Managing the Waiting Experience at Checkout [ ] Allard C. R. van Riel, Arcelor Chair of Innovation Strategy, HEC-Management School -

Transcription

1 Managing the Waiting Experience at Checkout [ ] Allard C. R. van Riel, Arcelor Chair of Innovation Strategy, HEC-Management School - University of Liège, Boulevard du Rectorat, 7 (B31) B-4000 Liège, Belgium. a.vanriel@ulg.ac.be Janjaap Semeijn, Faculty of Management Sciences, Open University of the Netherlands, P.O. box 2960, NL 6401 DL Heerlen, Netherlands. janjaap.semeijn@ou.nl Dina Ribbink, Robert H. Smith School of Business, University of Maryland, Van Munching Hall, College Park, MD 20742, USA. dribbink@rhsmith.umd.edu Yvette Peters, ypeters@yahoo.com

2 Abstract We investigate how waiting experiences at supermarket counters affect customer satisfaction. Effects of customers waiting experience on store image perceptions and satisfaction are hypothesized. Grocery store customers in the Netherlands were surveyed. Results show that more enjoyable waiting experiences result in better store image evaluations and satisfaction. The perceived length of waiting plays a crucial role. Other factors, such as control, justice and product importance were found to significantly influence satisfaction. Managing customers waiting experience can thus reduce the negative impact of waiting on satisfaction. Recommendations and a research agenda are provided. 1. Introduction Research on the satisfaction-profit chain (Anderson and Mittal, 2000) and the service-profitchain (Heskett et al., 1994; Heskett et al., 1997) shows that better service quality perceptions lead to more satisfied and loyal customers. However, waiting and delays considerably affect customers quality judgments (Dube et al., 1991; Maister, 1985; Taylor, 1994; Taylor and Claxton, 1994). There is evidence that delays and waiting are primarily a source of service dissatisfaction (Bitner et al., 1990; Clemmer and Schneider, 1993; Tom and Lucey, 1995). Services are characterized by perishability and simultaneity of production and consumption (Clemes et al., 2000), and cannot be stored (Zeithaml and Bitner, 2000). This makes dealing with fluctuating demand more difficult for service firms than for manufacturing firms. When matching supply and demand is difficult, queuing is unavoidable and service managers rate dealing with fluctuating demand as one of their biggest challenges (Zeithaml et al., 1985). Companies that manage the waiting duration at checkout well are considered to possess a competitive advantage (Kumar, 2005). Two general strategies exist for dealing with waiting and queues. First, more and better checkout counters, additional personnel, or more efficient scanning systems can be provided. Modifying the service delivery system mitigates negative effects of waiting by reducing the actual length of the wait (Sasser, 1976; Shostack, 1987). However, the possibilities of decreasing customers actual waiting time in queues are often limited: physical space limits the maximum number of checkouts and fast scanning systems are expensive (Tom and Lucey, 1995). The strategy of perception management (Dube-Rioux et al., 1988) attempts to reduce the customer s perception of the length of the waiting time ( ) without affecting the actual or objective waiting time (Tom and Lucey, 1995, p. 20). It is sufficient that customers perceive their wait as short enough and pleasant (Katz et al., 1991). The waiting experience can be improved by keeping people busy and distracted while waiting (Maister, 1985). Dellaert and Kahn (1999) also argue that the effect of pre-service delays on overall service evaluation and satisfaction can be managed by positively altering customers waiting experience. Anecdotal evidence is available about techniques such as filling time with activities and providing information about the duration or cause of the wait (Katz et al., 1991; Maister, 1985; Taylor, 1995). The field of wait-management is of increasing interest, but academic research on waiting experiences and their effects is scarce (Dellaert and Kahn, 1999; Hui et al., 1997; Hui and Tse, 1996; Taylor, 1995; Tom and Lucey, 1995). So far, most studies focused on delays and how the experience of a delay affects the satisfaction and evaluation of the service that follows (Dellaert and Kahn, 1999; Taylor, 1994). A major difference between a delay and a queue setting is the level of self-control over the wait situation. Furthermore, most research on wait perceptions was conducted in bank and airport settings, or in experimental settings simulating a bank or consultancy experience. Only few studies focused on transaction queues in supermarkets (Jones and Peppiatt, 1996; Tom and 2

3 Lucey, 1995). Little is known about how waiting at the checkout of a grocery store, affects the evaluation of the upcoming service delivery and the overall experience (Haynes, 1990; Katz et al., 1991; Tom and Lucey, 1995). To improve evaluations of services that involve waiting, customers waiting experiences must be managed better. It is therefore important to understand how customers experience waiting and how various wait-related issues eventually lead to dissatisfaction. This study is designed to explore the relationships between queuing, the waiting experience, store image and satisfaction. The study is guided by the following problem statement: What is the effect of the waiting experience in a queue at a supermarket checkout counter on customer satisfaction? The study is structured as follows. After a literature review, the research design is explained and the findings from an empirical study are reported. Conclusions are formulated, including theoretical and managerial implications. Limitations and suggestions for further research will also be addressed. 2. Literature Review Not every wait results in a similar experience, nor has it the same effects on customer satisfaction (Maister, 1985; Taylor, 1994). Waiting for service is defined as the time from which a customer is ready to receive the service until the time the service commences (Taylor, 1994, p. 56). Three types of wait can be distinguished in function of the point of time at which the wait is situated (Taylor, 1994). Customers can wait before, during, or after a transaction, called pre-process, in-process, and post-process respectively (Dube-Rioux et al., 1988). Pre-process and post-process waits are considered more unpleasant than in-process waits (Dellaert and Kahn, 1999). Pre-process waits appear longer, because customers waiting for the first human contact with a service organization are more impatient (Maister, 1985). These customers experience feelings of anxiety and fear of being forgotten. However, when waits take place at expected times and places, it does not matter whether they occur before, during or after the service (Dellaert and Kahn, 1999). Pre-service waits can be further categorized: pre-schedule waits (e.g. waiting for a dental appointment), delays (e.g. waiting for an airplane to take off), and pre-service queue waits (Taylor, 1994). This study investigates waiting in a pre-service queue. Despite the fact that other services precede the checkout (selecting groceries, asking advice from personnel, ordering fresh cheese or meat), waiting to pay is considered a pre-service wait. The checkout is a service encounter in itself: failing to live up to customers expectations during the final part of the service delivery can deteriorate all prior positive experiences (Zeithaml and Bitner, 2000). 2.1 Effects of Waiting Waiting for service is a negative experience. Service providers worry about the transfer of these negative feelings to service evaluations (Taylor, 1995). Several studies investigated effects of the actual waiting duration on service evaluation. Katz et al. (1991) and Clemmer and Schneider (1993) conducted experiments with queues of different lengths in a banksetting. Both studies found a negative relationship between how long customers had to wait in line, and their satisfaction with the received service. Taylor (1994) found an indirect relationship, where anger and uncertainty (affective reactions) mediated the negative correlation between a real delay at an airport and the perceived quality of the airline. Dellaert and Kahn (1999) conducted an experiment where students evaluated web sites after waiting for a download to be completed. They found that waiting negatively affects the overall evaluation of the website, but that there was no difference in satisfaction levels between longer and shorter waiting periods. Although Katz et al. (1991) found that not only actual waiting times, but also perceived length of the queue-duration negatively affected customer satisfaction, Hui et al. (1997) and 3

4 Hui and Tse (1996) found no significant effects of perceived time spent in a store on consumer s attitude towards that store. 2.2 Managing the Waiting Experience The waiting experience can be influenced (Dellaert and Kahn, 1999; Taylor, 1994). Larson (1987) argues that customers attitude toward queues may be influenced more strongly by other factors than by the duration of the wait. The factors to which Larson (1987) refers are the customer s perceptions of the wait. Maister (1985) provides suggestions for improving customers waiting experiences, but neither proposes a theoretical basis for his ideas nor does he offer empirical support. The principles of waiting (Maister, 1985) have been summarized by Antonides and Van Raaij (1998) into eight conditions under which customers perceive queues to be shorter and more pleasant (See Table 1). [PLEASE INSERT TABLE 1 ABOUT HERE] Variables of interest are the level of perceived control, degree of filled time, perceived social justice, value of the service, and the appearance of the waiting area. These factors can all be seen as antecedents of the waiting experience. 2.3 Evaluating Retail Shopping Services are often evaluated with a measurement of quality or a measurement of satisfaction. Although some researchers use both measures in one model (Bitner, 1990) consensus is growing that both concepts are fundamentally different in terms of their underlying causes and outcomes (Oliver, 1993a; Parasuraman et al., 1994). Quality is seen by Oliver (1993a, p. 71) as a comparison to excellence in service by the customer. Customer satisfaction is a broader concept. Service quality is one driver of customer satisfaction (Oliver, 1993a; Taylor and Baker, 1994; Zeithaml and Bitner, 2000), since customer satisfaction is also influenced by product quality, price, situational factors and personal factors (Zeithaml and Bitner, 2000). A service quality measure adapted to supermarket settings is store image (Semeijn et al., 2004). Bloemer and De Ruyter (1998, p. 501) define store image as the complex of a consumer s perceptions of a store on different (salient) attributes. Different authors have distinguished different store attributes that are part of the overall store image. These attributes are jointly referred to as the retail-mix. In line with the research conducted by Semeijn et al. (2004), three elements of the retail-mix are of interest to the present study: customers perceptions of the store s physical environment (Richardson et al., 1996), its merchandise, and the service quality (Baker et al., 1994). Customers use different retail-mix elements to form an overall evaluation of the store that will likely affect their attitude or satisfaction toward the store as a whole (Dick et al., 1995). Bloemer and de Ruyter (1998) found that store image influences loyalty through satisfaction. Customers evaluations of the entire shopping experience will thus likely be influenced by their evaluation of the store. This leads to the following hypothesis: H 1 : Store image directly affects satisfaction 2.4 The Waiting Experience Zeithaml and Bitner (2000) argue that store image, or store evaluation, is not the only antecedent of satisfaction, however. Waiting for service is generally perceived to be a negative experience (Katz et al., 1991; Taylor, 1994). An experience is defined by Gupta and Vajic (2000, p. 34) as the outcome of participation in a set of activities within a social context, where context refers to the physical setting, the arrangement of products and the social actors being present. As society becomes increasingly dynamic, time seems to be the factor most critical to customers shopping experiences (Peritz, 1993). Waiting is therefore often perceived as a time consuming experience not highly valued by customers. It seems common sense that the more an experience is disliked or found to be unpleasant, the more negative will be its impact on 4

5 the evaluation of the service of which the disliked experience is a part. Hui et al. (1997) showed that the more positive the evaluation of the service environment was, the stronger the approach behavior of customers towards a store. Customers experiences of waiting can influence perceptions of service quality and satisfaction (Larson, 1987). Therefore we hypothesize: H 2 : The waiting experience directly affects satisfaction H 3 : The waiting experience directly affects store image perceptions 2.5 Perceived Wait Duration Customers perceptions of a wait determine their waiting experience. In the eyes of customers, perceptions equal reality (Katz et al., 1991). Customers perceptions of time may differ from the objective, measured time (Hirsch et al., 1950; Hornik, 1984). Perceived wait duration, more than objective duration, seems to form the basis of reality for consumer experience, evaluation, and behavior (Barnett and Saponaro, 1985). Hornik (1984) adds that perceived wait duration is a key construct in explaining customers reactions to the wait. Consistent empirical evidence for the effect of perceived duration on satisfaction or quality evaluations is scarce. Katz et al. (1991) found that the longer a person believes he/she has waited, the more negative the service experience and evaluation will be. Limited empirical confirmation was found for the relationship between perceived wait duration and customer satisfaction (Folkes et al., 1987; Hui and Tse, 1996; Katz et al., 1991; Kellaris and Kent, 1992). Because of the appealing theory about the role of perceived duration in affecting satisfaction, perceived wait duration was included in the study. Perceived duration will be seen as a direct, negative antecedent of store image, wait experience and satisfaction. This leads to the following hypotheses: H 4a : Perceived wait duration directly, negatively affects the waiting experience H 4b : Perceived wait duration directly, negatively affects store image perception H 4c : Perceived wait duration directly, negatively affects satisfaction 2.6 Affective Responses Waits have been described as uncertain, frustrating, annoying, demoralizing, aggravating, stressful, and producing anxiety. These affective reactions can be summarized in two categories: uncertainty and anger (Taylor, 1994). When customers join a queue they do not know how long they will have to wait, and this creates feelings of anxiety and uncertainty. Increasing their uncertainty is the fear of having been forgotten or having chosen the wrong line (Maister, 1985). The longer a wait seems to last, the higher the level of uncertainty becomes. One s mood tends to bias perceptions and evaluations in a mood-congruent direction (Gardner, 1985), hence customers who are in a bad mood evaluate services more negatively and are less satisfied with the service than people in a good mood. Anger and associated feelings of annoyance, irritation and frustration are often inevitable results of delays (Sawrey and Telford, 1971). Anger can result from the uncertainty of the wait, the fact that the service provider does not live up to the promise of providing prompt service, or simply the presence of screaming children. The longer a wait lasts, the more likely the customer will experience feelings of anger and the more negative the overall service tends to be evaluated (Taylor, 1994). Uncertainty and anger mediate the relationships between wait-related-variables and service evaluations. The perceived cause of the delay, activities during the wait, perceived fairness affect uncertainty and anger felt by the customer. 2.7 Wait-related Variables The attribution of dissatisfaction, affecting how the wait is experienced and evaluated, has widely received research attention (Taylor, 1994; Zeithaml and Bitner, 2000). Weiner (1985) argues that it is part of human nature to engage in spontaneous causal thinking, particularly in 5

6 case of unexpected and negative events. Causes are identified in order to blame someone or something. Attribution theory is concerned with how people make attributions how they explain events and assign causes or blame for various outcomes (Clemmer and Schneider, 1993, p. 215). When a wait is longer than expected, customers try to determine the reasons. A consumer may, for example, perceive that an especially long wait is caused by a slow customer or an inefficient and slow checker. Similarly, a waiting line that is short or moves very fast may be attributed to an efficient checker, customers who empty their carts quickly or the presence of many service lines. Consumer attributions for the length and quality of their wait experience are numerous, but appear to have three common underlying dimensions: locus, controllability, and stability (Weiner, 1985). Locus involves a judgment on whom or what is responsible. Stability refers to the degree to which a cause is perceived as permanent (Bitner, 1990). Finally, controllability refers to the degree to which the responsible party has control over the cause (Taylor, 1994). Locus and control will be the two dimension of interest to this study. 2.8 Attribution The fact that customers attributions affect evaluations of a service encounter is well recognized. With regard to the effect of the locus dimension, customers have a strong tendency to blame the seller for product and service failures and that this negatively affects their service evaluation (Folkes et al., 1987). Yet, even if the service provider is blamed for a delay, customers may perceive varying degrees of service provider control over the delay. In general it is believed that the more control the service provider is perceived to have over the delay, the less satisfied customers are (Tom and Lucey, 1995). Bitner s (1990) model showed that the level of perceived service provider control over a service failure resulted in lower evaluation of the service. The perception that the service provider has control over the duration of the wait has a negative impact on performance evaluation and quality attributes (Taylor, 1994, 1995). Haynes (1990) mentions the effect of perceived control on the waiting time experience: the more the queue wait is attributed to factors controlled by the store, the less self-control customers feel over the situation, resulting in high levels of stress and anxiety, negatively affecting satisfaction: H 5a : Perceived store control is negatively related with the waiting experience H 5b : Perceived store control is negatively related with store image H5c: Perceived store control is negatively related with satisfaction 2.9 Degree of Filled Time While the perceived attribution for the queue-wait can make the delayed customers angrier and more frustrated, the filling of time should have a more positive effect on service evaluations. Time filled with reading tabloids at the dentist appears to pass more quickly than unfilled time (Haynes, 1990; Maister, 1985). Being attentive to the passage of time results in boredom (Maister, 1985) and unfilled time has a negative impact on the wait experience and subsequent overall service evaluation. It is therefore suggested to eliminate empty time by diverting attention away from waiting (Larson, 1987). The resource-allocation-model explains the impact of distraction on perceived wait duration. In waiting situations, customers naturally and actively estimate the wait duration and associated annoyance and frustration. Distraction increases mental activity and takes the attention away from the passage of time (Zakay, 1989). Thus, when time is perceived to be filled, less attention is paid to the passage of time, resulting in a less negative impact of the wait on experiences and service evaluations (Taylor, 1995) Activities as Filler Customers perceive time to be filled when they are engaged in activities, such as reading or filling out forms, but also passive, like watching TV or listening to music. There is some 6

7 empirical evidence that activities distract customers attention from the passage of time. Increased distraction in the form of looking at an electronic news board at a bank made customers more relaxed, the waiting experience more interesting and the overall satisfaction level higher (Katz et al., 1991). When passengers reported that their time was filled during a delay, they were less angry and consequently gave higher service evaluations than delayed airline passengers who did not perceive their time to be filled (Taylor, 1994). The way in which time is filled may further affect service evaluations (Maister, 1985) Environment as Filler Experiencing the environment as interesting or interactive is another, though closely related, way to eliminate empty time (Larson, 1987). Larson showed with examples in an anecdotal research that an actual wait reduction may not be as important as imaginative lobby design options (p. 897). He showed that live entertainment in a bank setting, in the form of music and exhibitions, resulted in a positive waiting experience. A good atmosphere and a nice layout, as perceived by customers, cause distraction and are expected to have a positive impact on the wait experience and hence the service evaluation (Hui et al., 1997). This discussion made clear that the degree to which time is perceived to be filled will likely influence the customers wait experience and service evaluation. Based on the resource allocation theory and previous research outcomes, the following hypotheses can be put forward: H 6a : Perceived degree of filled time directly, positively affects waiting experience H 6b : Perceived degree of filled time directly, positively affects store image H 6c : Perceived degree of filled time directly, positively affects satisfaction 2.10 Social Justice in the Waiting Area One of the most frequent irritants mentioned by customers at restaurants is the prior seating of those guests who arrived later. The feeling that somebody has successfully cut in front of you causes even the most patient customer to become furious. Great care to be equitable is vital (Sasser et al., 1979, p. 89). Unfair waits seem longer than equitable waits (Haynes, 1990; Maister, 1985). Does the level of perceived justice in a checkout queue affect the way the wait is experienced and the service evaluated? Notions of fairness, e.g. regarding the processing a complaint, are said to be central to customers perceptions of satisfaction with the defective products and services (Tax et al., 1998). It is likely that this same relation between fairness and satisfaction is present in the field of wait-perception. Maister (1985) and Larson (1987) mention social justice in the wait setting. Larson (1987, p. 896) concludes that in customers perceptions of queues, fear of social injustice can often dominate queue waiting times. Several incidents could occur while standing in line and which can be perceived as fair or unfair. Examples are other customers deciding to skip the line or observing that line A is moving much faster than line B, or after having stood in line for 10 minutes, customer A is almost up to be served. Then an additional checkout line opens and newcomers behind customer A scurry over to the new register, entering service approximately in a last-come, first-serve manner (Larson, 1987). Sometimes, different priority rules are on purpose applied to different customers, like for example supermarket express checkouts. Maister advises managers to ensure, regardless of what rules are being used, that (priority) rules match the customers sense of equity. That this is indeed important is shown by Larson (1987), who claimed that social justice is a key determinant in waiting satisfaction. Based on the previous discussion, it is hypothesized: H 7a : Perceived social justice directly affects the waiting experience H 7b : Perceived social justice directly affects store image perception H 7c : Perceived social justice directly affects satisfaction 7

8 2.11 Purchase Amount Waits for valued outcomes seem shorter (Haynes, 1990, p. 23). The more valuable the service, the longer a customer is willing to wait and that, hence, waiting for something of little value can be intolerable (Maister, 1985). Waiting to get out of a service environment is the worst wait of all (Maister, 1985), since no or little value is still to be received. The actual service of checking-out is likely not seen by many customers as a service and especially not as one worth waiting for: once the customer has her groceries, leaving the store as soon as possible is all that matters. What customers may perceive as value of service at checkout is the value of the goods in their shopping cart in terms of the number of goods bought and the level of interest in getting the goods at this very moment. Based on this interpretation of value of service, we assume that if customers have a shopping cart full of groceries, they are more likely to be tolerant of the wait than when only few products or unimportant extras are being purchased. The level of frustration and anger will be lower in the prior situation, resulting in a lower negative effect on the wait experience and service evaluation. The amount purchased has received little research attention. Verbeke et al. (1996) consider the total monetary purchase amount per shopping trip an important factor in determining customers reactions to out-of-stock situations in a grocery store. In the field of wait perception, Meyer (1994) includes a measure of subjective importance of the goal into his research on how wait-length is determined depending on goal-attractiveness. He found that the amount of time already spent in a queue was more salient for people to whom the goal or service was less attractive. This finding supports the assumption that the lower the perceived value of the service for which one stands in line, the more aggravating the wait is perceived to be. The following hypotheses are formulated: H 8a : total purchase amount directly, positively affects the waiting experience H 8b : total purchase amount directly, positively affects store image H 8c : total purchase amount directly, positively affects satisfaction 2.12 Waiting Area Appearance Cues in an organized environment may suggest competence, efficiency, care, and other positive attributes. In a disorganized environment the physical cue may suggest incompetence, inefficiency, and poor service (Bitner, 1990, p. 73). The appearance of the waiting environment might be an important factor in determining service evaluation. The relationship between store environment and store image has been studied before (Baker et al., 1994), but in articles on wait-perception, environment is only considered in the context of filling time and entertainment, not as a separate factor. Since services are more difficult to evaluate than products, due to their intangibility, customers rely on tangible cues and physical evidence to make quality and satisfaction judgments, such as appearance and layout of the physical facilities (Zeithaml and Bitner, 2000). Layout and cleanliness of the wait area can therefore be expected to affect the store image as well as service quality and overall satisfaction. Physical surroundings are part of the service experience (Zeithaml and Bitner, 2000). The appearance of the queuing area likely affects the wait experience. Although Baker et al. (1994) did not find design factors (including store layout) to significantly influence quality perceptions of merchandise and service, the following hypotheses are proposed: H 9a : Waiting area appearance directly influences the waiting experience H 9b : Waiting area appearance directly influences store image H 9c : Waiting area appearance directly influences satisfaction The proposed relationships are visualized in Figure 1. [PLEASE INSERT FIGURE 1 ABOUT HERE] 8

9 3. Research Methodology 3.1 Experimental Design To validate the theoretical model, a natural service setting was chosen. A natural setting has the advantage that the variance in various factors, needed to test the model, is automatically provided: in the supermarkets under consideration, queue-waits of various lengths, due to various causes and in changing settings occurred (Taylor, 1994). Questioning customers about evaluations and perceptions right after they experienced a service minimizes the carry-over effect from experiences gained during prior shopping-trips and trips to other supermarkets. Sampling among customers from different supermarket formulas allows greater generalizability of the results (Clemes et al., 2000). Hence, customers at one Edah and C1000 store in Maastricht and at an Albert Heijn (AH) store in Aalsmeer were included in the sample. The three selected chains vary substantially in store design, quality and assortment of their merchandise, image, pricing and promotion strategies. These differences could affect the outcome of the study. Please refer to Table 2 for a comparison of the stores. [PLEASE INSERT TABLE 2 ABOUT HERE] 3.2 Questionnaire and Data Collection A structured, self-administered, disguised questionnaire, consisting of 48 questions, was used. Multiple-item scales were constructed to increase reliability. Respondents were asked to indicate the extent to which they agreed or disagreed with 41 statements. Each seven-point Likert-scale was anchored by strongly disagree (7) and strongly agree (1) with the intermediate point labeled as neutral. An attempt was made to take as many items as possible from existing scales to enhance validity. However, not for all constructs could scales be found. Many items were adapted, rephrased or developed to apply to the setting and interest of this study. Because the survey instrument was developed specifically for this study, a pre-test was conducted to assess the reliability of the scale items, and to refine the instrument as a whole. The items in the questionnaire were translated into Dutch via a procedure of doubleback translation (Churchill Jr., 1979). Questionnaires were distributed to customers on week days and Saturdays during a two-week period in December. Questionnaires were handed out during hours that were indicated by the supermarket managers to be busy hours with long queues : 11:00 13:00 and 16:00 18:00. Customers were approached by means of convenient and judgmental sampling right before they were to leave the grocery store. The only information provided to respondents was that the study investigated the relationship between shopping-experiences and customer satisfaction. Customers were instructed to respond with reference to today s shopping-trip. 50 completed questionnaires were obtained from all three supermarket formulas. This complete-case-approach (Hair et al., 1998) resulted in a sample of 150 cases. 3.3 Scales The factors were tested for discriminant validity (Hair et al., 1998). Cronbach s alphas were calculated to test the scales internal reliability. Finally, factors were created by summating the scales and then used for testing the hypotheses. Table 3 presents items and factors. [PLEASE INSERT TABLE 3 ABOUT HERE] Satisfaction Satisfaction consists of a rational and emotional component (Yu and Dean, 2001). Thus, two types of satisfaction questions were included in the final questionnaire: three questions relating to rational satisfaction and three questions relating to emotional satisfaction. The questions were taken from a scale developed by Oliver (1993b) and customized for the present study. Principal component factor analysis revealed that in the present study customers did not seem to distinguish between two components of satisfaction. The factor Satisfaction had an Eigenvalue of 3.96 and explained 66.05% of the total variance. 9

10 3.3.2 Store Image Based on measures developed and tested by Semeijn et al. (2004) and Wu and Petroshius (1987), nine items of store image were included in the questionnaire. It was expected that the store image scale would provide three factors: layout, merchandise, and service. Factor analysis with Varimax rotation generated only two factors. The same three items loaded on the first factor, Service, with an Eigenvalue of 3.04 and explaining 50.6% of the variance, similar to previous research (Semeijn et al., 2004). The second factor is a combination of Semeijn et al. s (2004) Layout and Merchandise items and was for this study renamed into Merchandising. Merchandising includes strategies related to layout and display as well as breadth and depth of product range (Brassington and Pettitt, 2000). Merchandising had an Eigenvalue of 1.14 and explained 18.98% of the total variance Waiting Experience Waiting experience was measured with four items, adapted from previous studies (Katz et al., 1991; Mehrabian and Russell, 1974). One factor was identified, with an EigenValue of 2.90, explaining 72.55% of the total variance Perceived Wait Duration It was decided to put the three variables relating to this factor into a separate factor analysis. Initially, the three variables were included in the factor analysis with all other wait-relatedvariables, but an unexpected resulting factor distribution, which was inconsistent with the theory, demanded an isolated treatment of the perceived wait duration items. The resulting factor Perceived wait duration had an Eigenvalue of 2.31 and explained 76.91% of the total variance Other Wait-related Constructs Attribution was measured with variables adapted from Taylor (1994) and Folkes et al. (1987) and Wait area appearance variables were adapted and modified from Bitner (1990). The factors loaded essentially as expected, except for the factor that was initially labeled Value of service, which split into two different factors: Importance of purchased goods and Amount of products purchased. The factor Attribution was expected to split into a locus component and a control component, but this did not seem to be the case. The final factor analysis generated a six-factor solution, explaining 82.14% of the total variance (KMO =.73; Chi-Square = ). The Eigenvalues (EV) and explained percentage of variance for the generated factors are: Attribution (EV: 5.47; 32.19%); Degree of filled time (EV: 2.01; 16.56%); Social justice (EV: 2.82; 16.60%); Purchase importance (EV: 1.01; 5.49%); Amount of products purchased (EV: 1.18; 6.96%) and Wait area appearance (EV: 1.47; 8.64%). The discriminant validity of all factors was good, since all average-variance-explained values (reported in Table 3) exceed the squared correlations between all six constructs (see Table 4) (Fornell and Larcker, 1981). The internal reliability of the six factors was good with values well above Results 4.1 Correlations In Table 4 correlations between all factors are displayed. [PLEASE INSERT TABLE 4 ABOUT HERE] Significant correlations exist between all independent variables and the four evaluation variables and among the evaluation criteria as well. Seven of the hypothesized correlations can be considered moderate to strong (>.50). Due to their relatively strong relationships with the four evaluation variables, it is these seven independent variables that can be expected to be of highest importance in explaining the dependent variables in the regression analyses that will be discussed in the next section. 10

11 4.2 Regression results To assess the degree and character of relationships between the dependent and independent variables and to conclude which wait-related variables influence service evaluation the most, multiple regression analysis was used. The hypothesized relationships in the model were tested independently by means of four multiple regression analyses: one analysis with each of the four evaluation criteria as the dependent variable. The relationships hypothesized in the model, serving as an input for the regression analyses, are summarized in Figure 2. [PLEASE INSERT FIGURE 2 ABOUT HERE] Differences between the three Supermarket Formulas Before conducting the regression analyses, the factors were investigated on a descriptive level: all construct-means were examined for their level of concurrence between the respondents of the three stores. The differences between stores of all variables were analyzed with One-Way-ANOVA, reported in Table 5. [PLEASE INSERT TABLE 5 ABOUT HERE] Customers of the three supermarkets only had significantly different perceptions on three of the eleven factors. The degree to which customers perceived their time at the checkout to be filled (due to distractions and things to look at) was quite low in general (mean > 4), with Albert Heijn significantly scoring below the other two stores. Second, customers were overall quite satisfied with the level of fairness with which they perceived they were being treated in the queues (mean = 2.38). However, customers at the Albert Heijn perceived the most social justice during their wait and customers at the C1000 the least. Finally, there appears to be a significant difference in the perceptions of how organized and tidy the waiting area was. Customers of the C1000 appeared to be most content with the appearance of the waiting-area. Table 5 reveals that the customers were quite satisfied with their supermarkets (mean = 2.77), evaluated service and merchandising relatively positively (means of 2.48 and 2.93), did not dislike their wait experiences very much (mean = 3.22), did not perceive very long waits (mean = 4.53), and did not seem to attribute the cause for the wait duration solely to the supermarket (mean = 4.38). To test whether the data of the three retailers could be pooled, F-tests were applied to regressions according to the complete regression-equation (1) and between two sub-samples at the time. The Chow-test tests the following null-hypothesis (H 0 ): the same relationship exists between dependent and independent variables across retailers. Or in other words: the parameters in a regression model are the same in separate sub-samples (Chow, 1960). The results of the Chow-tests were inconclusive on pooling the retailer data. One test accepted the Ho while two others did not. Since pooling the data is more in line with this research s aim (exploring the relationship between queue perceptions and service evaluation instead of differences between stores) and helps in keeping the model clear, the data of the three retailers was pooled in testing the hypotheses Predictors of Satisfaction Variance inflation factors (VIF) were examined (Hair et al., 1998). The analysis revealed that wait experience, wait duration, and attribution had VIF-values between two and three, causing multicollinearity in the model. In the case of a small sample, with high correlations between independent factors, Hoerl and Kennard (1970) suggest using Ridge regression to reduce the effects of multicollinearity. A Ridge regression was thus conducted to minimize the effects of multicollinearity. A bias of k =.4 seemed sufficient to cancel out the effect of multicollinearity, since with this bias-level wait duration revealed to be of significant influence on satisfaction, just as hypothesized and shown in the correlation table. Even at the highest possible bias (k = 1) did the relationship between social justice and satisfaction remain negative, indicating that the 11

12 more people perceive they are being treated in a fair and equal way, the more dissatisfied they are with the overall service. It is shown that H 7c is not supported. The outcomes of the first regression analysis are shown in Table 6: [PLEASE INSERT TABLE 6 ABOUT HERE] The goodness-of-fit is quite high: R²adj. =.534. An F-value of was found (Sign. =.000). The results in Table 6 show that six out of ten independent variables have a direct effect on satisfaction. The results imply that positive perceptions about service and merchandising led to higher levels of satisfaction as was hypothesized (H 1 ). Besides, wait experience also accounted for a relatively high percentage of the level of satisfaction compared with the other variables (=.179): the less people disliked their time in line, the higher was the level of satisfaction with the overall shopping experience (H 2 ). The main expectation of this study is supported: waiting at the checkout counter influences satisfaction levels. The longer the customers felt they had to wait, the lower their level of satisfaction with the shopping-trip (H 4c ). In addition, the more customers perceived that the reason for the wait was in the hands of the store and could have been controlled, the more dissatisfaction occurred (H 5c ). Finally, the level of importance of the purchased products also seemed to be directly, positively related with satisfaction (H 8c ): the more important the purchased products were to the customers in line, the more satisfied they were with the shopping experience. Surprisingly, the effect of degree of filled time on satisfaction (H 6c ) was not significant (t = 1.48). Amount of products purchased (H 8c ), and appearance of the waiting area (H 9c ) were also not found to significantly explain the variation in satisfaction Predictors of Waiting Experience A regression analysis was conducted to test the hypotheses on the relationship between queuewaits and wait-related variables and the way customers experience the wait. In a standard regression, wait duration and attribution showed signs of multicollinearity (VIF-values above 2.5). Besides, attribution was found to be just non-significant in explaining the wait experience of customers (t = ), which is strange given the high correlation between the two variables (r = -.630). A Ridge regression with a relatively small bias of k = 0.45 was used to account for the multicollinearity suspicion. This regression resulted in a high R²adj. of.559 (F = , Sign. =.000), which indicates that almost 56% of the variance in the wait experience of customers can be accounted for by the variables in the regression analysis, which are presented in Table 6. The results show that the longer customers found they had to wait, the more unpleasant did they perceive their waiting experience (supporting H 4a ). Wait duration was the most important factor determining the customers wait experience ( = -.247). Other variables that made the time in the queue a more unpleasant, frustrating, and boring experience, were first of all social justice : an unfair treatment of the queues and customers reduced the pleasantness of the wait experience (supporting H 7a ). The same reasoning goes for attribution : the more people attributed the cause and controllability of the wait to the service provider, the more unpleasant they experienced the wait (supporting H 5a ). The degree to which customers perceived their waiting time to be filled with distractions and things to look at was an important factor that enhanced the waiting experience: the more customers felt occupied in the line, the more pleasant was perceived to be (supporting H 6a ). A nicely looking, clean queuing area and a sense of importance of the products just bought were also factors, although of lower impact, that made the wait experience more enjoyable (supporting H 9a at a.10 significance level and supporting H 8a ). Surprisingly, the hypothesis which expected customers with only few products in their carts to experience the wait to be more aggravating and unpleasant than people with many products was not supported (H 8a ). Figure 3 shows the empirically validated model. 12

13 [PLEASE INSERT FIGURE 3 ABOUT HERE] 5. Discussion Based on previous research (Oliver, 1993a; Zeithaml and Bitner, 2000), three evaluation criteria were defined: customer satisfaction, service quality, and wait experience, with service quality being measured by store image, as suggested by Semeijn et al. (2004). Contrary to findings of Yu and Dean (2001), satisfaction was not perceived by supermarket customers to consist of a cognitive and an emotional component, resulting here in one overall satisfaction measure. Two store image factors were revealed in a factor analysis: service and merchandising. On service loaded items of employee friendliness, knowledge, and helpfulness, and on merchandising items of store layout, product assortment and physical facilities. Positive store image perceptions lead to higher levels of satisfaction, supporting H 1. The more customers perceived that employees were friendly, helpful and knowledgeable, and the more these customers were attracted by the physical facilities, layout, and product assortment, the more satisfied they were with their overall shopping experience at their supermarket. This confirms previous findings (Bitner, 1990; Bloemer and de Ruyter, 1998). It also provides further support for the notion that store image is an antecedent of satisfaction and that both concepts are thus fundamentally different (Oliver, 1993a). With respect to H 2, there is strong support for the view that customers wait experiences are directly related to their level of satisfaction: the less customers disliked their time in line (or the more they enjoyed it), the higher their level of satisfaction with the overall shopping experience. Ensuring that customers feel more relaxed, less bored and frustrated while waiting could therefore increase customer satisfaction. The positive relationship between customers waiting experience and satisfaction level can likely be explained by the mood-congruency-theory. This theory states that mood tends to bias perceptions and evaluations in a mood-congruent direction (Gardner, 1985; Solomon et al., 1999). The theory could be extended to wait experiences: customers who are relaxed, joyful and not bored during a wait will evaluate the service more positively and are more satisfied with the service than people who feel stressed, agitated and bored. 5.1 Link between Perceived Wait Duration and Evaluation Criteria In previous research, the worries of service providers about the transfer of negative reactions to delays onto evaluations of service were expressed (e.g. Taylor, 1995). The results from the present study lend further support for the insight that delays and queue-waits, and the duration thereof, are negatively related to service evaluations (Katz et al., 1991; Taylor, 1995; Tom and Lucey, 1995). According to expectations, customers reported lower satisfaction levels and more unpleasant wait experiences the longer they perceived the wait to last, supporting (H 4a + c). This result complements the study by Taylor (1994) who only found an indirect effect between perceived delay duration and overall service evaluation via affect. The current study, however, provides evidence that the length of the queue wait, as perceived by the customer, is a direct predictor of customer satisfaction and by far the strongest direct influencer of a customer s wait experience. This result contradicts Hui et al. s (1997, p. 101) claim that a direct relation between perceived wait duration and service evaluation may look intuitively appealing, but there is very little empirical support for it. Customers waiting duration perceptions also influenced the evaluation of store image. There is a significant relationship between delay duration and satisfaction, mediated by the wait experience and merchandising. These mediating relationships intensify the negative impact of perceived wait duration on customer satisfaction levels. 5.2 Link between Wait-related Variables and Evaluation Criteria When customers have to wait in line, it is not just the perceived duration of the wait that contributes to how they experience the wait and evaluate the overall service. Prior research 13

14 demonstrates that other variables can be significant as well (Dellaert and Kahn, 1999; Maister, 1985; Taylor, 1994) Attribution Attribution theory is concerned with how people explain events and assign causes or blame for various (negative) outcomes (Clemmer and Schneider, 1993). H 5 argued therefore that perceived store locus and control over the queue-wait would be negatively related to customers evaluations. This was found to be the case: the more blame and control the service provider was perceived to have over the queue-wait, the lower the level of satisfaction (H 5c ), evaluation of merchandising (H 5b partially), and wait experience (H 5a ). This finding corroborates the results of Tom and Lucey (1995) and Taylor (1995) who found that higher levels of perceived service provider control over a delay led to lower evaluations of service. So, despite the fact that customers have control over choosing their own line and cashier in a supermarket setting, service providers are, in many cases, still perceived to deserve the blame for long and slowly moving lines, with negative consequences for service evaluations. A mediated relationship between attribution and satisfaction was also revealed, with wait experience and merchandising being the mediators intensifying the negative effect of service provider attribution on satisfaction. Given this strong negative impact of attribution, it is important to guide the perceived blame and controllability away from the service provider Degree of Filled Time When customers perceived their time as filled, evaluations of merchandising and the wait itself were higher (H 6a supported, H 6b partially supported), supporting previous findings (Katz et al., 1991; 1994; Zakay, 1989; Zakay and Hornik, 1991). This finding is in line with the resource-allocation-theory which states that distractions will take away people s attention from the wait, which will result in shorter perceived wait durations, less boredom and frustration, and better overall evaluations (Larson, 1987). The expectation that a filled waiting time is more pleasant than an unfilled time and that it positively affects store evaluations, is thus substantiated by the study. Distractions by means of activities as well as by the environment both seemed effective in enhancing the waiting experience and merchandising evaluations. The more people felt they were kept occupied and provided with things to do, the less unpleasant did they experience their time in line. Similarly, the extent to which people felt distracted by the environment and number of things to look at enhanced the pleasantness of their queuing experience. Although degree of filled time appears significantly, directly related with satisfaction when looked at in isolation, when other delay-related variables are taken into consideration at the same time, only an indirect effect on satisfaction remains. Katz et al. (1991) reported a similar finding that by introducing electronic news-boards at a bank, customer satisfaction levels increased, but not significantly Social Justice The role of social justice in a waiting situation had until now not been tested empirically. The present study made an attempt to show that the more people perceived they were unjustly being served slower and later than other customers, the more dissatisfied they would be with the overall service. However, no conclusive results were found. The one significant effect found, was the direct effect of social justice on the customer s waiting experience (supporting H 7a ): the less people had the impression that other customers were given a beneficial treatment or were being served too early, the more pleasant did they perceive their time in line to be. This finding is in line with the claims by Larson (1979) and Sasser et al.(1979), who used anecdotal airport and restaurant settings. It is surprising that social justice did not seem to have a direct, significant effect on satisfaction (not supporting H 7c ), nor on store image (not supporting H 7b ). The findings even 14