.
28
5. Results
In this section of the report, the results of the research are presented. First, the reliability of
the measures was tested. Then, for each hypothesis, the results are presented. For the sake of
parsimony, only the categorical or nominal control dummies that are significant in at least one
model are displayed in the results tables. However, in the regression models all dummies were
included.
The data collection took place from November 13
th
till November 20
th
, 2019, and resulted in
808 responses. Incomplete responses were removed, resulting in 721 complete responses.
5.1 Reliability of measures
For all multi-item measures, Cronbach’s alpha was utilized to indicate the reliability of the
measure. The Cronbach’s alpha of all relevant measures is shown in Table 3. The
accompanying Stata outputs and specific item correlations can be found in Appendix 3.2.
Measure Cronbach's Alpha
Affective commitment
0.72
Continuance commitment
0.79
Normative commitment
0.76
Self-determination
0.84
Social support
0.39
Table 3: Cronbach's Alpha of relevant measures
Social support has a Cronbach’s alpha of .39. This is not an acceptable score, and therefore
the three items have to be treated independently. This was expected, since every item asks
about a different, independent relationship (co-workers, supervisors and superiors).
29
5.2 Distribution of data
The histograms, scatterplots and residual test
can be found in Appendix 3.2.
At first sight, the histograms of the data
distribution appear to depict a moderately
normal distribution. Scatterplots of the three
dimensions did not indicate a significant
number of outliers
.
The inter-quartile ranges test found two
severe outliers at a 5% significance level.
The Shapiro-Wilk test further emphasized
this, and found high probability to reject normality of the error terms.
According to the Gauss-Markov Theorem, the OLS estimate is the best linear estimator for
testing the hypotheses if the error terms have a mean of zero, they do not show serial
correlation and are homoscedastic (Harville, 1976).
The error terms have a mean of zero. A test of the residuals showed that there is no significant
correlation between the error terms. Homoskedasticity, or
constant variance, was tested in Stata. Heteroskedasticity
was confirmed by the Breush-Pagan/Cook-Weisberg test.
In the scatterplot of Figure 3, the heteroskedasticity does
not seem severe, and caused by several outliers. Still, for
the baseline model an additional robustness check needed
to be performed, using robust standard errors while
accounting for outliers.
Figure
2: Scatterplots and histograms of data distribution for dependent
variables
Figure 3: Scatterplot residuals error terms
30
5.3 Correlations Matrix
The correlations matrix shows a number of significant correlations between the variables.
However, there are no problematic effect sizes. Categorical and nominal control variables
were excluded from the matrix.
The three dimensions of organizational commitment and self-determination show significant
correlations. There are significant correlations between peer social support and the
dimensions of organizational commitment. Additionally, several correlations can be seen
between the telecommuting intensities.
Table 4: Correlations Matrix, n=721
31
5.4 Results hypotheses
The results of the hypotheses are discussed with a results table for each hypothesis. These
tables summarize the results. The Stata outputs and additional tables can be found in
Appendix 3. For the first hypothesis, a baseline model was constructed to test the main
relationship of telecommuting intensity and organizational commitment. Next, for each
hypothesis a distinct mediator or moderator was added and tested within the baseline model in
order to conclude about the hypotheses.
Several control variables were selected for the baseline model. These control variables have
shown in the literature review to have explanatory value for organizational commitment,
based on previous research. The control variables are age, gender, country, education level,
industry, position within the company, tenure and income level. Country, education level and
industry were treated as categorical or nominal variables. For the sake of parsimony, only the
significant and baselevel dummies for these control variables were included in the tables, the
regression model however included all dummies, which can be seen in the Stata inputs in
Appendix 3.
5.4.1 Results Hypothesis 1
Hypothesis 1 entails a comparison between the three telecommuting intensities regarding their
respective means on organizational commitment. The baseline regression was used to test this
hypothesis. The results are presented in Table 5.
This regression used the non-telecommuters as the baseline group against the full-time
telecommuters and moderate telecommuters. As seen in the regression, full-time
telecommuters have comparable Affective commitment as non-telecommuters, while
moderate telecommuters have significantly higher Affective commitment. Therefore,
hypothesis H1a is not supported.
The results indicate no significant differences between the telecommuting intensity groups for
Continuance commitment. Hypothesis H1b is supported.
For the Normative commitment dimension, a significant difference was recorded between the
non-telecommuting group and the full-time telecommuting group, where the non-
telecommuters have a lower mean than the full-time telecommuters. Concurrently, the
moderate telecommuters have comparable Normative commitment as the full-time
telecommuters, meaning hypothesis H1c is supported.
32
Several other significant relations are present in the three models. Tenure is of significant
positive influence for all dimensions of organizational commitment, however the effect size is
smaller than the other significant variables. For Normative commitment, which represents a
feeling of obligation to remain at an organization, three countries of origin have significant
negative influence on the commitment. Furthermore, two levels of education have a negative
effect on Normative commitment. Gender, with the baseline male, has a positive influence for
females on Continuance commitment.
Table 5: Results hypothesis 1
33
As mentioned, the data did not pass all OLS assumption requirements. Since a OLS
regression was used for the testing of hypothesis 1, additional robustness checks had to be
performed to check if the OLS model was indeed the best fit. Two main problems were
identified: presence of severe outliers, and heteroskedasticity.
First, the outliers had to be accounted for. A studentized residuals procedure removed the
severe outliers from the data. A subsequent regression, using the same baseline model,
showed differences in results compared to the OLS model for hypothesis 1. This model can be
found in Appendix 3.4. It could be concluded the outliers significantly influence the results.
Second, the influence of heteroskedasticity was tested by performing the baseline regression
with removed outliers, using robust standard errors. The results from this regression can be
seen in Appendix 3.4. When comparing the robust model with the removed outlier model, the
results are comparable, also coefficients are identical and standard errors very similar. These
are indications that heteroskedasticity is not a significant problem for the model (Auld, 2012).
When looking at the residual distribution in Figure 4, heteroskedasticity does not seem
prevalent. Outputs from the other dimensions of organizational commitment showed similar
results. Taking into account the previous established lack of significant correlation between
error terms, the heteroskedasticity errors in the baseline OLS model were seemingly caused
by outliers.
Figure 4: Distribution of residuals for baseline model with removed outliers
The outliers are indeed problematic for normality assumptions. However, these outliers are
part of the research population, and there is no theoretical justification for removing the
outliers, or reducing their effect compared to other datapoints. Removing the outliers would
steer the results and analysis in a way that is not justifiable. Thus, the original OLS model is
still deemed the best fit for the analysis of the hypotheses.
34
To test for multicollinearity, a variance inflation factor was assessed for the relevant variables
in each model. These are all well below the threshold of 10, with a VIF of 2.01 for the
moderate group, and a VIF of 2.06 for the full-time group, so no multicollinearity was found
within the baseline model for the variables of interest.
5.4.2 Results Hypothesis 2
Hypothesis 2 proposes a mediation effect for self-determination in the telecommuting –
organizational commitment relationship.
In order to test hypothesis 2, the three-step mediation test of Baron and Kenny (1986) was
used. This test establishes if self-determination has mediating properties in the researched
relationship, and wether this is partial-, or full-mediation. If any of the steps is insignificant,
there is no mediation. Full mediation is established when the mediator causes the independent
variable to become insignificant. Step one of the test was regressing the independent variable,
telecommuting intensity, on the mediator, self-determination. Step two was regressing the
mediator on the dependent variable, organizational commitment. Step three was testing the
full model with the mediator included.
In addition to the three-step test, Sobel test and Monte Carlo Method for Assessing Mediation
test were used to further establish the mediation effect. These two tests both assess
significance of the indirect effect of mediation. The difference being that the Monte Carlo test
performs better than Sobel when certain properties of the data are unknown.
The (indirect) effect sizes in the tables can be interepreted as the independent variable
coefficient for the three steps of Baron and Kenny (1986), and as the indirect effect of
mediation for Sobel and Monte Carlo.
Table 6: Mediation effect Affective commitment
35
For the Affective commitment dimension, self-determination acts as a full-mediator for non-
telecommuters. Moderate telecommuting has no significant effect on self-determination,
therefore mediation is not possible, regardless of the dependent variable. For full-time
telecommuters, self-determination acts as a partial mediator for Affective commitment.
For Continuance and Normative commitment, partial mediation was established for non-
telecommuters, and full mediation for full-time telecommuters. Hypothesis 2 is partly
supported.
Results are consistent among all three methods for assessing mediation. For all dimensions,
the indirect effect is a substantial part of the total effect. Whereas the (indirect) effect for non-
telecommuters is negative, this effect is positive for full-time telecommuters.
Table 8: Mediation effect Normative commitment
Table 7: Mediation effect Continuance commitment
36
5.4.3 Results Hypothesis 3
Hypothesis 3 proposes a moderating effect for social support in the telecommuting intensity –
organizational commitment relationship.
A full model was formed, including an interaction term for each social support item with each
intensity of telecommuting. This full model can be found in Appendix 3.6. For all subsequent
moderating models the original variables were automatically omitted from the tables by Stata
due to multicollinearity, and therefore could not be included.
The high variance inflation factor (VIF) for the full model indicates high multicollinearity.
For each model, the overall F is significant, (Prob > F = 0.000), however most corresponding
t-values are insignificant. This indicates possible problems due to multicollinearity.
Further testing of the original full model with a correlations matrix indicated large
correlations among the social support factors. When eliminating the distinction between the
telecommuting intensities within each moderator, a new model was formed where three
moderators were formulated by adding up the three intensity levels for each item of social
support. The generation of these moderators and the correlations matrix and the new model
can be found in Appendix 3.6.
This new model has a significantly lower VIF for the new moderating variables, below the
arbitrary threshold of 10 (O’Brien, 2007). However, the new model’s results cannot be
interpreted correctly. The moderators treat telecommuting intensity as a continuous variable,
which it is not. Therefore, a subsample analysis model is the only model of which results can
be correctly interpreted.
A subsample analysis was performed, where the effect of all forms of social support were
tested for each telecommuting intensity, for each dimension of organizational commitment.
The subsample analysis is presented in Table 9. The subsample analysis produces identical
results to the new model, when sorting the new model’s regression by telecommuting
intensity. The subsample analysis allows for a more detailed look into each telecommuting
intensity.
37
Table 9: Subsample analysis for testing moderating effect
38
Table 9 presents the results from the subsample analysis. These results depict the distinct
differences among the telecommuting intensities. The corresponding R-squared for the
subsample analysis is substantially higher than the new model’s, implying stronger
explanatory power, however this may also be caused by differences in sample size. The
results show that social support from peers is only significant for the moderate- and non-
telecommuters for Affective commitment. In the Continuance commitment dimension social
support from peers is only significant for the non-telecommuters. Social support from
superiors is only significant for moderate telecommuters for Continuance commitment.
Tenure is only significant for the moderate- and non-telecommuting groups across all
organizational commitment dimensions.
Some dimensions of social support have significant positive interactions across the
dimensions of organizational commitment, and for several telecommuting intensities.
Hypothesis 3 is therefore partially supported.
5.4.4 Results Hypothesis 4
Hypothesis 4 suggests a positive effect of physical face-time on Affective commitment, for
full-time telecommuters only. This was tested using the baseline regression, there is no need
to distinct between subsamples of telecommuting intensity, since physical face-time was only
recorded for full-time telecommuters. The results are presented in Table 11. The results show
that frequency of physical face-time is only of significance for the Continuance commitment
dimension of organizational commitment. Though not significant, the effect of physical face-
time on Affective commitment is negative. Therefore, hypothesis 4 is not supported.
Table 10: Oneway ANOVA physical face-time Affective commitment
A oneway ANOVA produced more insight in this relationship. It can be seen that the
Affective commitment is highest for the group that never or less than once a year has physical
face-time with a co-worker. There is a significant drop for the once a year, once a month and
39
once a week group. Oneway ANOVA’s for the other organizational commitment dimensions
indicate no significant differences between the frequencies of physical face-time.
The Heckman correction model was used to test for possible selection bias in the OLS model.
The results from the Heckman correction model are presented in Table 12. For all dimensions
of organizational commitment, the likelihood ratio is insignificant. This indicates the
Heckman correction model is not necessary, and not better than the original OLS model. This
is reinforced by the fact that no substantial differences were noted between the variables of
interest in the Heckman correction model and the OLS model.
Table 11: Results Hypothesis 4
40
When looking at the results for the sample selection predictors, it can be deduced that having
no (main) office, and having the option of telecommuting full-time increase the probability of
telecommuting full-time. The further away a respondent lives from the office, it becomes
significantly less likely to telecommute full-time, compared to a baseline of having no office
at all. A relatively small negative effect is observed for age, whereas when age increases, the
likelihood of telecommuting full-time decreases.
Table 12: Results Heckman correction model
41
6. Discussion and implications
In this section of the report, the results are analyzed. For every hypothesis the relevant
conclusions are drawn, and set side by side to other studies.
6.1 Discussion
Hypothesis H1a is not supported. No significant difference is found between the full-time
telecommuting group, and the non-telecommuters regarding Affective commitment. The
moderate telecommuting group has higher Affective commitment than the other two
telecommuting intensities. The results are consistent with earlier studies on telecommuting
intensity and organizational commitment (Golden & Veiga, 2005; Golden, 2006). These
studies showed a curvilinear relationship between telecommuting intensity and organizational
commitment, the results indicate that this curvilinear relationship is also applicable when
increasing the maximum telecommuting intensity from nearly full-time, to full-time. Which
implies that the full-time telecommuters do not have more successful mechanisms in place to
counteract the negative consequences, mainly social isolation, the nearly full-time
telecommuters experienced in previous studies, regarding Affective commitment (Golden &
Veiga, 2005; Golden, 2006). It can be argued that moderate telecommuters are in a certain
balance of telecommuting, that they experience the benefits of telecommuting, such as
increased autonomy, but not experience the negative consequences, such as social isolation.
Hypothesis H1b is supported. No significant differences are found between the
telecommuting intensities regarding Continuance commitment. This implies that
telecommuting intensity is not a determinant variable to the perceived cost of leaving an
organization. However, it can be argued that full-time telecommuters have more job options
due to the lack of geographical restrictions to the job criteria. This increase in job options
could reduce the cost of leaving, however this might be counteracted by the fact that full-time
telecommuting jobs are not that prevalent as of yet for every industry, leading to the non-
significant results.
Hypothesis H1c is supported. Full-time and moderate telecommuters have higher Normative
commitment than non-telecommuters. This implies that when telecommuting is available, the
employee has a higher feeling of obligation to remain at the organization. This could be
caused by an increase in perceived self-determination for increasing levels of telecommuting.
This is consistent with a previous study on psychological empowerment, where it was shown
42
that forms of psychological empowerment, such as self-determination and perceived trust,
positively influenced Normative commitment (Jha, 2011)
Further, from the results of the control variables in the hypothesis 1 baseline regression it can
be concluded that tenure is of influence on all dimensions of commitment. Similar to Cohen’s
1993 study, the effect size is relatively small and therefore not meaningful for discussion
(Cohen, 1993). For a few countries, Normative commitment is significantly lower, this could
be due to cultural differences, where the feeling of obligation to remain at an organization is
not culturally imbued. This cultural sensitivity is in line with a study done on the influence of
Transformational leadership on Normative commitment, where culture acted as a strong
moderator for Normative commitment (Ramachandran & Krishnan, 2009).
Females have higher Continuance commitment than males, perhaps due to it being more
difficult for females to find suitable work. This extra difficulty would increase the cost of
leaving an organization for females, and thus Continuance commitment. This is especially
true in India, where part of this study’s respondents originate from and 66% of women’s work
is unpaid, compared to 12% unpaid work for men (Rawat, Rawat, Sheikh & Kotwal, 2019).
Overall, for hypothesis 1 it can be concluded that full-time telecommuters have comparable,
or higher organizational commitment than non-telecommuters. Moderate telecommuters have
on average the highest organizational commitment.
Hypothesis 2 is partially supported. There are some mediating properties established for self-
determination. Self-determination does not serve as a mediator for the moderate
telecommuting group for any dimension of organizational commitment. It is possible this lack
of significance is caused by large variation of intensities within the moderate intensity group.
For example: the perceived self-determination of an employee that telecommutes five hours a
week is reasonably assumed to be different from an employee that telecommutes thirty hours
a week.
For the non-telecommuters, self-determination is a full mediator for the Affective
commitment dimension, and a partial mediator for the Continuance- and Normative
dimensions. For full-time telecommuters, self-determination is a partial mediator for the
Affective commitment dimension, and a full mediator for the Continuance- and Normative
dimensions. For all intensities, the pure mediation effect of higher self-determination on
organizational commitment is positive. For the non-telecommuters the total effect that is
perceived is negative. Which means that a possible lack of self-determination is the cause for
43
the lower commitment scores shown in hypothesis 1. For full-time telecommuters this
perceived total effect is positive, which shows that self-determination is an important positive
factor for the increase in commitment. The results are in line with previous research on
employee empowerment, job satisfaction and organizational commitment and show that self-
determination captures the distinct difference between telecommuting intensities regarding
employee empowerment (Laschinger, Finegan, Shamian & Wilk, 2004; Tummers, van
Merode & Landeweerd, 2006).
For hypothesis 2 it can be concluded that self-determination functions as an important
mediator of organizational commitment. Self-determination explains partially, or fully, an
organizational commitment increase for full-time telecommuters and a decrease for non-
telecommuters.
Hypothesis 3 is partially supported. Social support from peers is the most important
moderator out of the three social support moderators. This social support from peers is most
important for the moderate and non-telecommuting groups for Affective commitment. Social
support from peers is not of influence on the Affective commitment of full-time
telecommuters. Therefore, mechanisms that involve stimulating the social support are not
necessarily effective for increasing organizational commitment for full-time telecommuters.
The results of moderate- and non-telecommuters are in line with previous research on the
telecommuting intensity – organizational commitment relationship, where it was found that
social support received influenced the level of commitment (Golden & Veiga, 2008; Madlock,
2013; Fay & Kline, 2011). Influence of social support on full-time telecommuting –
organizational commitment relationship is not prior researched, and the dissimilarity of
significance with the other telecommuting intensities is notable. Given prior results on the
negative effects of social isolation on job satisfaction, and the increased prevalence of social
isolation for full-time telecommuters, it is more likely that full-time telecommuters find their
social support from outside the company, for example at co-working spaces.
To summarize, social support from peers is the only social support item to significantly
influence the telecommuting intensity – organizational commitment relationship, and only for
the moderate- and non-telecommuters. Therefore, regarding full-time telecommuting, social
support (from peers) should not necessarily be accounted for, within the organization.
Hypothesis 4 is not supported. The frequency of physical face-time is not of influence on the
Affective commitment of full-time telecommuters. When looking at physical face-time as a
44
mechanism of increasing social support, the results are comparable to the results of hypothesis
3. When further inspecting the effect of the distinct frequency of physical face-time on
Affective commitment, it can be deduced that physically meeting less than once a year, or
more than one a month, yields higher Affective commitment for full-time telecommuters than
any frequency in between. So when implementing a mechanism to enhance physical face-
time, the frequency should be accounted for.
From the discussion section, several important managerial and academic implications can be
formulated.
6.2 Managerial implications
One of the most important takeaways from this research is regarding the new phenomenon of
telecommuting full-time. This study shows that full-time telecommuting is not worse for
organizational commitment than non-telecommuting, and is partly on par with moderate
telecommuting. Therefore, a manager should not be afraid of a decrease in organizational
commitment when implementing full-time telecommuting in its organization.
There are, however, several factors to take into account when implementing full-time
telecommuting.
First, regarding self-determination, and its effects on perceived trust and autonomy within the
job, a manager should aim to keep this intact when implementing full-time telecommuting.
Mechanisms that reduce self-determination will harm its positive influence on organizational
commitment. Likewise, when telecommuting is not an option for the organization,
implementing systems to increase self-determination will have a positive effect on
organizational commitment.
Second, when implementing full-time telecommuting no extra mechanisms are required to
enhance social support. Social support from peers, supervisors and superiors are not effective
on organizational commitment for full-time telecommuters. Therefore, when aiming to
counteract possible social isolation, other external methods should be examined, such as local
co-working spaces. This may indicate a new trend, where an employee’s colleague does not
necessarily work at the same company. This does not mean however, that social support
measures should be abolished altogether. Moderate- and non-telecommuters’ organizational
commitment still benefits from social support.
Thirdly, when trying to implement countermeasures for social isolation using physical face-
time with co-workers for full-time telecommuters, the results show it is preferable to either set
45
up meetings more than once a month, or less than once a year. Anything in between will do
more harm than good, regarding Affective commitment.
6.3 Academic implications
This research definitively shows that when researching the relationship of telecommuting
intensity on organizational commitment, organizational commitment should not be treated as
a singular dimension. The three dimensions of organizational commitment are distinct and
lead to mutually different results. The distinction between the three dimensions allow for a
more detailed analysis of organizational commitment, such as the effect of physical face-time
on Affective commitment, the influence of gender on Continuance commitment, or the
negative effect a country has on Normative commitment.
Normative commitment is shown to be substantially influenced by certain countries and
cultures. Also, the influence of gender on Continuance commitment may be dependent of the
state of gender equality in that country. Therefore when studying organizational commitment,
the culture of respondents should be accounted for, especially when selecting sampling
methods.
The new phenomenon of full-time telecommuting has shown itself to differ from prior
researched nearly full-time telecommuting. When researching telecommuting intensity, the
full-time distinction should be included in the research in order to get a complete picture.
Self-determination is shown to be an important mediator in the telecommuting intensity –
organizational commitment relationship. Further enforcing the fact that employee
empowerment is of importance when studying this relationship.
The sampling method was not the most preferred one for this research. Nonetheless, this
research adds to the information about the organizational commitment characteristics of the
population on the Amazon Mechanical Turk platform.
6.4 Future research
This study opens up new interesting pathways for future research. The effects of certain
cultures on the Normative commitment dimension are notable, and it would be interesting to
further research the distinct differences between cultures and countries and their effects on
Normative commitment.
The influence of gender on the Continuance commitment dimension implies that this effect is
based on certain inequalities between the gender’s job availability statistics. It would be
46
interesting to further research the moderating effect of a country’s job market gender
(in)equality, on Continuance commitment of employees in said country.
The increased prevalence of full-time telecommuting, and the accompanying results from this
research, motivate a more detailed look into this telecommuting intensity and its effects on
several firm-related outcomes, but also on psychological and social outcomes. The lack of
influence of social support on organizational commitment for full-time telecommuters is
noteworthy. Social support was otherwise deemed as a valid predictor of job satisfaction and
thus organizational commitment. Future research on full-time telecommuters should aim to
determine the predictors of job satisfaction for full-time telecommuters, and which
mechanisms are responsible for the effects.
In order to fully conclude about causality of telecommuting intensity on firm-related
outcomes, an experiment would be the most conclusive method of research. Although a
challenging proposition, an experimental design where equally representative groups are
assigned a telecommuting intensity within an organization, would garner the most reliable and
valid results regarding this phenomenon.
6.5 Limitations
The main limitation of this research is the fact that the sampling method is not random. This
has a negative influence on the validity of the results and affects the strength of causal claims.
Even though a preliminary analysis assessed the reliability of the sample, and the timeframe
of the research hindered a more extensive sampling method, a more valid sampling method is
preferred. In the results section, an attempt is made to identify the specific selection bias
present in the sample using the Heckman correction test, which did not indicate a significant
selection bias in the results. Additional testing of selection bias to address the sampling
problems would have been preferred.
An additional limitation is present in the operationalization of the telecommuting intensity
variable. It is preferred to operationalize telecommuting intensity as a continuous variable, so
the specific differences between telecommuting intensities can be studied in more detail. In
addition, telecommuting intensity as a continuous variable allows to distinguish the optimum
amount of telecommuting for the maximum organizational commitment.
In this research, telecommuting intensity is categorical. This is a deliberate choice since the
focus of the research was not on the moderate telecommuting group, but on the full-time
telecommuting group and its comparison with the other two intensities. Operationalizing
47
telecommuting intensity as a categorical variable allowed for the research to efficiently
distinguish between the three categories and look at full-time telecommuters in a more
detailed view.
Acknowledgements
I would like to thank my supervisor, Francis Park, for the helpful mentoring sessions and his
quick responses to my most urgent questions. I would also like to acknowledge my support
team: Sophie, Anita and Noud for their continued practical and emotional support during this
Master.
48
References
Allen, N. J., & Meyer, J. P. (1990). The measurement and antecedents of affective, continuance and
normative commitment to the organization. Journal of Occupational Psychology, 63(1), 1–18.
Allen, T. D., Golden, T. D., & Shockley, K. M. (2015). How effective is telecommuting? Assessing the
status of our scientific findings. Psychological Science in the Public Interest, 16(2), 40–68.
Anderson, A. J., Kaplan, S. A., & Vega, R. P. (2015). The impact of telework on emotional experience:
When, and for whom, does telework improve daily affective well-being? European Journal of Work
and Organizational Psychology, 24(6), 882–897.
Ashforth, B. E., & Mael, F. (1989). Social identity theory and the organization. Academy of Management
Review, 14(1), 20–39.
Aspinwall, L. G., & Taylor, S. E. (1992). Modeling cognitive adaptation: A longitudinal investigation of the
impact of individual differences and coping on college adjustment and performance. Journal of
Personality and Social Psychology, 63(6), 989.
Auld, C. (2012). The Intuition of Robust Standard Errors. Economics, Econometrics, Etc.
Avery, C., & Zabel, D. (2001). The flexible workplace: A sourcebook of information and research.
Greenwood Publishing Group.
BAILEY, N. B. K. D. E., & Kurland, N. B. (1999). The advantages and challenges of working here, there,
anywhere, and anytime. Organizational Dynamics, 28(2), 53–68.
Baker, E., Avery, G. C., & Crawford, J. D. (2007). Satisfaction and perceived productivity when
professionals work from home. Research & Practice in Human Resource Management.
Balfour, D. L., & Wechsler, B. (1996). Organizational commitment: Antecedents and outcomes in public
organizations. Public Productivity & Management Review, 256–277.
49
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological
research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social
Psychology, 51(6), 1173.
Becker, H. S. (1960). Notes on the concept of commitment. American Journal of Sociology, 66(1), 32–40.
Bettis, R. A., Ethiraj, S., Gambardella, A., Helfat, C., & Mitchell, W. (2016). Creating repeatable
cumulative knowledge in strategic management: A call for a broad and deep conversation among
authors, referees, and editors. Strategic Management Journal, 37(2), 257–261.
Bhattacharya, C. B., Rao, H., & Glynn, M. A. (1995). Understanding the bond of identification: An
investigation of its correlates among art museum members. Journal of Marketing, 59(4), 46–57.
Blegen, M. A. (1993). Nurses’ job satisfaction: A meta-analysis of related variables. Nursing Research.
Bolsu, R. (n.d.). What is Employee Ghosting? The Dark Side of ‘At-Will’ Employment. Retrieved 20
December 2019, from https://blog.namely.com/what-is-employee-ghosting
Brown, M. E. (1969). Identification and some conditions of organizational involvement. Administrative
Science Quarterly, 346–355.
Buchanan, B. (1974). Building organizational commitment: The socialization of managers in work
organizations. Administrative Science Quarterly, 533–546.
Buhrmester, M., Kwang, T., & Gosling, S. D. (2016). Amazon’s Mechanical Turk: A new source of
inexpensive, yet high-quality data?
Bullis, C., & Bach, B. W. (1989). Socialization turning points: An examination of change in organizational
identification. Western Journal of Communication (Includes Communication Reports), 53(3), 273–
293.
Caldow, J. (2009). Working outside the box: A study of the growing momentum in telework. Institute for
Electronic Government. IBM Corporation, 14.
50
Caykoylu, S., Egri, C. P., Havlovic, S., & Bradley, C. (2011). Key organizational commitment antecedents
for nurses, paramedical professionals and non-clinical staff. Journal of Health Organization and
Management, 25(1), 7–33.
Certo, S. T., Busenbark, J. R., Woo, H., & Semadeni, M. (2016). Sample selection bias and Heckman
models in strategic management research. Strategic Management Journal, 37(13), 2639–2657.
Chang, A., & Li, P. (2015). Is economics research replicable? Sixty published papers from thirteen journals
say’usually not’. Available at SSRN 2669564.
Cheney, G., & Tompkins, P. K. (1987). Coming to terms with organizational identification and
commitment. Communication Studies, 38(1), 1–15.
Cohen, A. (1993). Age and tenure in relation to organizational commitment: A meta-analysis. Basic and
Applied Social Psychology, 14(2), 143–159.
Cohen, A. (1996). On the discriminant validity of the Meyer and Allen measure of organizational
commitment: How does it fit with the work commitment construct? Educational and Psychological
Measurement, 56(3), 494–503.
Cohen, A., & Gattiker, U. E. (1994). Rewards and organizational commitment across structural
characteristics: A meta-analysis. Journal of Business and Psychology, 9(2), 137–157.
Comm, C. L., & Mathaisel, D. F. (2000). Assesssing employee satisfaction in service firms: An example in
higher education. The Journal of Business and Economic Studies, 6(1), 43.
Cramer, D. (1993). Tenure, commitment, and satisfaction of college graduates in an engineering firm. The
Journal of Social Psychology, 133(6), 791–796.
Crossan, G., & Burton, P. F. (1993). Teleworking stereotypes: A case study. Journal of Information
Science, 19(5), 349–362.
Crossman, A., & Lee‐Kelley, L. (2004). Trust, commitment and team working: The paradox of virtual
organizations. Global Networks, 4(4), 375–390.
51
Desanctis, G., & Monge, P. (1999). Introduction to the special issue: Communication processes for virtual
organizations. Organization Science, 10(6), 693–703.
Disadvantages of Remote Work | Mazzitti & Sullivan EAP. (2018, October 11). Retrieved 20 December
2019, from Mazzitti and Sullivan EAP website: https://www.mseap.com/disadvantages-remote-work/
dnevogt. (2019, April 20). 5 Common Challenges of Managing Remote Employees. Retrieved 20 December
2019, from Hubstaff Time Tracking Software website: https://blog.hubstaff.com/remote-management-
problems/
Dourish, P., & Bly, S. (1992). Portholes: Supporting awareness in a distributed work group. Proceedings of
the SIGCHI Conference on Human Factors in Computing Systems, 541–547. ACM.
Dunham, R. B., Grube, J. A., & Castaneda, M. B. (1994). Organizational commitment: The utility of an
integrative definition. Journal of Applied Psychology, 79(3), 370.
Dutton, J. E., Dukerich, J. M., & Harquail, C. V. (1994). Organizational images and member identification.
Administrative Science Quarterly, 239–263.
Eckhardt, A., Giordano, A., Endter, F., & Somers, P. (2019). Three Stages to a Virtual Workforce. MIS
Quarterly Executive, 18(1), 5.
Fay, M. J., & Kline, S. L. (2011). Coworker relationships and informal communication in high-intensity
telecommuting. Journal of Applied Communication Research, 39(2), 144–163.
Fay, M. J., & Kline, S. L. (2012). The influence of informal communication on organizational identification
and commitment in the context of high-intensity telecommuting. Southern Communication Journal,
77(1), 61–76.
Ferrazzi, K. (2014). Getting virtual teams right. Harvard Business Review, 92(12), 120–123.
Freeman, R. B. (1977). Job satisfaction as an economic variable. National Bureau of Economic Research
Cambridge, Mass., USA.
52
Future Workforce Report: Remote Work Is Set to Go Mainstream but Is Your Business Ready? (2018,
March 6). Retrieved 20 December 2019, from Upwork Blog website:
https://www.upwork.com/blog/2018/03/future-workforce-report-remote-work-mainstream/
Gainey, T. W., Kelley, D. E., & Hill, J. A. (1999). Telecommuting’s impact on corporate culture and
individual workers: Examining the effect of employee isolation. SAM Advanced Management Journal,
64(4), 4–4.
Gajendran, R. S., & Harrison, D. A. (2007). The good, the bad, and the unknown about telecommuting:
Meta-analysis of psychological mediators and individual consequences. Journal of Applied
Psychology, 92(6), 1524.
Gajendran, R. S., Harrison, D. A., & Delaney‐Klinger, K. (2015). Are telecommuters remotely good
citizens? Unpacking telecommuting’s effects on performance via i‐deals and job resources. Personnel
Psychology, 68(2), 353–393.
Golden, T. D. (2006). Avoiding depletion in virtual work: Telework and the intervening impact of work
exhaustion on commitment and turnover intentions. Journal of Vocational Behavior, 69(1), 176–187.
Golden, T. D., & Veiga, J. F. (2005). The impact of extent of telecommuting on job satisfaction: Resolving
inconsistent findings. Journal of Management, 31(2), 301–318.
Golden, T. D., Veiga, J. F., & Dino, R. N. (2008). The impact of professional isolation on teleworker job
performance and turnover intentions: Does time spent teleworking, interacting face-to-face, or having
access to communication-enhancing technology matter? Journal of Applied Psychology, 93(6), 1412.
Goldsborough, R. (2000). Making telecommuting work. Com. L. Bull., 15, 34.
Grusky, O. (1966). Career mobility and organzational commitment. Administrative Science Quarterly, 488–
503.
Hall, D. T., Schneider, B., & Nygren, H. T. (1970). Personal factors in organizational identification.
Administrative Science Quarterly, 176–190.
53
Harker Martin, B., & MacDonnell, R. (2012). Is telework effective for organizations? A meta-analysis of
empirical research on perceptions of telework and organizational outcomes. Management Research
Review, 35(7), 602–616.
Harville, D. (1976). Extension of the Gauss-Markov theorem to include the estimation of random effects.
The Annals of Statistics, 4(2), 384–395.
Herzberg, F., Mausnes, B., Peterson, R. O., & Capwell, D. F. (1957). Job attitudes; review of research and
opinion.
Hill, E. J., Hawkins, A. J., & Miller, B. C. (1996). Work and family in the virtual office: Perceived
influences of mobile telework. Family Relations, 293–301.
Hrebiniak, L. G., & Alutto, J. A. (1972). Personal and role-related factors in the development of
organizational commitment. Administrative Science Quarterly, 555–573.
Hup Chan, S. (2006). Organizational identification and commitment of members of a human development
organization. Journal of Management Development, 25(3), 249–268.
Huws, U., Korte, W. B., & Robinson, S. (1990). Telework: Towards the elusive office.
Iaffaldano, M. T., & Muchinsky, P. M. (1985). Job satisfaction and job performance: A meta-analysis.
Psychological Bulletin, 97(2), 251.
Igbaria, M., & Guimaraes, T. (1999). Exploring differences in employee turnover intentions and its
determinants among telecommuters and non-telecommuters. Journal of Management Information
Systems, 16(1), 147–164.
Iverson, R. D., & Roy, P. (1994). A causal model of behavioral commitment: Evidence from a study of
Australian blue-collar employees. Journal of Management, 20(1), 15–41.
Jaros, S. (2007). Meyer and Allen model of organizational commitment: Measurement issues. The Icfai
Journal of Organizational Behavior, 6(4), 7–25.
54
Jha, S. (2011). Influence of psychological empowerment on affective, normative and continuance
commitment: A study in the Indian IT industry. Journal of Indian Business Research, 3(4), 263–282.
Kanter, R. M. (1968). Commitment and social organization: A study of commitment mechanisms in utopian
communities. American Sociological Review, 499–517.
Karim, N. H. A., & Noor, N. H. N. M. (2017). Evaluating the psychometric properties of Allen and Meyer’s
organizational commitment scale: A cross cultural application among Malaysian academic librarians.
Malaysian Journal of Library & Information Science, 11(1), 89–101.
Kizza, J. M. (2007). Ethical and social issues in the information age (Vol. 999). Springer.
Knoop, R. (1995). Relationships among job involvement, job satisfaction, and organizational commitment
for nurses. The Journal of Psychology, 129(6), 643–649.
Lance, C. E., Butts, M. M., & Michels, L. C. (2006). The sources of four commonly reported cutoff criteria:
What did they really say? Organizational Research Methods, 9(2), 202–220.
Landers, R. N., & Behrend, T. S. (2015). An inconvenient truth: Arbitrary distinctions between
organizational, Mechanical Turk, and other convenience samples. Industrial and Organizational
Psychology, 8(2), 142–164.
Laschinger, H. K. S., Finegan, J. E., Shamian, J., & Wilk, P. (2004). A longitudinal analysis of the impact
of workplace empowerment on work satisfaction. Journal of Organizational Behavior: The
International Journal of Industrial, Occupational and Organizational Psychology and Behavior,
25(4), 527–545.
Lim, V. K. (1996). Job insecurity and its outcomes: Moderating effects of work-based and nonwork-based
social support. Human Relations, 49(2), 171–194.
Lipnack, J., & Stamps, J. (1999). Virtual teams: The new way to work. Strategy & Leadership, 27(1), 14–
19.
Lu, H., While, A. E., & Barriball, K. L. (2005). Job satisfaction among nurses: A literature review.
International Journal of Nursing Studies, 42(2), 211–227.
55
Luthans, F., Baack, D., & Taylor, L. (1987). Organizational commitment: Analysis of antecedents. Human
Relations, 40(4), 219–235.
Madlock, P. E. (2013). The influence of motivational language in the technologically mediated realm of
telecommuters. Human Resource Management Journal, 23(2), 196–210.
Mael, F. A., & Tetrick, L. E. (1992). Identifying organizational identification. Educational and
Psychological Measurement, 52(4), 813–824.
Malhotra, A., Majchrzak, A., & Rosen, B. (2007). Leading virtual teams. Academy of Management
Perspectives, 21(1), 60–70.
Marique, G., Stinglhamber, F., Desmette, D., Caesens, G., & De Zanet, F. (2013). The relationship between
perceived organizational support and affective commitment: A social identity perspective. Group &
Organization Management, 38(1), 68–100.
Markovits, Y., Davis, A. J., Fay, D., & Dick, R. van. (2010). The link between job satisfaction and
organizational commitment: Differences between public and private sector employees. International
Public Management Journal, 13(2), 177–196.
Mathieu, J. E., & Zajac, D. M. (1990). A review and meta-analysis of the antecedents, correlates, and
consequences of organizational commitment. Psychological Bulletin, 108(2), 171.
Mayer, R. C., & Schoorman, F. D. (1998). Differentiating antecedents of organizational commitment: A test
of March and Simon’s model. Journal of Organizational Behavior: The International Journal of
Industrial, Occupational and Organizational Psychology and Behavior, 19(1), 15–28.
McGee, G. W., & Ford, R. C. (1987). Two (or more?) dimensions of organizational commitment:
Reexamination of the affective and continuance commitment scales. Journal of Applied Psychology,
72(4), 638.
Meyer, J. P., & Allen, N. J. (1991). A three-component conceptualization of organizational commitment.
Human Resource Management Review, 1(1), 61–89.
Meyer, J. P., & Allen, N. J. (1997). Commitment in the workplace: Theory, research, and application. Sage.
56
Meyer, J. P., Stanley, D. J., Herscovitch, L., & Topolnytsky, L. (2002). Affective, continuance, and
normative commitment to the organization: A meta-analysis of antecedents, correlates, and
consequences. Journal of Vocational Behavior, 61(1), 20–52.
Miller, L. (2019, October 14). 4 Managerial Downsides of Remote Work (and How to Deal With Them).
Retrieved 20 December 2019, from Entrepreneur website:
https://www.entrepreneur.com/article/339613
Mottaz, C. J. (1988). Determinants of organizational commitment. Human Relations, 41(6), 467–482.
Mowday, R. T., Porter, L. W., & Steers, R. (1982). Organizational linkages: The psychology of
commitment, absenteeism, and turnover. San Diego, CA: Academic Press.
Mowday, R. T., Steers, R. M., & Porter, L. W. (1979). The measurement of organizational commitment.
Journal of Vocational Behavior, 14(2), 224–247.
Mueller, C. W., Boyer, E. M., Price, J. L., & Iverson, R. D. (1994). Employee attachment and noncoercive
conditions of work: The case of dental hygienists. Work and Occupations, 21(2), 179–212.
Niles, J. S. (1994). Beyond telecommuting: A new paradigm for the effect of telecommunications on travel.
USDOE Office of Energy Research, Washington, DC (United States).
Nilles, J. M. (1994). Making telecommuting happen: A guide for telemanagers and telecommuters.
Nunnally, J. C., & Bernstein, I. H. (1978). Psychometric testing. New York: McGraw-Hill.
O’Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality &
Quantity, 41(5), 673–690.
Okada, K.-I., Maeda, F., Ichikawaa, Y., & Matsushita, Y. (1994). Multiparty videoconferencing at virtual
social distance: MAJIC design. Proceedings of the 1994 ACM Conference on Computer Supported
Cooperative Work, 385–393. ACM.
Olson, M. H. (1983). Remote office work: Changing work patterns in space and time. Communications of
the ACM, 26(3), 182–187.
57
Olson, M. H. (1987). Telework: Practical experience and future prospects.
O’Reilly, C. A., & Chatman, J. (1986). Organizational commitment and psychological attachment: The
effects of compliance, identification, and internalization on prosocial behavior. Journal of Applied
Psychology, 71(3), 492.
Owl Labs. (n.d.). Global State of Remote Work 2018. Retrieved 20 December 2019, from
https://www.owllabs.com/state-of-remote-work/2018
Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding Mechanical Turk as a participant pool.
Current Directions in Psychological Science, 23(3), 184–188.
Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on amazon mechanical turk.
Judgment and Decision Making, 5(5), 411–419.
Porter, L. W., Steers, R. M., Mowday, R. T., & Boulian, P. V. (1974). Organizational commitment, job
satisfaction, and turnover among psychiatric technicians. Journal of Applied Psychology, 59(5), 603.
Pratt, M. G., & Rafaeli, A. (1997). Organizational dress as a symbol of multilayered social identities.
Academy of Management Journal, 40(4), 862–898.
Ramachandran, S., & Krishnan, V. R. (2009). Effect of transformational leadership on followers’ affective
and normative commitment: Culture as moderator.
Rawat, P. S., Rawat, S. K., Sheikh, A., & Kotwal, A. (2019). Women Organization Commitment: Role of
the Second Career & Their Leadership Styles. Indian Journal of Industrial Relations, 54(3).
Riketta, M., & Landerer, A. (2002). Organizational commitment, accountability, and work behavior: A
correlational study. Social Behavior and Personality: An International Journal, 30(7), 653–660.
Ritter, L. A., & Sue, V. M. (2007). Introduction to using online surveys. New Directions for Evaluation,
2007(115), 5–14.
Riva, G. (1999). Virtual reality as communication tool: A sociocognitive analysis. Presence, 8(4), 462–468.
58
Sagie, A. (1998). Employee absenteeism, organizational commitment, and job satisfaction: Another look.
Journal of Vocational Behavior, 52(2), 156–171.
Salancik, G. R. (1977). Commitment and the control of organizational behavior and belief. New Directions
in Organizational Behavior, 1, 54.
Schawbel, D. (2018, November 15). Survey: Remote Workers Are More Disengaged and More Likely to
Quit. Harvard Business Review. https://hbr.org/2018/11/survey-remote-workers-are-more-disengaged-
and-more-likely-to-quit
Selig, J. P., & Preacher, K. J. (2008). Monte Carlo method for assessing mediation: An interactive tool for
creating confidence intervals for indirect effects.
Shapiro, D. N., Chandler, J., & Mueller, P. A. (2013). Using Mechanical Turk to study clinical populations.
Clinical Psychological Science, 1(2), 213–220.
Sheldon, M. E. (1971). Investments and involvements as mechanisms producing commitment to the
organization. Administrative Science Quarterly, 16(2).
Shockley, K. M., & Allen, T. D. (2007). When flexibility helps: Another look at the availability of flexible
work arrangements and work–family conflict. Journal of Vocational Behavior, 71(3), 479–493.
Singh, P., Paleti, R., Jenkins, S., & Bhat, C. R. (2013). On modeling telecommuting behavior: Option,
choice, and frequency. Transportation, 40(2), 373–396.
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models.
Sociological Methodology, 13, 290–312.
Solinger, O. N., Van Olffen, W., & Roe, R. A. (2008). Beyond the three-component model of organizational
commitment. Journal of Applied Psychology, 93(1), 70.
Spreitzer, G. M. (1995). Psychological empowerment in the workplace: Dimensions, measurement, and
validation. Academy of Management Journal, 38(5), 1442–1465.
59
State of Remote Work 2019. (n.d.). Retrieved 20 December 2019, from https://buffer.com/state-of-remote-
work-2019
Steers, R. M. (1977). Antecedents and outcomes of organizational commitment. Administrative Science
Quarterly, 46–56.
Testa, M. R. (1999). Satisfaction with organizational vision, job satisfaction and service efforts: An
empirical investigation. Leadership & Organization Development Journal, 20(3), 154–161.
Tett, R. P., & Meyer, J. P. (1993). Job satisfaction, organizational commitment, turnover intention, and
turnover: Path analyses based on meta‐analytic findings. Personnel Psychology, 46(2), 259–293.
The 7 Challenges of Managing a Remote Team (and how to overcome them). (2019, April 9). Retrieved 20
December 2019, from TalentLMS Blog website: https://www.talentlms.com/blog/challenges-
managing-remote-team-how-overcome-them/
The Latest (Mindblowing) Remote Work Statistics in 2019 | Krisp. (n.d.). Retrieved 20 December 2019,
from https://krisp.ai/blog/mindblowing-remote-work-statistics/
The Remote Manifesto. (2015, April 8). Retrieved 20 December 2019, from GitLab website:
https://about.gitlab.com/blog/2015/04/08/the-remote-manifesto/
Thinking of Going Remote? Here’s All the Pros and Cons You Need to Know. (n.d.). Retrieved 20
December 2019, from https://toggl.com/out-of-office-why-go-remote/
Tummers, G. E., van Merode, G. G., & Landeweerd, J. A. (2006). Organizational characteristics as
predictors of nurses’ psychological work reactions. Organization Studies, 27(4), 559–584.
Van Dick, R., Hirst, G., Grojean, M. W., & Wieseke, J. (2007). Relationships between leader and follower
organizational identification and implications for follower attitudes and behaviour. Journal of
Occupational and Organizational Psychology, 80(1), 133–150.
Vandenberg, R. J., & Lance, C. E. (1992). Examining the causal order of job satisfaction and organizational
commitment. Journal of Management, 18(1), 153–167.
60
Verbeke, A., Schulz, R., Greidanus, N., & Hambley, L. (2008). Growing the virtual workplace: The
integrative value proposition for telework. Edward Elgar Publishing.
Wanberg, C. R., & Banas, J. T. (2000). Predictors and outcomes of openness to changes in a reorganizing
workplace. Journal of Applied Psychology, 85(1), 132.
Weiner, Y., & Gechman, A. (n.d.). S.(1977). Commitment: A behavioral approach to job involvement.
Journal of Vocational Behavior, 23, 254–269.
Wellman, B. (1996). For a social network analysis of computer networks: A sociological perspective on
collaborative work and virtual community. Proceedings of the 1996 ACM SIGCPR/SIGMIS
Conference on Computer Personnel Research, 1–11. ACM.
What Causes Workplace Ghosting? | Clutch.co. (n.d.). Retrieved 20 December 2019, from
https://clutch.co/hr/resources/what-causes-workplace-ghosting
Wiener, Y., & Vardi, Y. (1980). Relationships between job, organization, and career commitments and
work outcomes—An integrative approach. Organizational Behavior and Human Performance, 26(1),
81–96.
Wieseke, J., Ullrich, J., Christ, O., & Van Dick, R. (2007). Organizational identification as a determinant of
customer orientation in service organizations. Marketing Letters, 18(4), 265–278.
Wiesenfeld, B. M., Raghuram, S., & Garud, R. (1999). Managers in a virtual context: The experience of
self-threat and its effects on virtual work organizations. Journal of Organizational Behavior, 6, 31.
Wiesenfeld, B. M., Raghuram, S., & Garud, R. (2001). Organizational identification among virtual workers:
The role of need for affiliation and perceived work-based social support. Journal of Management,
27(2), 213–229.
Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of
organizational citizenship and in-role behaviors. Journal of Management, 17(3), 601–617.
Yen, J.-R. (2000). Interpreting employee telecommuting adoption: An economics perspective.
Transportation, 27(1), 149–164.
61
Yousef, D. A. (2000). Organizational commitment: A mediator of the relationships of leadership behavior
with job satisfaction and performance in a non-western country. Journal of Managerial Psychology,
15(1), 6–24.
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