Frequency of negative critical incidents and satisfaction with public transport services. II

Journal of Retailing and Consumer Services 8 (2001) 105}114

Frequency of negative critical incidents and satisfaction with public transport services. II Margareta Friman , Tommy GaK rling
* Service Research Center, Karlstad University, SE-65188 Karlstad, Sweden
Department of Psychology, Go( teborg University, P.O. Box 500, SE-405 30 Go( teborg, Sweden

Abstract A stated-preference study was conducted to investigate user satisfaction with public transport services. A convenience sample of 95 public transport users participated. The results of a previous large-scale survey were replicated in showing that overall satisfaction is related to satisfaction with treatment by employee, reliability of service, simplicity of information, and design. It was further shown that the total frequency of negative critical incidents a!ected overall satisfaction whereas the frequencies of di!erent types of negative critical incidents selectively a!ected attribute-speci"c satisfaction. In both cases relative rather than absolute frequency was important.  2001 Elsevier Science Ltd. All rights reserved. Keywords: Critical incidents; Satisfaction; Public transport service

1. Introduction Asking what makes users satis"ed or dissatis"ed with public transport services is important when operators face a steady decrease in demand (Benister, 1992). Changing the marketing strategy with the purpose to attract more users requires a focus on how user satisfaction is related to characteristics of the service (Andreassen, 1995). However, research on public transport has tended to focus on the technical aspects of the service (i.e., vehicle and facility design) rather than on the more important psychological and social aspects (Everett and Watson, 1987). A substantial amount of research has in recent years investigated consumer satisfaction (e.g., Cadotte et al., 1987; Churchill and Surprenant, 1982; Fornell, 1992; Oliver, 1980, 1997; Oliver and Swan, 1989; Tse and Wilton, 1988; Westbrook, 1987). A review of this research reveals two di!erent approaches. One approach emphasizes transaction-speci"c or encounter satisfaction, that is, satisfaction with single transactions or encounters with a product or service (e.g., Oliver, 1980; Oliver and DeSarbo, 1988). Another approach focuses on cumulative * Corresponding author. Tel.: #46-31-773-1881; fax: #46-31-7734628. E-mail addresses: [email protected] (M. Friman), tommy. [email protected] (T. GaK rling).

satisfaction (e.g., Bolton and Drew, 1991; Fornell, 1992; Westbrook and Oliver, 1991). In this approach it is assumed that satisfaction is determined by satisfying or dissatisfying encounters with a product or service over time. In both cases satisfaction is either de"ned as an overall judgment of satisfaction or decomposed into satisfaction with performance or quality attributes (Anderson and Sullivan, 1993; Cronin and Taylor, 1992; Gotleib et al., 1994). According to a model proposed and tested in Friman et al. (2001), negative critical incidents play an important role for users cumulative satisfaction with public transport services. A critical incident is an encounter that is particularly satisfying or dissatisfying (e.g., Bitner et al., 1990). Its occurrence is assumed to have a signi"cant impact on encounter satisfaction, partly because of the emotions it arouses (Mano and Oliver, 1993). An important theoretical issue is to understand how critical incidents a!ect cumulative and encounter overall and attribute-speci"c satisfaction (i.e., di!erent levels of overall satisfaction or di!erent levels of satisfaction with performance or quality attributes such as travel time, cost, or frequency of service). The frequency of occurrence of critical incidents is a possible determinant of cumulative satisfaction. On the basis of "ndings in memory research, it can be assumed that people are capable of judging the frequency of events (e.g., Greene, 1984; Jonides and Naveh-Benjamin, 1987). Some circumstances

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bolster this ability, for instance, if the events stand out (Fisk and Schneider, 1984; Taylor, 1991; Woodley and Ellis, 1989). Research also shows that people take into account the frequencies of past events when predicting future events (e.g., Medin and Edelson, 1988; Weber et al., 1993). If memory for frequencies of critical incidents is important for cumulative satisfaction, a related question asks how such frequencies are coded in memory. A direct relationship may simply exist between the level of satisfaction with a performance or quality attribute and the remembered frequency of a certain category or type of critical incident. If so, a correspondence should exist between the attributes of (attribute-speci"c) satisfaction and the ways public transport users categorize critical incidents. Second, an attribute level is assigned to each frequency (or frequency band) of critical incidents in the corresponding category. An example from public transport is that the remembered frequency of delays is recorded in memory as a certain degree of reliability of the service. Thus, the relationship between overall cumulative satisfaction and the frequency of critical incidents is not direct. If it is further assumed that overall cumulative satisfaction is related to attribute-speci"c cumulative satisfaction, as illustrated in Fig. 1 the consequence is that the latter mediates the in#uence of the frequency of critical incidents on overall cumulative satisfaction. Friman et al. (2001) examined the impact of negative critical incidents (NCIs) on attribute-speci"c and overall cumulative satisfaction with public transport services. In a survey of a representative sample of public transport users, it was shown that the remembered frequency of NCIs decreased overall cumulative satisfaction and that attribute-speci"c cumulative satisfaction mediated this e!ect. A structural model was proposed and tested using maximum-likelihood estimates based on covariances between the di!erent measures. This type of analysis makes possible to refute hypothetical causal relations. It is however not a substitute for inferences from experiments in which causes are systematically varied. Our present goal

Fig. 1. Hypothetical relationships between cumulative overall satisfaction, cumulative attribute-speci"c satisfaction, encounter attribute-speci"c or overall satisfaction, and negative critical incidents.

was therefore to replicate in a controlled experimental study the previous "nding that overall and attributespeci"c cumulative satisfaction are in#uenced by the frequency of di!erent types of NCIs. 1.1. Overview and hypotheses A stated-preference method was employed to investigate the impact of frequency and type of NCIs on overall and attribute-speci"c cumulative satisfaction. By means of this method responses are elicited to systematically varied scenarios so that causal relations can be inferred (e.g., Ben-Akiva et al., 1999; Hensher, 1994). In the present study the scenarios consisted of descriptions of NCIs which occurred with di!erent frequencies. The NCIs were exemplars of the following four types which previous research (Friman et al., 1998) has indicated that a majority of users encounter in public transport: inappropriate treatment of customers by employees (e.g., willingness to serve, knowledge, and competence); unreliability of the service (e.g., existence and frequency of delays); failure to provide adequate information (e.g., vagueness and inaccessibility of departure and destination information); and inadequate design of vehicles, equipment, and stops (e.g., stops without shelter or little space in the vehicle). As noted above negative critical incidents are de"ned as salient dissatisfying encounters. Therefore, they should have an immediate e!ect that modi"es cumulative satisfaction. Whether this holds true for the material used was tested in one phase of the study in which respondents rated the impact of the four NCIs on overall and attribute-speci"c cumulative satisfaction. The hypothesis (H1) was that the impact of the NCIs would decrease overall and attribute-speci"c satisfaction. To make possible to test for the selective e!ects of the di!erent NCIs on attribute-speci"c satisfaction, a set of attributes corresponding to the di!erent types of NCIs was selected and ratings of satisfaction on these attributes subjected to multivariate statistical analyses. Friman et al. (2001) found that attribute-speci"c satisfaction mediates the e!ect of the frequency of NCIs on overall satisfaction. By varying the frequencies of the four types of NCIs for a speci"ed time period, the following hypotheses were tested: (H2) overall satisfaction decreases with the total frequency of NCIs; (H3) attributespeci"c satisfaction decreases with the frequency of the corresponding types of NCIs. An alternative possibility is that the di!erent types of NCIs vary in how large impact they have on satisfaction. In Friman et al. (2001) an e!ect of absolute frequency was demonstrated on satisfaction. However, absolute frequency could not be distinguished from relative frequency. In the present study absolute and relative frequencies were therefore varied independently. Although no speci"c hypothesis is o!ered, it may be noted that

M. Friman, T. Ga( rling / Journal of Retailing and Consumer Services 8 (2001) 105}114

Gigerenzer and Goldstein, 1996, among others, argue that absolute frequency information is more natural for people to process. Also, inferring relative frequencies from memory may be more di$cult since it requires attention to non-occurrences. Recent NCIs are assumed to have a stronger impact on satisfaction (Folkes, 1994). If more recent NCIs are more likely to be available in memory (Tversky and Kahneman, 1973), customers may estimate the frequency of future NCIs to be higher when an NCI has occurred recently and therefore they will become less satis"ed. A low recency may conversely be perceived to imply a low frequency of future NCIs, thus satisfaction would increase. A "nal hypothesis (H4) thus states that the recency of NCIs decreases satisfaction. By means of specifying di!erent time intervals in conjunction with the frequency information, the validity of this hypothesis was examined.

2. Method 2.1. Respondents A convenience sample of 95 undergraduate students at Karlstad University, 25 men and 70 women, was recruited to the study. They participated in return for a movie check. Their mean age was 26.0 yr (SD"6.4). Table 1 presents some travel-related sample descriptives. As can be seen, respondents used public transport rather frequently although other modes were available. 2.2. Procedure A booklet was answered by respondents in "ve di!erent classes while being monitored by a female experimenter. The booklet consisted of four modules. In the "rst module respondents rated their current satisfaction with the public transport service. In this module and the

Table 1 Travel-related sample descriptives (N"95) Descriptives

%

Access to car Access to motorbike/moped Access to bike Use of public transport (journeys/month) Work Shopping Picking up/dropping o! children Visiting friends/relatives Leisure Opportunity to use other modes


50 2 89

M

SD

9.6 2.5 0.3 1.9 2.1 2.2

6.6 3.8 3.1 2.9 3.8 0.8

Estimated by respondents.
Rated on a four-point scale ranging from never (0) to always (3).

107

following two, the ratings were made of overall satisfaction (2 scales) and satisfaction with four attributes (2 scales per attribute) (see Table 3). On each scale respondents indicated a number which could range from 10 (very dissatis"ed) to 90 (very satis"ed) through 50 (neither satis"ed nor dissatis"ed). In the second module respondents read descriptions of four NCIs that they were asked to imagine had occurred. The NCIs (see Appendix A) represented the four most frequent types recorded in Friman et al. (1998): treatment by employee, reliability of service, simplicity of information, and design. For each NCI respondents rated how satis"ed they would be with the current public transport service immediately following its occurrence. In the questionnaire one description was presented on each page. Respondents were in the third module presented with nine scenarios indicating how many times each of the four NCIs had occurred during a speci"ed time period. They rated their satisfaction with the public transport service for each scenario appearing on a separate page. The NCIs were referred to by labels. Respondents had access to a single page with the descriptions and were encouraged to read a description once again whenever they felt that they did not remember it clearly. As shown in Table 2, di!erent combinations of three frequencies of occurrence of the four types of NCIs were presented in each scenario according to a fractional factorial experimental design. Random assignment was made of respondents to three groups consisting of 31 (Group A), 33 (Group B), and 31 individuals (Group C). In Group A respondents were instructed that the NCIs had occurred during the last month (recency), in Groups B and C that they had occurred during the last three months (non-recency). In Group B the absolute frequency was the same and in Group C the relative frequency was the same as in Group A. Questions aiming at describing the sample were asked in the fourth module. The descriptives included sex, age, access to di!erent modes (e.g., car, motorbike/moped, or bicycle), and how often respondents had the opportunity to choose other modes (rated on a four-point scale ranging from never to always). Finally, respondents estimated how frequently each month they used public transport for work trips, shopping trips, picking up/dropping o! children, visiting friends/relatives, and leisure trips.

3. Results 3.1. Factor analysis of current satisfaction Descriptives for the ratings of current satisfaction are displayed in Table 3. The data are given for the total sample since no group di!erences were observed.

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Table 2 Fractional factorial experimental design with four factors at three levels Types of NCIs

C1 C2 C3 C4 C5 C6 C7 C8 C9

Treatment by employee

Reliability of service

Simplicity of information

Design

Low frequency Low frequency Low frequency Medium frequency Medium frequency Medium frequency High frequency High frequency High frequency

Low frequency Medium frequency High frequency Low frequency Medium frequency High frequency Low frequency Medium frequency High frequency

Low frequency Medium frequency High frequency Medium frequency High frequency Low frequency High frequency Low frequency Medium frequency

Low frequency High frequency Medium frequency Medium frequency Low frequency High frequency High frequency Medium frequency Low frequency

Note: Low frequency"Group A 2 times last month, Groups B and C 2 and 6 times last three months; medium frequency"Group A 4 times last month, Groups B and C 4 and 12 times last three months; high frequency"Group A 6 times last month, Groups B and C 6 and 18 times last three months.

Table 3 Correlations, means (M), and standard deviations (SD) of overall satisfaction and satisfaction with attributes. Labels written in brackets are also used in the "gures Question Overall satisfaction with public transport Overall satisfaction using public transport The employees commitment Treatment by employee Trustworthiness of public transport Punctuality Comfort Number of seats Frequency of departure Appropriate information M SD

V1

V2

V3

V4

V5

V6

V7

V8

V9

V10

[V1]

1.00

[V2]

0.56

1.00

[V3] [V4] [V5]

0.39 0.32 0.56

0.34 0.44 0.51

1.00 0.68 0.41

1.00 0.37

1.00

[V6] [V7] [V8] [V9] [V10]

0.38 0.37 0.35 0.55 0.43

0.28 0.45 0.31 0.32 0.25

0.27 0.16 0.25 0.24 0.19

0.38 0.09 0.24 0.18 0.23

0.66 0.34 0.41 0.39 0.18

1.00 0.18 0.24 0.23 0.22

1.00 0.33 0.09 0.29

1.00 0.09 !0.04

1.00 0.28

1.00

58.8 19.5

64.3 21.7

48.7 23.5

52.5 22.4

63.7 21.0

62.7 22.4

58.2 23.5

49.2 27.4

50.6 27.0

55.6 23.8

In trying to replicate the previous "ndings (Friman et al., 2001), a "rst step was to examine the factor structure of the ratings of current attribute-speci"c satisfaction. A model was analyzed positing a fourfactor representation composed of the attributes treatment by employee, reliability of service, simplicity of information, and design. The parameters were estimated with the maximum likelihood method available in LISREL VIII (JoK reskog and SoK rbom, 1993). As Table 4 shows, the "t is acceptable. All parameter estimates were signi"cant. An additional analysis using LISREL VIII was performed including the measures of overall satisfaction. The model posited that overall satisfaction is in#uenced by attribute-speci"c satisfaction (Fig. 2). Table 4 shows

that the "t of the model is not quite satisfactory although all parameter estimates are signi"cant. In summary, a four-factor model of attribute-speci"c satisfaction produced an acceptable "t. The factors were treatment by employee, reliability of service, simplicity of information, and design. Furthermore, overall satisfaction was related to these factors. 3.2. Change in satisfaction related to single NCIs The study design made possible to assess the e!ect of the single NCIs on overall and attribute-speci"c current satisfaction. The ratings of current satisfaction were therefore compared to the ratings of satisfaction following a speci"ed NCI in any of the four categories. In these

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109

to design that had reliably less e!ect on all attributes except design in which case the e!ect was reliably larger. In summary, the results largely con"rmed that satisfaction signi"cantly decreases when respondents are exposed to single NCIs. NCIs related to treatment by employees, reliability of service, and simplicity of information appeared to have larger e!ects on overall satisfaction than NCIs related to design. Furthermore, type of NCI selectively in#uenced attribute-speci"c satisfaction. 3.3. Change in satisfaction related to the frequency of NCIs

Fig. 2. Standardized parameter estimates and, within parentheses, tstatistics of the estimated model of cumulative attribute-speci"c satisfaction. Table 4 Summary of alternative models for attribute-speci"c satisfaction Goodness-of-"t Four-factor model

Structural model

s (df"14, n"95) NNFI CFI RMSEA s (df"31, n"95) NNFI CFI RMSEA

23.33, p(0.06 0.89 0.95 0.08 99.17, p(0.001 0.67 0.77 0.15

Note: GFI"goodness-of-"t index; NNFI"non-normed "t index; RMSEA"the root-mean-square error of approximation.

comparisons, a measure of overall satisfaction and measures of satisfaction with the di!erent attributes were obtained by averaging in each case across the two scales assumed to measure the variable. The data were processed for the total sample since no group di!erences were observed. Table 5 shows the mean ratings of overall satisfaction and attribute-speci"c satisfaction for each type of NCI. Inspection of the results indicate that respondents in accordance with hypothesis H1 rated overall and attribute-speci"c satisfaction lower after having encountered the NCIs. Paired samples t-tests con"rmed that these changes were signi"cant. Separate oneway repeated-measures analyses of variance (ANOVAs) con"ned to the ratings of satisfaction following the NCIs yielded signi"cant e!ects of type (Table 5). Means of the ratings were compared across the NCIs by separate Bonferonni-corrected t-tests at p"0.05. For overall satisfaction, the NCI related to design had reliably less e!ect on the ratings than the other NCIs. Furthermore, the e!ects of the NCIs were largest on satisfaction with the attribute that corresponded to the type of NCI. An exception was the NCI related

In order to investigate whether the frequency of the di!erent types of NCI leads to a change in satisfaction, means of the ratings were calculated for each frequency. In Table 6 these means are displayed for each group and type of NCI. As may be seen, in support of hypothesis H2, for all NCIs overall satisfaction decreases with the frequency. Furthermore, consistent with hypothesis H3, satisfaction with the di!erent attributes decreases with the frequency of the corresponding NCIs. Separate 3 (group) ; 3 (frequency) mixed factorial ANOVAs with repeated measures on the last factor were performed on each dependent variable for each type of NCI. The Fratios from the ANOVAs are given in Table 7. Estimates of partial u (Kirk, 1995) indicating strength of the e!ects of frequency are also shown. As can be seen, the ratings of overall satisfaction yielded signi"cant e!ects of the frequency. The e!ect is larger for the NCIs related to treatment by employee and reliability of service than for the others. The ANOVAs on the attribute ratings yielded signi"cant e!ects of the frequency of the corresponding NCIs. Separate t-tests on the ratings of overall satisfaction showed that the means for low frequency di!ered from the means for medium and high frequencies whereas the di!erence between the latter means only reached signi"cance for treatment by employee and reliability of service. Furthermore, separate t-tests on the ratings of attribute-speci"c satisfaction showed that the means for low, medium, and high frequencies di!ered signi"cantly on the corresponding NCIs. Some other e!ects of the frequency on the attribute-speci"c ratings of non-corresponding NCIs also reached signi"cance, although these e!ects were much smaller than for corresponding NCIs. Table 6 also shows that the means for Group B are invariably higher than the means for Groups A and C indicating that relative rather than absolute frequency a!ects the ratings. However, except for the ratings on the design attribute, the mean di!erences between Groups A and C are not in the direction expected from hypothesis H4. Thus, recency did not seem to have any e!ect. Furthermore, as Table 7 shows, except for design the e!ect of group did not quite reach signi"cance on the ratings of overall satisfaction. Separate t-tests comparing the means of Group B to the combined means of Groups

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Table 5 Mean ratings of current and change of overall satisfaction and attribute-speci"c satisfaction Attribute

Satisfaction

Overall

Current Change

Employee

Reliability

Simplicity

Design

Current Change

Current Change

Current Change

Current Change

NCI

Employee Reliability Simplicity Design Employee Reliability Simplicity Design Employee Reliability Simplicity Design Employee Reliability Simplicity Design Employee Reliability Simplicity Design

M 61.6 25.5 23.1 28.5 39.8 50.7 14.0 23.8 25.0 41.3 63.6 23.7 11.6 29.5 51.8 53.1 34.1 32.0 26.8 42.7 53.8 40.8 43.4 44.2 22.9

t

F


14.35H 17.18H 13.62H 10.61H

24.86H

15.65H 10.68H 10.49H 4.31H

62.15H

14.08H 25.01H 14.83H 4.85H

131.56H

7.53H 9.41H 12.40H 5.54H

23.46H

6.23H 5.34H 4.86H 4.20H

58.12H

Note: On each scale respondents indicated a number which could range from 10 (very dissatis"ed) to 90 (very satis"ed) through 50 (neither satis"ed nor dissatis"ed). p(0.05. Current vs. change of satisfaction.
Change of satisfaction between di!erent NCIs.

A and C revealed, however, signi"cant e!ects on the ratings of overall satisfaction. Still, except for design, no such e!ects were observed on the corresponding attributes for the di!erent types of NCIs. In summary, the results demonstrate that the frequencies of NCIs in#uence overall satisfaction. Furthermore, frequencies of di!erent types of NCIs selectively in#uence attribute-speci"c satisfaction. There was also some indication of a stronger in#uence on overall satisfaction of NCIs related to treatment by employee and reliability of service. The results suggested that relative frequency is more important for satisfaction than absolute frequency. There were however no di!erences due to recency of the NCIs.

4. Discussion In order to account for users satisfaction with public transport services, Friman et al. (2001) outlined a theoretical framework suggesting a causal path from memory for the frequencies of negative critical incidents (NCIs) to overall cumulative satisfaction mediated by attributespeci"c cumulative satisfaction. Friman et al. (2001)

found correlational support for this hypothesis. The present study is an experimental test of whether the frequency of di!erent types of NCIs a!ects overall and attributespeci"c cumulative satisfaction. The results reported in Friman et al. (2001) concerning the relation between overall and attribute-speci"c cumulative satisfaction were supported by the present ratings of current cumulative satisfaction submitted to con"rmative factor analyses. It was shown that attribute-speci"c satisfaction with public transport services entails the attributes treatment by employee, reliability of service, simplicity of information, and design. In addition, overall satisfaction was related to attribute-speci"c satisfaction. The present results also con"rmed that the di!erent types of NCIs reported by Friman et al. (1998) had signi"cant impacts on satisfaction. In fact, all single NCIs were found to decrease current overall satisfaction with the public transport service. The impact of NCIs related to treatment by employee and reliability of service were, however, larger than the impact of the others. Furthermore, the results showed that the di!erent types of NCIs had an equally strong, selective impact on satisfaction with the corresponding attributes.

C 40.2 35.0 30.1 38.4 35.2 31.6 38.6 34.4 32.2 37.6 33.9 33.7

A 42.8 33.3 28.0 36.4 35.9 31.2 36.6 33.8 33.5 33.9 35.7 33.9

B 47.3 38.6 29.4 38.5 38.8 38.0 39.8 38.8 36.7 38.6 37.9 38.8

C 43.0 34.4 27.3 37.5 34.8 32.4 35.8 33.9 35.0 34.6 37.1 32.9

Employee

A 33.8 33.5 27.6 39.3 29.7 25.7 33.5 29.8 31.4 31.3 32.9 30.5

B 41.5 36.5 36.1 46.6 37.3 30.2 39.7 35.5 39.0 39.6 39.1 35.3

C 34.1 29.9 29.6 36.6 28.5 28.5 31.7 29.7 32.3 30.6 34.3 28.8

Reliability

A 49.1 42.5 42.9 45.5 44.7 44.2 50.9 43.5 40.1 48.0 45.3 40.8

B 57.1 51.9 50.1 55.4 51.5 51.8 58.3 52.4 48.1 57.5 49.9 51.4

C 51.0 47.2 50.3 52.9 46.4 49.2 54.6 49.1 44.8 53.5 48.6 46.3

Simplicity

A 48.9 47.1 44.2 48.9 44.7 46.8 48.5 44.7 46.9 60.4 45.8 34.8

B 75.1 67.1 68.6 72.9 70.4 67.5 75.2 65.4 70.4 81.2 70.7 59.0

Design

Note: A (n"31); B (n"33); C (n"31). Absolute frequency was the same in Groups A and B whereas relative frequency was the same in Groups A and C.

Design

Simplicity

Reliability

B 56.8 44.7 42.6 51.7 47.2 45.2 51.8 46.6 45.8 52.2 46.6 45.3

A 39.8 37.6 34.0 41.4 36.5 33.5 41.4 34.5 35.3 40.2 37.9 33.4

NCI Employee

Frequency Low Medium High Low Medium High Low Medium High Low Medium High

Overall

Measures of satisfaction

Table 6 Mean overall and attribute-speci"c satisfaction for low, medium, and high frequency of NCIs in Groups A, B, and C

C 60.5 56.2 53.5 56.7 55.9 57.7 54.7 59.5 56.1 66.6 52.6 51.1

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Table 7 F-ratios corresponding to frequency, group and their interaction, and strength of the e!ects of frequency (partial u) NCI

Overall

Employee

Reliability

Simplicity

Design

Frequency (F) u Group
(G) F;G

16.63HHH 0.10 2.56> 1.64

31.21HHH 0.17 0.34 0.18

7.54HH 0.04 1.30 0.96

9.39HHH 0.06 0.79 1.27

8.27HH 0.05 3.91H 0.79

Frequency (F) u Group (G) F;G

15.24HHH 0.09 2.56> 0.13

5.04HH 0.03 1.10 0.36

34.80HHH 0.19 1.31 1.41

3.54H 0.02 0.77 0.65

1.75 0.01 3.88H 1.09

Frequency (F) u Group (G) F;G

10.29HHH 0.06 2.58> 0.21

1.88 0.01 0.36 0.36

4.98HH 0.03 1.33 0.37

31.24HHH 0.18 0.76 0.09

1.58 0.01 3.31* 1.11

Frequency (F) u Group (G) F;G

10.72HHH 0.06 2.56> 0.69

0.82 0.00 0.36 0.67

4.34H 0.02 0.66 0.94

12.15HHH 0.07 0.79 0.86

40.58HHH 0.22 3.82H 1.26

Employee

Reliability

Simplicity

Design

df"2, 184 (before applying Greenhouse}Geisser correction of degrees of freedom).
df"2, 92. df"4, 184 (before applying Greenhouse}Geisser correction of degrees of freedom). Note: >p(0.10, Hp(0.05, HHp(0.01, HHHp(0.001.

Evidence indicates that the frequency of events is remembered (e.g., Greene, 1984; Jonides and Naveh-Benjamin, 1987). Additionally, frequency information stored in memory has been shown to a!ect judgments (e.g., Hastie and Park, 1986). Hence, it is plausible to assume that the frequencies of NCIs modify cumulative satisfaction. This was con"rmed in the present study in that the total frequency of the NCIs had a signi"cant e!ect on the ratings of overall satisfaction. The results from an experimental study thus strengthen the conclusion reached by Friman et al. (2001) based on structural equation modeling of correlational data. At the same time, the results also suggested that the frequency of di!erent types of NCIs should be weighted. The frequencies of NCIs related to treatment by employee, reliability of service, and simplicity of information had larger e!ects than the NCI related to design. However, the frequencies of the di!erent NCIs had about equally large selective e!ects on the ratings of satisfaction with the corresponding attributes. Thus, the di!erent weights may re#ect a di!erential impact of the di!erent attributes on overall satisfaction. Relative frequency rather than absolute frequency appeared to determine satisfaction. No e!ect was however obtained of the recency of the NCIs. An explanation for this negative "nding may be the opera-

tional de"nition of recency in this study (i.e., last month vs. last three months). It is possible that respondents still interpreted the information as frequencies, thus they perhaps did not focus only on the events during the last month. Further contributing to this possible #aw is that respondents did not personally experience the emotional impacts of the NCIs. In summary, the results from the present stated-preference study show that both single NCIs and memory for their frequency a!ect cumulative satisfaction with public transport services, either overall or selectively through satisfaction with the di!erent quality attributes treatment by employee, reliability of service, simplicity of information, and design. Since it may not be presupposed that stated preferences permit valid generalizations, the conclusion is strengthened by the fact that the present results are consistent with previous results of a large-scale survey (Friman et al., 1998, 2001). 4.1. Implications and conclusion The results of the previous series of studies (Friman et al., 1998, 2001) together with the present "ndings contribute to an increased knowledge of the relationship between user satisfaction with public transport services and the frequency of occurrence of encounters that di!ers

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negatively from what is expected. Furthermore, treatment by employee, reliability of service, simplicity of information, and design were found to be related to user satisfaction. The critical incident technique (Flanagan, 1954; Bitner et al., 1990; Keaveney, 1995) is a frequently used method to obtain information for improving a service. The technique identi"es critical incidents, which deviate signi"cantly from what the customer expects. The present results speak to the validity of the method in public transport by suggesting that a low frequency of negative critical incidents increases satisfaction. However, intervention studies are also needed in which managerial or other measures, which can be demonstrated to decrease the occurrence of negative critical incidents, are shown to increase user satisfaction. Identifying attributes, which are important for satisfaction with public transport services, has direct managerial implications. Perhaps, the most unique "nding in the present research is the importance of employee behavior. Here, several possibilities are available including more extensive training of employees, empowering and/or rewarding customer-oriented behavior. Although it has proven di$cult to improve the reliability of public transport services (e.g., avoiding delays), the present results nevertheless highlight that additional e!orts should be put into this. The new information systems that are being implemented in many places may hopefully reduce negative experiences of inaccessible information. The results highlight that technical equipment and their management also needs to be improved.

Acknowledgements The present research was "nancially supported by a grant to the Service Research Center from the Swedish Communications and Transport Research Board. The authors thank Bo Edvardsson and Satoshi Fujii for valuable assistance.

Appendix A. Descriptions of negative critical incidents (NCIs) A.1. Treatment by employee You are taking a journey which involves catching a connecting bus. Both the vehicle you are in and the connecting one arrive simultaneously at the stop. Together with several other passengers you get o! and run towards the connecting bus, but the driver closes the doors and drives away. It is not past the listed departure time, and it would not have taken more than 30 s for the driver to let you onboard.

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A.2. Reliability of service You decide to take a bus and arrive at the stop in plenty of time only to discover that the vehicle has already left before the scheduled time. A.3. Simplicity of information While you wait at the stop, a bus for a destination other than the one you are heading for arrives, stops, and then continues. After having left and no other bus in sight, you and other passengers begin to suspect that it was the vehicle you were waiting for. On checking the timetable, you discover that no bus going in the direction shown on the vehicle was due to depart from that stop at that time. Thus, the incorrect destination had been displayed. You must now either wait for the next one or "nd some other means of reaching your destination. A.4. Design The arriving vehicle is almost full. The driver stops and allows you and several other passengers onboard. Some of the new passengers "nd a place to sit, but others, including you, are forced to stand for the whole journey. During the remainder of the journey even more passengers are allowed onboard.

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