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Do the Hustle! Empowerment from Side-Hustles and Its Effects on Full-Time Work Performance

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Side-hustles, income-generating work performed alongside full-time jobs, are increasingly common as the gig economy provides opportunities for employees to perform supplementary work. Although scholars suggest that side-hustles conflict with full-time work performance, we assert psychological empowerment from side-hustles enriches full-time work performance. We argue that side-hustle complexity—the motivating characteristics of side-hustles—positively relates to empowerment and that side-hustle motives moderate this relationship. A study of 337 employees supports these assertions. We then investigate spillover of side-hustle empowerment to full-time work performance in a 10-day experience-sampling method study of 80 employee-coworker dyads. We address an affective pathway in which daily side-hustle empowerment enriches full-time work performance through side-hustle engagement and positive affect at work. We also consider a cognitive pathway in which side-hustle empowerment distracts from full-time work performance through side-hustle engagement and attention residue—persistent cognitions about side-hustles during full-time work. Overall, performance enrichment from side-hustles was stronger than performance conflict. We also consider affective shift from full-time work to side-hustles, finding negative affect from full-time work strengthens the relationship between side-hustle empowerment and engagement. Combined, our two studies examine the source of side-hustle empowerment and how and why side-hustle empowerment influences affective and cognitive experiences during full-time work.
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Do the Hustle! Empowerment from Side-hustles and Its
Effects on Full-time Work Performance
Journal:
Academy of Management Journal
Manuscript ID
AMJ-2018-0164.R3
Manuscript Type:
Revision
Keywords:
Work and family < Human Resource Management and Industrial
Relations < Topic Areas, Job design, roles, and tasks < Organizational
Behavior < Topic Areas, Empowerment < Group/team emergent states <
Organizational Behavior < Topic Areas
Abstract:
Side-hustles, income-generating work performed alongside full-time
jobs, are increasingly common as the gig economy provides
opportunities for employees to perform supplementary work. Although
scholars suggest that side-hustles conflict with full-time work
performance, we assert psychological empowerment from side-hustles
enriches full-time work performance. We argue that side-hustle
complexity—the motivating characteristics of side-hustles—positively
relates to empowerment and that side-hustle motives moderate this
relationship. A study of 337 employees supports these assertions. We
then investigate spillover of side-hustle empowerment to full-time work
performance in a 10-day experience-sampling method study of 80
employee-coworker dyads. We address an affective pathway in which
daily side-hustle empowerment enriches full-time work performance
through side-hustle engagement and positive affect at work. We also
consider a cognitive pathway in which side-hustle empowerment
distracts from full-time work performance through side-hustle
engagement and attention residue—persistent cognitions about side-
hustles during full-time work. Overall, performance enrichment from
side-hustles was stronger than performance conflict. We also consider
affective shift from full-time work to side-hustles, finding negative affect
from full-time work strengthens the relationship between side-hustle
empowerment and engagement. Combined, our two studies examine the
source of side-hustle empowerment and how and why side-hustle
empowerment influences affective and cognitive experiences during full-
time work.
Academy of Management Journal
Do the Hustle! Empowerment from Side-hustles and
Its Effects on Full-Time Work Performance
Hudson Sessions
University of Oregon
Sessions@uoregon.edu
Jennifer D. Nahrgang
Arizona State University
Jennifer.Nahrgang@asu.edu
Manuel J. Vaulont
Arizona State University
Manuel.Vaulont@asu.edu
Raseana Williams
Arizona State University
Raseana.Williams@asu.edu
Amy L. Bartels
University of Nebraska-Lincoln
Amy.Bartels@unl.edu
Correspondence concerning this article should be addressed to Hudson Sessions, Lundquist College of
Business, University of Oregon (Sessions@uoregon.edu).
We thank Markus Baer and three anonymous reviewers for helping us to improve our work. We are also
grateful for insightful feedback from Mike Baer and Kevin Corley. We acknowledge the financial support
provided by the Department of Management and Entrepreneurship at Arizona State University. We also
acknowledge a presentation of an earlier version of our work at the 2018 Annual Meeting of the Academy
of Management in Chicago, Illinois.
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DO THE HUSTLE! EMPOWERMENT FROM SIDE-HUSTLES AND ITS EFFECTS ON
FULL-TIME WORK PERFORMANCE
ABSTRACT
Side-hustles, income-generating work performed alongside full-time jobs, are
increasingly common as the gig economy provides opportunities for employees to perform
supplementary work. Although scholars suggest that side-hustles conflict with full-time work
performance, we assert psychological empowerment from side-hustles enriches full-time work
performance. We argue that side-hustle complexity—the motivating characteristics of side-
hustles—positively relates to empowerment and that side-hustle motives moderate this
relationship. A study of 337 employees supports these assertions. We then investigate spillover
of side-hustle empowerment to full-time work performance in a 10-day experience-sampling
method study of 80 employee-coworker dyads. We address an affective pathway in which daily
side-hustle empowerment enriches full-time work performance through side-hustle engagement
and positive affect at work. We also consider a cognitive pathway in which side-hustle
empowerment distracts from full-time work performance through side-hustle engagement and
attention residue—persistent cognitions about side-hustles during full-time work. Overall,
performance enrichment from side-hustles was stronger than performance conflict. We also
consider affective shift from full-time work to side-hustles, finding negative affect from full-time
work strengthens the relationship between side-hustle empowerment and engagement.
Combined, our two studies examine the source of side-hustle empowerment and how and why
side-hustle empowerment influences affective and cognitive experiences during full-time work.
With the rise of platform technologies and increased demand for freelancers, contractors,
and other “gig” workers (Maxim & Muro, 2018), it has never been easier for employees to
supplement their primary employment with a side-hustle, or income-generating work performed
alongside a full-time job (Ashford, Caza, & Reid, 2018; Dokko, Mumford, & Schanzenbach,
2015; Merriam-Webster Online Dictionary, n.d.). The ubiquity of the phenomenon can be seen
in the estimated 44 million US workers who participate in side-hustles (Clark, 2017, 2018), as
well as books, social media sites, and podcasts dedicated to serving those seeking or managing
side-hustles (e.g., Guillebeau, 2017; Loper, 2013). Indeed, Uber’s (2018) recent advertising
campaign goes as far as to invite everyone with a car to “get your side-hustle on” by driving for
Uber on the side.
Although they are widespread, side-hustles have been disparaged by both employers and
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scholars, who characterize them as an activity that conflicts with full-time work performance.
For example, some organizations explicitly prohibit side-hustles in their employment contracts
(Kirkham, 2017; Lussier & Hendon, 2018). Scholars have predominantly upheld this perspective
about the detriments of side-hustles, arguing that side-hustles are a “distraction that harms job
performance” (Rodell, 2013: 1275; see also Betts, 2006; Sliter & Boyd, 2014). The basis of this
assertion is that a side-hustle drains an employee’s finite resources, thereby diminishing their
capacity to perform well in a full-time job (e.g., Barnett, 1998; Haas, 1999). This consensus
about the derogative effects of side-hustles suggests to managers and employees that
participating in side-hustles is detrimental to the successful performance of full-time work.
Although this consensus is intuitive, we challenge it by suggesting that employees may
accrue benefits from side-hustles that, in turn, enrich full-time work performance. Specifically,
side-hustles provide opportunities to personalize, direct, and take ownership of work (e.g.,
Petriglieri, Ashford, & Wrzesniewski, 2019). Consider, for example, a full-time accountant who
has a side-hustle of completing odd jobs on TaskRabbit—an online platform that matches
freelance labor with local demand. This individual has control over when, where, and how to
approach work for TaskRabbit and is otherwise closely connected to the work process and
outcomes. The experience of these work characteristics may promote the individual’s sense of
empowerment, or sense of freedom to shape an activity and its context (Spreitzer, 1995). In turn,
the positive day-to-day experience of side-hustle empowerment may carry forward to enrich full-
time work performance. We ground our theory building about the positive spillover of side-
hustles in role enrichment theory—a theory of the beneficial effects of psychological resources
transferred between domains (Greenhaus & Powell, 2006)—and concurrently consider the
potential for side-hustles to distract from full-time work performance.
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Given organizations’ and scholars’ potential misunderstanding of the interplay of side-
hustles and full-time work, the purpose of our paper is to (1) advance understanding of the
prevalent phenomenon of side-hustles and (2) shift the consensus about how and why side-
hustles impact performance in one’s full-time job. We address both of these points in a novel
way by employing an empowerment perspective. As a first step toward unpacking the
phenomenon of side-hustles, we consider what makes side-hustles empowering. We argue that
side-hustle empowerment depends on the work characteristics of the side-hustle (i.e., side-hustle
complexity) and the reasons why employees participate in side-hustles (i.e., side-hustle motives).
We combine these two considerations to investigate how side-hustle motives moderate the
relationship between side-hustle complexity and side-hustle empowerment.
Building on this consideration of between-person differences in side-hustle
empowerment, we then examine the spillover of daily side-hustle empowerment to full-time
work performance. Scholarly and practical interest in empowerment has largely stemmed from
its downstream effects on employee motivation and, subsequently, performance (Thomas &
Velthouse, 1990). We assert that daily side-hustle empowerment exerts spillover effects through
side-hustle engagement, a motivational state entailing positive affect and cognitive attention and
absorption (Kahn, 1990; Newton, LePine, Kim, Wellman, & Bush, 2020; Schaufeli, Bakker, &
Salanova, 2006). Given the affective and cognitive nature of engagement, we outline an affective
pathway in which daily side-hustle empowerment enriches full-time work performance through
increased side-hustle engagement and positive affect within full-time work, and we address a
cognitive pathway in which daily side-hustle empowerment distracts from full-time work
performance through increased side-hustle engagement and ensuing attention residue (Leroy,
2009; Newton et al., 2020). Finally, we consider a reciprocal effect of full-time work on side-
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hustles by using the affective shift model (Bledow, Schmitt, Frese, & Kühnel, 2011) to
understand when the affective and cognitive paths we outline may be stronger or weaker.
We make several contributions. First, we advance understanding of how the changing
world of work shapes outcomes for employees and organizations. The increase in gig work in the
US represents nearly all of net employment growth since 2005, and gig work is even more
prevalent outside the US (Cappelli & Keller, 2013; Katz & Krueger, 2016). Addressing this
development, Ashford and colleagues (2018: 24) assert that “the new world of work is on our
doorstep, and organizational studies seems woefully unprepared.” Our study of side-hustles
examines a unique, contemporary work-arrangement in which we argue that workers anchor the
benefits of independent gig work (i.e., empowerment) to the stability of a traditional work role.
Our contribution to better understanding this contemporary means of “organizing” work is of
particular importance to organizational behavior research in the modern era.
Second, we use role enrichment theory to challenge the consensus about the effects of
side-hustles on full-time work. Specifically, we advance understanding of the spillover effects of
side-hustle empowerment and engagement for affective and cognitive experiences during full-
time work as well as the implications for employees’ performance. In addition to addressing an
impetus for spillover (i.e., empowerment) and specific pathways for performance enrichment and
conflict, our investigation of spillover from side-hustles advances understanding of
empowerment and affective shift within the multiple domain literature (e.g., Rodell, 2013).
Specifically, we build understanding of the spillover of psychological empowerment across
domains (e.g., side-hustles and full-time work) through engagement, positive affect, and
attention residue. In addition, we gain understanding of the affective shift that takes place across
domains by extending research demonstrating affective shift between the morning and afternoon
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at work (e.g., Bledow et al., 2011; Bledow, Rosing, & Frese, 2013).
Third, in addition to addressing side-hustle complexity and its relationship with side-
hustle empowerment, we consider why people engage in side-hustles (i.e., side-hustle motives)
and how these motives moderate the effects of side-hustle complexity on side-hustle
empowerment. This effort is needed to understand worker outcomes that are driven by the
interaction between side-hustle complexity and the motives that workers bring to the activity. In
particular, we integrate a framework of work motives (Cable & Edwards, 2004; Schwartz, 1992)
with theory from the job design literature that suggests that worker motives affect how
vigorously people respond to work complexity (Hackman & Oldham, 1980). Thus, our work
aligns with and advances theorizing from the job design literature that indicates that both work
characteristics, and the motives that people have for work, affect subsequent psychological states
(Hackman & Oldham, 1976)—in our case, side-hustle empowerment.
We approach our investigation into the phenomenon of side-hustles with two studies (see
Figure 1 for an overview of our studies). In Study 1, a sample of 337 employees, we provide
insight into between-person differences in assessments of side-hustle empowerment, thereby
providing a base for our exploration of the downstream implications of side-hustles for employee
performance in full-time work. In Study 2, an experience sampling method (ESM) study of 80
employee-coworker dyads, we investigate our assertions about how the experience of side-hustle
empowerment enriches full-time work performance by examining daily fluctuations in workers’
baseline experiences over a 10-day period (Gabriel et al., 2019).
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THEORY AND HYPOTHESES
The Phenomenon and Work Characteristics of Side-Hustles
Side-hustles are a domain in which full-time employees participate in income-generating
work that is separate from their full-time jobs. This arrangement has also been referred to as
moonlighting or multiple jobholding (Betts, 2006; Caza, Moss, & Vough, 2018; Crawford,
1978). However, “side-hustle” is the increasingly popular term for the phenomenon because of
its close association with the gig economy (Clark 2017, 2018; Merriam-Webster Online
Dictionary, n.d.). Within the gig economy, side-hustle is a narrower term than “gig work” as a
side-hustle is gig work that specifically occurs alongside one’s primary job. We consider the
phenomenon of side-hustles through the lens of job characteristics theory (Hackman & Oldham,
1976) because it “remains the dominant model of job design today” (Grant, Fried, & Juillerat,
2011: 421) and thus is an apt theoretical perspective for understanding the characteristics of side-
hustles (i.e., task autonomy, task significance, task identity, skill variety, and task feedback).
For example, side-hustles take place outside organizational boundaries, supervisor
control, and strictly formalized systems (Petriglieri et al., 2019). Therefore, side-hustles offer
freedom to choose how work is done, when and where work takes place, and often what work
one performs (Ashford et al., 2018). The freedom to schedule work, make decisions, and choose
methods of performing the work suggests that side-hustles tend to feature task autonomy
(Hackman & Oldham, 1976; Morgeson & Humphrey, 2006). Further, side-hustles often take
place in the customer-facing service economy (Fried, Levi, & Laurence, 2008; Spreitzer,
Cameron, & Garrett, 2017). Therefore, side-hustle workers generally contract directly with
customers or clients (Ashford et al., 2018). The resulting proximity to customers, the benefactors
of the side-hustle work, should be associated with task significance (Fried et al., 2008; Grant,
2007), or tasks that feature substantial effect on the lives of other people (Hackman & Oldham,
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1976).
Moreover, workers often direct the completion of side-hustle work from beginning to end
(Ashford et al., 2018; Petriglieri et al., 2019). This independent execution of tasks represents low
interdependence, or relatively few contextual features outside an individual that affect his or her
activity (Campion, Medsker, & Higgs, 1993). Additionally, providing goods or services in side-
hustles commonly occurs over a matter of minutes or hours as exemplified by the role of an Uber
driver or worker on TaskRabbit (Spreitzer et al., 2017). Given this low interdependence and
short turnaround for deliverables, side-hustles often feature task identity, or a sense of
completing easily-identifiable, whole pieces of work (Hackman & Oldham, 1980).
Side-hustles may also provide opportunities to learn fresh routines and practice new skills
as workers direct the entire work process (Ashford et al., 2018). Said differently, in the same
manner that employees operating in flat organizational structures exercise greater skill variety
(Davis, 1995; Wegman, Hoffman, Carter, Twenge & Guenole, 2018), workers tend to operate
outside hierarchies in side-hustles, which provides opportunities to employ a variety of skills.
Thus, side hustles can feature skill variety, or require a number of different skills and talents
(Hackman & Oldham, 1976).
Finally, the absence of organizational membership in side-hustles encourages individuals
to define themselves by the performance of work itself (Petriglieri et al., 2019). This close
connection to the work is associated with visibility of when things are going well or poorly
(Ashford et al., 2018). The tendency of independent workers to define themselves by the work
itself, as well as the high visibility of outcomes, suggests that side-hustles likely exhibit task
feedback, or direct and clear information about the effects of their performance (Hackman &
Oldham, 1976; Petriglieri et al., 2019). The availability of task feedback is further enhanced by
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technological advances in side-hustles (Wegman et al., 2018; e.g., driver ratings on Uber/Lyft,
HIT acceptance rates on Amazon’s Mechanical Turk, seller reviews from online sales platforms).
In sum, the phenomenon of side-hustles can be understood in terms of the extent of work
complexity, or degree of “independence, opportunity to use a variety of skills, information about
[one’s] performance, and chance to complete an entire and significant piece of work“ (Baer,
Oldham, & Cummings, 2003: 576; hereafter referred to as side-hustle complexity).1 Job
characteristics theory posits that this complexity reflects the motivating potential of work, which,
in turn, shapes the psychological state of workers (Hackman & Oldham, 1976). Empowerment is
a particularly salient psychological state of the work characteristics of side-hustles because side-
hustle complexity provides opportunities for workers to act as a causal agent within the activity.
Thus, we consider the relationship between side-hustle complexity and a worker’s psychological
state of empowerment.
Side-hustle Complexity and Side-hustle Empowerment
Whereas side-hustle complexity refers to the motivating potential of side-hustles based
on their characteristics, empowerment represents a set of cognitions that emerge from the
experience of complexity. More specifically, empowerment represents cognitions of self-
determination, impact, competence, and meaning (Spreitzer, 1995; Thomas & Velthouse, 1990).1
Seibert, Wang, and Courtright (2011) argue that although empowerment theory has shared roots
with the psychological states from job characteristics theory (i.e., experienced meaningfulness,
1 We note that we consider side-hustle complexity and side-hustle empowerment in our theorizing and methods as
aggregated, higher-order constructs. Regarding complexity, considering work characteristics in the aggregate aligns
with the original theorizing from Hackman & Oldham (1976). Moreover, empirical work that suggests that the work
characteristics are best represented and more predictive of criteria (e.g., psychological states) when treated as a
multidimensional construct (e.g., Fried & Ferris, 1987). Concerning empowerment, meta-analytic evidence suggests
that the four empowerment cognitions share antecedents and operate as a better predictor of behavioral outcomes as
a unitary, second-order construct rather than four separate constructs (Seibert, Wang, & Courtright, 2011;
Humphrey, Nahrgang, & Morgeson 2007). This aggregation of empowerment cognitions also aligns with Spreitzer’s
(1995) original theorizing, and thus, we treat empowerment as a single, cohesive construct.
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responsibility for the outcomes, and knowledge of results), it deviates from and advances the
theory in important ways. Specifically, although both theories consider meaning and self-
determination, empowerment theory also includes competence and impact—perceptions that
specifically relate to an active orientation toward work in which workers feel able and desirous
to shape work and its context (Conger & Kanungo, 1988; Seibert et al., 2011; Spreizer, 1995,
1996). Overall, we assert that experiencing higher levels of side-hustle complexity will be
associated with a greater degree of psychological empowerment.
For example, the task autonomy in side-hustles should positively relate to workers’ sense
of self-determination (i.e., a perception of choice in initiating and regulating action; Kraimer,
Seibert, & Liden, 1999; Spreitzer, 1995) because it represents freedom. Additionally, side-hustle
task autonomy may relate to perceived meaning (i.e., an evaluation of value in work; Spreitzer,
1995) provided that doing activities that are self-chosen increases the perceived value of the
activity (Weinstein, Ryan, & Deci, 2012). Increased meaning from autonomy arises because
autonomy enables workers to fit tasks to their values, and by doing so, creating a better fit of the
tasks to their value system (Berg, Wrzesniewski, & Dutton, 2010). The task identity in side-
hustles should increase perceived competence (i.e., a belief in one’s capability to skillfully
perform work tasks; Spreitzer, 1995). Task identity prompts a sense of competence because
completing whole pieces of work fosters sense of control, mastery, and pride in worker’s abilities
(Gist & Mitchell, 1992; Hackman & Oldham, 1976; Hodson, 1998; Morgeson & Humphrey,
2008). Further, the task feedback in side-hustles should be associated with a sense of impact (i.e.,
a perception that one’s performance in an activity makes a difference; Kraimer et al., 1999;
Spreitzer, 1995). Task feedback promotes perceived impact because a close connection to
information about one’s performance within a side-hustle provides evidence that a worker’s
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performance is observable and influential to others (Greenberger & Strasser, 1986; Hackman &
Oldham, 1976; Kraimer et al., 1999). In sum, to the extent that side-hustles exhibit complexity,
we expect a positive association with side-hustle empowerment.
Hypothesis 1: Side-hustle complexity positively relates to side-hustle empowerment.
The Moderating Effect of Side-hustle Motives
In addition to understanding what makes side-hustles empowering, it is also important to
consider the reasons why employees participate in side-hustles given that the motives for
pursuing side-hustles may regulate how people respond to side-hustle complexity. Specifically,
Hackman & Oldham (1980: 85) argue that work motives2 are “critical in determining how
vigorously an individual will respond to a job high in motivating potential” (Hackman & Lawler,
1971; Hackman & Oldham, 1976). Thus, we suggest that side-hustle motives will moderate the
relationship between side-hustle complexity and side-hustle empowerment. Because individuals
may have a variety of motives for working on their side-hustles, we draw on the comprehensive
work motives framework from Cable and Edwards (2004) that specifies self-enhancement, self-
transcendence, openness-to-change, and conservation work motives (Schwartz, 1992).
Side-hustles generally involve a self-enhancement motive, or the pursuit of personal
interests in terms of increased pay and prestige (Sliter & Boyd, 2014). However, additional
motives may arise. In addition to self-enhancement, Cable and Edwards (2004; Schwartz, 1992)
suggest that workers may have a self-transcendence motive in which they seek to promote the
welfare of other people. This is accomplished by forming and developing relationships through
the side-hustle or doing work that benefits others. For example, an individual may choose to
2 We note that although Hackman & Oldham (1980) refer to needs, the terms needs and motives are largely
synonymous and often used interchangeably (Pittman & Zeigler, 2007). Deci and Ryan (2000) argue that “needs”
represent the pursuit of fundamental nutriments that promote well-being whereas “motives” refer more broadly to a
desire for any particular outcome. We therefore use the term motive as it subsumes fundamental needs and other
desires.
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drive for Lyft to pursue increased social interactions. Further, an individual may work on a side-
hustle because of an openness-to-change motive, which entails seeking new intellectual and
emotional interests (Cable & Edwards, 2004). Workers pursue this motive through seeking
increased variety and autonomy. For example, employees who want more variety in their work
lives could pursue new intellectual interests within a side-hustle in which they make handcrafts
and sell them on Etsy, an online platform for selling handmade goods. Finally, an individual may
pursue a side-hustle because of a conservation motive, consisting of a desire for security or to
preserve stability (Schwartz, 1992). This entails seeking to quell uncertainty and pursue role
clarity in a side-hustle.
Side-hustle workers with self-enhancement, self-transcendence, openness-to-change, and
conservation motives for their side-hustles will be more likely to value the opportunities and
internal rewards that side-hustle complexity offers (Hackman & Oldham, 1976, 1980). These
opportunities and rewards include the potential for empowerment, or to shape side-hustle work
and its context in line with their motives (Spreitzer, 1995). Individuals with strong side-hustle
motives will have an eagerness to exploit opportunities that side-hustle complexity offers to align
the activity and its context with desired outcomes. This more vigorous response should
strengthen the relationship between side-hustle complexity and side-hustle empowerment
because side-hustle workers with strong motives will increasingly capitalize on opportunities to
act as a causal agent. In contrast, individuals who are lacking strong side-hustle motives may fail
to register the motivating potential of their side-hustles, may not value such motivating potential,
or may even be threatened by it (Hackman & Oldham, 1980). These workers will likely not
exploit the opportunities to shape the activity and its context.
Hypothesis 2: The positive relationship between side-hustle complexity and side-hustle
empowerment is moderated by side-hustle motives such that the relationship is stronger
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for workers with high (a) self-enhancement, (b) self-transcendence, (c) openness-to-
change, and (d) conservation motives.
Side-hustle Empowerment and Side-Hustle Engagement
Thus far, we have argued that between-person differences in side-hustle complexity will
be positively associated with side-hustle empowerment and that this relationship will be
moderated by side-hustle motives. We now consider the potential spillover of side-hustle
empowerment to full-time work by examining daily, within-person variance in side-hustle
empowerment and its relationship to full-time work performance. We do so because, in addition
to global assessments of empowerment (Thomas & Velthouse, 1990), empowerment cognitions
ebb and flow as workers continually assess themselves in relation to the work environment
(Spreitzer, 1995). Thus, we examine empowerment, its relationship with engagement, and its
spillover effects to full-time work performance on a daily basis.
Although side-hustles have often been cast in a disparaging light, we adopt a role
enrichment theory perspective to suggest that empowerment from side-hustles enriches, as well
as conflicts with, full-time work performance. We expect that daily side-hustle empowerment
will be associated with engagement, which entails a positive affective state and cognitive
attention and absorption (Kahn, 1990). Engagement is a motivational state, involving
simultaneous investment of affective, cognitive, and physical energy in work (Rich, LePine, &
Crawford, 2010; Kahn, 1990). Empowerment has been associated with motivation since its
inception in the management literature (Conger & Kanungo, 1988; Kanter, 1977) and is viewed
as a “proximal cause” of motivation (Thomas & Velthouse, 1990: 678). Thus, we expect side-
hustle empowerment to be positively associated with side-hustle engagement.
Engagement arises when a worker perceives meaning (i.e., a return on investments of the
self within work), availability (i.e., capability to perform the work at hand), and safety (i.e., the
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absence of fear of negative consequences; Kahn, 1990; Rich et al., 2010). Side-hustle
empowerment captures a worker’s sense of ownership of tasks, and this personal connection to
the activity enhances its positive valuation (Thomas & Velthouse, 1990). In turn, this positive
valuation promotes a sense of meaningfulness thereby increasing engagement. Moreover,
empowerment represents an assessment that the task at hand is within one’s power (Conger &
Kanungo, 1988). This sense of power should foster an evaluation of sufficient personal resources
to perform effectively (Anderson, John, & Keltner, 2012) thereby enhancing engagement
because of a judgment of availability. Finally, the sense of personal power associated with
empowerment (Spreitzer, 1995) increases focus on rewards and inattention toward risks
(Anderson, & Berdahl, 2002; Anderson et al., 2012; Keltner, Gruenfeld, & Anderson, 2003).
This inattention toward risks enhances perceived safety, resulting in increased engagement. In
sum, we expect daily assessments of side-hustle empowerment to promote perceived
meaningfulness, availability, and safety associated with side-hustle work, resulting in increased
side-hustle engagement.
Hypothesis 3: Daily side-hustle empowerment positively relates to daily side-hustle
engagement.
Side-hustle Enrichment of Full-time Work Performance
We assert that side-hustle empowerment influences full-time work performance through
side-hustle engagement, which has both an affective and cognitive component (Newton et al.,
2020; Schaufeli et al., 2006). Side-hustle empowerment, which positively relates to a state of
engagement, fosters psychological resources. Specifically, a state of engagement entails positive
emotions such as enthusiasm, inspiration, happiness, and alertness (Schaufeli et al., 2006; Rich et
al., 2010). This positively valenced affective state represents a psychological resource, or an
“asset that may be drawn on when needed to solve a problem or cope with a challenging
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situation” (Greenhaus & Powell, 2006: 80; Hobfoll, 2002). Thus, positive affect represents a key
psychological resource as it helps with persistence in problem solving and improved coping by
cooperating with others (Greenhaus & Powell, 2006; Tsai, Chen, & Liu, 2007; Hobfoll, 2002).
Interestingly, positive affect—or the extent of feeling enthusiastic, active, and alert
(Watson, Clark, Tellegen, 1988)—accrued in one domain is a resource that carries forward to
other domains (Edwards & Rothbard, 2000; Greenhaus & Powell, 2006). Thus, affective states
from side-hustles will likely influence affective experiences within full-time work because
affective states do not reset between domains (Judge & Ilies, 2004; Newton et al., 2020; Song,
Foo, & Uy, 2008). Meta analyses uphold this spillover effect across domains (Casper, Vaziri,
Wayne, DeHauw, & Greenhaus, 2018; Ford, Heinen, & Langkamer, 2007) and support our
assertion that the positive affective state underlying side-hustle engagement should persist as
employees enter full-time work, increasing daily positive affect within full-time work.
The spillover of psychological resources across domains, including positive affect,
enhances employee performance (Greenhaus & Powell, 2006). Scholars suggest that positive
affect enhances full-time work performance in two ways (Tsai et al., 2007). First, positive affect
is associated with improved employee performance because of increased task persistence, or the
continuance of a chosen behavior for a greater duration (Seo, Barrett, & Bartunek, 2004). That is,
individuals persist longer in activities when they are in a positive affective state (Erez & Isen,
2002; Martin, Ward, Achee, & Wyer, 1993). Increased task persistence comes from better recall
of past successful performances when in a positive affective state (Bower, 1981) as well as
greater confidence in future performances (Gist & Mitchell, 1992). Thus, increased task
persistence results in improved performance due to prolonged effort and problem solving within
work (Stajkovic & Luthans, 1998). Second, positive affect enhances employee performance due
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to increased cooperation with coworkers (Lyubomirsky, King, & Diener, 2005). Employees with
a high level of positive affect are more inviting of coworker interactions and more likely to reach
out to coworkers with help (Carlson, Charlin, & Miller, 1988; Tsai et al., 2007). This increased
cooperation positively relates to improved performance by enhancing the amount of help that
employees receive when working (Podsakoff & MacKenzie, 1997). In sum, we expect daily side-
hustle empowerment to enrich daily full-time work performance through increased side-hustle
engagement and positive affect.
Hypothesis 4: Daily side-hustle empowerment positively relates to daily full-time work
performance through daily side-hustle engagement and daily positive affect within full-
time work.
Side-hustle Conflict with Full-time Work Performance
In addition to potential performance enrichment through an affective pathway, side-hustle
empowerment may also conflict with full-time work performance through a cognitive pathway.
A potential detriment of an individual’s engagement in one domain is that it divides the
individual’s attention when performing activities within another domain (Leroy, 2009; Marks,
1977). As side-hustle empowerment increases employee engagement, attention on (i.e., time
spent thinking) and absorption in (i.e., intensity of one's focus) a side-hustle grows (Kahn, 1990).
Attention and absorption in a domain prompts individuals to continue thinking about activities in
that domain as they transition their attention to another activity (Leroy, 2009; Newton et al.,
2020). Thus, side-hustle engagement should be positively associated with attention residue, or
the persistence of cognitions about the side-hustle domain as an individual performs activities in
the full-time work domain (Leroy, 2009; Newton et al., 2020). In short, we expect attention on
and absorption in side-hustles to persist in full-time work as employees reflect back on recent
episodes of side-hustle engagement as well as look forward to upcoming side-hustle work (Leroy
& Glomb, 2018).
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Unfortunately, allocating attention to one domain can hinder performance in another
domain (Edwards & Rothbard, 2000). Specifically, attention residue serves as a distraction that
hinders performance at work (Leroy, 2009; Newton et al., 2020) as mental effort and attention
are necessary when performing any mental task (Kahneman, 1973). Attentional capacity
diminishes when attention becomes diverted across multiple processes (Norman & Bobrow,
1975), and thus, performance suffers for two reasons. First, simultaneously attending to multiple
processes in one’s mind increases cognitive load, which slows down performance (Kanfer &
Ackerman, 1989). Second, errors accrue as distracted workers are prone to “failures of divided
attention” (Kahneman, 1973: 141). Thus, as attention is diverted, performance loss occurs as the
competition for cognitive resources is associated with a slower work pace and increased errors.
In sum, we expect daily side-hustle empowerment to conflict with daily full-time work
performance through increased side-hustle engagement and attention residue.
Hypothesis 5: Daily side-hustle empowerment negatively relates to performance within
full-time work through daily side-hustle engagement and daily attention residue within
full-time work.
Affective Shift Between Full-time Work and Side-Hustles
Finally, we examine the reciprocal spillover of full-time work experiences to side-hustles.
To do so, we draw on the affective shift model, a model of intra-individual affective change that
connects affect, cognitions, and motivation (Bledow et al., 2011; Yang, Simon, Wang, & Zheng,
2016). This model suggests that when a negative affective state is followed by an activity that
induces a positive affective state, engagement increases (Bledow et al., 2013). Applied to our
model, we expect negative affect within full-time work to strengthen the relationship between
side-hustle empowerment and side-hustle engagement.
The basis for the affective shift model is that negative affect—subjective distress and an
unpleasurable mood state (Watson et al., 1988)—signals that things are not going well and
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corrective action is needed (Bledow et al., 2011). A negative affective state protrudes mental
processes and prompts an analytic mode of information processing in which individuals
experience heightened attention to details and sensitivity to discrepancies, including a focus on
impending deadlines or lack of goal progress (Bledow et al., 2013; Schwarz & Bless, 1991; Yang
et al., 2016). This analytic mode of information processing focuses individuals on the
discrepancy between their current negative affective state and a more desirable positive affective
state. This focus, in turn, enables an accurate grasp of the situation and sets the foundation for
executing goal-directed action in subsequent activities (Frijda, 1988; Kuhl, 2000). Ensuing
positive affect then heightens reward expectations, prompting eagerness and energy to attain
positive outcomes (Higgins, 1997; Yang et al., 2016). Consequently, work engagement increases
when an event introduces positive affect following a negative affective state (Bledow et al.,
2011; Carver & Scheier, 1990).
Drawing on the affective shift model, we assert that the relationship between side-hustle
empowerment and side-hustle engagement will be stronger when an individual has experienced
negative affect within full-time work earlier in the day. A prior episode of negative affect within
full-time work results in an analytic information processing mode, which fosters a discrepancy-
focus and encourages goal-directed action (Yang et al., 2016). As side-hustle empowerment
evokes positive emotions (Spreitzer, 1995), this positive affect serves as a means to correct the
discrepancy between the negative affective state from full-time work and a desired positive
affective state. Further, the increased positive affect is associated with heightened reward
expectations that promotes increased activity. In sum, negative affect from full-time work earlier
in the day should strengthen the relationship between side-hustle empowerment and side-hustle
engagement given affective shift between the domains. In turn, we expect that negative affect
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from full-time work will strengthen both the positive serial indirect effect of the affective
pathway in our model as well as the negative serial indirect effect of the cognitive pathway.
Hypothesis 6: Negative affect within full-time work from earlier in the day strengthens
the relationship between daily side-hustle empowerment and daily side-hustle
engagement, such that a positive relationship will occur at low levels of negative affect
and a stronger positive relationship will occur at high levels of negative affect.
Hypothesis 7: Negative affect within full-time work from earlier in the day strengthens
(a) the positive serial indirect effect between daily side-hustle empowerment and daily
full-time work performance through daily side-hustle engagement and positive affect and
(b) the negative serial indirect effect between daily side-hustle empowerment and daily
full-time work performance through daily side-hustle engagement and attention residue.
OVERVIEW OF STUDIES
To explore the between- and within-person dynamics in our model, we conducted two
studies. In Study 1, we examine the phenomenon of side-hustles and address between-person
differences in the relationship between side-hustle complexity and empowerment (Hypothesis 1).
We also examine side-hustle motives as moderators of this relationship (Hypothesis 2). In Study
2, we investigate the interplay of side-hustles and full-time work performance (Hypotheses 3
through 7). The ESM design of Study 2 enables us to examine within-person, daily fluctuations
from workers’ central tendencies (Gabriel et al., 2019). Specifically, we test the spillover effect
of within-person variance in side-hustle empowerment as it relates to full-time work enrichment
and conflict. We also test the affective shift that occurs between full-time work and side-hustles.
Our approach of addressing global assessments of empowerment in Study 1 and the ebb and flow
of empowerment in Study 2 aligns with theoretical work from Thomas and Velthouse (1990).
STUDY 1: METHOD
Samples and Procedure
Study 1 included 337 full-time employees with side-hustles. We recruited participants
through Facebook pages and Reddit communities associated with side-hustles, LinkedIn, and a
network of MBA graduates. This recruitment approach has been used in various top-tier
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management journals (e.g., Colquitt, Baer, Long, & Halvorsen-Ganepola, 2014; Vogel, Rodell,
& Lynch, 2016). Our sample was 45% female. On average, participants were 29.6 years old (SD
= 6.94), mostly held a bachelor’s degree or higher (69%), and engaged in a variety of side-
hustles (e.g., Uber driving, graphic design, selling goods online) and full-time jobs. See Table A1
in Appendix A for details on work roles. Median annual income was $3,000 for side-hustles and
$45,000 for full-time jobs—comparable to the median income of $48,500 for full-time US
workers over age 25 (U.S. Department of Labor, 2019).
Participants provided demographics on a registration survey and completed three surveys
separated by three weeks each to reduce common method bias (Doty & Glick, 1998; Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003). A total of 417 participants provided ratings of side-hustle
complexity on the first survey, and 370 participants rated their side-hustle motives on the second
survey (89% response rate). On the third survey, 342 participants rated the extent to which they
generally experience empowerment when working on their side-hustle (92% response rate). We
excluded 5 participants who, when asked if they responded conscientiously to one of our
surveys, indicated they had not (Meade & Craig, 2012). Our final sample entailed 337 employees
after listwise deletion. We note that of the 582 workers who expressed initial interest in the
study, 417 participated in one or more of the surveys (72% response rate). We paid participants
in Study 1 $5 per survey completed as well as a $5 bonus if they completed all three surveys.
Measures
All measures were rated with 5-point scales (1 = strongly disagree to 5 = strongly agree).
Side-hustle complexity. We assessed side-hustle complexity with the five dimensions of
the job characteristics model using scales from Morgeson and Humphrey (2006). We measured
task autonomy with a 4-item measure (e.g., “My side-hustle allows me to make a lot of decisions
on my own”), task identity with a 4-item measure (e.g., “My side-hustle is arranged so that I can
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do an entire piece of work from beginning to end”), task feedback with a 3-item measure (e.g.,
“My side-hustle provides me with information about my performance”), task significance with a
4-item measure (e.g. “My side-hustle is very significant and important in the broader scheme of
things”), and skill variety with a 4-item measure (e.g., “My side-hustle requires the use of a
number of skills”). We averaged the five dimensions to obtain a combined measure of side-
hustle complexity (e.g., Fried & Ferris, 1987; = .83).
Side-hustle motives. We assessed side-hustle motives from Cable and Edwards (2004;
Schwartz, 1992). Each item included the stem “I work on my side-hustle to…” In line with
Schwartz (1992; Cable & Edwards, 2004), we aggregated these dimensions to form 6-item
measures of the four work motives of self-enhancement (pay and prestige; e.g., “increase my
income”, “gain respect”; = .68), self-transcendence (altruism and relationships; e.g., “be of
service to society”, “develop close ties with other people”; = .90), openness-to-change (variety
and autonomy; e.g., “do many different things”, “make my own decisions”; = .90), and
conservation (security and authority; e.g., “be certain I have work in the future”, “have the final
say”; = .82).
Side-hustle empowerment. We assessed side-hustle empowerment using the 12-item
empowerment measure from Spreitzer (1995). This measure captures cognitions of self-
determination (e.g., “I have considerable opportunity for independence and freedom in how I do
my side-hustle”), impact (e.g., “The impact of my side-hustle is large“), competence (e.g., “I am
confident about my ability to do my side-hustle”), and meaning (e.g., “The work I do on my
side-hustle is meaningful to me”). In line with theory and meta-analytic evidence (Seibert et al.,
2011), we averaged across dimensions to obtain a combined measure ( = .82).
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Analysis and Results
Given potential overlap in the motivational constructs in our model, we ran confirmatory
factor analyses (CFA) on the dimensions underlying side-hustle complexity, side-hustle motives,
and side-hustle empowerment. This measurement model demonstrated adequate fit with the data
2 = 2467.95, df = 1294, p < .01, CFI = .93, RMSEA = .05, SRMR = .05) and was superior to a
general factor model 2 = 13283.77, df = 1430, p < .01, CFI = .26, RMSEA = .16, and SRMR =
.15; cf. Antino, Rico, & Thatcher, 2019; Zhang, George, & Chattopadhyay, in press). To further
investigate construct validity, we computed the average variance extracted for each dimension
(AVE) and found that all exceeded the recommended value of .50 (MacKenzie, Podsakoff, &
Podsakoff, 2011) and were larger than the squared correlations between the latent factors
(Fornell & Larcker, 1981). Taken together, these results provide evidence of distinctiveness
among the underlying construct dimensions, suggesting that the aggregation of these dimensions
resulted in distinguishable constructs.3 Table 1 provides means, reliabilities, and correlations. We
tested Hypotheses 1 and 2 using ordinary least squares (OLS) regression. We included all of the
side-hustle motives, alongside side-hustle complexity, in a single regression to account for the
shared variance between them. We then entered the interaction terms in separate models because
such a large number of correlated predictors may introduce multicollinearity issues that can bias
results (Schwab, 2005).
Hypothesis 1 predicted that side-hustle complexity would be positively related to side-
hustle empowerment. In support of this hypothesis, we found a positive relationship between
3 A helpful reviewer pointed out potential overlap between some of our items. For example, the items “My side-
hustle allows me to plan how I do my work” and “My side-hustle is very significant and important in the broader
scheme of things” from our side-hustle complexity measure seemingly overlap with the following empowerment
items (respectively): “I have significant autonomy in determining how I do my side-hustle” and “The impact of the
side hustle is large.” To consider the effect of this overlap on our final model, we excluded the two aforementioned
items from our measure of side-hustle complexity. Re-running our analyses without these two items did not change
the pattern or significance level of our results.
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side-hustle complexity and side-hustle empowerment (b = .43, SE = .05, p < .01).4 Although not
hypothesized, we note that a self-enhancement motive had no main effect on side-hustle
empowerment, self-transcendence and openness-to-change motives had positive main effects on
side-hustle empowerment (p < .01), and a conservation motive had a negative main effect on
side-hustle empowerment (p < .05).
We then tested the moderating effects of side-hustle motives on the relationship between
side-hustle complexity and side-hustle empowerment. We mean-centered our predictors before
creating interaction terms and plotted the slopes at plus and minus one standard deviation for
each motive (Aiken & West, 1991). The interactions of side-hustle complexity with self-
enhancement (b = .15, SE = .07, p < .05), self-transcendence (b = .11, SE = .04, p < .01), and
conservation (b = .14, SE = .04, p < .01) were significant, while the interaction of side-hustle
complexity with openness-to-change was not significant (b = .00, SE = .04, n.s.). The plots of
these interactions (see Figure 2) revealed that high levels of self-enhancement, self-
transcendence, and conservation motives strengthened the relationship between side-hustle
complexity and side-hustle empowerment. Thus, Hypotheses 2a, 2b, and 2d were supported, and
Hypothesis 2c was not supported.
----------------------------------------
Insert Table 1 and Figure 2 about here
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Discussion of Study 1
In Study 1, we examined the phenomenon of side-hustles by considering what makes
side-hustles empowering and whether the reasons for pursuing side-hustles strengthen or weaken
4 To further support job characteristics theory’s causal ordering of work complexity preceding critical psychological
states, we also ran a model in which we controlled for psychological empowerment captured on the second survey as
a predictor of side-hustle empowerment captured on the third survey. With the inclusion of this control for prior
levels of side-hustle empowerment, side-hustle complexity retained its positive affect on side-hustle empowerment
(b = .23, SE = .06, p < .01). These findings align with our assertion that side-hustle complexity precedes side-hustle
empowerment as well as the ordering that job characteristics theory predicts.
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this relationship. We found that side-hustle complexity was positively associated with side-hustle
empowerment. Moreover, we identified motives that serve to regulate how people respond to
side-hustle complexity. We found that side-hustle complexity had a stronger effect on side-hustle
empowerment when workers have a strong motive to increase income (self-enhancement),
connect with or benefit others (self-transcendence), or seek security in side-hustles
(conservation). We note that although the motive for increased income is likely the most
universal motive for side-hustles, the other motives we examined had moderating effects while
controlling for the motive for increased income. In sum, Study 1 supported our assertions of
side-hustle complexity positively relating to side-hustle empowerment and side-hustle motives
determining how vigorously workers respond to side-hustle complexity.
STUDY 2: METHOD
Sample and Procedure
In Study 2, we considered the spillover of daily side-hustle empowerment to full-time
work performance. We did so in a 10-day ESM study of 80 employee-coworker dyads, which
resulted in 2,124 observations. Our sample was 62% female. On average, the focal employees in
our sample were 40 years old (SD = 11.00) and worked for their full-time employers for 10 years
(SD = 9.31). Participants performed a variety of side-hustles (e.g., driving for Uber/Lyft, event
photography, completing surveys online, selling goods online) and full-time jobs (e.g., teacher,
software engineer, sales associate, nurse), which suited our research design as it improves
generalizability (Kerlinger & Lee, 2000). See Table A1 in Appendix A for details about work
roles.
We followed the same recruitment approach as Study 1. Participants were required to
provide the names of three coworkers with whom they have frequent contact during their full-
time work. After receiving the participants’ coworker nominations, we randomly selected one
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coworker and invited him or her to participate. By doing so, we sought to increase the validity of
performance ratings as focal employees could not completely control the source of their
performance evaluations, and ratings did not exclusively come from the participant’s closest
friend at work. On average, coworkers in our sample (66% female) were 39 years old (SD =
11.91) and worked for their full-time employers for 8 years (SD = 9.07). Our employee-coworker
dyads worked together for an average of 7 years (SD = 7.60). We carefully looked for
irregularities in the contact information provided for each participant. For example, we removed
participants who provided their own name for the name of a coworker, had suspicious email
addresses (e.g., v3142br@hotmail.com), or provided unrealistic information (e.g., having worked
with a coworker for 10 years but only being 24 years old).
Our ESM design enabled us to capture within-person, daily variation in side-hustle and
full-time work experiences (Gabriel et al., 2019). Employees received two daily surveys. We
sent the first survey in the evening before workdays (Sunday-Thursday). We considered evening
side-hustle work because all participants were occupied by full-time jobs from “9-to-5,” and
participants reported working on their side-hustles for an average of 3 or more evenings per
week. We expected previous evening experiences to have an effect on next-day work
experiences, which is in line with prior studies, such as sleep research (e.g., Barnes, Lucianetti,
Bhave, & Christian, 2015; Wagner, Barnes, Lim, & Ferris, 2012) and other spillover research
(Butts, Becker, & Boswell, 2015; Lanaj, Johnson, Barnes, 2014; Song et al., 2008). Our timing
also provided a compact time frame between side-hustle work and our observations, offered time
separation between side-hustle and full-time work experiences, and aligned with our assertions
of temporal precedence between variables (Fisher & To, 2012). The evening survey captured
side-hustle empowerment, time spent working on side-hustles, and side-hustle engagement.
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We sent the second employee survey at midday during full-time work (Monday-Friday),
which captured positive and negative affect at work as well as attention residue. Coworkers
received one daily survey at the end of the workday (Monday-Friday), which captured employee
work performance. Each survey link expired after a few hours to ensure participants reported on
their most recent side-hustle or work experiences. We paid focal employees $3 for each day that
they completed our two surveys, a $5 bonus for completing 100% of the first three days, and a $5
bonus for completing 7 or more days. Coworker participants received $2 for completing their
daily survey, a $5 bonus for completing 100% of the first three days, and $5 for completing 7 or
more surveys.
Of the 164 employees who expressed initial interest in the study, 111 had coworkers who
registered for the study (67% response rate), and a total of 89 employee-coworker dyads
completed one or more days of surveys (80% response rate). We followed recommendations to
include only dyads with at least three days of complete data in our analyses (e.g., Singer &
Willett, 2003; Trougakos, Hideg, Cheng, & Beal, 2014). Participants could not provide ratings of
daily side-hustle empowerment and daily side-hustle engagement needed for analysis on days in
which they did not perform side-hustle work. As a result, our analyses did not include
observations in which individuals did not work on their side-hustles (only 8% of the evenings;
please see supplementary analyses on the effects of this approach). After listwise deletion, our
final sample entailed 507 complete observations from 80 employee-coworker dyads with an
average of 6.3 complete days per dyad. To clarify, an “observation” consists of an evening
survey and midday survey from employees, an end-of-day survey from coworkers as well as
each of these surveys from the preceding day to control for previous-day measures.
Measures
All scale measures used a 5-point Likert scale (1 = strongly disagree to 5 = strongly
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agree). We utilized short, reliable measures due to our ESM design, which require shortened
measures to increase response rates and avoid mental fatigue (Beal & Weiss, 2003).
Side-hustle empowerment. Participants rated empowerment cognitions related to their
side-hustles using the 12-item measure of empowerment from Study 1 (Spreitzer, 1995; α = .91).
Side-hustle engagement. Participants rated side-hustle engagement using the 6-item
measure from Bakker and Xanthopoulou (2009). Sample items are “This evening, while working
on my side-hustle, I have felt enthusiastic about my work” and “This evening, while working on
my side-hustle, I have been completely immersed in my work” = .93).
Negative and positive affect within full-time work. Participants rated affective states at
their full-time work using the 10-item, shortened form of the PANAS from Mackinnon, Jorm,
Christensen, Korten, Jacomb, and Rodgers (1999). The lead-in to the items was “Today, while
working on my full-time job, I have felt …” The five items for negative affect were “Upset,”
“Afraid,” “Nervous,” “Scared,” and “Distressed” = .92). In our analysis, we time lagged the
negative affect variable to apply the afternoon preceding side-hustle work. The five items for
positive affect were “Enthusiastic,” “Inspired,” “Alert,” “Determined,” and “Excited” = .96).
Attention residue. Participants rated attention residue related to their side-hustle using the
3-item attention residue scale from Newton and colleagues (2020). Whereas the original items
refer to a prior task, we adapted the items to refer to a side-hustle. A sample item is “Today,
while working at my full-time job, I have kept thinking about my side-hustle” = .94).
Full-time work performance. Coworkers rated the focal participant’s work performance
using a 3-item measure of task performance from Griffin, Neal, and Parker (2007). We adapted
the wording of the items to reference the employee from the study. A sample items is “Today,
[Employee first name] has carried out the core parts of his/her job well” = .78).
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Control variables. We controlled for previous-day levels of side-hustle engagement,
positive affect within full-time work, attention residue, and work performance (cf. Johnson,
Lanaj, & Barnes, 2014; Scott & Barnes, 2011; see Figure 3). To account for daily fluctuations in
the amount of contact between employees and coworkers, we also controlled for the coworker’s
opportunity to observe the focal employee using a 3-item measure from Judge and Ferris (1993;
see also Baer, Matta, Kim, Welsh, & Garud 2018; Rodell, 2013). A sample item is “Today, I
have had the opportunity to observe [Employee Name]’s behavior” = .95). We also controlled
for time spent working on the side-hustle because it relates directly to potential conflict between
side-hustles and full-time work (i.e., “How much time have you spent working on your side-
hustle this evening after work?”).
Analysis and Results
First, we assessed the fit of our measurement model by conducting a multi-level CFA in
Mplus 7.4 (Múthen & Múthen, 2017). Items were loaded on their respective constructs and
specified at the within-person level to examine the factorial structure. The fit of this
measurement model was acceptable (CFI = .93, RMSEA = .06, SRMR = .07). Next, we
examined within-person variance for our study variables in null models and found all study
variables had substantial within-person variance (i.e., 23% to 47% within-person variance; see
Table 2), which suggests that multilevel modeling is appropriate.
To test our hypotheses, we clustered observations by dyad, group-mean centered our
predictors, and allowed for random intercepts within the analysis of our model (Beal & Weiss,
2003; Hofmann & Gavin, 1998; Preacher, Zhang, & Zyphur, 2016). More specifically, we
group-mean centered side-hustle empowerment and full-time work negative affect to understand
how daily fluctuations in these predictors affected daily side-hustle engagement, full-time work
positive affect, attention residue, and full-time work performance. To further isolate daily
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fluctuations in the variables in our model, we controlled for previous-day levels of side-hustle
engagement, positive affect within full-time work, attention residue, and work performance. The
inclusion of these previous-day controls enables us to interpret our results as a change in the
level of these variables and offers further evidence for our hypothesized causal direction (Beal,
2015). We then specified a multilevel path model in Mplus and examined all variables at the
within-person level (Level 1). This model exhibited an acceptable fit to the data (CFI = .93,
RMSEA = .09, SRMR = .05). Means, standard deviations, correlations, and reliabilities of the
study variables are presented in Table 3. See Table 4 and Figure 3 for the results of the
multilevel path analysis.
--------------------------------
Insert Tables 2, 3, and 4 as well as Figure 3 about here
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Hypothesis 3 predicted that daily side-hustle empowerment would be positively related to
daily side-hustle engagement. We found support for this hypothesis ( = .65, SE = .08, p < .01). 5
The pseudo R2 for side-hustle engagement was 51.1% (see Figure 3 and Table 4).
Next, we tested Hypothesis 4, which predicted that daily side-hustle empowerment would
positively relate to full-time work performance through daily side-hustle engagement and
positive affect within full-time work. We found that side-hustle engagement positively related to
next-day positive affect within full-time work ( = .22, SE = .06, p < .01; see Figure 3). We also
found that daily positive affect within full-time work positively related to daily full-time work
performance ( = .12, SE = .02, p < .01). To analyze serial mediation, we tested for a significant
indirect effect, which occurs when there is a significant product of path coefficients along a
mediation chain, while controlling for the direct effect (MacKinnon, Lockwood, & Williams,
5 We note that the relationship between empowerment and engagement also holds for each of the four empowerment
cognitions as predictors. That is, using daily self-determination, impact, competence, or meaning as the independent
variable in our model is also positively associated to engagement to the same degree of significance (p < .01).
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2004; Tofighi & MacKinnon, 2016). We used a resampling method to avoid biased indirect
effect estimates caused by the non-normal distribution of multiplied path coefficients. We used
the Monte Carlo method (20,000 repetitions), resulting in bias-corrected confidence intervals for
our indirect effects (MacKinnon et al., 2004; Preacher & Selig, 2012). We found a positive serial
indirect effect of daily side-hustle empowerment on daily full-time work performance
(IND = .02, 95% CI [.008, .030]), supporting Hypothesis 4 (see Figure 3 and Table 4). The
pseudo R2 for positive affect was 49.3% and for full-time work performance was 46.9%.
We then tested Hypothesis 5, which predicted that daily side-hustle empowerment would
negatively relate to daily full-time work performance through side-hustle engagement and
attention residue. We found that daily side-hustle engagement positively related to attention
residue within full-time work ( = .16, SE = .05, p < .01; see Figure 3). We also found that daily
attention residue within full-time work negatively related to daily full-time work performance
( = –.05, SE = .02, p < .01). Finally, we found support for the negative serial indirect effect from
daily side-hustle empowerment to daily full-time work performance (IND = –.01, 95% CI [–.011,
–.001]). Thus, Hypothesis 5 was supported (see Figure 3 and Table 4). The pseudo R2 for
attention residue within full-time work was 62.2%.
Lastly, we tested our hypotheses related to affective shift. Hypothesis 6 predicted that
daily negative affect within full-time work would strengthen the relationship between subsequent
side-hustle empowerment and side-hustle engagement. The interaction term for side-hustle
empowerment negative affect within full-time work was significant ( = .70, SE = .20, p < .01).
The plot of the interaction (Figure 4) shows that daily side-hustle empowerment was positively
associated with daily side-hustle engagement when negative affect within full-time work was
low ( = .31, SE = .13, p < .05) and that the positive relationship was stronger when negative
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affect within full-time work was high ( = .99, SE = .13, p < .01). Thus, Hypothesis 6 was
supported. Hypothesis 7a predicted that the positive indirect effect of side-hustle empowerment
on full-time work performance through side-hustle engagement and positive affect would be
moderated by negative affect within full-time work. We found that this indirect effect was
significant at low levels of negative affect within full-time work (IND = .01, 95% CI [.001,
.018]) and significant at high levels of negative affect within full-time work (IND = .03, 95% CI
[.011, .045]). Importantly, the difference between the low and high conditions was statistically
significant (DIFF = .02, 95% CI [.003, .041]), suggesting that the serial indirect effect is
moderated by negative affect within full-time work. Thus, Hypothesis 7a was supported.
Hypothesis 7b predicted that the negative indirect effect of side-hustle empowerment on full-
time work performance through side-hustle engagement and attention residue would be
moderated by negative affect within full-time work. We found that this indirect effect was
significant at low levels of negative affect within full-time work (IND = –.00, 95% CI [–.006,
–.000]) and significant at high levels of negative affect within full-time work (IND = –.01, 95%
CI [–.017, –.002]). Furthermore, the difference between the low and high conditions was
statistically significant (DIFF = –.01, 95% CI [–.022, –.004]), suggesting that the serial indirect
effect is moderated by negative affect within full-time work. Thus, Hypothesis 7b was supported.
----------------------------------------
Insert Figure 4 about here
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Supplementary Analyses and Robustness Checks
We found that empowerment was associated with side-hustle engagement and spilled
over to full-time work via two pathways: an affective pathway through positive affect and a
cognitive pathway through attention residue. We compared these pathways by testing whether
the indirect effect of the affective pathway (IND = .02) was different than the absolute value of
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the indirect effect of the cognitive pathway (IND = .01) by employing the product of coefficients
approach and the Monte Carlo method of resampling in the R program (MacKinnon, Lockwood,
Hoffman, West, & Sheets, 2002; Preacher & Selig, 2012). Results found the indirect effect of
side-hustle empowerment on full-time work performance through positive affect was
significantly stronger than the indirect effect of side-hustle empowerment on full-time work
performance through attention residue (DIFF = .01, 95% CI [.001, .024]).
Our analysis excluded days in which participants did not work on their side-hustles
because we could not obtain ratings of side-hustle empowerment and side-hustle engagement on
these days. Concerns about sample selection may be somewhat mitigated given that participants
worked on their side-hustles for the sizeable majority of evenings in our study: 901 evenings out
of 976 evening surveys reported (92%). We acknowledge the potential for endogeneity in that
some factors may make participants more or less likely to work on their side-hustles and have a
bearing on variables in our model. To explore such potential confounds, we created a
dichotomous variable to capture side-hustle work on a given day (0 = did not work on the side-
hustle, 1 = worked on the side-hustle). We then analyzed whether the focal variables in our
model significantly predicted this dichotomous variable using a logit model with clustered
standard errors (Wooldridge, 2016). This test revealed that none of the variables in our model
were significant predictors of whether participants worked on their side-hustles in a given
evening, with the exception of attention residue within full-time work rated earlier in the day
(b = .58, SE = .20, p < .01). Thus, participants were more likely to conduct evening side-hustle
work following days in which they thought about their side-hustles at work. We suggest that the
controls we included for previous-day levels of attention residue, as well as all other endogenous
variables in our model, help account for the influence of these variables as potential confounds.
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Following recommendations, we conducted our hypothesis testing with and without
several control variables (e.g., Breaugh, 2008; Spector & Brannick, 2011). Removing side-hustle
work time as a control had no effect on the significance level of any of our findings. Removing
opportunity to observe had no effect on the significance level of our findings with the exception
of the relationship between attention residue and full-time work performance. We retained
opportunity to observe as a control variable because it addresses a factor that can confound
performance ratings (Judge & Ferris, 1993; see also Baer et al., 2018; Rodell, 2013). Removing
previous-day controls for all of our endogenous variables strengthened our effects. However, we
retained these controls to enable us to interpret our results as a change in each variable from the
previous day (Johnson et al., 2014; Scott & Barnes, 2011).
We were also interested in whether there was a curvilinear effect for side-hustle activity.
We found no effects for side-hustle empowerment as a curvilinear predictor of side-hustle
engagement (b = .02, SE = .17, n.s.), side-hustle engagement as a curvilinear predictor of
positive affect within full-time work (b = 0.04, SE = .05, n.s.), or side-hustle engagement as a
curvilinear predictor of attention residue (b = 0.09, SE = .05, n.s.). We did find a curvilinear
relationship between side-hustle engagement and side-hustle work time (b = .32, SE = .05, p <
.01). The plot of this relationship suggests that a one-unit increase in side-hustle engagement
exponentially increases the amount of time that participants spend on their side-hustles.
Finally, we were interested in whether the extent of side-hustle income altered the
relationship between side-hustle empowerment and side-hustle engagement or the spillover of
side-hustle activities to full-time work. To examine this effect, we considered whether side-
hustle income as well as the proportion of total income from side-hustle work (i.e., side-hustle
income divided by full-time work income plus side-hustle income) served as cross-level
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moderators in these relationships. However, neither side-hustle income nor the proportion of
total income from side-hustle work significantly moderated the relationship between side-hustle
empowerment and side-hustle engagement, side-hustle engagement to positive affective within
full-time work, or side-hustle engagement to attention residue. Thus, we did not find that side-
hustle income had significant effects on the relationships in our model.
Discussion of Study 2
In Study 2, we considered how side-hustles positively and negatively relate to
performance in one’s full-time job as well as when these effects are stronger or weaker. More
specifically, we sought to better understand the spillover effects of side-hustle empowerment and
engagement on affective and cognitive experiences during one’s full-time work. This parallel
consideration of affective and cognitive effects aligns with other recent work (e.g., Christian &
Ellis, 2011; Koopman, Lanaj, & Scott, 2016; Newton et al., 2020). We found support for an
affective pathway in which side-hustle empowerment enriched full-time work performance
through side-hustle engagement and positive affect within full-time work. Further, our findings
supported a cognitive pathway in which side-hustle empowerment conflicted with full-time work
performance through side-hustle engagement and attention residue. In our supplemental
analyses, we found that the affective pathway had a significantly greater effect on full-time work
performance than the cognitive pathway, indicating a net positive effect of side-hustle
empowerment on full-time work performance. Regarding when these affective and cognitive
effects were stronger or weaker, we also found that experiences in full-time work had an effect
on side-hustles. Specifically, negative affect during full-time work earlier in the day strengthened
the relationship between side-hustle empowerment and side-hustle engagement due to an
affective shift between the domains. In turn, this effect significantly moderated the affective and
cognitive pathways we theorized. Overall, results from our ESM design informed variation in
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employees’ affective and cognitive experiences in full-time work as well as daily performance
fluctuations as predicted by deviations in their mean levels of side-hustle empowerment and
negative affect in full-time work (Gabriel et al., 2019).
GENERAL DISCUSSION
Theoretical Implications
For millions of workers, involvement in the gig economy entails participating in side-
hustles in conjunction with full-time work. Despite the prevalence of this phenomenon,
organizational studies have been slow to consider developments in the new world of work
(Ashford et al., 2018). Our work sought to advance understanding of the confluence of gig work
and traditional work roles by considering side-hustles and their effects on full-time work
performance from an empowerment perspective. We offer more balanced consideration of side-
hustles that accounts for benefits not considered by prior work, while still accounting for
potential downsides. Interestingly, the arrangement we considered suggests that workers may be
able to reap the benefits of independent work while retaining the stability of a traditional work
role, avoiding the downsides of full reliance on gig work (Ashford et al., 2018). That is, side-
hustles offer empowerment as workers feel able to shape the work and its context, and the
organizational-affiliation of a full-time job may offer a sense of belonging, self-esteem, and
reduced social anxiety (Ashforth, Harrison, & Corley, 2008). Advancing understanding of the
arrangement of holding a side-hustle and full-time job contributes to theory by focusing on the
contemporary phenomenon of how work is presently being organized and its effects on
employees and organizations.
Role enrichment theory guided our investigation of the spillover effects of side-hustle
empowerment and engagement on the affective and cognitive experiences of employees during
full-time work. Our findings demonstrate side-hustles have both enriching and conflicting effects
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on full-time work. Overall, we found a net benefit of side-hustle empowerment on full-time work
performance, which is significant as side-hustles have generally been cast in a negative light
(e.g., Rodell, 2013). Our efforts contribute to the long-standing debate about the effects of
engaging in activities outside work as enriching (Greenhaus & Powell, 2006; Sieber, 1974) or
conflicting with (Barnett, 1998; Haas, 1999) a full-time work role. Furthermore, whereas others
have focused solely on the spillover of emotions to address enrichment and conflict from
engaging in work and family domains (e.g., Rothbard, 2001), we couple affective spillover with
consideration of cognitive spillover (cf. Newton et al., 2020). More specifically, we advance
theory about the spillover of empowerment across domains by specifying an affective and
cognitive pathway through which empowerment in one domain (i.e., side-hustles) influences
affective states, cognitions, and behavior in another domain (i.e., full-time work) through work
engagement. Moreover, our work points to the importance of affective shift between domains
rather than solely affective shift between the morning and afternoon at work. Taken together, our
work builds theory about how side-hustle empowerment affects full-time work performance for
better and worse and the moderating role of affective shift that strengthens this relationship.
Our consideration of side-hustle empowerment builds on recent research indicating that
independent work leads to fulfillment and positive emotions because workers feel they can
personalize the role (Petriglieri et al., 2019). We use job characteristics theory to advance
understanding of the phenomenon of side-hustles. More specifically, we found that whether or
not employees experience side-hustle empowerment depends on the complexity of the side-
hustle and on the motives for engaging in the side-hustle. We utilize theorizing from the job
design literature that suggests that both work characteristics and the motives of workers affect
psychological outcomes (Hackman & Oldham, 1976). We found that motives for increasing
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income, connecting with or benefitting others, or seeking security in side-hustles strengthened
the relationship between side-hustle complexity and side-hustle empowerment. Thus, our work
contributes to theory by identifying the precise motives people have for engaging in side-hustles
and how these motives regulate the effects of side-hustle complexity on empowerment.
Future Research
Our research into the phenomenon of side-hustles also opens up further investigations
into this unique work arrangement and the gig economy more broadly. Future research could
explore how individuals can craft their overall “work lives” to be more meaningful or cultivate a
satisfying work identity (Wrzesniewski & Dutton, 2001) by pairing a side-hustle with full-time
work. For example, employees could adopt side-hustles that supplement needs that are partially
met by full-time work (i.e., supplementary fit) or select side-hustles that fulfill needs that full-
time work is missing (i.e., complementary fit). Both supplementary and complementary
arrangements between side-hustles and full-time work could enrich employee well-being or
experiences within full-time work (e.g., Cable & Edwards, 2004). Future research could examine
how workers can successfully craft an enriching fit between side-hustles and full-time work.
Such an approach could focus on supplementary or complementary experiences of work
characteristics or fulfillment of psychological needs or work characteristics between side-hustles
and full-time work. Alternatively, future research could consider the effect of congruence
between side-hustle work and full-time work in terms of knowledge and skills. One benefit of a
side-hustle that employs similar knowledge and skills to full-time work is that it can provide
training that one can apply within full-time work (Betts, 2006). However, such congruence in the
activities could prevent employees from psychologically detaching from full-time work, which is
associated with diminished recovery from full-time work and increased exhaustion (Sonnentag,
Binnewies, & Mojza, 2010). Thus, future research could also consider the interesting tension that
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exists in the supplementary and complementary experiences of side-hustles and full-time work.
Although we adopted an empowerment perspective, future research could explore
alternative perspectives to address the positive and negative effects of side-hustle on full-time
work performance. An interesting extension of our work would be to examine whether holding a
side-hustle adds to the demands present in a full-time job in terms of challenge/hindrance stress
(e.g., Cavanaugh, Boswell, Roehling, & Boudreau, 2000; LePine, Podsakoff, & LePine, 2005;
Podsakoff, LePine, & LePine, 2007). Although we partially address the effects of combined
workload from side-hustles by controlling for time spent working on side-hustles, a more
concerted study of combined workload would advance the topic. Further, future research could
employ a boundary theory perspective to consider the costs and benefits of transitioning between
side-hustles and full-time jobs (Ashforth, Kreiner, & Fugate, 2000). This approach could
advance current research into managing multiple work identities (Caza et al., 2018).
Relatedly, the seemingly higher latitude in determining a side-hustle compared to the
external factors that determine one’s full-time job is worthy of consideration within future
research. The labor market for side-hustles and full-time work are described quite differently by
sociologists. For example, scholars have argued that the new economy consists of a primary,
traditional job market as well as a separate secondary market comprised of more flexible work
(Sennett, 2006; Sweet & Meiksins, 2013). Thus, as opposed to the primary market from which
workers draw their “careers,” work from the secondary labor market (i.e., gig economy) appears
to be easier to adopt and discard (Ashford et al., 2019; Ashford et al., 2018). The high degree of
latitude in selecting side-hustles may shape how employees pair their side-hustle with full-time
work to enrich their experience in full-time work to a greater or lesser degree.
Finally, our investigation of side-hustles sheds light on a large component of the gig
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economy. However, side-hustles are just one type of “gig” performed in the new world of work.
Many freelancers, contractors, and gig workers piece together a variety of “gigs” to constitute
full-time employment. Whereas qualitative investigations have shed light on the experience of
those in the gig economy (Caza et al., 2018; Petriglieri et al., 2019), future quantitative
investigations are needed. Specifically, our results point to spillover effects between side-hustles
and full-time work that are likely even more prevalent as workers engage in, or perhaps “juggle,”
multiple gigs. Although we found a net positive benefit of spillover, handling multiple daily
transitions or working for multiple organizations with varying norms could result in both positive
and negative outcomes for workers (e.g., O’Leary, Mortensen & Woolley, 2011; Newton et al.,
2020; Rapp & Mathieu, 2019) and thus is worthy of future investigations.
Potential Limitations
Our work entails some limitations that should be noted and could be addressed with
future research. Our survey methodology is accompanied by potential common method bias in
self-reported relationships, which can inflate correlations and raise questions about causal
directions (Podsakoff et al., 2003). In response, we employed the two most effective procedural
steps to limiting the effects of common method bias—temporal and source separation (Doty &
Glick, 1998). In both Study 1 and Study 2, we applied temporal separation between our measures
of interest. In Study 2, we utilized source separation between our measures rated by employees
and performance outcomes rated by coworkers. Although we present theoretically grounded
arguments about the causal relationships proposed within our model and include control
variables to aid in our assertions, limited causal inferences can be made within survey research.
Future research could advance the study of side-hustles further by employing an experimental
ESM (cf. Song et al., 2018) in which data is captured before and after a sample of full-time
employees adopt side-hustles.
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We also note two limitations related to side-hustle work characteristics. First, we relied
on worker perceptions of side-hustle characteristics, which could be biased, rather than on
objective data about side-hustle work characteristics. However, research has found that objective
work characteristics shape perceptions of work characteristics (Fried & Ferris, 1987). After
reviewing findings about potential bias introduced by self-ratings of work characteristics and
performing their own analysis, Fried and Ferris (1987) concluded that problems associated with
self-rated work characteristics are less serious than initially believed. Thus, research has
traditionally relied on rater perceptions of work characteristics as evidenced by extensive use of
the job diagnostic survey over the last four decades (Hackman & Oldham, 1976). Nonetheless,
our work is limited by dependence on self-ratings of work characteristics, and future work could
compare our findings to studies using objective data from O*NET data or work characteristics
rated by a coworker. Second, we also note the variance in side-hustle complexity in Study 1,
which reflects heterogeneity in side-hustle work. Intuitively this is not surprising as creating and
selling art on Etsy on the side of full-time work presents more complex work than cleaning
apartments on the side (e.g., lower skill variety, less task significance). Thus, although we found
an overall net positive effect of side-hustle empowerment on full-time work performance from a
within-person perspective, the variance at the between-person level, indicates that some workers
experience side-hustles that lack motivating potential and subsequently experience limited
empowerment from side-hustle work. However, given our consideration of within-person
variance in Study 2, the conclusions from our model about the positive and negative implications
of side-hustles for full-time work performance should apply to individuals with a high baseline
level of empowerment as well as individuals with lower baseline levels of empowerment.
Another limitation of our work is that the effect of hours worked on side-hustles does not
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have strong and clearly interpretable results in our model. For example, when we consider the
indirect effects of hours worked on side-hustles in place of side-hustle empowerment, we
observe a small indirect effect of hours worked on side-hustles on full-time work performance
through side-hustle engagement and positive affect at work (IND = .001, 95% CI = .000, .002 )
and insignificant indirect effects through side-hustle engagement and attention residue
(IND =.000, 95% CI = -.001, .000). These effects suggest that an individual would need to work
a large number of hours before having any substantive effect on full-time work performance.
Moreover, reverse causality is an issue in that side-hustle engagement may well predict hours
worked on side-hustles rather than the other way around. Thus, our model does not provide a
clear account of the effects of hours worked on side-hustles for full-time work outcomes. Instead,
our work better conveys how experiences in side-hustles (i.e., empowerment) affects full-time
work experiences. However, hours worked on side-hustles may have spillover effects given the
finite resources of employees. Future research could apply a conservation of resources approach
(Hobfoll, 1989) to examine how the number of hours spent working on side-hustles, as well as
the degree of scheduling flexibility, supplies or depletes employee resources in full-time work.
Moreover, as with all research, a limitation of our work is that we were unable to include
several interesting constructs and theoretical approaches within the scope of our paper. For
example, part of the appeal of side-hustles is that they present opportunities to obtain work
outside of one’s full-time job. This acquisition of supplementary work may provide a sense of
relief from feeling stuck in one’s day job. This point has particular bearing on our argument
about autonomy in side-hustles. Specifically, beyond work scheduling autonomy, decision-
making autonomy, and work methods autonomy that we capture, side-hustles may provide a
more global sense of autonomy in which individuals feel that they can always choose to have
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another job. Thus, side-hustles may provide a “hope for control” over an employee’s work life
and associated optimism about new work avenues. Future research could consider how the
psychological effect of feeling more in control of one’s work options from adopting a side-hustle
shapes employee outcomes. This point is particularly applicable to employee turnover given that
employment opportunities outside full-time work affect turnover intentions (e.g., Gerhart, 1990).
Finally, our recruitment approach through message boards addressed the difficulty of
obtaining data about individuals who work on side-hustles—the most frequently cited reason for
a lack of systematic consideration of side-hustles and multiple jobholding (e.g., Sliter & Boyd,
2014). Limitation of this approach include not knowing exactly how many people saw our posts
and decided not to participate, and we may have recruited participants who are more enthusiastic
about side-hustles than the average side-hustle worker who may not participate in message
boards on the topic. However, we note that the message boards we posted to were focused on
finding, developing, and managing side-hustles rather than extolling the benefits of the activity.
We also sought to recruit participants broadly by posting to over fifteen different message
boards. Drawing on various sources should have helped with the diversity in our sample.
Additionally, our ESM design in Study 2 helps to account for between-person differences that
may be systematically related to participating in message boards (e.g., extraversion) by focusing
on within-person variance. An advantage of our sample is that we recruited participants involved
with many different organizations and side-hustles, and this diversity in our sample should aid
the generalizability of our findings (Kerlinger & Lee, 2000).
Practical Implications
Our findings also have several practical implications. Given the sheer number of
employees who engage in side-hustles (Clark, 2018), organizations should be cognizant that they
may employ many individuals who participate in side-hustles. Managers should consider it a
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worthwhile endeavor to understand how side-hustles shape full-time work given our findings
related to full-time work performance. Ultimately, our findings suggest that side-hustles offer
empowerment, which results in a mixture of positive and negative effects with an overall net
positive effect. Thus, managers may find that the benefits of allowing employees to engage in
side-hustles outweighs their costs. Further, attempting to limit what employees do outside of
work, such as participating in side-hustles, could create resentment among employees. A more
fruitful approach may be combatting other distractions at work (Jett & George, 2003) as these
other interruptions will compound the effects of attention residue from side-hustles. We note that
our findings suggest that experiences during side-hustles (i.e., the extent of side-hustle
empowerment) appear to have a more significant effect on employee outcomes than merely
considering the number of hours worked. However, employees have finite resources (Hobfoll,
1989), so working long hours on a side-hustle may have adverse consequences such as
exacerbating work-family conflict.
The present research also has implications for employees who maintain side-hustles.
Overall, our study presents a positive outlook for employees with side-hustles as our findings
suggest that these employees can, in addition to increasing their income, experience
psychological empowerment, which positively spills over into the workplace. However, our
Study 1 findings suggest that the extent to which employees experience side-hustle
empowerment is influenced by what they do (i.e., work characteristics) and why they do it (i.e.,
motives). Although side-hustle complexity was associated with increased empowerment,
employees who maintain a side-hustle will have to weigh the benefits of increased income and
positive affect at work with the benefits they would receive from using their limited time outside
of work in other ways. For example, time with family (e.g., Rothbard, 2001), leisure activities
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(e.g., Vogel et al., 2016), volunteering (e.g., Rodell, 2013), and sleeping (e.g., Barnes, Wagner,
& Ghumman, 2012) all can have significant benefits for energy, recovery, well-being, and other
positive outcomes at work. Although these other non-work activities offer benefits, our findings
that side-hustles provide empowerment, in addition to supplemental income, is a point of
encouragement for the large and growing population of workers who participate in side-hustles.
Conclusion
The new world of work is on our doorstep (Ashford et al., 2018), and as organizational
scholars, we have much to learn about contemporary work dynamics. To that end, we
investigated the phenomenon of side-hustles and the effects of opportunities to shape the work
and context therein. We found that employees do indeed experience empowerment from side-
hustles to the extent that the work has high motivating potential. Furthermore, employees
respond more vigorously to side-hustles depending on the motives for which they are pursued.
We also found that the empowering experience of side-hustles spillover to full-time work to both
enrich and conflict with full-time work performance, although the net effect of side-hustle
empowerment on full-time work performance was positive. Overall, our research advances
understanding of the gig economy and its implications for employees and organizations as well
as opening avenues for future research.
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TABLES AND FIGURES
Table 1. Study 1 Descriptive Statistics, Correlations, and Reliabilities of Study Variables
Variable
Mean
SD
1
2
3
4
5
6
1. Side-hustle complexity
3.51
0.57
(.83)
Side-hustle motives
2. Self-enhancement
3.32
0.55
.46**
(.68)
3. Self-transcendence
2.39
0.95
.45**
.48**
(.90)
4. Openness-to-change
3.40
0.94
.39**
.32**
.30**
(.90)
5. Conservation
2.92
0.88
.46**
.52**
.41**
.54**
(.82)
6. Side-hustle empowerment
3.61
0.59
.60**
.40**
.51**
.44**
.33**
(.82)
Note. n = 337. Coefficient alpha is provided along the diagonal.
* p < .05; ** p < .01; two-tailed.
Table 2. Study 2 Variance Components of Null Models for Daily Variables
Within-Individual
Variance 2)
Between-
Individual
Variance 00)
Percentage of
Variability
Within-Individual
0.10**
0.27**
27.0%
0.12**
0.23**
34.3%
0.21**
0.36**
36.8%
0.38**
0.86**
30.6%
0.35**
1.20**
22.6%
0.18**
0.20**
47.4%
Note. ρ2 = within-individual variance in the dependent variable. τ00 = between-individual variance in the dependent variable. Percentage of variability within-
individual was computed as ρ2 / 2 + τ00).
* p < .05; ** p < .01; two-tailed.
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Table 3. Study 2 Descriptive Statistics, Correlations, and Reliabilities of Study Variables
Note. Level 1: n = 507. Level 2: n = 80. Average coefficient alpha across days is provided along the diagonal. All correlations are at the within-person level. All
correlations above the diagonal at the between-person level. Between-person correlations were calculated using the aggregated Level-1 variables.
* p < .05; ** p < .01; two-tailed.
Variable
Mean
SD
1
2
3
4
5
6
7
8
1. Side-hustle Empowerment
4.07
0.63
(.91)
–.18
.79**
.40**
.37**
.33**
a.31**
.40**
2. Full-time Work Negative
Affect
1.40
0.70
–.02
(.92)
–.23*
–.43**
.28*
–.37**
.08
.00
3. Evening Side-hustle
Engagement
3.90
0.75
.22**
–.07
(.93)
.43**
.43**
.23*a
aa.36**
.46**
4. Full-time Work Positive
Affect
3.64
1.08
.02
.02
.47**
(.96)
–.04 a
.59**
.20
.43**
5. Full-time Work Attention
Residue
2.99
1.22
.06
–.02
.37**
.07
(.94)
–.04a
.28*
.28*
6. Full-time Work
Performance
4.22
0.60
.03
.00
.27**
.46**
.06a
(.78)
.01
.54**
7. Side-hustle Work Time
(hours)
2.08
1.33
.06
–.05
.28**
.23**
.16**
.07
.34**
8. Opportunity to Observe
4.28
0.78
.05
.03
.37**
.37**
.27**
.52**
.28**
(.95)a
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Table 4. Study 2 Results of Multilevel Path Analysis
Variables
Side-hustle
engagement ()
Positive affect within
full-time work ()
Attention residue within
full-time work ()
Full-time work
performance ()
Side-hustle empowerment
0.65**
–0.02
0.03
–0.06
Full-time work negative affect
–0.11
Interaction of side-hustle engagement
and full-time work negative affect
0.70**
Previous-day side-hustle
engagement
0.63**
Side-hustle work time
0.04**
Side-hustle engagement
0.22**
0.16**
Previous-day positive affect within
full-time work
0.62**
Positive affect within full-time
work
0.12**
Previous-day attention residue
within full-time work
0.73**
Attention residue within full-time
work
–0.05**
Previous-day full-time work
performance
0.40**
Coworker opportunity to observe
0.24**
Pseudo R2
51.1%
49.3%
62.2%
46.9%
Note: All variables at the within-person level, n = 507. Hypothesized coefficients are bolded. Controlling for previous day ratings of focal constructs enables us
to interpret our results as a change in that criteria from the previous day (Johnson et al., 2014; Scott & Barnes, 2011). *p < .05, **p < .01; two-tailed.
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Figure 1. Empowerment from Side-hustles and Its Spillover Effects on Full-time Work Performance
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Figure 2. Study 1 Interaction Effects of Side-hustle Complexity and Side-hustle Motives on
Side-hustle Empowerment
Figure 2a. Interaction effect of side-hustle complexity and self-enhancement on side-hustle
empowerment.
Low Side-hustle complexity
High Side-hustle complexity
3
3.5
4
Low Self-enhancement
High Self-enhancement
Side-hustle empowerment
Figure 2b. Interaction effect of side-hustle complexity and self-transcendence on side-hustle
empowerment.
Low Side-hustle complexity
High Side-hustle complexity
3
3.5
4
4.5
Low Self-
transcendence
High Self-
transcendence
Side-hustle empowerment
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Figure 2c. Interaction effect of side-hustle complexity and conservation on side-hustle
empowerment.
Low Side-hustle complexity
High Side-hustle complexity
3
3.5
4
Low Conservation
High Conservation
Side-hustle empowerment
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Figure 3. Study 2 Path Model of Side-hustle Enrichment and Conflict with Full-time Work Performance
.22**
.73**
.16**
.12**
-.05**
Daily
side-hustle
empowerment
(evening)
Full-time work
positive affect
(next day,
midday)
Full-time work
negative affect
(midday)
Daily
side-hustle
engagement
(evening)
Daily
side-hustle
engagement
(previous day)
Daily full-time
work
performance
(next day,
end-of-day)
.70**
(H6/H7)
.65** (H3)
Full-time work
attention residue
(next day,
midday)
Full-time work
attention residue
(pervious day)
Full-time work
positive affect
(previous day)
Full-time work
performance
(previous day)
.40**
.62**
Note. We controlled for side-hustle empowerment on our mediators and
dependent variable. The gray variables are controls that were modeled but
not hypothesized. Side-hustle work time and opportunity to observe were
also modeled (see Table 4). All variables were considered on a daily level.
* p < .05; ** p < .01; two-tailed.
.63**
(H4)
(H5)
(H4)
(H5)
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Figure 4. Study 2 Interaction of Side-hustle Empowerment and Full-time Work Negative
Affect on Side-hustle Engagement
Low Side-hustle
Empowerment
High Side-hustle
Empowerment
3.5
4
4.5
Low Full-time Work
Negative Affect
High Full-time Work
Negative Affect
Side-hustle Eengagement
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APPENDIX A: JOB FAMILIES OF STUDY PARTICIPTANS
Table A1. O*NET Job Families for Side-hustles and Full-time Jobs (Study 1 and Study 2)
Job Family per O*NET Taxonomy
Study 1
Side-hustles
Study 1
Full-time Jobs
Study 2
Side-hustles
Study 2
Full-time Jobs
Architecture and Engineering
1%
4%
3%
3%
Arts, Design, Entertainment, Sports, and Media
15%
5%
12%
5%
Building and Grounds Cleaning and Maintenance
1%
1%
-
-
Business and Financial Operations
12%
7%
16%
3%
Community and Social Service
-
2%
-
3%
Computer and Mathematical
4%
12%
3%
9%
Construction and Extraction
-
1%
3%
-
Education, Training, and Library
4%
7%
-
10%
Farming, Fishing, and Forestry
-
-
-
3%
Food Preparation and Serving Related
1%
3%
-
4%
Healthcare Practitioners and Technical
1%
5%
-
5%
Healthcare Support
2%
2%
-
-
Installation, Maintenance, and Repair
5%
1%
5%
1%
Legal
-
2%
-
-
Life, Physical, and Social Science
19%
5%
18%
1%
Management
1%
14%
3%
24%
Military Specific
-
1%
-
-
Office and Administrative Support
9%
10%
3%
10%
Personal Care and Service
8%
4%
5%
4%
Production
1%
1%
3%
4%
Protective Service
-
1%
-
-
Sales and Related
6%
10%
10%
11%
Transportation and Material Moving
10%
2%
15%
-
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Hudson Sessions (sessions@uoregon.edu) is an Assistant Professor in the Department of
Management at the University of Oregon’s Lundquist College of Business. He received his PhD in
Management from the W. P. Carey School of Business at Arizona State University. His research
focuses on alternative work arrangements, the interface between work and life domains, and
employee voice.
Jennifer D. Nahrgang (jennifer.nahrgang@asu.edu) is a Professor of Management and
Entrepreneurship at the W.P. Carey School of Business at Arizona State University. Jennifer holds
a PhD in Organizational Behavior from the Eli Broad College of Business at Michigan State
University. In the area of research, Jennifer focuses on leadership processes and leadership
development, team dynamics and effectiveness, employee voice and engagement, and the future
world of work.
Manuel J. Vaulont (manuel.vaulont@asu.edu) is a doctoral student in the W. P. Carey School of
Business at Arizona State University. He received his B.Sc. in industrial-organizational
psychology from Philipps-Universität in Marburg, Germany. His research focuses on team
coordination processes, employee overqualification, and research methods.
Raseana Williams (raewilliams1993@gmail.com) received a master's degree from the W. P.
Carey School of Business at Arizona State University. Her research interests include leadership,
teams, and diversity.
Amy L. Bartels (amy.bartels@unl.edu) is an Assistant Professor of Management at the University
of Nebraska-Lincoln. She received her PhD in Management from the W. P. Carey School of
Business at Arizona State University. Her research focuses on understanding the dynamics of
leadership and teams as well as drivers of employee well-being both within and outside the
workplace.
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... Another overlapping area is the identit and empowerment of gig workers. Petriglieri et al. (2019) explore how these workers man age their identities in precarious work environments, while Sessions et al. (2021) analyz how side hustles can empower workers and influence their primary job performance. Ad ditionally, articles from Waldkirch et al. (2021) and Gleim et al. (2019) delve into the dy namics of worker perceptions and the dual roles of algorithms and peer-based support i the gig economy. ...
... (2022)andWiener et al. (2023) examine how algorithmic management affects Uber drivers, highlighting issues of stress and legitimacy. Another overlapping area is the identity and empowerment of gig workers.Petriglieri et al. (2019) explore how these workers manage their identities in precarious work environments, whileSessions et al. (2021) analyze how side hustles can empower workers and influence their primary job performance. Additionally, articles fromWaldkirch et al. (2021) andGleim et al. (2019) delve into the dynamics of worker perceptions and the dual roles of algorithms and peer-based support in the gig economy. ...
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Purpose Digital platform work monitored by algorithms is increasingly supplementing or substituting standard employment. Though gig workers are faced with the vulnerable, fragile and precarious digital platform work environment, the reason why gig workers remain highly willing to show good task performance has been so far unexamined. Building upon the reciprocity of the social exchange theory, this study aims to explore the antecedents and boundary condition of facilitating gig workers’ task performance. Design/methodology/approach First, to minimize common method variance, decline spurious mood effects and ensure data robustness, we conducted a two-wave time-lagged survey and collected 269 survey responses from gig workers on different gig platforms in China (e.g. Meituan, Eleme, Didi, Credamo, Zaihang) at two time nodes. Second, abiding by two stage procedures of the PLS-SEM (partial least square structural equation model) approach, we analyzed a moderated mediation model in the digital platform work context. Findings Results present that both platform work remuneration and flexibility help gig platforms develop an affective trust relationship with gig workers, thus encouraging them to repay the platform by performing platform tasks well. Algorithmic monitoring shows a “double-edged sword” moderating role since it weakens the indirectly positive relationship between platform work remuneration and task performance via affective trust but enhances the indirectly positive relationship between platform work flexibility and task performance via affective trust. Practical implications Understanding the importance of remuneration and flexibility in developing affective trust can help platforms design effective human resource management (HRM) strategies that enhance worker motivation of maintaining high engagement and performance under precarious working conditions. Additionally, optimizing the “double-edged sword” moderating role of algorithmic monitoring makes it more humanized, enhancing the efficiency with these HRM strategies and making both workers and platforms beneficial. Originality/value These findings offer an affective trust-based explanation for the mechanism of maintaining high work performance motivation in the nonstandard and precarious employment from the social exchange perspective, while understanding the (de)humanized aspect of algorithmic monitoring by revealing its “double-edged sword” moderating role.
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The continuous acquisition of knowledge and skills throughout one's life, encompassing both formal and informal learning experiences in diverse settings, is referred to as lifelong learning. This trend promotes both professional and personal growth because it is driven by internal motivations. The capacity to extract meaning from experiences and the deliberate effort to reflect and adjust are qualities that define lifelong learning. It necessitates continuing education and the ability to adjust as one's career changes. Participating in non-formal adult education programs and community service can foster lifelong learning. Philosophical viewpoints such as Friedrich Nietzsche's have also impacted the idea. Employees must pursue lifelong learning in order to stay competitive and grow in their careers as the workplace changes. It provides advantages like improving skills for present roles, getting ready for new chances and career changes, and keeping intellectual curiosity and work engagement.
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