A meta-analytic investigation of cyberloafing

Abstract

Purpose
Cyberloafing, using technology to idle instead of work, is a particularly concerning issue for many organizations due to its perceived widespread impact on productivity. The purpose of this paper is to meta-analytically examine the growing literature on this construct in order to gain insights into its nomological network and guide future research.

Design/methodology/approach
After a systematic literature search, the authors conducted psychometric meta-analyses to estimate the relationships of 39 different correlates with cyberloafing. The meta-analytic database was comprised of 54 independent samples contributing 609 effect sizes.

Findings
Results indicate that boredom, engagement, and self-control exhibit strong relationships with cyberloafing, but employees’ attitudes surrounding and opportunities to engage in cyberloafing also proved powerful predictors. Contrary to common stereotypes, age and other demographic variables exhibited negligible effects. Employment variables (e.g. tenure, organization level, and income) were also negligibly related to cyberloafing. Emotional stability, conscientiousness, and agreeableness exhibited modest negative relationships with cyberloafing, whereas self-control demonstrated a strong negative relationship. Although cyberloafing strongly correlated with overall counterproductive work behaviors, the findings suggest it is unrelated to other components of job performance.

Research limitations/implications
Because the cyberloafing literature is in its early stages, the present study drew on a limited number of samples for several of the relationships analyzed. Rather than providing conclusive evidence of the nomological network of cyberloafing, these analyses reinforce the need for empirical investigation into several important relationships.

Originality/value
As the first quantitative review of the emerging cyberloafing literature, this study synthesizes related studies from disparate disciplines, examines the nomological network of cyberloafing, and highlights future directions for research into this phenomenon.

Full text

Career Development International
A meta-analytic investigation of cyberloafing
Brittany K. Mercado, Casey Giordano, Stephan Dilchert,
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Brittany K. Mercado, Casey Giordano, Stephan Dilchert, (2017) "A meta-analytic investigation of
cyberloafing", Career Development International, Vol. 22 Issue: 5, pp.546-564, https://doi.org/10.1108/
CDI-08-2017-0142
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A meta-analytic investigation
of cyberloafing
Brittany K. Mercado
Martha & Spencer Love School of Business, Elon University,
Elon, North Carolina, USA
Casey Giordano
Department of Psychology, University of Minnesota Twin Cities, Minneapolis,
Minnesota, USA, and
Stephan Dilchert
Department of Management, Baruch College, CUNY, New York, New York, USA
Abstract
Purpose –Cyberloafing, using technology to idle instead of work, is a particularly concerning issue for many
organizations due to its perceived widespread impact on productivity. The purpose of this paper is to meta-
analytically examine the growing literature on this construct in order to gain insights into its nomological
network and guide future research.
Design/methodology/approach –After a systematic literature search, the authors conducted
psychometric meta-analyses to estimate the relationships of 39 different correlates with cyberloafing.
The meta-analytic database was comprised of 54 independent samples contributing 609 effect sizes.
Findings –Results indicate that boredom, engagement, and self-control exhibit strong relationships with
cyberloafing, but employees’attitudes surrounding and opportunities to engage in cyberloafing also proved
powerful predictors. Contrary to common stereotypes, age and other demographic variables exhibited
negligible effects. Employment variables (e.g. tenure, organization level, and income) were also negligibly
related to cyberloafing. Emotional stability, conscientiousness, and agreeableness exhibited modest negative
relationships with cyberloafing, whereas self-control demonstrated a strong negative relationship. Although
cyberloafing strongly correlated with overall counterproductive work behaviors, the findings suggest it is
unrelated to other components of job performance.
Research limitations/implications –Because the cyberloafing literature is in its early stages, the present
study drew on a limited number of samples for several of the relationships analyzed. Rather than providing
conclusive evidence of the nomological network of cyberloafing, these analyses reinforce the need for
empirical investigation into several important relationships.
Originality/value –As the first quantitative review of the emerging cyberloafing literature, this study
synthesizes related studies from disparate disciplines, examines the nomological network of cyberloafing, and
highlights future directions for research into this phenomenon.
Keywords Meta-analysis, Productivity, Cyberloafing
Paper type Research paper
Technological advances positively contribute to employee productivity in many ways,
increasing accessibility of critical information, catalyzing task completion, and enhancing
collaboration in a variety of ways (e.g. telecommuting, enabling virtual teamwork).
However, jobs with frequent and convenient information technology access also provide
employees with opportunities to misuse such technology. In a recent survey of over two
thousand employed Americans, 62 percent of employees reported spending some of their
workday on social networking websites, and 10 percent indicated that they spend
30 percent or more of their workday on these sites (Ethics Resource Center, 2012). Of those
employees who were actively utilizing social media at work, only 14 percent limited their use
to lunch hours or other unpaid time. Similarly, Salary.com’s (2014) Wasting Time at Work
Survey found that 89 percent of employees reported wasting time at work every day, with
57 percent reporting wasting at least an hour each day; all of the commonly preferred time
wasting techniques consisted of visiting various webpages for personal purposes.
Career Development International
Vol. 22 No. 5, 2017
pp. 546-564
© Emerald Publishing Limited
1362-0436
DOI 10.1108/CDI-08-2017-0142
Received 24 May 2016
Revised 1 February 2017
Accepted 14 July 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1362-0436.htm
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Organizations are clearly concerned with their workers’cyberloafing. This is exemplified by
the 43 percent of employers who block access to social media platforms on organization-owned
computers or handheld devices (Society for Human Resource Management, 2011). The extent of
employee time losses have alarmed organizations and consequently sparked a growing interest
among both scholars and practitioners who seek to identify mechanisms to reduce or avoid
these costly employee behaviors.
Cyberloafing
Lim (2002) originally conceptualized cyberloafing as employees’voluntary use of their
organizations’internet access for nonwork purposes during work time or, more simply, the
“IT way of idling on the job”(p. 678). Since cyberloafing was introduced in the academic
literature, opportunities to engage in technologically-facilitated loafing have expanded
greatly, resulting in a proliferation of conceptualizations of the construct. Many studies now
define and operationalize cyberloafing more broadly to include behaviors that use
information technology for purposes other than internet activity (e.g. nonwork-related
computing; Bock and Ho, 2009), while others examine specific types of cyberloafing, such as
social media use, that have risen in prevalence in recent years (Charoensukmongkol, 2014).
Recent empirical work in this area has also broadened the construct definition to include
additional devices that employees can utilize to cyberloaf (e.g. tablets, smartphones), no
longer requiring that technology be organizationally provided. In fact, items in the most
commonly used cyberloafing measures focus on specific activities but do not specify how
employees obtained access to technology. These conceptual shifts reflect technological
advances that have occurred in the past two decades. For example, in the early days of
cyberloafing, internet access was less common and more expensive; therefore, employees’
unsanctioned use of organizationally provided bandwidth was a prime concern. Today, with
employees frequently bringing their own data-enabled devices to work, managers are
concerned with other consequences of cyberloafing, such as time theft, productivity losses,
or unsafe behaviors. Despite subtle differences among the many conceptualizations of
cyberloafing and related constructs, they uniformly focus on employees using technological
devices to facilitate a break or “escape”from work and attend to nonwork tasks. As such,
these behaviors can be considered a form of withdrawal that is facilitated by information
technology. Therefore, for the purposes of this study, we will inclusively conceptualize
cyberloafing as employee behaviors that involve using information and communication
technologies to engage in nonwork behaviors instead of working. This approach
encompasses the many definitions encountered in our systematic review of the literature.
Cyberloafing threatens nearly all organizations because employees in most jobs have the
opportunity to engage in these behaviors on a variety of information technology devices.
Workers paid hourly can cyberloaf during dedicated work hours just as salaried workers
can use the internet for personal matters instead of accomplishing work tasks.
A salesperson reading the news rather than helping a customer; a receptionist e-mailing
friends during work hours; and an executive browsing Facebook during meetings are all
examples of cyberloafing. Also, unlike hacking or financial theft, cyberloafing does not
require extensive technological skill or criminal intent. The increasing use of
organizationally and privately owned internet-connected technological devices for both
personal and professional purposes, and their ubiquity among workers across occupations
regardless of job complexity, make cyberloafing a serious organizational concern.
Some scholars have explored the construct’s structure and identified potential
dimensionality. Blanchard and Henle (2008) empirically distinguished two primary forms
of cyberloafing, minor and serious. In their taxonomy, minor cyberloafing consists primarily
of e-mail-related and slacking behaviors, whereas serious cyberloafing includes behaviors
such as viewing adult-oriented sites and online gambling. Other scholars have distinguished
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construct structure by the content of the behaviors, such as Lim and Teo’s (2005) e-mail vs
browsing distinction or Mahatanankoon et al.’s (2004) three dimensions of personal
web usage in the workplace: personal e-commerce (e.g. buying and selling online);
personal information research (e.g. researching personal hobbies); and personal
communication (e.g. interacting with family and friends). Because various investigations
have utilized different conceptualizations and measures of cyberloafing, there remains a
certain lack of clarity regarding the construct’s structure. Findings to date suggest that
cyberloafing ranges in severity and encompasses several different types of behaviors, from
surfing the internet and conducting personal errands to sending text messages and
communicating on social media while working.
The nomological network of cyberloafing has been of particular interest to researchers and
practitioners alike as they attempt to better understand the phenomenon and find paths to its
prediction and prevention. Scholars have examined a vast array of correlates. Classic theories
have guided investigation into cyberloafing’s relationships with perceptions of justice
(e.g. neutralization; Lim, 2002), employee attitudes, and intentions (e.g. theory of planned
behavior; Askew et al., 2014). Additionally, personality variables and job characteristics have
received attention, likely due to the direct practical implications of such findings (e.g. through
use in employee selection).
Beyond predicting cyberloafing, substantial inquiry has focused on whether
cyberloafing indeed results in detrimental outcomes (i.e. negatively relates to job
performance) or whether it might provide a necessary mechanism for overburdened
employees to take crucial breaks (i.e. with neutral or even positive impact on productivity).
Essentially, managers and researchers have both questioned whether cyberloafing is a
counterproductive work behavior. Media reports provide scenarios in which cyberloafing
is clearly counterproductive. For example, consider the train dispatcher who was playing
mobile games on the job (Smale, 2016). Due to his inattention, he failed to properly direct
two trains which then collided, leaving over 80 passengers injured and 11 killed.
As horrific and egregious as single cases may be, not all instances of cyberloafing
behaviors are necessarily deemed negative in the scholarly literature, which has presented
varied perspectives.
Block (2001) argued that cyberloafing was just a new version of traditional loafing; viewing
it as merely another form of employee counterproductivity; he posited that it should be
managed using the same techniques and strategies that had traditionally been effective for
other CWB. Bock and Ho (2009), along with others, demonstrated not only the negative
influence of nonwork-related computing on job performance but also the larger negative effects
of nonwork-related computing compared to other nonwork activities that do not involve
technology (e.g. traditional loafing). Another study investigated emergency department
employees’Facebook usage on hospital workstations and found the health care workers spent
an average of 12 minutes per hour browsing Facebook alone (Black et al., 2013). Unfortunately,
such nonwork-related behavior increased with workload, such that employees viewed
Facebook more frequently in times of higher patient volumeand severity. In this case,the costs
of a behavior as seemingly harmless as social networking extend beyond organizational
resource loss to more significant consequences, including endangering patient well-being.
In contrast, Cao et al. (2016) recently demonstrated that social media use can promote
employees’social capital,facilitating knowledge transfer and consequently work performance.
Lim and Chen (2012) also considered the potential benefits of cyberloafing to employees’
emotional states and demonstrated that certain forms of cyberloafing, such as browsing the
internet, positively influenced employees’positive affect. Beyond the costs and benefits of
cyberloafing to organizations, these behaviors may yield additional, nonwork benefits to
employees. Because technology has blurred the work-life boundaries for many workers,
invading personal time with work tasks (e.g. constant accessibility and off-hours e-mailing),
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employees may see cyberloafing as a way to restore the balance between work and
nonwork domains.
We have undertaken this review without an a priori judgment of how and why
cyberloafing behaviors should be addressed, recognizing their potential to be manifestations
of counterproductivity or opportunities for necessary cognitive relief. We attempt to
investigate the nomological network of cyberloafing and allow evidence to demonstrate the
nature and valence of these work behaviors. Employers are trying to reduce occurrence of
cyberloafing behaviors, but further insight is needed in order to determine whether (and if so,
to what extent) a reduction in employee cyberloafing actually aligns with organizational goals,
both in terms of productivity as well as employee engagement.
The present study
We have two primary objectives for this meta-analytic investigation of cyberloafing.
First, we seek to summarize the growing literature on cyberloafing and related constructs.
Although this body of work is still in its early stages, substantial progress has been made
over the past 15 years to understand these behaviors and their correlates. Because that
progress spanned different disciplines and conceptual labels, many important findings have
gone undetected rather than contributing to a coherent body of work. We hope that by
cumulating results from these studies, we can help catalyze research into employee
cyberloafing. The secondary objective for this study is to guide future research by
highlighting areas that are promising, yet neglected to date.
Methods
Literature search and inclusion criteria
We conducted a sixfold literature search to uncover studies that were relevant for inclusion
in the present set of meta-analyses. First, we searched the PsycINFO, PsycARTICLES,
Business Source Complete, Academic Search Complete, Social Sciences Full Text, and
SocINDEX with Full Text databases using the following keywords: personal internet use,
nonwork related computing, cyberloaf*, cyberslack*, cyberdevian*, and social media in
conjunction with (“AND”)employee*, work*, and job. We included databases from beyond
industrial organizational psychology, organizational behavior, and management due to the
interdisciplinary nature of the cyberloafing construct. Second, we used Google Scholar to
identify articles that cited Lim’s (2002) seminal article on cyberloafing. This technique
allowed us to locate many unpublished documents, including works-in-progress and
conference papers that were made available online by the authors. The majority of included
studies were sourced from these first two searches. Third, we conducted manual searches of
the programs from the annual conferences of the Academy of Management and the Society
for Industrial and Organizational Psychology for the past ten years, yielding 16 relevant
presentations. Six of those had since become available in other published form, and we
contacted the authors to inquire about the remaining ten. Of those authors contacted, three
provided sufficient results to be considered for inclusion. Fourth, because Computers in
Human Behavior was the most common publication outlet among the uncovered studies, we
also examined the journal’s upcoming issues, including articles that are available online
first, in press, or in preparation and may not yet be indexed. This search yielded three
relevant articles, two of which were usable. Fifth, we contacted prominent researchers in this
research domain to request potentially available raw data and unpublished work. However,
none of these researchers had unpublished work to share. Finally, we conducted a search of
the reference lists of all included studies. This yielded an additional 91 studies to be
considered for inclusion.
Studies with sufficient information to extract a correlation (or effect size that could be
converted to a correlation) between cyberloafing behaviors and any other variable were obtained.
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Over the past decade, constructs highly congruent with cyberloafing have emerged under
different labels in other disciplines, including cyberslacking, personal web usage,
technological time banditry, nonwork-related computing, social media use at work, and
counterproductive computer use (Anandarajan and Simmers, 2004; Bock and Ho, 2009;
Brock et al., 2013; Charoensukmongkol, 2014; Gallagher, 2009; Pee et al., 2008; Vitak et al., 2011).
Due to their conceptual similarity, we included a variety of these variables in our data set as
forms of cyberloafing. Although this approach leads to slightly more heterogeneous analyses in
terms of construct measures included, the primary differences between these behavioral
categories are their names, and it was our intention to examine the cyberloafing
construct comprehensively.
The initial database consisted of 221 sources that reported a relationship between
cyberloafing and other variables of interest. Of these, we retained only studies that met the
following five inclusion criteria: First, we only included studies that utilized behavioral
measures of cyberloafing (e.g. excluding studies relying purely on intentions to commit such
behaviors). Second, studies had to operationalize cyberloafing within an occupational
context (e.g. studies drawing on students cyberloafing in class were excluded). Third, we
included only studies that involved reports of employee cyberloafing behaviors in real work
settings and thus excluded experimental manipulations of cyberloafing in laboratory
studies. Fourth, we included studies that reported correlations or effect sizes that could be
converted to correlations, but not studies that only reported results from multiple regression
or structural equation modeling analyses. Fifth, we excluded any sources that suppressed
statistically insignificant results to avoid an upward bias in cumulated effects (Schmidt and
Hunter, 2014). In total, 49 studies met these inclusion criteria and were subsequently coded
by the second author. In total, 12 percent of these studies were coded by an additional coder;
they identified only one discrepancy, which was subsequently resolved. The coded studies
were based on 54 unique samples and yielded 609 separate effect sizes. Several studies
contributed multiple independent samples, which offset the deficit created by studies using
duplicate sample pools (e.g. Pew internet and American Life sample)[1]. In most studies,
numerous correlates were examined in each sample and thus contributed to separate meta-
analyses reported here. In order to avoid second order sampling error to the degree possible,
we analyze and report only relationships where at least three independent samples reported
an effect for the variables of interest, in line with previous conventions
(e.g. Berry et al., 2007; Cohen-Charash and Spector, 2001). In sum, we utilized 315 distinct
correlation coefficients to examine the relationships between cyberloafing and 40 variables.
Table I lists and defines the core constructs included in these analyses.
Measures of cyberloafing
Our broad literature search approach led to the inclusion of studies utilizing a wide variety of
measures of cyberloafing. Two of the most common measures, Lim’s (2002) and Lim and Teo’s
(2005) cyberloafing scales, asked how time was spent online at work. More recently, Mercado and
Dilchert (2016a, b, c, d) assessed the extent to which employees engage in various cyberloafing
behaviors while they should be working. Despite these differences, there is substantial similarity
across items both within and across measures, with each scale comprised primarily of various
internet browsing and messaging behaviors. Due to differences in facet structures across these
measures,withmanystudiesreportingonlyone general factor of cyberloafing, an overall
cyberloafing dimension was most appropriate and feasible for these meta-analyses.
Meta-analytic procedure
In addition to coding effect sizes between cyberloafing and each reported variable,
we recorded rating source (e.g. self-report, other rating, objective records), measure
characteristics (e.g. item number, reliability estimates), and sample characteristics
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(e.g. demographics and work experience) for potential use in moderator analyses.
Psychometric meta-analyses were conducted based on procedures outlined by Schmidt and
Hunter (2014) using the Open Psychometric Meta-Analysis software (Wiernik, 2015).
Occasionally, a single source reported multiple effect sizes from the same unique sample
that were relevant to the same analysis (e.g. multiple job performance facets). To ensure
Variable Definition
Cyberloafing Employee behaviors that involve using information and communication technologies
to engage in nonwork behaviors instead of working
Agreeableness The Big Five personality dimension reflecting the extent to which a person is likable,
cooperative, and conflict-avoidant
Conscientiousness The Big Five personality dimension reflecting the extent to which a person is
dedicated, disciplined, orderly, and detail-oriented
Emotional stability The Big Five personality dimension reflecting the extent to which a person is calm
and secure and is not anxious or volatile
Openness The Big Five personality dimension reflecting the extent to which a person is
curious, intelligent, imaginative, and independent
Extraversion The Big Five personality dimension reflecting the extent to which a person is
sociable, assertive, gregarious, and energetic
Self-control The personality trait reflecting the extent to which a person monitors and inhibits
his/her impulses, thoughts, and behaviors
Self-efficacy The extent to which a person believes in his/her own abilities, including general as
well as technology-specific forms of self-efficacy
Boredom The extent to which a person experiences a negative affective state of under-
stimulation and disengagement from his/her situation
Job satisfaction The extent to which an employee experiences a positive affective state upon
appraising his/her job
Attitudinal
engagement
The extent to which an employee is enthusiastic about his/her work and committed
to the organization, including identification with the job and perceptions of
meaningfulness with his/her work
Empowerment/job
autonomy
The extent to which an employee perceives authority or power over his/her work
tasks or within the workplace more generally
Support The extent to which an employee perceives support from his/her manager,
organization, or coworkers
Organizational justice The extent to which an employee perceives fairness in the workplace
Distributive justice The extent to which an employee perceives fairness in the distribution of outcomes
or rewards
Interactional justice The extent to which an employee perceives he/she has been fairly and
respectfully treated
Procedural justice The extent to which an employee perceives fairness in the processes used to
determine reward or outcome distribution
Neutralization The extent to which a person rationalizes deviant behaviors to justify or excuse them
Performance Employee behaviors that contribute to the organization and its members, including
job and task performance as well as citizenship behaviors
Overall CWB Employee behaviors that detract from organizational goals or well-being,
including those that bring about negative consequences for the organization
and/or its members
Time theft/loafing Employee behaviors that use paid work time for nonwork purposes
Norms The extent to which an employee perceives cyberloafing to be normal or prevalent in
his/her workplace
Monitoring The extent to which an employee perceives that his/her cyberloafing is being
monitored electronically by the organization
Guidelines or rules The extent to which a workplace is governed by guidelines, rules or policies about
technology use at work
Consequences The extent to which an employee perceives that there will be punishment, sanctions,
or other costs as a result of their cyberloafing
Table I.
Overview of
core constructs
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independence of effect size estimates contributing to each analysis, and (secondarily) to
ensure consistency with regard to the constructs included in each analysis, we formed
composite correlations (cf. Ghiselli et al., 1981) for cases where the required scale
intercorrelations were available and averaged effects if this was not the case. Averaging
correlations leads to a more conservative estimate of the underlying relationships; thus,
average correlations are acceptable alternatives when a composite cannot be computed
(Schmidt and Hunter, 2014). When composite correlations were calculated, reliabilities of the
composites were calculated using Mosier’s (1943) formula. In cumulating the available
effects in individual meta-analyses, the biasing influences of sampling error as well as
attenuation due to measurement error in the predictor and criterion were corrected using
statistical artifact distributions. A list of artifact distributions used in the corrections can be
found in Table II. Due to the limited number of studies as well as a lack of consistent
normative information for cyberloafing and other construct measures in this emerging
research domain, it was difficult to ascertain the extent to which range restriction had an
influence on the observed effects. Therefore, no corrections for range restriction could be
applied. Any resulting true correlations should be considered conservative estimates for this
reason. Moderator analyses were also not conducted due to the lack of consistently available
information as well as insufficient sample sizes from the included studies.
Results
Table III presents meta-analytic results for the relationship between cyberloafing,
demographic background, and employment variables. Gender and age displayed negligible
relationships with cyberloafing ( ρ¼−0.07, −0.08, respectively), whereas education
displayed a modest positive effect ( ρ¼0.11), signifying that more educated individuals
engaged in greater cyberloafing. Employment variables also exhibited varied relationships
with cyberloafing. Job tenure, organizational level, and income demonstrated negligible
effects ( ρ¼−0.08, 0.08, and 0.05, respectively), indicating that cyberloafing is pervasive
across various types of employees and organizational levels. However, hours worked per
week demonstrated a small positive relationship ( ρ¼0.12) with cyberloafing, indicating
that individuals engage in such behaviors as their time on the job/task increases.
Personality variables displayed a modest but persuasive pattern of true-score
correlations with cyberloafing (see Table IV ). While openness and extraversion were
unrelated to cyberloafing ( ρ¼0.01 and 0.00, respectively), agreeableness,
conscientiousness, and emotional stability demonstrated modest negative relationships
(ρ¼−0.11, −0.11, and −0.16, respectively). Such a pattern of results might be expected
based on previous findings on the relationships between these three Big Five dimensions
(often conceptualized as the core of a construct termed “socialization”)and
counterproductive work behaviors (CWB) (see Berry et al., 2007; Ones et al., 1993, 2005).
The two narrower traits for which sufficient data were available, self-control and
self-efficacy, displayed even more notable relationships. Self-control demonstrated a
negative and moderately strong relationship ( ρ¼−0.32); self-efficacy (across global and
computer/internet-specific measures) exhibited a moderate positive relationship with
cyberloafing ( ρ¼0.20)[2]. In sum, individuals who are high in self-control are less likely to
exhibit cyberloafing; the same is true (albeit to a lesser degree) of individuals who are high
in socialization as well as those lower on self-efficacy.
We next examined the relationships between attitudinal, engagement, and organization
perception variables and cyberloafing (see Table V ). Both boredom and empowerment/job
autonomy demonstrated moderate positive relationships with cyberloafing ( ρ¼0.24 and
0.21, respectively), indicating that bored employees and those who are empowered to
determine the course of their daily actions are more likely to engage in cyberloafing.
In contrast, employee engagement was moderately negatively related to cyberloafing
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(ρ¼−0.21), suggesting that engaged employees who are highly committed to their jobs will
be less likely to cyberloaf. Cyberloafing was negligibly related to both job satisfaction
(ρ¼−0.04, and 0.01, with and without one extreme outlier, respectively) and perceptions of
organizational support ( ρ¼0.03).
Following employee attitudes, we considered how employee perceptions of the organization
might influence their behaviors. Organizational justice demonstrated a small negative
Variable k rxx SDrxx Mffiffiffiffiffi
rxx
pSD ffiffiffiffiffiffi
rxx
p
Cyberloafing 42 0.87 0.07 0.93 0.04
Emotional stability
a
459 0.77 0.10 0.87 0.06
Extraversion
a
186 0.80 0.07 0.89 0.04
Openness
a
32 0.76 0.08 0.87 0.05
Agreeableness
a
26 0.79 0.05 0.89 0.03
Conscientiousness
a
90 0.77 0.08 0.87 0.05
Self-control
a
48 0.70 0.12 0.84 0.07
Self-efficacy
a
264 0.90 0.00 ––
Boredom 7 0.91 0.04 0.95 0.02
Job satisfaction
a
13 0.84 0.06 0.92 0.03
Attitudinal engagement 5 0.88 0.09 0.94 0.05
Empowerment/job autonomy 3 0.90 0.02 0.95 0.01
Support 4 0.83 0.11 0.91 0.06
Organizational justice 5 0.92 0.04 0.96 0.02
Distributive justice
a
66 0.91 –– –
Interactional justice 8 0.86 0.06 0.92 0.04
Procedural justice
a
66 0.91 –– –
Neutralization 3 0.89 0.05 0.94 0.03
Performance
a,b
7 0.90 –– –
Overall CWB 7 0.86 0.05 0.93 0.03
Time theft/loafing 4 0.70 0.06 0.84 0.04
Favorable attitude toward cyberloafing 7 0.90 0.04 0.95 0.02
Intentions to cyberloaf 6 0.89 0.09 0.94 0.05
Perceived benefits of cyberloafing 4 0.89 0.05 0.94 0.03
Habitual cyberloafing 5 0.86 0.07 0.93 0.04
Usage/time on internet 1 0.91 0.00 0.95 0.00
Internet/social media skills/experience 1 0.79 0.00 0.89 0.00
Ability to hide cyberloafing 3 0.89 0.03 0.94 0.02
Norms 10 0.86 0.08 0.93 0.04
Monitoring 2 0.75 0.01 0.86 0.01
Guidelines or rules 2 0.73 0.00 0.85 0.00
Consequences 4 0.89 0.06 0.94 0.03
Notes: k, number of independent reliability estimates in distribution; rxx , average reliability estimate; SDrxx ,
standard deviation of reliability estimates; Mffiffiffiffiffi
rxx
p, average of the square roots of reliability estimates; SD ffiffiffiffiffiffi
rxx
p,
standard deviation of the square roots of the reliability estimate. Analyses for variables not listed in this table
were not corrected for attenuation due to unreliability.
a
Reliability artifact distribution obtained from existing
meta-analytic literature; for rows with missing SD of estimates, only kand the mean of estimates were
available from the literature. Reliability artifact distributions for Big Five personality trait measures as well
as the compound trait self-control were obtained from Dilchert (2008), who compiled comprehensive artifact
distributions based on meta-analytic work by Ones and colleagues (sources included Birkland and Ones, 2006,
for emotional stability; Davies et al., 2008, for extraversion; Connelly et al., 2008, for openness; Connelly et al.,
2008, for Agreeableness; and Connelly and Ones, 2007, for conscientiousness). The artifact distribution for
self-efficacy measures was obtained from Seltzer (2013);
b
the typically more suitable value of 0.52 used in
most meta-analysis of supervisory ratings of job performance was not used, as all studies contributing to the
present meta-analysis employed exclusively self-report measures of performance. Correlations with job
performance were corrected using an internal consistency reliability estimate of 0.90, based on seven values
reported in the meta-analysis by Harris and Schaubroeck (1988)
Table II.
Reliability artifact
distributions
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relationship with cyberloafing ( ρ¼−0.12); this effect also occurred at the dimension level for
interactional justice and procedural justice ( ρ¼−0.10 and −0.11, respectively) but not
distributive justice ( ρ¼0.00). Neutralization, a rationalization process that utilizes perceptions
of inequity as justification for one’s own wrongdoing, was strongly positively related to
cyberloafing ( ρ¼0.43), suggesting that individuals are more likely to engage in it if they feel
they are owed due to not being repaid for investments they have made into the company.
Next, we examined the influence of employees’attitudes toward cyberloafing and their
opportunities to engage in these behaviors (see Table VI for detailed results). Favorable
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Gender
a
23 7,019 −0.07 0.11 0.09 0.02 −0.07 0.10 −0.11, −0.03 −0.20, 0.05
Age 23 8,301 −0.08 0.12 0.10 0.02 −0.08 0.11 −0.13, −0.04 −0.22, 0.06
Education 6 2,948 0.11 0.13 0.12 0.05 0.11 0.13 0.00, 0.23 −0.05, 0.28
Hours worked 6 1,858 0.11 0.06 0.00 0.02 0.12 0.00 0.07, 0.17 0.12, 0.12
Job tenure 10 3,116 −0.07 0.10 0.08 0.03 −0.08 0.09 −0.14, −0.01 −0.19, 0.03
Organization level 8 2,943 0.07 0.13 0.12 0.05 0.08 0.13 −0.01, 0.17 −0.08, 0.24
Income 8 2,807 0.05 0.11 0.10 0.04 0.05 0.11 −0.03, 0.14 −0.08, 0.19
Notes: k, number of independent samples contributing to analysis; N, total sample size; r, mean sample-size-
weighted observed correlation; SD
r
, standard deviation of mean sample-size-weighted correlations; SD
res
,
residual standard deviation; SEr, standard error of r;ρ, true-score correlation (corrected for unreliability in
both measures for cases where artifact distributions are listed in Table II); 90% CI
ρ
¼90% confidence interval
of ρ; 80% CV
ρ
¼80% credibility values of ρ.
a
Male ¼0, female ¼1
Table III.
Meta-analytic results
for demographic
background and
employment variables
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Emotional stability 8 2,253 −0.13 0.08 0.05 0.03 −0.16 0.06 −0.22, −0.09 −0.24, −0.08
Extraversion 7 2,006 0.00 0.10 0.08 0.04 0.00 0.09 −0.08, 0.09 −0.12, 0.12
Openness 7 2,006 0.01 0.07 0.04 0.03 0.01 0.05 −0.06, 0.07 −0.05, 0.07
Agreeableness 7 2,005 −0.09 0.06 0.00 0.02 −0.11 0.00 −0.16, −0.06 −0.12, −0.11
Conscientiousness 11 3,212 −0.09 0.07 0.04 0.02 −0.11 0.05 −0.16, −0.07 −0.17, −0.05
Self-control 5 1,224 −0.25 0.27 0.27 0.12 −0.32 0.34 −0.65, 0.02 −0.76, 0.12
Self-efficacy 6 1,744 0.17 0.10 0.08 0.04 0.20 0.09 0.10, 0.29 0.08, 0.31
Note: See Table III for notes
Table IV.
Meta-analytic results
for personality
variables
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Boredom 7 1,939 0.21 0.08 0.05 0.03 0.24 0.06 0.17, 0.31 0.16, 0.32
Job satisfaction 14 4,868 −0.04 0.19 0.18 0.05 −0.04 0.22 −0.15, 0.06 −0.32, 0.23
(without outlier) 13 4,595 0.01 0.06 0.03 0.02 0.01 0.04 −0.03, 0.05 −0.04, 0.06
Attitudinal engagement 7 2,333 −0.18 0.20 0.19 0.08 −0.21 0.22 −0.40, −0.02 −0.49, 0.07
Empowerment/job
autonomy 4 1,788 0.18 0.09 0.08 0.05 0.21 0.09 0.08, 0.33 0.09, 0.32
Support 4 866 0.03 0.10 0.07 0.05 0.03 0.08 −0.11, 0.17 −0.08, 0.14
Organizational justice 6 1,132 −0.10 0.08 0.04 0.03 −0.12 0.04 −0.19, −0.04 −0.17, −0.06
Distributive justice 8 2,051 0.00 0.16 0.15 0.06 0.00 0.17 −0.12, 0.12 −0.21, 0.22
Interactional justice 8 2,585 −0.09 0.14 0.13 0.05 −0.10 0.15 −0.21, 0.01 −0.29, 0.09
Procedural justice 9 2,289 −0.10 0.15 0.14 0.05 −0.11 0.15 −0.22, −0.01 −0.30, 0.08
Neutralization 3 684 0.38 0.08 0.05 0.04 0.43 0.05 0.28, 0.58 0.36, 0.50
Note: See Table III for notes
Table V.
Meta-analytic results
for attitudinal,
engagement, and
organization
perception variables
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attitudes toward cyberloafing exhibited a strong positive relationship ( ρ¼0.42) and
intentions to cyberloaf very strongly positively correlated with cyberloafing ( ρ¼0.61).
Additionally, employee perceptions of the benefits of cyberloafing demonstrated a moderate
positive relationship with the construct ( ρ¼0.28). Habitual cyberloafing exhibited a very
strong positive effect on cyberloafing ( ρ¼0.66), indicating that individuals who display
addictive behavioral tendencies of technology use across life contexts engage in more
cyberloafing at work. Employees’technology access (e.g. the proportion of time spent on the
internet) was positively related to cyberloafing ( ρ¼0.20). Employees’technology skills and
experience strongly positively related to the construct ( ρ¼0.40). Additionally, as might be
expected, employees’ability to hide cyberloafing demonstrated a strong positive
relationship with cyberloafing ( ρ¼0.41).
We also examined the relationships between cyberloafing and CWB as well as overall
performance, conceptualized heterogeneously as the positive components of job performance
(e.g. work performance, task performance, organizational citizenship behaviors; see Table VII).
Cyberloafing was negligibly related to performance ( ρ¼−0.05), yet it was strongly positively
related to overall CWB ( ρ¼0.38) and the narrower counterproductivity construct of time theft/
loafing other than cyberloafing ( ρ¼0.39). To better understand the structure and homogeneity
of the construct, we also investigated the intercorrelations among facets of cyberloafing in the
few studies that reported such results (see Table VIII). Whether studies separated cyberloafing
by content of behavior (e.g. e-mailing vs browsing) or severity, subscales of cyberloafing were
very highly correlated ( ρs¼0.69 and 0.71, respectively for content and severity taxa).
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Favorable attitude toward
cyberloafing 8 1,919 0.37 0.14 0.12 0.05 0.42 0.14 0.32, 0.52 0.24, 0.60
Intentions to cyberloaf 6 1,622 0.53 0.05 0.03 0.02 0.61 0.03 0.55, 0.66 0.56, 0.65
Perceived benefits of cyberloafing 5 2,201 0.24 0.23 0.23 0.10 0.28 0.26 0.02, 0.53 −0.06, 0.61
Habitual cyberloafing 5 851 0.57 0.14 0.13 0.06 0.66 0.15 0.50, 0.81 0.47, 0.85
Usage/time on internet 9 2,745 0.17 0.09 0.07 0.03 0.20 0.07 0.14, 0.26 0.10, 0.29
Internet/social media skills/experience 3 742 0.33 0.14 0.13 0.08 0.40 0.16 0.11, 0.69 0.20, 0.60
Ability to hide cyberloafing 3 695 0.36 0.13 0.11 0.07 0.41 0.13 0.16, 0.65 0.24, 0.57
Note: See Table III for notes
Table VI.
Meta-analytic results
for attitude and
opportunity variables
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Performance 14 3,866 −0.05 0.16 0.15 0.04 −0.05 0.17 −0.14, 0.04 −0.27, 0.17
Overall CWB 9 2,659 0.32 0.12 0.11 0.04 0.38 0.12 0.29, 0.46 0.22, 0.53
Time theft/loafing 4 1,150 0.30 0.16 0.15 0.08 0.39 0.19 0.15, 0.63 0.15, 0.64
Note: See Table III for notes
Table VII.
Meta-analytic results
for performance
variables
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
E-mailing activities
Browsing activities 4 1,010 0.61 0.07 0.05 0.04 0.69 0.06 0.59, 0.79 0.61, 0.76
Serious behaviors
Minor behaviors 2 561 0.59 0.21 0.21 0.15 0.71 0.25 −0.44, 1.00 0.39, 1.00
Note: See Table III for notes
Table VIII.
Meta-analytic
intercorrelation results
for cyberloafing facets
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The last group of variables we examined consisted of organizational norms and policies
(see Table IX for detailed results). Although monitoring exhibited a negligible relationship
with cyberloafing ( ρ¼−0.06), organizational guidelines or rules governing technology use
negatively influenced cyberloafing ( ρ¼−0.15). In contrast, employees’perceptions of
negative consequences of cyberloafing were unrelated to the criterion ( ρ¼0.01). Unlike the
other organizational influences, norms were strongly positively related to cyberloafing
(ρ¼0.37), such that employees who perceived cyberloafing behaviors to be normal and
prevalent were substantially more likely to display such behaviors themselves.
Discussion and directions for future research
Results from this first meta-analysis of the increasingly popular cyberloafing construct
yielded several noteworthy findings. First, although young, inexperienced employees
(or specific generations and cohorts, such as Millennials) are often accused of greater misuse
of information technology and increased cyberloafing, our results indicate that age, job
tenure, and organizational level are unrelated to the phenomenon. This is particularly
striking, given current, widespread concerns regarding the unprofessionalism of today’s
younger cohorts with regard to many workplace behaviors, especially those relating to
information technology use (e.g. Center for Professional Excellence at York College of
Pennsylvania, 2013). This disparity between coworkers’perceptions of younger employees’
technology use and the lack of age effects in cyberloafing may be explained by the largely
hidden nature of technology use. Younger employees might more readily adopt technology
in general, which might be misinterpreted by colleagues as cyberloafing. In contrast to the
negligible effects of age, education demonstrated a small positive effect on cyberloafing.
Although surprising, the positive effect of job autonomy may shed some light on this
finding, given the likelihood that individuals with higher education might hold positions
granting them more opportunities to cyberloaf.
Second, although several broader personality variables exhibited relationships with
cyberloafing, we identified two narrow personality traits that were more useful in
explaining potential mechanisms. For example, self-control was strongly negatively
related to cyberloafing. This evidence is in line with research on the importance of
predictor-criterion bandwidth matching, and suggests that further investigation into
specific personality traits and their relationships with this narrow-bandwidth subset of
work behaviors is merited. An important caveat should be noted: although these initial
findings are interesting, the self-control-cyberloafing relationship was limited by a very
small number of samples contributing to the analyses (k¼5). These effects certainly merit
further empirical investigation across new samples and job contexts. Research examining
the mechanisms underlying this relationship can enhance understanding of cyberloafing as
well as provide an evidence-based foundation on which to develop managerial interventions
to reduce these behaviors.
Another narrow trait, self-efficacy, also demonstrated a noteworthy relationship with
cyberloafing. Most importantly, self-efficacy is generally regarded as a desirable trait as it
empowers individuals to accomplish their tasks. However, in this case, our findings indicate
Variable kN rSD
r
SD
res
SE of rρSD
ρ
90% CI
ρ
80% CV
ρ
Norms 12 2,580 0.32 0.17 0.16 0.05 0.37 0.18 0.27, 0.47 0.14, 0.61
Monitoring 7 1,504 −0.05 0.06 0.00 0.02 −0.06 0.00 −0.11, 0.00 −0.06, −0.06
Guidelines or rules 8 2,430 −0.12 0.15 0.13 0.05 −0.15 .17 −0.27, −0.03 −0.37, 0.07
Consequences 5 996 0.00 0.26 0.25 0.11 0.01 0.28 −0.27, 0.28 −0.35, 0.36
Note: See Table III for notes
Table IX.
Meta-analytic results
for norms and
organizational policies
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that self-efficacy exhibits a moderate positive relationship with cyberloafing. This is yet
another opportunity for future research to more deeply explore the mechanism of the
cyberloafing phenomenon. Employers would not typically wish to reduce the self-efficacy of
their employees (either general or computer-specific), yet they may wish to diminish their
employees’cyberloafing. Further investigation is necessary to determine how employers
can continue to encourage self-efficacy among their employees without fostering
cyberloafing. Does quantity of workload influence the effects of self-efficacy? Do people
with high self-efficacy exhibit greater optimism with regard to task ease and thus feel
enabled to procrastinate? Do capable employees experience greater boredom? Do employees
with greater self-efficacy feel more fully invested in their organizations and thus rationalize
their cyberloafing? Finally, how do computer/internet specific self-efficacy measures
interact with opportunity to engage in or hide cyberloafing in determining employees’
behaviors? Each of these questions presents an opportunity for future investigation that can
guide distinct and practically meaningful organizational interventions. Another strong
predictor of cyberloafing was a rationalization technique called neutralization. The studies
that we meta-analyzed operationalized neutralization using the “metaphor of the ledger,”
which consists of employees considering how much they contribute to the organization.
Then, the employees evaluate whether they feel they have been sufficiently compensated or
recognized for those contributions. If they do not feel that the relationship is equitable,
employees feel reduced guilt and enhanced justification when engaging in questionable acts.
Very little research has examined neutralization in the context of cyberloafing
(in our analyses, k¼3), but some scholars have already begun to examine the
mechanisms at play in this relationship. For example, perceptions of injustice have been
examined as a predictor of neutralization (Lim, 2002). However, the scholarly literature has
yet to examine how employees’experiences of neutralization and consequent cyberloafing
behavior might be positively influenced. Are there opportunities to alleviate these
perceptions of inequity before the situation escalates? Can these negative employee
experiences be remedied, at least in part, by avenues to voice employees’concerns and
managerial interventions that prioritize them? Although rationalization is generally linked
to undesirable behaviors, few empirical investigations to date have attempted to provide
solutions to these problems.
Much concern about cyberloafing has stemmed from its apparent prevalence within
organizations. Most people have witnessed or participated in these behaviors, and many
employers have terminated employees for them (American Management Association and
The ePolicy Institute, 2007). Our findings on the strong relationship between norms and
cyberloafing further emphasize the problematic nature of cyberloafing becoming a normal
and acceptable behavior. People who do not perceive these behaviors as deviant are
substantially more likely to engage in them, thus perpetuating the normality of these largely
unproductive behaviors. Perhaps further contributing to this issue is the ineffectiveness of
monitoring initiatives and sanctions in the management of these behaviors. While such
interventions might be indirectly responsible for some deterrence via norms, they are clearly
insufficient to address the growing trend. Therefore, new interventions merit further
exploration, potentially including personnel selection and training to influence norms as
well as job design considerations to account for bored and disengaged employees.
Cyberloafing has become controversial in recent years as scholars have debated its
nature as a negative detractor from organizational effectiveness vis-a-vis a positive
contributor to employee productivity and well-being via recovery. Although our analyses do
not allow us to infer the nature of these relationships, our findings do indicate that
cyberloafing is only negligibly related to job performance. This does not mean
that cyberloafing is entirely unproblematic. On the contrary, our results indicate that
cyberloafing is strongly positively related to overall CWB as well as the narrower
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counterproductivity construct of time theft/loafing. Future research is necessary to better
understand this phenomenon, particularly in light of past research indicating that other
forms of counterproductive behaviors negatively relate to the positive components of job
performance (Berry et al., 2007; Dalal, 2005; Rotundo and Sackett, 2002). It is possible that
the apparent null relationship between cyberloafing and performance is instead
substantially more complex, moderated by the length, frequency, or type of cyberloafing
where only some forms or levels are problematic. The various conceptualizations of
cyberloafing included in this analysis may also be responsible for these findings.
The majority of studies summarized in our meta-analyses relied on measures that did not
explicitly mention whether the behavior was interfering with a work task, thus
compromising performance. For example, social media use in the workplace may manifest
itself in a variety of ways, some perhaps restorative or merely insubstantial, while others
could compromise performance for an entire workday (e.g. constant connectivity that
distracts from a task which requires focus). In addition, using the measures employed by
these studies, the same behavior could be counterproductive for some employees (e.g. those
who should be working) but not for others who might have downtime while they await
their next task, a rationale consistent with earlier arguments by information systems
scholars (e.g. Silver et al., 1995).
Even if cyberloafing serves as an effective recovery method for employees, it still has
substantial potential to cause harm to the organization. Employers should consider ways to
differentiate between legitimate and illegitimate (i.e. counterproductive) forms of
cyberloafing. If cyberloafing is a type of positive break, it can be managed similarly to
other work breaks, which are typically governed by organizational guidelines and
sanctions. For example, in many positions, meal and rest breaks are clearly delineated and
monitored. If such breaks were not governed, some individuals would abuse the
opportunity, and such behavior would be considered a form of CWB by most definitions.
The same approach can be taken in managing cyberloafing to provide fair and equitable
treatment across employees while also preserving productivity. Related to the limitations
listed above, we found several notable methodological weaknesses in primary studies.
First, we found that many different scales are utilized to assess cyberloafing and related
constructs. Although the differences sometimes reflect only a slightly different
conceptualization, they are typically the result of each study adapting a common
measure (i.e. Lim, 2002; Lim and Teo, 2005). This has led to extensive inconsistency and
sometimes incomparability across studies. Just as importantly, the proliferation of measures
has hindered the advancement of systematic research on cyberloafing as many studies
focus on adapting and validating scales for specific applications rather than on furthering
our understanding of these important employee behaviors generally. The majority of
studies that adapt common measures often do so without providing psychometric evidence
to support those decisions. For this literature to evolve and grow systematically, a validated,
generally applicable scale must be established and widely accepted. Although the analyses
relied on few studies, we were encouraged by the strong convergence of cyberloafing facets,
demonstrating substantial homogeneity across items and supporting our decision to focus
on overall cyberloafing. Although the construct of cyberloafing has been assessed in many
different ways, there is a notable lack of other-reports of employee cyberloafing. This is
perhaps to be expected, as previous works on cyberloafing have emphasized the potential
for employees to conceal these behaviors (Wagner et al., 2012; Zhang et al., 2015). However,
especially considering the notable relationship between cyberloafing and habitual
cyberloafing, employees may not fully recognize the extent to which they engage in these
behaviors. Other reports might provide deeper insights into these behaviors.
Another methodological limitation of cyberloafing investigations to date is that they
have assumed stability in employee cyberloafing over time. Essentially, these behaviors are
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assessed as though employees maintain a constant level of cyberloafing. However, there are
rational arguments –and some limited empirical evidence –to suggest that situational
influences can have more substantial impact on cyberloafing on certain occasions (e.g. when
employees are sleep-deprived; Wagner et al., 2012). Therefore, within-subject investigation into
the changes in employee cyberloafing would greatly contribute to this growing literature.
Conclusions
In this study, we meta-analytically summarized the growing literature on employee
cyberloafing. Our findings suggest several important influences on these generally undesirable
behaviors, including moderate effects of personality variables as well as strong effects of
contextual influences (e.g. norms) and employee attitudes. Just as importantly, we identified
many opportunities for future development of this literature. Investigations of cyberloafing are
still in their nascent stages, and extensive research is needed to better understand these
employee behaviors and their antecedents and outcomes. Prior to this study, the various
studies on cyberloafing each created new frameworks based on a limited number of variables
relevant to one specific foundational theory (e.g. theory of planned behavior). While continued
development of this literature is necessary, we hope that these findings will aid researchers in
developing frameworks more holistically and selecting variables based on evidence of their
relevance to the relationship of interest. The present set of meta-analytic results can provide a
starting place for a more empirically grounded approach to model formation.
Notes
1. Following proper meta-analytic procedure, each unique sample contributed to any given analysis only
once, even if it was reported in multiple sources. In those cases, the source with the most comprehensive
information (e.g. on predictor or criterion measures or reliability estimates) was included.
2. Seltzer’s (2013) meta-analytic investigation showed that there is high convergence of global and
domain-specific self-efficacy measures, as well as high convergence of self-efficacy measures across
different specific domains. This, in addition to the modest SD
ρ
, suggests relative homogeneity and
generalizability of findings despite the inclusion of the different types of scales in this analysis.
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Corresponding author
Brittany K. Mercado can be contacted at: bmercado2@elon.edu
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