Running head: NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN
Stop and Go, Where is My Flow? How and When Daily Aversive Morning Commutes
Are Negatively Related to Employees’ Motivational States and Behavior at Work
Fabiola H. Gerpott*
WHU – Otto Beisheim School of Management, Management Group
Erkrather Str. 224a, 40233 Duesseldorf, Germany, firstname.lastname@example.org
Trinity Business School, Trinity College Dublin, Dublin 2, Ireland, RIVKINW@tcd.ie
University of East Anglia, Norwich Business School
Norwich Research Park, Norwich, NR4 7TJ, United Kingdom, D.Unger@uea.ac.uk
* Both authors contributed equally
Correspondence concerning this article should be addressed to Fabiola H. Gerpott, WHU – Otto
Beisheim School of Management, Erkrather Str. 224a, 40233 Duesseldorf, Germany. Email:
email@example.com, phone: +49 176 6461 2659
There is no specific funding to report for this research. The authors declare that there is no
conflict of interest. An earlier version of this paper was presented at the 2019 EAWOP
conference in Turin (Italy) and we thank the participants for their insightful feedback.
© 2021, American Psychological Association. This paper is not the copy of record and may
not exactly replicate the final, authoritative version of the article. Please do not copy or cite
without authors' permission. The final article will be available, upon publication, via its
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 2
Despite convincing evidence about the general negative consequences of commuting for
individuals and societies, our understanding of how aversive commutes are linked to employees’
effectiveness at work is limited. Drawing on theories of self-regulation and by extension a
conservation of resources perspective, we develop a framework that explains how an aversive
morning commute—a resource-depleting experience characterized by interruptions of automated
travel behaviors—impairs employees’ immersion in uninterrupted work (i.e., flow), which in
turn reduces employee effectiveness (i.e., work engagement, subjective performance, and OCB-
I). We further delineate theoretical arguments for daily self-control demands as a boundary
condition that amplifies this relation and propose the satisfaction of employees’ basic needs as
protective factors. Two diary studies across 10 workdays (Study 1: 53 employees, 411 day-level
data points; Study 2: 91 employees, 719 day-level data points) support most of our hypotheses.
Study 1 demonstrates that daily aversive morning commutes negatively affect employees’ daily
work engagement through lower levels of flow experiences, but only on days with high impulse
control demands. In addition, we find initial support that employees’ general autonomy and
competence needs satisfaction attenuate this interaction. Study 2 rules out alternative
mechanisms (negative affect, tension), demonstrates ego depletion as an additional mediator of
the relation between aversive morning commutes and work effectiveness and replicates the
hypothesized three-way interaction for daily competence need satisfaction. We critically discuss
the findings and reflect on corporate interventions, which may allow people to more easily flow
to and at work.
Keywords: commuting; conservation of resources; flow experience; self-regulatory
resources; employee effectiveness
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 3
Stop and Go, Where is My Flow? How and When Daily Aversive Morning Commutes Are
Negatively Related to Employees’ Motivational States and Behavior at Work
Notwithstanding attempts to promote teleworking (Browne, 2018) and exceptional
circumstances during the COVID-19 pandemic (Thompson, 2020), more than 90% of employees
commute to work every day, with average commuting times steadily increasing (Federal
Statistical Office Germany, 2012; Ingraham, 2017; Office for National Statistics UK, 2014; Zhu
et al., 2017). Given the high prevalence of commuting, you are likely one of those people who
traveled from home to work this morning. How did you experience your morning commute?
Unfortunately, on some days, you may answer this question by describing aversive commute
experiences, such as referring to your morning commute as “a nightmare” (Ye & Ma, 2019) or
“hell” (Gerdemann, 2019) or telling “tales of a frustrated commuter” (Seay, 2019). Your
commute may have been slow or unpleasant or may have knocked you out of rhythm, for
example, because the traffic flow was interrupted by stop-and-go driving. Indeed, Kahneman and
Krueger (2006) suggest that people’s morning commutes tend to be among their least enjoyable
daily activities. You can probably vividly imagine being drained when arriving at work after such
an aversive commute experience. What does your organization do to help you overcome this
feeling and facilitate a smooth transition into the workday? Most likely “Not much.”
The prevalence of commuting as a necessary but often unpleasant experience has prompted
researchers from various fields to study its consequences for both individuals and societies. For
example, previous research has demonstrated the negative effects of commuting on individuals’
general health and well-being (Koslowsky, 1997; Lorenz, 2018; Novaco & Gonzalez, 2009;
VitalityHealth, 2017). Furthermore, because many employees consider that the time spent
commuting to work adds to their overall working hours and thus reduces their hourly wages,
scholars have also investigated trade-offs between pay and length of the commute (Dauth & Haller,
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 4
2020; Nogland & Small, 1995). On the societal level, research has provided evidence concerning
the broader negative impact of commuting on environmental pollution (Coria & Zhang, 2017;
Johansson et al., 2017), destruction of the environment through expanding and maintaining
infrastructure (Laurance et al., 2009), and traffic congestion (Fosgerau et al., 2018; Wu et al., 2019).
Overall, research suggests that commuting is largely harmful for both individuals and societies.
However, we cannot draw an equally rich picture of the consequences of commuting for
organizations in terms of whether and how employees engage with their daily work.
The lack of awareness of and evidence about the work-related consequences of aversive
morning commutes (i.e., negative subjective experiences of impeded goal attainment while
traveling from home to work; Stokols et al., 1978) has resulted in most organizations
externalizing commuting costs and neglecting the implementation of measures to protect
employees from the potentially harmful effects of aversive commutes. To increase organizations’
willingness and ability to address this focal topic, there is a need for research that links
commuting to organizational effectiveness (Ma & Ye, 2019) and identifies the mechanisms
underlying this link. Moreover, identifying contingencies that can reduce the adverse effects of
aversive morning commutes could provide managers with specific insights into how they can
alleviate the adverse organizational consequences of this somewhat unavoidable stressor through
appropriate interventions. Thus, our research seeks to contribute to an emerging conversation
about commuting spillover (i.e., interrelationships between commuting and work experiences,
Calderwood & Mitropoulos, 2020; Zhou et al., 2017) by examining the mechanisms and
boundary conditions of the link between aversive commutes and employee effectiveness.
From a theoretical perspective, a crucial element of an aversive morning commute is that
it impedes goal pursuit (i.e., arriving at work on time). In contrast to an uninterrupted commute,
which for the most part relies on automated cognitive processing and behaviors (Stokols et al.,
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 5
1978), overcoming an aversive morning commute necessitates effortful inhibition of behavioral
responses (e.g., abstaining from driving faster and more aggressively) and additional decision-
making (e.g., considering alternative routes to work). This core proposition that an aversive
morning commute constitutes a goal-inhibiting and resource-depleting experience characterized
by a shift from automated toward controlled cognitive processing underlies the conceptual link
between an aversive morning commute and employees’ immersion in uninterrupted work. In
other words, we explicate that a depleting commute spills over to the workplace and reduces the
likelihood that employees will lose themselves in fluent peak states of motivation referred to as
flow experiences (Csikszentmihalyi & LeFevre, 1989). Flow experiences build employees’
resources at work and thereby facilitate work engagement (i.e., a pervasive positive motivational
state that captures the degree to which employees apply their cognitive, physical, and emotional
energies to their jobs), in-role behaviors (i.e., subjective performance, referring to the perceived
effective fulfillment of job duties), and extra-role behaviors (i.e., intrapersonal organizational
citizenship behavior [OCB-I], which refers to discretionary acts that go beyond job duties) at the
end of the workday. These indicators of employee effectiveness have been identified as crucial
predictors of organizational functioning (Call & Ployhart, in press; Christian et al., 2011).
Self-regulation (Muraven & Baumeister, 2000) and by extension conservation of
resources theory (COR; Hobfoll et al., 2018) provide a framework to delineate the proposed
mechanisms and identify contingencies that can modulate the adverse effects of an aversive
morning commute. Engaging in self-regulation, consumes individual’s regulatory resources
resulting in ego depletion—a state of reduced regulatory resources (Muraven & Baumeister,
2000). Furthermore, the lack of resources, makes individuals more vulnerable to resource loss
and less capable of resource gain (Hobfoll et al., 2018). This is because reduced resources (i.e.,
ego depletion) trigger a resource protection mode characterized by motivational tendencies to
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 6
conserve and protect remaining resources (Chong et al., 2020; Giacomantonio et al., 2014;
Muraven et al., 2006). Integrating these propositions, we argue that the depletion of regulatory
resources through an aversive commute initiates a daily regulatory resource loss process, which
reduces the likelihood of experiencing flow. We further suggest that this resource loss process is
exacerbated by additional work-related self-control demands, such as the requirement to inhibit
spontaneous, impulsive response tendencies and emotions to maintain controlled, purposeful
behavior (i.e., impulse control demands, Schmidt & Neubach, 2007). This moderating effect
occurs because coping with self-control demands requires employees to invest regulatory
resources, which becomes increasingly difficult when experiencing tendencies to protect and
conserve said resources. Thus, coping with self-control demands when in states of ego depletion
after an aversive morning commute should result in an overadditive depletion of an employees’
regulatory resource pool, which impairs flow experiences and associated employee effectiveness.
COR theory not only outlines loss processes but can also be integrated with self-
determination theory (Ryan & Deci, 2000), which states that the satisfaction of basic psychological
needs at work (autonomy, competence, and relatedness) enhances intrinsic motivation associated
with activities at work that are congruent with deeply held values or one’s ‘true self’ (Ryan & Deci,
2001). This in turn replenishes employees’ pool of regulatory resources and thereby facilitates the
willingness to invest said resources at work (Deci & Ryan, 2001, 2008; Van den Broeck et al.,
2016). Expanding our theoretical framework through self-determination theory, we propose work-
related psychological needs satisfaction as a motivational contingency, which counteracts the
tendency to conserve regulatory resources through replenishing said resources (Van den Broeck et
al., 2016). To summarize, we propose that work-related needs satisfaction can interrupt the daily
regulatory resource loss process initiated by an aversive morning commute and exacerbated by
work-related self-control demands, which reduces flow experiences and culminates in impaired
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 7
employee effectiveness (cf. Figure 1).
Our research aims to make three contributions. First, we identify flow experiences as a
central mechanism of the daily link between an aversive morning commute and employee
effectiveness. Conceptually, connecting an interrupted travel experience (i.e., an aversive morning
commute) with employees’ subsequent experiences of fluent, uninterrupted task work (i.e., flow)
unites two seemingly disparate streams of research under the umbrella of COR theory. More
specifically, by focusing on the role of regulatory resources in the relation between a daily aversive
commute and flow experiences, our research expands notions on flow as a psychological state
entering which requires the initial investment of regulatory resources but once it is experienced,
flow can replenish regulatory resources. Second, based on our integration of self-regulation and
COR theory, we consider self-control demands as a moderator of the proposed relationship. Based
on the notion that individuals enter a state of regulatory resource protection when feeling depleted,
we theorize that having to further self-regulate when experiencing motivational tendencies to
conserve resources overtaxes employees' pool of regulatory resources, which manifests in reduced
flow experiences. Our research thus outlines the theoretical mechanisms that can explain why
coping with multiple self-control demands exhibits overadditive effects (Dang, 2018; Diestel &
Schmidt, 2011; van Woerkom et al., 2016). Finally, our research links self-determination theory
with a resource protection perspective to theoretically delineate and empirically test the proposition
that motivational contingencies can interrupt daily resource loss processes initiated by an aversive
morning commute and exacerbated by self-control demands.
Flow as the Link Between an Aversive Morning Commute and Work Engagement
Work-related motivational states refer to a set of energetic forces that determine the
intensity, direction, and duration of an employee’s efforts toward achieving a goal such as
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 8
completing work tasks (Pinder, 2008; Robbins & Judge, 2019). In contrast to traits, motivational
states fluctuate between and even within days. We seek to expand our understanding of these day-
to-day fluctuations by focusing on aversive morning commutes. Specifically, we draw on self-
regulation (Muraven & Baumeister, 2000) and by extension COR theory (Hobfoll, 1989; Hobfoll
et al., 2018; Hobfoll & Shirom, 2001) to explicate how an aversive commute reduces an
employee’s experiences of peak motivation (i.e., flow), that in turn replenishes resources and
contributes to more global longer-lasting motivational states at work.
According to self-regulation theory, individuals strive to limit their use of self-regulatory
resources, especially when they have depleted some of those resources (Muraven et al., 2006). This
ties in with COR theory which suggests that a low availability of resources results in tendencies to
conserve remaining resources (Chong et al., 2020; Giacomantonio et al., 2014). The resource-
draining experience of an aversive morning commute results in a state of ego depletion (Zhou et
al., 2017), which entails that employees subsequently attempt to preserve their remaining
regulatory resources. This resource protection mode manifests when employees experience a
goal-inhibiting incident and subsequently work in a “state of distractibility [...] that prevents
employees from being fully engaged” (Leroy et al., 2020, p. 44). Interruptions require employees
to shift from states of automatic cognitive processing that is highly efficient and requires barely
any self-regulation towards states of controlled processing that are much more resource-
intensive, as they involve conscious planning, decision-making, and monitoring of cognitions
and associated behaviors (Baumeister et al., 2000). Due to its regular occurrence, commuting is
for most employees a habit that relies foremost on automatic processing (Elfering et al., 2013).
However, aversive commute experiences require employees' self-regulation to shift toward
controlled cognitive processing (Leroy et al., 2020). For example, employees may need to adapt
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 9
daily work plans when arriving later at work or decide during the commute whether to pass on
information about potential delays to colleagues. In turn, states of controlled cognitive
processing deplete regulatory resources and put employees into a resource protection mode.
This resource protection mode prevents employees from experiencing of positive
motivational states at work. Since individuals must invest resources to gain resources (Hobfoll et
al., 2018), a resource protection mode can paradoxically prevent flow experiences at work,
defined as positive motivational states that manifests in short, intensive peak experiences during
any activity or task. While flow is an enjoyable state that can restore regulatory resources,
reaching it requires initial regulatory resource investment (Csikszentmihalyi et al., 2005). For
example, to experience flow, employees must self-regulate to overcome initial motivational
barriers when beginning with a challenging work task, and, because flow does not occur
instantly, employees must resist distractions and interruptions when persisting with that task to
eventually reach this peak state of motivation. Doing so, however, becomes increasingly difficult
when employees are in a resource protection mode associated with states of ego depletion. The
absence of flow, in turn, makes employees feel less physically, cognitively, and emotionally
connected with their work and prevents “successful recovery from (…) energy-draining
experiences” (Demerouti et al., 2012, p. 278). In summary, an aversive morning commute triggers
a daily regulatory resource loss process that prevents the benefits of the resource-restoring function
of flow experiences (Demerouti et al., 2012; Sonnentag et al., 2012). This argument aligns with
the COR theory’s proposition that resource depletion makes individuals more vulnerable to
resource loss and less capable of resource gain (Hobfoll et al., 2018).
Expanding our argument toward employee effectiveness, we propose that employees show
less work engagement—a core indicator of employee effectiveness (Schneider et al., 2018)—on
days when they experienced flow less frequently due to an aversive morning commute. Work
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 10
engagement constitutes a pervasive motivational state that captures the degree to which employees
apply their cognitive, physical, and emotional energies to their jobs (Newton et al., 2020). In
contrast to flow, which represents an acute state of immersion in a particular task or activity that
can but does not need to be work-related, work engagement is not focused on any specific task,
objective, or activity but instead describes a general connection with one’s work on multiple levels
(Demerouti et al., 2012). More specifically, work engagement encompasses a physical-energetic
component during work (vigor), an emotional component of being proud of the work one is doing
(dedication), and a cognitive component of feeling engrossed when working hard (absorption). A
core difference between work engagement and flow is that flow is a task-specific motivational state
consisting of being focused on a present activity, the merging of action and awareness, the
feeling that the activity is guided by an inner logic, and a change in one’s experience of time
(Csikszentmihalyi, 1975). Supporting the conceptual uniqueness of the task-specific nature of
flow and the general nature of work engagement, both constructs exhibit differential
relationships with work outcomes (Van Ittersum, 2015).
The theoretical rationale for the positive link between flow and work engagement is based
on the resource recovery function of flow. During states of flow, employees perceive their tasks or
activities as interesting and enjoyable, which develops and broadens motivational resources toward
their job (Demerouti et al., 2012). That is, flow experiences make individuals feel more positive
about their jobs and can foster energy for broader work tasks beyond the activity at hand. In line
with this notion, two diary studies (Demerouti et al., 2012; Xanthopoulou et al., 2018) have shown
that flow is related to day-specific recovery and vigor as well as a lower level of end-of-workday
exhaustion and a reduced need for recovery. To summarize, we pose the following hypothesis:
Hypothesis 1: The negative day-specific relation between an aversive morning commute
and work engagement is mediated by flow experiences.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 11
The Moderating Role of Daily Impulse Control Demands
Impulse control demands, which encompass dealing with an unfriendly customer or talking
politely to an unpleasant colleague reflect a prevalent daily demand for most employees. Coping
with this demand requires employees’ self-regulation, which depletes their regulatory resources
(Diestel & Schmidt, 2011; Rivkin et al., 2015; Schmidt & Neubach, 2007). Field (Diestel &
Schmidt, 2011; van Woerkom et al., 2016) and experimental studies (Dang, 2018) have
demonstrated that coping with multiple self-control demands jointly overtaxes employees’
regulatory resources leading higher level of depletion than predicted by their additive effects.
The notion that multiple activities that require self-regulation might reinforce each other
and exert overadditive effects can be explained based on COR theory (Hobfoll & Shirom, 2001),
which suggests that resource loss stemming from depleting activities reduces available resources
for subsequent activities and makes employees more vulnerable when they are forced to expend
additional resources to cope with upcoming demands (van Woerkom et al., 2016). This increased
vulnerability emerges because depleted employees must not only self-regulate to cope with the
additional upcoming demands but also overcome motivational tendencies to conserve regulatory
resources. In other words, they are in a resource protection mode (Chong et al., 2020) that
sensitizes them toward further resource demands, but they cannot follow their natural tendency
to withdraw from these demands to replenish their regulatory resources. Instead, employees who
face high impulse control demands at work are prompted by their work situation to invest
regulatory resources to handle such demands. As such, employees who are depleted face the risk
of a loss spiral, which COR theory describes by stating that people with fewer resources are
more likely to experience further loss of resources (Hobfoll et al., 2018).
Transferred to the context of an aversive morning commute, the previous line of
argumentation implies that an employee who arrives at work in an already depleted state (Zhou et
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 12
al., 2017) becomes more defensive toward investing further resources (Halbesleben et al., 2014;
Hobfoll & Shirom, 2001). When this employee is confronted with high daily work-related impulse
control demands, investing regulatory resources becomes disproportionally more difficult because,
in addition to the depleting effect of the demand itself, the employee must overcome the urge to
conserve their resources. That is, the employee’s state of depletion puts them into a heightened
resource protection mode that, according to COR theory emerges when individuals have already
lost resources (Chong et al., 2020; Muraven et al., 2006). In turn, the employee must invest
comparatively more regulatory resources to handle the demands than when in a non-depleted
state. Because experiencing flow necessitates the initial expenditure of regulatory resources, this
translates into a reduced likelihood of experiencing flow, which ultimately manifests in lower
work engagement. In combination, this leads to the following hypothesis:
Hypothesis 2: Day-specific impulse control demands moderate the indirect negative
day-specific relation between an aversive morning commutes and work engagement via
flow experiences such that the relationship becomes stronger when impulse control
demands are high.
Basic Needs Satisfaction as a Protective Factor against the Joint Effects of an Aversive
Commute and Self-Control Demands
Thus far, we focused on the regulatory resource loss process initiated by an aversive
morning commute and exacerbated by self-control demands. As both stressors cannot always be
avoided, the question of how employee effectiveness can be protected from the adverse interplay
of both stressors arises. To answer this question, we propose motivational contingencies as
potential moderators that can interrupt the regulatory resource loss process. More specifically,
previous research has suggested that the intrinsic motivation associated with activities that are
congruent with deeply held values or one’s “true self” facilitates employees' optimal functioning
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 13
(Abuhamdeh, 2012; Ryan & Deci, 2001). According to self-determination theory (Ryan & Deci,
2000), the satisfaction of three basic psychological needs represents a core contingency, which
enhances intrinsic motivation: The need for autonomy (i.e., an individual’s desire to act
according to integrated norms and values and thus to be the origin or source of one’s behavior),
the need for competence (i.e., a capacity to interact effectively in a specific environment and to
experience opportunities to enhance and express these capabilities), and the need for relatedness
(i.e., a feeling of staying connected with and being cared for by significant other).
Drawing on COR theory’s proposition that people with greater resources are less
vulnerable to resource loss and better positioned for resource gain (Halbesleben et al., 2014;
Hobfoll & Shirom, 2001), we argue that a work environment that satisfies employees’ basic
psychological needs facilitates intrinsic (in contrast to extrinsic) motivation, which helps maintain
and enhance regulatory resources (Ryan & Deci, 2008). Thus, an employee whose needs are
satisfied can draw on an expanded pool of regulatory resources, which enhances their willingness
to invest said resources at work and reduces the tendency to protect their remaining regulatory
resources when they are depleted through an aversive morning commute. The reduced
susceptibility to conserving regulatory resources is particularly helpful in alleviating the
overadditive resource drain caused by coping with self-control demands in a depleted state because
it helps employees to overcome motivational tendencies to protect remaining resources, which
makes coping with self-control demands less depleting. Accordingly, employees with high needs
satisfaction still possess sufficient regulatory resources to experience flow even when confronted
with both an aversive morning commute and additional impulse control demands.
In line with theoretical and empirical calls to examine the distinct effects of each need (van
Den Broeck et al., 2010), we next outline the unique contribution of each need to enhance
employees’ regulatory resource pools and reduce the tendency to conserve regulatory resources.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 14
First, employees with high autonomy need satisfaction engage in work out of a sense of
autonomous choice and volition. This can—but does not necessarily—overlap with employees’
job autonomy (Cooman et al., 2013). If employees feel that their autonomy need is satisfied, they
experience harmonious and efficient behavioral regulation (i.e., intrinsic motivation) that
expands their regulatory resource pools (Ryan & Deci, 2008), which in turn helps them to avoid
entering a resource preservation mode associated with ego depletion. In contrast, employees with
low autonomy need satisfaction are more likely to engage in work out of a sense of external
pressure and to perceive that they cannot determine when and how to tackle work demands. This
lack of autonomy need fulfillment thus entails that they are in an alerted state of monitoring their
remaining resources, which means they need to invest much more of their remaining resources to
experience flow than their autonomously motivated counterparts.
Second, high competence need satisfaction counteracts the tendency to conserve
regulatory resources in the face of overadditive resource demands by facilitating automatic (as
opposed to controlled) cognitive processing when engaging in work-related activities
(Baumeister et al., 2000). Experimental (Fairclough et al., 2005) and applied (Ohly et al., 2017)
research supports this notion by demonstrating that being competent in a certain area facilitates
automated processing. As it is efficient and requires barely any self-regulation (Kaplan &
Berman, 2010), automatic processing helps to maintain and preserve regulatory resources for
challenging work tasks. To illustrate, when attempting to resolve a customer’s problem, an
experienced employee can draw on solutions that were effective in the past, leaving them with
more regulatory resources to fully focus on the interaction with the customer. In summary,
employees whose competence need satisfaction is high can rely on automatic processing for
many work tasks, which helps them to mobilize regulatory resources when confronted with
demands and reduces the tendency to enter a resource protection mode.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 15
Third, relatedness need satisfaction helps to enhance employees’ regulatory resources,
particularly through positive experiences when working with others. High relatedness need
satisfaction entails that employees regularly experience positive social interactions at work, which
support human flourishing (Ryan & Deci, 2001). Specifically, social support at work due to high
relatedness need satisfaction may enhance employees’ regulatory resources and help them to
overcome the urge to conserve self-regulatory resources in the face of overadditive demands. For
one, employees who experience high relatedness need satisfaction benefit from the social drive of
those around them (Owens et al., 2016). That is, being able to relate to others at work is associated
with a motivational momentum, which makes it more likely to experience states of flow when
confronted with overadditive depletion of regulatory resources. To summarize, we examine the
moderating effects of autonomy, competence, and relatedness need satisfaction on the impact of
aversive commutes and impulse control demands on flow experiences and formulate the following
Hypothesis 3: Employees’ satisfaction of their general work-related needs for (a)
autonomy, (b) competence, and (c) relatedness moderates the proposed moderated
mediation model such that the moderating effect of day-specific impulse control demands
on the day-specific indirect effect of an aversive morning commute on work engagement
via flow experiences becomes weaker when the satisfaction of employees’ work-related
needs for (a) autonomy, (b) competence, and (c) relatedness is high.
Participants and Procedure
We conducted a daily diary study to test the proposed model. The data were collected in
Germany via the organizational contacts of the researchers and student assistants. The research
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 16
protocol was developed in line with the APA Ethical Principles as the organizational policies at
the authors’ institutions at the time of data collection for Study 1 did not require ethical approval
for noninvasive, survey-based research. We emailed potential participants explaining the
procedure of the study and asking them to complete an informed consent form. After employees
gave their consent, they received a pre-survey to measure demographics, general characteristics
of their work commute as well as basic needs satisfaction. At the end of this pre-survey,
participants chose 10 workdays (Monday-Friday) during the following month, on which they
commuted to work and wished to receive the day-specific surveys. These days could, but did not
have to, be consecutive. Night and shift workers were excluded from our data collection. For
each selected day, participants indicated their estimated times at which they planned to start and
finish work as well as to arrive at home after work. Subsequently, participants received three
surveys a day in alignment with their indicated times. We administered the morning survey one
hour after the start of work, the afternoon survey one hour before the end of work, and the
evening survey one hour after arriving at home. If participants did not complete a survey within
an hour after the reception, we sent a reminder. Participants had three hours to respond until the
specific survey was deactivated.
In total, 60 out of 78 contacted employees completed the pre-survey. We had to exclude
seven participants because they did not respond to any daily surveys. This resulted in a final
sample of N = 53 (overall response rate of 68%). On the day-level, the 53 participants provided
data for 411 days out of potential 530 days (53 participants x 10 days), resulting in a response
rate of 78%. Taking the demanding nature of the study and the fact that participants received no
compensation into account, our response rates of 68% on the person-level and 78% on the day-
level are satisfactory (e.g., Dumas & Perry-Smith, 2018; Menges et al., 2017). Moreover, we
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 17
examined differences in demographic characteristics between participants who completed the
initial survey and the daily surveys (N = 53) and those who only completed the initial survey (N
= 7) through t-tests. Our results indicate no significant differences in relevant demographic
characteristics between these groups (age: t = 0.44, df = 5.67, p = .67; gender: t = -0.45, df =
6.11, p = .67; distance to work: t = -1.17, df = 8.91, p = .27; commute by car: t = 0.20, df = 6.06,
p = .85; commute by public transport: t = -0.44, df = 6.35, p = .67; commute by walking or
cycling: t = 0.20, df = 5.82, p = .85).
Participants worked in various sectors (17% health, 11% banking and insurance, 11% IT
and communication, 9% education and teaching, 9% craftsmen, 6% retail, 6% public service, 6%
manufacturing, and 25% in other sectors). Their age ranged from 19 to 62 years (M = 38.00; SD
= 13.51). The rate of female participants was 57%. Participants’ distance to work ranged from 1
to 140 km (M = 19.40 km; SD = 21.86 km). Most participants commuted by car (62%), followed
by public transport (25%), and cycling and walking (13%). The average time for the commute to
work was 32.74 min (SD = 23.88 min.).
Measures and Control Variables
Basic Needs Satisfaction. We measured work-related autonomy, competence, and
relatedness needs satisfaction in the pre-survey with a 12-item scale from Chiniara and Bentein
(2016), who introduced a shortened version of the original basic needs satisfaction scale
developed by Van den Broeck et al. (2010). A research assistant translated the English original
items to German. Then the second author back-translated them to English and compared them
with the original items. If the translated version was different from the original, we searched for
a more appropriate German translation using an online dictionary and then asked a third research
assistant to translate the adapted German item to English again. This step ensured that we did not
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 18
have any discrepancies between the meaning of the German and English items. Each need was
measured with four items (e.g., autonomy: “How satisfied are you with the opportunities to take
personal initiatives in your work?”, = .92; competence: “How satisfied are you with the feeling
of being competent at doing your job?”, = .87, relatedness: “How satisfied are you with the
positive social interactions you have at work with other people?”, = .88). All items were rated
on a 5-point response scale (1 = very dissatisfied; 5 = very satisfied).
Aversive Morning Commute. We assessed aversive morning commute in the morning
with six items from the subscale developed by Novaco et al. (1990). Participants rated how they
experienced commuting to work. An exemplary item is: “Today, my commute to work was …”
“crowded (e.g., heavy traffic, crowded buses) — empty”. We used the same translation-back-
translation procedure as outlined above. All items were rated on a 5-point Likert scale with
semantic differentials (e.g., 1 = uninterrupted; 5 = stop and go; -range across days = 84 – .95).
Flow Experiences. We assessed day-specific flow experiences in the afternoon with seven
items from the German Flow Short Scale (Engeser & Rheinberg, 2008; Rheinberg et al., 2003).
Due to high cross-loadings on work engagement in our multilevel confirmatory factor analyses
(MCFAs), we removed three items from the original 10-item scale. Participants rated their flow
experiences throughout the day on a 7-point rating scale (1 = not at all; 7 = a great deal; -range
across days = .81 – .93). An example is “Today, my thoughts/activities ran fluidly and smoothly.”
Impulse Control Demands. We measured day-specific impulse control demands in the
afternoon with six items from the German self-control demands scale (Schmidt & Neubach,
2007). Participants rated the degree to which they had to control day-specific impulses during
work on a 5-point Likert rating scale (1 = not at all; 5 = a great deal; -range across days = .83 –
.93). An example item is “In the last hours, my job required me not to lose my temper”.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 19
Work Engagement. We assessed day-specific work engagement in the evening after
work with the German 9-item version (Sonnentag, 2003) of the Utrecht Work Engagement Scale
(Schaufeli et al., 2006; -range across days = .96 – .97), which was adapted for day-specific
assessment and involves three facets: vigor (e.g., “Today, I felt strong and vigorous at my
work.”), dedication (e.g., “Today, I was enthusiastic about my job.”), and absorption (e.g.,
“Today, I felt happy when I was working intensely.). The response format ranges from 1 =
strongly disagree to 6 = strongly agree. As suggested by Xanthopoulou et al. (2009), we
incorporated the three facets of work engagement into a general work engagement factor.
Control Variables. We controlled for commute time because it may influence the
likelihood of aversive commute experiences and has been linked to decreased work motivation
(VitalityHealth, 2017). Commute time was measured with one item each day in the morning (i.e.,
“How many minutes did it take you to commute to work today?”).
We conducted MCFAs to assess the psychometrical distinctness of our variables. In line
with suggestions by Dyer et al. (2005), we specified the day-level variables in our model at the
within- and the satisfaction of each basic need at the between person-level. To evaluate the
goodness of fit of our models, we used cut-off values as recommended by Hu and Bentler (1999;
root mean square error of approximation [RMSEA] =.06; comparative fit index [CFI] = .95;
standardized root mean square residual within and between [SRMRw/b] = .08). However,
because these cut-off points were derived from simulated data that do not take nested data
structures into account, a deviation from these cut-off values should not unequivocally lead to
rejecting the proposed theoretical model (Williams et al., 2020). The results of MCFAs
examining different models are presented in Table 1. In line with our theoretical propositions a
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 20
model, which distinguishes between all variables on the between (3-Factors: autonomy,
competence, and relatedness need satisfaction) and the within-person level (4-Factors: Aversive
morning commute, flow experience, impulse control demands, and work engagement) yielded a
satisfactory fit: χ2(395) = 1053.97, p < .01, RMSEA= .064, CFI = .914, SRMRw/b) = .059/.096)
and performed better than any other model in which we combined different variables into a
We published the data for Study 1 and the Mplus codes for the analysis presented in the
results section on the Open Science Framework (doi:10.17605/OSF.IO/DMVTQ). Because day-
level data were nested within person-level data, our hypotheses were tested through Multilevel
Structure Equation Modelling (MSEM; see Preacher et al., 2010) in Mplus 8.2 (Muthén &
Muthén, 1998-2012). This method allows for analyses on multiple levels and is less prone to bias
than more traditional approaches to multilevel mediation analysis (e.g., Multilevel Modelling; for
further information see Preacher et al., 2010). We examined our hypotheses by specifying a 1-1-1
moderated mediation model with random slopes (Preacher et al., 2010) and maximum likelihood
estimation with robust standard errors.
On the within-person level, we specified three random slopes, which vary across Level-2
units, for the relationships between aversive morning commute (X), impulse control demands
(W), and the interaction of aversive morning commute and impulse control demands (X*W) on
the one hand and flow experiences (M) on the other hand. Subsequently, work engagement (Y)
was predicted by aversive morning commute (X) and flow experiences (M). On the between-
person level, we specified satisfaction of each basic need (Z1, Z2, Z3) to predict both
endogenous variables (i.e., flow experiences and work engagement). Moreover, each need was
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 21
specified to predict all three random slopes. The direct effects of each cross-level moderator on
all random slopes correspond with two-way interactions of the main predictor and these variables
(X*Z and W*Z) in traditional moderation analyses (Dawson & Richter, 2006). The relation of
the satisfaction of each need with the random slope linking the interaction between aversive
morning commute and impulse control demands to flow experiences represents three-way
interaction for each need (X*W*Z).
Following Hofmann and Gavin (1998) and Ohly et al. (2010), we person-mean centered
all exogenous Level-1 variables to statistically control for potential between-person differences
related to these constructs (i.e., distance to work) by removing these from the data. Because we
use MSEM and specify flow and work engagement on both levels the variance of these variables
is decomposed into a within- and between-person part, which on the within-person level is
equivalent to person-mean centering (Preacher et al., 2010) but does not change the between-
level intercept of these variables to zero. Finally, as on the between-person level basic needs
satisfaction are highly correlated (see Table 2), we applied residual centering to orthogonalize the
items to measure the satisfaction of each need from the other two (Geldhof et al., 2013). This
procedure removes the collinearity between the satisfaction of one need to the other two needs
from the model (Geldhof et al., 2013), which also allows us to examine the unique moderating
role of each need. To avoid reintroducing multicollinearity between needs by simultaneously
examining orthogonalized variables (i.e., double orthogonalization; Geldhof et al., 2013), we
specified multiple models to test the proposed three-way interactions. Following the procedure
outlined by Geldhof et al., (2013) we applied residual centering at the item level. In Model 1, we
centered autonomy need satisfaction by regressing all items of competence and relatedness need
satisfaction on each of the items measuring autonomy need satisfaction. In Models 2 and 3 we
applied the same procedure to competence and relatedness need satisfaction. In all three models,
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 22
we also added the raw scores of those needs, which were not-residually centered. To facilitate the
interpretation of coefficients we grand mean centered all three needs (Enders & Tofighi, 2007).
Because the conventional bootstrapping method of re-sampling cannot be applied in
multilevel modeling (Preacher & Selig, 2012; Van der Leeden et al., 2008), we utilized a Monte
Carlo approach of re-sampling to estimate confidence intervals for the indirect effects to test the
proposed mediation hypotheses (Preacher & Selig, 2012). Specifically, we computed bias-
corrected 95% confidence intervals (CI) based on 20,000 re-samples using the software provided
by Preacher and Selig (2012). For testing the moderated mediation effects, we extended the above
procedure to test conditional indirect effects where the magnitude of the first-stage coefficient was
calculated at a lower (– 1 SD) and higher (+1 SD) levels of impulse control demands and basic
needs satisfaction (Koopman et al., 2016; Lanaj et al., 2014). The presence of an indirect effect is
rejected if a corresponding confidence interval does include zero (Preacher et al., 2007).
Table 2 displays descriptive statistics, internal consistencies, and correlations among all
Study 1 variables. Before testing our hypotheses, we examined the focal variables’ within- and
between-person variation. For aversive morning commute, impulse control demands, flow
experience, and work engagement the proportions of within-person variance were 69.1%, 37.2%,
42.1%, and 23.2%, respectively, justifying the application of multilevel modeling.
Table 3 shows the results of our multilevel structure equation models. Where the results
between the three tested models correspond with the results of Model 1, we will exemplary
present the results of Model 1. With regard to direct effects, our data show a negative relation
between day-specific aversive morning commute and flow experiences (γ = -.15, p < .01), and a
positive relation between flow experiences and work engagement (γ = .48, p < .01). Hypothesis 1
suggests an indirect effect of an aversive morning commute on work engagement through
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 23
reduced flow experiences. Our data supports this hypothesis as the 95% CI for the indirect effect
did not include zero (γ = -.07, p < .01; 95% CI [-.129, -.025]).
Hypothesis 2 proposes that impulse control demands moderate the indirect effect of an
aversive morning commute on work engagement through flow experiences. In support of this
hypothesis, the random slope of aversive morning commute (AC)×impulse control (IC) demands
interaction, and flow experiences was significant (γ = -.23, p = .02). To explore this within-
person interaction, we plotted the relationship at conditional values of impulse control demands
(+/–1 SD; Cohen et al., 2003). Figure 2 demonstrates that only on days when impulse control
demands are higher than a person’s average there is a significant negative relation between
aversive morning commute and flow experiences at work. To examine the proposed moderated
mediation hypothesis, we again computed the conditional indirect effects for low and high levels of
day-specific impulse control demands. In line with Hypothesis 2, the 95% CI of the indirect effect
from aversive morning commute on work engagement through flow experiences on days with high
levels of impulse control demands did not include zero (γ = -.15, p < .01; 95% CI [-.239, -.061]).
Whereas this indirect effect was not significant on days with low levels of impulse control
demands (γ = .00, p = .95; 95% CI [-.077, .068]). The difference between these conditional
indirect effects was also significant (γ = -.14, p = .02; 95% CI [-.271, -.021]).
Hypotheses 3a-c suggest basic needs satisfaction for autonomy, competence, and
relatedness as cross-level moderators of the AC×IC interaction. Accordingly, we argue that the
moderated mediation via flow experiences is weaker for individuals with high (a) autonomy, (b)
competence, and (c) relatedness needs satisfaction. Our results do not support the proposed
moderating effects for the unique effect of each need as the three-way interactions for each
residually centered need did not become significant (Model 1 - AC ICautonomy need
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 24
satisfaction (NSA): γ = .00, p = .99; Model 2 - ACIC competence need satisfaction (NSC): γ
= .20, p = .38; Model 3 - ACICrelatedness need satisfaction (NSR): γ = -.03, p = .78;). Yet, in
Models 1 and 2 where we applied residual centering to autonomy and competence need
satisfaction, the three-way interaction for the raw scores (non-residual centered) of autonomy and
competence needs satisfaction became significant (Model 1 - ACICNSC: γ = .25, p = .02;
Model 2: ACICNSCA: γ = .17, p = .03). Residual centering did not affect the results for
relatedness need satisfaction. Thus, our data did not support the proposed three-way interaction
effect for relatedness need satisfaction. In sum, comparing the results of the first two- (cf. Model 1
and 2) to the last model (cf. Model 3) indicates that the three-way interactions for autonomy or
competence need satisfaction become significant once the collinearity between these needs is
removed from the data through residually centering to one of the needs. Moreover, the fact that
three-way interactions is significant for the non-residually centered autonomy (cf. Model 2) and
competence (cf. Model 1) needs satisfaction strongly suggests that the shared variance between
person-level autonomy and competence needs satisfaction is responsible for the three-way
interaction effect. We draw this conclusion because the shared variance is still present in each non-
centered need whereas it is removed from the residually centered need.
We further examined whether the patterns of these three-way interaction effects of the non-
residually centered needs correspond with our predictions by plotting the interactions and
conducting simple slope tests (Dawson & Richter, 2006; see Figure 3). Pairwise slope difference
tests to compare the slopes for high (+1SD) and low (-1SD) levels of person-level basic needs
satisfaction and day-level impulse control demands suggest that for individuals with higher
competence (Model 1: Slope difference = -0.05, t = -0.32, p = .75) or autonomy (Model 2: Slope
difference = -0.11, t = -0.71, p = .48) need satisfaction there was no significant difference in slopes
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 25
for days with higher compared to lower day-specific impulse control demands. In contrast, for
employees who experience lower competence- (Model 1: Slope difference = -0.54, t = -2.96, p < .
01) or autonomy (Model 2: Slope difference = -0.54, t = -3.38, p < .01) need satisfaction, there was
a significant difference between slopes for days with high compared to low impulse control
We also examined the conditional indirect effects for all four combinations of needs
satisfaction (higher vs. lower) and impulse control demands (higher vs. lower). The results show
that for individuals with higher competence- or autonomy need satisfaction on days with both
higher and lower impulse control demands there was no indirect effect of an aversive morning
commute on work engagement through flow experiences (cf. Table 3). Accordingly, the
difference between conditional indirect effects for higher as compared to lower daily levels of
impulse control demands was not significant for individuals with higher competence- (Model 1:
γ = -.02, p = .74; 95% CI [-.167, .109]) or autonomy (Model 2: γ = -.05, p = .49; 95% CI [-.205, .
095]) need satisfaction.
For individuals with lower levels of competence or autonomy needs satisfaction, there
was also no significant indirect effect of an aversive morning on work engagement on days with
lower levels of impulse control demands (cf. Table 3), whereas on days with higher impulse
control demands there was a significant adverse indirect effect of an aversive morning commute
on work engagement via flow experiences (cf. Table 3). The difference between the previously
mentioned conditional indirect effects became significant for individuals with lower competence
(Model 1: γ = -.26 p < .01; 95% CI [-.432, -.093]) or lower autonomy need satisfaction (Model 2:
γ = -.26, p < .01; 95% CI [-.403, -.116]).
Finally, we calculated the amounts of variance in our endogenous variables explained by
our predictors. As traditional R2 values are not available for MSEM, we followed
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 26
recommendations by Snijders and Bosker (2012); for discussion of the validity of this approach
see also LaHuis et al., 2014). The predictors explained 40.2% of the total variance for flow
experiences and 38.5% for work engagement at the within-person level. These proportions of
explained variance do not only support the theoretical, but also practical relevance of our model.
To test the robustness of our findings, we examined the relevance of previous day
endogenous variables for our results. On the within-person level for each endogenous variable
(flow experiences and work engagement), we specified the same variable measured on the
previous day as a predictor. As our diary study involved ten workdays, we also controlled for
cyclical effects, as the repeated presentation of survey measures across time may affect
participants’ responses (Beal & Ghandour, 2011; Gabriel et al., 2019). Accordingly, we added
day, sine of day, and cosine of day to predict both endogenous variables. The results demonstrate
that the matching previous day predictors (t-1 - flow experiences and work engagement) were
significantly related to each outcome (t - flow experiences and work engagement), whereas there
were no significant cyclical effects. Notably, the inclusion of both previous-day predictors and
cyclical effects did not affect the main findings of our study.
In line with current recommendations to expand the interpretability of significance
values, we also conducted post-hoc power analyses. The results of these analyses reflect the
probability of replicating our findings (Bliese & Wang, 2020). These analyses indicate that for
the main and indirect effects of an aversive morning commute on work engagement via flow
experiences observed power was in line with recommendations of at least 80% (all t’s > 2.81;
Bliese & Wang, 2020). However, the observed power for the two-way interaction of aversive
morning commute and impulse control demands was 62.9%, while the observed power values
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 27
for the three-way interactions involving autonomy and competence needs satisfaction analyses
were 59.1% and 68.5%, respectively. These probabilities indicate a higher likelihood of detecting
the proposed direct and indirect effects in a follow-up study with the same sample size compared
to the proposed two- and three-way interaction effects.
Discussion Study 1
The results of Study 1 support a daily adverse chain of effects linking aversive morning
commutes to work engagement through flow experiences. This indirect relation was exacerbated
on days with high impulse control demands. Furthermore, we found support for the proposed
cross-level three-way interactions for autonomy and competence needs satisfaction, such that for
individuals with higher autonomy and competence needs satisfaction, flow experiences were less
impaired by the regulatory resource loss process initiated by an aversive morning commute and
exacerbated by self-control demands.
Despite its contributions, Study 1 is subject to at least four limitations, which we
addressed in a second study. First, in line with previous research on the depleting effects of pre-
work experiences (Lanaj et al., 2014; Zhou et al., 2017), our theoretical argument suggests ego
depletion as an additional mediator in our model. More specifically, we argue that an aversive
morning commute depletes regulatory resources, which makes it more difficult for employees to
experience flow. Our moderated mediation model and, in particular, the two-way interaction with
impulse control demands support this proposition. Nevertheless, in Study 1, we do not explicitly
examine regulatory resource depletion as a mediator. Despite the strong theoretical rationale for
regulatory resource depletion as the core mechanism underlying the adverse effects of aversive
morning commutes, alternative mechanisms could also be responsible for the detrimental impact
of aversive commutes. For example, the transactional model of driver stress suggests that
aversive commute experiences induce negative affective states and tension, which in turn impair
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 28
work-related outcomes (Matthews, 2002). To further disentangle the proposed mechanisms
linking aversive morning commutes to employee effectiveness, in Study 2, we tested ego
depletion after the commute as an additional mediator of the proposed relations while controlling
for negative affect and tension as potential alternative mechanisms.
Second, we separated the measurement times of our mediator flow experiences and our
outcome work engagement in Study 1, but both variables still referred to the entire workday. As
such, we did not explicitly consider that flow experiences precede work engagement. We
therefore further disentangled these relations in Study 2 by examining time-lagged relationships
between flow experiences and work-related outcomes (see Rivkin et al., 2018).
Third, while we selected work engagement as an outcome that is highly relevant for
organizational functioning (Christian et al., 2011; Halbesleben, 2010; Knight et al., 2017),
scholars in the resource-based tradition have also expressed interest in behavioral performance
outcomes (Call & Ployhart, in press). This call has also been echoed in the emerging literature on
the spillover effects of commuting on behavioral indicators of employee effectiveness
(Calderwood & Mitropoulos, 2020). To expand our contribution, we also examined in-role and
extra-role performance as additional outcomes in Study 2. Because performing well in core and
extra-role tasks at work on a given day requires self-regulatory resources (Binnewies et al., 2009)
that employees can obtain through flow experiences (Bakker et al., 2011; Kasa & Hassan, 2015),
we argue that the adverse spillover effects of aversive morning commutes should also reduce
employees’ in-role and extra-role performance (see Schaeffer et al., 1988).
To summarize, we addressed the shortcomings of Study 1 by explicitly studying ego
depletion as an additional mediator and by expanding the range of outcomes to include
behavioral indicators of employee effectiveness.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 29
Hypothesis 4: The negative day-specific relation between employees’ perceptions of an
aversive morning commute and (a) work engagement, (b) subjective performance, and
(c) OCB-I is sequentially mediated by ego depletion and flow experiences.
The fourth limitation of Study 1 concerns the three-way cross-level interactions involving
person-level general basic needs satisfaction. Whereas work-related needs satisfaction has most
typically been studied as a person-level variable that reflects traits or trait-like terms, a growing
body of research has highlighted the pivotal role of daily (within-person) fluctuations in work-
related needs satisfaction (De Gieter et al., 2018; Hewett et al., 2017; Reis et al., 2000; van Hooff
& Geurts, 2015). However, thus far, it is not clear whether it is reasonable to expect homology
between more long-term person- and more short-term day-level satisfaction of basic needs, as
person- and day-level relations can differ (Chen et al., 2005; Reis et al., 2000). More specifically,
person-level studies focus on the effects of employees’ general need fulfillment at work, whereas
day-level studies investigate daily fluctuations in need fulfillment as compared to an employees’
baseline (Reis et al., 2000).
To address the question of homology, we examined day-level basic needs satisfaction in
Study 2 as a protective factor against the joint effects of ego depletion following an aversive
morning commute and daily impulse control demands. We investigated the proposed three-way
interactions on the relation between ego depletion and flow experience rather than the link
between aversive morning commute and ego depletion (see Figure 1) because, in line with
previous research (Chong et al., in press; Lanaj et al., 2014; Tong et al., 2019), we do not expect
basic needs satisfaction to prevent the depleting effects of stressors that require self-regulation
(such as an aversive morning commute); instead, we expect that it will mitigate the impact of
resource loss processes on subsequent experiences and behaviors at work. Accordingly, our
theoretical argument suggests that high basic needs satisfaction restores employees’ regulatory
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 30
resource pools thereby interrupting the regulatory resource loss processes initiated by aversive
morning commutes and exacerbated by daily impulse control demands.
Besides testing for homologous effects, the focus on day-level needs satisfaction allowed
us to further disentangle the unique moderating effects of each need. In line with previous
evidence that indicates substantial correlations among autonomy and competence need
satisfaction at the between-person level (Van den Broeck et al., 2016), Study 1 suggests that the
common variance of autonomy and competence need satisfaction is responsible for the protective
function of those needs. However, initial evidence from within-person research on needs
satisfaction suggests that day-specific autonomy and competence need satisfaction share less
common variance as indicated by the weaker correlations of these needs on the within- as
compared to the between-person level (de Gieter et al., 2018; Ilies et al., 2017). This weaker
correlation may therefore allow us to examine whether the unique daily satisfaction of each need
can protect employee effectiveness from the regulatory resource loss process initiated by an
aversive morning commute.
First, on days when an employee’s autonomy need satisfaction is particularly high, they
may experience a satisfactory degree of freedom to do their work as they prefer and to engage in
work tasks at their own pace. These experiences enhance the employee’s regulatory resource
pools through positive feelings of agency and intrinsic motivation (Csikszentmihalyi, 1975;
Engeser & Schiepe-Tiska, 2012). Accordingly, the satisfaction of having autonomous control over
their work should reduce the depleting nature of having to cope with self-control demands when
in states of ego depletion, leaving employees’ with sufficient regulatory resources to fully engage
in work tasks, which increases the likelihood to experience flow at work on that day.
Second, on days with particularly high competence need fulfillment, employees experience
a higher degree of less effortful automatic cognitive processing as opposed to more effortful
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 31
controlled processing while working (Kaplan & Berman, 2010), which helps maintain their pool of
regulatory resources and reduce tendencies to conserve said resources. As such, regulatory
resource-draining experiences (e.g., an aversive morning commute and impulse control demands)
should not prevent an employee who experiences high daily competence need satisfaction from
engaging in challenging work tasks. Accordingly, employees may still experience peak episodes
of flow in the face of high demands on a day at which their need for competence is satisfied.
Third, on days with particularly high relatedness need satisfaction, employees experience
many fulfilling social encounters at work. We expect that the perceived social connectedness and
support on that day replenishes an employees’ regulatory resource pool (Ryan & Deci, 2001),
thus preventing them from entering a resource protection mode, which in turn helps protect their
flow experiences from having to cope with impulse control demands in a depleted state. In
contrast, on days when an already depleted employee does not feel supported by and connected
with others at work, dealing with additional demands can quickly put people in a narrow-minded
cognitive state of maladaptive affect-focused rumination (Gabriel et al., 2020) and self-
awareness (see Leary, 2005).
In sum, our theoretical arguments and empirical evidence support the proposed homology
regarding the role of person- and day-level basic needs satisfaction in our research model.
Hypothesis 5: Employees’ impulse control demands and satisfaction of their day-specific
work-related needs for (a) autonomy, (b) competence, and (c) relatedness moderate the
proposed moderated mediation model, such that the moderating effect of day-specific
impulse control demands on the day-specific indirect effect of an aversive morning
commute on work engagement, subjective performance, and OCB-I via ego depletion and
flow experiences becomes weaker when the satisfaction of employees’ day-specific needs
for (a) autonomy, (b) competence, and (c) relatedness is high.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 32
Participants and Procedure
The data collection was conducted as part of a larger study via Prolific Academic in the
UK, an online provider that offers access to participants and guarantees high-quality data (Palan
& Schitter, 2018; Peer et al., 2017). Walter et al. (2019) have shown that data collected via online
providers possess similar psychometric properties and produce criterion validity that generally
falls within the credibility intervals of existing meta-analytic results from conventionally sourced
data. Previous research has demonstrated that compared to participants recruited via other
platforms (e.g., Mechanical Turk, Crowd Flower), participants recruited via Prolific Academic
are more diverse and produce higher-quality data (Palan & Schitter, 2018; Peer et al., 2017).
The research protocol for Study 2 was approved by the Norwich Business School’s
Research Ethics Committee. First, we selected participants for Study 2 by conducting an
eligibility check. Eligible participants had to be at least 18 years old, work full-time in the UK
(no shift work), and commute to work at least four workdays between Monday and Friday during
the time of the data collection. We screened N = 211 participants, of whom N = 108 participants
were eligible. These 108 employees received a pre-survey (as in Study 1) with an informed
consent form. This pre-survey was completed by N = 98 participants. In this pre-survey, we
asked participants to estimate the times at which they started work and arrived at home on each
workday in the two weeks starting on the following Monday. Depending on the indicated times,
each participant received three surveys a day. The morning survey was administered one hour
after the start of work, the noon survey four hours after the start of work, and the evening survey
one hour after arriving at home. As in Study 1, participants received a reminder if they did not
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 33
complete a survey within an hour after receipt. After receiving each survey, participants were
given 2.5 hours to respond; thereafter, the specific survey was automatically deactivated.
Participants received compensation of £0.50 for each completed survey. In line with Gabriel and
colleagues’ (2019) recommendations to increase the response rate, we offered a conditional
monetary incentive of £10.00 if participants completed all surveys on seven out of ten days.
We excluded seven participants (from the initial N = 98 responses) who did not complete
any daily surveys. In total, N = 91 employees (84% response rate on the person-level) completed
surveys in a period of 10 days, resulting in 719 day-level data points (7.90 days per employee;
79% response rate on the day-level). While the response rate on the person-level was higher than
in Study 1, the day-level response rate was comparable. We also examined differences in relevant
demographic characteristics between participants who completed the initial survey and the daily
surveys (N = 91) and those who did not complete the daily surveys (N = 7). Our results suggest
that respondents’ were older than non-respondents (t = 3.96, df = 13.52, p < .01) and were more
likely to commute by public transport (t = 5.04, df = 90.00, p < .01); otherwise there were no
significant differences in demographic characteristics between both groups (distance to work: t =
-0.57, df = 9.12, p = .58; gender: t = 0.23, df = 6.90, p = .83; commute via car: t = 1.74, df =
7.67, p = .12; commute via walking or cycling: t = 0.07, df = 6.88, p = .94).
Participants (77 % female) worked in various sectors (17% teaching & education, 10% IT
& communication, 9% health, 9% finance & insurance, 8% construction, 7% retail, 7% public
administration, 7% science, 26% in other sectors). Their age ranged from 20 to 65 years (M =
36.70; SD = 10.42) and their distance to work from 0.5 to 61 miles (M = 9.77; SD = 10.91). Most
participants commuted by car (59%), followed by public transport (22%), and cycling and
walking (15%). The mean time of the commute to work was 31.91 min (SD = 21.27 min).
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 34
Measures and Control Variables
We used the same scales as in Study 1 to measure aversive morning commute (morning; -
range across days = .83 – .90), flow experiences (noon; -range across days = .87 – .93), impulse
control demands (noon; -range across days = .90 – .98), and work engagement (evening; -
range across days = .95 – .96). Moreover, we rephrased the items of the autonomy (noon; -
range across days = .92 – .96), competence (noon; -range across days = .86 – .96), and
relatedness (noon; -range across days = .89 - .96) need satisfaction scales so that these referred
to day-specific basic needs satisfaction.
Ego Depletion. We measured ego depletion in the morning with five items from Ciarocco
et al.’s scale (2010). Participants rated the statements in regard to how they feel right now on a 5-
point rating scale (1 = strongly disagree; 5 = strongly agree; -range across days = .94 – .96). An
example is “Right now, I feel like my willpower is gone”.
Subjective Performance. We measured day-specific subjective performance in the
evening with two items (Williams & Anderson, 1991). Participants assessed their level of
engagement in their core job activities on a 7-point Likert rating scale (1 = not at all; 7 = a great
deal; -range across days = .86 – .96). An example is “Today, I performed tasks that were
expected of me.”
OCB-I. Day-specific OCB-I was assessed in the evening with four items (Williams &
Anderson, 1991). Participants rated day-specific OCB-I on a 6-point intensity-rating scale (1 =
not at all; 6 = a great deal; -range across days = .92 – .96). An example is “Today, I helped
others at work.”
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 35
Control Variables. To demonstrate that ego depletion constitutes a dominant mechanism
that underlies the adverse effects of aversive morning commutes and to rule out alternative
explanations, we controlled for negative affect and tension in our analyses. Both constructs were
rated on 5-Point Likert scales (1 = Very slightly/not at all; 5 = Extremely) and assessed in the
morning. Negative affect was measured with six items (see Sonnentag et al., 2008) that were
based on the Positive and Negative Affect Schedule (Watson et al., 1988; -range across days = .
84 – .95). An exemplary item is “Right now, I feel upset”. Tension was measured with six items
from the Profile Mood States (Shacham, 1983; = .82 – .96). An exemplary item is “Right now,
I feel tense”. As in Study 1, we also controlled for commute time.
As in Study 1, we assessed the psychometrical distinctness of our day-level measures
with MCFAs. Since Study 2 exclusively focused on within-person relations, we specified all
variables on the within-person level (Dyer et al., 2005). As theoretically proposed, a 12-Factor
model on the within-person level in which each of our variables is represented as a distinct factor
yielded an acceptable fit (χ2 (1824) = 4430.41, p < .01, RMSEA = .045, CFI = .904, SRMRw = .
046; cf., Table 1). This model exhibited a better data fit than any alternative model in which we
specified different variables as a single factor (cf., Table 1).
We provide the data for Study 2 and Mplus codes on the website of the Open Science
Framework (doi:10.17605/OSF.IO/DMVTQ). We extended the specified MSEM in Study 1 to
examine the proposed hypotheses. First, aversive morning commute predicted ego depletion as the
first-stage mediator in our model. Moreover, flow experiences—the second-stage mediator—was
predicted by aversive morning commute and the satisfaction of all three needs on the within-person
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 36
level. The proposed moderating effects of impulse control demands, and daily satisfaction of each
basic need were examined by specifying the two-way interactions of ‘ego depletionimpulse
control demands, ego depletionbasic needs satisfaction’, and ‘impulse controlbasic needs
satisfaction’ as well as the three-way interactions (ego depletionimpulse control demandsbasic
needs satisfaction) to predict flow experiences. Finally, we specified paths from ego depletion, flow
experiences, and aversive morning commute to our outcomes work engagement, subjective
performance, and OCB-I.
As in Study 1, we applied residual centering on an item level to orthogonalize each need
from the other two needs. Accordingly, we specified three models to prevent double
orthogonalization (Geldhof et al., 2013). This means that we applied residual centering to
autonomy, competence, and relatedness need satisfaction respectively in Model 1, 2, and 3. In
each model, the raw (i.e., non-residually centered) scores of the remaining two needs were
added. To account for their potential confounding effects, we added morning commute time,
negative affect, and tension as controls to predict all endogenous variables in our model.
Following suggestions by Hofmann and Gavin (1998) and Ohly et al. (2010), we applied person-
mean centering to all exogenous variables in our model. We used the Monte Carlo approach of
re-sampling described in Study 1 to estimate the confidence intervals for the conditional indirect
effects (Preacher & Selig, 2012).
The descriptive statistics, internal consistencies, and correlations among all variables of
Study 2 are presented in Table 4.
Before testing our hypotheses, we examined the within- and between-person variation in
all study variables. The relatively high proportions of within-person variance for aversive
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 37
morning commute (60.7%), ego depletion (57.2%), flow experiences (42.4%), impulse control
demands (38.1%), autonomy (25.5%), competence (27.0%), and relatedness (22.5%) need
satisfaction, work engagement (34.0%), subjective performance (44.1%), and OCB-I (26.9%)
justify the application of multilevel analyses.
The MSEM results are presented in Table 5. As in Study 1 for the effects that do not
differ between the three models, we will exemplarily present the results of Model 1. In line with
our predictions there was a positive relationship between day-specific aversive morning
commute and ego depletion (γ = .19, p < .01), and a negative relation between ego depletion and
flow experiences (γ = -.28, p < .01) also when controlling for negative affect (γ = .01, p = .93)
and tension (γ = -.11, p = .24) as potential alternative mechanisms. Finally, flow experiences
were positively related to all three outcomes (work engagement: γ = .30; subjective performance:
γ = .19; OCB-I: γ = .14; all p’s < .01).
Hypothesis 4 suggests an indirect effect of aversive morning commute on work
engagement, subjective performance, and OCB-I through increased ego depletion and reduced
flow experiences at work. In support of Hypothesis 4 a-c, the 95% CIs for the serial mediation
through ego depletion and flow experience on all outcomes at mean levels of impulse control
demands as well as autonomy, competence, and relatedness needs satisfaction did not include
zero (cf. Table 6).
Hypothesis 5 proposes a moderated mediation in which day-specific impulse control
demands and (a) autonomy, (b) competence, and (c) relatedness need satisfaction moderate the
indirect effects of aversive morning commute on all three outcomes. Out of the proposed three-
way interactions, only the three-way interaction for residual centered competence need
satisfaction (i.e., ego depletionICNSC) was significantly related to flow experiences (Model 2:
γ = .27, p = .02), thus providing support for Hypothesis 5b but nor for Hypotheses 5a and 5c.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 38
As in Study 1, we plotted the three-way interaction to examine whether its pattern
corresponds with Hypothesis 5b and examined simple slopes as well as slope differences
(Dawson & Richter, 2006) at values of 1 SD above and below the mean for both moderators (i.e.,
impulse control demands, and competence need satisfaction). The pattern of the three-way
interaction corresponds with our proposition. More specifically, slope difference tests indicate
that there is no significant two-way interaction between ego depletion and impulse control
demands on days with high competence need satisfaction (Model 2: slope difference between
low and high impulse control demands = 0.08, t = 0.70, p = .48). In contrast, on days with low
competence need satisfaction there is a marginally significant two-way interaction between ego
depletion and impulse control demands (slope difference between low and high impulse control
demands = -0.18, t = -1.84, p = .07).
Further testing the hypothesized moderated mediation proposed in Hypothesis 5b, we
computed 95% CIs for the indirect effects for all combinations of competence need satisfaction
(high vs. low) and impulse control demands (high vs. low) on all three outcomes. Our results
indicate that for all combinations of competence need satisfaction and impulse control demands
there was an indirect effects of aversive morning commute through ego depletion and flow
experience on each outcome as indicated by all corresponding 95% CIs including zero (cf. Table
6). In support of Hypothesis 5b pairwise comparisons of the differences in conditional indirect
effects indicated that on days with high competence need satisfaction, there were no differences
in indirect effects between high and low levels of daily impulse control demands (Model 2: Work
engagement: γ = .01, p = .46; 95% CI [-.008, .019]; Model 2: Subjective performance: γ = .00, p
= .46; 95% CI [-.005, .014]; Model 2: OCB-I: γ = .00, p = .47; 95% CI [-.004, .009]) whereas on
days when competence need satisfaction was low there was a marginally significant (p < .10)
difference in indirect effects for days with high as compared to low impulse control demands for
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 39
all outcomes (work engagement: γ = -.01, p = .06; 90% CI [-.022, -.001]; subjective performance:
γ = -.01, p = .06; 90% CI [-.015, -.001]; OCB-I: γ = -.01, p = .07; 90% CI [-.012, -.001]).
Finally, the amounts of explained within-person variance for all endogenous variables in
our model were 18.4% for ego depletion, 8.9% for flow experiences, and 36.0% for work
engagement: 22.2% for subjective performance, and 7.7% for OCB-I. Thus, considering that
various influences on work-related effectiveness outcomes exist, our models still account for
relevant amounts of variability in endogenous variables.
We conducted the same additional analyses as in Study 1 to test the robustness of our
findings. First, we examined the impact of previous day dependent variables and specified the
same variable measured on the previous day as a predictor for each dependent variable on the
within-person level. Moreover, we controlled for cyclical effects by adding day, sine of the day,
and cosine of the day to predict all dependent variables. The results of these analyses
demonstrate that the respective previous day predictors were only significantly related to our
outcomes (work engagement: γ = .24, p < .01; subjective performance: γ = .19, p < .01; OCB-I: γ
= .30, p < .01). There was no evidence for cyclical effects regarding participants’ responses.
Moreover, as in Study 1, the inclusion of previous day predictors and cyclical effects did not
affect the main results.
As in Study 1, we report observed power for the proposed effects (Bliese & Wang, 2020).
For the direct effects, observed power was above 80% (all t’s > 2.81; Bliese & Wang, 2020). For
the indirect effects, observed power was above 80% when predicting work engagement (post-hoc
power = 82.3%), whereas for subjective performance (post-hoc power = 68.3%), and OCB-I
(post-hoc power = 58.4%) as outcomes observed power was below 80%. Finally, for the
interaction effect involving daily competence need satisfaction, observed power was also below
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 40
80% (post-hoc power = 64.8%). In sum, the results of Study 2 largely replicate Study 1’s
findings and observed power analyses highlight that the examined effects, for the most part,
should remain stable if examined in another study with the same sample size.
The profound knowledge of the general adverse effects of commuting on individuals and
societies has not yet been matched by an equally elaborated investigation of the mechanisms and
boundary conditions linking daily aversive morning commutes to employee effectiveness. In line
with our propositions, the results of two daily diary studies support the depletion of employees’
regulatory resources and flow experiences as focal mechanisms underlying the adverse day-
specific impacts of aversive morning commutes on motivational (work engagement) and
behavioral (in-role and extra-role behaviors) indicators of employee effectiveness. The proposed
role of regulatory resources is implied by the interaction of an aversive morning commute with
self-control demands in predicting flow experiences in Study 1 and directly supported by the
sequential mediation via ego depletion in Study 2. We further tested whether the satisfaction of
between- and within-person differences in basic needs satisfaction can protect employees against
the joint overadditive depleting effects of aversive morning commutes and self-control demands.
Our results indicate that for more general between-person differences in needs satisfaction the
common features of autonomy and competence need satisfaction protect employees’ flow
experiences and associated effectiveness from the joint depleting effects of an aversive morning
commute and self-control demands. For within-person differences, in needs satisfaction, our
research identifies that day-specific competence need satisfaction exhibits a similar protective
effect as between-person differences in autonomy and competence need satisfaction.
Our research offers several theoretical implications. First, we specify the regulatory
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 41
resource loss process that links an aversive morning commute to employee effectiveness.
Specifically, the present research contributes to a better understanding of the link between an
aversive morning commute and employee effectiveness by expanding upon the role of regulatory
resource depletion and flow experiences as underlying mechanisms. Study 1 shows that flow
experiences and work engagement are related across the whole workday. Study 2 expands these
findings by demonstrating time-lagged relations between ego depletion after an aversive
commute, flow experiences, and associated employee effectiveness. From a theoretical
perspective, these time-lagged relations are particularly relevant because they emphasize the role
of flow as both a resource-demanding (Csikszentmihalyi et al., 2005; Debus et al., 2014) and
once reached a resource-recovering psychological state. Notably, research has mostly focused on
the resource-recovering function of flow, thus leaving some room for theorizing about the
resource-demanding nature of entering states of flow (see Sonnentag et al., 2012).
Second, by conceptualizing day-specific work-related self-control demands as a
moderator of the proposed mediation model, we provide further evidence for the overadditive
effects of coping with multiple self-control related stressors before and at work (van Woerkom et
al., 2016). Previous cross-sectional studies have demonstrated that more stable work-related self-
control demands interact to predict impaired well-being (Diestel & Schmidt, 2011). Our research
extends these findings by demonstrating that akin to the interactive effects of these general self-
control demands, short-term day-specific demands on self-control exhibit similar interactive
effects and overtax employees’ regulatory resources. We develop a theoretical explanation for
these overadditive effects by integrating self-regulation and COR theory. In particular, the results
of Study 2, which demonstrate an interactive effect of ego depletion and impulse control
demands on flow experiences when daily competence need satisfaction is low, support our
theoretical reasoning that the depletion of regulatory resources is associated with the tendency to
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 42
conserve remaining regulatory resources. In turn, employees must invest regulatory resources not
only to deal with impulse control demands but also to overcome the urge to preserve regulatory
resources, which overtaxes their pools of regulatory resource and prevents flow experiences.
Thus, our research contributes to self-regulation theory by explaining why coping with multiple
self-control demands is “really bad” for employees’ regulatory resources (Diestel & Schmidt,
Third, our research also sheds light on the role of inter- and intraindividual differences in
basic needs satisfaction as buffering moderators of the interplay of ego depletion following an
aversive morning commute and self-control demands. In Study 1, we address the call for
conceptual frameworks that incorporate both day-specific and general capacities (Luthans &
Youseef, 2007). In Study 2, we test for homology across levels, thereby extending recent research
suggesting that within-person fluctuations in needs satisfaction may also play a pivotal role in
predicting employee effectiveness (e.g., De Gieter et al., 2018; Hewett et al., 2017; Reis et al.,
2000). We found support for the proposed three-way interactions of person- and day-level
competence need satisfaction in both studies. As such, our findings particularly highlight the
importance of competence need satisfaction as a general and a day-specific motivating contingency
that can protect employees from the joint overadditive effects of ego depletion through an aversive
morning commute and self-control demands. These findings strongly correspond with the
theoretical notion and empirical evidence that the challenge-skill balance of an activity is a crucial
determinant for experiencing flow (Fong et al., 2015). This balance is also a crucial characteristic
of high competence need satisfaction (Van den Broeck et al., 2010). Thus, the theoretical match of
competence need satisfaction as a moderator with flow as an outcome of the proposed three-way
interaction may explain the consistent moderating effects of competence needs satisfaction across
levels found in both studies (see also De Jonge & Dorman, 2006).
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 43
Study 1 also supported the moderating effect of person-level autonomy need satisfaction,
whereas there was no corresponding effect in Study 2. However, our findings also indicate that not
the unique proportions of variance of autonomy or competence needs satisfaction (i.e., obtained
through orthogonalizing each need from the remaining two needs) accounts for the proposed
buffering effect but rather the shared variance among the autonomy and competence needs
satisfaction variables. This interpretation is also supported by the corresponding patterns of the
three-way interaction effects for autonomy and competence needs satisfaction in Study 1 as well
as the fact that these interaction effects only become significant once the collinearity between
these needs is removed from the model through residual centering. In other words, the protective
function of both needs results from the high overlap of these needs on the between-person level.
The differential evidence for the three-way interaction of autonomy need satisfaction on the
between- as compared to the within-person level highlights that despite convincing theoretical
arguments for homologous effects, it is still important to empirically test such effects (Chen et al.,
2005). A theoretical explanation for the relative importance of general rather than short-term day-
specific autonomy need satisfaction could lie in the ambivalent resource-related role of autonomy
satisfaction on the day-level. A high level of daily autonomy need satisfaction means that
compared to the employee’s mean level of autonomy need satisfaction, an employee feels more
autonomous at work on that day. This above-average level of autonomy entails that the employee
may not have automatic scripts for deciding how to work on that day, meaning they need to make
conscious decisions to organize, and implement tasks. Accordingly, they may not benefit from
additional regulatory resources provided by autonomy need satisfaction. A high level of general
autonomy need satisfaction, in contrast, means that employees regularly perceive they can do their
work the way they deem best, thus allowing them to develop automated scripts for making most
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 44
use of the autonomy they have. Hence, they make better use of the autonomy to conduct their work
with self-developed routines that they feel work best for their resource levels, thus leaving them
with a more fueled resource pool than their counterparts who experience less autonomy need
satisfaction. This argument is supported by theorizing on the double meaning of job control which
outlines that high control is only beneficial for those who can handle it (Meier et al., 2008).
Neither person- nor day-level relatedness need satisfaction moderated the proposed
relationships. This points to a higher relevance of cognitive aspects of motivation rather than a
more general resource recovering function of basic needs satisfaction for experiencing flow at
work in the face of demands that deplete regulatory resources. In line with this notion, cognitive
evaluation theory—a sub-theory of self-determination theory (Deci & Ryan, 1985)—has focused
on autonomy and competence needs satisfaction as key psychological constructs to explain why
some people find it easier to experience flow (Abuhamdeh, 2012; Kowal & Fortier, 1999). It is
conceivable, however, that the protecting role of relatedness need satisfaction in the face of
overadditive demands for experiencing flow foremost applies in situations where work involves
social interactions (e.g., teamwork, customer contact). Accordingly, the three-way interaction for
relatedness need satisfaction may be more likely to manifest in environments in which work
requires interacting with others. As our study did not account for this contextual variable, future
theorizing may consider it to clarify the motivational function of relatedness need satisfaction.
Limitations and Future Research
This research is not without limitations that may inform future research. First, our
findings may have been influenced by the studies’ context. The conditions of commuting in
Germany and the UK are comparable to many countries in Europe and North America, implying
that our results may be generalizable to these regions. However, while most commuters in the US
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 45
(Desjardins, 2018) and in Germany (Federal Statistical Office Germany, 2017) take less than 30
minutes to commute from home to work, conditions are more challenging in many Asian
countries. For example, the average commuting time in Beijing (China) is 52 minutes (World
Economic Forum, 2017). Future research could investigate whether more challenging journeys to
work are associated with even stronger impaired employee effectiveness. Relatedly, ethnicity
(which we did not assess) and cultural norms for commuting may also influence these effects.
Second, we did not sample enough active commuters who cycled or walked to work to
compare the motivational consequences of different types of commuting. Adam et al.’s research
(2018) suggests that active commuting is more enjoyable than passive commuting (e.g., driving by
car, going by public transport). Furthermore, evidence from multi-wave studies suggests that active
commuting is less resource depleting and may even restore resources (Martin et al., 2014) and that
it has positive effects on physiological fitness (Blond et al., 2019). Yet, to our knowledge, no diary
study has so far investigated whether the mode of transport influences perceptions of day-specific
commutes and how this in turn relates to employees’ motivational states and behaviors. Exploring
the unique effects of active versus passive commuting, a future within-person field experiment
(Michiels & Onghena, 2019) may ask people to switch between active and passive modes of
transport on different days. Relatedly, future research could explore the impact of teleworking,
which renders commuting obsolete, on employees’ day-specific flow experiences and associated
effectiveness. In fact, the COVID-19 pandemic has forced many employees to suddenly work from
home and stop commuting. We hope to see research that compares this exogenously induced “no-
commute” situation with the subsequent situation (i.e., people commuting to work again). On the
one hand, initial evidence indicates that no commute is not a satisfying solution either (Humagain
& Singleton, 2020), as it makes it more difficult for people to separate home and work
(Jachimowicz et al., in press). On the other hand, commuting in the context of the COVID-19
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 46
pandemic may be even more depleting, as it is associated with additional self-control demands
(e.g., wearing a mask, inhibiting the urge to touch one’s face, controlling impulsive reactions
toward others who are not adhering to social distancing guidelines). To conclude, disentangling the
commute experience is a promising area for future research (Calderwood & Mitropoulos, 2020).
Third, to avoid additional confounding factors, we did not include shift workers in our
studies. However, commuting at variable times (i.e., due to varying shift work) may be an
additional contingency that warrants further investigation. As we initially outline, due to its
recurring nature, for most employees commuting predominantly relies on automatic cognitive
processing (Elfering et al., 2013), which is efficient in its consumption of regulatory resources
(Baumeister et al., 2000). Indeed, transportation research (e.g., Chang & Mahmassani, 1988;
Mahmassani, 1990; Mahmassani & Tong, 1986) shows that individuals gain experience with
their route to work and become experts at estimating the best departure time with the goal to
arrive on time (i.e., neither too early nor too late). However, commuting at different times should
prevent forming commuting habits and an accurate estimation of optimal commuting times is
much more difficult for shift workers because their commuting time varies (Nogland & Small,
1995). The commute of shift as compared to non-shift workers thus requires more controlled
cognitive processing such as planning, monitoring the progress, and adapting the commute if
necessary. To summarize, diving deeper into unusual commuting times could be a valuable
extension of our model.
Lastly, a promising endeavor would be to extend our conceptual framework by zooming
into positive commute experiences. Similar to the argument in the positive and negative
affectivity literature (Cropanzano et al., 2003; Watson et al., 1999), the absence of a negative
commute experience does not equal a positive commute experience. The latter refers to a
stimulating activity that can come into place, for example, through inspiring conversations with
one’s co-workers on the way to work or by transitioning into one’s work role by planning the
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 47
workday (Jachimowicz et al., in press). Such positive commute experiences may help maintain
and expand regulatory resources, thereby facilitating flow experiences at work.
First, our research highlights that for organizations the time is ripe to stop externalizing
the costs of aversive morning commutes to individual employees or societies, but instead to
explore new ways on how to reduce the negative consequences of aversive morning commutes.
Organizationally determined work schedules can dictate the time frames during which employees
must commute, thus making it difficult to optimize departure times to avoid high congestion
(Nogland & Small, 1995). In other words, commuting is heavily determined by organizational
practices (e.g., static work schedules) that often increase the likelihood of encountering
unfavorable external circumstances (e.g., commuting during rush hours). An immediate
intervention could be to reduce the aversiveness of the commute experience by providing
flexible work schedules. This would allow employees to travel off-peak and has been associated
with improved physical and mental health as well as higher productivity (VitalityHealth, 2017).
Second, organizations might consider that high competence need satisfaction protects
employees from the joint adverse consequences of an aversive morning commute and self-
control demands. Thus, a reasonable implication is to increase employees’ general, as well as
daily competence need satisfaction. Promising approaches to improve general levels of
competence need satisfaction are, for example, interventions to enhance employees' work-related
skills (Ryan & Deci, in press) or to equip them with strategies to increase their perceived
competence despite high work demands (Weigelt et al., 2018). On a daily level, managers with a
good knowledge of their employees’ skillsets could assign tasks appropriate for their employees’
skill levels and offer support for challenging work tasks (Van den Broeck et al., 2016).
Third, turning to a broader level of policy implications, governments can play a pivotal role
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 48
in reducing aversive commute experiences. Since delays are among the most prevalent aversive
commute experiences (Gatersleben & Uzzell, 2007), investments in infrastructure (e.g., intelligent
traffic lights, automatic speed limits) and public transport (e.g., more trains, networks optimized by
machine learning approaches) could reduce aversive commutes. Further, policy decisions can help
change people’s preferred ways of commuting, thus leading to a potentially more balanced
capacity utilization. For example, research has shown that investment in safe cycling lanes
increases the number of people who cycle to work (Pucher & Buehler, 2017).
Finally, societal beliefs and norms about work-/life spaces also play a role in determining
how we commute. For many decades, architects separated the space for work, life, and recreation
(De Jong & Schuilenburg, 2006). While this improved unhygienic living conditions in the past,
today’s higher production standards have made this function obsolete in many countries. Instead,
increases in property prices in city centers cause both employees and organizations to move to
more rural areas increasing commuting duration (Ingraham, 2017; Zhu et al., 2017). Rethinking
the integration of work and life spheres is thus a question for our communities and policymakers
alike. In that regard, it is possible that the recent shift toward “working from home” due to the
COVID-19 pandemic results in a reconsideration of how we separate work and life.
Although commuting is an everyday experience for everyone who works outside the
home, its dynamic nature and implications for daily life in organizations have been largely
overlooked. We provided a conceptual framework outlining the motivational consequences of an
aversive commute from a self-regulatory resource perspective and explored work-related basic
needs satisfaction as resilience factors against its adverse effects. We hope that our work inspires
scholars and practitioners alike to engage in a constructive dialogue to help employees to
smoothly flow to work so that they can experience more flow at work.
NEGATIVE EFFECTS OF MORNING COMMUTES: HOW AND WHEN 49
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Table 1. MCFA Results (Study 1 and Study 2)
Note. df = Degrees of freedom, RMSEA= Root Mean Square Error of Approximation, CFI = comparative fit index, SRMR = Standardized Root Mean Square
Residual, S-B = Satorra-Bentler
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Table 2. Means, Standard Deviations, and Intercorrelations (Study 1)
Note. aGender (1 = female, 2 = male). bLeadership position (1 = yes, 2 = no). Correlations below the diagonal represent person-level correlations (N = 53).
Correlations above the diagonal are day-level correlations (N = 411). Person-level variables in italic. Numbers in bold p < .05.
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Table 3. MSEM Results and Within-Person Conditional Indirect Effects of Aversive Morning Commute via Flow Experiences on Work Engagement (Study 1)
Note. Nbetween = 53; Nwithin = 411; SE = standard error; LLCI = lower-level confidence interval (95%); ULCI = upper-level confidence interval (95%). In each model,
all effects were included simultaneously to predict flow experiences and work engagement. Confidence intervals, which do not include zero, are marked in bold;
95% confidence intervals for parameter estimates of the direct effects are available upon request.
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Table 4. Means, Standard Deviations, and Intercorrelations (Study 2)
Note. aGender (1 = female, 2 = male). bLeadership position (1 = yes, 2 = no). Correlations below the diagonal are person-level correlations (N = 91).
Correlations above the diagonal are day-level correlations (N = 719). Person-level variables in italic. Numbers in bold p < .05.
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Table 5. MSEM Results (Study 2)
Note. SE = standard error; Nbetween = 91; Nwithin = 719. In each model, all effects were included simultaneously to predict all endogenous variables. In Model 1
residual centering was applied to autonomy need satisfaction, in Model 2 to competence need satisfaction and in Model 3 to relatedness need satisfaction.
Except for the estimates predicting flow experiences, all other estimates were identical across all three tested models. 95% confidence intervals for parameter
estimates of the direct effects are available upon request.
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Table 6. Within-Person Conditional Indirect Effects of Aversive Morning Commute via Ego Depletion and Flow Experience on Work Engagement, Subjective
Performance, and OCB-I (Study 2).
Note. SE = standard error; LLCI = lower-level confidence interval (95%); ULCI = upper-level confidence interval (95%); Confidence intervals are calculated
using the Monte Carlo method for assessing mediation (MacKinnon et al., 2004); Confidence intervals which do not include zero are depicted in bold.
Figure 1. Conceptual Model
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Note. Dashed lines depict indirect effects.
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Figure 2. Within-Person Interaction Effect of Aversive Morning Commute and Impulse Control Demands on Flow Experience at Work (Study 1).
Note. The plot is based on the results of Model 1 and does not differ across all three models.
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Figure 3. Cross-Level Three-Way-Interaction Effects of Aversive Morning Commute, Impulse Control Demands, and Basic Need Satisfaction for (a) Autonomy and
(b) Competence on Flow Experience (Study 1)
Note. For the three-way interaction involving autonomy need satisfaction (a) plots are based on the results of Model 2 and for the three-way interaction
involving competence need satisfaction (b) plots are based on the results of Model 1.
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Figure 4. Within-Person Three-Way-Interaction Effect of Ego Depletion, Impulse Control Demands, and Basic Need Satisfaction - Competence on Flow
Experience (Study 2)
Note. The plot is based on the results of Model 2.