Journal of Hospitality & Tourism
Research
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Investing in Interactional Justice: A Study of the Fair Process Effect within a Hospitality Failure Context
Thérèse A. Collie, Beverley Sparks and Graham Bradley
Journal of Hospitality & Tourism Research 2000 24: 448
DOI: 10.1177/109634800002400403
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JOURNAL
Collie
et al.OF
/ INTERACTIONAL
HOSPITALITY & TOURISM
JUSTICE RESEARCH
INVESTING IN
INTERACTIONAL JUSTICE:
A STUDY OF THE FAIR PROCESS
EFFECT WITHIN A HOSPITALITY
FAILURE CONTEXT
Thérèse A. Collie
Beverley Sparks
Graham Bradley
Griffith University, Gold Coast
Past research has demonstrated that considerations of distributive, procedural, and
interactional justice independently influence customers’ fairness and satisfaction ratings
in many contexts. Other research shows evidence of a “fair process” effect—a tendency for
customers to be more accepting of poor outcomes when they perceive the outcome allocation process to be fair. Van den Bos, Lind, Vermunt, and Wilke (1997) have reported that this
effect may operate only when the outcomes received by others are unknown. Set in a hospitality service recovery context, this study examined the impact of interactional justice and
knowledge of others’ outcomes on customers’ service evaluations. A 2 (interactional justice) 4 (others’ outcomes) experimental design was employed in which 176 respondents
reported their perceptions of fairness and levels of satisfaction after imagining themselves
to be customers in a hypothetical service scenario. Contrary to previous research, evidence
of the fair process effect was found irrespective of the presence or absence of information
regarding others’ outcomes. Implications for the tourism and hospitality industry and justice theory development are discussed.
KEYWORDS: justice theory; fairness perceptions; customer satisfaction; service recovery.
One of the authors recently had the following experience:
While attending an overseas conference held at an island resort hotel, the
author made a short (3-minute) phone call to her husband. On checking out of the
hotel the following day, the author discovered she had been charged $68 for the
call. She drew this apparent overcharging to the attention of the hotel clerk, and
subsequently to the clerk’s supervisor, who politely agreed that the amount was
excessive and immediately reduced the cost of the phone call to $37—a 45%
reduction! (Point A)
Journal of Hospitality & Tourism Research, Vol. 24, No. 4, November 2000, 448-472
© 2000 International Council on Hotel, Restaurant and Institutional Education
448
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Later that day, while waiting in line in the local airport departure lounge, the
author struck up a conversation with a fellow traveler who happened to be returning home after attending the same conference at the same hotel. The author related
her story of the discounted phone charge. Her colleague responded that the same
thing had happened to her, and she had received a 75% reduction in the price of her
phone bill. (Point B)
Seeing the author’s reaction, she hastily added, “But, listen to this: I know of
another delegate who was required to pay the full amount, despite lodging a similar protest!” (Point C)
How would you feel as the customer at Points A, B, and C in the above story?
Would you think the hotel staff had treated you fairly? Would you be satisfied with
the service provided? Would you return to this hotel on subsequent visits to the
island? And, more central to the theme of the present article, would your answers
have been any different if, instead of the polite treatment you received, the hotel
staff had spoken to you in a discourteous and dismissive manner?
Justice is one of the most important concepts receiving attention in the social
and organizational psychology literature (Bazerman, 1993; Cropanzano &
Greenberg, 1997). It is important that the application of justice theory to service
settings such as in the tourism and hospitality industry is also an emerging
research domain (see, e.g., Blodgett, Hill, & Tax, 1997; Bowen, Gilliland, &
Folger, 1999; Hocutt, Chakraborty, & Mowen, 1997; Sparks & McColl-Kennedy,
2000). Indeed, the theoretical frameworks underpinning justice research offer
extensive opportunities for better understanding hospitality encounters, especially service failures. This article draws on theory and research into justice to
learn more about the ways in which customers evaluate their experiences of service failure. To achieve this, we explore hospitality customers’ satisfaction and
fairness judgments when they either do or do not have information about the sort
of compensation other customers have received in similar situations. In addition,
we examine the extent to which the nature of the interaction between customer
and service provider affects customer reactions when varying amounts and types
of information are available. Thus, we seek to demonstrate the usefulness and
importance of interactional justice in recovering service failures within a hospitality setting.
Service Failures and Recovery
The hospitality industry exhibits many of the classic service characteristics
(e.g., intangible product, simultaneous production and consumption) that make
100% zero-defect service delivery virtually impossible. Following a failure in the
delivery of a service, organizations frequently attempt to retrieve the situation by
identifying and responding to customer needs and expectations (Bell & Zemke,
1987). More formally, this process of service recovery has been defined in terms
of tactics aimed at “returning aggrieved customers to a state of satisfaction with
the organization after a service . . . has failed to live up to expectations” (Zemke &
Bell, 1990, p. 43). Service recovery is important because there is evidence to suggest that when a service delivery system fails, customers’ satisfaction or dissatisfaction levels and their word-of-mouth and return intentions are dependent on the
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content or form of the employee response (Bitner, Booms, & Tetreault, 1990;
Blodgett & Granbois, 1992). If these efforts do not meet customers’ needs and
expectations, the resultant dissatisfaction may have serious long-term negative
consequences for the service organization (Boshoff, 1999; Tax & Brown, 1998).
In contrast, appropriate recovery responses to service failures can create satisfied
and loyal customers (Brown, Cowles, & Tuten, 1996). Devising a sound understanding of the efficacy of alternative service recovery tactics is vital to the industry. One potentially productive approach to increasing our understanding of customer evaluations and intentions following service failure comes from the body of
theory and research into justice.
Justice Theory and Research
Justice, as treated by social and organizational scientists, is defined
phenomenologically; an act is considered “just” because someone perceives it as
such (Bazerman, 1993; Cropanzano & Greenberg, 1997; Folger & Cropanzano,
1998; Leventhal, 1980; Seiders & Berry, 1998). Contemporary theories of justice
date back more than 30 years. Early theorizing focused on distributive justice
(Homans, 1961); that is, people’s perceptions of the fairness of the outcomes they
receive or resource distribution decisions (e.g., Adams, 1963).1 A second wave of
justice inquiry, heralded by the seminal work of Thibaut and Walker (1975), demonstrated that an individual’s response to the allocation of resources was also
influenced by the fairness of the allocation process, or procedural justice (e.g.,
Korsgaard, Schweiger, & Sapienza, 1995). In short, distributive justice concerns
the fairness of ends, and procedural justice emphasizes the means used to achieve
those ends (Greenberg, 1987, 1990).
More recently, researchers have described types of unjust treatments that can
not be easily subsumed under the traditional concepts of procedural or distributive
justice (e.g., Lind & Lissak, 1985; Mikula, 1986). Many (e.g., Blodgett et al.,
1997; Clemmer & Schneider, 1996; Tax, Brown, & Chandrashekaran, 1998), but
by no means all (see, e.g., Greenberg, 1990), contemporary justice theorists recognize the existence of a third dimension of justice. Most notably, Bies and his
colleagues (e.g., Bies, 1987; Bies & Moag, 1986; Bies & Shapiro, 1987; Folger &
Bies, 1989; Tyler & Bies, 1990) argued that fairness concerns regarding how a
decision maker behaves during the enactment of procedures denotes people’s
concern for interactional justice. This interactional (or social) form of justice
relates to the informal and dynamic aspects of outcome allocation procedures and
particularly refers to those aspects of an exchange that concern communication
processes and the treatment of individuals (e.g., courtesy, respect, explanations)
(Cropanzano & Greenberg, 1997). By contrast, the term procedural justice is now
frequently used to refer to the perceived fairness of the policies, procedures, and
other structural criteria used by decision makers to arrive at an outcome (Blodgett
et al., 1997).
The motivation for researchers to study procedural and interactional justice
arises from the belief that issues other than outcomes shape perceptions of fairness (Lind & Tyler, 1988). Indeed, a considerable body of research evidence demonstrates that all three of these dimensions of justice—distributive, procedural,
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and interactional—independently affect fairness, satisfaction, and other evaluations (Clemmer & Schneider, 1996; Cropanzano & Greenberg, 1997; Greenberg,
1987; Lind & Tyler, 1988). Furthermore, researchers have provided intriguing
evidence as to the interactive effects of the combination of these justice elements
(Brockner & Wiesenfeld, 1996). Indeed, one of the most robust findings in social
and organizational psychology is the “fair process effect,” whereby outcome evaluations and subsequent behavior are moderated by perceptions of process justice.
Put another way, the fair process effect suggests that if people consider a procedure to be fair, they are more accepting of its consequences (Folger &
Cropanzano, 1998; Kim & Mauborgne, 1997). (For a summary of studies demonstrating this effect, see Van den Bos, Lind, Vermunt, & Wilke [1997].)
The implications of the operation of this effect are quite profound. If people are
more willing to tolerate an unfavorable outcome if delivered in a fair manner, then
organizations can control the damage caused by the implementation of tough
decisions by ensuring that the decision-making process, and the ways in which
these decisions are communicated, are beyond reproof. The fair process effect
thus has potential applications in a diverse range of organizational contexts. These
range from situations where organizations decide to restructure, downsize, or
relocate, to those where customer loyalty is placed at risk by the need to withdraw
previously offered services.
The Ubiquity of the Fair Process Effect
Given the wide-ranging implications of the fair process effect, there is a need
for researchers to explore and clarify the parameters under which it operates.
Indeed, recent research evidence has cast doubt on the ubiquity of the effect. In an
innovative experiment, Van den Bos, Lind, and colleagues (1997) used a computer-based simulation to manipulate participants’ exposure to two kinds of information: First, the participants received varying information regarding the outcomes received by other people in similar situations (social comparison equity
information), and second, they received varying information regarding the outcome allocation process (procedural justice information). Van den Bos, Lind, and
colleagues predicted that the fair process effect would be found only in conditions
where participants could not rely on social comparison equity information to
make judgments of outcome fairness and satisfaction. Their hypothesis was supported: When the referent other person’s outcome was not known, the fair process
effect was evident; that is, procedural justice information influenced the participants’ evaluations. However, when the other’s outcome was known, and irrespective of whether the other’s outcome was better, worse, or equal to the participant’s
outcome, there was no evidence of a fair process effect: Ratings of outcome fairness and satisfaction did not significantly differ between conditions of fair and
unfair procedures. In other words, in the presence of social comparison data, procedural justice information appeared redundant: Participants used the information about others’ outcomes to make their evaluations, rather than being influenced by information regarding the fairness of procedures. See Figure 1 for an
overview of Van den Bos, Lind, and colleagues’ findings. Similarly designed
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Figure 1
Representation Indicative of Van den Bos, Lind, Vermunt,
and Wilke’s (1997) Fairness and Satisfaction Ratings
additional tests of their hypothesis replicated these results (Van den Bos, Lind, et al.,
1997; Van den Bos, Wilke, Lind, & Vermunt, 1998).
To explain their results, Van den Bos, Lind, and colleagues (1997) argued that
generally people do not have access to information about other people’s outcomes. Accordingly, people are typically compelled to rely on information that is
available; namely, procedural justice data (Van den Bos, Lind, et al., 1997; Van
den Bos, Wilke, et al., 1998). Thus, in most conditions, others’ outcomes are
unknown, and so procedural justice data are used, in a heuristic manner, to shape
impressions of overall fairness and satisfaction (Van den Bos, Lind, et al., 1997;
Van den Bos, Wilke, et al., 1998). On the other hand, in those rare circumstances
where information regarding the outcomes received by others is available, this
information is given greater weight than procedural data in the formation of justice evaluations (Van den Bos, Lind, et al., 1997). In such situations, people place
limited reliance on procedural justice information, and their outcome judgments
show no evidence of the fair process effect.
Van den Bos and colleagues’ evidence and arguments regarding the limitations
of the fair process effect are, at first glance, quite appealing. However, there are
several reasons for caution and for further pursuit of this line of research. First,
Van den Bos and colleagues’ (1997, 1998) studies are limited by their use of single-item scales to measure the dependent variables. Such an approach potentially
undermines the reliability, precision, and content validity of their fairness and satisfaction measures (De Vaus, 1995). Replication using well-established multiitem scales is warranted. Second, Van den Bos, Lind, and colleagues (1997)
tempered their conclusions by emphasizing that there may be “some, as yet
unidentified conditions” (p. 1043) where social comparison equity information is
present, yet strong effects of procedures on outcome evaluations occur. Hence,
there may be value in seeking to identify such conditions. Third, there is an impor-
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tant limitation to the external validity of Van den Bos and colleagues’ (1997,
1998) findings. In these studies, the operationalization of process justice was
exclusively structural in nature. Participants were informed either that they did or
did not have input (“voice”) into the outcome allocation decision. There was no
direct human contact: Participants’ opportunities for input (or lack thereof) were
through a computer interface. Hence, issues of interactional justice were effectively eliminated from the experimental task. This exclusive focus on procedural
justice leaves open the issue of whether Van den Bos and colleagues’ conclusions
can be generalized to other contexts and forms of process justice. There is a need,
therefore, for further research that operationalizes justice in interactional, rather
than procedural, fairness terms.
Service Provision in the Tourism and Hospitality
Sector: The Role of Justice in Customer Evaluations
Until recently, most of the research into justice issues was situated in workplace and legal contexts. However, the past decade has seen a growing interest in
the application of justice theories to service encounters (see, e.g., Clemmer &
Schneider, 1996; Sparks & McColl-Kennedy, 2000; Tax, 1993). Much of this
early interest initially focused on outcome fairness rather than procedural and
interactional justice. Nevertheless, like the workplace and legal contexts, all
forms of justice are now seen as relevant to service settings (Clemmer & Schneider, 1996). This interest in the application of a justice framework to service industries has come about because of a recognition of the contribution the perspective
can make to understanding the nature and dynamics of the service provider–customer relationship.
The provision and receipt of services within the hospitality and tourism sector
involves an exchange between customer and service provider. Both parties
receive (and presumably assess) an outcome, and both recognize (and presumably
evaluate) the existence of formal structures (e.g., hours of opening, modes of payment, queuing systems, refund policy, complaint handling procedures) that regulate the process of outcome allocation. Thus, considerations of distributive and
procedural justice potentially affect customer (and staff) evaluations. At its core,
however, the service encounter is social in nature; fundamentally, it involves one
human being interacting with another (Czepiel, 1990; Czepiel, Solomon,
Surprenant, & Gutman, 1985; Mattsson, 1994; Price, Arnould, & Tierney, 1995;
Siehl, Bowen, & Pearson, 1992). Moreover, services, such as those in the tourism
and hospitality industry, rely heavily on the service provider’s interpersonal skills
(Nikolich & Sparks, 1995). Indeed, it is the quality of interpersonal interaction
between the customer and contact employee that often influences customer evaluations of services (Bitner, Booms, & Mohr, 1994; Iacobucci, Ostrom, & Grayson,
1995; Schneider & Bowen, 1985; Schneider, Parkington, & Buxton, 1980).
Support for this view is provided by Price, Arnould, and Deibler (1995), who
found that failure to meet minimum standards of civility in a service encounter
(i.e., a failure to meet interactive justice standards) induced negative emotional
responses in customers “more than any other service provider performance factor” (p. 49). Similarly, in their recent review of the psychological literature on
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interpersonal emotions in services, Dubé and Menon (1998) highlighted the critical role of socialization in forming consumer–provider interpersonal exchanges.
Hence, feelings of satisfaction with service encounters are widely thought to be
influenced by the level of service provider adherence to fair and consistent behavior patterns (Solomon, Surprenant, & Gutman, 1985). Furthermore, the failure of
a service employee to adhere to norms of service behavior may have important
consequences for his or her customers. Lovelock, Patterson, and Walker (1998)
argue that seemingly uncaring or rude behavior toward a customer by service staff
may violate the customer’s self- esteem “because the customer feels they should
be treated with more respect” (p. 450). These authors argue that such poor treatment (which could be characterized as low levels of interactional justice) violates
basic human needs such as fairness and a sense of self-worth and may result in
customer complaints in an effort to restore self-esteem.
The role of front-line service employee behavior in customer–service provider
interactions is especially crucial in service recovery situations (Boshoff, 1997;
Johnston, 1995; Tax, 1993; Tax & Brown, 1998). Research into service recovery
has demonstrated that customers’ perceptions of interactional justice are particularly salient when service fails (Bowen et al., 1999; Sparks & McColl-Kennedy,
2000). Goodwin and Ross (1989), for instance, found that if a customer complained about a service failure, both rudeness and the style of interaction strongly
influenced ratings of perceived fairness. A more recent service failure study by
Tax and his colleagues (1998) also found that the most pervasive customer service
expectations concerned courtesy and empathy. Likewise, an experiment by
Hocutt and colleagues (1997) showed that interactional justice–oriented service
recovery attempts (i.e., prompt, courteous service employees) led to higher satisfaction ratings than when interactional justice was low. These results prompted
Hocutt and colleagues (1997) to suggest that in service recovery, interactional justice concerns may be more important than distributive justice issues. Similarly,
Sparks and McColl-Kennedy (2000) found that in service recovery, positive demonstrations of interactional justice (such as politeness and concern) on the part of a
service provider resulted in high ratings of fairness and satisfaction.
There is, therefore, quite a large body of research evidence to support the belief
that, contrary to Van den Bos and colleagues’ findings, considerations of interactional justice influence outcome judgments irrespective of the presence or
absence of information regarding the outcomes received by other customers.
Folger and Cropanzano’s (1998) Fairness Theory offers insights into possible
mechanisms through which interactional justice has this pervasive (fair process)
effect. This theory emphasizes the underlying cognitive mechanism of “counterfactual thinking” in the assignation of moral accountability to those responsible
for the allocation of outcomes (Folger, 1993). Counterfactual is literally defined
as “counter to the facts” (Roese, 1997), or thinking “what might have been”
(Roese & Olson, 1997, p. 1). Thus, when evaluating the fairness of another’s
actions, an individual might imagine possible alternative behaviors and assess
whether any of the alternative actions would have been morally superior (Folger &
Cropanzano, 1998). For example, if an individual experiences discourteous treatment (i.e., low levels of interactional justice), they might easily imagine that it
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would have been feasible for the other party to have acted courteously, and that
such courtesy would be more in keeping with prevailing moral precepts.
According to this theory, when unfairness is perceived, an aggrieved party
seeks to determine culpability for the offense (i.e., who is to blame) and the
motives and intentions of the perceived offender. Moral accountability is then
assigned to the offending person or agency. Folger and Cropanzano (1998) posit
that interactional justice may prove to be a more important moderator of reactions
to unfairness than either procedural or distributive justice, because greater ambiguity potentially exists as to the moral accountability of both procedural structures and tangible outcomes. On the other hand, because of the immediacy and
transparency of social interactions, it may be relatively easier to assign moral
accountability when interactional justice principles are violated (Folger &
Cropanzano, 1998). To extrapolate somewhat, customers participating in a service encounter are likely to be in direct and immediate receipt of interactional justice information, and are more likely to use this information to assign moral
accountability than to use other more ambiguous distributive and procedural justice information. There is, however, little empirical evidence directly supporting
Fairness Theory, and even less supporting the speculative extrapolations of the
theory proposed here.
Aims and Hypothesis
In summary, it is widely accepted that perceptions of a fair process influence
outcome evaluations. Van den Bos and colleagues (1997, 1998) have reported evidence and proposed arguments indicating that this effect does not hold when
information regarding others’ outcomes is available. However, both of Van den
Bos and colleagues’ studies were limited in several ways. Specifically, these
researchers operationalized process justice in exclusively structural terms, performed their tests in an impersonal context, and used single-item dependent measures. Both past research into the service encounter and Fairness Theory (Folger &
Cropanzano, 1998) suggest that considerations of interactional justice are crucial
in service recovery situations, and that these considerations will influence outcome evaluations regardless of the presence or absence of information regarding
others’ outcomes.
The aim of the current study was to investigate whether Van den Bos and colleagues’ (1997, 1998) results generalize to contexts where interpersonal aspects
of an exchange are salient. To answer this question, we tested the impact of
interactional justice and distributive social comparison equity information on
evaluations of outcome fairness and satisfaction within a hospitality service
recovery setting. In an adaptation of Van den Bos and colleagues’ (1997, 1998)
methodology, we held constant procedural justice and the participants’ outcomes
while experimentally manipulating both interactional justice (either high or low)
and knowledge of others’ outcomes (either a referent other’s outcome is unknown
or it is equal, better, or worse than that of the focal customer). This latter manipulation has ecological validity within the tourism and hospitality context because,
although there are many occasions when customers are unaware of the outcomes
received by others, there is a similar number of situations when customers have
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the opportunity to observe (or hear about), for example, the size of another customer’s restaurant meal, the prices others paid for a package tour, or the compensation others received for delayed hotel check-ins. The story that introduced this
article is a case in point.
Given the limitations of Van den Bos and colleagues’ (1997, 1998) research
and the evidence suggesting that interactive justice considerations are central to
customer evaluations in service recovery situations, we put forward the following
hypothesis:
Hypothesis: Customer evaluations of fairness and satisfaction will vary significantly
with the level of interactional justice, regardless of whether the outcome of others
is known.
A finding in support of this hypothesis would have several implications. First,
such a finding would suggest that interactional justice functions differently from
procedural justice when social comparison equity information is available. This
would serve to strengthen the case for maintaining a theoretical and empirical distinction between these two dimensions of justice. Second, this finding would suggest that it may be premature to accept Van den Bos and colleagues’ conclusion
concerning the redundancy of information regarding nondistributive forms of justice when others’ outcomes are unknown. Third, the finding would underscore the
need for service organizations to implement management, selection, and training
policies aimed at the maintenance and enhancement of customer evaluations of
interactional justice. If, on the other hand, Van den Bos and colleagues’ finding is
replicated using an interactional justice manipulation within a service recovery
context, none of the above would follow. Rather, the implication would appear to
be that organizations that are able to communicate social comparison equity information to their customers will achieve little further advantage in investing in the
promotion of interactional justice.
METHOD
Design
A 2 (interactional justice [IJ]: high or low) × 4 (others’ outcomes [OO]:
unknown, better, worse, equal) independent groups factorial experimental
research design was utilized. Four dependent variables (DVs) were measured: (a)
outcome fairness, (b) satisfaction, (c) word-of-mouth (WOM) intention, and (d)
return intention.
Participants
A convenience sample of 176 university undergraduate students (114 women,
61 men, and 1 of unspecified gender) enrolled in a 1st-year psychology course
acted as participants. The mean age of the participants was 21.1 years (SD = 4.19).
Participants received course credit for participating in the experiment. The use of
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457
students for such research can be justified on the grounds that the task was one that
the respondent was likely to identify and be familiar with given the context.
Materials
Scenarios
Experimental scenarios have proved valuable in the study of subjective reactions to procedures (Lind & Tyler, 1988) and are used extensively in both justice
and services (including hospitality and tourism) research (see, e.g., Barling &
Phillips, 1993; Bitner, 1990; Boshoff, 1997; Brown et al., 1996; Goodwin & Ross,
1992; Hocutt et al., 1997; Mattila, 1999). Hence, eight service recovery scenarios
were specifically developed for this study through two pilot studies. The scenarios, set in a theme park restaurant, were identical except for manipulations of the
two independent variables (refer to the Appendix for complete scenario text). In
all scenarios, procedural justice was held constant and operationalized as the customers being given a formal opportunity to verbally state what outcome he or she
would prefer and complete a written feedback card. In all versions of the scenario,
the restaurant attendant’s gender and age were not revealed, the customer paid $8
for the meal, and the customer later discussed the price paid by other students for
an equivalent meal.
Independent Variables
The four OO conditions were operationalized as (a) unknown: the customer
was unaware of the cost of the other students’ meals; (b) better: the other students
paid $4 each for their meals; (c) worse: the other students paid $12; and (d) equal:
both the customer and other students paid $8. In the high interactional justice conditions, the service provider (the restaurant attendant) displayed courtesy, concern, and empathy toward the customer, whereas low interactional justice was
operationalized as a rude service provider who displayed no concern or empathy
toward the customer.
Dependent Measures
The DVs (outcome fairness, satisfaction, and WOM and return intentions)
were measured using multi-item scales, with each item requiring a response on a
7-point continuum (1 = very unfair/dissatisfied/unlikely, 7 = very fair/satisfied/likely). A recent scenario-based experiment by Blodgett and colleagues
(1997) provided the scales for three of the DVs: outcome fairness, and WOM and
return intentions. The scales used by Blodgett and colleagues were considered
reliable (reported alphas of .92, .87, and .91 respectively). The multi-item satisfaction scale was adapted from Oliver and Swan (1989) because this scale has
been successfully utilized in other recent service fairness studies (e.g., Sparks &
McColl-Kennedy, 2000; Tax et al., 1998). Additional 7-point scale items were
used to check the manipulation of the independent variables and the perceived
believability of the scenarios.
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Table 1
Scale Reliabilities and Descriptive Statistics
M
SD
Number
of Items
α
4.33
3.27
6.3
1.22
1.66
.7
4
12
5
.74
.97
.79
5.32
1.33
1.19
0.51
4
4
.96
.96
Scale
Outcome fairness
Satisfaction
Believability manipulation check
Interactional justice manipulation check
High
Low
Note: All items were measured on a 7-point scale; higher values indicate more positive ratings of the dependent variable in question.
Procedure
Participants were randomly allocated to one of the eight experimental conditions (n = 22 per condition). A booklet containing the appropriate version of the
service scenario and the series of questions measuring the DVs, as well as several
items providing manipulation and believability checks, was issued to each participant. Participants were instructed to read the scenarios, imagine that the scenarios
depicted had happened to them in the role of the customer, and answer the series of
questions as if they were the customer. Participants completed the task in small,
noninteracting groups under the supervision of the researchers.
RESULTS
Preliminary Analyses
Because the reliability coefficient (α) for the scales used exceeded 0.7, all
scales were considered reliable (De Vaus, 1995) (see Table 1). Prior to the application of the primary multivariate analysis of variance (MANOVA) technique, preliminary data screening was conducted (per Hair, Anderson, Tatham & Black,
1995). To ensure assumptions of MANOVA were met, 12 cases were deleted.
Thus, in total, 164 cases were available for the main analyses.
Bivariate correlations of the four DVs showed significant correlations among
all DVs. The associations between satisfaction, return intentions, and WOM
scales were considered excessive (r > .85) and, in accordance with the approach
adopted in past research (see, e.g., Clemmer, 1993), the scales were averaged to
form a single satisfaction scale. The use of an expanded satisfaction scale that
incorporates behavioral intention items is consistent with the practice adopted in
previous research (see, e.g., Goodwin & Ross, 1992). Hence, all subsequent analyses were based on two DVs: (a) outcome fairness, and (b) the expanded satisfaction scale. Table 1 presents the descriptive statistics for these two DVs.
2
Manipulation Checks
Analysis of the manipulation check variables demonstrated that independent
variable manipulations (IJ and OO) and the procedural justice constant were both
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Table 2
Tests of Interpersonal Procedural Justice, Others’ Outcomes, and Their Interaction
IV
IJ
OO
IJ × OO
DV
Outcome fairness
Satisfaction
Outcome fairness
Satisfaction
Outcome fairness
Satisfaction
Univariate F
a
99.21
359.58a
7.05a
1.86
0.78
0.42
df
Stepdown F
df
α
1,156
1,156
3,156
3,156
3,156
3,155
99.21***
158.25***
7.05***
0.22
0.78
0.8
1,156
1,155
3,156
3,155
3,156
3,155
.025
.025
.025
.025
.025
.025
a. Significance level cannot be evaluated but would reach p < .001 in a univariate context.
***p < .001.
perceived as intended by respondents. In addition, the results indicated that participants perceived the scenarios as believable (see Table 1).
Main Analyses
A significant multivariate effect was indicated for interactional justice, F(2,
155) = 178.73, p < .001, and for others’ outcomes, F(6, 312) = 3.43, p < .01, suggesting that there were significant differences between both IJ and OO conditions
for the dependent variables measured. The multivariate IJ by OO interaction was
not significant, F(6, 312) = .79, p = .58. The results suggest a strong association
between IJ and the combined DVs, partial η2 = .7, and a more modest association
between OO and the DVs, partial η2 = .06.
Because the results of Bartlett’s test of sphericity indicated significant interrelations among the dependent variables (p < .001), the Roy-Bargmann stepdown
analysis was used to assess the impact of interactional justice and others’ outcomes on each of the dependent variables (Tabachnick & Fidell, 1996). Because
the main theoretical thrust of the current research is justice, outcome fairness was
the dependent variable initially tested, followed by the second dependent variable, satisfaction. The stepdown analysis assumption of homogeneity of regression was tested at the stringent level of α = .01 (Tabachnick & Fidell, 1996) and
found to be satisfactory (for the satisfaction scale, F(7, 148) = 2.4, p > .01). The
results of univariate and stepdown analyses are summarized in Table 2.
The stepdown analyses revealed that ratings of outcome fairness made a
unique contribution to differences between levels of OO, stepdown F(3, 156) =
7.05, p < .001. After the variability due to outcome fairness was entered, satisfaction did not add to the effect of OO, stepdown F(3, 155) = 0.22, p = .88). However,
more central to the focus of the current study, the results of the stepdown analyses
reveal a unique contribution to the prediction of differences between high IJ and
low IJ participants by both outcome fairness, stepdown F(1, 156) = 99.21, p <
.001, and satisfaction, stepdown F(1, 155) = 158.25, p < .001. Therefore, the testing of the hypothesis proceeded utilizing both DVs.
Evaluation of the hypothesis that IJ will affect the dependent variables regardless of the level of OO required the creation of a dummy variable labeled “group.”
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Figure 2
Group Means for Dependent Variable Outcome Fairness
Thus, there were eight groups representing the experimental conditions, which
enabled a one-way analysis of variance (ANOVA) and a series of four planned
orthogonal contrasts to be conducted per DV. To control for Type I error, the
results of each paired contrast were evaluated using Bonferroni’s correction (α =
.0125). Graphical representations of the group means are presented in Figure 2
(outcome fairness) and Figure 3 (satisfaction).
For the first DV, outcome fairness, Levene’s test for homogeneity of variances
was not significant (p > .05), so the pooled variance estimate t tests were interpreted for the contrasts performed. The first planned contrast involved participants in the two OO unknown conditions. It showed that in keeping with previous
fair process findings, mean ratings of outcome fairness were significantly higher
for participants in the high IJ condition (M = 5.32) than those in the low IJ condition (M = 4.11), t(156) = 4.2, p < .001. This finding replicates that of Van den Bos,
Lind, and colleagues (1997). The second contrast between OO better participants
showed that for those in the high IJ condition, the mean outcome fairness rating
(M = 4.43) was significantly higher than low IJ participants’ mean outcome fairness rating (M = 3.16), t(156) = 4.35, p < .001. The third planned contrast involved
participants in the OO worse conditions. Again, significantly higher outcome fairness ratings were found for those in the high IJ condition (M = 5.31) than low IJ
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Figure 3
Group Means for Dependent Variable Satisfaction (expanded)
participants (M = 3.54), t(156) = 6.09, p < .001. Likewise, the final planned contrast concerning those in the OO equal conditions showed that high IJ (M = 5.06)
participants perceived their outcomes as significantly fairer than low IJ participants (M = 3.57), t(156) = 5.3, p < .001.
A similar pattern of results was observed for the second DV, satisfaction. However, because Levene’s test for homogeneity of variances was significant (p <
.05), the heterogeneous variance t tests were interpreted for the contrasts performed. The first planned satisfaction contrast also showed the fair process effect,
with mean ratings of satisfaction significantly higher for participants in the high
IJ, OO unknown condition (M = 4.85) than for those in the low IJ, OO unknown
condition (M = 2.0), t(35.96) = 11.01, p < .001. The second contrast between OO
better conditions showed that high IJ participants’ mean satisfaction rating (M =
4.22) was significantly higher than low IJ participants’ mean satisfaction rating
(M = 1.71), t(27.44) = 9.76, p < .001. The third planned contrast involved OO
worse participants and also demonstrated significantly higher satisfaction ratings
for those in the high IJ condition (M = 4.59) than low IJ participants (M = 1.9),
t(29.55) = 8.75, p < .001. As was the case for all previous comparisons, the final
planned satisfaction contrast, which related to the OO equal conditions, similarly
found that high IJ participants (M = 4.8) were significantly more satisfied than low
IJ participants (M = 1.85), t(33.19) = 9.42, p < .001.
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DISCUSSION
The current study investigated the fair process effect under conditions of varying knowledge of others’ outcomes. Levels of interactional justice were manipulated in a series of scenarios depicting face-to-face service recovery encounters
set in the hospitality sector. Consistent with the hypothesis, it was found that irrespective of whether participants were aware or unaware of the outcomes of others,
participants in conditions where the service provider was courteous and respectful
(high IJ) perceived significantly higher levels of outcome fairness and reported
significantly higher levels of satisfaction than participants in conditions where the
service provider was rude and disrespectful (low IJ). Thus, the fair process effect
was observed—interactional justice did make a difference—across all outcome
conditions.
These findings demonstrate that outcome evaluations are influenced by
interactional elements even though information about others’ outcomes is available. More specifically, the results indicate that, at least within a hospitality service recovery setting, the interpersonal treatment of customers significantly
affects evaluations of outcome fairness and satisfaction even when information
about others’ outcomes is known. Thus, it appears that the present study’s focus
on interactional fairness within a service recovery context has revealed at least one
of the hitherto “unidentified conditions” to which Van den Bos, Lind, and colleagues (1997, p. 1043) alluded, where strong effects of procedures on outcome
judgments are found despite the presence of social comparison equity information. Accordingly, it also appears that Van den Bos, Lind, and colleagues’ (1997)
proposition concerning the redundancy of process information when social comparison equity data are present does not generalize to the present context.
In contrast to the strong effect associated with interactional justice, the others’
outcomes manipulation yielded a more modest result. Although the multivariate
effect associated with others’ outcomes was statistically significant, the stepdown
test revealed that this effect was significant for fairness but not for satisfaction.
Apparently, knowledge of others’ outcomes influenced participants’ evaluations
of the fairness of the amount the customers paid but did not extend to satisfaction
with the service encounter nor to future intentions in relation to the particular hospitality outlet. These findings imply that interactional justice has both a larger and
a more pervasive influence on customer evaluations than is the case for social
comparison equity information. The findings are consistent with those of
Blodgett and colleagues (1997), who reported that interactional justice was a
more potent determinant of complainants’ repatronage and negative word-ofmouth intentions than were either distributive or procedural justice. It is interesting that Blodgett and colleagues also reported a significant interaction between
distributive and interactional justice, a finding not replicated here when knowledge of others outcomes was the independent variable.
Procedural Versus Interactional Justice
This study provided a partial replication of that conducted by Van den Bos,
Lind, and colleagues (1997). That study’s finding that process factors affect out-
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come evaluations only when others’ outcomes are unknown was not confirmed.
The two studies differed in several ways, any of which may have contributed to the
discrepant findings. For example, the multi-item measures of the dependent variables used in the current study may have produced more reliable and valid findings than those obtained previously.
A second, more plausible basis for the different findings from the studies was
the different type of process justice manipulated. Procedural justice was manipulated by Van den Bos, Lind, and colleagues (1997) and held constant in our
research, whereas interactional justice was manipulated here but eliminated altogether in the experimental task used by Van den Bos, Lind, and colleagues.
Although it is also possible that the discrepant findings can be partly explained in
terms of the strength of these manipulations (an issue that should be put to future
empirical test), it appears reasonable to conclude that the nature of the process justice manipulation, especially when combined with a congruent scenario that rendered this manipulation salient, was the most critical factor. To the extent that this
is so, the contrasting findings of the two studies provide further evidence that the
two forms of process justice are empirically distinctive and should be theoretically distinguished in future discussions. This stance might be further validated
by future studies that include manipulations of high and low levels of both procedural and interactional justice, as well as social comparison equity information.
Such research would provide an opportunity to further test Fairness Theory’s postulations regarding the relative importance and ease of interpretation of interactional, as compared with procedural, justice, and the consequent independent
and interactive effects of these two forms of process justice on outcome fairness
and related evaluations.
Mechanisms Involved
Our study did not explicitly focus on the mechanisms through which
interactional justice has its effect on the participants’ evaluations. Certainly, the
findings can be interpreted as being consistent with Fairness Theory’s (Folger &
Cropanzano, 1998) postulation that it is the relative lack of ambiguity concerning
interactional justice (at least when compared with procedural and distributive
issues) that explains the potency of the obtained effects. However, a definitive test
of this hypothesis would require the experimental manipulation of this ambiguity
variable.
If, however, a Fairness Theory approach is pursued, other possible mechanisms by which interactional justice influenced the results can be suggested. The
Fairness Theory posits that a universal theme integrating the spectrum of justice
models is the consideration of who is morally accountable for a perceived injustice and the direction of responses toward that party (Folger & Cropanzano,
1998). Using this framework, it could be inferred that in determining perceptions
of moral accountability, participants in the low interactional justice conditions
engaged in counterfactual comparisons of their experiences of rudeness and disrespect with (a) what should have been done (e.g., “I should have been treated
politely and respectfully by the restaurant attendant”); (b) what feasibly could
have been done (e.g., “The restaurant attendant could easily have been more cour-
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teous, or more empathic toward my situation”); and (c) how they would have felt if
something different had happened (e.g., “If only the restaurant attendant had been
more polite, I would not have felt so upset”). Future research could be usefully
directed toward explicating the counterfactual thinking that mediates the relationship between instances of injustice and the assignation of moral accountability.
Such research would attempt to probe the participants’ thinking in the face of low
interactional justice by the inclusion of measures of the participants’ perceptions
of the extent to which (a) the service provider violated moral norms (what should
they have done here?); (b) the service provider had discretionary control over
alternative recovery options (what else could they have done?); and (c) how the
customers’ feelings would have been different if other options had been adopted.
Participants in conditions of high interactional justice, on the other hand, were
placed in the role of a customer subjected to what Fairness Theory might term a
positive “process event”. To date, the theory has not offered any substantive explanation of the psychological mechanisms underlying the more favorable evaluations likely to be elicited by experiences of perceived fairness. Accordingly, two
alternate, and rather tentative, explanations for these results are tendered here.
First, perhaps in the high interactional justice conditions, dignified and respectful
treatment meets (“confirms”) participants’ implicit normative expectations (cf.
Mattsson, 1994; Seiders & Berry, 1998). The confirmation of high interactional
justice expectations may then elicit positive feelings in these participants, and
these feelings may influence ratings of outcome fairness and satisfaction.
A second possibility is that rather than producing positive feelings, service
provider adherence to treatment norms may simply fail to produce negative affective responses (cf. Westbrook & Oliver, 1991). In other words, the norm of courteous and respectful treatment may be so embedded in the psyches of people in general, and customers in particular, that when received, it is scantly noticed. Perhaps,
then, the issue of courteous and respectful treatment only becomes salient when it
is not received. In short, a positive display of interactional justice may only be
noticeable by its absence.
Regardless of which explanation is adopted to explain the favorable evaluations under conditions of high interactional justice, it seems unlikely that the participants in these conditions would have perceived a need to assign moral accountability in these instances, because a violation of fundamental moral precepts had
not occurred. Such positive process events, and their associated underlying psychological mechanisms, provide an avenue for future research into, and possible
extensions to, Fairness Theory.
Limitations
As with all research methods, the approach taken here is limited in several
ways. For instance, little published validity data appear to exist for the dependent
measures, although they are reliable and arguably high in content validity. In addition, because the dependent measures assessed the subjective perceptions of participants, it may be useful for future studies to direct efforts to the development
and utilization of behavioral measures to validate the perceptual data used in the
current study. Another limitation is that the generalizability of the results may be
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reduced because a student sample was utilized (cf. Brown et al., 1996; Clemmer,
1993; Goodwin & Ross, 1992). Future research could extend the sample to a
broader representation of the consumer population.
In addition, the findings might not be applicable to services or service failures
other than those depicted in the scenarios (Clemmer, 1993; Goodwin & Ross,
1992). Yet, Lovelock and colleagues (1998) caution that it is equally unwise to
“over-generalise about services [or] . . . assume that each service industry is
unique” (p. 32). This suggests that the results may, at a minimum, apply to services that share certain fundamental characteristics with the hospitality services
utilized in the current study. Finally, the use of projective, role-playing scenarios
might also reduce the external validity of the findings (Barling & Phillips, 1993;
Bitner, 1990; Brown et al., 1996). Participants could have experienced difficulty
responding as they would if they were a customer in a similar, genuine service situation (Bitner, 1990; Blodgett et al., 1997). Against this, however, it should be
noted that the mean response to the believability manipulation check (including
the item “I was able to adopt the role of the customer depicted in the scenario”, see
Table 1) exceeded 6 on the 7-point scale.
Managerial Implications
The results of this study have notable practical implications for hospitality and
tourism organizations whose frontline staff interact directly with customers.
Given that there is persuasive empirical evidence that customer evaluations of service encounters have important consequences for word-of-mouth behaviors and
repeat business, there is a need for service organizations to devote resources to
ensuring that service encounters seldom fail and, when they do, are always recovered. The results of the current study underscore the extent to which customer
evaluations are shaped by perceptions of the interactional justice of the service
encounter. Indeed, the results, in conjunction with similar findings from previous
research, suggest that managers should pay more attention to devising and implementing policies that facilitate evaluations of high interactional justice. A number
of complementary approaches can be taken to enhance and maintain high levels of
interactional justice at the service provider–customer interface.
First, service provider displays of dignity and respect may be influenced by the
training policies of service organizations. The provision of appropriate interpersonal and communication skills training to customer contact employees appears
extremely important for customer satisfaction and loyalty (see, e.g., Bitran &
Hoech, 1990; Lewis & Entwistle, 1990). Given the salience of interactional concerns within the service recovery context of the current study, specific training in
the courteous and respectful treatment of customers in service failure and recovery situations appears warranted.
Although training frontline staff in interactional justice elements may be useful, some commentators highlight the inherent problems in the assumption that
sociability toward customers is a skill that can be taught to employees (Hurley,
1998; Romm, 1989). Hurley (1998) suggests that, despite appropriate training
and the support of organizational systems, not all people will “display the proper
service behaviors consistently if their personality is not aligned with these types
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of behavior” (p. 187). Hence, the recruitment and selection practices within service organizations may play a crucial role in facilitating the respectful and courteous treatment of customers. Thus, rather than focusing organizational energies
exclusively on the training and development of frontline employees, it may prove
equally fruitful to channel efforts into the recruitment of the types of people who
will facilitate a positive service climate for both employees and customers alike
(cf. Hurley, 1998).
More generally, there is evidence that high levels of interactional justice will be
manifested to the extent that a service climate characterized by courtesy and
respect pervades the entire organization (Schneider, 1990). Although perhaps
beyond the narrow scope of the current research, note can be taken of Schneider’s
(1973) suggestion that the work climate created by service organizations for their
employees influences employee behavior toward customers. Hence, it appears
that it is not enough for service organizations to require employees to treat customers politely and respectfully; leaders and managers within organizations
should create a climate of respect and dignity through their own treatment of
employees (Bitran & Hoech, 1990; Bowen et al., 1999).
CONCLUSION
The present study offers important theoretical and practical insights into justice concerns within the hospitality and tourism sector organizations. Evidence
was found consistent with Fairness Theory’s proposition that interactional justice
may be the most potent moderator of reactions to unfair outcomes. The results
also suggest that, at least in service recovery settings, interactional justice functions differently from procedural justice, thus lending support to the theoretical
differentiation of these two organizational justice dimensions. The placement of
the research within a service recovery environment yielded the first known context where fair process effects were found despite the presence of social comparison equity information. Hence, the findings suggest the claim that procedural justice information is redundant when others’ outcomes are known does not
generalize to service recovery environments. The importance of dignified and
respectful treatment of customers (and employees) by service organizations is
also highlighted, with implications for service climate creation and the training
and selection of customer contact staff. Thus, amid the continuing complexity of
the justice construct, the current study might be best encapsulated by the simple
words of Bell and Zemke (1987): “When service fails, first treat the person, then
the problem” (p. 34).
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APPENDIX
Sample Scenario
Instructions:
READ THE FOLLOWING SCENARIO AND IMAGINE THIS HAPPENED TO YOU.
Imagine you are on a day trip arranged by the student guild to one of the local theme parks.
Although there is a whole bus load of students, you don’t know many people. When you arrive at the theme park, the bus load splits up into lots of small groups, and you head off with
a student you recently met in one of your tutorials. After enjoying some of the rides, you
and your new friend decide to eat. As part of the arrangement with the theme park, the student guild has given each student a lunch coupon that allows you to buy a set meal from the
main restaurant for a low $8 (meals normally start at $12). However, when you go to order
the meal, the following occurs:
The attendant smiles/frowns and asks pleasantly/abruptly, “What would you like?”
“I have this special coupon for an $8 meal—I’d like to order that please.”
The attendant takes the coupon from you with an interested/disinterested look on their face.
After inspecting the coupon, the attendant, sounding concerned/indifferent says, “I’m really very sorry/I’m sorry. These coupons are out of date—we stopped taking them last
month.” Seeming slightly perplexed/annoyed, the attendant continues, “You can see that
the use-by date is written right here on the coupon. That was over two weeks ago.”
“But the coupon is part of the package that we all received today! We’re all from the uni,
and our student guild organised them especially with the theme park for us to use today,”
you reply emphatically.
At this point the attendant seems to become very understanding/agitated,and, in a sympathetic/irritated voice, says, “This meal is usually $12. What would you like us to do?”
“Well at the very least I’d like to get what is on the coupon!” you respond.
The attendant then replies sincerely/abruptly, “I know this must be very frustrating for
you/You people always want something for nothing. I’ll just have to go and check.” The attendant walks over to the counter and returns with a pre-printed visitor comment card that
they place/thrust in front of you. Smiling/glaring, the attendant says, “Seeing as I have to
refer to the manager, it’s the park’s policy that you are given the opportunity/get to fill in
one of our feedback cards.” The attendant gives you a pen and then leaves to consult with
the manager.
Whilst the attendant is away, you record the details of the incident on the feedback card.
The attendant returns and says very politely/huffily, “No problem/Well you’re in luck . . . .
you can have the meal for $8.” You and your friend place your order for the discount meals.
As you leave the restaurant after finishing your meal, you hand the attendant feedback card
and think to yourself, “Well at least I had a say about that.”
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Later, at the pre-arranged time, all the students meet back at the bus. On the journey back to
uni, you overhear two students sitting across the aisle from you talking about the lunch coupons. You ask them whether they’d had any problem ordering the meal on the coupon, to
which one of them replies
[equal outcome] “Yeah, they wanted to charge us $12, but we ended up getting it for
$8—the amount on the coupon!”
[better outcome] “Yeah, they wanted to charge us $12, but we ended up getting it for
$4—even less than the amount on the coupon!”
[worse outcome] “Yeah, they wanted to charge us $12, and that’s what we ended up having
to pay!”
[unknown] “Yeah,” and then they continued their own conversation.
Straight after the other student’s reply, the bus arrives back at uni. Everyone immediately
leaves the bus and goes their separate ways.
Note: Experimental manipulations are italicized. IJ manipulations appear throughout the scenario text, with high IJ scenario text appearing first in the italicized text. Manipulations of the
second independent variable, OO, appear in the second last paragraph of the scenario text.
Each participant received one of the eight versions of the scenario (2 [IJ] × 4 [OO] manipulations).
NOTES
1. In accordance with much of the literature (see, e.g., Brockner & Wiesenfeld, 1996;
Folger & Cropanzano, 1998; Lind & Tyler, 1988), the terms fairness and justice, and distributive and outcome, are used interchangeably throughout this article.
2. Full details of the items used are available from the first author on request.
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Submitted October 28, 1999
Accepted January 1, 2000
Refereed Anonymously
Thérèse A. Collie (e-mail: t.collie@gu.edu.au) is a senior research assistant, and Beverley
Sparks, Ph.D. (e-mail: b.sparks@gu.edu.au), is an associate professor, in the School of
Tourism and Hotel Management at Griffith University, Gold Coast (PMB 50, Gold Coast
Mail Centre, QLD, Australia 9726); and Graham Bradley (e-mail: g.bradley@mailbox.gu.edu.au) is a senior lecturer in the School of Applied Psychology at Griffith University, Gold Coast (PMB 50, Gold Coast Mail Centre, QLD, Australia 9726).
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