chapter 11 customer satisfaction, service failure, and service recovery

C H A P T E R• • • • 11

Customersatisfaction,

service failure, andservice recovery

Anna S. Mattila and Heejung Ro

Customer satisfaction, service failure, and service recovery

Introduction

Thischaptercriticallyreviewsconceptualizationsandempiricalevidencein support of customer satisfaction, service failure, and service recoveryand their role in hospitality and tourism management. One of the mostbasic principles in hospitality marketing is that organizational perfor-mance is enhanced by satisfying customers. Satisfaction is a major out-come of marketing activity and it links decision-making processes andconsumption with post-purchase phenomena, such as attitude change,complaining behavior, word-of-mouth, repeat purchase and brand loy-alty (e.g., Oliver, 1980). Although hospitality and tourism organizationsmay consider customer satisfaction as a major goal, not all service expe-riences are satisfactory from the customer’s perspective (Ennew andShoefer, 2003). Service failures can, and often do, occur. One reason forthese failures is the labor-intensive nature of the hospitality industry,which inevitably leads to more heterogeneous outcomes compared togoods production processes (Kotler et al., 2006). Service performancevariability and failures also arise from the inseparability of service pro-duction and consumption. Given the relatively high frequency of servicefailures, service recovery has been identified as one of the key ingredi-ents for achieving customer loyalty (e.g., Tax and Brown, 2000). As aresult, developing an effective service recovery policy has become animportant focusofmanycustomerretentionstrategies (Smithetal., 1999).Service recovery strategies involve actions taken by service providers torespond to service failures (Grönroos, 2000). Both what is done (com-pensation) and how it is done (employee interaction with the customer)influence customer perceptions of service recovery (e.g., Levesque andMcDougall, 2000).This chapter provides a critical analysis of the literature on cus-

tomer satisfaction, service failure, and service recovery in the field ofhospitality and tourism management and identifies several strategiesthat hospitality organizations can implement in response to dissatisfy-ing service experiences. Following a brief overview of the conceptu-alization and measurement of the constructs of interest, an attempt ismade to bring to the reader’s attention the importance of broadeningthe scope of research in this field. This approach naturally indicatesavenues that future research might fruitfully explore. The chapter con-cludes by presenting a comprehensive framework for the customer’spost-purchase evaluation processes.

Background

Customer satisfaction

What is customer satisfaction?

Despite extensive research on satisfaction, researchers cannot agreeon a common definition for the concept. Oliver (1997) addresses this

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Handbook of Hospitality Marketing Management

definitional issue by noting that “everyone knows what satisfaction

is until asked to give a definition. Then it seems, nobody knows”

(p. 13). Due to its elusive nature, the literature is replete with different

conceptual and operational definitions of consumer satisfaction.

Most definitions favor the notion of consumer satisfaction as an

evaluative process. Specifically, there is an overriding theme of con-

sumer satisfaction as a summary concept [i.e., a fulfillment response

(Oliver, 1997); overall evaluation (Fornell, 1992); summary attribute

phenomenon (Oliver, 1992)]. Satisfaction is also often viewed as an

attitude-like judgment based on a series of consumer–product inter-

actions (Yi, 1990). However, there is disagreement concerning the

nature of this summary concept.

Researchers portray consumer satisfaction as either a cognitive or an

affective response. For example, Westbrook and Reilly (1983, p. 256)

refer to satisfaction as ‘an emotional response,’ while Howard and

Sheth (1969, p. 145) consider satisfaction as ‘a buyer’s cognitive state.’

More recent definitions seem to incorporate emotions (Giese and Cote,

2000), and there are several conceptual and operational definitions indi-

cating that satisfaction is a mixed response comprised of both cognitive

and affective dimensions (e.g., Oliver, 1997). Recent research indicates

that the relative importance of affect versus cognition on satisfaction

judgments might be time-dependent (Cote et al., 1989). For example,

Homburg et al. (2006) show that the impact of cognition on satisfaction

evaluations increases over time while the role of affect diminishes.

Although satisfaction has been conceptualized in terms of either a

single transaction (i.e., an evaluative judgment following the purchase

occasion) or a series of interactions with a product over time, Anderson

and Fornell (1994) note that nearly all satisfaction research has adopted

the former, transaction-specific view. Indeed, several scholars have crit-

icized the marketing field for treating satisfaction as a static evaluation

derived from a single trial event.

The single-transaction view is particularly problematic for hospi-

tality and tourism services that typically are composed of a series of

service encounters within a single consumption experience. For exam-

ple, tourism is a high-involvement, high-risk purchase, thus leading to

a complex evaluation process with no predictable critical evaluation

point (Bowen and Clarke, 2002). While some researchers focus on a

single aspect of the travel experience such as shopping satisfaction

(Heung and Cheng, 2000; Reisinger and Turner, 2002), others include

multiple attribute dimensions such as tourist attractions, facilities,

services, and prices (Yu and Goulden, 2006) and satisfaction with the

tour provider and tour package (Hsu, 2000). Middleton and Clarke

(2001), for instance, demonstrate the interdependence of various

components of the travel package in driving overall satisfaction (i.e.,

a medley of products). Tourists are thus likely to evaluate their travel

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experiences holistically rather than decomposing them to isolatedattribute-level components.Hospitality experiences typically involve a series of service encoun-

ters. Satisfaction occurs at each encounter, and each encounter con-tributes to overall satisfaction. For example, Lemmink et al. (1998)examined the dining service delivery process by breaking it down intofour distinct stages: (a) reception, (b) ordering, (c) meal consumption,and (d) check-out. Satisfaction scores were gathered at each stage aswell as at the global level. The carry-over effects from previous stagessupport the notion of satisfaction as a cumulative concept.In tourism and hospitality research, satisfaction is often used as an

independent variable to predict behavioral intentions such as revisitto the destination (e.g., Petrick et al., 2001; Petrick and Backman, 2002;Alegre and Cladera, 2006); return to the hotel or casino (Kandampullyand Suhartanto, 2000; Lucas, 2003); or engaging in positive word-of-mouth (e.g., Petrick, 2004; Petrick et al., 2006). Moreover, the relativeimportance of various attributes in driving these outcomes has beena topic of numerous studies in the hospitality and tourism literature(e.g., Barsky, 1992; Yüksel and Rimmington, 1998).

Dissatisfaction

Compared to satisfaction, conceptualizing dissatisfaction has receivedrelatively little attention in consumer research. In general, dissatisfac-tion responses are relatively strong reactions to consumption episodes.Dissatisfaction is often accompanied with intense emotions (e.g., anger,frustration) and perceptions of unfairness. Most research on dissatis-faction has focused on understanding consumers’ behavioral responsessuch as complaining behaviors and negative word-of-mouth communi-cation (e.g., Tax, Brown, and Chandrashekaran, 1998). As such, extantliterature is relatively silent in terms of defining dissatisfaction (Gieseand Cote, 2000). Satisfaction research has, however, examined the uni-dimensionality of the satisfaction/dissatisfaction construct (Maddox,1981). Consumer dissatisfaction is typically portrayed as a bipolaropposite of satisfaction (e.g., Spreng et al., 1996; Mittal et al., 1999;).Alternatively, satisfaction and dissatisfaction are sometimes viewedas two different dimensions (e.g., Mano and Oliver, 1993). While theformer approach involves well-known scales (e.g., very satisfied vs.very dissatisfied), unipolar satisfaction and unipolar dissatisfactionmeasures are employed with the latter conceptualization. To illus-trate this measurement issue, consumers can have mixed reactions toa consumption episode. A restaurant patron might be satisfied withgood food but dissatisfied with a rude server. Under these conditions,satisfaction and dissatisfaction should be viewed as separate dimen-sions. Having defined satisfaction and dissatisfaction, the next section

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will briefly discuss the theoretical frameworks underlying consumers’post-purchase evaluation processes.

The expectancy disconfirmation with performance model

The dominant conceptual model in the customer satisfaction litera-ture is the disconfirmation of expectations paradigm (Oliver, 1977;Wirtz and Mattila, 2001). Later, the paradigm has evolved consider-ing the role of performance in the process (Oliver, 1980; Churchilland Surprenant, 1982), and then it has been named the expectancydisconfirmation with performance model (Oliver, 1997). This modelposits that customer satisfaction is related to the degree and directionof the disconfirmation experience, where disconfirmation is defined asthe gap or difference between an individual’s pre-purchase expecta-tions and perceived performance of the product/service (Oliver, 1980).Consumers’ expectations are (a) confirmed when the product/serviceconforms to expectations; (b) negatively disconfirmed when perfor-mance is less than expected, and (c) positively disconfirmed whenperformance is better than expected (Patterson and Johnson, 1993).The disconfirmation model is parsimonious and intuitively appealing(Iacobucci et al., 1994) and it has received strong empirical support(e.g., Boulding et al., 1993). Figure 11.1 is a simplified version of theexpectancy disconfirmation with performance model.Despite robust support for the intervening role of disconfirmation in

the satisfaction formation process, research also suggests that perceivedperformance might directly influence satisfaction (e.g., Anderson andSullivan, 1993; Oliver, 1993; Oliver, 1994). It has been empirically shown

Expectations

Disconfirmation

Performanceoutcomes

Satisfaction/Dissatisfaction

Figure 11.1A general model of expectancy disconfirmation with performance (based on Churchilland Surprenant, 1982; Oliver, 1997)

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that direct causal links from perceived performance to satisfaction cansignificantly increase the proportion of explained variance in satisfac-tion, and that sometimes perceived performance can be an even betterpredictor of satisfaction than the disconfirmation-of-expectations vari-able (Churchill and Surprenant, 1982; Tse and Wilton, 1988).The most controversial variable in the disconfirmation paradigm,

however, is the comparison standard (e.g., Wirtz and Mattila, 2001).A large amount of theoretical debate and empirical research hasrevolved around the question on what standard(s) people use in thecomparison process. This line of research has resulted in six broadclasses of pre-experience standards. They are (1) predictive expecta-tions (e.g., Oliver, 1980), (2) ideal performance (e.g., Sirgy, 1984), (3)needs and wants coined as value-percept (Westbrook and Reilly, 1983)or desires (Spreng and Olshavsky, 1993), (4) experience-based stan-dards (Cadotte, Woodruff, and Jenkins, 1987), (5) comparisons withsocial norms (Swan, 1983), and (6) multiple standards (e.g., Sirgy, 1984;Spreng et al., 1996). Discussions on these standards are provided else-where (e.g., Yi, 1990; Spreng and Olshavsky, 1993), and this reviewwill now move on to consequences of satisfaction and dissatisfaction.

Consequences of consumer satisfaction and dissatisfaction

Most satisfaction models link satisfaction with positive outcomes suchas loyalty and positive word-of-mouth. Overall satisfaction has beenshown to mediate the effects of quality and price on loyalty intentacross various service categories (Fornell et al., 1996; Bolton and Lemon,1999; Gallarza and Saura, 2006). Given its close linkage to loyalty, con-sumer satisfaction is believed to drive the firm’s profitability (Oliver,1997). The basic idea is that satisfaction improves profitability byexpanding the business by gaining market share, earning customer loy-alty, improving a brand’s reputation, selling more to current markets,increasing margins, and other strategies (Barsky and Nash, 2003). Yetsome recent studies report only a weak connection between satisfactionand loyalty (e.g., Skogland and Siguaw, 2004).Consumer complaining behavior research has attempted to under-

stand how dissatisfaction influences consumers’ post-failure responses.This stream of research has identified two types of response categories:behavioral responses and response styles. The former examines con-sumers’ behavioral responses to dissatisfaction using dissatisfactionlevel, switching costs, and perceived responsiveness as predictorvariables. In contrast, the latter category examines consumers’response styles to dissatisfaction based on personal characteristics andsocio-demographics.Day and Landon (1977) introduced the generally well-received

public–private distinction in complaint behaviors. Under their taxon-omy, dissatisfied consumers would either ‘take some action’ or ‘take no

301 • • •


action.’ If action was taken, it was labeled as either public (e.g., redresssought from the seller, legal action, or third-party complaint) or pri-vate action (e.g., personal boycott or negative word-of-mouth). While,the ‘take no action’ response is described as ‘forget about the inci-dent and do nothing,’ customers may return to the same serviceprovider. This description is consistent with the notion of ‘loyalty’ inHirschman’s (1970) framework. Based on Day and Landon’s taxonomyand Hirschman’s framework, Singh (1988) specifies three categories ofconsumer complaining behavior: (1) voice, reflecting actions directedtoward the seller; (2) private, involving negative word-of-mouth andexit; (3) third party, relating to actions directed toward external agen-cies such as the Better Business Bureau and legal options. In consumerbehavior, negative word-of-mouth is considered as a distinct construct(Richins, 1983; Singh, 1990), and four responses (exit, voice, negativeword-of-mouth and third-party action) are commonly used in con-sumer complaining studies (e.g., Blodgett and Granbois, 1992).In a restaurant context, Jones et al. (2002) found that consumers can

be classified into three types: those not likely to complain, those whocomplain to anyone, and those who complain via word-of-mouth. Theyfurther suggest that word-of-mouth complainers are under greateramount of psychological stress than those in the other two groupsand that they tend to be less price-conscious and less susceptible tointerpersonal influence than complain-to-anyone complainers. The nextsection of this chapter will briefly review research on service failuresand service recovery.

Service failure

Service failures are viewed as a significant determinant of customerdissatisfaction and switching behaviors (Fornell and Wernerfelt, 1987;Keaveney, 1995; Smith and Bolton, 1998; Tax and Brown, 1998). Asa result, stabilizing the endangered relationship with dissatisfied cus-tomers by utilizing an effective service recovery policy has become themain focus of many customer retention strategies (Stauss and Friege,1999). In fact, most service organizations are forced to pay attention toservice recovery since lingering dissatisfaction is not limited to the inci-dent or customer at hand (Brown, 1997). Various studies indicate thatupset customers may tell 10–20 people about their bad experience witha service company (Zemke, 1999). Because every service encounter isthe ‘Moment of Truth’ from the customer’s perspective, we will firstdefine the term service encounter.

Service encounters

Surprenant and Solomon (1987) define the service encounter as ‘adyadic interaction between a customer and a service provider.’ This

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definition focuses on the interpersonal element of the service deliveryprocess. From a broader perspective, Shostack (1985) defines the serviceencounter as ‘a period of time during which a consumer directly inter-acts with a service firm.’ Her definition encompasses all aspects of theservice, including contact with the firm’s personnel, its physical facil-ities, and other visible elements. Moreover, Shostack’s conceptualiza-tion entertains the idea that service encounters can occur without anyhuman interaction elements. This aspect of the service encounter is par-ticularly relevant in today’s high-tech environment where many partsof the service are performed by the consumer via self-service technolo-gies (e.g., self check-in at airports and hotels). Since most hospitalityservices include a high degree of interaction between employees andcustomers, therefore, there are plenty of possibilities for service failures.

Service failures

Service failures arise when customers experience dissatisfactionbecause the service was not delivered as originally planned or expected.It is important to keep in mind that service failures are determined bythe customer and not by the service organization (Ennew and Schoefer,2003). Classifying service failures according to their type is a usefulfirst step in understanding consumer reactions to failure incidents.The services marking literature recognizes two types of service

encounter failures: outcome and process failures (Bitner, et al., 1990).The outcome dimension reflects what customers actually receive fromthe service (e.g., a clean hotel room), whereas the process dimensioninvolves how they receive the service, that is, the manner in whichit is delivered (Parasuraman et al., 1985). Bitner et al. (1990) used acritical-incident technique to identify common themes in service fail-ures. Their analysis involving 700 failure incidents in the airline, hotel,and restaurant industry, resulted in the following three broad servicefailure categories:

Category 1. Employee Responses to Service Delivery FailureWhen the service delivery system fails, contact employees are requiredto respond to the customer’s request and the employee response deter-mines the customer’s perceived satisfaction and dissatisfaction. In gen-eral, service delivery system failures consist of three types of failures:(1) unavailable service, (2) unreasonably slow service, and (3) othercore service failures. All these incidents are directly linked to the coreservices (e.g., the hotel room, the restaurant meal service, the airplaneflight). Unavailable service refers to services that are normally avail-able,but are lacking or absent in the relevant context, such as cancelledflights or a hotel that is overbooked. Unreasonably slow service relatesto services or employees that customers perceive as being inordinatelyslow in fulfilling their functions (e.g., flight delays and lengthy queues

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in a theme park). Other core service failures encompass all other aspects

of the service that do not meet basic performance standards for the

industry. For example, the hotel room is dirty, the restaurant meal is

cold, or the baggage arrives damaged. The latter category is deliber-

ately kept broad to reflect the various core services offered by different

industries.

Category 2. Employee Responses to Customer Needs and RequestsThe second category relates to employee responses to individual cus-

tomer needs and special requests. Customer needs can be implicit

or explicit (Ennew and Schoefer, 2003). An airline fails to meet an

implicit need when a flight schedule is changed without notifying its

customers so that alternative connection flights cannot be arranged.

Explicit requests, on the other hand, consist of four types: (1) special

needs, (2) customer preferences, (3) customer errors, and (4) disruptive

others. Special needs involve taking care of individual requests or needs

(e.g., medical requests or language requirements). Employee responses

to customer preferences typically require some form of customization

in the service delivery process. For example, menu item substitutions

involve modifications based on customer preferences. Responding to

customer errors involves steps taken to correct the problem (e.g., lost

theatre tickets or lost hotel keys). Finally, service employees might need

to take action against disruptive others (i.e., requesting customers to

refrain from smoking in the restaurant’s non-smoking sections).

Category 3. Unprompted and Unsolicited Employee ActionsThe third category of service failures involves events and employee

behaviors that are unexpected from the customers’ point of view. These

actions are not initiated by the customer, nor are they part of the

normal service delivery system. These unprompted employee actions

can be sub-divided into five types: (1) lack of attention, (2) unusual

actions, (3) cultural norms, (4) gestalt, and (5) adverse circumstances.

Lack of attention is common among employees with attitude problems

whereas unusual behaviors reflect rudeness, abusiveness, and inappro-

priate touching. The cultural norms sub-category refers to the actions

that violate cultural norms (e.g., lying, stealing, cheating, and other

activities considered unfair by the customer). The gestalt sub-category

refers to the holistic nature of customer evaluations. Thus, customers

are unable to attribute dissatisfaction to any single feature of the event

or particular action of the employee. Yet customers evaluate the service

experience in a holistic manner such as in ‘everything went wrong’.

To illustrate, a customer might be highly dissatisfied with his/her

vacation but not be able to identify any specific incidents that caused

this dissatisfaction. Finally, the adverse circumstances sub-category

includes incidents in which the customer is particularly displeased

with the way a contact employee handles a stressful situation.

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Service recovery

Service recovery can be defined as actions designed to resolve prob-lems, alter negative attitudes of dissatisfied customers, and ultimatelyretain these customers (Miller et al., 2000). Service recovery is not lim-ited to customers who voice their dissatisfaction (Smith et al., 1999).The purpose of service recovery is to ‘seek out and deal with servicefailures (Johnston, 1995, pp. 53–71).’ It is the ‘seeking out’ part thatdistinguishes recovery from complaint handling, as a vast majority ofdissatisfied customers do not bother to complain. Instead, they votewith their feet and switch to another service provider.Recovery management is considered to have a significant impact

on customer evaluations because customers tend to be more emotion-ally involved in recovery service than in routine service encounters(Bitner et al., 1990). Justice theory appears to be the dominant theoreti-cal framework applied to service recovery (Tax and Brown, 2000) and,hence, the discussion will now turn to fairness theories.

Fairness of recovery: Justice theory

Literature on customer complaint management shows that consumersexpect ‘fair’ resolutions to product and service failures (e.g., Blodgettet al., 1997). Similar to complaint handling, customers evaluate percep-tion of fairness with the service recovery by three factors: outcomes,procedural fairness, and interactional treatment (Goodwin and Ross,1992; Tax et al., 1998; Smith et al., 1999). Smith et al. (1999) devel-oped a comprehensive model of customer satisfaction with servicefailure/recovery encounters and tested it in both a restaurant and ahotel context. Their findings suggest that customers prefer to receiverecovery resources that match the type and magnitude of the failure.Also, Blodgett et al. (1977) suggest that consumers’ evaluation of thethree justice components (distributive, interactional, and proceduraljustice) in service recovery situations have impact on post-complaintbehavior such as re-patronage and negative word-of-mouth. The fol-lowing diagram (Figure 11.2) illustrates the role of perceived justice inservice failure/recovery encounters.Distributive justice reflects the outcome fairness and focuses on the

compensation provided for customers’ loss and/or inconvenience suf-fered (Smith et al., 1999; Tax et al., 1998). As a result, many serviceorganizations offer various combinations of refunds, credits, discounts,and apology to make peace with dissatisfied customers. Procedural fair-ness involves the policies and rules by which recovery effort decisionsare made (Smith et al., 1999). The speed with which service failures arecorrected or complaints are handled is one of the major determinantsof customer perceptions of procedural justice (Blodgett et al., 1997; Taxet al., 1998). Interactional justice, in contrast, refers to the manner in

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Failurecontext

Type offailure

XMagnitudeof failure

Initiation

Apology

Responsespeed

Compensation Distributivejustice

Interactionaljustice

Satisfactionwith service

recovery

Post-complaintbehavior

Proceduraljustice

Recoveryattributes

Perceivedjustice

Figure 11.2Customer evaluation of service failure/recovery encounters: the effect of perceived justice on servicerecovery satisfaction and post-complaint behavior (based on Blodgett et al., 1997; Smith et al., 1999)

which the customer is treated during the recovery process (Smith et al.,1999). For example, courtesy and empathy (Tax and Brown, 1998) andpoliteness, and concern and neutrality (Sparks and McColl-Kennedy,2001) have been shown to influence customers’ overall perceptions ofjustice.The most recent conceptualization of justice suggests that inter-

actional justice can be analyzed further to present two separate dimen-sions: interpersonal treatment and informational justice (Colquitt, 2001;Colquitt et al., 2001; Mattila and Cranage, 2005). Informational jus-tice taps into the perceived adequacy and truthfulness of informationexplaining the causes for unfavorable outcomes (Colquitt, 2001). Therole of information in service failure situations has been explored ina restaurant context. Information inadequacy increases consumer frus-tration (Susskind, 2005) and an informed choice increases loyalty fol-lowing a service failure, as a result of customers’ willingness to shareresponsibility (Cranage, 2004).The relationship between the various justice dimensions is complex

owing to their interactive effects. Sparks and McColl-Kennedy (2001)examined the various combinations of procedural, interactional, anddistributive justice related to service recovery strategies within a hotelsetting and found that satisfaction varied significantly depending onthe various combinations of recovery measures. Ok et al. (2005) alsosuggest that all three dimensions of justice had positive effects onrecovery satisfaction. Similarly, Wirtz and Mattila (2004) demonstratethat recovery outcome (e.g., compensation), procedures (e.g., speed ofrecovery), and interactional treatment (e.g., apology) have a joint effecton post-recovery satisfaction in a restaurant setting. Last, Hoffman andKelley (2000) propose that the evaluation of service recovery efforts

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depends on six contingencies related to interactional and distributionaljustice: (1) depth of the relationship, (2) proximity of the relationship,(3) duration of the encounter, (4) degree of customization, (5) criticalityof consumption, and (6) switching costs.The next section of this review will discuss several critical top-

ics in the recent service recovery literature. We will touch on therole of emotions in the service recovery process, the importance ofrelationship-building in influencing customer perceptions, the mythof service recovery paradox, individual difference factors tangent tocustomer perceptions of service recovery, and how to build effectiveservice recovery strategies.

The role of emotions in the service failure and recovery encounters

Despite the importance of emotions for service organizations (e.g.,Maute and Dubé, 1999), empirical investigations of customers’ affec-tive responses to service failures remain scarce (for notable exceptions,see Smith and Bolton, 2002; Yi and Baumgartner, 2004; Chebat andSlusarczyk, 2005). Having a richer understanding of how negativeemotions influence customers’ satisfaction evaluations and behavioralresponses is particularly important, owing to consumers’ heightenedinvolvement in the consumption experience, in the context of servicefailures (Price et al., 1995; Jayanti, 1998).The common view in satisfaction research is that specific emo-

tions such as anger, sadness, and regret contribute to dissatisfaction(Mano and Oliver, 1993; Oliver, 1997; Smith and Bolton, 2002). Theinteractions between emotions and (dis)satisfaction (and related post-purchase behaviors) can be modeled by two approaches: the valence-based approach and the specific-emotions approach (Zeelenberg andPieters, 2004). In the valence-based approach, negative emotions areexpected to lead to more serious dissatisfaction, while positive emo-tions are expected to result in high satisfaction levels. The overallvalence (satisfaction – dissatisfaction) then becomes the driving forcebehind consumers’ behavioral responses to service failures. Yet, someresearchers argue that important nuances in emotions are not cap-tured in the overall valence approach (Laros and Steenkamp, 2005) andthat focusing on specific emotions is more meaningful in understand-ing consumers’ responses to dissatisfying consumption experiences(Zeelenberg and Pieters, 2004). The specific-emotions approach focuseson the idiosyncratic elements of particular emotions (Zeelenberg andPieters, 2004). Recent studies demonstrate that specific negative emo-tions have a direct impact on behavior, over and above dissatisfaction(Laros and Steenkamp, 2005; Pieters and Zeelenberg, 2005). Serviceencounters, especially failed ones, often result in specific negativeemotions, and these discrete emotions partly determine subsequentbehaviors (Zeelenberg and Pieters, 2004).

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The specific-emotions approach relies on attribution theory as a

source of negative emotions. The attribution theory suggests that peo-

ple are rational information processors whose actions are influenced by

causal inferences (Folkes, 1984). Previous research has shown that cus-

tomers’ attributions about the failures they experience influence their

attitudes and behavioral intentions toward the firm (Folkes, 1984; Bit-

ner, 1990;). For example, attributing responsibility to someone else for

what is happening (external attribution) produces anger, disgust, or

contempt, whereas blaming one’s self (internal attribution) generates

emotions of shame and guilt. Conversely, believing that an event can-

not be helped and that the situation is to blame (situational attribution)

leads to feelings of sadness or fear (Stephens and Gwinner, 1998).

In psychology, anger, sadness, guilt, and anxiety are considered as

distinct negative emotions (Lazarus, 1999) and prior research in con-

sumer behavior suggests that these surface as anger, disappointment,

regret, and worry in the consumer context (Yi and Baumgartner, 2004).

Some of previous findings regarding these four emotions are discussed

in the following list.

• Anger occurs when another person is blamed for the problem (Smith

and Ellsworth, 1985; Lazarus, 1999;). Bougie et al. (2003) suggest

that angry customers behave aggressively and complain about the

problem.• Disappointment is felt when an outcome is not as good as expected

and it is typically associated with blaming others or circumstances

(Zeelenberg and Pieters, 2004).• Regret usually involves self-blame and an acknowledgement that one

has made a mistake (Zeelenberg et al., 1998).• Worry is related to prospects of undesirable events and uncertainty

about what to do (Yi and Baumgartner, 2004). For example, con-

sumers may feel worried when a flight is delayed and might become

a cancellation, yet they don’t know what to do about the situation.

Recent research in the hospitality and tourism literature has started

to uncover the impact of emotions in driving customers’ post-failure

perceptions (e.g., McColl-Kennedy and Sparks, 2003). Relying on coun-

terfactual thinking and accountability, McColl-Kennedy and Sparks

suggest that customers assess whether the service provider could and

should have done something more to remedy the problem and how

they would have felt had these actions been taken. Moreover, when

service providers do not appear to exhibit an appropriate level of effort,

consumers interpret the lack of effort as ‘not caring’. This lack of car-

ing in turn leads to strong emotional responses such as anger and

frustration. Finally, Smith and Bolton (2002) suggest that customers’

emotional responses to service failures are context-specific and that the

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effects of emotions vary across industry settings (e.g., restaurant andhotels). In their study, emotions failed to influence recovery perceptionin the restaurant setting.

The impact of customer relationships in service failureand recovery encounters

Customer relationship with a service organization can alter their reac-tions to service failures and recoveries. Some research postulates thatstrong customer relationships act as a bufferwhen service failures occur,thus resulting in lower levels of dissatisfaction. For example, Berry(1995) suggests that customers may exhibit a greater tolerance for fail-ures when they have cultivated a social bond with the service provider.Similarly, Tax et al. (1998) found that positive prior-service experiencemitigated the negative effects of poor complaint handling on customercommitment and trust. Moreover, Hess et al. (2003) show that cus-tomers who expect the relationship to continue have lower servicerecovery expectations, and these lower service recovery expectations, inturn, have a positive impact on post-recovery satisfaction. Scanlan andMcPhail (2000) suggest that perceived personalization, social bonding,reliability, and familiarization are the key factors in building relation-ships with hotel customers.There is, however, some evidence to suggest that customer loyalty

might magnify the negative customer responses following service fail-ures. For example, Mattila (2004) suggests that emotionally bondedcustomers might feel betrayedwhen a service failure occurs, thus result-ing in sharp decrease in post-recovery attitudes. Moreover, customerswith lower levels of emotional bonding with the service provider mightbe more forgiving when the service recovery is effectively handled.

Recovery paradox and double deviation

‘Service recovery paradox’ refers to a situation in which secondary sat-isfaction (i.e., satisfaction after a failure and recovery effort) is higherthan pre-failure satisfaction (Smith and Bolton, 1998). ‘Double devi-ation’ effect, on the other hand, states that poorly handled servicerecoveries exacerbate already low customer evaluations following afailure (Bitner et al., 1990).The evidence for service recovery paradox in the hospitality and

tourism literature is inconclusive. McCollough (2000) shows that whenthe hotel’s recovery efforts successfully mitigate the harm caused bythe failure, a recovery paradox may be possible. However, this posi-tive outcome may not translate into higher service quality perceptionsif the failure is perceived to be stable. Conversely, a successful ser-vice recovery might not be sufficient for the recovery paradox in themeeting and convention segment of the industry (Oh, 2003). He argues

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that successful recoveries do not strengthen customers’ original sat-isfaction. In fact, failures and recoveries – no matter how successfulthe recoveries might be – collectively undermine the customers’ origi-nal satisfaction that could have been experienced without any failure.Moreover, Ok et al. (2005) suggest that although a service failure ini-tially hurts customer satisfaction, effective complaint handling throughservice recovery may reinforce the reliability perception and relation-ship continuity. They emphasize the notion that recovery efforts shouldbe viewed not only as a strategy to recover immediate satisfaction butalso as a relationship-building tool.

Cultural and gender differences in consumers’ perceptionsof service recovery

Cultural norms and values are likely to influence customers’ per-ceptions of fairness and satisfaction with the service recovery pro-cess. Mattila’s and Patterson’s (2004a) cross-cultural examination ofpost-recovery satisfaction (East-Asia versus Unites States) suggest thatoffering compensation can be particularly effective among Americanconsumers while offering an explanation for the failure had a posi-tive impact on customer perceptions regardless of the customer’s cul-tural orientation. Differences due to cultural background were alsofound in the attribution process for service failures. Mattila and Pat-terson (2004b) show that the differential sensitivity of East-Asian andAmerican consumers to situational constraints influences consumers’attribution processes, and thus moderates their satisfaction with theservice recovery process. More specifically, they suggest that a causalexplanation for service failure decreases the likelihood of US con-sumers falling prey to the fundamental attribution error. Poon andLow (2005) demonstrate that post-recovery satisfaction was higheramong Western travelers than their Asian counterparts. Lorenzoni andLewis (2004) suggest that Italian airline crew members react to servicefailures with a more emotionally-based strategy than British airlineemployees. Finally, the findings from Becker’s (2000) study with fourcultures (Americans, Scandinavians, Asians, and Latinos) suggest thatdifferent perceptions of time, different value systems, and differentapproaches to communication influence customer reactions to servicefailures. Complaint intentions also seem to vary across cultural bound-aries (Yüksel et al., 2006). For instance, Heung and Lam (2003) suggestthat Chinese diners tend to be passive in voicing their dissatisfactionto the service provider. Yet they were quick to engage in private com-plaint behaviors such as word-of-mouth communication and ceasingto patronize the restaurant.Regarding gender effects, male and female consumers seem to place

a differential emphasis on various elements of the service recovery pro-cess. Women want their views heard during the service recovery and

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to be allowed to provide input, while men do not view voice as impor-tant (McColl-Kennedy et al., 2003). In a similar vein, Mattila et al.(2003) showed that in service failure situations negative affective dis-plays had a double whammy impact on male participants’ satisfactionratings.

How to develop effective service recovery strategies?

To guide managers in designing an effective strategy, Tax and Brown(1998) suggest a four-stage approach to service recovery. Their ser-vice recovery process framework suggests that the first two stagesfocus on identifying and resolving individual customer problems. Thenext two stages in the process focus on how recovery data can beclassified and integrated with other firm data to identify profitableservice-improvement investments. They suggest that companies needto develop a comprehensive service recovery system that encouragesdissatisfied customers to voice their complaints and that provides afair process and outcome. They also stress that service design andinvestment decisions should be based on understanding of the vitalrole that recovery plays in contributing to improved performance, cus-tomer and employee satisfaction, customer loyalty, and ultimately thefirm’s profitability.In the hospitality literature, Hoffman and Chung (1999) identify 11

recovery strategies commonly used by hotel and restaurant operations.They classified these strategies into five separate areas (compensatoryresponses, managerial responses, corrective responses, empatheticresponses, and no action taken). In a restaurant setting, strategies con-sisting of discounts and free meals were by far the preferred recoverytactic while room upgrades were the most commonly used methodin the hotel segment. Prior research further suggests that satisfactionwith the recovery effort varies depending on the various combina-tions of recovery methods (Sparks and McColl-Kennedy, 2001). In thecontext of theme parks, apology, correction, empathy, compensation,follow-up, acknowledgement, explanation, exceptional treatment, andmanagerial intervention are the most frequently encountered servicerecovery methods (Lewis and McCann, 2004). According to Davidow(2000), there are six different dimensions of organizational responsesto service failures (timeliness, facilitation, redress, apology, credibil-ity, and attentiveness) that affect post-complaint customer behaviorssuch as repurchase and word-of-mouth activity. But it is importantto bear in mind that service recovery strategies are highly context-specific. The level of post-recovery satisfaction may depend on severalfactors such as the magnitude of the service failure, the customer’sperception of the criticality of the consumption, and whether the ser-vice provider or the customer is the first to notice the service failure(Mattila, 1999).

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Directions for future research

A number of problems and serious omissions currently plague researchon customer satisfaction in the hospitality and tourism literature.Although research in marketing and consumer behavior clearly sug-gests that consumers’ satisfaction judgments are at least partially drivenby affect, satisfaction studies in the field of hospitality and tourismcontinue to focus on cognitive determinants of satisfaction. Most ofthese studies have employed the disconfirmation paradigm and, hence,little is known about the role of emotions in influencing customer sat-isfaction with hospitality and tourism services. The reliance on a singleparadigm clearly hinders our understanding of the complex satisfac-tion/dissatisfaction construct.Service failures and service recovery are topics of great interest

to hospitality scholars. Research in this area has resulted in interest-ing industry-specific applications for complaint handling and servicerecovery strategies. Clearly, service recovery has an important impacton the company’s bottom-line via customer retention. But unfortu-nately, service recovery is often regarded as an operational concern,rather than a strategic weapon (La and Kandampully, 2004). To thatend, there is an urgent need to broaden our understanding of the con-sequences of dissatisfying service experiences by connecting servicerecovery to other key concepts such as customer loyalty. One avenue toget there is to systematically conduct a meta-analysis on service recov-ery studies published in the main hospitality and tourism journals.There is a dire need for more cross-cultural research in both satis-

faction and service recovery. Service encounters and recovery effortsare essentially social exchanges with interaction between the serviceprovider and customer being a crucial component of satisfaction. Giventhe degree of interpersonal contact and communication involved inmost hospitality and tourism services it stands to reason that culturalvalues are likely to influence the evaluation process. In fact, the fieldof hospitality and tourism offers an ideal context for studying culture-bound differences in customer perceptions of service encounters.In terms of methodology, satisfaction research in the field of hos-

pitality and tourism is dominated by survey research and case study(e.g., Gundersen et al. 1996; Lewis and MaCann, 2004; Poria, 2004;Hemmington et al., 2005). Since there is no common instrument tomeasure satisfaction, the validity of the measures used is somewhatof a concern. Particularly in the area of hospitality and tourism, theliterature lacks empirical studies that compare the validity and reliabil-ity of various measures across studies (Crompton and Love, 1995; Ohand Parks, 1997). The Critical Incident Method (CIT) has been widelyapplied to understand hospitality customers’ reactions to service fail-ures and service recovery attempts (e.g., Bitner et al., 1990; Hoffmanet al., 1995; Mack et al., 2000; Kivelä and Chu, 2001; Lewis and Clacher,2001; Susskind, 2005;), but it is important to be aware of the limitations

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of this technique. The CIT is a retrospective research method, thusbeing subject to memory lapses. Moreover, the qualitative nature of thedata sometimes creates problems with category labels (Gremler, 2004).Unfortunately, the use of experimental designs is mainly limited to ser-vice recovery research (e.g., Levesque andMcDougall, 2000). Moreover,longitudinal studies are rare in the hospitality and tourism literature(for a rare exception see Bernhardt et al., 2000). There undoubtedlyis a need to broaden the scope of methodologies used in hospitalityinquiry.

Summary and conclusions

Integrating our discussions on customer satisfaction/dissatisfaction,service failure, and service recovery, we developed a conceptual frame-work shown in Figure 11.3. Our conceptual model proposes that whencustomers experience a service failure, the initial dissatisfaction turnsinto more specific negative emotions depending on the customers’appraisal of the responsibility of the problem. By incorporating thespecific-emotions approach with causal attribution theories, the currentmodel includes four negative emotions: anger arising from controllablefailures with others blamed, disappointment stemming from uncontrol-lable causes that can be attributed to the situation, regret resultingfrom self-blame, and worry coming from threat with uncertainty (seeYi and Baumgartner, 2004, for detailed discussion on these four emo-tions). These negative emotions will lead to customer responses to thefailure situation (e.g., complain directly on the spot, spread negativeWord-of-mouth, or vow to never return to that service provider). If thecustomers voice their dissatisfaction to the service provider, some formof service recovery is likely to follow. Customers will then evaluate theservice recovery efforts based on perceived fairness. An exceptionallysuccessful service recovery may sometimes convert dissatisfied cus-tomers into even more satisfied customers (recovery paradox) whilean unsuccessful service recovery is bound to lead to a highly negativedouble deviation effect. According to our model, post-consumptionsatisfaction may be assessed at three time points, satisfaction witha particular transaction experience (T-satisfaction), satisfaction withservice recovery effort by the organization (R-satisfaction), and over-all/accumulated satisfaction with the service provider/the company(O-satisfaction).Our framework offers a starting point for broadening our thinking on

consumers’ post-consumption evaluation processes. There needs to bean increase in the amount of effort focused on developing theory thatcan guide hospitality research on these important topics. Systematic,validated research studies, based on the guidelines suggested above,will inform us how to link the important post-purchase constructs

313 • • •

Handbook

ofHospitality

Marketing

Managem

ent

Attribution

Service failure

Disconfirmation

T satisfaction

R-satisfaction

O-satisfaction

O-dissatisfaction

Recovery paradox

Repeatpositive WOM

Post-purchase behaviorService recoveryDisconfirmation

R-dissatisfactionDouble deviation

Switchthird-party

negative WOM

T-dissatisfaction

Complaindirectly

Negativeemotions:

AngerDisappointment

RegretWorry

Servicerecovery

Fairness

Figure 11.3A conceptual model of satisfaction, service failure, and service recovery

••

•314


of satisfaction, service failure, and service recovery with consumers’behavioral responses. We hope that this chapter serves as an impetusfor such an effort.

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