Waiting for service: the effectiveness of recovery strategies

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Waiting for service is a frustrating experience for many customers. It can be an important factor in the customer’s evaluation of the service and can lead to a negative impression of the service provider (Taylor, 1994). In response, service firms employ two techniques:

1 operations management to reduce the actual wait; and

2 perceptions management to reduce the perceived wait (Katz et al., 1991).

In spite of this, waits still occur, including waiting for service even with a reserved time.

The characteristics of waits – when they occur, length, knowledge, activities and cause – influence the customer’s perception of the wait and the degree to which they affect the evaluation of service. Of interest here are pre- process, post-schedule waits (Dube-Rioux et al., 1988; Taylor, 1994) where the customer waits after the reserved or appointed time to receive the service. These waits are common, annoying and can lead to customers switch- ing service providers (Dube-Rioux et al., 1988;

Keaveney, 1995; Taylor, 1994).

When customers reserve a time to receive a service and then wait, a service promise is broken. This article explores the effectiveness of recovery strategies in these failure situations. An experiment was conducted in which respondents encountered a service failure (waiting even with a reservation) at a restaurant or hotel under different conditions. Then, based on different recovery strategies, their future intentions towards the service provider were measured. The results identify the relative effectiveness of different recovery strategies when a service failure involving waiting occurs. It extends the research on waiting by incorporating the effects of recovery strategies such as compensation or assistance on service evaluation.

Background

Much of the research on waiting has focused on strategies to reduce or avoid waits through the use of operations management

techniques or altering the perceived wait through perceptions management (Katz et al., 1991; Maister, 1985). For example, queuing

theory and modification of the service delivery process are two methods that can be used to reduce waiting time. Perceptions management includes strategies or tactics that fill or occupy the customer’s time while they wait for the service (Maister, 1985). This investigation focuses on the effectiveness of recovery strategies when the service firm has broken the reservation promise and the customer has to wait.

To provide a context for this study, prior research on factors influencing waiting time and customers’ evaluation of service is reviewed. The length of wait directly affects service evaluation. Studies have consistently found a negative relationship between actual or perceived time spent waiting and service quality evaluations; longer delays result in lower service evaluation (Clemmer and Schneider, 1989; Hornik, 1982; Katz et al., 1991;

Taylor, 1994). With respect to perceived waiting time, customers frequently overestimate the amount of time they spend waiting in line (Hornik, 1982; Katz et al., 1991). As the percep- tion of waiting time increases, customer satisfaction tends to decrease (Katz et al., 1991). In this study the waiting time until service is delivered is stated:

• one hour in the case of a restaurant meal;

and

• two hours in the case of a hotel reservation.

These are considered long waits, particularly given that the promise (the reserved time) has been broken.

When customers do not know how long the wait will be, knowledge of wait, the uncer- tainty can create anxiety and uneasiness, which, in turn, influences the evaluation of the service (Hui and Tse, 1996; Maister, 1985;

Taylor, 1994). It has been proposed that customers feel better about the service if they know how long they have to wait because it reduces uncertainty (Larson, 1987; Maister, 1985). In this study, the waiting time is known and uncertainty is not an issue.

Based on the premise that occupied time is shorter than unoccupied time, activities dur- ing wait, research has found that when wait- ing time was “filled” (i.e. occupied), versus not “filled”, customers’ service evaluations were higher (Taylor, 1994). Further, the

Waiting for service: the effectiveness of recovery strategies

Gordon H.G. McDougall

Professor, School of Business & Economics, Wilfrid Laurier University, Waterloo, Ontario, Canada

Terrence J. Levesque

Assistant Professor, School of Business & Economics, Wilfrid Laurier University, Waterloo, Ontario, Canada

International Journal of Contemporar y Hospitality Management

11/1 [1999] 6–15

Hospitality industr y, Ser vices

Abstract

Two experiments examined the effectiveness of ser vice recover y strategies in situations where the ser vice firm made customers wait even though they had made a reser vation. The recover y strategies – apology only, assistance, compensation, assistance plus compensation – which reflected industr y practices, did not lead to positive future intentions towards the ser vice firm. While assistance plus compensation was the most effective strategy, respondents still held negative future intentions towards the ser vice firm.

Other factors that had an impact included the type of hospitality ser vice, restaurant or hotel, and the purpose for buying the service. The major implication was that current industr y recover y practices were inadequate in mitigating negative intentions.

When ser vice firms break a promise, effective recover y requires considerable effor t to overcome customers’ negative intentions.

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Gordon H.G. McDougall and Terrence J. Levesque Waiting for ser vice: the effectiveness of recover y strategies

11/1 [1999] 6–15

degree of filled time is related to the perception of waiting time (Taylor, 1994). Both Maister (1985) and Larson (1987) argue that unfilled time during a wait can negatively affect the waiting experience. In a similar vein, the more people pay attention to the passage of time, the slower it seems to pass (Hornik, 1982). In this study, one recovery strategy is compensation that contains an activity component (voucher for drinks or a free meal) which “fills” time.

If the cause of the wait is perceived to be under the service provider’s control, the customer’s anger increases, the perceived waiting time increases and service evaluation declines (Taylor, 1994). If customers per- ceive that the service provider has control over the cause of the service failure, including a long wait or delay, they become more angry and dissatisfied than when they per- ceive that the cause is out of the firm’s control (Bitner et al., 1990; Taylor, 1994). In this study, the service provider has complete control of the situation and has caused the customer to wait.

The type of wait also influences service evaluation. Customers can wait before (pre- process), during (in-process) or after (post- process) a transaction (Dube-Rioux et al., 1988). Pre-process waits tend to be viewed as more unpleasant than in-process waits (Dube- Rioux et al., 1988). Pre-process waits can be categorized into three types:

1 pre-schedule (customer arrives early for appointment);

2 post-schedule (customer waits after the appointed time to receive the service); or 3 queue waits (where service is usually pro-

vided on a first come, first served basis) (Taylor, 1994).

This investigation examines pre-process, post-schedule waits; waiting after the sched- uled time to receive the service. Punctuality, an issue with these type of waits, affects overall evaluation of service (Taylor, 1994). In summary, this study places respondents in a situation where the service firm has broken the reservation promise, the waiting time is known and long, and the service firm has caused the wait.

Customers expect a firm to provide the core service which includes the contractual aspects of the service and reflects the reliability of the service (i.e. accuracy, consistency, dependability and punctuality) (Gronroos, 1984; Maister, 1985; Parasuraman et al., 1991;

Taylor, 1994). When asked to identify service encounters that resulted in dissatisfying experiences, customers frequently mentioned core service failures (Bitner et al., 1990; Hoff- man et al., 1995; Kelley et al., 1993). As well,

core service failures, which can include reserved tables that were occupied, were a major reason for customers switching service providers (Keaveney, 1995). Here the core failure involves a delay in receiving the service (e.g. table not ready even though customer has a confirmed reservation for 6 p.m.).

In this situation it is anticipated that where no recovery strategy is offered, respondents’

future intentions towards the service provider will be extremely negative.

Service recovery strategies

Service recovery strategies describe the actions that service providers take in response to defects or failures (Gronroos, 1988). These actions range from “do nothing”

to “whatever it takes to fix the problem”.

Within this range, the most common and frequently used actions are:

• apology;

• assistance; and/or

• compensation (Bitner et al., 1990; Hart et al., 1990; Hoffman et al., 1995; Kelley et al., 1993).

The effectiveness of recovery strategies depends on the situation and is influenced by such factors as importance and type of service. Effectiveness is also dependent on the way in which the service provider handles the problem; responsiveness, empathy and understanding improve the effectiveness of the strategy (Bitner et al., 1990; Hart et al., 1990). Thus, both what was done and how it was done contribute to the effectiveness of the recovery strategy. For this investigation, the primary focus is on what was done in terms of the relative effectiveness of assistance and compensation. Apology was incor- porated into all the recovery strategies because it is the minimum that would be offered by a service provider.

Assistance involves actions taken to rectify the problem. The goal is to bring the

customers back to the level of services they initially expected or contracted for. Assist- ance is possibly the most effective single recovery strategy because it can bring the customer back to the original purpose of buying the service. In the case of certain core failures (e.g. waiting for service even with a reservation), it is argued that the service firm has little leeway; it must fix the problem quickly (Parasuraman et al., 1991). With this view, assistance is a necessity, and compensation plus other actions may add to the success of the recovery effort. In this study, assistance is a reduction in the time the customer waits for the service.

Compensation involves monetary payments for the inconvenience the customer has experienced. Assistance alone may not offset

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the trouble “costs” of the problem and customers may expect compensation as a fair settlement (Goodwin and Ross, 1992). Com- pensation is also an effective recovery strat- egy. Hoffman et al. 1995, found that compensa- tion (e.g. free food, discounts, coupons) was rated most effectively in restaurant service failures that included slow or unavailable service. Compensation was also effective in an experiment that involved waiting for service (Goodwin and Ross, 1992). In this study, compensation is a voucher for drinks (restaurant) or a meal (hotel) that includes an activity to occupy the waiting time.

Based on the above, it is hypothesized that:

H1: When a pre-process, post-schedule wait occurs, offering an apology only is the least effective recovery strategy with respect to improving customers’ future intentions toward the service provider.

H2: When a pre-process, post-schedule wait occurs, assistance is a more effective recovery strategy than compensation with respect to improving customers’

future intentions toward the service provider.

H3: When a pre-process, post-schedule wait occurs, assistance and compensation is a more effective recovery strategy than assistance only or compensation only with respect to improving customers’

future intentions towards the service provider.

Service expectations

Service expectations are internal standards or benchmarks against which customers judge or measure the quality of service they receive. Expectations are influenced by a set of factors including personal needs, past experience and service provider promises (Zeithaml et al., 1993). To illustrate, when a consumer purchases a service for a special occasion from a provider that promises “first class” service, relatively high expectation levels have been set. If the promises are not met, consumers are more likely to complain than in situations where the service provider set lower expectations (Parasuraman et al., 1991).

Following this, when a service failure occurs in a high versus low expectation situation, a larger gap will be created between performance and expectations. Customers will have more negative future intentions towards the service provider with a given service recovery strategy in the higher expectations situation. When service failures occur, customers are likely to hold higher expectations for service recovery from a

service firm that is delivering a superior level of service quality (Kelley and Davis, 1994).

In this study expectation levels are set depending on the purpose of the purchase; in the restaurant situation the meal is either a casual occasion or a celebration and in the hotel situation the visit is either a stop-over or a destination stay.

It is anticipated that expectation levels will affect future intentions toward the provider as proposed in the following hypothesis:

H4: When a pre-process, post-schedule wait occurs in a low expectations situation versus a high expectations situation, for a given service recovery strategy, customers’ future intentions towards the service provider will be more positive.

Methodology

The study design

The study reported here was one component of a larger project on service issues in the hospitality sector. The design of the study was guided by four decisions. First, because the major purpose of the research was to investi- gate the relative effectiveness of recovery strategies in different situations, an experimental design was employed. Second, inter- views were conducted with service managers in the hospitality sector to identify realistic service failures and service recovery strategies that had been used in response to these types of service failures. With this advice, the external validity of the experiment was increased. Third, the co-operation of a hotel was obtained and the survey was administered to hotel guests. This provided a sample that helped ensure realism and again increased external validity (McCullough, 1995). Finally, manipulation checks were conducted prior to the final design to ensure that expectation levels (two levels) were appropriate.

To test the hypotheses, an experimental procedure that used manipulations of hotel and restaurant contexts was employed. A respondent was presented with two separate service failure scenarios, one involving hotel reservations and the second involving restaurant reservations. The research design for each experiment (hotel and restaurant) was a four (levels of recovery) by two (levels of expectations) between subjects design. As shown in Tables I and II, the hotel (Table I) and restaurant (Table II) experiments were identical in terms of design but varied in terms of operational definitions.

The service recovery strategy was operationalized as a four-level factor with the following levels: “apology only,” “compensate,”

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“assist,” and “compensate and assist.”

“Apology only” was operationalized as the service provider saying: “I am very sorry for the inconvenience but there is nothing I can do to help you.” An apology was considered the minimum response and was included in

each of the remaining strategies. The guid- ance of service managers in the restaurant industry helped shape the recovery strategies.

The two expectation levels for the hotel scenarios were operationalized as a Table I

Hotel experiment Level Expectations

Low At the busiest time of the summer tourist season, you made reservations at Motel Beta that is part of a national “no frills” chain. You needed a room for an overnight stay on the way to your vacation. The chain gets a good rating from the Canadian Automobile Association. When you arrived at Motel Beta at 5 p.m. you found your room would not be ready for another two hours even though you had received a confirmation number for your reservation with a 3 p.m. check-in time. The desk clerk said: “I am very sorry for the inconvenience”.

High At the busiest time of the summer tourist season, you made reservations at Hotel Alpha, part of a national hotel chain, which the Canadian Automobile Association rates very highly. You had planned a four-day vacation with this specific hotel in mind because it offers many features including a health club, swimming pool, fine restaurants, and a reputation for giving special attention to its guests. When you arrived at Hotel Alpha at 5 p.m. you found you room would not be ready for another two hours even though you had received a confirmation number for your reservation with a 3 p.m. check-in time. The desk clerk said: “I am very sorry for the inconvenience”.

Level Recovery

Apology only “There is nothing I can do to help you.”

Compensate “There is nothing I can do to help you. For your trouble here is a voucher for a complimentary meal”.

Assist “Let me phone Housekeeping to see whether they can do your room right away.” The clerk called Housekeeping and then said: “Your room will be ready in 30 minutes.”

Compensate “Let me phone Housekeeping to see whether they can do your room right away.” The clerk called and assist Housekeeping and then said: “Your room will be ready in 30 minutes. Here is a voucher for a

complimentary meal for your trouble.”

Table II

Restaurant experiment Level Expectations

Low Last Friday morning you made a restaurant reservation on the spur of the moment for Friday night. Because you wanted to have a casual meal with your family, you chose a restaurant that is well known for good food and service in a relaxed setting. When you arrived at 6 p.m., the time you had reserved, you found you would have to wait an hour for a table. The waiter said: “I am very sorry for the inconvenience”.

High Last Friday you had restaurant reservations to celebrate a family occasion. You made reservations well in advance and you let the restaurant know that it was a special occasion. You chose a restaurant that was well known for excellent food and service in a formal setting. When you arrived at 6 p.m., the time you had reserved, you found you would have to wait an hour for a table. The waiter said: “I am very sorry for the inconvenience.”

Level Recovery

Apology only “There is nothing I can do to help you.”

Compensate “There is nothing I can do to help you. For your trouble here is a voucher for complimentary refreshments”.

Assist “Let me talk to the manager to see if we can get you a table sooner.” On returning, the waiter said:

“Your table will be ready in 20 minutes.”

Compensate “Let me talk to the manager to see if we can get you a table sooner.” On returning, the waiter said:

and assist “Your table will be ready in 20 minutes. For your trouble, here is a voucher for complimentary refreshments.”

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destination hotel for a four-day stay (high) and a no frills motel chain on the way to a vacation (low). For the restaurant scenarios, the levels were operationalized as a family celebration at a restaurant known for excellent food and service in a formal setting (high) and a casual family meal in a restaurant known for good food and service in a relaxed setting (low).

The study operationalized the future intentions by using items that measured respondents’ likelihood of engaging in exit (switch to another service provider), voice (complain to the service provider) and word of mouth (tell others about problem/recommend to friends) intentions (1 = not likely at all and 7

= extremely likely). The items were drawn from a previous study (Zeithaml et al., 1996) and are the behaviours that customers engage in when they encounter service problems (Hirschman, 1970).

Manipulation check of factors

Before finalizing the experimental design, separate manipulation checks were

performed for expectation levels. Briefly, the results showed that respondents viewed the descriptions of the special occasion restaurant (destination hotel) and the casual restaurant (motel) to be different and in the predicted direction. In both cases, respondents expected to pay more and receive more services at the special occasion restaurant (destination hotel).

In a further manipulation check, annoyance ratings were measured for the wait situation for the restaurant and hotel. For the hotel (room not ready even after check-in time) the average annoyance rating was 5.1 and for the restaurant (table will not be ready for an hour) the rating was 6.4 where 1 = “not annoyed at all” and 7 = “extremely annoyed”.

Thus, both waits were annoying with the restaurant wait being very annoying.

The questionnaire

In the study, each respondent was assigned to one of the eight treatments. The questionnaire instructions asked respondents to assume that the situation (scenario) had just happened to them and they were asked how they would react to it. One of the scenarios and the items used to measure respondents’

reaction is provided in the Appendix.

Data collection

The sampling frame for the study was guests staying at a 1,600-room hotel located in down- town Toronto, Ontario. The questionnaires were distributed over a two-week period to capture a broad range of guests. A total of 1,811 questionnaires were distributed over

the course of the study and 636 were com- pleted for an overall response rate of 35 per cent. Prior to the analysis, the questionnaires were screened for missing data, response patterns that indicated low discrimination ability and logic inconsistencies. A total of 44 questionnaires were removed, leaving a sample of 592 respondents for the analysis.

Briefly, the demographic characteristics of the sample were: the gender split was 52 per cent male, 48 per cent female; the majority of respondents (59 per cent) were between 30 and 49 years of age; annual family income was bi-modal with approximately 25 per cent of the sample between $50,000 and $70,000 and 25 per cent over $100,000; and more than 60 per cent of the respondents had an under- graduate or a graduate degree. Relative to larger populations, the sample was more affluent and had a higher education level.

This was expected, given the hotel was part of a well-known chain that targets the business traveller and the tourist market that seeks amenities.

The questionnaire included a final check on the hotel problem. Respondents’ degree of annoyance with “room not ready even after check-in” was measured and the annoyance rating was 5.0 where 1 = “not annoyed at all”

and 7 = “extremely annoyed”. Further, 70 per cent of respondents had experienced the problem of “arriving to find the room was not ready.” These results confirmed that the problem was annoying and common.

Results

Table III summarizes the distribution of the future intentions scores for the eight items. It was apparent from the means that the experimental conditions provoked definite

responses tending toward the unfavourable ends of the scales from the provider’s viewpoint. Further, the responses to the restaurant scenerios were more negative than the hotel scenerios. Overall, these results indicated that a core service failure involving waiting was bad for the provider regardless of its recovery strategy.

Reliability analysis indicated that the items could be represented by one dimension that reflected respondents’ future intentions towards the provider (alpha = 0.90 for restaurant and 0.88 for hotel). Consequently, for the hypotheses tests the eight items were added to create a single measure.

Table IV shows the cell means of the summed intentions scales along with the marginal and grand means. A striking feature of the results was the evidence that industry-standard recovery practices did not

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approach restoring the customer’s intentions toward the provider. A summed score of 56 represented the most positive expression of intentions toward the provider. The apology only, or baseline position, revealed a large gap to be bridged with any recovery strategy. This gap was not bridged. Efforts beyond standard industry practices would be required to achieve positive future intentions.

The cell means indicated a clear positive association between recovery and future intentions for both scenarios. Analysis of variance revealed significant main effects for the recovery factor for the hotel experiment and for the restaurant scenario (Table V).

Post hoc tests of the differences among the cell means supported the hypothesis (H1) that apologizing alone was the least effective response to a waiting failure. However, post hoc tests did not support the hypothesis (H2 ) that assistance produced a more favourable reaction than compensation. There was no evidence that assistance and compensation were not equally effective. Post hoc tests did support hypothesis H3 that the combination of assistance and compensation was more effective than either action alone.

The cell means suggested that expectations affect intentions as predicted by hypothesis H4 for the restaurant scenario and not for the Table III

Behavioural intentions – descriptive statistics^a

Hotel Restaurant

Item Mean SD^b Mean SD^b

1. Complain to staff 3.90^c 2.23 2.93 2.10

2. Switch to a competitor 3.10 1.76 2.65 1.63

3. Tell friends about problem 3.43 1.99 2.80 1.97

4. Do less business 2.99 1.86 2.53 1.84

5. Recommend to those who ask 2.81 1.69 2.53 1.74

6. Make first choice 2.50 1.70 2.24 1.57

7. Continue to do business 3.28 1.97 2.65 1.68

8. Encourage friends 2.71 1.67 2.56 1.61

Notes: ^aIncreasing values signify more favourable behaviour from the provider’s viewpoint

bStandard deviation

cOn average, across all treatments, a respondent rated “complain to staff” at 3.90 (scale reversed) where 1 = not likely at all and 7 = extremely likely

Table IV

Future intentions scores by scenario

Hotel experiment

Assistance and

Apology only Compensation Assistance compensation Total

Destination 19.63^a 26.79 26.68 29.94 25.41

No frills 18.56 22.71 26.12 29.56 24.04

Totals 19.12 24.64 26.38 29.75 24.71

Restaurant experiment

Celebration 14.55 19.35 19.19 24.63 19.21

Casual meal 17.81 22.42 24.62 24.94 22.54

Totals 16.04 20.97 22.21 24.78 20.95

Notes: ^aIncreasing values signify more favourable behaviour from the provider’s viewpoint. Scores can range from 8 to 56, with the mid-point being 32

Table V ANOVA results

Hotel Restaurant

Effect F p F p

Recovery 13.01 0.000 7.90 0.000

Expectations 1.48 0.225 5.73 0.017

Interaction (RxE) 0.49 0.691 0.67 0.574

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hotel scenario. Analysis of variance

supported this conclusion. The main effect of expectations was significant for the restaurant scenario but not for the hotel scenario.

The absence of a significant interaction effect for the restaurant scenario indicated there was no relationship between expectations and the incremental effects of different recovery levels. The absence of a significant interaction effect for the hotel scenario revealed that the main effect of expectations was not being masked by the level of recovery.

For the hotel scenario, recovery represents the only influence on future intentions.

Overall, the results of the two experiments suggested that when pre-process, post- schedule waits occur, the provider must, at the least, do something to partially recover.

Assistance plus compensation was most effective in every situation. Offered alone, assistance and compensation each had the same beneficial effect. Further, respondents who had planned a special occasion at a restaurant viewed the pre-process, post-schedule wait as more serious than those who had planned a casual meal.

Discussion

Concerning the overall effectiveness of recovery, the results suggested that when a service failure involving waiting occurred, service recovery strategies (including both assistance and compensation) that were represen- tative of industry practices did not lead to positive future intentions towards the service provider. In these situations, “bonding” of the customer to the firm through the service recovery strategy did not occur (Hart et al., 1990). This finding, that industry practice may not be effective at recovering, suggests that “bonding” the customer requires further efforts by the service provider.

A priori, it was assumed that a pre-process, post-schedule wait was severe; it was long, caused by the provider, and was a broken promise (Dube-Rioux et al., 1988; Taylor, 1994).

The results confirmed this; when only an apology was offered, respondents’ future intentions were very negative. Further, even when offered both assistance and compensation, respondents still held negative future intentions towards the provider. Pre-process, post-schedule waits present a considerable challenge for managers in the hospitality industry. The challenge may be met, in part, by how the recovery strategy is offered. Prior research has shown the importance of the contact employee in turning core failures into satisfactory experiences (Bitner et al., 1990).

The relative effectiveness of assistance versus compensation was equivalent. While it had been predicted that assistance would be more effective based on the notion that core failures must be quickly fixed (Parasuraman et al., 1991), compensation was as effective, supporting prior research in the hospitality area (Goodwin and Ross, 1992; Hoffman et al., 1995). Reducing the waiting time (assistance) or offering tangible compensation (which included a component to occupy the waiting time) did, to a degree, mitigate the negative intentions. It suggests that “doing

something” beyond an apology was important, but it was not enough. As noted, offering both assistance and compensation still left respondents with negative intentions.

Expectations only played a role in the restaurant scenerios. Two points are worth noting here. First, respondents’ intentions were more negative in the restaurant scenerios than the hotel scenerios (Table IV). The restaurant failure was probably more serious because the one-hour wait was relatively long compared to the time that would be taken to consume the service. Second, the celebration (high expectations), in contrast to the casual meal (low expectations), was a situation where the consequences of problems were more serious. A well-planned evening to

“honour” a family occasion was spoiled because of the service provider. In contrast, with the hotel scenerios, the wait, relative to consuming the service was smaller, and the consequences in either high or low expectations were less serious. This suggests that (un)acceptability of the wait was a more important factor in the restaurant scenerios (Dube-Rioux et al., 1988; Hui and Tse, 1996).

Consequently, the relative effectiveness of recovery strategies was dependent on the occasion.

Note: with pre-process, post-schedule waits the length of the wait was not the prime deter- minant of the respondents’ reactions. As mentioned above, the shorter wait scenerios led to more negative intentions which indicated that other characteristics, such as the consequences of waits and the wait time relative to the total time to consume the service, need to be considered when determining the relationship between waiting and service evaluation.

Implications

The major implication of this study for service managers in the hospitality industry was that, given that a core failure involving waiting had occurred, regardless of the recovery strategy, respondents held negative future Gordon H.G. McDougall and

Terrence J. Levesque Waiting for ser vice: the effectiveness of recover y strategies

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intentions. In no situation were respondents’

future intentions favourable towards the service provider. The concept that customers could be “bonded” to the firm with service recovery strategies that reflected industry practices was not supported in this study. Pre- process, post-schedule waits present a considerable challenge for service firms and probably require efforts that incorporate both what is offered and how it is offered (i.e. the process dimensions of service recovery including empathy, responsiveness and understanding).

Service firms should focus on reducing or eliminating these failures that are under their control. A major cause of these failures is overbooking; a practice that may achieve short-term gains but result in long-term costs. Customer retention and positive word of mouth are important drivers of profits in this industry and both are at risk when customers encounter these types of waits. Ser- vice firms would be well advised to examine the trade-offs between overbooking and/or insufficient staff to prepare for customers’

arrival and negative intentions towards the firm due to waits.

The recovery strategy of assistance plus compensation has the greatest positive effect on customers’ future intentions towards the provider. While the impact of this strategy does not bring customers “back” to the firm, it does mitigate, to some degree, the negative intentions. From a strategic viewpoint, offering assistance and compensation is the high- est cost but the benefit may be substantial when considering the long-term value of a customer. Regardless, at a minimum the firm needs to offer either assistance or compensation or customers will likely be “terrorists”

who do not return and spread negative word of mouth about the firm (Jones and Sasser, 1995).

Service firms should understand that, even with a pre-process, post-schedule wait, situational aspects matter. The restaurant waits led to more negative intentions than hotel waits, in spite of the fact that the waits were shorter. Further, when personal consequences were serious (e.g. a spoiled family celebration), intentions were more negative.

The staff who interact with these customers should identify the context and provide cus- tomized strategies to mitigate the negative intentions.

The limitations of the study should be recognized. The study dealt only with core service failures that involved waiting. These results may not be generalized to other types of service problems that involve breaking promises. The experiment measured stated future intentions and while researchers have found these measures to be reasonable cor-

relates for actual behaviour (Rust et al., 1995), it is recognized that there may be discrepan- cies between stated and actual behaviours.

Further, the levels of compensation were bounded by industry practices. Larger compensation levels are likely to lead to more positive intentions towards the provider.

Another limitation was that, because it was a “paper and pencil” study, it did not capture the “tone of the relationship” between the service provider and the customer in the problem situation. However, anecdotal evidence can capture the service provider’s willingness to go “beyond the call of duty,” to

“take ownership of the problem” and to

“tailor the response to the customer’s needs”.

In these instances, the customer may “bond”

to the organization because of the special way in which the service provider handled the situation. The critical incident technique allows the researcher to capture some of the relationship aspects as evidenced by findings that show the importance of the service provider in problem situations (Bitner et al., 1990). In this investigation, the results reflected a scenario that contained a brief conversation that could be described as friendly and helpful (depending on the scenario) but did not offer a strong emotional content.

Three suggestions for future research are offered. First, incorporating relationship aspects into the recovery strategies would allow for a comparison of the relative effectiveness of the tangible and intangible aspects of recovery strategies. Second, extending the research to compare the impact of service recovery strategies in other types of wait problems (e.g. waiting during the service delivery) would help in understanding the dynamics of waiting and service evaluation.

Third, extending the research to other wait situations, particularly those where the customer has higher switching costs (e.g. profes- sional services), would test the limits of customer retention when the provider makes the customer wait.

In summary, the research examined an important issue for service providers: what happens when the firm breaks a promise, makes the customer wait, and various recovery strategies that reflect current industry practices are offered? From the service provider’s perspective, the results are troubling. Customers held negative future intentions towards the service provider regardless of the recovery strategy offered including assistance plus compensation.

Clearly, customers do not like pre-process, post-schedule waits. The best strategy a service firm can pursue is to eliminate these waits, which they can do.

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Appendix. Sample scenario

Below is a situation that you might encounter concerning reservations at a hotel. Please assume that the situation has just happened to you. We would like to know how you would react to it.

At the busiest time of the summer tourist season, you made reservations at Hotel Alpha, part of a national hotel chain that the Canadian Automobile Association rates very highly. You had planned a four-day vacation with this specific hotel in mind because it offers many features including a health club, swimming pool, fine restaurants, and a reputation for giving special attention to its guests.

When you arrived at Hotel Alpha, at 5 p.m., you found your room would not be ready for another two hours, even though you had a confirmation number for your reservation with a 3 p.m. check-in time.

The desk clerk said: “I am very sorry for the inconvenience. Let me phone Housekeeping to see whether they can do your room right away”. The clerk called Housekeeping and then said:

“Your room will be ready in 30 minutes”.

Please show how likely you would be to do each of the following things by circling a number between 1 and 7. Circling a 1 means that you are not likely to do it at all and circling a 7 means that you are extremely likely to do it.

How likely would you be to:

Not at all Extremely likely likely

1. Complain to Hotel Alpha’s staff ? 1 2 3 4 5 6 7

2. Recommend Hotel Alpha to someone who seeks your advice? 1 2 3 4 5 6 7 3. Switch to a competitor in making future travel plans? 1 2 3 4 5 6 7 4. Tell friends and relatives about the problems you had at

Hotel Alpha? 1 2 3 4 5 6 7

5. Consider Hotel Alpha your first choice for accommodation? 1 2 3 4 5 6 7 6. Continue to do business with Hotel Alpha if its prices

increase? 1 2 3 4 5 6 7

7. Do less business with Hotel Alpha in the next few years? 1 2 3 4 5 6 7 8. Encourage friends and relatives to do business with

Hotel Alpha? 1 2 3 4 5 6 7