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Perception and Attribution of Employees’ Effort and
Abilities: The Impact on Customer Encounter Satisfaction
Nina SPECHT Sina FICHTEL Anton MEYER
Sina FICHTEL Research and Teaching Associate Institute of Marketing Ludwig-Maximilians-University Munich Ludwigstrasse 28 RG 80539 Munich GERMANY Phone: 0049-(0)89-2180-3321; Fax: 0049-(0)89-2180-3322; e-mail: [email protected] Anton MEYER Professor and Head of Institute Phone: 0049-(0)89-2180-3321; Fax: 0049-(0)89-2180-3322; e-mail: [email protected] Nina SPECHT Research and Teaching Associate Phone: 0049-(0)89-2180-3321; Fax: 0049-(0)89-2180-3322; e-mail: [email protected]
Perception and Attribution of Employees’ Effort and Abilities:
The Impact on Customer Encounter Satisfaction
Keywords Service encounter, Perceived employee’s effort and abilities, Attribution theory,
Customer satisfaction, Critical incident technique, Experiment
Abstract We examine if and how customers perceive effort and abilities of an employee in
the service encounter and to what extend this perception influences customer satisfaction.
Results from two empirical studies (one critical incident study and one experiment) show that
customers do spontaneously and explicitly attribute their encounter experience to service em-
ployees’ effort and abilities; both determinants are perceived by certain behavioral cues. Re-
sults show further, that the specific and direct impact of perceived effort and abilities on cus-
tomer satisfaction varies within different service types. Across service types (Study 1) results
reveal a stronger impact of perceived effort on satisfaction than of perceived abilities. This
impact is not eliminated even if service outcome is statistically controlled. In consideration of
two specific service types (retail and financial services) under experimental conditions (Study
2), results support a strong and positive impact of both determinants on satisfaction with per-
ceived abilities being stronger in the financial service setting. Results from Study 2 show fur-
ther the independent influence of both determinants on satisfaction since this influence is not
eliminated even when the perceived service outcome is statistically controlled. Conceptually
and theoretically this paper builds on motivation theory, naïve psychology, and attribution
theory, and service specific satisfaction research. Implications for both research and man-
agement will be discussed.
INTRODUCTION
Facing strong competition, businesses now recognize customer satisfaction as a primary goal
on the path to profitability, especially as a result of research suggesting the significant influ-
ence of customer satisfaction on retention (Cronin and Taylor, 1992; Oliver, 1980) and, in
turn, profitability (Reichheld and Sasser, 1990). Within this context, “moments of truth” re-
flect a fundamental means of quality management. Both service companies and manufactur-
ing firms that offer customer service therefore must understand which aspects of a service
encounter determine customer satisfaction. Research and management note the relevance of
the employee in customer–employee interactions as a crucial determinant of satisfaction, to
the point of claiming that “The offering is the employee” (Zeithaml et al., 1996).
Thus, extensive theoretical and empirical work in personal selection, human resource, and
service research literature focuses on the employee, his or her service orientation, and service
competence during customer interaction processes. Whereas some research concentrates pri-
marily on the personality dimension of service orientation, and therefore on an employee’s
predisposition to engage in service-oriented behavior (e.g., Brown et al., 2002; Cran, 1994;
Frei and McDaniel, 1998; Hogan et al., 1984; Hollenbeck and Whitner, 1988), other studies
focus more on employee behavior itself and its impact on quality and customer satisfaction
(e.g., Bettencourt and Gwinner, 1996; Bitner et al., 1990, 1994; Chandon et al., 1997; Coenen,
2001; Cronin et al., 2000; Farrell et al., 2001; Grönroos, 1982; Hartline and Ferrell, 1996;
Meyer and Mattmüller, 1987; Mohr and Bitner, 1995; Parasuraman et al., 1985, 1988; Win-
sted, 2000).
On a meta-level, two behavioral drivers provide important determinants of customer satisfac-
tion in customer–employee interactions: the employee’s motivation, as perceived by his or her
effort, and competence, as perceived by his or her abilities. The importance of these drivers
appears in basic definitions of service that take customers’ point of view (Meyer, 1991, 1998):
Services refer to the offered effort and abilities of employees applied directly to the customer
or an object he or she possesses. This definition clearly states that the employee and his or her
perceived effort and abilities represent the service from a customer’s point of view.
Despite the broad consensus about the importance of effort and abilities, no research provides
empirical evidence for their simultaneous perception by customers, their relationship, or their
influence on customer satisfaction. This study attempts to close this research gap by investi-
gating, through two studies (one exploratory study and one experiment) that use three types of
data (critical incident descriptions, survey responses and experimental data), (1) whether cus-
tomers perceive service providers’ effort and abilities during service encounters, (2) the be-
havioral cues customers use to assess effort and abilities, (3) whether perceived effort and
abilities influence customer satisfaction, and (4) whether perceived effort and abilities influ-
ence customer satisfaction when service outcome is statistically controlled.
Our results thus contribute to a deeper understanding of customer satisfaction in interpersonal
service encounters because they explore the nature and role of perceptions of service provid-
ers’ effort and abilities as dominant process factors, as well as their relevance in direct com-
parison with the perceived service outcome. Research is based on naïve psychology (Heider,
1958), attributional research developed in Bernhard Weiner’s attributional theory of motiva-
tion and emotion’ (Weiner, 1985, 1986) and motivation theory.
CONCEPTUAL BACKGROUND AND THEORETICAL FOUNDATION
Service Research
Customer satisfaction with services depends not only on the service outcome (what the cus-
tomer receives during the exchange) but also on the process of service delivery, or the quality
of the interaction itself (how the customer receives value) (Czepiel, 1990; Grönroos, 1990).
Moreover, traditional research conceptually and empirically analyzes specific service quality
and satisfaction dimensions, which relate closely to service providers’ behavior. Such re-
search was triggered by the well-known SERVQUAL studies (Parasuraman et al., 1985,
1988), which state that in addition to tangible elements, the reliability, responsiveness, assur-
ance, and empathy associated with service provision determine a customer’s service evalua-
tion. Therefore, disregarding situational facilitators and inhibitors, perceived performance
strongly depends on the individual employee and his or her behavior. However, the multi-
item measurement applied by SERVQUAL has been subject to the criticism that it cannot
capture the specific nature of service transactions as personal and individual social interaction
processes (Babakus and Boller, 1992; Carman, 1990; Lee et al., 2000). Inspired by such criti-
cism, Bitner et al. (1990) published a well-respected research study in which they apply criti-
cal incident methods to capture central dimensions of service encounter satisfaction. Com-
pared with close-ended surveys, their approach generates inductive and detailed information
about customer satisfaction with a service encounter and places employees’ behavior at the
center of interest.
However, no research theoretically investigates and empirically tests both perceived effort
and perceived abilities as core behavioral representatives of employees’ performance, deter-
mines their impact on customers’ encounter satisfaction, or analyzes their possible interaction
effects. Therefore, to obtain a deeper understanding of effort and abilities as behavioral driv-
ers of human performance, their relationship, and their perception and psychological anchor-
ing in the mind of observers (i.e., customers), we move from the field of service research to
draw on motivation theory, naïve psychology, and attribution theory.
Motivation Theory
Motivation literature offers insight into the relationships among performance, motivation, and
ability and assumes outcomes are direct functions of motivation multiplied by ability (Lawler,
1966; Vroom, 1960, 1964; Lawler, 1966). According to this approach, “to achieve a high
level of performance a person must have both the ability and the motivation to perform effec-
tively” (Baldwin, 1958). Although some authors regard motivation as the predominant factor
(e.g., French, 1957), others assert the equality of both attributes (e.g., Fleishman, 1958; Locke
et al., 1978; Vroom, 1964). Moreover, motivation literature links these constructs to concrete
descriptions of perceptions; for example, motivation perceptions rely on effort, or the dis-
played energy put into a behavior (Locke et al., 1978). Because ability represents a task-
related, relative construct however, it is hard to specify a perceptual definition. For example,
Vroom (1964) defines a person’s ability to perform a task as “the degree to which he pos-
sesses all of the psychological attributes necessary for a high level of performance excluding
those of a motivational nature” but ignores to describe how abilities are perceived.
Naïve Psychology
With his naïve analysis of action, Heider (1958) demonstrates that the outcome of behavioral
action depends on two components: a personal and an environmental force. Behavioral out-
come is a function of both personal and environmental components and result from their addi-
tive relation. The personal component consists of a motivational factor, determined by a per-
son’s intention and effort, and a multiplicative enabling power factor that reflects a person’s
ability, temperament, etc. In contrast, the environmental component is characterized by the
degree of task difficulty, chance, and luck. To capture common situations, Heider (1958) sug-
gests a regrouping of these components that leads to the concepts of trying (personal motiva-
tional factor) and being enabled (personal power factor plus environmental factor). Thus, per-
sonal inputs to behavioral action comprise one motivational component represented by inten-
tion and effort, which determine the trying for the outcome, and one non-motivational com-
ponent, which reflects the concept of being enabled and encompasses the ability of a person
and the situational factors. In the context of our research, Heider’s research suggests effort
refers to the strength of motivation, which can be perceived explicitly by observing the behav-
ior of a person, whereas ability involves the general aptitude of a person (physically and men-
tally), though his work provides no guidance about perceiving abilities.
Attribution Theory
On the basis of Heider’s (1958) naïve psychology theory, attribution theory analyses the rela-
tionship between personal perceptions and interpersonal behavior (Weinert, 1998) to take into
account people’s perceptions of human interactions. We focus on the attributional research
developed by Bernhard Weiner (1985, 1986) in his attributional theory of motivation and
emotion. Weiner finds that perceived abilities and effort represent the dominant perceptual
causes of human performance (and its outcome) that determine the perceiver’s cognitive, af-
fective, and intentional reactions. This process of attribution occurs particularly in response to
negative, unexpected, or important outcomes (Weiner, 1985, 1986; see also Folkes, 1982;
Weiner and Handel, 1985; Wong and Weiner, 1981).
To incorporate Weiner’s attribution theory into our research task, we must address causal as-
criptions of achievement-related actions and outcomes. In this regard and on the basis of Hei-
der’s work, Weiner identifies four decisive causes: perceived effort and abilities, perceived
luck, and task difficulty (Weiner and Kukla, 1970). However, empirical investigations show
effort and abilities dominate perception, such that “In nearly all reported investigations, how
competent we are and how hard we try are the most frequently given explanations of success
and failure” (Weiner, 1986). The impact of effort and abilities as the perceived causes of ac-
tions and outcomes appears in discussions of the so-called “fundamental error of attribution”
(Gilbert and Malone, 1995; Jones and Davis, 1965; Kelley, 1973; Miller et al., 1981, 1990;
Miller and Rorer, 1982), which argues that people tend to overestimate internal causes (e.g.,
effort, abilities) but underestimate external causes (e.g., fate, luck) when evaluating the behav-
ior and behavioral consequences of others (Werth, 2004). Even when perceivers know about
constraining situational circumstances, they still attribute actions and outcomes to internal
determinants. Therefore, service customers likely attribute a negative outcome to an em-
ployee’s effort and abilities, even when they know that something else, such as a computer
system error, bad weather, or just bad luck, was responsible for it. Jones and Nisbett (1971)
show such internal attributions take place particularly when the attributor is an observer; if he
or she is an actor, the person instead tends to attribute his or her own actions to situational
requirements and therefore makes external attributions. In our context, employees as actors
likely therefore attribute a negative outcome not to their own effort and abilities but rather to
external circumstances.
These three theories underline the central position of effort and ability as behavioral drivers of
human performance and suggest their multiplicative connection. They further explain the psy-
chological consequences (e.g., customer satisfaction) and intentions (e.g., word-of-mouth)
that can result from observers’ perceptions of these drivers. In turn, these theories could make
important contributions to service encounter research by suggesting perceived effort and abili-
ties as behavioral drivers for encounter satisfaction. However, none of the theories can pro-
vide in-depth insights into perceived effort and perceived abilities, because they fail to pro-
vide concrete behavioral cues for representing these two constructs.
Therefore, the first stage of our research is explorative in nature and addresses the following
research questions: (1) Do customers actually perceive service providers’ effort and abilities
during service encounters? (2) What behavioral cues do customers use to determine employ-
ees’ effort and abilities? (3) Do perceived effort and abilities influence encounter satisfaction?
and (4) Do perceived effort and abilities influence customer satisfaction when perceived ser-
vice outcome is statistically controlled?
Whereas the first two research questions focus on exploring the existence and nature of effort
and abilities in a service context from the customer’s point of view, the latter two examine
their influence on encounter satisfaction and thus represent cognitive and emotional evalua-
tions of an interaction (Stauss, 1999). They further take into consideration perceived service
outcome as an additional relevant determinant of satisfaction (e.g., Czepiel et al., 1985;
Grönroos, 1990; Mohr and Bitner, 1995; Parasuraman et al., 1985; Zeithaml et al., 1996).
STUDY 1: CRITICAL INCIDENT STUDY
To explore in depth the constructs of perceived effort and abilities and answer our four re-
search questions in Study 1, we apply a mix of methods. Study 1 therefore combines the ex-
plorative critical incident technique (CIT) with a questionnaire approach before conducting a
formal experiment in Study 2.
Survey Instrument
The survey instrument asks respondents to write a two-page description of a critical incident
with a service provider they had experienced in the past six months. This first part of the sur-
vey instrument does not contain any information about our two constructs of interest. After
writing about the incident, subjects completed a questionnaire that contains a combination of
scales and open-ended questions to probe their perceptions of the described encounter, with a
focus on their perceptions of employees’ effort and abilities and their satisfaction with the
interaction.
We combine critical incident descriptions and survey data for several reasons. First, the CIT,
developed by John Flanagan in 1954 and since then applied in different marketing contexts
(e.g., Pollay, 1985; Swan and Jones Combs, 1976; Zimmer and Golden 1988), captures the
individual and socially interactive nature of a service encounter experience particularly well
(Bitner et al., 1990, 1994; Mohr and Bitner, 1995; Nyquist and Booms, 1987; Stauss and
Weinlich, 1995). The incident reporting reflects subjects’ original thoughts, including their
cognitive, affective, and intentional reactions, but does not force them into a certain pattern,
which results in “‘pure’ customer data. CIT allows marketers to see how customers think”
(Nyquist and Booms, 1987). Therefore, if respondents mention the employee’s effort and
abilities in their reported critical incidents without being asked for it, they freely provide evi-
dence of the relevance and perception of these constructs (research question 1). Second, open-
and close-ended questions about the reported incidents capture and operationalize the nature
of perceived effort and abilities (research question 2). Through a combined analysis of each
critical incident and the questionnaire, we can analyze the relationship of perceived effort and
abilities with satisfaction and outcome measures (research questions 3 and 4). Third, the de-
tailed incident descriptions refresh subjects’ memory, which prompts them to answer the
questionnaire accurately and thus improves the data quality.
Sample
We administered the survey to 150 people with university affiliations (e.g., students, person-
nel). This sample size is sufficient for the exploratory nature of this study. We required that
respondents have experience with service consumption and writing skills that would enable
them to express their experience.
Measures
Critical Incidents. The CIT employs the methodology recommended by several service re-
searchers (e.g., Bitner et al., 1990, 1994; Meuter et al., 2000; Mohr and Bitner, 1995; Stauss,
1994). Respondents report the details of a service encounter incident that fulfills the following
criteria: The incident (1) involved a concise employee interaction, (2) was especially satisfy-
ing or dissatisfying, (3) represented a discrete episode, (4) allowed for a detailed description,
(5) was not more than six months in the past, and (6) showed unambiguous (not alternating)
employee behavior. We place no restrictions on the type of service.
Perceived Effort and Abilities (open-ended). The two open-ended questions ask respondents
to specify the behavioral cues they used to perceive the service provider’s effort and abili-
ties.These questions indicate, from a customer perspective, which behavioral cues form the
focal constructs.
Perceived Effort and Abilities (closed-ended). After responding to the open-end questions,
respondents evaluated 25 items on a seven-point Likert scale, on which 1 represents full
agreement. To measure perceived effort, we adapt 6 items from Mohr and Bitner (1995): at-
tentiveness, energy put into behavior, endeavor, time spent, endurance, and effort itself. To
measure perceived abilities, we derive 19 items from the literature to measure all facets of
perceived abilities, which includes items for perceived methodical, professional, and social
competence (Delhees, 1994; Goleman, 1999; Nerdinger, 1998; Schuler and Barthelme, 1995):
knowledge, competence, ability to organize, self-assurance, credibility, reliability, conscien-
tiousness, self-confidence, eye contact, communication skills, capability, tolerance, patience,
put oneself into the customer’s place, understanding, friendliness, empathy, professionalism,
and abilities. With this question, we develop scales for both perceived effort and perceived
abilities.
Customer Satisfaction. For the context of this study, we define satisfaction as an attitude-like
construct that comprises both cognitive and emotional components (Herrmann and Johnson,
1999; Johnson et al., 1995; Meyer and Ertl, 1996; Oliver, 1993, 1994; Stauss, 1999). We
gather our measurement items from Mohr and Bitner (1995) and Bitner et al. (1990) and ask
respondents to report (1) their overall satisfaction, (2) their satisfaction with the employee,
and (3) their satisfaction with the transaction process on seven-point scales anchored by com-
pletely satisfied and dissatisfied.
Perceived Service Outcome. To measure whether customers obtained their preferred service
outcome during the encounter, we include one item with a seven-point Likert scale that ques-
tions whether, by the end of the incident, respondents received the service they wanted when
they approached the firm (adapted from Mohr and Bitner, 1995; a score of 1 represents full
agreement). Similar to the measures of perceived effort and abilities, this outcome measure
represents a quality judgment and thus differs from satisfaction judgments, which include a
stronger component of individual value in the evaluation.
Demographics. Finally, the questionnaire includes items related to information about the re-
spondents, such as gender, age, and educational level.
Results
Sample. Of the 150 research respondents, 130 correctly completed the critical incident study
and the questionnaire. In terms of demographics, 54.6% were female, and subjects’ ages
ranged from 18 to 70 years with a mean of 30 years of age. One-third of all subjects were stu-
dents, whereas the other two-thirds already had university degrees.
Respondents could write about any service firm, so the selected service types include retail
(28 respondents), railway transportation (18), telecommunication (16), financial institutions
(14), restaurants (14), hairdressers (10), airlines (4), medical institutions (3), car repair (3),
and other (20).
Scales. The satisfaction measure (three items) reveals a mean of 4.23 and a standard deviation
of 2.66. For our reliability check, we compute Cronbach’s coefficient alpha as a measure of
internal consistency. The resulting reliability estimate is quite high for satisfaction (0.96), and
our explorative factor analysis confirms the convergent validity of the scale. The perceived
service outcome measure indicates a mean of 3.57 and a standard deviation of 2.45. As we
expected, the measures of satisfaction and service outcome evince a strong positive correla-
tion (r = 0.767).
Research question 1: Do customers perceive the service provider’s effort and abilities during
service encounters? We use a deductive content analysis to examine the critical incident de-
scriptions and determine whether respondents make spontaneous references to employees’
effort and abilities. As a starting point for analyzing the critical incidents, we use the 25 items
that represent perceived effort and abilities (see Measures) as the categories for a coding
scheme applied by three expert teams. We adjust this coding scheme on the basis of a pretest
of 20 incidents. Furthermore, we apply a two-step approach to the content analysis. First, two
well-trained, two-student expert teams coded the incidents independently. Second, a third
expert team (first and second author) compared any deviant results from the preceding step
and arrived at a final estimate. The percentage of agreement (PoA) (Kolbe and Burnett, 1991)
and measure of interjudge reliability (index of Perreault and Leigh, 1989) are very good, with
PoA = 0.87 and Ir = 0.908 (Gremler, 2004). No additional categories needed to be added to
the coding scheme, which reveals the high content validity of our research (Keaveney, 1995).
The results from the content analysis expose that all 130 incidents contain spontaneous de-
scriptions of perceived effort and abilities that refer to items found in the literature for both
constructs, such as “he was very helpful,” “he was obviously overcharged,” “the employee
spent a lot of time on my concern,” and “he had excellent professional competence.” Thus,
the critical incidents clearly confirm that customers notice employees’ effort and abilities.
Research question 2: What behavioral cues do customers use to determine employees’ effort
and abilities? After describing their critical incidents, respondents answered two open-ended
questions about the behavioral cues they used to perceive that the service provider had shown
or not shown effort and abilities. We apply the CIT coding scheme and a subsequent fre-
quency analysis to analyze these answers.
The respondents perceive our theoretically derived items for perceived effort and abilities but
do not always assign them to their respective theoretical construct. For example, they assign
many items to both perceived effort and abilities, which suggests customers have difficulty
discriminating between constructs. However, for some items, the assignment frequency dif-
fered enough (i.e., frequency difference of 10) that we can clearly assign them to either per-
ceived effort or perceived abilities (see Table I).
6622Technical knowledge / competence
10
0
15
16
22
28
33
39
90
Assignment Frequency to
Perceived Effort
20Self-Confidence / self-assurance
25Abilities
5Flexibility
6Conscientiousness
1Time spent
12Attentiveness
20Friendliness
29Empathy
41Effort / endeavor / energy put into behavior
Assignment Frequency to
Perceived Abilities
Behavioral Cues / Items
Cues clearly assigned to perceived effort
Cues clearly assigned to perceived abilities
Table I: Frequency analysis of behavioral categories and their assignment to perceived
effort and perceived abilities
In particular, respondents generally perceive abilities on the basis of displayed technical
knowledge/competence, abilities themselves, and self-confidence/self-assurance. In contrast,
they consider the displayed effort itself, endeavor, energy put into the behavior, empathy,
friendliness, attentiveness, time spent, conscientiousness, and flexibility as indicators of ef-
fort. This cue assignment indicates that customer perceptions do not completely reflect the
theoretical definitions of perceived abilities and effort; rather, some behavioral cues of abili-
ties appear to represent the effort dimension for customers. In practice, customers almost al-
ways perceive abilities on the basis of cues that represent professional competence. Further-
more, professionalism, which the literature considers a clear synonym for perceived abilities,
gets assigned equally to perceived effort and abilities by customers, so from customers’ per-
spective, professionalism reflects both constructs.
We also conduct a factor analysis (principal component analysis, Varimax rotation) to analyze
the responses to the 25-item battery. After eliminating cross-loading items, we extract a two-
factor result, namely, perceived effort and perceived abilities, which confirms our preceding
findings. The effort factor comprises not only cues derived from effort literature but also be-
havioral cues from social competence literature (e.g., empathy, friendliness).
These findings offer an empirically tested scale for perceived effort and abilities that conflicts
with the current view in the literature. Our final scale of perceived effort contains 11 items
(effort, patience, energy put into behavior, understandability, endurance, time spent, empathy,
friendliness, tolerance, credibility, and endeavor) and shows very high reliability (Cronbach’s
α = 0.97). The mean value of perceived effort is 3.98, with a standard deviation of 2.46. The
final three-item scale of perceived abilities (knowledge, self-assurance, abilities) also reveals
good reliability (α = 0.81), a mean value of 2.98, and a standard deviation of 2.25.
Research question 3: Do perceived effort and abilities influence encounter satisfaction? To
analyze the influence of perceived effort and abilities on customer satisfaction, we regress
satisfaction on these factors. The resulting ß coefficients of both independent components
indicate a positive and significant impact on satisfaction (perceived effort β = 0.752, per-
ceived abilities ß = 0.186, p < 0.001). However, the impact of perceived effort is significantly
greater than that of perceived abilities. The adjusted R2 of 0.78 indicates that 78% of the vari-
ance in satisfaction may be explained by perceived effort and abilities.
Because our theoretical foundation suggests a contingent relationship between perceived ef-
fort and abilities, we integrate the interaction effect into our regression analysis and find a
significant interaction (ß = -0.253, p < 0.001) that explains 3% more of the variance (R2 =
0.81). As Figure 1 reveals, the hybrid interaction suggests perceived effort moderates the im-
pact of perceived abilities on satisfaction.
completely satisfied
dissatisfied
perceived abilities perceived efforthigh low
satis
fact
ion
high perceived effort
low perceived effort
completely satisfied
dissatisfied
satis
fact
ion
high perceived abilities
low perceived abilities
high low
Figure 1: Profile plots indicating the interaction of perceived effort and abilities on satis-
faction
Research question 4: Do perceived effort and abilities influence customer satisfaction when
perceived service outcome is statistically controlled? Finally, our combined regression of the
three quality dimensions of perceived effort, perceived abilities, and perceived outcome (R2 =
0.81) shows that perceived outcome (ß = 0.236, p < 0.001) is more important for explaining
satisfaction than are perceived abilities (ß = 0.120, p < 0.05) but less important than perceived
effort (ß = 0.649, p < 0.001). When we test for the significance of the differences in the ß val-
ues (Howell, 2004), we find no significant results for the three variables; therefore, we inter-
pret the hierarchy with caution.
To examine the influence of perceived effort and abilities on customer satisfaction independ-
ently from perceived service outcome, we perform regression analyses on two subsamples
defined by a median split: subjects who perceived a positive outcome and those who per-
ceived a negative outcome. In both cases, we find a significant and strong impact of perceived
effort on satisfaction (positive ß = 0.736, p < 0.001; negative ß = 0.667, p < 0.001). However,
perceived abilities have a significant impact on satisfaction only for those subjects who per-
ceive a negative service outcome (negative ß = 0.231, p < 0.05; positive ß = 0.126, p < 0.5).
Conclusions from Study 1
Study 1 clearly reveals that customers perceive employees’ abilities and effort and spontane-
ously evaluate whether and how an employee exerts effort or abilities (research question 1).
Our sample judges both perceived effort and abilities positively. However, the specific behav-
ioral cues customers use to assign perceived employee effort and abilities differ from those
provided in current literature. Therefore, we develop two reliable scales for use in further
analyses (research question 2). When we apply these scales, we find that both behavioral con-
structs have a positive and significant impact on customer satisfaction and largely explain
satisfaction, though perceived effort has more relevance than perceived abilities. We also un-
cover a significant interaction effect, which shows that perceived effort acts as a moderator
for the impact of perceived abilities on satisfaction (research question 3). Finally, when we
consider perceived service outcome, we find that perceived effort has a strong and positive
impact, independent of the outcome, whereas perceived abilities are significant only in the
case of negative outcome (research question 4). These results show that subjects who report a
positive outcome think of employees’ abilities only accidentally. This mirrors Weiner’s
(1986) attributional theory of motivation and emotion which suggests that the process of attri-
bution and therefore the causal search for perceived effort and abilities of the employee (fun-
damental error of attribution) is especially instigated by a negative outcome.
STUDY 2: EXPERIMENT
Because we reveal the importance of perceived effort, abilities, and outcome for encounter
satisfaction in Study 1, we conduct Study 2 to develop a deeper understanding of how cus-
tomers perceive effort, abilities, and outcome vis-à-vis. Therefore, we use a discriminant ma-
nipulation of the three variables to examine the impact of perceived abilities, perceived effort,
and perceived service outcome on customer satisfaction with a laboratory experiment.
Hypotheses
Our experimental study relies on five hypotheses, which are based on our conceptual and
theoretical work, as well as the empirical findings from Study 1. Specifically, we argue that
H1: Perceived effort and abilities relate positively to customer satisfaction.
This hypothesis is mainly based on Weiner’s attributional theory of motivation and emotion,
naïve psychology and motivation theory as well as on service research literature (e.g., Mohr
and Bitner, 1995, Parasuraman et al., 1988; Meyer and Mattmüller, 1987) and the results of
Study 1.
H2: The strength of the relationship between perceived abilities and customer satisfaction
relates positively to perceived effort.
Naïve psychology and motivation theory discussed the multiplicative interaction of effort and
ability (Heider, 1958; Vroom, 1960; Vroom, 1964; Lawler, 1966); the hypothesized strength
of effort in this interaction draws back on the results from Study 1 as well as suggestions
coming from motivation theory (e.g., French, 1957).
H3: Perceived service outcome has positive influence on customer satisfaction.
In the service marketing field it is assumed that service outcome is crucial for customer satis-
faction (e.g., Parasuraman et al. 1985; Czepiel et al., 1985).
H4: Perceived effort relates positively to customer satisfaction when the service outcome is
statistically controlled.
With this hypothesis it is suggested that effort as the dominant process variable has an inde-
pendent impact on satisfaction and therefore influences satisfaction beyond its effect on ser-
vice outcome. It is based on service research literature (e.g., Parasuraman et al. 1985; Czepiel
et al., 1985; Grönroos, 1990) as well as results from Study 1.
H5: The influence of perceived abilities on customer satisfaction depends on service outcome.
Weiner’s attributional theory of motivation and emotion suggests that the attribution process
and therefore causal search is particularly initiated when service outcome is negative (e.g.,
Weiner, 2000). Hypothesis H5 combines this insight with results from Study 1; it suggests
that perceived abilities, being a less dominant process variable in comparison to perceived
effort, only impact satisfaction in case of a negative outcome and therefore are outcome de-
pendent.
Research Design and Procedures
To investigate these five hypotheses, we develop a factorial design, with effort (high/low) and
abilities (high/low) as the independent variables and service outcome (positive/negative) and
service type (retail/financial services) as the supplementary variables. Therefore, we apply a 2
× 2 × 2 × 2 design with 16 treatment cells.
Stimuli
We recognize that laboratory experiments are appropriate only when (1) we can create realis-
tic service settings and (2) the simulated service settings can produce the same experience as
an actual service setting (Bateson and Hui, 1992). Therefore, we develop audio-visual stimuli
to account for the multisensory nature of a service encounter to ensure ecological validity.
This realistic presentation of a service encounter through a video stimulus offers control over
the independent variables; it also considers any interfering variables and combines internal
and external validity (Sparks et al., 1997). We create the video stimuli using a scenario tech-
nique and writing specific stage directions for the actors. Respondents watched one scenario
and were to put themselves in the customer’s position. To enhance realism and minimize the
influence of stereotype-related bias in the two service settings, we hired one male and one
female actor and had the videos produced professionally.
To manipulate perceived effort, the employee/actor displayed two different levels of effort
itself, energy put into behavior, endurance, and time spent with the customer during the inter-
actions. The two-level manipulation of the employee’s perceived abilities is based on the dis-
played knowledge, self-assurance, and abilities themselves. Finally, we manipulate perceived
outcome in the retail setting according to whether the customer left the shop with the pullover
he or she wished to buy (positive outcome) or if the pullover was not in stock and therefore
the customer had to leave without it (negative outcome). In a financial service setting, we ma-
nipulate perceived outcome by whether the customer could make a decision about a specific
financial investment (positive outcome) or not (negative outcome). The critical incidents from
Study 1 serve as examples that we use to transform the abstract behavioral items into concrete
behavioral directions for the actors and develop realistic scenarios in the two service settings.
Each video stimulus had a playing time of approximately three minutes.
Sample
In accordance with experimental research quality requirements (Calder et al., 1981, 1982,
1983; Friedrichs, 1990; Kruglanski, 1973; Webster and Kevin, 1971), we administered the
survey to a homogenous student convenience sample with experience with the two service
types. Our total sample size includes 420 students.
Procedures
We ran the experiment for five days, between 9:00 am and 6:00 pm, during a two-week pe-
riod. We randomly assigned participants to one of the sixteen film scenarios (between-
subjects design). Participants watched the film on a big screen (maximum of 15–20 people at
a time) and received no information about the purpose of the study; their instructions only
indicated they were to concentrate on the video stimuli, not talk with other participants, and
fill out the questionnaire after watching the video. At the beginning of each film, a recorded
announcer gave an introduction (service type–specific) and told participants to take over the
customer’s role and concentrate on how they would think and feel in the position of the cus-
tomer in this situation. After having watched the film, they received questionnaires, which
they answered at their own speed.
Measures
We apply a seven-point Likert scale for all measures, on which 1 represents full agreement.
The items measuring satisfaction come from Study 1, and we measure service outcome with
three items: (1) Overall, I got the expected outcome; (2) I got the outcome I intended; and (3)
The aim of my visit was achieved. We measure perceived effort in accordance with the ma-
nipulation of the four items, that is, displayed energy put into behavior, endurance, time spent,
and effort itself. Our measure of perceived abilities includes three items: displayed knowl-
edge, self-assurance, and abilities. Finally, we include additional measures of the realism of
the scenario and the ease with which the respondent imagined him- or herself in the role of
the customer, to determine whether the experimental procedures worked as intended.
Results
Sample. Of the 420 initial questionnaires, we retain 400 for the final analyses (25 per treat-
ment group). Of all respondents, 45.9% are male, and their ages varied between 19 and 50
years with a mean of 24 years of age.
Scales and Validity of the Experimental Procedure. We conduct reliability and validity analy-
ses for each scale in both scenarios and achieve satisfying results. Participants found the sce-
narios realistic (means of 2.71 for retail and 2.93 for financial service) and the role playing
easy (means of 2.43 for retail and 2.38 for financial service).
Manipulation Checks. To test whether our manipulations of perceived effort, abilities, and
outcome were perceived as intended, we ran a one-way ANOVA for each industry grouping.
The findings indicate that the manipulations were successful (effort retail: F(1, 191) = 532.27,
p < 0.001; effort financial services: F(1,192) = 158.03, p < 0.001; abilities retail: F(1,192) =
429.97, p < 0.001; abilities financial services: F(1,191) = 470.77, p < 0.001; outcome retail:
F(1,191) = 713.11, p < 0.001; outcome financial services: F(1,192) = 144.97, p < 0.001).
Hypotheses Testing. We test all five hypotheses using regression analysis and present the re-
sults in Table II. The relationship between perceived effort and abilities and satisfaction is
positive and significant for both the retail setting (perceived effort ß = 0.519, p < 0.001; per-
ceived abilities ß = 0.487, p < 0.001) and the financial services setting (perceived effort ß =
0.340, p < 0.001; perceived abilities ß = 0.594, p < 0.001), in support of H1. However, the
results do not support H2; in the retail setting, our analysis of the interaction effects shows a
significant but ordinal interaction, which means that the main effects of both perceived effort
and abilities can be interpreted and no moderator emerges. In the financial setting, the interac-
tion is also significant, and both main effects are interpretable. Diagrams even show the visi-
ble tendency of the employee’s perceived abilities to moderate perceived effort.
Our analysis of H3 shows that perceived service outcome significantly influences customer
satisfaction in both settings (perceived outcome retail ß = 0.358, p < 0.001; perceived out-
come financial services ß = 0.706, p < 0.001). The independent influence of perceived effort
and abilities on satisfaction, compared with perceived outcome, suggests support for H4 but
not H5. In these experimental conditions, both variables have a significant, positive, and
strong influence on customer satisfaction, independent of perceived service outcome. For the
financial service setting, we find that with statistical control of the outcome, the perceived
abilities of the employee have an even stronger influence on satisfaction than does perceived
effort; in the retail setting, the influence of both determinants remains nearly equal.
Not supported for retail since moderation direction is not as assumed
H2 0,637
p < 0,001-4,891-0,206
Satisfaction Perceived effort xperceived abilities
Supported for financial services
Not supported for financial services
H4
H5
0,617
0,384
p < 0,001p < 0,001
p < 0,005p < 0,001
4,8128,364
3,5886,367
0,3390,590
0,2970,527
Satisfaction, when perceived outcome is positive*
Satisfaction, when perceived outcome is negative*
Perceived effortPerceived abilities
Perceived effortPerceived abilities
Supported for financial servicesH30,495p < 0,00114,0100,706
SatisfactionPerceived outcome
Not supported for financial services since moderation direction is not as assumed
H2 0,620
p < 0,005-3,055-0,132
SatisfactionPerceived effort xperceived abilities
Supported for financial servicesH1 0,603
p < 0,001p < 0,001
7,14212,468
0,3400,594
Satisfaction
Perceived effortPerceived abilities
Financial Service (n=200)
Supported for retail
Not supported for retail
H4
H5
0,621
0,629
p < 0,001p < 0,001
p < 0,001p < 0,001
7,8508,614
9,0287,327
0,4970,545
0,5690,462
Satisfaction, when perceived outcome is positive*
Satisfaction, when perceived outcome is negative*
Perceived effortPerceived abilities
Perceived effortPerceived abilities
Supported for retailH30,124p < 0,0015,3780,358
SatisfactionPerceived outcome
Supported for retail H1 0,594
p < 0,001p < 0,001
11,27010,583
0,5190,487
Satisfaction Perceived effortPerceived abilities
Retail (n=200)
ResultHAdjusted R²
Significance T
TßDependent Variable
Independent Variables
* A median-split of the sample was conducted to classify subjects in groups of positive/negative perceived service outcome.
Table II: Summary of hypothesis test results
Overall, the results support H1, H3, and H4 for both service types. In experimental condi-
tions, we thus show that the impact of perceived abilities on satisfaction increases and even
exceeds that of perceived effort in a financial services setting.
CONCLUSION AND IMPLICATIONS
Our research provides interesting and fundamental insights into customer–employee interac-
tions during service encounters, which represent moments of truth for companies of almost
any kind, because they are manifold in nature and not only apply to pure service companies.
Our results clarify how customer satisfaction during service encounters develops across and
within different service settings and thereby provide implications for human resources, ser-
vice, and sales managers. In addition, the results clearly reinforce the importance of service
delivery process quality for achieving customer satisfaction, as well as that of employee be-
havior for influencing perceptions of effort and abilities, which represent direct determinants
of customer satisfaction.
With Study 1, we demonstrate that perceived employee effort is more important for customer
satisfaction than are perceived abilities, suggesting that managers should focus predominantly
on effort, including performance elements that represent social competence. However, Study
2 indicates that the relative importance of perceived effort and abilities depends on the service
type, which implies differentiated management conclusions. Companies thus must examine
customers’ perceptions of their employees’ encounter behavior in depth to evaluate and effec-
tively and efficiently manage perceived effort and abilities as the main determinants of cus-
tomer satisfaction.
In turn, practitioners should acknowledge behavioral training represents a significant satisfac-
tion management approach. The continuous auditing of perceived effort and abilities should
be a focus of regular satisfaction surveys; our operationalization and development of generic
scales for perceived effort and abilities offer a valuable contribution to this. Also, human re-
source management should include self-evaluation tests for designated encounter employees
regarding the display of effort and abilities in customer-contact situations.
In addition to the content-related implications of this study, we note the importance of our
methodological approach for managers. In combining CIT with a video experiment, we sug-
gest ways that firms can (1) analyze critical encounter interactions in depth from a customer’s
point of view and (2) effectively and efficiently optimize and manage these interactions by
manipulating the relevant behavioral cues. The video stimuli rated by customers (such as in
Study 2) can help firms to consequently implement our results in everyday encounter situa-
tions. First, they provide a means to evaluate hypothetical behavioral changes before the
company undertakes cost-intensive employee training. Second, they serve as training videos
with great didactic value, which help close the organizational and procedural gap between
market research and frontline implementations.
LIMITATIONS AND SUGGESTIONS FOR FURTHER RESEARCH
Similar to any empirical study, our research suffers from several limitations. With regard to
the general applicability of our findings, we note restrictions imposed by the sample charac-
teristics. Because we mainly use university students or persons with university degrees, our
sample does not represent the broad scope of German service customers. Moreover, our data
were collected in Germany, which raises the question of the transferability of our findings to
other cultural regions. Furthermore, we acknowledge the limitation of the methodical ap-
proaches of our two studies. The explorative study (Study 1) samples particularly satisfying
and dissatisfying encounters and eliminates more typical, middle-of the road encounters, so
the results cannot represent the impact of perceived effort and abilities in normal encounters,
which might be of less strength. In addition, the isolated manipulation of the three variables in
Study 2 might overestimate the influence of perceived abilities on satisfaction in the two sce-
narios. In the financial service scenario, the recorded introductions at the start of the movie
stimulus might have overemphasised the impact of perceived outcome on customer satisfac-
tion.
Further research should transfer this study to different cultures. Taking different dependent
variables into account (e.g., customer emotions, customer loyalty and brand perceptions)
might offer a valuable contribution to the fields of service or brand research. In addition, it
seems advisable that further research should consider social stereotypes and their impact on
perceptions of interpersonal behavior and social judgments. Attractiveness, race, age, and
gender can cause stereotypic reactions (Schneider, 2004), so employee appearance might rep-
resent a separate determinant, along with employee behavior, for customers’ effort and abili-
ties perceptions and thus affect satisfaction with a service encounter. Finally, as we noted
from the start, we investigate behavioral cues that represent the constructs of perceived effort
and abilities from a customer’s point of view, which means we disregard the potential influ-
ence of the employee’s personality as a behavioral predisposition. Additional research there-
fore might investigate if and how personality traits influence employees’ behavior and, in
turn, the perceived effort and abilities of an employee.
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