Relationships Among Service Quality, Image, Customer Satisfaction and Loyalty in a Hong Kong Franchised Bus Company

Relationships among Service Quality, Image, Customer Satisfaction and Loyalty in a Hong Kong Franchised Bus Company
Iris M. H. Yeung*
Abstract
Market share of franchised buses in Hong Kong decreases since 2004 irrespective of increase in service quality as reported by Tang and Lo (2010). This paper investigates how service quality, image, satisfaction and loyalty are related to gain insight on the decreasing market share problem based on data collected from passengers of a franchised bus company in Hong Kong in 2004. The structural equation modelling results support the hypothesis that (1) service quality affects satisfaction and image directly, (2) image affects overall satisfaction and loyalty directly, and (3) overall satisfaction affects loyalty directly. However, the results do not support the hypothesis that service quality affects loyalty directly. Service quality has only indirect effect on loyalty through image and overall satisfaction. So even though the service quality may be increasing, the indirect effect of service quality on loyalty is not adequate to increase market share.

Keywords: image, loyalty, public transport, satisfaction, service quality, structural equation model. Field of Study: Customer Service and Customer Relations

Introduction
In Hong Kong, public transport is the dominant transport mode, accounting for approximately 90% of daily passenger journeys over the past 10 years (Transport Department (1999, 2003)). Public transport comprises railways, franchised buses, public light buses, taxi service, non-franchised bus services for residents, ferries, railway feeder buses, and peak tramways. Among these modes, railways and franchised buses play an important role, carrying over seven million passenger journeys per day, or approximately 70% of the total public transport patronage (Transport Department (1995–2010)). Market share of franchised buses is generally higher than that of railways. In 2002, market share of franchised buses peaked at 39.8%, whereas market share of railways at the time was a mere 32.3%. However, with the opening of new rails, market shares of franchised buses and railways were 32.4% and 38.8% respectively in 2010. Other than competition from other modes, franchised buses compete with each other as well for the operating right of new bus routes. Moreover, the franchise can be terminated based on poor performance. Thus, service quality is essential to maintain market share and increase profitability under fierce competition.
Iris M. H. Yeung , Department of Management Sciences, City University of Hong Kong, Kowloon Tong, Kowloon,Hong Kong, Tel.: + 852-3442-8566; Fax: + 852-3442-0189, E-mail address: [e-mail] (I.M.H. Yeung)

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In fact, quality of services for both railways and franchised buses has continuously improved over the past years. Using Mass Transit Railway (MTR) and Kowloon Motor Bus Limited (KMB) as references, Tang and Lo (2010) commented that the quality of rail and bus service provision improved from 1984 to 2004, particularly in terms of service supply and based on technical measures such as vehicle-kilometre per capita and real fare increase rate. However, market share of franchised buses, including KMB, started to drop since 2004 irrespective of increase in service quality as reported by Tang and Lo (2010). As passengers decide on which transport mode to take, this paper investigates how service quality, image, satisfaction and loyalty are related in order to gain insight into decreasing market share problem from passengers‟ perspective. In line with Tang and Lo‟s study, the analysis is based on a data set collected from passengers in 2004. Further, among all the franchised bus operators in Hong Kong, KMB has the longest history and is currently the largest, occupying approximately 70% of the franchised bus share in Hong Kong. Thus, KMB‟s quality of service affects many people in Hong Kong; it is of interest to a large share of the population and therefore merits investigation. The remainder of the paper is organized as follows. Section 2 presents the literature review of the four constructs and the research hypothesis of the proposed structural model. Section 3 describes the research methodology. The results of exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation model (SEM) are provided in Section 4. Finally, Section 5 presents the concluding remarks with limitations of the study and suggestions for future research directions. Literature Review Service quality Parasuraman et al. (1985, 1988) developed the SERVQUAL instrument, which consists of 22 attributes under five distinct dimensions (i.e., reliability, assurance, tangibles, empathy, and responsiveness). They defined service quality as the difference or gap between customers‟ expectations and perceived performance and proposed to use gap scores to measure service quality. Despite the widespread use of SERVQUAL in various industries and countries, some scholars such as Brady et al. (2002), Cronin and Taylor (1992, 1994), Zhao et al. (2002) reported that service quality is more accurately assessed by the perceptions of quality rather than the „gap‟ scores. Another criticism on the SERVQUAL instrument is that the 22 associated attributes have been deemed inappropriate, or that they cannot be simply adopted for measuring service quality in all service industries (Cronin and Taylor, 1992; Lai and Chen, 2011). According to Ladhari (2009), 30 industry-specific measures of service quality have been developed between 1990 and 2007 in different industries and countries.

Corporate image Corporate image can be defined as the overall impression that is formed in people‟s minds about a firm (Barich and Kotler 1991). Some researchers thought that service quality affects image (See, for example, Ostrowski et al (1993), Aydin and Ozer (2005), Nguyen and LeBlanc 1998). Also, it has been reported that corporate image can also affect customer satisfaction and customer loyalty (see, for example, Hart and Rosenberger 2004).

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Customer satisfaction According to Oliver (1997, 2010), customer satisfaction is defined as a judgment that a product or service provided a pleasurable level of consumption-related fulfillment. Also there are two levels of individual consumer‟s satisfaction: transaction-specific satisfaction and cumulative satisfaction. Transaction-specific satisfaction or encounter satisfaction is identified as a fulfillment response to a single transaction or encounter, whereas cumulative satisfaction is a judgment based on many occurrences of the same experience and not just one-time experience. For both cases (encounter satisfaction and cumulative satisfaction), satisfaction is either defined as an overall judgment of satisfaction or decomposed into satisfaction with performance or quality attributes (Cronin and Taylor 1992). “Overall” “cumulative” satisfaction is commonly used by researchers such as Mittal et al. 1999 and Spreng et al. 1996. Loyalty According to Oliver (1997 P392;2010), loyalty is defined as “a deeply held commitment to rebuy or repatronize a preferred product or service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts that have the potential to cause switching behavior”. There are two approaches to customer loyalty: behavioural and attitudinal. Behavioral loyalty refers to a customer‟s actual behavior to repeat purchases of products or services and recommend whereas attitudinal loyalty refers to a customer‟s intention to repurchase and willingness to recommend. Attitudinal loyalty is more commonly used in many research studies (Loureiro and Kastenholz 2011) and relatively easy to measure. Relationships among perceived service quality, corporate image, overall satisfaction, and loyalty There is much previous research exploring the quality-satisfaction-loyalty (QSL) relationship. It is generally believed in marketing and service industries that (1) good service quality results in customer satisfaction, (2) good service quality attracts customers and hence lead to customer loyalty and (3) high satisfaction level is likely to create customer loyalty. However, it has also been reported that satisfaction may not be adequate enough to lead to loyalty, though loyal customers are almost typically satisfied (Cronin and Taylor 1992; Cronin et al 2000). Furthermore, corporate image is also found to affect customer satisfaction and loyalty. Customers who develop a positive image towards a company will tend to have high customer satisfaction through a halo effect (see for example, Hart and Rosenberger 2004; Lai et al 2009). Hart and Rosenberger (2004) reported that image has a “marginally significant” direct effect on customer loyalty, but a substantial effect mediated by customer satisfaction. Therefore, image can affect loyalty directly and indirectly. Based on the above literature review, this paper considers the structural model presented in Figure 1. The hypothesis proposed in the model are given below: H1: Service quality has a significant, positive and direct effect on corporate image.
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H2: Service quality has significant, positive, and direct effect on customer satisfaction. H3: Service quality has a significant, positive and direct effect on loyalty. H4: Corporate image has a significant, positive and direct effect on customer satisfaction. H5: Corporate image has a significant, positive and direct effect on loyalty. H6: Customer satisfaction has a significant, positive and direct effect on loyalty.
Methodology Sampling and Data Collection The target population of this study comprises purely KMB passengers. KMB has three main types of bus routes running through urban Kowloon, the New Territories, and crossharbour. Stratified sampling was employed to select the bus routes within each type of stratum: urban Kowloon, New Territories, and cross-harbour. Passengers over 16 years old waiting at the bus stops or stations to ride the selected bus routes and had ridden a KMB bus in the previous month were invited for interview. A total of 855 passengers were randomly selected to complete the questionnaire; only 636 samples were valid and included in the analysis. Successful response rate was 74.4%. To complete the questionnaire, passengers must be waiting for the bus at the bus stop. It should be noted that passengers arriving at the bus stop and boarding the bus immediately with little or no waiting period are relatively difficult to interview. Thus, the questionnaire must be as short as possible to encourage response, taking into consideration that respondents may easily lose their patience or may be in a hurry, as well as the fact that buses may arrive during the interview. The time for conducting the survey was scheduled from 7:00 a.m. to 11:00 p.m. on both weekdays and weekends to interview both peak-hour and non-peak-hour passengers. The interview was conducted in Cantonese in March 2004. Measurement and Data Analysis Based on a comprehensive review of the transport literature, detailed search on the printed materials and KMB Web sites, and results of focus groups, 15 attributes of service quality were derived. The order of these attributes in the questionnaire is as follows: clarity of bus number design, bus route map, bus stop location, fare, discount, bus frequency, bus punctuality, bus service time, bus route coverage, travelling/driving safety, driver attitude (anything related to the driver other than driving such as politeness and friendliness, caring about the safety of passengers when they board get on or off the bus), bus cleanliness, seat design (such as comfort, seat layout, leg space), air-conditioning, and bus stop information. Passengers‟ perception of the performance of service quality are measured by asking them to rate each service quality attribute on a satisfaction scale (1 = very dissatisfied and 5 = very satisfied). This type of measurement scale is used by researchers such as Huang et al. (2006), Lin et al. (2011), and Tam et al. (2005).

The overall satisfaction, corporate image and loyalty are measured by a singleitem. Although the use of single-item measures may weaken the estimated relationships, such measures have been used successfully in many research studies (see for example, Bolton and Drew 1991; Bolton and Lemon 1999; Cronin and Taylor 1992; Brunner et al 2008; Mittal, Kumar and Tsiros 1999). As mentioned above, the questionnaire must be short enough to encourage response. Use of multi-item scales for overall satisfaction, corporate image and loyalty will mean longer questionnaire and may affect the response rate and overall reliability. Therefore, single-item measures for these three constructs are considered adequate for this exploratory study.
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Overall satisfaction is measured on a 5-point Likert scale with (1=very dissatisfied and 5 = very satisfied). As the respondents had ridden a KMB bus in the previous month, “overall” cumulative satisfaction is appropriate in this study. Corporate image is measured on a five-point scale from “very bad” to “very good” whereas customer loyalty is measured by the intention to increase ridership in the coming month on a five-point scale from “definitely will not” to “definitely will”. Repurchase intention and willingness to recommend others are two common indicators of loyalty. As Hong Kong people are already familiar with KMB and its service and hence it is less necessary for the respondents to recommend KMB bus service to others, so this study uses repurchase intention only to measure loyalty.
In this paper, we conduct exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation model (SEM) to these data. Results and Discussion Exploratory and Confirmatory Factor Analysis Because two attributes – „bus route coverage‟ and „bus stop information‟ – have cross loading and low reliability problems, EFA is performed on the remaining 13 service quality attributes using principle axis factoring extraction method and orthogonal rotation. The results of EFA on perceived service quality are shown in Table 1. Five factors with eigenvalue greater than one are retained. The factors are labelled as follows. Factor 1 is highly related with bus punctuality, bus frequency, and service time; thus, it represents reliability. Factor 2 is highly related with bus route map, bus number sign, and bus stop information; thus, it represents bus travelling information. Factor 3 is highly related with seat arrangement, air-conditioning, and cleanliness; thus, it represents bus environment. Factor 4 is highly related with fare and discount; thus, it represents price factor. Finally, Factor 5 is highly related with driver attitude and travel safety; thus, it represents driving or travelling factor. Cronbach‟s alpha level for the five factors varies from 0.658 to 0.745, which are above the generally agreed lower limit of 0.6 and hence suggesting high internal consistency among the variables within each factor (Nunnally and Bernstein, 1994). The results of performing CFA on the perceived service quality scores are shown in Tables 2a and 2b respectively. All goodness of fit statistics shown in the bottom part of Table 2a suggest that the measurement model for the service quality has a good fit to the data : small ratio of chi-square value to degrees of freedom (2.03); goodness of fit index (GFI), goodness of fit index adjusted for degrees of freedom (AGFI), Bentler‟s comparative fit index (CFI), normed fit index (NFI), and non-normed fit index (NNFI) are greater than the threshold value of 0.9; and root mean square residual (RMR) and root mean square error of approximation (RMSEA) are more below the threshold value of 0.05. The measurement model for the service quality also has high validity and reliability. Firstly, standardized factor loadings and t values of the factor loadings being significantly different from zero at the 0.001 level support the convergent validity of all attributes. Further, as none of the correlation between the factors is greater than the square root of the AVE for the corresponding factors (see Table 2b), the perceived service quality scores demonstrate discriminant validity. Secondly, the composite reliability of all five factors exceeds the minimally acceptable value of 0.6. Moreover, four out of five factors have variance extracted estimate (AVE) greater than or close to the threshold value of 0.5. Only the „bus environment‟ factor has an average variance estimate below the threshold value. However, this test is conservative. Therefore, as a whole, it can be concluded that the perceived service quality scores have 5

Yeung good reliability. Five summated scales are created and used as indicators for the latent construct “perceived service quality” in the subsequent structural equation model. Structural equation model (SEM)

A structural model is fit to the perceived service quality, corporate image, overall satisfaction and loyalty data according to the model structure given in Figure 1. The path between service quality and loyalty is found to be insignificant and dropped based on Wald tests. The goodness of fit indices for the revised structural model, shown in the bottom part of Table 3, suggest a good fit to the data: small ratio of chisquare to degree of freedom (< 2), great values of GFI, AGFI, CFI, NFI, NNFI (> 0,9) and small RMR and RMSEA values (< 0.05). The estimation results in Table 3 indicate that both H1 (quality  image) and H2 (quality  satisfaction) are strongly supported, with standardized path coefficients of 0.523 and 0.386 respectively. However, H3 (quality  loyalty) is not supported based on insignificant standardized path coefficient. It can be seen below that service quality has only indirect effect on loyalty through overall satisfaction and corporate image. So it indicates that high service quality is not adequate to create loyal customers for franchised bus company. The estimation results show moderate support for H4 (image  satisfaction) with the standardized path coefficient of 0.192 whereas weak support for H5 (image  loyalty) and H6 (satisfaction  loyalty), with the corresponding standardized path coefficients of 0.105 and 0.124 respectively. To summarize, the results support five out of six hypothesis (H1 - H2, H4 – H6). Furthermore, the magnitude of the support is strong for H1 and H2, medium for H4 and weak for H5 and H6. In terms of explanatory power, the model accounts for 26.3% of the variance in overall satisfaction, 27.4% of the variance in image and 3.6% of the variance in loyalty. In other words, the model has medium explanatory power for both overall satisfaction and image but low explanatory power for loyalty. The low explanatory power for loyalty may imply that there is not much guarantee that a customer with good perceived service quality, overall satisfaction and corporate image will be loyal and repeat purchase. The management should consider other factors that affect loyalty apart from service quality, overall satisfaction and corporate image. The direct, indirect and total effects of service quality, corporate image and overall satisfaction on loyalty is given in Table 4. It is interesting to see that corporate image plays a more important role than overall satisfaction in affecting loyalty, which are consistent with the findings of researchers such as Abdullah 2000.
Concluding Remarks EFA concludes that there are five factors behind the perceived service quality scores. According to CFA, the measurement model for this five-factor structure performs well in terms of validity and reliability and hence five summated scales can be used as indicators for service quality in developing structural model. SEM supports the sequence: service quality

 corporate imageoverall satisfactionloyalty. However, it is found that service quality affects loyalty only indirectly through overall satisfaction and corporate image. So it may explain why high service quality is not adequate to lead to customer loyalty. The table of indirect, direct and total effects of service quality, overall satisfaction and image on loyalty shows that corporate image has higher total impact on loyalty, as
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Yeung compared with satisfaction. So to increase loyalty, improving the corporate image of KMB in passengers‟ mind is more important than improving satisfaction. As the explanatory power of these three constructs (service quality, overall satisfaction and image) for loyalty is very low (3.6%), it seems that efforts are still needed to increase loyalty through other means. There are several limitations in this study. The generalizability of this study is limited due to three reasons. Firstly, this study used one single item only to measure overall satisfaction, corporate image and loyalty to reduce the burden of respondents and the time for the interview. For further research, multiple-item scales are preferred so that their validity and reliability can be assessed through CFA. Also they may enhance the interpretation and prediction of overall satisfaction and loyalty. Secondly, the analysis is based on a survey data set collected in March 2004 when the market share of franchised buses such as KMB began to decrease. However, further study is necessary to examine whether the relationships among service quality, customer satisfaction, corporate image and customer loyalty change with time. Thirdly, the explanatory power for loyalty in terms of service quality, customer satisfaction and corporate image is low. Further analysis to investigate the predictors of loyalty other than service quality, overall satisfaction and corporate image is needed.
References

Abdullah M, Al-Nasser A and Husain N (2000). “Evaluating functional relationship between image, customer satisfaction and customer loyalty using general maximum entropy”, Total Quality Management, vol 11, P. S826-9. Aydin S and Ozer G (2005). “The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication market.” European Journal of Marketing, 39 (7/8), P910-925. Barich H and Kotler P (1991),”A framework for marketing image management,”, Sloan Management Review, P94-104. Bolton R N and Drew J H (1991). “A multistage model of customers‟ assessments of service quality and value.”, Journal of Consumer Research, 17 (March), P375-384. Bolton R N and Lemon K N (1999). “A dynamic model of customers‟ usage of services: usage as antecedent and consequence of satisfaction.” Journal of Marketing Research, 36 (2), 171-186.
Brady MK, Cronin JJ and Brand R (2002) Performance only measurement of service quality: A replication and extension. Journal of Business Research 55:17-31

Brunner T A, Stocklin M and Opwis K (2008). “Satisfaction, image and loyalty: new versus experienced customers.” European Journal of Marketing, 42 (9/10), p1095-1105. Cronin J J and Taylor S A (1992). “Measuring Service Quality: A Reexamination and Extension.”, Journal of Marketing, 56 (July): 55-68.
Cronin JJ, Taylor SA (1994) SERVPERF versus SERVQUAL: Reconciling performance-based and perceptions-minus-expectations measurements of service quality. Journal of Marketing 58:125-131.

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Cronin J J, Brady M K and Hult G T M (2000). “Assessing the effects of quality, value and customer satisfaction on consumer behavioral intentions in service environments.”, Journal of Retailing, 76 (2), P193-218. Hart A E, Rosenberger P (2004). “Effect of corporate image in the formation of customer loyalty: an Australian replication.”” Australian Marketing Journal, 2004, 12(3), P88-96.
Huang YC, Wu CH, Hsu JCJ (2006) Using importance –performance analysis in evaluating Taiwan medium and long distance. National Highway Passenger Transportation Service Quality 8:98-104. Ladhari R (2008). Alternative measures of service quality: a review. Managing Service Quality 18:65-86.

Lai F, Griffin M, and Babin B (2009) How Quality, Value, Image, and Satisfaction Create Loyalty at a Chinese Telecom. Journal of Business Research, Vol 62, pp. 980-986.
Lai WT, Chen CF (2011) Behavioral intentions of public transit passengers – The roles of service quality, perceived value, satisfaction and involvement. Transport Policy 18:318-325. Lin CN, Tsai LF, Wang PW, Su WJ and Shaw JC (2011) Using the expected importance and perceived satisfaction of tourists to construct indicators for improvement of resort hotel service quality. IJCSNS International Journal of Computer Science and Network Security 11:P91-94.

Loureiro S M C and Kastenholz E (2011), “Corporate reputation, satisfaction, delight and loyalty towards rural lodging units in Portugal”, International Journal of Hospitality Management, 30, P575-583. Mittal V, Kumar P and Tsiros M (1999). Attribute-level performance, satisfaction and behavioral intentions over time: a consumption-system approach. Journal of Marketing, 63(2), p88-101. Nguyen N and Leblanc G (2001). “Corporate image and corporate reputation in customers‟ retention decisions in services.” Journal of Retailing and Consumer Services, 8(4), P227-236.
Nunnally Jr JC, Bernstein IH (1994) Psychometric theory, 3/e, New York: McGraw-Hill Book Company.

Oliver R L (1997, 2010). Satisfaction: A behavioral perspective on the consumer. McGraw Hill, New York. Ostrowski P L, O‟Brien T V and Gordon G L (1993). “Service Quality and Customer Loyalty in the Commercial Airline Industry.”, Journal of Travel Research 32, P16-24.
Parasuraman A, Zeithaml VA, Berry LL (1985) A conceptual model of service quality and its implications for future research. Journal of Marketing 49:41-50. Parasuraman A, Zeithaml VA, Berry LL (1988) SERVQUAL: A Multiple Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing 64:12-40

Spreng R A, MacKenzie S B and Olshavsky R W (1996). A re-examination of the determinants of consumer satisfaction. Journal of Marketing, 60(3), p15-32.
Tam ML, Tam ML, Lam WHK (2005) Analysis of airport access mode choice: A case study in Hong Kong. Journal of Eastern Asia Society for Transportation Studies 6:708-723. Tang SB, Lo HK (2010) On the financial viability of mass transit development: the case of Hong Kong. Transportation 37:299-316. Transport Department (1995-2010) Annual Transport Digest. Government of the Hong Kong special administrative region. Transport Department (1999) Third Comprehensive transport study final report. Government of the Hong Kong special administrative region. Transport Department (2003) Travel Characteristics Survey. Government of the Hong Kong special administrative region. 8

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Zhao X, Bai CH, Hui YV (2002) An empirical assessment and application of SERVQUAL in a Mainland Chinese department store. Total Quality Management 13:241-254.

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Table 1 Five-factor structure of perceived service quality scores and Cronbach‟s Alpha (with attributes „bus route coverage‟ and „bus stop information‟ being deleted)
Service quality Attributes Clarity of bus number sign Bus route map Bus stop location Fare Discount Bus frequency Bus punctuality Bus service time Bus route coverage (NA) Travel safety Driver attitude Cleanliness Seat arrangement Air-conditioning Bus stop information (NA) Factor 1 Factor 2 0.632 0.865 0.449 Factor 3 Factor 4 Factor 5

0.777 0.649 0.652 0.902 0.407 0.799 0.551 0.520 0.780 0.495

Eigenvalue 4.11 1.44 1.27 1.11 Variance (%) 31.61 11.08 9.76 8.52 Cronbach‟s alpha 0.745 0.722 0.658 0.726 Overall MSA = 0.797, cumulative variance explained = 68.70%, communality = 6.853 Root mean square residual = 0.012, RMSP = 0.024, Cronbach‟s alpha = 0.816

1.01 7.73 0.693

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Table 2a Results of confirmatory factor analysis on perceived service quality
Loadin g 0.728 0.795 0.557 0.751 0.765 0.736 0.876 0.535 t 18.0 1 19.7 3 13.4 6 16.2 3 16.4 4 19.0 0 23.0 8 13.2 8 17.5 4 14.7 9 Reliabilit y 0.739 0.530 0.632 0.311 0.729 0.564 0.585 0.766 0.541 0.767 0.286 0.703 0.663 0.426 Variance Extracted 0.491

Bus information factor Clarity of bus number sign route map Bus Bus stop location Price factor Fare Discount Reliability factor Bus frequency Bus punctuality Bus service time Bus route coverage (NA) Driving factor Travel safety Driver attitude

0.574

0.532

0.545

0.814 0.653

Bus environment factor 0.663 Cleanliness 0.677 15.1 0.459 9 Seat arrangement 0.675 15.1 0.456 5 Air-conditioning 0.531 11.9 0.282 2 Bus stop information (NA) Fit indices: Chi-square = 130.55, df = 55, Chi-square / df =2.03 GFI = 0.969, AGFI = 0.949, CFI = 0.966, NFI = 0.943, NNFI = 0.951 RMR = 0.023, RMSEA = 0.047

0.399

Table 2b Correlation between factors for the measurement model on perceived service quality
Bus information Price Reliability Driving Bus environment Bus information 0.701 0.451 0.404 0.474 0.334 Price  0.758 0.453 0.393 0.340 Reliability   0.729 0.461 0.438 Driving    0.738 0.519 Bus environment     0.631

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Table 3 Standardized path coefficients of the Structural Model
Standardized parameter estimates 0.566 0.558 0.641 0.586 0.503 0.523 0.386 -t-value Hypothesis Conclusion

Independent variable  Dependent variable Service quality  Bus information Price Reliability Driving Bus environment Corporate image Overall satisfaction Loyalty Corporate image  Overall Satisfaction Loyalty

9.99 -10.71 10.19 9.23 9.4 6.6 -1 2 3 Supported Supported Not supported

0.192 0.105

4.26 2.47

4 5

Supported Supported

Overall satisfaction  Loyalty 0.124 2.92 Fit indices: Chi-square = 27.7, df = 18, Chi-square / df = 1.54 GFI = 0.989, AGFI = 0.978, CFI = 0.988, NFI = 0.967, NNFI = 0.981 RMR = 0.009, RMSEA = 0.029

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Supported

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Table 4. Direct, Indirect and total effects on loyalty Direct Indirect -0.105 0.124 0.115 0.024 -

Total 0.115 0.129 0.1240

Service quality Image Satisfaction

Corporate image H1 Service Quality H4 H2 H6 H5

Loyalty

Figure 1 Hypothetical Structural Model Satisfaction Overall

H3

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References: Brady MK, Cronin JJ and Brand R (2002) Performance only measurement of service quality: A replication and extension. Journal of Business Research 55:17-31 Brunner T A, Stocklin M and Opwis K (2008) Cronin JJ, Taylor SA (1994) SERVPERF versus SERVQUAL: Reconciling performance-based and perceptions-minus-expectations measurements of service quality. Journal of Marketing 58:125-131. Lai F, Griffin M, and Babin B (2009) How Quality, Value, Image, and Satisfaction Create Loyalty at a Chinese Telecom. Journal of Business Research, Vol 62, pp. 980-986. Nunnally Jr JC, Bernstein IH (1994) Psychometric theory, 3/e, New York: McGraw-Hill Book Company. Zhao X, Bai CH, Hui YV (2002) An empirical assessment and application of SERVQUAL in a Mainland Chinese department store. Total Quality Management 13:241-254.