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A Social Mindfulness Approach to Understanding Experienced Customer Mistreatment: A Within-Person Field Experiment
Journal: Academy of Management Journal
Manuscript ID AMJ-2016-0448.R3
Manuscript Type: Revision
Keywords:
Stress, strain, and well-being < Attitudes, Cognitions, and Affect < Organizational Behavior < Topic Areas, Mood and emotions < Attitudes, Cognitions, and Affect < Organizational Behavior < Topic Areas, Field experiment < Quantitative Orientation < Research Methods
Abstract:
We apply a social mindfulness lens (Van Doesum, Van Lange, & Van Lange, 2013) to understand the phenomenon of perceived customer mistreatment. Recognizing that both recall of prosocial acts and perspective taking invoke the motivation to be mindful in social
interactions, we investigated whether these two types of interventions affect customer service employees’ experience of customer mistreatment. Additionally, we investigated whether these two interventions might also buffer the relation of employees’ daily experience of customer mistreatment and their negative mood at the end of the workday. Finally, we examined whether the interventions, via their effects on daily experience of customer mistreatment and afternoon negative mood, could reduce dysfunctional coping responses in the evening (i.e., employee rumination and maladaptive shopping). We conducted a within-person field experiment utilizing a daily experience sampling approach with 94 customer service employees whom we surveyed for 15 consecutive workdays. Consistent with our expectations, both interventions significantly
reduced the daily experience of customer mistreatment compared to a control condition. Recall of prosocial action also significantly buffered the positive relation of daily experience of customer mistreatment with afternoon negative mood. Moreover, both interventions had significant indirect effects on dysfunctional coping responses in the evening. We discuss theoretical and practical implications of these findings.
Academy of Management Journal
1
A Social Mindfulness Approach to Understanding Experienced
Customer Mistreatment: A Within-person Field Experiment
YIFAN SONG
University of Florida
Stuzin Hall, P.O. Box 117165
Gainesville, FL 32611-7165
YIHAO LIU
University of Illinois at Urbana-Champaign
504 E. Armory Avenue
Champaign, IL 61820
MO WANG
University of Florida
Stuzin Hall, P.O. Box 117165
Gainesville, FL 32611-7165
KLODIANAN LANAJ
University of Florida
Stuzin Hall, P.O. Box 117165
Gainesville, FL 32611-7165
RUSSELL E. JOHNSON
Michigan State University
632 Bogue St., Office N438
East Lansing, MI 48824-1121
JUNQI SHI (corresponding author)
Sun Yat-sen University
Lingnan College
Guangzhou, 510275
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A SOCIAL MINDFULNESS APPROACH TO UNDERSTANDING
EXPERIENCED CUSTOMER MISTREATMENT:
A WITHIN-PERSON FIELD EXPERIMENT
ABSTRACT
We apply a social mindfulness lens (Van Doesum, Van Lange, & Van Lange, 2013) to
understand the phenomenon of perceived customer mistreatment. Recognizing that both recall of
prosocial acts and perspective taking invoke the motivation to be mindful in social interactions,
we investigated whether these two types of interventions affect customer service employees’
experience of customer mistreatment. Additionally, we investigated whether these two
interventions might also buffer the relation of employees’ daily experience of customer
mistreatment and their negative mood at the end of the workday. Finally, we examined whether
the interventions, via their effects on daily experience of customer mistreatment and afternoon
negative mood, could reduce dysfunctional coping responses in the evening (i.e., employee
rumination and maladaptive shopping). We conducted a within-person field experiment utilizing
a daily experience sampling approach with 94 customer service employees whom we surveyed
for 15 consecutive workdays. Consistent with our expectations, both interventions significantly
reduced the daily experience of customer mistreatment compared to a control condition. Recall
of prosocial action also significantly buffered the positive relation of daily experience of
customer mistreatment with afternoon negative mood. Moreover, both interventions had
significant indirect effects on dysfunctional coping responses in the evening. We discuss
theoretical and practical implications of these findings.
Keywords: Social mindfulness; Customer mistreatment; Prosocial motivation; Perspective
taking; Negative mood; Rumination; Maladaptive shopping
Given the significant growth of the service economy over the past decades, interest in
improving frontline service employees’ performance and well-being has increased (Groth &
Goodwin, 2011). One topic related to service employees’ performance and well-being that has
received extensive attention is customer mistreatment, which is defined as low-quality
interpersonal treatment that employees receive from customers (Wang, Liao, Zhan, & Shi, 2011).
Numerous studies have documented negative effects of customer mistreatment on service
employees. For example, customer mistreatment has been shown to negatively influence service
employees’ cognition, such as impairing their working memory (e.g., Rafaeli, Erez, Ravid,
Derfler-Rozin, Treister, & Scheyer, 2012) and threatening their self-efficacy (e.g., Dormann &
Zapf, 2004), which in turn results in lower performance (e.g., Choi, Kim, Lee, & Lee, 2014;
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Goldberg & Grandey, 2007) or even increasing customer-directed sabotage (e.g., Skarlicki, van
Jaarsveld, Shao, Song, & Wang, 2016; Skarlicki, van Jaarsveld, & Walker, 2008; Wang et al.,
2011). To make matters worse, customer mistreatment may also culminate in poor employee
physical health (e.g., Sliter, Pui, Sliter, & Jex, 2011), negative emotions (e.g., Rupp & Spencer,
2006; Zapata-Phelan, Colquitt, Scott, & Livingston, 2009), and exhaustion (e.g., Grandey,
Dickter, & Sin, 2004; Zhan, Wang, & Shi, 2016).
Although not explicitly stated, most studies assume that employees’ subjective
experience of customer mistreatment is a true reflection of actual customer mistreatment
behaviors. The experience of customer mistreatment, however, is based on complex perceptual
and evaluative judgments that may vary substantially within and across people (e.g., Skarlicki et
al., 2008). Given the inherently subjective nature of experienced customer mistreatment (Bies,
2001) and the relevance of employees’ own perceptions at work, the current study focuses on
understanding employees’ subjective experience of customer mistreatment. Our emphasis on
employees’ subjective experience of mistreatment is aligned with the original conceptualization
of customer mistreatment from Bies (2001) as a type of interactional injustice experience, which
by nature involves “perceptions” and “judgements”.
Furthermore, the well-documented associations between employees’ experience of
customer mistreatment and subsequent negative consequences also beg for studies that provide
insights on how to reduce subjective experiences of customer mistreatment and its concomitant
outcomes. Although previous studies have identified various personal characteristics (e.g., moral
identity, Skarlicki et al., 2008; negative affectivity, Walker, van Jaarsveld, & Skarlicki, 2014)
and contextual variables (e.g., perceived organization support, Wang, Liu, Liao, Gong,
Kammeyer-Mueller, & Shi, 2013; organizational climate of support, Shih, Lie, Klein, & Jiang,
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2014) that buffer the negative effects of customer mistreatment, it would be especially useful to
learn what could be done to reduce the experience of customer mistreatment in the first place.
We aim to address the above-mentioned issues by integrating a social mindfulness
framework (Van Doesum, Van Lange, & Van Lange, 2013) with motivated information
processing theory (Kunda, 1990; Salancik & Pfeffer, 1978) to better understand how experienced
costumer mistreatment affects employees. A social mindfulness framework is particularly
relevant to our work because it recognizes the importance of other-orientedness in social
interactions by highlighting the need to both “see” others’ perspectives and “do” prosocial acts
for others (Van Doesum et al., 2013: 86). We capture social mindfulness’ aspects of seeing and
doing with perspective taking and recall of prosocial acts, respectively, because these are
intricately related to other-orientedness and key drivers of prosocial orientation (Batson, Sager,
Garst, Kang, Rubchinsky, & Dawson, 1997; Grant & Dutton, 2012; Van Doesum et al., 2013).
Furthermore, the social mindfulness framework is particularly well-aligned with customer
service contexts such as ours where managing distressed customers while protecting one’s own
well-being are equally important goals for employees (e.g., Groth & Grandey, 2012; Koopmann,
Wang, Liu, & Song, 2015).1
Whereas the social mindfulness framework speaks more directly to why perspective
taking and prosocial recall as forms of other-orientedness matter in social interactions, motivated
information processing theory (Kunda, 1990; Salancik & Pfeffer, 1978) speaks to how such
prosocial orientation can shape the way employees process and interpret other people’s behaviors
in interdependent contexts (e.g., Dutton, Workman, & Hardin, 2014; Grant & Sumanth, 2009).
According to motivated information processing theory, employees’ motivation shapes how they
1 Consistent with recent research, our theorizing does not assume that being other-oriented (e.g., showing concern
for customers) precludes the possibility of self-interest (e.g., protecting employees’ own well-being) (e.g., Bolino &
Grant, 2016; Grant & Berry, 2011).
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attend to and process information, interactions, and contextual cues (Kunda, 1990; Salancik &
Pfeffer, 1978). This theory suggests that – as the two primary ways of evoking prosocial
motivation (Grant & Dutton, 2012; Maner, Lucer, Neuberg, Ciadini, Brown, & Sagarin, 2012;
Stocks, Lishner, & Decker, 2009; Tasimi & Young, 2016; Van Lange, 2008; Young, Chakroff,
& Tom, 2012) – perspective taking and prosocial recall are likely to shape employees’
experience of customer mistreatment. Employees exposed to the two prosocial interventions are
likely to notice, encode, and retain information that is consistent with their prosocial motives and
downplay information that is inconsistent with these motives in ways that impact their
subsequent perceptions and behaviors.
Consistent with information processing theory, a related goal of our research is to
investigate whether these two prosocial interventions buffer the relationship between service
employees’ experience of customer mistreatment and negative affective reactions. Work events
are proximal causes of people’s affective reactions (Weiss & Cropanzano, 1996) and appraisal
processes of events play a critical role in determining such reactions (Lazarus, 1991).
Specifically, an event first triggers a primary appraisal process that evaluates whether the event
is goal-relevant. This initial appraisal is followed by a secondary appraisal process that evaluates
the expected consequences of the event, which shape people’s emotional reactions. According to
motivated information processing theory, customer mistreatment experiences will be appraised
as less negative when employees are exposed to the prosocial interventions (e.g., Brewer, 2012;
Van Doesum et al., 2013). For these reasons, we expect that the two prosocial interventions will
protect employees’ mood from being severely harmed by experienced customer mistreatment.
The current study also aims to enrich the customer mistreatment literature by extending
the criterion space of service employees’ customer mistreatment experience. Specifically, we
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examine two self-focused maladaptive emotion regulation strategies that are intended to reduce
people’s negative emotion reactions, namely rumination and maladaptive shopping (e.g.,
LeMoult, Arditte, D’Avanzato, & Joormann, 2013; Saintives & Lunardo, 2016; Tice &
Bratslavsky, 2000). Rumination represents a psychological indicator and maladaptive shopping a
behavioral indicator of employees’ self-focused and maladaptive reactions to customer
mistreatment. Examining these two variables extends the range of after-work spillover outcomes
of work-related experiences (e.g., Barnes & Wagner, 2009; Frone, 2008; Liu, Wang, Bamberger,
Shi, & Bacharach, 2015), and aligns well with our purpose of investigating the effectiveness of
other-oriented interventions that reduce the detrimental effects of customer mistreatment
experiences. Because rumination and maladaptive shopping are self-focused strategies for coping
with negative emotions, using other-oriented interventions to shift employees’ attention from the
self to others may prove especially effective for mitigating the emotion-based costs of customer
mistreatment. The model we propose and test is illustrated in Figure 1.
Taken together, the current study offers several key contributions. First, integrating the
social mindfulness framework with motivated information processing theory, the current study
sheds light on the subjective processes involved in service employees’ experience of customer
mistreatment. Second, our focus on prosocial orientation as captured by perspective taking and
prosocial recall introduces a potentially valuable theoretical lens for understanding the benefits
of other-oriented processes involved in service employees’ interaction with customers. Third, the
current study not only furthers our theoretical understanding of the social information processing
mechanisms underlying employees’ experience of customer mistreatment, but also identifies
feasible means for leveraging these theoretical insights for practice. Similar to other intervention
studies in the field of organizational behavior (e.g., Bono, Glomb, Shen, Kim, & Koch, 2013),
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we provide examples of actionable steps that can be taken to protect employees from suffering
the detrimental consequences of negative work experiences. Finally, to ensure generalizability
and ecological validity, we utilized a within-person field experiment design and implemented
daily interventions among a sample of customer service employees. In doing so, we address the
call for employing experimental designs in field settings to simultaneously strengthen internal
and external validity (Shadish, Cook, & Campbell, 2002).
THEORETICAL BACKGROUND AND HYPOTHESIS DEVELOPMENT
Social Mindfulness Framework
The social mindfulness framework posits that motivation and ability to be socially
mindful enable individuals to pay attention to the needs and interests of others in social
interactions (Brewer, 2012; Van Doesum et al., 2013). Customer mistreatment is a prevalent
daily phenomenon in customer service contexts (Wang et al., 2011). For this reason, we focus on
motivation to be socially mindful rather than on ability because ability is less malleable at the
day level (e.g., Decety & Batson, 2007), and may take time to develop (e.g., Allen, Fonagy, &
Bateman, 2008). Our approach is consistent with dual-process studies that focus either only on
motivation effects or only on ability effects even though both may be relevant in a particular
context (e.g., Bless & Schwarz, 1999; Chaiken & Trope, 1999). Based on the social mindfulness
framework, we expect that how employees experience and react to customer mistreatment is
determined in part by their prosocial orientation, which we manipulate via recall of prosocial
action and perspective taking interventions.
The social mindfulness framework posits that to be mindful of others means to both see
others’ needs and to act in ways that help others, which are well captured by perspective taking
and prosocial recall, respectively (Van Doesum et al., 2013). Both interventions enable a focus
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on the needs and interests of others and are the two fundamental types of other-oriented
interventions utilized in the prosocial literature (e.g., Dutton et al., 2014; Gilin, Maddux,
Carpenter, & Galinsky, 2013). Furthermore, both interventions afford participants psychological
and behavioral benefits, such as reduced interpersonal biases and increased social capital via the
performance of other-oriented behaviors (e.g., Grant & Dutton, 2012; Ku, Wang, & Galinsky,
2015), and are likely to have implications for how employees perceive as well as respond to
mistreatment from their customers.
Recall of Prosocial Action
People who exhibit the motivation to act prosocially tend to focus on protecting and
promoting others’ welfare (e.g., Grant, 2007; Kim, Van Dyne, Kamdar, & Johnson, 2013). Given
that service employees’ work largely requires them to attend to and care about customers’ needs
and to help meet customers’ demands, we expect that asking service employees’ to recall a time
when they were prosocial may influence how employees interpret customers’ behaviors that
could otherwise be construed as aggressive or unreasonable. This is because recalling a time
when one was socially mindful of others triggers empathetic interests and concerns that are
aligned with the needs of their interaction partners (Bolino, Harvey, & Bachrach, 2012). When
employees recall a time when they were prosocial and mindful of the needs and interests of
others, they are likely to subsequently interpret customers’ mistreatment behaviors as a signal for
needing help, rather than norm-violating interpersonal treatment towards them. Additionally,
activating prosocial motivation can lead people to engage in context-dependent processing, such
that they pay greater attention to social cues and consider situational variance in the actions of
others (Kühnen & Oyserman, 2002). A consequence of such processing is that employees will
empathize with customers and attribute any perceived mistreatment from them to unfortunate
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circumstances that customers experienced. Such attributions reduce the perception and potency
of mistreatment behavior.
Based on the arguments above, we expect that an intervention which activates employees’
motivation to be socially mindful will subsequently reduce their subjective experience of
customer mistreatment. Recalling past prosocial actions can remind individuals that they are
prosocially motivated (Conway & Peetz, 2012), and is also likely to initiate a self-verification
process by which individuals tend to regulate their behavior in ways that are consistent with their
other-oriented tendencies in the past (Burke, 1991; Mayfield & Taber, 2009; Swann, 1983).
Indeed, research suggests that when prosocial activities are recalled, people become more
committed to helping (Farmer & Van Dyne, 2010; Nelson & Norton, 2005) and may pay less
attention to negative interpersonal events that contradict their other-orientedness, such as
customer mistreatment. Thus, since recalling a prosocial action activates service employees’
motivation to be socially mindful of others, we expect that it will reduce their subjective
experience of customer mistreatment:
Hypothesis 1: On days when employees receive the recall of prosocial action intervention
in the morning, they will perceive less daily customer mistreatment compared to when
they do not receive any intervention.
Moderating Effect of the Recall of Prosocial Action
Although the motivation to be socially mindful may lessen the customer mistreatment
experience, it is unlikely to completely eliminate such experience. Therefore, we further propose
that the motivation to be socially mindful may also buffer the relation of such mistreatment
experience with service employees’ subsequent negative mood. Work events elicit proximal
affective reactions, which in turn shape distal attitudes and behaviors (Weiss & Cropanzano,
1996). Two appraisal processes (i.e., primary appraisal and secondary appraisal) are involved in
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the generation of emotional reactions to work events (Lam & Chen, 2012; Weiss & Cropanzano,
1996). Upon receipt of customer mistreatment, employees are likely to experience negative
emotions if the mistreatment is appraised as personally relevant (primary appraisal) and yields
negative consequences (secondary appraisal; Dormann & Zapf, 2004). Many empirical studies
report positive relations of experienced customer mistreatment with negative emotional reactions.
For example, customer mistreatment is linked to anger (e.g., Rupp & Spencer, 2008; Spencer &
Rupp, 2009), anxiety (e.g., Wegge, Van Dick, & von Bernstorff, 2010; Zhan, Wang, & Shi,
2013), and general negative emotions (e.g., Groth & Grandey, 2012; Volmer, Binnewies,
Sonnentag, & Niessen, 2012). Therefore, in line with existing empirical evidence, we expect that
daily customer mistreatment will be positively related to afternoon negative mood.
Building on our framework of social mindfulness, we expect that the recall of prosocial
action intervention will buffer the positive relationship between customer mistreatment and
afternoon negative mood. This is because when individuals are motivated to help others, they
will show more understanding when interpreting others’ behaviors (Reed & Aquino, 2003).
Owing to the context-dependent processing associated with an activated prosocial motivation
(Kühnen & Oyserman, 2002), customer mistreatment is unlikely to be interpreted as personally
targeting the employee. Instead, such mistreatment will likely be interpreted in terms of the
broader context and attributed to unfavorable circumstances, thus reducing its emotional potency.
Therefore, we expect that with the recall of prosocial action intervention, employees will be less
likely to experience negative mood elicited by customer mistreatment:
Hypothesis 2: Recall of prosocial action intervention will moderate the positive relation
of daily perceived customer mistreatment with afternoon negative mood, such that this
relation will be weaker on days when employees receive the recall of prosocial action
intervention in the morning compared to days when there is no intervention.
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Perspective Taking
One of the main ways to be socially mindful of others is to try and take their perspective.
Thus, apart from recalling past prosocial behaviors, prosocial motivation can also be activated by
taking others’ perspective (Baston et al., 1997). Indeed, a number of studies have revealed that
imagining how one would feel in another person’s situation evokes individuals’ empathic
concern and motivates people to help others (Batson et al., 1997; Batson, Chang, Orr, &
Rowland, 2002; Galinsky, Ku, & Wang, 2005; Van Lange, 2008). Building on motivated
information processing theory, we expect that the perspective taking intervention will motivate
service employees to attend, encode, process, and subsequently react to customer behaviors in
ways that are consistent with their prosocial orientation.
Perspective taking can prompt service employees to show more empathic concern to
customers and provide more satisfying customer service, which may result in reduced customer
mistreatment experiences. That is, taking customers’ perspective may motivate employees to
consider customers’ needs and welfare as more personally relevant and meaningful (Parker &
Axtell, 2001) and attach more importance to solving customers’ problems (Axtell, Parker,
Holman, & Totterdell, 2007). As a result, perspective taking likely enhances employees’ service
performance, thus reducing customers’ dissatisfaction with the service quality and customers’
mistreatment behaviors.
Further, the prosocial motivation evoked by taking customers’ perspective may also
prompt service employees to perceive and interpret customer mistreatment behaviors in a less
negative light. Employees with activated prosocial motivation tend to pay less attention to social
information that is not aligned with their prosocial intention. Therefore, perspective taking will
motivate employees to pay less attention to negative interactions with customers. In addition,
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employees may also feel empathy and concern toward customers and think of them in terms of
being in an unfortunate situation rather than as rude or abusive individuals (Davis, 1983). Indeed,
there is some evidence showing that experimentally manipulated perspective taking is associated
with better psychological and physical synchrony among partners who experience conflict
(Nelson, Laurent, Bernstein, & Laurent, 2017). For these reasons, we hypothesize that
perspective taking will decrease employees’ negative appraisal of customers’ behaviors:
Hypothesis 3: On days when employees receive the perspective taking intervention in the
morning, they will perceive less daily customer mistreatment compared to when they do
not receive any intervention.
Moderating Effect of Perspective Taking
Given that the reduced customer mistreatment experience resulting from perspective
taking may still lead to undesired employee consequences (e.g., negative mood), we further
expect that the perspective taking intervention may also buffer the effect of perceived customer
mistreatment on employees’ negative mood. In the situation of customer mistreatment,
customers tend to perceive their own behaviors as legitimate responses to unpleasant service
(Groth & Grandey, 2012), whereas employees are likely to interpret customers’ behaviors as
unfair actions targeted at themselves (Rupp & Spencer, 2006). As a result, in the absence of
other-oriented motivation, employees tend to experience negative mood following mistreatment
(Wang et al., 2013; Zhan et al., 2013). In contrast, motivated information processing theory
suggests that the perspective taking intervention may motivate service employees to process their
customer’s perspective in a prosocial manner, and thus direct employees’ attention to situational
factors that drive customer behaviors, thereby viewing mistreatment as less personally relevant
(Vescio et al., 2003; Vorauer, Martens, & Sasaki, 2009; Wegner & Finstuen, 1977). Perspective
taking lessens the extent to which people experience self-oriented feelings like anxiety and
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distress in response to tense interpersonal interactions (Davis, 1983). When mistreatment is seen
as less personally relevant, then employees’ negative emotional response to mistreatment may be
muted. Therefore, we hypothesize:
Hypothesis 4: Perspective taking intervention will moderate the positive relation of daily
perceived customer mistreatment with afternoon negative mood, such that this relation
will be weaker on days when employees receive the perspective taking intervention in the
morning compared to days when there is no intervention.
Customer Mistreatment and Employee Self-Focused Maladaptive Outcomes
Affective reactions elicited by work events have downstream influences on cognition and
behavior (Weiss & Cropanzano, 1996). It is not surprising, then, that the negative emotion
induced by customer mistreatment can be detrimental for service employees (Koopmann et al.,
2015). For instance, service employees who experience negative mood may engage in emotion-
based maladaptive coping (Spector & Fox, 2002), which refers to reactions to negative emotions
that produce long-term dysfunctional outcomes (Brown, Westbrook, & Challagalla, 2005). In
this study we examine two such self-focused, emotion-based maladaptive outcomes: rumination
and maladaptive shopping.
Conceptualized as a self-focused form of maladaptive cognition, rumination refers to
persistent thoughts that focus on one’s failures and negative mood for extended periods of time
(Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008). Research has robustly reported that negative
affect leads to ruminative self-focused attention (e.g., Mor & Winquist, 2002; Smith & Alloy,
2009) and that rumination is a maladaptive outcome of customer mistreatment (Baranik, Wang,
Gong, & Shi, 2017; Wang et al., 2013). Unlike problem-solving or distraction strategies that
remove focus away from the self, rumination keeps the negative thoughts accessible in memory,
which perpetuates people’s negative mood rather than diminishing it (e.g., Wang et al., 2013).
Cognitive theories of rumination suggest that rumination is triggered by goal failure (Martin &
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Tesser, 1996). Because emotional reactions serve as feedback for the effectiveness of on-going
goal pursuits (e.g., Johnson, Howe, & Chang, 2013; Johnson, Chang, & Lord, 2006), it is
conceivable that negative mood may signal goal failure for service employees, thus precipitating
rumination.
Apart from rumination, shopping can also serve as a self-focused, emotion-based coping
behavior that is used to regulate one’s mood states (Hama, 2001; Jacobs, 1986). Dittmar, Long,
and Bond (2007) investigated the motivation behind online shopping, and found that mood
enhancement was a key driver of people’s personal shopping behavior. Such shopping is also a
self-focused behavior, as impulsive consumption behaviors are positively associated with an
individualistic self-construal (e.g., Chen, Ng, & Rao, 2005). Although shopping is not
necessarily maladaptive, it can lead to financial and/or mental problems when it occurs without
proper self-control (Carver & Scheier, 1998). Self-regulation perspectives posit that individuals
draw from a limited pool of self-regulatory resources to control their cognition and behavior
(Beal, Weiss, Barros, & MacDermid, 2005; Johnson, Muraven, Donaldson, & Lin, 2017). When
employees experience customer mistreatment, self-regulatory resources are consumed as they try
to avoid the distraction of negative mood while performing in-role tasks (Carver, Scheier, &
Weintraub, 1989; Grandey et al., 2004). As a result, these employees will have impaired
regulatory resources by the end of the workday, making it difficult to regulate subsequent mood-
enhancing behaviors (e.g., shopping) at appropriate levels (Fabes & Eisenberg, 1997; Liu, Song,
Koopmann, Wang, Chang, & Shi, in press).
Shopping as a maladaptive behavior has received little attention from organizational
researchers yet it is a prime example of how negative work experiences can spillover to non-
work domains. Indeed, personal shopping is a common after-work activity for employees
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(Browne, Durrett, & Wetherbe, 2004) and people tend to rely on maladaptive shopping in
misguided efforts to manage their negative mood (Dittmar et al., 2007; Donnelly, Ksendzova, &
Howell, 2013). Such shopping can also be maladaptive by causing serious financial problems
and threatening individuals’ mental health in the long run (e.g., when people lack control over
shopping impulses; Baumeister, 2002; Edwards, 1993). Based on the above, we hypothesize:
Hypothesis 5: Negative mood will mediate (a) the positive relation of daily perceived
customer mistreatment with employee evening rumination, and (b) the positive relation of
daily perceived customer mistreatment with employee evening maladaptive shopping.
Combining all of the hypotheses above, we propose that the recall of prosocial action and
perspective taking interventions will reduce the maladaptive self-focused evening outcomes (i.e.,
rumination and maladaptive shopping) of customer mistreatment, via their effects on employees’
perceived customer mistreatment and the concomitant negative mood. By shifting employees’
attention away from the self and toward others, these social mindfulness interventions may prove
especially effective at curbing self-focused cognitions and impulsive behaviors later in the day.
Thus, we hypothesize:
Hypothesis 6: Compared to the control condition, (a) recall of prosocial action and (b)
perspective taking will reduce evening rumination via their effects on perceived customer
mistreatment and afternoon negative mood.
Hypothesis 7: Compared to the control condition, (a) recall of prosocial action and (b)
perspective taking will reduce evening maladaptive shopping via their effects on
perceived customer mistreatment and afternoon negative mood.
METHOD
Sample and Procedure
We collected data from a call center of a large bank located in southeast China. The
bank’s retail business department assisted us in distributing the study announcement to every call
center customer service employee (N = 96), along with a letter assuring them that their responses
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would be kept confidential and only used for third-party research purposes. Ninety-four
employees agreed to participate in our study (response rate = 97.92 %). Of the 94 participants,
86.2% were female, they had an average age of 21.1 years (SD = 2.8), an average organizational
tenure of 1.7 years (SD = 1.6), and an average of 13.1 (SD = 1.8) years of education. Participants’
major work responsibilities included responding to customers’ requests, dealing with complaints,
and providing other customer service support via phone. On average, they received about 80
calls from customers per day during the study period. Given that participants’ daily work
involves frequent interactions with customers, and that mistreatment is more likely in less
personal (i.e., non-face-to-face) exchanges, the likelihood that they were exposed to daily
customer mistreatment is quite high (Grandey et al., 2004). This specific sample is therefore
ideal for the purposes of our study. Further, since the call center industry is among the fastest-
growing segments of the economy, and organizations are increasingly moving service
interactions to call centers (Batt, 2002; van Jaarsveld, Walker, & Skarlicki, 2010), our call center
setting is relevant for many organizations (Wang et al., 2011).
Data collection occurred in two phases. In the first phase, all participants completed a
brief questionnaire about demographics (i.e., gender, age, and organizational tenure). A month
later, in the second phase, participants completed daily surveys 4 times per workday (i.e.,
morning, noon, afternoon, and evening) for 3 consecutive weeks. Across the 15 survey days (i.e.,
5 workdays × 3 weeks), the compliance rate was 100%, thus we received 1410 responses in total
from participants (i.e., 4 daily surveys × 5 workdays × 3 weeks × 94 participants). The unusually
high compliance rate owes to company sponsorship of the study, use of company time to fill out
the daily surveys, and financial incentives for completing all surveys.
Regarding the timing of survey administration, the morning survey (measuring negative
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mood) was distributed to the participants when they first arrived at work in the morning. When
participants finished their morning work around noon, the noon survey (measuring customer
mistreatment experienced during the morning work) was distributed and completed prior to the
lunch break. At the end of the afternoon before participants left work, they completed the
afternoon survey (measuring customer mistreatment experienced during the afternoon work and
employee afternoon negative mood). After participants handed in the afternoon survey, the
evening survey (measuring rumination and maladaptive shopping) was distributed to them to
bring home. Participants were instructed to complete the evening survey prior to going to bed.
Participants turned in the completed evening surveys as soon as they arrived at work the next
morning (with the exception that Friday evening surveys were turned in on the following
Monday morning). Each survey took around 5-10 minutes to complete, which is consistent with
the recommended survey length for daily diary studies (Fisher & To, 2012).
During the 5 workdays of the first week, all participants were assigned to the control
condition and thus did not receive any intervention in the morning. In the second week, we
randomly assigned half of the participants to the recall of prosocial action intervention and these
participants then received perspective taking intervention during the third week. The other half of
the sample were assigned to the perspective taking intervention during the second week, and then
to the recall of prosocial action intervention during the third week. We did this to counter-
balance the sequence of experimental treatment at the week level, which we also controlled for in
our analyses. Interventions were administered in the morning after the participants completed the
morning surveys, thus we captured morning baseline mood prior to the intervention.
Social Mindfulness Interventions
Recall of prosocial action. The recall of prosocial action intervention was adapted from
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Weinstein and Ryan (2010). Specifically, participants in this condition were instructed to recall
and describe one of their recent prosocial behaviors: “Please describe an act where you helped
someone else or did something for a good cause in your work or everyday life recently. Describe
the nature of the helping act, your relation to the person or persons whom you helped, and your
feelings after the helping behaviors. Please include as many details as possible. Please do not
refer to the same event that you have described in the past.” The participants wrote their
responses in the survey booklet, which covered both work and non-work prosocial behaviors. In
our data analysis, recall of prosocial action intervention was coded as a dummy variable at the
day level (1 = “received the recall treatment” vs. 0 = “did not receive the recall treatment”).
Perspective taking. The perspective taking intervention was adapted from Weyant (2007).
Specifically, participants in this condition were asked to recall and answer a few questions about
a rude phone conversation they had with a customer during the previous day. Questions included
“How did you feel about the phone call in general?”, “What was the customer’s problem in terms
of products/service?”, and “How did you assist him/her with the problem?” Then, participants
were instructed to imagine that they were in the position of the customer and to answer a few
questions from the perspective of the customer. Questions included “Please describe the problem
about which you are calling”, “What kind of products and information do you need?”, “How do
you want to be treated during the phone call?”, and “What kind of service will make you feel
satisfied?” The participants wrote their answers to all questions in the survey booklet. In our data
analysis, the perspective taking intervention was coded as a dummy variable at the day level (1 =
“received the perspective taking treatment” vs. 0 = “did not receive the perspective taking
treatment”).
Manipulation check. We conducted two manipulation check pilot studies to verify the
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effectiveness of our social mindfulness interventions. In the first pilot, we recruited a sample of
120 university students (average age = 20.9 years with a SD of 0.7; 63.1% were female) from a
major Chinese university located in the same city as the bank call center to examine the
effectiveness of the recall of prosocial action intervention. Participants were randomly assigned
into either a recall of prosocial action condition or control condition (we used the same recall of
prosocial action manipulation as reported above). Following Lyubomirsky, Sousa, and
Dickerhoof (2006), participants in the control condition did not recall or write down anything
before responding to the survey. Following the manipulation, participants responded to a survey
containing manipulation check items (i.e., prosocial motivation) and filler items (i.e., positive
mood, negative mood, and vigor). In particular, we used the 5-item scale developed by Grant and
Sumanth (2009) to measure prosocial motivation (α = .74; e.g., “I get energized by working on
tasks that have the potential to benefit others”). We measured positive mood (α = .70; e.g.,
“excited”) and negative mood (α = .89; e.g., “angry”) using 10 items each that were developed
by Watson, Clark, and Tellegan (1988). We used the 6-item scale developed by Schaufeli,
Bakker, and Salanova (2006) to measure vigor (α = .78; e.g., “I feel strong and vigorous now”).
Results revealed that participants in the recall of prosocial action condition (M = 4.23, SD = .47)
reported higher levels of prosocial motivation than those in the control condition (M = 4.06, SD
= .48; t = 2.01, p < .05; Cohen’s d = .36). In addition, they did not differ on the other measures
(i.e., positive mood, negative mood, and vigor). These findings are encouraging with respect to
the efficacy of our intervention for improving participants’ prosocial motivation.
In the second pilot, we recruited a separate sample of 120 students (average age = 21.1
years with a SD of 0.8; 54.2% were female) from the same university to examine the efficacy of
the perspective taking intervention. Participants were randomly assigned into either a perspective
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taking condition or control condition. Since the participants were not service employees, we
followed Rafaeli et al.’s (2012) procedure and asked participants from both conditions to read
the transcripts of an aggressive service call as a simulation of a real customer mistreatment
experience. In the perspective taking condition, participants answered questions regarding the
service call first from the perspective of the service employee and then from the perspective of
the customer. Participants in the control condition only answered questions from the perspective
of the service employee (they were not instructed to take the customer’s perspective). Afterwards,
participants responded to a survey containing manipulation check items (i.e., perspective taking,
α = .67) and the same filler items as those used in the first pilot study (i.e., positive mood, α = .76;
negative mood, α = .87; and vigor, α = .85). Perspective taking was measured by the 7-item scale
developed by Miller, Birkholt, Scott, and Stage (1995; e.g., “I try to look at everybody’s side of a
disagreement before I make a decision”). Results indicated that participants in the perspective
taking condition (M = 3.75, SD = .62) reported greater perspective taking than those in the
control condition (M = 3.53, SD = .55; t = 2.04, p < .05; Cohen’s d = .38). No differences were
found for positive mood, negative mood, and vigor. These results suggest that our intervention
successfully increased participants’ intention to take other peoples’ perspective.
Measures
We followed Brislin’s (1980) translation-back translation procedure to translate the
measures from English to Chinese. Unless noted otherwise, participants responded to each item
using a 5-point response scale (from 1 = Strongly disagree to 5 = Strongly agree; see all
measurement items in Appendix).
Negative mood. On both the morning and afternoon surveys, negative mood was
measured using an 8-item scale developed by Mohr et al. (2005). Participants were asked to
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indicate the extent to which they agreed that each of the eight items described their current mood
states (e.g., “hostile” and “angry”). Across the 15 survey days, the mean Cronbach’s alpha for
this scale was .86 on the morning survey (with a range of [.78, .89]; SD = .03) and .89 on the
afternoon survey (with a range of [.83, .92]; SD = .02).
Customer mistreatment. On both the noon and afternoon surveys, employees’ experience
of customer mistreatment was measured using an 18-item scale developed by Wang et al. (2011).
Participants rated how frequently they experienced customer mistreatment in the morning or
afternoon on a 5-point scale (0 = never, 1 = a few times, 2 = half of the time, 3 = a majority of the
time, and 4 = all of the time). Across the 15 surveyed days, the mean Cronbach’s alpha was .95
for the noon survey (with a range of [.93, .96]; SD = .01) and .95 for the afternoon survey (with a
range of [.93, .96]; SD = .01). We used the average score of morning and afternoon customer
mistreatment ratings to represent employees’ daily customer mistreatment, which helps in part to
alleviate potential retrospective biases. The distribution of daily customer mistreatment was
positively skewed (skewness = 1.61; kurtosis = 3.52), which is not surprising given its low base-
rate nature (Grandey, Foo, Groth, & Goodwin, 2012).
Rumination. On the evening survey, rumination was measured using an 8-item scale
developed by Wang et al. (2013; e.g., “I could not stop thinking about the bad experience my
clients gave me today” and “Thoughts and feelings about how my clients hurt me today kept
running through my head”). Across the 15 surveyed days, the mean Cronbach’s alpha was .96
(with a range of [.93, .97]; SD = .01). The distribution of evening rumination was positively
skewed (skewness = 1.36; kurtosis = 1.29) due to its low base-rate feature (e.g., Wang et al.,
2013).
Maladaptive shopping. To measure maladaptive shopping behavior, we used two items
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from the compulsive shopping scale developed by Edwards (1993) and one item from the
impulse buying scale developed by Verplanken and Herabadi (2001). The reason we did not use
the full scales is because most of the items from the scales confound individuals’ feelings about
the shopping experience during or after shopping (e.g., “I feel guilty or ashamed after I go on a
buying binge” from Edwards [1993]; “I can become very excited if I see something I would like
to buy” from Verplanken and Herabadi [2001]). In addition, the scales are comprised of too
many items to feasibly include in daily surveys. The three items we used were “After work, I
bought things that I do not need or will not use,” “After work, I bought things even though I
couldn’t afford them,” and “After work, I went shopping despite the fact that I did not have spare
time or the money.” Across the 15 surveyed days, the mean Cronbach’s alpha was .84, ranging
from .70 to .90 (SD = .05). The distribution of evening maladaptive shopping was positively
skewed (skewness = .82; kurtosis = .13) due to its low base-rate feature (e.g., Manolis & Roberts,
2008). Additionally, because the skewness and kurtosis values of our dependent variables are all
within the suggested cutoffs for multivariate skewness (|3.00|) and kurtosis (|10.00|)
recommended by Kline (2011, p. 63; the same criterion has also been used by Mawritz,
Greenbaum, Butts, & Graham, in press), we did not normalize these variables for the analyses
reported in the manuscript.2
To verify the validity of our maladaptive shopping measure, we recruited a sample of 148
employees using Amazon Mechanical Turk (participants received one dollar as payment for
completing the survey). Of the 148 participants, 43.9% were female, their average age was 36.2
2 In supplementary analyses, we used square-root-transformed dependent variables, and log-transformed dependent
variables to correct for their skewness. Both sets of analyses replicated our results reported in this manuscript. These
tests indicate that our findings are robust and unlikely to be driven by non-normal distributions of the dependent
variables. We also applied multiple approaches to detecting potential outliers in our dependent variables (i.e., 2 SDs
around the mean, Kline, 2011; Median absolute deviation approach, Leys, Ley, Klein, Bernard, & Licata, 2013), yet
our pattern of findings remained the same. Interested readers can contact the first author for detailed information.
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years (SD = 11.3), and their average organizational tenure was 16.5 years (SD = 10.8). We
checked respondents’ locations according to their IP address-based longitudes and latitudes at the
time when they responded to our survey, which revealed that 143 of 148 respondents were based
in the US. The online survey was conducted in the morning, and participants reported their after-
work maladaptive shopping from the previous day (α = .87) as well as their mood regulation
motivation for shopping using a 7-item scale developed by Dittmar et al. (2007; α = .93; e.g.,
“Buying things arouses my emotions and feelings”). Participants also directly reported how
much money they spent after work during the previous day and what percentage of this money
was unnecessary. Results revealed that participants’ responses on maladaptive shopping were
positively related to mood regulation motivation (r = .73, p < .01), their total expenses (r = .29, p
< .01), and their reported percentage of unnecessary spending (r = .33, p < .01), all of which
provide support for the validity of our maladaptive shopping measure.
Order of intervention. We created a dummy variable to represent the order of the two
interventions for each participant. This variable was coded as 0 for participants who received the
recall of prosocial action intervention first, and 1 for those who received the perspective taking
intervention first.
Analytic Strategy
We used multilevel modeling to estimate the hypothesized model in Mplus 7.2 (Muthén
& Muthén, 2012) because of the nested data structure. We tested the mediation hypotheses using
Monte Carlo simulation procedures in the open-source software R (http://www.quantpsy.org).
This method accurately reflect the asymmetric nature of the sampling distribution of the indirect
effect (Preacher, Zyphur, & Zhang, 2010).
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We specified a two-level model to examine the hypothesized model.3 At Level-1 (i.e.,
within-person level), we specified the fixed effects of both interventions on daily customer
mistreatment, afternoon negative mood, evening rumination, and evening maladaptive shopping.
We also specified the effects of daily customer mistreatment on afternoon negative mood,
evening rumination, and evening maladaptive shopping. The effects of afternoon negative mood
on evening rumination and evening maladaptive shopping were also specified. In addition, the
effects of the interaction terms between the social mindfulness interventions and daily customer
mistreatment (i.e., daily customer mistreatment × recall of prosocial action intervention, and
daily customer mistreatment × perspective taking intervention) on afternoon negative mood,
evening rumination, and evening maladaptive shopping were specified. Further, we controlled
for the effects of morning negative mood on daily customer mistreatment and afternoon negative
mood. The effect of Day T – 1’s evening rumination on Day T’s evening rumination, as well as
the effect of Day T – 1’s evening maladaptive shopping on Day T’s evening maladaptive
shopping were also controlled. At Level-2 (i.e., between-person level), we controlled for the
effects of intervention order on all Level-1 endogenous variables. Recall of prosocial action
intervention, perspective taking intervention, daily customer mistreatment, and morning negative
mood were group-mean centered to remove between-person variance in estimating the within-
person effect of our model (Enders & Tofighi, 2007). The interaction terms were created after
group-mean centering the two intervention dummy variables and daily customer mistreatment.
3 Following an anonymous reviewer’s suggestion, we also estimated a 3-level model (daily surveys nested in weekly
intervention conditions, which are further nested in persons) to test our hypotheses. The 3-level model yields similar
results to our 2-level model. We also tested our 2-level model using the MLR (Maximum likelihood estimation with
robust standard errors) to mitigate concerns of potential unmodeled heterogeneity (Curran, West, & Fince, 1996;
Hox, Maas, & Brinkhuis, 2010), and the results of these analyses were similar to our current results. Interested
readers can contact the first author for detailed information.
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RESULTS
Table 1 presents the means, standard deviations, reliabilities, and correlations for the
focal variables. One-way random-factor ANOVA results showed that the between-person
variance was significant for daily customer mistreatment (ICC [1] = .73, F (93, 1,316) = 40.71, p
< .01), afternoon negative mood (ICC [1] = .57, F (93, 1,316) = 21.26, p < .01), evening
maladaptive shopping (ICC [1] = .54, F (93, 1,316) = 18.79, p < .01), and evening rumination
(ICC [1] = .50, F (93, 1,316) = 15.98, p < .01). These results indicate that there is substantial
variance in the mediators and outcome variables at the between- and within-person levels,
therefore warranting the use of multilevel modeling to analyze our data.
Hypothesis Testing
The coefficients in the hypothesized model are presented in Table 2 and Figure 2.4 We
used Snijders and Bosker’s (1999) formulas to calculate pseudo-R2 (~R
2) for the effect sizes for
predicting outcomes. Predictors included in the model accounted for 13% of the within-person
variance in employee daily experience of customer mistreatment, 16% in afternoon negative
mood, 24% in evening rumination, and 28% in evening maladaptive shopping. As is shown in
Table 2, both interventions – recall of prosocial action (γ = -.09, p < .05) and perspective taking
(γ = -.10, p < .01) – were negatively related to service employees’ daily experience of customer
4 We also controlled for time effects (whether there is linear trend in study variables across the 15 surveyed days)
and day-of-the-week effects (using Monday as the reference, four dummy variables for Tuesday, Wednesday,
Thursday, and Friday were controlled) on all the endogenous variables in our model. Findings were virtually
identical with and without these two effects. For the sake of brevity, we report results without these control variables.
In addition, in order to investigate whether our intervention effects changed over time, we tested the moderation
effect of time on the two intervention effects. Specifically, we created a variable (i.e., day of the week as a
continuous variable) to represent time. We then created two interaction terms (i.e., time × recall of prosocial
intervention and time × perspective taking intervention) and tested their effects on customer mistreatment
experience. Results showed that time did not significantly moderate recall of prosocial action’s effect on customer
mistreatment experience (γ = .02, p > .05) or perspective taking’s effect on customer mistreatment experience (γ
= .01, p > .05). Therefore, it does not appear that our intervention effects changed over time.
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mistreatment.5 This finding indicates that on the days when employees received either
intervention in the morning, they experienced less customer mistreatment compared to the days
without any intervention. Therefore, Hypotheses 1 and 3 were supported.6
In addition, participants’ daily experience of customer mistreatment was positively
related to their afternoon negative mood (γ = .25, p < .01), and this positive relation was
moderated by recall of prosocial intervention (γ = -.27, p < .05). Following Cohen, Cohen, West,
and Aiken’s (2003) procedure, we plotted the effect of daily customer mistreatment on afternoon
negative mood at conditional values of recall of prosocial action interventions (i.e., 0 vs. 1) in
Figure 3. As shown in the figure, the effect of daily customer mistreatment on afternoon negative
mood was not significant when there was the prosocial action intervention in the morning (γ
= .07, p > .10), but positive and significant when there was no intervention in the morning (γ
= .34, p < .01). Thus, Hypothesis 2 was supported. The perspective intervention, however, did
not moderate the relation of daily customer mistreatment with afternoon negative mood (γ = -.14,
p > .10). Thus, Hypothesis 4 was not supported.
Afternoon negative mood was positively related to both evening rumination (γ = .24, p
< .01) and evening maladaptive shopping (γ = .22, p < .01). The indirect effect of perceived daily
customer mistreatment on evening rumination via afternoon negative mood was .066, with a 95%
CI of [.018, .122]. The indirect effect of daily customer mistreatment on evening maladaptive
5 To test the indirect effects of the interventions on outcome variables, our main analyses reported here are based on
multilevel modeling. We also conducted repeated-measure ANOVAs and found that the means of employee daily
experience of customer mistreatment were significantly different across experimental and control conditions, F(2,
938) = 16.12, p < .01, ω2 = .10. According to Keppel (1991: 66), a .10 value of ω
2 indicates a medium effect size
(typically ranging from .06 to .15) for the repeated-measure design. Further probing within-person paired-
differences across experimental and control conditions, we found that daily experience of customer mistreatment
was higher in the control condition (Mcontrol condition = .63, SD = .60) than in the recall of prosocial action condition
(Mrecall of prosocial action condition = .54, SD = .56; t = 3.98, p < .01; Cohen’s d = .18), and in the perspective taking condition
(Mperspective taking condition = .53, SD = .51; t = 5.13, p < .01; Cohen’s d = .25).
6 We also compared the two interventions’ effects on employees’ daily experience of customer mistreatment, and
observed that the difference between the two was .014, with 95% confidence interval (CI) of [-.072, .101]. Because
the CI contains zero, the two intervention effects are not significantly different from each other.
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shopping via afternoon negative mood was .056, with a 95% confidence interval (CI) of
[.016, .104]. Because these CIs do not contain zero, Hypotheses 5a and 5b were both supported.
The indirect effects of the two interventions on the distal outcomes are summarized in
Table 3. Specifically, the indirect effect of the prosocial action intervention on afternoon
negative mood via daily customer mistreatment was -.022, with a 95% CI of [-.048, -.004].
Similarly, the indirect effect of the prosocial action intervention on evening rumination via daily
customer mistreatment and afternoon negative mood was -.005, with a 95% CI of [-.014, -.001].
The indirect effect of the prosocial action intervention on evening maladaptive shopping via
daily customer mistreatment and afternoon negative mood was -.005, with a 95% CI of [-.012,
-.001]. Given that these CIs do not contain zero, Hypotheses 6a and 7a were both supported.
The indirect effect of the perspective taking intervention on afternoon mood via daily
customer mistreatment was -.025, with a 95% CI of [-.050, -.006]. The indirect effect of the
perspective taking intervention on evening rumination via daily customer mistreatment and
afternoon negative mood was -.006, with a 95% CI of [-.012, -.001]. Lastly, the indirect effect of
the perspective taking intervention on evening maladaptive shopping via daily customer
mistreatment and afternoon negative mood was -.006, with a 95% CI of [-.014, -.001]. Because
the CIs do not contain zero, Hypotheses 6b and 7b were both supported. Above all, results
indicated that both other-oriented interventions––recall of prosocial action and perspective
taking––decreased employees’ daily experience of customer mistreatment, which in turn reduced
afternoon negative mood and, later on, reduced evening rumination and maladaptive shopping.
DISCUSSION
This study breaks new ground by investigating the effects of two daily prosocial
interventions on employees’ experiences of and responses to customer mistreatment in a field
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experiment. We found that on days when service employees were instructed to recall a prosocial
action in the morning (vs. control condition), they experienced less (vs. more) customer
mistreatment during the day, and in turn, lower (vs. higher) negative mood in the afternoon,
which was associated with less (vs. more) rumination and maladaptive shopping in the evening.
We observed comparable intervention effects for perspective taking in the morning. Further, we
found that the prosocial action intervention also buffered the relation of employees’ experience
of customer mistreatment with afternoon negative mood.
Theoretical and Practical Implications
We discuss six theoretical implications of our findings. First, our study extends the
customer mistreatment literature by highlighting the distinction between actual customer
mistreatment and employees’ subjective experience of customer mistreatment and by
investigating the antecedents of employees’ experience of customer mistreatment following a
social mindfulness framework (Van Doesum et al., 2013). Previous research has mainly focused
on the detrimental effects of customer mistreatment and moderators of such effects (e.g.,
Dormann & Zapf, 2004; Grandey et al., 2004; Wang et al., 2013), while overlooking the
processes that potentially drive employees’ experience of customer mistreatment. Drawing from
the social mindfulness framework, our study demonstrates how two other-oriented daily
interventions (viz., recall of prosocial action and perspective taking) help mitigate employees’
experience of customer mistreatment. In doing so, we applied and examined the social
mindfulness framework in customer service setting and thus contributed to both the social
mindfulness and customer mistreatment literatures.
On the one hand, we highlighted how the integration of social mindfulness with
motivated information processing theory is fruitful for understanding customer mistreatment
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experiences. This integrated approach is particularly relevant because whether people respond to
prickly interpersonal interactions in maladaptive ways largely depends on their motivation of
being socially mindful (Van Doesum et al., 2013). On the other hand, we also responded to
recent calls to identify antecedents of customer mistreatment experience (e.g., Koopmann et al.,
2015) and provided insights to an important but unaddressed question: “How can we reduce
employees’ experience of customer mistreatment?” Specifically, our findings demonstrate that
employees’ prosocial orientation plays important roles in the formation of customer mistreatment
perceptions as well as employee reactions to such perceptions. These findings are consistent with
prior arguments that prosocial mindfulness motivates employees to have empathetic interests that
are aligned with customer needs (Bolino et al., 2012; Van Doesum et al., 2013).
Second, our research also contributes to the work-to-nonwork spillover literature.
Specifically, we focused on a prevalent yet rarely studied maladaptive self-focused behavior –
evening maladaptive shopping – and showed that employees’ daily experience of customer
mistreatment led to more maladaptive shopping in the evening via the mediating effect of
afternoon negative mood. While shopping is a popular topic in fields like marketing (e.g.,
Hausman, 2000) and clinical psychology (e.g., Dittmar, 2004), it is overlooked in the
management literature. Previous studies on maladaptive shopping have either focused on
individual differences as antecedents (e.g., Bosnjak, Galesic, & Tuten, 2007; Wang & Yang,
2008) or examined maladaptive shopping as a consequence of traumatic stress (e.g., Mandel &
Smeesters, 2008; Somer & Ruvio, 2014). It is surprising that associations of work experiences
with after-work maladaptive shopping are rarely explored, especially given that work comprises
one-third of employees’ daily lives and impacts various after-work maladaptive behaviors (e.g.,
Barnes & Wagner, 2009; Liu, Wang, Chang, Shi, Zhou, & Shao, 2015; Liu, Wang, Zhan, & Shi,
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2009). Despite being rarely explored, maladaptive shopping is relevant to consider within a
social mindfulness and motivated information processing framework because impulsive
consumption behaviors are symptomatic of an individualistic self-focus (Chen et al., 2005).
Becoming more prosocial, which shifts attention away from the self, should therefore reduce
impulsive and individualistic acts. For this reason we positioned maladaptive shopping as an
example of a self-focused maladaptive coping outcome of customer mistreatment experiences,
and our study is among the first to link work-related experiences to maladaptive shopping. Our
findings therefore extend the range of spillover consequences of employees’ work-related
experiences and provide initial insight into maladaptive shopping. Further research that identifies
the impact of work-related experiences on maladaptive shopping and other impulsive self-
focused behaviors is warranted.
Third, our within-person field experiment design alleviates common concerns about
internal validity and ecological validity (e.g., Cook & Campbell, 1979; Rafaeli et al., 2012).
Specifically, our within-person experiment design removes the potential confounding effects of
individual differences and variations in organizational contexts, enabling us to focus exclusively
on the effects of the interventions. Additionally, our field experiment design has advantages over
laboratory studies using student samples in that our research setting and sample match the target
setting and potential users of the interventions (Dipboye & Flanagan, 1979). When possible,
future research ought to use a similar research design to obtain clear causal inferences and
generalizable findings. Future research can build upon our study by exploring possible boundary
conditions of the reported intervention effects, including moderation effects of individual
differences and organizational contexts. For instance, while we manipulated employees’ other-
orientedness by treating prosocial motivation as a malleable state, it can also have chronic, trait-
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like counterparts (e.g., Grant & Sumanth, 2009; Meglino & Korsgaard, 2004; Parker & Axtell,
2001). It may be that the trait-like characteristics might augment or perhaps diminish the effects
of the social mindfulness interventions. In addition, as indicated by the high ICC in customer
mistreatment experience, such mistreatment tended to vary greatly between employees. Although
it is not clear whether these differences are driven by personalities that may impact perception
(e.g., neurotic employees may perceive more mistreatment), or by general customer service
quality (e.g., employees providing low-quality service are more likely to be mistreated), it is
important to take individual differences into consideration (Koopmann et al., 2015). As such, one
direction for future research is to examine possible interaction effects between individual
differences and the prosocial interventions. In addition, the effects of the interventions may also
vary across different contexts, given that supportive (Shih et al., 2014) and empowering (Yagil &
Ben-Zur, 2009) organizational contexts impact employees’ motivation, cognition, and behavior.
Thus, it would also be fruitful to consider whether and how organizational contexts bound the
effects of the recall of prosocial action and perspective taking interventions.
Fourth, our finding did not support our hypothesis about the buffering effect of the
perspective taking intervention on the positive relation of customer mistreatment with negative
mood. On the one hand, perspective taking may reduce negative affective reactions by increasing
service employees’ other-orientation and causing them to attribute customer mistreatment to
non-self (e.g., situational) factors (Vescio et al., 2003). On the other hand, perspective taking
may also reduce self-serving thinking (Miller & Ross, 1975), making employees more aware of
their failures to provide satisfactory service (as inferred from customer mistreatment). These goal
failure experiences may subsequently lead to rumination and persistent negative mood states
(e.g., Wang et al., 2013). If both of these mechanisms operate concurrently, then it would be
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difficult to detect the moderation effect of the perspective taking intervention. Future research
that directly examines potential mechanisms (and possibly counteracting ones) underlying
perspective taking would be useful.
Fifth, although we did not hypothesize full mediation effects of negative mood in linking
daily experience of customer mistreatment to evening maladaptive coping outcomes, our results
suggest a full mediation pattern. Such a finding supports our choice of negative mood as the
critical mediation mechanism. Specifically, drawing from self-regulation perspectives, we
theorized and showed that employees’ experienced negative events (i.e., customer mistreatment)
first triggered their affective responses (i.e., negative mood), which subsequently resulted in
maladaptive coping (i.e., rumination and maladaptive shopping). This is consistent with prior
studies that conceptualized affective reactions as the critical mechanism linking customer
mistreatment to negative outcomes (e.g., Groth & Grandey, 2012; Spencer & Rupp, 2009). In
addition, we also did not find significant moderation effects of the two interventions on the direct
effects of experienced customer mistreatment on maladaptive coping outcomes, suggesting that
the buffering impacts of our interventions appeared to work on reducing the effect of customer
mistreatment on negative mood, and subsequently influencing maladaptive coping.
Sixth, in our manipulation check study, recall of prosocial actions intervention was found
to have no effect on participants’ positive mood, which appears counterintuitive and contrary to
the largely reported positive association between prosocial behaviors and positive mood (e.g.,
Lyubomirsky & Layouts, 2013). However, recent studies (e.g., Lanaj, Johnson, & Wang, 2016;
Weinstein & Ryan, 2010) also indicate that relationships between helping and helpers’ positive
mood might be more complicated than a simple positive association, due to employees’ various
motivations and the potential costs of helping behaviors. For instance, according to self-
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determination theory (Deci & Ryan, 2000), prosocial actions driven by intrinsic motivation are
more likely to lead to satisfaction, compared to those driven by extrinsic motivation.
Consistently, Weinstein and Ryan (2010) found that autonomous helping was positively
associated with helper positive affect whereas controlled helping was negatively associated with
helper positive affect. Additionally, prosocial behaviors may also result in personal cost, which
can make the prosocial activity an unpleasant experience. For example, engaging in prosocial
behaviors consumes employees’ regulatory resources, possibly leaving them too depleted to
effectively perform other work activities (Lanaj et al., 2016; Lin & Johnson, 2015; Lin, Ma, &
Johnson, 2016). Given that we did not distinguish between autonomous versus controlled helping
or solicit details about helping-related costs in our recall of prosocial action intervention, it
should not be expected that this recall intervention would necessarily induce positive mood.
More research is needed to investigate the underlying mechanisms and unpack the seemingly
complicated effect that the recall of prosocial action intervention has on positive mood.
We now turn our attention to the practical implications of our findings. While customer
mistreatment’s damaging effect on service employees’ well-being is well-established, this
phenomenon remains a headache for organizations because organizations have little control over
customers and thus cannot directly prevent them from exhibiting norm-violating behaviors
(McColl-Kennedy, Patterson, Smith, & Brady, 2009). To alleviate such concerns, our findings
point to some rather easily implementable strategies to improve service employees’ well-being.
For example, instructing service employees to recall recent prosocial actions prior to beginning
the workday produced a meaningful decrease in their daily experience of customer mistreatment
and negative mood in the afternoon. Moreover, the effects of this intervention persisted into the
evening, resulting in less self-focused maladaptive coping at home. Accordingly, organizations
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could develop formal programs encouraging employees to build daily routines of deliberately
reflecting on their prosocial behaviors before they start working so as to improve their work
experience during the day and well-being after work. Moreover, a recall prosocial action
intervention would also mitigate the extent to which customer mistreatment elicits negative
emotional reactions in employees, on days when such mistreatment occurs. As such, it is likely
that by applying such a daily intervention, service employees’ well-being may be improved in
the long run.
In a similar vein, our study suggests that instructing employees to take the perspective of
customers would also lessen employees’ experience of customer mistreatment and negative
mood during the day, and their self-focused maladaptive coping during the evening. While there
are many reasons to encourage employees to exercise greater perspective taking (e.g., greater
cooperation), the improvements in daily well-being and reductions in maladaptive coping that we
observed in this study are especially important given that they are closely relevant to employees
physical and mental health (Sliter et al., 2011). Having said that, we also want to emphasize the
importance of exercising caution with the above-mentioned interventions. There is always a risk
that some organizations may improperly use these interventions to compel service employees to
view customer mistreatment as acceptable. Executives and managers should practice these
interventions with good intentions and aim to improve employees’ well-being, instead of trying
to desensitize employees to customers’ abusive behaviors. In addition, these employee-oriented
interventions should be implemented in combination with other practices that increase supervisor
support to prevent potential escalation of customer mistreatment due to employees’ improved
resilience.
Finally, our study documented that negative mood was the linchpin that linked customer
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mistreatment experience during the day with self-focused maladaptive coping after work. This
finding, along with previous research, highlights the importance of effective emotion regulation
following negative work events (Doerwald, Scheibe, Zacher, & van Yperen, 2016; Scheibe,
Spieler, & Kuba, 2016; Zhan et al., 2013). To this end, Hargrove, Winslow, and Kaplan (2013)
summarized various exercises that can be used to promote service employees’ emotion
regulation, including self-distancing (Kross & Ayduk, 2011) and mindfulness (Erisman &
Roemer, 2010) activities. Organizations can leverage this knowledge by developing training
programs involving these emotion regulation activities to improve service employees’ well-being.
Limitations and Future Directions
Despite the important theoretical and practical implications of our findings, they should
be interpreted in light of some limitations. First, except for the interventions, all other variables
were self-reported by employees, which may be biased owing to common method variance.
However, we took several steps to mitigate common method and source bias (e.g., Johnson,
Rosen, & Djurdjevic, 2011; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). First, we measured
the mediator and outcome variables at different times. Second, we controlled for baseline levels
of the outcome variables from prior times, enabling us to assess change in affect and maladaptive
coping, which also mitigates concerns with common method variance. Third, we used group-
mean centering for our level 1 variables, which removes potential between-person confounds
such as social desirability. Thus, it is unlikely that our results are driven by method artifacts.
Future studies could build upon our work by using objective measures (e.g., customer service
monitoring records) and other-reports (e.g., family-reported rumination).
Second, both our manipulation check and model estimation results suggest that the
prosocial recall intervention activates employees’ prosocial motivation. Although this idea is
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well-aligned with previous research findings (e.g., Reed, Aquino, & Levy, 2007), the recall of
prosocial action can also lead to moral licensing, which paradoxically reduces prosocial behavior
and increases deviant behavior (e.g., Klotz & Bolino, 2013; Lin et al., 2016; Miller & Effron,
2010). For instance, Lin, Ma, and Johnson (2016) found that managers acted more abusive after
exhibiting ethical behavior due to moral licensing. In a similar vein, Mazar and Zhong (2010)
found that people gained moral license after purchasing organic products and thus acted less
altruistically. These theorizing and findings would suggest a positive relation of recalling
prosocial actions with maladaptive behaviors in our study, such that recalling prosocial actions
would give employees license to engage in impulsive self-serving shopping. This inconsistency
hints at the presence of potential moderating factors that are worthy of further investigation. For
example, Conway and Peetz (2012) leveraged construal level and action identification theories to
argue that recalling distant (abstract) moral action would make moral identity more salient and
induce people to act consistent with this identity, whereas recalling recent (concrete) moral
action reminds people that they have already fulfilled moral goals and thus are free to act less
morally. Future research is needed to identify situations where the recall of prosocial action is
beneficial versus detrimental.
Third, the generalizability of the current findings may be limited by our Chinese call
center sample. Although call center operations and managerial practices in China are similar to
other countries, China’s collectivistic culture, which emphasizes the importance of societal
norms and culturally-defined roles, may have shaped our interventions’ effects. Additionally,
Takaku, Weiner, and Ohbuchi (2001) found that the effects of a perspective taking intervention
were significant in an American sample but not a Japanese one. The authors ascribed this
inconsistency to differences in individualism–collectivism. Further, given that the experience of
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customer mistreatment involves complex perceptual and cognitive processing, it is possible that
cultural differences also play a role in shaping service employees’ experience of customer
mistreatment. As such, our two other-oriented interventions may operate somewhat differently in
individualistic cultures, which creates a need for samples from other cultures to cross-validate
the current findings.
Fourth, similar to other experimental studies, our findings may be subject to potential
confounds such as practice effects, Hawthorne effects, and demand effects (Shadish et al., 2002).
For example, due to our within-person design, a practice effect may have occurred such that
participants’ perceptions of customer mistreatment were altered by filling out surveys repeatedly
in the first week (i.e., the control condition). Further, participants might have reported more
favorable outcomes in the intervention conditions just because any intervention was
implemented (i.e., Hawthorne effect), or because they speculated that researchers expected
different responses in the intervention conditions (i.e., demand effect). Despite these potential
alternative explanations, from a post hoc perspective, our findings may to some extent rule out
the possibility that the reported intervention effects were purely due to practice effects.
Specifically, as reported in Footnote 4, our results still hold when we control for time and day-of-
the-week effects, which is unlikely to occur if the intervention effects are influenced by repeated
practices. Nevertheless, we encourage future studies to apply more rigorous designs that can
overcome the potential confounding effects (Cook & Campbell, 1979).
Fifth, we applied a crossover design where only the order of the two intervention
conditions was counterbalanced in order to guarantee an uncontaminated baseline-control
measure of focal variables (Shadish et al., 2002). Although such a design has several advantages
(e.g., providing no-treatment baseline for assessing later intervention effects, avoiding the
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situation where some participants were given more things to do than others), it cannot
completely rule out the alternative explanation that our intervention effects were partly driven by
participants’ general reactions to any interventions (compared to no intervention at all). Such a
concern may be addressed by using a fully-counterbalanced design, where the order of all
conditions (both the control condition and the intervention conditions) is counterbalanced (Crano
& Brewer, 2014). However, it is important to note that a fully-counterbalanced design may create
other issues that can jeopardize the internal validity of the findings (e.g., participants in one
intervention condition could have spoken to participants in the control condition).
Sixth, although we found significant direct and indirect intervention effects, the reported
effect coefficients appear small, which might raise concerns regarding the meaningfulness and
replicability of our findings. We report effect sizes (e.g., Cohen’s d, pseudo-R2, andω2
) to assist
with interpreting our intervention effects’ magnitude. These effect sizes are comparable to other
studies using similar designs (e.g., Liu, Song, Li, & Liao, 2017; Matta, Scott, Colquitt,
Koopman, & Passantino, 2017; Uy, Lin, & Ilies, in press). In addition, the small three-path
indirect effect coefficients are actually not surprising, given that by definition they are products
of three regression coefficients that are usually smaller than 1 (Taylor, MacKinnon, & Tein,
2007). Therefore, a small raw point estimate of indirect effect does not necessarily indicate a
small effect size of the mediation effect. Further, following recommendations by Preacher and
Kelley (2011), the reported intervention effects (both direct and indirect effects) need to be
interpreted considering the scaling and ranges of the focal variables, especially given that the
outcome variables we focused on were low-base-rate negative experiences. Moreover, the
seemingly small effects may still be practically useful considering the low cost of the
interventions and the relatively long time lapse between the interventions and the outcome
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variables. According to Cortina and Landis (2009: 299), for a low-cost intervention, “any
nonzero relationship has important implications.” Similarly, Prentice and Miller (1992) also
suggested that small effect sizes are particularly meaningful when a minimal manipulation of the
independent variable or a difficult-to-influence dependent variable is involved. As such, we
believe that our findings are informative and practically meaningful despite the seemingly small
effects. Having said that, we should still be careful not to draw overly strong conclusions about
the intervention effects that prosocial recall and perspective taking may have in practical
application. Future studies applying similar design are needed to further validate our findings and
help relieve the concern about our seemingly small intervention effect.
Finally, one remaining question is whether or not the effects of the two interventions
extend beyond the evening. Although we observed that the effects are robust enough to affect
evening consequences of customer mistreatment on the same day the daily intervention was
administered, we have no direct evidence to support whether and how long our intervention
effects persist after the intervention is stopped. Nevertheless, we speculate that our interventions
will endure beyond the same day based on prior findings on the frequency and effect durations of
self-reflection interventions (e.g., Lyubomirsky, Sheldon, & Schkade, 2005; Seligman, Steen,
Park, & Peterson, 2005). For example, Grant and Dutton (2008) found that after recalling
experiences as a benefactor (vs. beneficiary) for 15 min per day for 2 to 4 days, individuals
exhibited more prosocial behavior two weeks later. We encourage future research to extend the
study window and investigate how persistent the effects of our two interventions are. This is
especially important from an applied perspective because practitioners would be interested to
know with what frequency and duration the interventions are most effective.
A second question is whether or not our interventions impact actual customer
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mistreatment, given our focus on service employees’ experience of (vs. actual) customer
mistreatment. Nevertheless, based on Groth and Grandey’s (2011) negative exchange spiral
model in employee–customer interactions, it is possible that our interventions may also reduce
actual customer mistreatment. Specifically, this model posits that customer mistreatment tends to
ignite employees’ negative emotions or even antisocial behaviors, which may in turn result in
service delivery failure (Wang et al., 2011). Once customers perceive the low-quality service,
they are more likely to respond by mistreating service employees, creating a negative spiral.
Such incivility spirals are ubiquitous in work settings (Rosen, Koopman, Gabriel-Rossetti, &
Johnson, 2016). However, our interventions may break this negative spiral by weakening the link
between customer mistreatment and employees’ negative reaction (e.g., negative mood).
Therefore, implementing our interventions may also produce effects that extend to customer
outcomes. We hope that future studies will test such potential intervention effects by
incorporating measures of actual mistreatment behaviors and customer outcomes.
A final question is whether the two interventions only impact employees’ processing of
customer behaviors via our theorized mechanism. Although past research has established that
both recall of prosocial behaviors and perspective taking consistently invoke individuals’ other-
oriented motivation (Batson et al., 1997; Grant & Dutton, 2012; Maner et al., 2012; Stocks et al.,
2009; Tasimi & Young, 2016; Van Lange, 2008; Young et al., 2012), we did not provide a direct
test of this mechanism in the current study (except for the manipulation check for recall of
prosocial action), nor did we test potential alternative mechanisms (e.g., interventions’ effects on
the ability of being socially mindful). Future studies may want to build on our findings and
examine whether recall of prosocial action and perspective taking may also function through
different mechanisms. Nonetheless, our findings indicate that there are practical and low-cost
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interventions available that leverage social mindfulness and motivated information processing
theories to aid the well-being of employees who experience customer mistreatment.
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TABLE 1
Means, Standard Deviations, Reliabilities, and Correlations among the Focal Variables
Variables Means Within
SD
Between
SD
1 2 3 4 5 6 7
1. Morning negative mood 1.82 .41 .51 (.86) -- -- .32** .93** .62** .45**
2. Recall of prosocial action intervention vs. control .33 -- -- -.05* -- -- -- -- -- --
3. Perspective taking intervention vs. control .33 -- -- -.04 -.50** -- -- -- -- --
4. Daily customer mistreatment experience .57 .28 .48 .09** -.06* -.10** (.95) .38** .30** .36**
5. Afternoon negative mood 1.83 .44 .53 .38** -.07** -.02 .14** (.89) .64** .49**
6. Evening rumination 1.74 .63 .67 .13** -.07* .02 .14** .21** (.84) .44**
7. Evening maladaptive shopping 1.97 .58 .67 .10** -.12** -.04 .13** .19** .10** (.96)
Notes. * p < .05, ** p < .01. Between-person correlations are above the diagonal (N = 94) and within-person correlations are below the diagonal (N = 1,410). The
average Cronbrach’s alpha coefficients are in parentheses along the diagonal. No between-person correlations are reported for prosocial intervention and
perspective taking intervention since the variables do not have between-person variance.
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TABLE 2
Simultaneous Multilevel Path Model Tests and Results
Variables Daily customer
mistreatment
experience
Afternoon negative
mood
Evening rumination
(Day T)
Evening maladaptive
shopping (Day T)
Estimate SE Estimate SE Estimate SE Estimate SE
Level-1 (Within-person level)
Intercept .65** .08 1.68** .09 .60** .22 .57** .21
Morning negative mood .05† .03 .39** .05
Recall of prosocial action intervention
vs. control
-.09* .03 -.05 .04 -.04 .05 -.16** .05
Perspective taking intervention
vs. control
-.10** .03 -.02 .03 .02 .05 -.10* .05
Daily customer mistreatment experience .25** .09 .11 .13 .05 .09
Daily customer mistreatment experience ×
Recall of prosocial action intervention
-.27* .14 .30 .21 .20 .14
Daily customer mistreatment experience ×
Perspective taking intervention
-.14 .10 .14 .21 .30 .19
Afternoon negative mood .24** .05 .22** .05
Evening rumination (Day T-1) .15** .04
Evening maladaptive shopping (Day T-1) .13** .04
Residual variance at Level 1 .08** .01 .17** .01 .39** .05 .33** .03
Level-2 (Between-person level)
Manipulation order -.16 .10 -.13 .10 .03 .12 -.10 .11
Residual variance at Level 2 .22** .05 .23** .03 .29** .06 .23** .05
Notes. N = 1,410. †p <.10, * p < .05, ** p < .01.
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TABLE 3
Summary of Hypothesized Indirect Effects
Hypothesized Indirect Effect Point
Estimate
95% Confidence
Interval
Proportion of
Mediation (Pm)
Hypothesis 5a
Daily customer mistreatment experience � Afternoon negative mood � Evening
rumination
.066* [.018, .122] 21%
Hypothesis 5b
Daily customer mistreatment experience � Afternoon negative mood � Evening
maladaptive shopping
.056* [.016, .104] 20%
Hypothesis 6a
Recall of prosocial action intervention � Daily customer mistreatment experience �
Afternoon negative mood � Evening rumination
-.005* [-.014, -.001] 9%
Hypothesis 6b
Perspective taking intervention � Daily customer mistreatment experience �
Afternoon negative mood � Evening rumination
-.006* [-.012, -.001] 8%
Hypothesis 7a
Recall of prosocial action intervention � Daily customer mistreatment experience �
Afternoon negative mood � Evening maladaptive shopping
-.005* [-.012, -.001] 8%
Hypothesis 7b
Perspective taking intervention � Daily customer mistreatment experience�
Afternoon negative mood � Evening maladaptive shopping
-.006* [-.014, -.001] 9%
Note.* Significant based on 95% confidence interval.
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FIGURE 1
Hypothesized Model.
Daily experience of
customer mistreatment
(Noon survey and
afternoon survey)
Recall of prosocial action
intervention
(Morning)
Perspective taking
intervention
(Morning)
Afternoon negative mood
(Afternoon survey)
H5a/H6
Evening rumination
(Evening survey)
H1/H6a/H7a
H3/H6b/H7b
H5b/H7 Evening maladaptive
shopping
(Evening survey)
H2
H4
H5/H6/H7
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FIGURE 2
Multilevel Path Model Estimation Results
Notes. N = 1,410. †p <.10, * p < .05, ** p < .01. For the sake of brevity, we do not present direct effects in the current model. Please
refer to Table 2 for the direct effects of the intervention variables on afternoon negative mood and evening rumination and
maladaptive shopping, as well as the direct effects of daily customer mistreatment on evening rumination and maladaptive shopping.
Daily experience of
customer mistreatment
(Day T Noon and
Afternoon)
Recall of prosocial action
intervention
(Day T Morning)
Perspective taking
intervention
(Day T Morning)
Afternoon negative mood
(Day T Afternoon)
.24**
Evening rumination
(Day T Evening)
-.09*
-.10**
.22** Evening maladaptive
shopping
(Day T Evening)
-.27*
-.14
.25**
Morning negative
mood
(Day T Morning)
.05† .39**
Evening rumination
(Day T-1 Evening)
Evening maladaptive
shopping
(Day T-1 Evening)
.13**
.15**
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FIGURE 3
Recall of Prosocial Action Intervention Moderates the Effect of Daily Customer
Mistreatment on Afternoon Negative Mood
1
1.5
2
2.5
3
3.5
low high
Aft
ern
oon
Neg
ati
ve
Mood
Daily Experience of Customer Mistreatment
Control Condition
Recall of Prosocial Action
Intervention
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APPENDIX
Customer Mistreatment:
“How frequently did you experience the following this morning (afternoon)? Please respond on
a 5-point scale, with 0 = Never, 1 = A few times, 2 = Half of the times, 3 = A majority of the time,
and 4 = All of the time”.
1. Clients demanded special treatment.
2. Clients thought they were more important than others.
3. Clients asked you to do things they could do by themselves.
4. Clients vented their bad mood out on you.
5. Clients did not understand that you had to comply with certain rules.
6. Clients complained without reason.
7. Clients made exorbitant demands.
8. Clients were impatient
9. Clients yelled at you.
10. Clients spoke aggressively to you.
11. Clients got angry at you even over minor matters.
12. Clients argued with you the whole time throughout the call.
13. Clients refused to listen to you.
14. Clients cut you off mid-sentence.
15. Clients made demands that you could not deliver.
16. Clients insisted on demands that are irrelevant to your service.
17. Clients doubted your ability.
18. Clients used condescending language to you.
Negative Mood:
“To what extent do you agree that the following items describe your current mood states? Please
respond on a 5-point scale, with 1 = Strongly disagree and 5 = Strongly agree.”
1. Jittery
2. Ashamed
3. Nervous
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4. Hostile
5. Guilty
6. Angry
7. Dejected
8. Sad
Rumination:
“To what extent do you agree with the following statements describing your experience this
evening? Please respond on a 5-point scale, with 1 = Strongly disagree and 5 = Strongly agree.”
1. I couldn’t stop thinking about the bad experiences I had with my clients today.
2. Thoughts and feelings about how my clients hurt me today kept running through my head.
3. Strong feelings about what my clients did to me today kept bubbling up.
4. Images of today’s bad experiences with my clients kept coming back to me.
5. I brooded about how my clients treated me badly today.
6. I found it difficult not to think about the bad experiences that I had with my clients today.
7. I found myself replaying the bad experiences with my clients over and over in my mind.
8. Even when I was engaged in other tasks, I thought about the bad experiences with my clients
today.
Maladaptive Shopping:
“To what extent do you agree with the following statements describing your behaviors this
evening? Please respond on a 5-point scale, with 1 = Strongly disagree and 5 = Strongly agree.”
1. After work, I bought things that I do not need or will not use.
2. After work, I bought things even though I couldn’t afford them.
3. After work, I went shopping despite the fact that I did not have spare time or the money.
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Biographical Sketches
Yifan Song ([email protected]) is a Ph.D. Candidate in the Warrington College of
Business at University of Florida. Her current research interests include newcomer socialization,
leadership and power in teams, employee well-being, and migrant worker adjustment.
Yihao Liu ([email protected]) is an Assistant Professor at the School of Labor &
Employment Relations and Department of Psychology, University of Illinois at Urbana-
Champaign. He earned his Ph.D. in management from University of Florida. His primary
research interests include occupational stress and well-being, workplace interpersonal behaviors,
and newcomer socialization and adjustment.
Mo Wang ([email protected]) is the Lanzilotti-McKethan Eminent Scholar Chair
and the Director of Human Resource Research Center at the Warrington College of Business at
University of Florida. He received his Ph.D. in industrial-organizational psychology and
developmental psychology from Bowling Green State University. His research interests include
older worker employment and retirement, newcomer and expatriate adjustment, occupational
health psychology, teams and leadership, and advanced quantitative methods.
Klodiana Lanaj ([email protected]) is an Associate Professor in the
Warrington College of Business at University of Florida. She received her PhD from Michigan
State University. Her research focuses on leadership, self-regulation, and team processes and
performance.
Russell E. Johnson ([email protected]) is an Associate Professor of Management in the
Broad College of Business at Michigan State University. He received his PhD in Industrial and
Organizational Psychology from the University of Akron. His research explores cognitive and
affective processes that underlie organizational behavior.
Junqi Shi ([email protected]) is a Full Professor in the Lingnan College at Sun Yat-sen
University, China. He received his Ph.D. in industrial-organizational psychology from Peking
University. His current research interests include leadership, work stress, occupational
health, and emotional labor.
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