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10 Years of Research on Technostress Creators and Inhibitors: Synthesis and Critique

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Organizations implement new technologies frequently to achieve competitive advantage. Constant change, however, requires employees to adapt to new business requirements. This could become a source of environmental pressure, creating stress among employees and, subsequently, leading to negative outcomes for organizations. Technostress refers to an individuals' incapability to cope with IT in a healthy manner. Extant research has uncovered factors that create technostress and studied mechanisms to alleviate the negative outcomes of this phenomenon. The current study reviews literature on technostress creators and inhibitors since 2008, and critically analyzes the current state of knowledge about their effects. Our review of findings from 23 relevant studies highlights opportunities for researchers to examine the separate and differential effects of individual technostress creators and inhibitors. More research in this area may help practitioners develop context-specific programs to tackle that specific dimensions of technostress creators and the specific benefits of technostress inhibitors.
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A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
1
10 Years of Research on Technostress
Creators and Inhibitors: Synthesis and
Critique
Completed Research
Jalal Sarabadani
Washington State University
jalal.sarabadani@wsu.edu
Michelle Carter
Washington State University
michelle.carter@wsu.edu
Deborah Compeau
Washington State University
deborah.compeau@wsu.edu
Abstract
Organizations implement new technologies frequently to achieve competitive advantage. Constant change,
however, requires employees to adapt to new business requirements. This could become a source of
environmental pressure, creating stress among employees and, subsequently, leading to negative outcomes
for organizations. Technostress refers to an individuals’ incapability to cope with IT in a healthy manner.
Extant research has uncovered factors that create technostress and studied mechanisms to alleviate the
negative outcomes of this phenomenon. The current study reviews literature on technostress creators and
inhibitors since 2008, and critically analyzes the current state of knowledge about their effects. Our review
of findings from 23 relevant studies highlights opportunities for researchers to examine the separate and
differential effects of individual technostress creators and inhibitors. More research in this area may help
practitioners develop context-specific programs to tackle that specific dimensions of technostress creators
and the specific benefits of technostress inhibitors.
Keywords
Technostress, technostress creators, technostress inhibitors, literature review
Introduction
To keep pace with dynamic markets and create new sources of competitive advantage, organizations
implement new information technologies (IT) frequently. For employees, this means constantly adapting
to changing business needs and demands, in order to accomplish work tasks. This creates pressure (for
training, for availability outside of work, and for other changes), which has the potential to create stress
(Ragu-Nathan et al. 2008; Wang et al. 2008). Stress associated with IT use has negative consequences,
such as reduced commitment to the organization, increased turnover intention (Ahmad et al. 2014; Maier
et al. 2015), ultimately leading to wasted investment in IT and unrealized benefits (Rangarajan et al. 2005).
Stress related to IT use (known as technostress) has been investigated since the mid-1980s (Brod 1984) and
many researchers have tried to address its associated problems (Brod, 1984; Arnetz et al., 1997). One of the
most prominent research studies (Ragu-Nathan et al. 2008) addressed the effect of technostress creators
on outcomes such as job satisfaction and organizational commitment. That work also examined mitigation
mechanisms to tackle technostress. Since then, numerous papers have investigated the effects of
technostress creators and inhibitors on behavioral and psychological outcomes. These papers are marked
by both consistency (e.g., the relationship between technostress creators and performance) and
A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
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inconsistencies (e.g., the relationship between technostress creators and productivity). Hence, the current
study reviews literature on technostress creators and inhibitors since 2008, and critically analyzes the
current state of knowledge about their effects. Specifically, we pose the following questions:
1. What technostress creators and psychological and behavioral outcomes are witnessed in
technostress research?
2. Which technostress inhibitors can mitigate the negative psychological and behavioral outcomes?
We begin by outlining the research methodology and explain how we gathered papers to do our review.
Then, we define the key technostress concepts and the theoretical foundation that guides our research. Next,
we critically review the literature and report the results. Finally, we provide future research directions.
Research Methodology
Our review methodology follows the guidelines presented by Webster et al. (2002). Because we focus on
the model and constructs introduced by Ragu-Nathan and his colleagues in 2008, we limit our review to
research papers published in the last 10 years. We did not take the seminal paper by (Tarafdar et al, 2007)
as our baseline because it considers only the effects of technostress creators and productivity as the outcome
while the paper by (Ragu-Nathan et al, 2008) introduced a more comprehensive model including
technostress inhibitors, job satisfaction, organizational commitment and organizational continuance.
We conducted a keyword search on Google Scholar which includes most of the databases of information
systems. We used key words such as “technostress creators”, technostress inhibitors”, technostress
mitigation” and “negative outcomes of technostress”. We also searched for relevant papers in common
databases such as INFORMS, Science Direct and EBSCO. In addition, we reviewed all of the articles in the
basket of eight journals
1
to identify any papers that were not picked up in our keyword searches. Our initial
searches resulted in 31 papers. We reviewed the title and abstract of all papers and excluded papers that
were neither about the effects of technostress creators nor technostress inhibitors. This resulted in eighteen
papers for review. Having read the initial papers, and to ensure we did not miss any other relevant papers
from journals and leading conferences, we conducted backward and forward searches of the chosen papers.
This resulted in the identification of eleven further papers, of which five remained after applying the
exclusion criteria. In total, 23 papers met our criteria for inclusion.
Theoretical Foundation
Technostress was first defined by Brod in 1984 as “a modern disease of adaptation caused by an inability to
cope with the new computer technologies in a healthy manner (Sami et al, 2006). More recently, (Ragu-
Nathan et al., 2008) drew on the transactional model of stress (TMS) (Lazarus 1966; Folkman et al. 1979)
to develop a conceptualization of technostress in the IS domain.
Developed by Richard Lazarus (1966) and Susan Folkman and coauthors (1979), TMS explains how
individuals experience stress when environmental demands exceed their abilities and the available
resources to accomplish a task. TMS was originally specified as a process model, wherein an individual
undertakes a primary appraisal of whether a situation poses a threat and if so, conducts a secondary
appraisal of their resources to cope. TMS can also be represented as a variance model with four major
components: stressors, situational factors, strain and organizational outcomes. The theory is well-
established in the information systems literature, having been used to study user reactions to IT change
(Beaudry et al. 2005, 2010; Tsai et al. 2017) and IT professional updating (Pazy 1994; Tsai et al. 2007), as
well as technostress (Ragu-Nathan et al. 2008; Hung et al. 2011)
Ragu-Nathan and colleagues employed TMS as a basis to explain the effects of IT on stress. They introduced
the constructs technostress creators as equivalent to stressors, technostress inhibitors as equivalent to
situational factors, job satisfaction (inversely) as equivalent to strain and organizational continuance
1
MIS Quarterly (MISQ), Information Systems Research (ISR), Journal of the Association for Information Systems
(JAIS), Journal of Management Information Systems (JMIS), Information Systems Journal (ISJ), Journal of
Information Technology (JIT), European Journal of Information Systems (EJIS), and Journal of Strategic
Information Systems (JSIS).
A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
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commitment as equal to other organizational outcomes. Figure 1 depicts the conceptual model. Table 1
presents the original components of the transactional model and the IS context specific definition.
Figure 1. Conceptual model of technostress (adapted from Ragu-Nathan et al., 2008)
Table 1. Original and IS context-specific definitions of the transactional model of stress
Synthesis of Research
In the sections that follow, we outline the findings of our literature review. We begin by exploring the
outcomes of technostress that have been identified in prior research. We then describe the
conceptualization of technostress creators and show their observed effects on the identified outcomes. We
Original Definition
IS Context Specific Definition
Key
References
Stressors
The elements which create
stress in individuals such as
event or demands in the
context of work
Known as technostress creators
which have been defined as the set
of factors that lead to technostress
in organizations.
(Ragu-Nathan
et al. 2008)
Strain
The psychological,
behavioral negative
outcomes of stressors on
individuals at work and
organizational contexts like
job dissatisfaction and lack
of job involvement
Introduced as job satisfaction
(inversely) which reflects “a
pleasurable or positive emotional
state resulting from the appraisal of
one’s job or job experiences”
(Ragu-Nathan
et al. 2008,
P.423;
Tarafdar et al.
2015)
Situational
Factors
Are known as the
mechanism that can weaken
the effect of stressors and
reduce them such as job
control and social support
Introduced as technostress
inhibitors to refer to the factors
which reduce technostress namely
technical support provision, literacy
facilitation and involvement
facilitation
(Ragu-Nathan
et al. 2008;
Tarafdar et al.
2015)
Other
Organizational
Outcomes
The other outcomes of
strain on individuals like
absenteeism and turnover
Introduced two broad concepts as
organizational commitment and
continuance commitment as the
outcome of job satisfaction
(Ragu-Nathan
et al. 2008)
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Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
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repeat this process for technostress inhibitors, highlighting the different theoretical roles they have been
accorded in the literature.
Outcomes of Technostress
Our review of the literature identified six major psychological and behavioral outcomes as a result of
negative effects of technostress: end-user satisfaction, job satisfaction, performance, productivity
organizational commitment and continuance commitment (Ragu-Nathan et al. 2008; Tarafdar et al. 2010;
Hung et al. 2011; Ahmad et al. 2014; Ioannou et al. 2017). These are referred to collectively as “strain”.
In a related research stream, Ayyagari et al (2011) conceptualized strain differently as the experience of
stress. These authors measured strain as the extent to which the individual feels tired, drained, or burned
out from using technology. In this conceptualization, job satisfaction is an outcome of strain, much like
organizational outcomes are outcomes of job satisfaction in Ragu-Nathan et al’s (2008) model.
Technostress Creators
Technostress creators are perceptions of elements that are likely to produce stress. Ragu-Nathan et al.
(2008) conceptualize technostress creators as a latent (reflective) second-order construct (Law et al. 1998)
with five dimensions corresponding to five stress-producing conditions: techno-overload, techno-invasion,
techno-complexity, techno-insecurity and techno-uncertainty. Techno-overload occurs when users are
faced with a high volume of information to do their tasks and it is hard for them to differentiate useful from
useless information. Techno-invasion is the result of being always online and connected, which leads to a
feeling of an imbalance between work and personal life. Techno-complexity is associated with users’ feeling
that their knowledge is not adequate to complete tasks using the system and that they are forced to spend
too much time learning IT-related systems. Techno-insecurity describes the situation when employees
worry about losing their jobs and being replaced either by new IT-based systems or with more experienced
people who have better understanding of the system. Techno-uncertainty describes the situation where
users of systems feel forced to update their knowledge due to constant upgrades in the IT-based systems.
The Effect of Technostress Creators on Strain
The effect of technostress creators has been studied in various contexts, such as education, manufacturing
and service industries (Tarafdar et al. 2010; Fuglseth et al. 2014; Jena 2015). Table 2 shows that
technostress creators lead to several strains arising from use of IT in organizations (Tu et al. 2005; Kumar
et al. 2013). One of the most consistent strains reported is reduced end-user satisfaction (Tu et al. 2008;
Tarafdar et al. 2011; Fuglseth et al. 2014). Findings show a negative association between overall effect of
technostress creators and end-user satisfaction among employees. Similar results were observed for the
relationship between technostress creators and job satisfaction (Ragu-Nathan et al. 2008; Kumar et al.
2013; Jena 2015). In addition, extant research investigated the association between technostress creators
and performance and productivity. While studies of the relationship between technostress creators and
performance show a consistent negative relationship (Tarafdar et al. 2010; Jena 2015; Ioannou et al. 2017),
the relationship between technostress creators and productivity is ambiguous. Three of five studies carried
out by Tarafdar and her colleagues found a negative relationship between technostress creators and
productivity (Tarafdar et al. 2005; Tarafdar et al. 2007; Tarafdar et al. 2011).
One study found a positive relationship (Hung et al. 2011) and another found no significant effect of
technostress creators on productivity among Chinese employees (Tu et al. 2005). The relationship between
technostress and commitment also received attention from scholars and the results indicate that
technostress creators exerts a small to moderate negative effect on organizational commitment (Tarafdar
et al. 2011; Kumar et al. 2013; Ahmad et al. 2014; Jena 2015).
Decomposing the Effects of Technostress Creators
As noted, technostress creators and inhibitors are viewed as latent second order constructs. As such, most
studies have considered only the overall effect of technostress creators on outcomes. A few studies, however,
have investigated the individual effects of each contributing factor (i.e. techno-invasion, techno-overload,
techno-complexity, techno-insecurity and techno-uncertainty) on strain such as end-user satisfaction, job
A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
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satisfaction, performance, productivity and commitment (Tu et al. 2005; Ragu-Nathan et al. 2008;
Ayyagari et al. 2011; Ahmad et al. 2014).
Dependent
Variable
References
Direction
Magnitude
Key findings
End-User
Satisfaction
(Tarafdar et al. 2010)
Negative
B= -0.18, P< .05
Impacts are close
except one study
(Fuglseth et al. 2014)
All show a negative
effect of technostress
creators on end-user
satisfaction.
(Tu et al. 2008)
Negative
B= -0.19, P= .003
(Ioannou et al. 2017)
Negative
B= -0.17, p= .03
(Tarafdar et al. 2011)
Negative
B= -0.18, P= .005
(Fuglseth et al. 2014)
Negative
B= -0.42, P< .05
Range
-0.17 to -0.42
Job
satisfaction
(Ragu-Nathan et al.
2008)
Negative
B= -0.13, P< .01
The results are in one
direction.
However, the
magnitude change
from small to medium
among these studies
(Jena 2015)
Negative
B= -0.41, p= .01
(Tarafdar et al. 2011)
Negative
B= -0.35, P< .001
(Kumar et al. 2013)
Negative
B= -.028, P= .25
Range
-0.13 to -0.41
Performance
(Tarafdar et al. 2010)
Negative
B= -0.33, P< .01
Results are consistent.
All are negative and
path coefficients are
similar.
(Jena 2015)
Negative
B= -0.33, P= .05
(Tarafdar et al. 2015)
Negative
B= -0.15, P= .05
(Ioannou et al. 2017)
Negative
B= -0.27, p= .001
Range
-0.15 to -0.33)
Productivity
(Tu et al. 2005)
Non-Significant
Overall, there is a
negative effect of
technostress creators
on productivity while
one study found
positive effect and one
found no effect
(Tarafdar et al. 2005)
Negative
B= -0.28, P< .01
(Tarafdar et al. 2007)
Negative
B= -0.28, P< .01
(Tarafdar et al. 2011)
Negative
B= -0.22, P< .001
(Hung et al. 2011)
Positive
B= 0.26, P< .001
Range
-0.22 to 0.26
Table 2. The overall effect of technostress creators on strain
Ayyagari et al. (2011) found a positive relationship between some technostress creators and perceptions of
strain among working professionals. In another study, conducted in China, Tu et al. (2005) tested every
dimension of technostress creators on the productivity of 700 Chinese employees from industries such as
IT, financial management, and traditional manufacturing. Their results showed that techno-invasion and
techno-insecurity had negative relationships which were negatively related to productivity, while techno-
overload had a positive relationship. Meanwhile, techno-complexity and techno-uncertainty were not
significantly related to productivity. Moreover, Ahmad et al. (2014) investigated the separate effects of
technostress creators on organizational commitment among librarians and found techno-overload and
techno-uncertainty were positively associated with organizational commitment while other factors did not
have a contributing role. These authors assert that a moderate amount of stress (eustress) is necessary to
enhance commitment in organizations.
Commitment
(Ahmad et al. 2014)
Negative
F= 5.83, p< .001
The results indicate
that the relationship is
negative and
moderate.
(Jena 2015)
Negative
B= -0.37, P= .00
(Tarafdar et al. 2011)
Negative
B= -0.13, P= .05
(Kumar et al. 2013)
Negative
B= -0.27, P= .25
Range
-0.13 to -0.37
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As summarized in Table 3, individual technostress creators exert differential effects on strain. This
highlights the importance of understanding the differential effects of individual technostress creators on
strain. Still, only a few studies have undertaken this granular level of analysis. Understanding these
relationships will not only help to uncover contributors to specific strains, but will also aid in the design of
mitigation mechanisms to overcome such issues.
Table 3. Separate effects of individual factors of technostress creators on strain
Technostress Inhibitors
Technostress inhibitors are factors that decrease the impact of technostress on employees, either directly
or indirectly. As with technostress creators, Ragu-Nathan et al. (2008) conceptualized technostress
inhibitors as a second order latent factor, this time with three dimensions, namely technical support
provision, literacy facilitation and involvement facilitation. Technical support provision refers to the
technical and help desk support that the IT team provides to end-users when new IT are implemented.
Literacy facilitation refers to the facilitation and dissemination of IT knowledge in organization to
encourage users to better understand the benefits of using IT. User involvement refers to encouraging and
involving users in different phases of implementing new IT, to alleviate their technostress.
In the transactional model of stress, technostress inhibitors are theorized to either moderate the
relationship between technostress creators and strain or to reduce stress by directly impacting strain. The
articles we reviewed examined both these proposed effects, as well as the role of technostress inhibitors as
antecedents to technostress creators (reducing the techno-stressor). As with technostress creators,
technostress inhibitors exhibited differential effects at the aggregate and at the component level
The Overall Effect of Technostress Inhibitors on Strain
As outlined in Table 4, five papers examined the direct effect of technostress inhibitors on strain. While the
magnitudes of effects vary, all of the studies show that inhibitors promote positive outcomes, including end
user satisfaction, job satisfaction, performance, productivity, continuance intention and organizational
commitment. Of note, Fuglseth et al (2014) shows a much smaller effect of the inhibitors on end-user
satisfaction and continuance intention. This result may be an outlier but warrants further examination.
Dependent
Variable
Independent
Variable
Reference
Direction
Magnitude
Perception of
Strain
Work-home conflict
(Ayyagari et al. 2011)
Positive
B= 0.17, P< .01
work-overload
Positive
B= 0.26, P< .01
Job insecurity
Positive
B= 0.10, P< .01
Techno-complexity
Not considered
(Role Ambiguity)
Positive
B= 0.27, P< .01
Productivity
Techno-invasion
(Tu et al. 2005)
Negative
Not available
Techno-overload
Positive
Not available
Techno-insecurity
Negative
Not available
Techno-complexity
Non-Significant
Not available
Techno-uncertainty
Non-Significant
Not available
Organizational
Commitment
Techno-invasion
(Ahmad et al. 2014)
Non-Significant
B= -0.15, P = .07
Techno-overload
Positive
B= 0.17, P= .03
Techno-insecurity
Non-Significant
B= 0.05, P= .56
Techno-complexity
Non-significant
B= -0.04, P= .62
Techno-uncertainty
Positive
B= 0.29, P< .001
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Table 4. The overall effect technostress inhibitors on strain
The Moderating Effect of Technostress Inhibitors
Ragu-Nathan et al. (2008) conceptualized and tested the moderating effect of technostress inhibitors. They
found no significant overall effect of technostress inhibitors on the relationship between technostress
creators and job satisfaction (B= -0.005, P= .378). Following that, only two papers considered the overall
effect of technostress inhibitors as a moderator between technostress creators and strain (Tu et al. 2008;
Hung et al. 2011). In their article, Tu et al. (2008), ran a multiple regression analysis and found that
technostress inhibitors had no moderating effect on the relationship between technostress creators and
end-user satisfaction (B= -.22, P= .355). In another study, (Hung et al. 2011) introduced stress inhibitors,
comprised of stress management training, job control, and individual rewards, to measure the moderating
effect of stress inhibitors on the relationship between ubiquitous technostress creators and job stress. The
results, found no significant relationship (B=1.36, P= .108). These results, presented in Table 5, are
consistent with the original model of technostress. It can be argued that technostress inhibitors may
themselves increase the burden and make the situation more complex for employees.
Relationship
Reference
Direction
Magnitude
Technostress creators Job satisfaction
(Ragu-Nathan et
al. 2008)
Non- Significant
B= -0.005, P= .38
Technostress creators End-user
satisfaction
(Tu et al. 2008)
Non-Significant
B= -0.22, P= .35
Technostress creators Job Stress
(Hung et al. 2011)
Non-Significant
B=1.36, P= .11
Table 5. Moderating effect of technostress inhibitors
Decomposing the Effects of Technostress Inhibitors on Strain
The studies we reviewed focused primarily on the overall positive impact of technostress inhibitors on
strain from the use of IT in organizations. A few studies have focused on individual inhibiting factors,
including technical support provision, literacy facilitation and involvement facilitation (Table 6). In one
study, Tarafdar et al. (2010) examined the effects of involvement facilitation on End-user performance and
found a positive relationship between them though it was small (B= 0.18, P< .05). They also found positive
support for innovation support on end-user satisfaction (B= 0.24, P<.001).
Dependent variables
Reference
Direction
Magnitude
End-user
satisfaction
(Tu et al. 2008)
Positive
B= 0.51, P= .00
(Fuglseth et al. 2014)
Positive
B= 0.18, P<.05
Range
(B= 0.18) ( B= 0.51)
Job Satisfaction
(Jena 2015)
Positive
B= 0.31, P= .00
(Ragu-Nathan et al. 2008)
Positive
B= 0.34, P< .01
Range
(B= 0.31) ( B= 0.34)
Performance
(Jena 2015)
positive
B= 0.32, P= .04
Productivity
(Hung et al. 2011)
Positive
B= 0.71, P< .001
Continuance
intention
(Ragu-Nathan et al. 2008)
Positive
B= 0.13, P< .01
(Fuglseth et al. 2014)
Positive
B= 0.03, P< .05
Range
(B= 0.03) ( B= 0.13)
Organizational
commitment
(Jena 2015)
Positive
B= 0.29, P= .01
(Ragu-Nathan et al. 2008)
Positive
B= 0.39, P< .01
Range
(B= 0.29) ( B= 0.39)
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In another study, Ahmad et al. (2014) examined the moderating effect of each technostress inhibitor factors
on the relationship between techno-overload, techno-uncertainty and organizational commitment. Their
findings showed no significant moderating effect of literacy facilitation and involvement facilitation in the
relationship between technostress creators and organizational commitment while technical support
moderated the relationship between techno-overload and organizational commitment.
Dependent
Variable
Independent
Variable
Moderating
Variable
Reference
Direction and
Magnitude
End-user
satisfaction
Involvement
Facilitation
None
(Tarafdar et al.
2010)
Positive
B= 0.18, P<.05
Innovation
support
None
Positive
B= 0.24, P<.001
Technostress
creators
Involvement
Facilitation
None
Negative
B= -0.17, P<.05
Organizational
commitment
Techno-overload
Literacy facilitation
(Ahmad et al. 2014)
Non-significant
Techno-
uncertainty
Literacy facilitation
Non-significant
Techno-overload
Technical Support
F= 5.70, P= .02
Techno-
uncertainty
Technical support
Non-significant
Techno-overload
Involvement
facilitation
Non-significant
Techno-
uncertainty
Involvement
facilitation
Non- significant
Table 6. The direct and moderating effects of individual technostress inhibitors on strain
Developing understanding of which individual technostress inhibitors are most important in reducing
specific strains will help in efforts to design effective context-specific remedies to mitigate negative
outcomes of technostress creators. To that end, more research at a granular level is needed, to determine
the differential effects of individual technostress inhibitors on strain.
Technostress Inhibitors as the Antecedents of Technostress Creators
Recent literature has begun to consider the direct effects of technostress inhibitors on technostress creators.
As shown in Table 7, two studies find that technostress inhibitors negatively influence technostress creators
(Jena 2015; Tarafdar et al. 2015). Still, no study, to the best of our knowledge, has investigated the role of
individual technostress inhibitors as antecedents of specific technostress creators.
Dependent variable
Independent Variable
Reference
Direction and Magnitude
Technostress creators
Technostress inhibitors
(Jena 2015)
Negative, B= -0. 34, P =. 02
(Tarafdar et al. 2015)
Negative, B= -0.15, P< .05
Table 7. The overall effects of technostress inhibitors on technostress creators
Discussion
Our review of the literature provides three main contributions. First, we show that technostress creators
are a consistent (negative) influence on psychological and behavioral outcomes. Individuals who experience
IT-related stressors have lower job satisfaction and lower performance, and are more likely to leave their
current jobs. The variation in the magnitude of these effects across studies, however, suggests the possibility
of moderating effects that have yet to be uncovered. Second, we show that technostress inhibitors act to
reduce strain primarily through direct effects. Consistent with Ragu-Nathan et al. (2008), we find no
evidence that inhibitors moderate the relationship between technostress creators and strain. This might be
explained by the additional complexity and burden on employees that mitigation mechanisms such as
involvement or literacy facilitation could create. We do find some evidence that the effect of technostress
A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
9
inhibitors is mediated by their effects on technostress creators. However, this finding is based on only two
studies and requires additional confirmation. Third, following the logic of Karahanna et al (2006) in
modeling compatibility beliefs, and based on the work of Edwards (2001), we decomposed technostress
creators and inhibitors to study their individual effects. We observed that doing so results in different
conclusions. This is an important finding because it challenges the original conceptualization of these
constructs as latent second order factors.
Our research suggests several directions for future research. First, we believe a sufficient body of evidence
has emerged to support more formal review methods, such as meta-analysis. Conducting a meta-analysis
would allow us to make stronger statements about the magnitudes of the effects of technostress creators
and inhibitors. Second, as noted above, we believe there is a need for additional research, to help resolve
some of the mixed effects. It is also worth broadening the scope of the study to consider other technostress
creators and inhibitors to expand the current understanding of the phenomenon. Pursuing decomposed
models of technostress creators and inhibitors is one way that this may occur. Searching for missing
moderators (that would explain the variation in effect magnitudes) is another possible direction for future
research. Alternatively, we recognize that even though technostress creators and inhibitors have formed a
substantial core of research on technostress, other models and approaches have been developed (Maier et
al. 2015; Tarafdar et al. 2017) and we see opportunity to enrich our theorizing by drawing on these models.
Lastly, we believe there is an opportunity to integrate Ayyagari et al’s (2011) conceptualization of strain into
the transactional model. Excluding the construct which most closely captures the felt experience of stress,
as much research in this domain has done, ignores the affective mechanism through which stressors create
the outcomes such as job satisfaction and performance. We must, however, acknowledge the limitations of
our work. Our review focused on a subset of IS journals and while we have attempted to extend our coverage
through forward and backwards searches and keywords searches, our data may not be comprehensive.
Having that said, we intend to continue to develop our database of articles to extend our analysis in future
studies.
In conclusion, the program of research begun by Ragu-Nathan et al (2008) has shown the importance of
technostress and has provided a model to explain its effects. Our review of the research shows broad
agreement on many issues, but highlights key opportunities to reconcile the points of inconsistency and
extend the findings further. We believe more research in this area will give more detailed and concrete
results about the main predictors of technostress in organizations. This will allow practitioners to not only
increase their focus on the main source of stress but will help them have context-specific programs to tackle
that specific dimension of technostress creator and the specific benefits of technostress inhibitors.
References
Ahmad, U. N. U., S. M. Amin and W. K. W. Ismail (2014). "Moderating effect of Technostress inhibitors on
the relationship between Technostress creators and organisational commitment." Jurnal Teknologi
67(1): 51-62.
Arnetz, B. B. and C. Wiholm (1997). "Technological stress: Psychophysiological symptoms in modern
offices." Journal of psychosomatic research 43(1): 35-42.
Ayyagari, R., V. Grover and R. Purvis (2011). "Technostress: technological antecedents and implications."
MIS Quarterly 35(4): 831-858.
Beaudry, A. and A. Pinsonneault (2005). "Understanding user responses to information technology: A
coping model of user adaptation." MIS Quarterly: 493-524.
Beaudry, A. and A. Pinsonneault (2010). "The other side of acceptance: studying the direct and indirect
effects of emotions on information technology use." MIS Quarterly: 689-710
Brod, C. (1984). Technostress: The human cost of the computer revolution, Addison Wesley Publishing
Company.
Edwards, J. R. “Multidimensional Constructs in Organizational Behavior Research: An Integrative
Analytical Framework,” Organizational Research Methods (2:2), April 2001, pp. 144-192.
Folkman, S., C. Schaefer and R. S. Lazarus (1979). "Cognitive processes as mediators of stress and coping."
Human Stress and Cognition: 265-298.
Fuglseth, A. M. and Ø. Sørebø (2014). "The effects of technostress within the context of employee use of
IT." Computers in Human Behavior 40: 161-170.
A Review of Technostress Creators and Technostress Inhibitors
Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018
10
Hung, W.-H., L.-M. Chang and C.-H. Lin (2011). Managing The Risk Of Overusing Mobile Phones In The
Working Environment: A Study Of Ubiquitous Technostress. PACIS.
Ioannou, A. and A. Papazafeiropoulou (2017). "Using IT Mindfulness to Mitigate the Negative
Consequences of Technostress."AMCIS.
Jena, R. (2015). "Technostress in ICT enabled collaborative learning environment: An empirical study
among Indian academician." Computers in Human Behavior 51: 1116-1123.
Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Reconceptualizing compatibility beliefs in technology
acceptance research. MIS Quarterly, 781-804.
Kumar, R., R. Lal, Y. Bansal and S. K. Sharma (2013). "Technostress in Relation to Job Satisfaction and
Organisational Commitment among IT Professionals." International Journal of Scientific and
Research Publications 3(12): 1-3.
Law, K. S., C.-S. Wong and W. M. Mobley (1998). "Toward a taxonomy of multidimensional constructs."
Academy of Management Review 23(4): 741-755.
Lazarus, R. S. (1966). "Psychological stress and the coping process."
Maier, C., S. Laumer, A. Eckhardt and T. Weitzel (2015). "Giving too much social support: social overload
on social networking sites." European Journal of Information Systems 24(5): 447-464.
Maier, C., S. Laumer, C. Weinert and T. Weitzel (2015). "The effects of technostress and switching stress on
discontinued use of social networking services: a study of Facebook use." Information Systems Journal
25(3): 275-308.
Pazy, A. (1994). "Cognitive schemata of professional obsolescence." Human Relations 47(10): 1167-1199.
Ragu-Nathan, T., M. Tarafdar, B. S. Ragu-Nathan and Q. Tu (2008). "The consequences of technostress for
end users in organizations: Conceptual development and empirical validation." Information systems
Research 19(4): 417-433.
Rangarajan, D., E. Jones and W. Chin (2005). "Impact of sales force automation on technology-related
stress, effort, and technology usage among salespeople." Industrial Marketing Management 34(4):
345-354.
Sami, L. K. and N. Pangannaiah (2006). "“Technostress” A literature survey on the effect of information
technology on library users." Library Review 55(7): 429-439.
Tarafdar, M., C. L. Cooper and J. F. Stich (2017). "The technostress trifectatechno eustress, techno
distress and design: Theoretical directions and an agenda for research." Information Systems Journal.
Tarafdar, M., E. B. Pullins and T. RaguNathan (2015). "Technostress: negative effect on performance and
possible mitigations." Information Systems Journal 25(2): 103-132.
Tarafdar, M., B. Ragu-Nathan, T. Ragu-Nathan and Q. Tu (2005). "Exploring the impact of technostress on
productivity." Proceedings of the 36th Annual Meeting of the Decision Sciences Institute
Tarafdar, M., Q. Tu, B. S. Ragu-Nathan and T. Ragu-Nathan (2007). "The impact of technostress on role
stress and productivity." Journal of Management Information Systems 24(1): 301-328.
Tarafdar, M., Q. Tu and T. Ragu-Nathan (2010). "Impact of technostress on end-user satisfaction and
performance." Journal of Management Information Systems 27(3): 303-334.
Tarafdar, M., Q. Tu, T. Ragu-Nathan and B. S. Ragu-Nathan (2011). "Crossing to the dark side: examining
creators, outcomes, and inhibitors of technostress." Communications of the ACM 54(9): 113-120.
Tsai, H. P. and D. Compeau (2017). "Change-Related Communication and Employees' Responses During
the Anticipation Stage of IT-Enabled Organizational Transformation: A Case Study." ACM SIGMIS
Database: the DATABASE for Advances in Information Systems 48(4): 30-50.
Tsai, H. Y., D. Compeau and N. Haggerty (2007). "Of races to run and battles to be won: technical skill
updating, stress, and coping of IT professionals." Human Resource Management 46(3): 395-409.
Tu, Q., M. Tarafdar, T. Ragu-Nathan and B. S. Ragu-Nathan (2008). "Improving end-user satisfaction
through techno-stress prevention: some empirical evidences." AMCIS 2008 Proceedings: 236.
Tu, Q., K. Wang and Q. Shu (2005). "Computer-related technostress in China." Communications of the
ACM 48(4): 77-81.
Wang, K., Q. Shu and Q. Tu (2008). "Technostress under different organizational environments: An
empirical investigation." Computers in Human Behavior 24(6): 3002-3013.
Webster, J. and R. T. Watson (2002). "Analyzing the past to prepare for the future: Writing a literature
review." MIS Quarterly: xiii-xxiii.
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