Empirical evidence, observed across a variety of service industries, indicates that customers who have experienced problems with service suppliers are often dissatisfied with the ways in which problems are resolved. For example, an early study revealed that only 30-53% of customers who experienced problems with one of seven services they purchased were satisfied with the resolution (Andreasen and Best, 1977). In more recent research, only 50-67% of customers who experienced difficulties with one of five service companies were satisfied with the outcome (Berry and
Parasuraman, 1991). Furthermore, it appears that, while marketing of products and services differs in many ways, customer satisfaction with services is particularly tied to the resolution of problems. Since word-of- mouth (WoM) regarding problem resolution can be a major positive or negative force in building a firm’s reputation and retaining customers (Reichheld and Sasser, 1990), the reward to companies which resolve problems to the customer’s satisfaction appears to be very high (Hart et al., 1990).
Given the acknowledged importance of service recovery, it is surprising that so few large-scale field studies have focussed on this topic; as Kelley and Davis (1994) succinctly state: “…A dearth of empirical research confines any theoretical discussion to anecdotal reports” (p. 52). This study examines the relative importance of service recovery activities in determining overall satisfaction and consequent behavioral intentions. Data from a large field study are analyzed to address the research questions.
Background and research questions
To some degree, overall satisfaction in a service failure situation is determined by two factors: the outcome of the original service encounter based on specific service attributes (Singh, 1991), and attributes associated with the service recovery process (Parasuraman et al., 1991). Service recovery processes are those activities in which a company engages to address a customer complaint regarding a perceived service failure (Grönroos, 1988). For example, a service failure could be a core-service problem such as unavailability of the service (no service personnel with the appropriate skills are available), exceptionally slow service, mistakes in the service (e.g. bank statement errors), etc. In addition, as suggested by Kelley and Davis (1994), service failures can vary in seriousness – from something trivial (e.g. a mover being a few minutes late in arriving to pick up one’s household goods) to being very serious (e.g. the mover damaging a priceless family heirloom).
Parasuraman et al. (1988) identify two primary types of dimensions operating when consumers evaluate a service encounter: outcome
dimensions and process dimensions. Though both dimension types occur in both the original service encounter and the service recovery, the research of Berry and Parasuraman (1991) indicates that outcome is the primary driver of consumer evaluations of service during the initial service encounter, while process is the primary driver during service recovery: “A service failure is
Service recovery: impact on satisfaction and intentions
Richard A. Spreng, Gilbert D. Harrell and Robert D. Mackoy
Service recovery
Dimension types
essentially a flawed outcome that reflects a breakdown in reliability…Even though reliability is of foremost concern to customers during initial
performance of a service, the process dimensions assume prominence during recovery service” (Berry and Parasuraman, 1991, p. 46). Thus, whereas the original service outcome attributes have a strong effect on consumers during their initial experience, the service recovery process dimensions may assume great importance when consumers have a complaint. Original service and service recovery may play different roles in determining overall satisfaction, yet it is unknown how these two aspects of customer satisfaction influence overall satisfaction and behavioral intentions regarding future purchases of the service.
One might expect that satisfaction with the process of problem resolution will be more important than initial service attributes in influencing overall satisfaction and those intentions (Bitner et al., 1990; Hart et al., 1990).
Specifically, the role of customer-contact personnel during service recovery is expected to be a key factor in determining overall satisfaction (Martin, 1993). Past research has found evidence that complainers who were satisfied with the recovery response have higher repurchase intentions than those who were satisfied and did not complain (Gilly, 1987). Service recovery efforts are likely to be very salient to consumers, due to heightened attention and evaluation as a result of the service failure. In addition, the recovery process is likely to be the last experience the consumer has had with the company, resulting in a recency effect. Thus, when the consumer contemplates a service provider for the next transaction, the effectiveness of the service recovery effort may have a greater effect on intentions than the original service failure.
Further, ineffective service recovery efforts have the potential of increasing dissatisfaction. Hart et al. (1990, p. 150) found that “More than half of all efforts to respond to customer complaints actually reinforce negative reactions to service” (emphasis in original).
Within the Berry and Parasuraman (1991) framework, then, the question of relative influence of original versus recovery activities on satisfaction arises.
Thus, the first key research question addressed in this study is: given that a service problem has occurred, how important are service recovery processes relative to the initial service outcomes in contributing to overall satisfaction?
Repeat purchase behavior is an important issue for most marketers. While many marketing activities are designed to gain new customers, concern for repeat purchasing by current customers is designed to maintain existing customers by decreasing customer exit. Since the cost of gaining a new customer usually greatly exceeds the cost of retaining a customer, managers are increasingly concerned with minimizing customer defections. Research has consistently found a relationship between satisfaction and repurchase intentions (see Yi, 1990, p. 104 for a review). Therefore, one of the important consequences of satisfaction is increased repurchase intentions.
Halstead and Page (1992) found that satisfaction with the complaint response led to higher repurchase intentions for dissatisfied consumers, i.e.
satisfaction with the service recovery process influenced intentions.
Similarly, WoM has been identified in past research as an important postpurchase behavior for several reasons (Day, 1980). WoM
communication provides face-to-face, often vivid information that is highly credible. This information can influence others’ beliefs about a particular firm, and their intentions to purchase from the firm. There is also evidence Service recovery
effort
Word of mouth
that consumers give negative information and non-marketer controlled sources of information greater weight in their purchase decisions (Lutz, 1975). Finally, satisfaction/dissatisfaction has been found to an antecedent to WoM behavior (Yi, 1990).
Because the effect of service recovery versus the initial service failure on repurchase intentions and WoM has not been well researched, the second key research question addressed in this study is: among consumers who have experienced a service problem, how is satisfaction related to intentions to repurchase and to engage in positive word-of-mouth behaviors?
To address these two research questions, we studied consumers experiencing problems in a highly involving service: interstate movement of household belongings. This business is characterized by wide variance in customer satisfaction and uneven repeat purchase. The service failure examined was perceived damage of the consumer’s personal household goods by a moving company; the service recovery opportunity occurred when consumers submitted claims for the damage.
Overall satisfaction was modeled as depending on customer satisfaction with specific attributes of the moving experience. Overall satisfaction then influences repeat purchase and word-of-mouth intentions. (It should be noted that, given the long repurchase cycles in this industry, firms are generally more concerned with word-of-mouth.)
Attributes of satisfaction and hypothesized relationships
The household moving arena is complex, and there are many points at which damage to goods can occur. First, the company’s packing crew packs household goods in the consumer’s home. Next, the driver comes and supervises the same or often a different crew in moving the items into the truck. The driver then supervises another team in unloading and unpacking at the destination. Finally, in the case of damaged or lost goods, customers interact on the telephone and in person with company claims agents.
Unfortunately, although structural frameworks exist to analyze some service situations (for example, Garland and Westbrook, 1989; Singh, 1991), they are not applicable here. Prior exploratory research indicated, however, that salient attributes of the move might include:
● packing of goods;
● the timeliness of packing and pick-up;
● the driver;
● the amount of damage to the household belongings; and
● the service after delivery (claims handling).
We have classified the first four items as original service outcome attributes and the last item as a service recovery process dimension. From both the consumer’s and the firm’s perspective, the most important service failure is damaged goods, and the biggest opportunity for service recovery is after- service claims handling.
It was hypothesized that behavioral intentions for WoM and repurchase intentions are influenced by overall satisfaction, which in turn depends on specific attributes, including satisfaction regarding packing, the driver, timing and damage, as well as the process attribute of service after delivery.
The five dimensions expected to influence behavioral intentions are indicated in Figure 1.
Overall satisfaction
Summary of study methods and findings
Key research questions were addressed using data from 410 customers who reported damage following a move of their household goods. Path
coefficients were estimated for the conceptual model shown in Figure 1, and form the basis of the discussion which follows. The Appendix contains additional details regarding the study methodology and results.
The first four variables indicated in Figure 1 all relate to customer satisfaction with specific attributes of the original service, while the fifth (“claims personnel”) is associated with the service recovery process. All five were measured on five-point “extremely dissatisfied” to “extremely
satisfied” scales. Each of the five variables is hypothesized to affect overall satisfaction, which in turn influences repurchase intentions and positive word-of-mouth intentions. All paths indicated were found to be significant and positive. The model fits well and 74% of the variance in overall satisfaction is explained by the four original service and one service recovery variables.
The largest determinant of overall satisfaction is satisfaction with claims personnel, the service recovery variable; its effect even exceeds the effect of the damage variable, the original cause of the service failure. The service recovery variable also has the largest indirect effect on both intentions to repurchase and intention to recommend the service provider to friends and relatives, i.e. positive word of mouth (see Appendix). Thus, the study results support the hypothesis that service recovery dominates overall satisfaction formation and positive intentions.
According to this research, for people with service problems related to moving, satisfaction with post-delivery claims personnel during service recovery is more influential on overall satisfaction and behavioral intentions than is satisfaction with initial service outcome attributes. In fact, these data
Overall satisfaction
Word of mouth Repurchase
intention
Satisfaction with pick-up
time Satisfaction
with driver Satisfaction
with proper packing
Satisfaction with damage
Satisfaction with claims personnel
0.21 0.20
0.22
0.25
0.34
1.0
0.87
Figure 1. Service recovery model – service attributes, satisfaction, and behavioral intentions (standardized path estimates)
Post-delivery claims personnel
Key research questions
show that service after delivery has a stronger effect on intentions than does satisfaction with packing, timeliness, driver, and damage. Damage does directly affect overall satisfaction; however, although damage is the initial cause of the dissatisfaction here, it appears that, once customers are in a service recovery situation, their post-delivery treatment by customer-contact personnel is a very important factor. The degree to which the customer service staff are successful in satisfying the customer has a strong direct effect on overall satisfaction and a strong indirect effect on repurchase intentions and word of mouth. In other words, once a customer experiences a problem and seeks resolution, the performance of recovery process elements significantly influences behavioral intentions. The magnitude of this effect demonstrates the key role of this type of complaint handling.
Managerial implications and recommendations
The finding that service recovery process variables have a relatively greater effect on overall satisfaction and behavioral intentions than do original service outcome variables is congruent with results obtained from similar recovery situations in a product-marketing context (Fornell and Wernerfelt, 1987). In other words, the manner in which post-delivery service is handled can have a larger influence on overall satisfaction and behavioral intentions than does the customer’s satisfaction with original service outcomes.
Specifically, these results support the conceptual claims made by Berry and Parasuraman (1991) that service recovery process variables are more important than original service outcome variables during service recovery.
Service recovery processes may have this relatively large impact regardless of whether the recovery process had negative or positive results. It is possible that a negative result in recovery is magnified by virtue of it being the second time that the firm has failed (i.e. once in the original failure and now in the recovery attempt); Bitner et al. (1990) describe this as “double deviation” from expectations. Positive results in recovery may diminish the effect of the original failure for several reasons:
● Through effective recovery communications, the consumer is led to believe the service provider is fair (e.g. admits its mistakes, makes restitution, etc.).
● The recovery effort “takes away” all the negative consequences of the service failure.
● The service provider influences the consumer to make attributions which cause the consumer to place blame elsewhere.
Thus, in both positive and negative recovery outcomes, the recovery can take on greater importance than the original service failure.
These results have implications for a wide range of service providers, and indicate the importance of the recovery process by which service failures are handled. Once a problem occurs, the way in which the firm deals with the customer can both influence the consumer’s satisfaction with the aspect of the service failure (in this case “damage”) and affect overall satisfaction, repurchase intentions and word of mouth.
Several specific recommendations follow from these findings. Though some of these recommendations have been articulated previously, this is the first time the recommendations are supported by such strong empirical evidence.
First, companies should develop an excellent service recovery program. The emphasis of such a program should be on training customer-contact and Positive results in
recovery
Importance of recovery process
claims personnel. Service personnel who deal with dissatisfied customers must understand their critical role. They should be trained not only to deal with the actual service failure, but also to do so in such a way that the consumer is satisfied with the way in which the problem is resolved. These service recovery personnel also should be given the power necessary to address the service failure adequately. Unsolicited comments provided by respondents indicated that “token” responses by a company resulted in the most vehemently negative responses. As an example of a company which avoids this problem, Firnstahl (1989) describes a customer satisfaction program in which front-line employees were given responsibility and authority to correct problems, without having to get approval from
managers. When there is a service failure, any employee can do anything to make the customer happy.
Second, once a service recovery program is in place, companies should actively encourage complaining behavior (see Halstead et al., 1993). Some firms provide guarantees that offer substantial benefits for those who complain. For example, Embassy Suites provides a free stay if the customer is not 100% satisfied, and this guarantee is likely to elicit complaints that would not normally be made. Too often customers choose not to complain, and instead just take their business to a competitor. The company has a better chance of retaining a customer by encouraging that customer to complain, and then addressing the complaint, than it does by assuming that non-complaining customers are satisfied. Identifying and contacting consumers who have experienced service failure is a necessary first step in trying to rectify problems.
Third, because it is more cost effective to retain a customer than it is to attract a new customer (see Fornell and Wernerfelt, 1987), companies should reevaluate their relative budget allocations to these two activities. Are service recovery programs adequately funded? As Firnstahl (1989) points out, although service recovery programs can be expensive, they can be viewed as opportunities to make service system improvements that will ultimately result in more customers who are satisfied with the firm, as well as reductions in costs through the improvements on the service delivery system. Since each complaint often represents many other customers who were dissatisfied, but did not complain, actively encouraging customer complaints for the purpose of improving the service delivery system is an excellent way to collect information about the firm’s performance. Further, service recovery programs can provide benefits by viewing it as positive word-of-mouth advertising.
The current study does raise additional questions. For example, why did service recovery activities play such a large role in forming overall satisfaction? Future research can address the specific reasons why this is true. A second question concerns the accuracy of measuring customer evaluations only after the problem occurred. In this study, it is possible that by collecting data only after the recovery process (and therefore, after the damage occurred), consumer responses to other original service attributes are biased. Given how data were collected in this study and in virtually all other studies of service recovery, it is impossible to analyze the effects of measurement timing. Future longitudinal studies can address the question of whether measurement bias is introduced by collecting data only at the conclusion of service recovery efforts.
Encouraging complaints
Reevaluating budget allocations
The present study provides evidence of the importance of service recovery in producing satisfied customers who intend to use the firm’s services in the future, and would provide positive word of mouth. Service recovery was found to be even more important than the original service failure that led to the service recovery interaction. Firms can and should use service failures to identify service system problems, reduce customer defections, and increase loyalty and positive word of mouth.
References
Andreasen, A.R. and Best, A. (1977), “Customers complain – does business respond?”, Harvard Business Review, Vol. 55, July-August, pp. 93-101.
Berry, L. and Parasuraman, A. (1991), Marketing Services, The Free Press, New York, NY.
Bitner, M.J., Booms, B.H. and Tetreault, M.S. (1990), “The service encounter:
diagnosing favorable and unfavorable incidents”, Journal of Marketing, Vol. 54, January, pp. 71-84.
Day, R. (1980), “Research perspectives on consumer complaining behavior”, in Theoretical Developments in Marketing, Lamb, C.W. and Dunne, P.M. (Eds), American Marketing Association, Chicago, IL, pp. 211-5.
Firnstahl, T.W. (1989), “My employees are my service guarantees”, Harvard Business Review, Vol. 67, July-August, pp. 4-8.
Fornell, C. and Wernerfelt, B. (1987), “Defensive marketing strategy by customer complaint management: a theoretical analysis”, Journal of Marketing Research, Vol. 24, November, pp. 337-46.
Garland, B. and Westbrook, R. (1989), “An exploration of client satisfaction in a nonprofit context”, Journal of the Academy of Marketing Science, Vol. 17, Fall, pp. 297-303.
Gilly, M.C. (1987), “Postcomplaint processes: from organizational response to repurchase behavior”, Journal of Consumer Affairs, Vol. 21, Winter, pp. 293-313.
Grönroos, C. (1988), “Service quality: the six criteria of good perceived service quality”, Review of Business, Vol. 9, Winter, pp. 10-3.
Halstead, D. and Page, T.J. (1992), “The effects of satisfaction and complaining behavior on consumer repurchase intentions”, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, Vol. 5, pp. 1-11.
Halstead, D., Dröge, C. and Cooper, M.B. (1993), “Product warranties and post- purchase service”, Journal of Services Marketing, Vol. 7 No. 1, pp. 33-40.
Hart, C.W.L., Heskett, J.L. and Sasser, W.E., Jr (1990), “The profitable art of service recovery”, Harvard Business Review, Vol. 68, July-August, pp. 148-56.
Kelley, S.W. and Davis, M.A. (1994), “Antecedents to customer expectations for service recovery”, Journal of the Academy of Marketing Science, Vol. 22, Winter, pp. 52-61.
Lutz, R.J. (1975), “Changing brand attitudes through modification of cognitive structure”, Journal of Consumer Research, Vol. 1, March, pp. 49-59.
Martin, C.L. (1993), “Editorial – welcome new readers, new publisher”, Journal of Services Marketing, Vol. 7 No. 1, p. 3.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991), “Understanding customer expectation of service”, Sloan Management Review, Vol. 32, Spring, pp. 39-48.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple- item scale for measuring customer perceptions of service quality”, Journal of Retailing, Vol. 64, Spring, pp. 12-40.
Peterson, R.A. and Wilson, W.R. (1992), “Measuring customer satisfaction: fact and artifact”, Journal of the Academy of Marketing Science, Vol. 20, Winter, pp. 61- 71.
Reichheld, F.F. and Sasser, W.E., Jr (1990), “Zero defections: quality comes to services”, Harvard Business Review, Vol. 68, September-October, pp. 105-11.
Increasing loyalty
Singh, J. (1991), “Understanding the structure of consumers’ satisfaction evaluations of service delivery”, Journal of the Academy of Marketing Science, Vol. 19, Summer, pp. 223-44.
Yi, Y. (1990), “A critical review of consumer satisfaction”, in Zeithaml, V.A. (Ed.), Review of Marketing, Vol. 4, America Marketing Association, Chicago, IL, pp. 68-123.
Appendix Method
The study population consisted of households completing interstate moves within the continental USA during a three-month period. A random sample of 5,520
households was selected and received a mail questionnaire from a major university.
An introductory note addressed the questionnaire to the person most responsible for decisions regarding the move.
A total of 1,447 questionnaires were completed, and although the 26% response rate compares favorably with research using the mail-out methodology, potential nonresponse bias was still a concern. Therefore, a telephone validation survey with a sample of respondents (143) and nonrespondents (72) was completed. The telephone survey used wording identical to that used here. Results were similar between respondents and nonrespondents, although the former tended to be slightly more satisfied on some measures. Since there was no evidence of differences in the relationships between specific attributes and overall behavioral intentions, it was deemed appropriate to proceed with detailed analysis of the mail-out results.
Subjects were instructed to rate only those aspects of the move with which they had contact. Respondents who had damage to their belongings and who completed all relevant measures were retained for this analysis. This produced a final sample size of 410.
Measures of constructs
Five-point scales anchored by “extremely dissatisfied” (1) and “extremely satisfied”
(5) were used for all measures except repeat purchase intention and word of mouth.
The repeat purchase intention measure asked: “If needed, would you select the same company again?” (yes/no). The word-of-mouth question was: “If asked, would you recommend this company to others?”, using a five-point scale anchored by “no” and
“extremely likely”, with “somewhat likely” as a midpoint.
Results
Like most measures of satisfaction, most of the data were slightly negatively skewed (Peterson and Wilson, 1992). Also as expected, satisfaction with damage was positively skewed, since all 410 subjects had contact with the claims personnel regarding damage. Means are not presented in order to preserve confidentiality regarding the amount of satisfaction/dissatisfaction.
Path analysis was conducted using LISREL. LISREL is a structural equations modeling program which estimates the path coefficients that show the relationships among variables. The coefficients can be interpreted in the same way as standardized coefficients in regression analysis, that is, larger coefficients indicate stronger relationships between variables. Parameter estimates and model fit indices (LISREL 8) are reported in Table AI.
Indirect effects of one variable on another (discussed in the text) are calculated by multiplying the standardized coefficients. For example, the indirect effect of satisfaction with the damage on WoM is 0.25 ×0.87 = 0.22, while the indirect effect of satisfaction with claims personnel is 0.37 ×0.87 = 0.32. The indirect effects are also available in the LISREL output.
■
Estimate t-Value
Antecedent relationships Initial service attributes:
Proper packing –> overall satisfaction 0.21 6.75
Driver –> overall satisfaction 0.20 6.96
Pick-up time –> overall satisfaction 0.22 7.76
Damage –> overall satisfaction 0.25 7.35
Service recovery attribute:
Claims personnel –> overall satisfactiona 0.34 11.18
Consequent relationships Effects of overall satisfaction:
Overall satisfaction –> word of mouth 0.87 24.88
Overall satisfaction –> intentions 1.00 35.46
a Claims personnel –> overall satisfaction path is significantly larger than the damage –>
overall satisfaction path at p < 0.08; it is significantly larger than the paths associated with the other three initial service attribute paths at p < 0.01
Notes:
Model fit indices are as follows: χ2= 66.53; degrees of freedom = 17; p-value = < 0.001;
goodness-of-fit index = 0.97; and root mean square residual = 0.025
Table AI. Parameter estimates and model fit indices (completely standardized results)
Richard A. Spreng is Assistant Professor of Marketing and Gilbert D. Harrell is Professor of Marketing, both at the Eli Broad Graduate School of Management, Michigan State University, East Lansing, Michigan, USA. Robert D. Mackoy is Assistant Professor of Marketing, College of Business Administration, Butler University, Indianapolis, Indiana, USA.
