Examining Antecedents and Consequences of Tourist Satisfaction: A Structural Modeling Approach

TSINGHUA SCIENCE AND TECHNOLOGY ISSNll1007-0214ll17/18llpp397-406 Volume 14, Number 3, June 2009

Examining Antecedents and Consequences of Tourist Satisfaction: A Structural Modeling Approach WANG Xia (ฅ ຍ)**, ZHANG Jie (჆ ࠎ), GU Chaolin (‫ڄ‬дॿ)†, ZHEN Feng (შ ‫)ע‬ School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; † School of Architecture, Tsinghua University, Beijing 100084, China Abstract: While the importance of tourist satisfaction has been recognized by academic researchers for at least four decades, adequate tourist satisfaction models have not been developed or validated. This study presents a tourist satisfaction model for a destination and explores the antecedents (tourist expectations, destination image, perceived quality, and perceived value) and the consequences (tourist complaints and tourist loyalty) of tourist satisfaction using Guilin for the case study. Structural equation modeling results support the tourist satisfaction model of tourist expectations, destination image, perceived quality, and perceived value as four key antecedents of tourist satisfaction, with tourist satisfaction having a negative effect on tourist complaints and a positive effect on tourist loyalty. Managerial implications are drawn from the study findings and suggestions are given for future work. Key words: tourist satisfaction; destination; structural equation modeling (SEM); Guilin

Introduction Tourist satisfaction is viewed as an important research topic by both practitioners and academics. From a managerial point of view, tourist satisfaction is the primary source of future revenue and is regarded as the key factor in winning market share. In academia, tourist satisfaction has been a popular topic since the early 1960s, reflected by the constant growth of literature on tourist satisfaction. Since the 1980s, consumer satisfaction research in marketing has led to efforts to examine the causes and results of tourist satisfaction[1-5]. However, most of these studies explained antecedents and consequences of tourism satisfaction from a single perspective, with no comprehensive model of tourist satisfaction yet developed. Although researchers have identified major driving factors of tourist satisfaction such as tourist Received: 2007-10-24; revised: 2008-04-22

** To whom correspondence should be addressed. E-mail: [email protected]; Tel: 86-25-83596903

expectations[6], perceived quality[7-10], perceived value[11-13], and destination image[14,15], most of these constructs were investigated separately with respect to their relationships with tourist satisfaction. The interrelationships among these constructs as well as their direct and indirect effects on tourist satisfaction have not yet been investigated. In addition, when exploring consequences of tourist satisfaction, most research has focused on the positive association between tourist satisfaction and tourist loyalty[16-18]. Few studies have addressed the relationship between tourist satisfaction and tourist complaints. Therefore, the formation process and behavior consequence of tourist satisfaction have not yet been fully examined. In addition, most tourist satisfaction studies have focused on western cultures, with few studies in Asian countries and almost none in China. Whether or not these findings apply in Asia is still an open point that has yet to be fully examined. This study presents an integrated tourist satisfaction model for one destination for simultaneously exploring

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the effects of antecedents (tourist expectations, destination image, perceived quality, and perceived value) and consequences (tourist loyalty and tourist complaints) of tourist satisfaction to explain the formation and results of tourist satisfaction. The tourist satisfaction model is evaluated using the structural equation modeling approach and Guilin, a beautiful Chinese city for a case study.

1

Theoretical Background

1.1

Tourist satisfaction model

The investigation of consumer satisfaction in marketing and tourism began in the 1960s with many studies exploring consumer satisfaction with integrated models. Early models were given by Oliver[1], Fornell et al.[4], Anderson and Sullivan[19], De Ruyter et al.[20], Lan and Tse[21] and Ping[22], with more recent ones by Hellier et al.[23], Lam et al.[24], and Um et al.[25] One of the most comprehensive studies is that of Fornell et al.[4] who investigated the causes (customer satisfaction, perceived quality, and perceived value) and effects (customer complaints and customer loyalty) of customer satisfaction in the U.S. The theoretical and empirical methods used in this study are mostly based on those of Fornell et al.[4] The present tourist satisfaction model is shown in Fig. 1. The tourist satisfaction is the center of a chain between the cause and result relationships running from the antecedent constructs of tourist satisfaction, tourist expectations, destination image, perceived quality, and perceived value, to the consequences of tourist satisfaction, tourist complaints, and tourist loyalty. There are 13 path hypotheses connecting the seven constructs with each path representing a hypothesized casual relationship with the direction of the effect

Fig. 1

Tourist satisfaction model

identified as either positive (+) or negative (). The theoretical underpinning of these constructs and hypotheses is analyzed in the following sections. 1.2

Theoretical background of constructs and hypotheses

1.2.1 Tourist expectations Expectations are related to the performance of a product or service as anticipated by the consumers[26]. The expectation-disconfirmation paradigm has often been used to analyze consumer satisfaction[1,27], with the results suggesting that consumer satisfaction/dissatisfaction is a result of a comparison between a consumer’s pre-purchase expectations and their post-purchase evaluation. However, this paradigm has been questioned by some researchers who argued that the role of expectations on satisfaction may depend on the context[23,28-31], so they used a perceived performance approach to model the antecedents of satisfaction. However, the positive relationship between expectations and satisfaction has been empirically proven in various contexts[4,6]. Bosque et al.[6] demonstrated that tourist satisfaction was positively affected by tourist expectations. As a compromise, this study uses the result of Bosque et al.[6] with the first hypothesis as H1 Tourist expectations for a destination have a positive effect on tourist satisfaction. In addition, as suggested by Fornell et al.[4], consumer expectations are associated with perceived quality and perceived value which both affect tourist satisfaction indirectly through quality-satisfaction and value-satisfaction linkages. H2 Tourist expectations for a destination have a positive effect on perceived quality. H3 Tourist expectations for a destination have a positive effect on perceived value. 1.2.2 Destination image The destination image is defined as an individual’s mental representation of the knowledge, feelings, and overall perception of a particular destination[32]. It has been widely acknowledged that destination image strongly affects tourist behavior such as destination choice, participation (i.e., perceived quality and perceived value), and evaluation (i.e., satisfaction). Based on theses perspectives, three more hypotheses are proposed. H4 Destination image has a positive effect on

WANG Xia (ฅ ຍ) et alġExamining Antecedents and Consequences of Tourist Satisfaction …

perceived quality. H5 Destination image has a positive effect on perceived value. H6 Destination image has a positive effect on tourist satisfaction. In addition, some research in the service industry literature has also catalogued image as a driving factor in the formation of consumer expectations[6,33], because image to some degree represents the true capabilities of a service provider, allowing consumers to more accurately anticipate service quality. H7 Destination image has a positive effect on tourist expectations. 1.2.3 Perceived quality Quality is considered to be the overall evaluation made by consumers regarding the excellence of a product. The topics of quality and satisfaction have probably been discussed more than any other issues of consumer behavior, with the positive relationship between the two constructs confirmed by prior studies[3,7,34]. There is also a general consensus that perceived quality exercises a positive influence on perceived value. H8 Perceived quality of a destination has a positive effect on tourist satisfaction. H9 Perceived quality of a destination has a positive effect on perceived value. 1.2.4 Perceived value The perceived value is the consumer’s overall assessment of product utility based on perceptions of what is received and what is given[35]. According to the equity theory[36], consumer satisfaction occurs when consumers receive more value than they spend; thus, perceived value can be an appropriate measure to gauge satisfaction. The positive relationship between perceived value and tourist satisfaction has also been identified in the tourism field[11,13]. H10 Perceived value of a destination has a positive effect on tourist satisfaction. 1.2.5 Tourist complaints Effective handling of consumer complaints can improve market reputation and enhance economic profitability; therefore, consumer complaint behavior is receiving increasing attention. According to Hirschman’s exit-voice theory, when consumers become dissatisfied, the immediate consequence is increased consumer complaints[37]. Although the negative relationship between satisfaction and complaints has been illustrated

399

in the marketing literature, whether it holds true in the tourism context is not clear. Therefore, this study seeks to study the relationship between complaints and satisfaction for tourists. H11 Tourist complaints for a destination are related negatively to tourist satisfaction. 1.2.6 Tourist loyalty Consumer loyalty is the consumers’ intention or actual behavior to repeatedly purchase certain products[38]. In the past two decades, various researchers have incorporated the concept of consumer loyalty into the tourism context[39-41]. Some studies have indicated that tourist loyalty is bi-dimensional, including both attitudinal commitment and behavioral revisit intention[16]. Other studies have identified tourist satisfaction as one of the major predictors of tourist loyalty[7,8]. Therefore, H12 A positive relationship exists between tourist satisfaction and tourist loyalty for a destination. In addition, as pointed out by Fornell[2], the relationship between consumer complaints and consumer loyalty is uncertain, depending on the effectiveness of the complaint handling. A positive path coefficient relating complaints and loyalty implies that the product provider is very successful in turning complaining customers into loyal customers. A negative path coefficient, on the contrary, indicates ineffective handling of consumers’ complaints. This study is based on 20 in-depth interviews with officials, experts, and managers in the tourism sector, discussing the relationship between tourist complaints and tourist loyalty. The interviews included 4 officials from the Guilin Tourism Bureau, 6 experts from Guilin universities, and 10 managers from tourism businesses (3 from hotels, 3 from travel agencies, 2 from tourist shops, and 2 from traffic companies). Ninety percent of the interviewees felt that tourist complaints have a negative relationship with tourist loyalty. Therefore, H13 A negative relationship exists between tourist complaints and tourist loyalty for a destination.

2 Methodology 2.1

Questionnaire design and operationalization of constructs

The seven constructs in the tourist satisfaction model are latent variables that cannot be observed directly. Hence, a questionnaire was designed as the survey

400

instrument. The questions were based on a comprehensive review of existing studies with specific destination peculiarities also taken into account. The questionnaire consisted of two parts. Part 1 contained seven sets of questions to measure the seven constructs with 35 questions. A five-point Likert scale was used as the response format. Part 2 recorded the respondents’ demographic information and travel behavior. (1) Operationalization of tourist expectations Fornell et al.[4] suggested that consumer expectations can be measured in three dimensions as overall expectations of quality, expectations regarding customization, and expectations regarding reliability. Therefore, the current study measured tourist expectations based on these three items. Respondents were asked to evaluate these items along a five-point scale (1= very low and 5= very high). (2) Operationalization of destination image Chen and Tsai[12] selected 20 measures of destination image grouped into four dimensions as destination brand, nature and culture, sun and sand, and entertainment. This study used their findings with all but one item (sun and sand) which is irrelevant in the case of Guilin. Respondents were asked to evaluate the image of Guilin for these three items along a five-point scale (1 = unfavorable and 5 = favorable). (3) Operationalization of perceived quality The SERVQUAL instrument proposed by Parasuraman et al.[27] has often been used to measure quality. This instrument of perceived quality, however, has been questioned by researchers[28-31] due to the need to measure not only perceptions but also expectations. Cronin and Taylor[28] and Crompton and Love[34] suggested that measuring perceived quality based on performance alone was superior to the SERVQUAL approach. Following this perspective, four items adopted from Hui et al.[42], Chen and Tsai[12], and Wang et al.[43] were used to assess perceived quality, including attractions, food and accommodation, transportation, and local environment. Respondents were asked to evaluate the four items on a five-point scale (1= very unsatisfactory and 5= very satisfactory). (4) Operationalization of perceived value According to equity theory[36] and the findings of Heskett et al.[44], perceived value can be measured in terms of price, time, and effort. These three dimensions were also employed by Bolton and Drew[45] and Chen and Tsai[12], and were proved to be reliable and valid.

Tsinghua Science and Technology, June 2009, 14(3): 397-406

Following these investigations, this paper measured perceived value by asking the respondents, “Is your visit in Guilin worth your money, time, and effort?” Responses rated their feelings from “definitely not worth it” (1) to “definitely well worth it” (5). (5) Operationalization of tourist satisfaction Consumer satisfaction is conceptualized as the consumers’ evaluation of consumption experience incorporating both affective and cognitive dimensions[46-48]. According to this viewpoint, three items were developed to measure tourism satisfaction. One item measured the affective dimension: “How satisfied were you with your visit to Guilin?” (1= not at all satisfied to 5= very satisfied). Two items measured the cognitive dimension: “How does Guilin, in general, rate compared with what you expected?” (1= much worse than expected to 5= much better than expected) and “How do you rate Guilin as a destination compared with similar places?” (1= much worse to 5 = much better). (6) Operationalization of tourist complaints Complaint behavior represents multiple responses resulting from dissatisfaction, with complaint options ranging from seeking redress to complaining to third parties[49,50]. Based on the studies of Rogers et al.[49] and Singh[51] and the characteristics of tourist behavior, this research measured tourist complaints by three items as (1) “Will you seek redress from service provider?” (2) “Will you complain to a third party?” and (3) “Will you publicize negative aspects of Guilin to your friends or relatives?” Respondents were asked to answer the three questions from “not likely at all” (1) to “very likely” (5). (7) Operationalization of tourist loyalty Revisit intentions and willingness to make recommendations have been widely used to infer tourist loyalty and have been proved to be reasonable measures of loyalty[52-54]. Thus, two questions were developed to measure tourist loyalty: (1) “How likely is it that you will visit Guilin in the future?” (1= not likely at all to 5= very likely) and (2) “Will you recommend Guilin to your friends and relatives?” (1= not likely to 5= definitely). 2.2

Sample design and data collection

The data for this study was collected in Guilin during December 2006. Guilin is one of the most popular destinations in China, receiving 13.338 million tourists (1.11 million were international) in 2006. The survey

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WANG Xia (ฅ ຍ) et alġExamining Antecedents and Consequences of Tourist Satisfaction …

was conducted at the Guilin Train Station and Airport. The target population was individuals over the age of 18 years old and who had completed their travel within Guilin. A total number of 800 questionnaires were distributed using the convenience sampling technique, with 192 unacceptable questionnaires removed. After elimination, 608 questionnaires were used for data analyses, representing a sampling error in the case of an infinite population (the size of the population is not available) of 4.06% for a confidence level of 95.5% (p= q = 0.5). Table 1

3

Results

3.1

Reliability test

Before evaluating the model, the reliability of the measurement items was tested using Cronbach’s D test to assess the internal consistency of the seven constructs in the model. Dvaried from 0.79 to 0.92 (see Table 1), exceeding the minimum threshold of 0.7[55]. Thus, the measurement items reliably gauged the constructs.

Psychometric properties of the measurement model

Constructs and indicators

Standardized Error loadings variance

Tourist expectations Overall expectations of quality

0.84

0.29

Expectations regarding customization

0.72

0.48

Expectations regarding reliability

0.73

0.47

Destination image Destination brand

0.81

0.34

Nature and culture image

0.69

0.53

Entertainment image

0.75

0.43

Perceived quality Attractions

0.92

0.15

Food and accommodation

0.81

0.34

Transportation

0.77

0.41

Local environment

0.74

0.45

Money value

0.78

0.39

Time value

0.65

0.58

Effort value

0.74

0.45

Overall satisfaction

0.82

0.33

Satisfaction compared with expectations

0.73

0.47

Satisfaction compared with other similar places

0.69

0.52

0.59

0.65

Perceived value

Tourist satisfaction

Tourist complaints Seek redress from service provider Complain to third party

0.67

0.55

Negative word-of-mouth

0.89

0.21

Visit Guilin in the future

0.57

0.68

Recommendation to friends/relatives

0.93

0.14

Tourist loyalty

3.2

Measurement model

The reliability of the measurement model was tested using the confirmatory factor analysis in LISREL 8.70.

Cronbach’s D

Composite reliability

Average variance extracted

0.92

0.81

0.59

0.87

0.80

0.56

0.89

0.89

0.66

0.83

0.77

0.53

0.84

0.79

0.56

0.82

0.77

0.53

0.79

0.73

0.59

Several common model fit indices were used as criteria to judge the measurement tenability, NCI (Ȥ2/df), GFI, AGFI, NFI, NNFI, CFI, and RMSEA. Table 2 shows the recommended values and test results for these

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indices. As indicated, all indices exceeded their common acceptance levels, demonstrating that the measurement model exhibited a good fit with the collected data. Table 2 Goodness-of-fit indices for the measurement and structural models Recommended

Measurement

Structural

value

model

model

NCI (Ȥ /df)

2.00-5.00

3.260

2.410

GFI

>0.90

0.900

0.910

Index 2

AGFI

>0.90

0.910

0.920

NFI

>0.90

0.940

0.920

NNFI

>0.90

0.940

0.940

CFI

>0.90

0.960

0.940

RMSEA

İ0.008

0.035

0.047

Next, the psychometric properties of the measurement model were evaluated in terms of the composite reliability, convergent validity, and discriminant validity. First, the composite reliability was calculated as indicated by Fornell and Larcker[56], with the results ranging from 0.73 to 0.89 exceeding the critical value of 0.7[55]. Second, the convergent validity was assessed by the average variance extracted. As indicated in Table 1, the results were all above the recommended 0.5 level, demonstrating that the convergent validity was satisfied for the measurement model. Third, the discriminant validity was examined by comparing the squared correlation between each pair of the constructs with the extracted average variance. The results showed that all the constructs met this test, with none of the squared correlations surpassing the average variance extracted. Therefore, all these tests indicated that the measurement model had adequate reliability and validity. Table 3

3.3

Structural equation model

After establishing the confidence in the measurement model, the structural equation modeling (SEM) analysis was conducted using the maximum likelihood (ML) estimation method to examine the relationships between each pair of constructs. The fit indices of the structural model indicated a good fit to the data with NCI= 2.41, GFI= 0.91, AGFI = 0.92, NFI = 0.92, NNFI = 0.94, CFI = 0.94, and RMSEA = 0.047 as shown in Table 2. An analysis of the estimated standardized path coefficients gave the direction and significance of the hypothesized relationships among the seven constructs as shown in Fig. 2 and Table 3. As indicated in Fig. 2, 12 of the 13 path coefficients were significant at p < 0.05. Hypotheses H1-H10 indicated direct and indirect paths linking antecedent constructs and tourist satisfaction. As expected, tourist expectations had a significant positive impact on both tourist satisfaction (ȕ = 0.27, t = 4.53) and perceived quality (ȕ = 0.26, t = 4.38); thus, support H1 and H2. However, the hypothesis of tourist

Fig. 2 Tourist satisfaction model test results

Direct, indirect, and total effects among the seven constructs

Path

Direct effect

Indirect effect

Total effect

Tourist expectations ĺ Tourist satisfaction

0.27

0.17

0.44

Destination image ĺ Tourist satisfaction

0.45

0.42

0.87

Perceived quality ĺ Tourist satisfaction

0.64

0.17

0.81

Perceived value ĺ Tourist satisfaction

0.46

ʊ

0.46

0.56

ʊ

0.56

Tourist satisfaction ĺ Tourist loyalty

0.71

0.21

0.50

Tourist complaints ĺ Tourist loyalty

0.37

ʊ

0.37

Tourist satisfaction ĺ Tourist complaints

WANG Xia (ฅ ຍ) et alġExamining Antecedents and Consequences of Tourist Satisfaction …

expectations having a positive effect on perceived value was not confirmed (ȕ=0.09, t = 0.16); therefore, H3 was then eliminated. H4 to H7 suggested positive relationships between destination image and perceived quality (H4, ȕ = 0.21, t = 4.14), perceived value (H5, ȕ = 0.23, t = 4.62), tourist satisfactions (H6, ȕ = 0.45, t = 6.56), and tourist expectations (H7, ȕ = 0.54, t = 6.94). Perceived quality was found to be a significant predictor in determining tourist satisfaction (ȕ = 0.64, t = 7.89) and had a positive association with perceived value (ȕ = 0.36, t = 5.61), supporting hypotheses H8 and H9. Likewise, perceived value appeared to be an important antecedent of tourist satisfaction (ȕ = 0.46, t = 6.23); thus, H10 was therefore supported. Hypotheses H11-H13 indicated the linkages between tourist satisfaction and consequence constructs. The path estimate of 0.56 (t = 7.45) for H11 demonstrated that tourist satisfaction negatively affected tourist complaints. Also, the path coefficient relating tourist satisfaction and tourist loyalty was significant (ȕ = 0.71, t = 8.48), confirming H12. Finally, tourist complaints had a significantly negative effect on tourist loyalty (ȕ = 0.37, t = 4.71), thus supporting H13.

4

Conclusions and Implications

Tourist satisfaction is a feeling generated both by cognitive and emotional aspects of tourism activities, as well as an accumulated evaluation of various components and features of the destination. Tourist satisfaction is based on many factors such as tourist expectations, destination image, perceived quality, and perceived value. It is also closely related with the tourists’ post-purchase behavior (tourist complaints and loyalty). Previous studies tended to explore the antecedent and consequence variables of tourist satisfaction from a single perspective and concentrated almost exclusively on western destinations. This research uses an integrated tourist satisfaction model with Guilin as a case study. This study has two specific theoretical contributions for the tourism industry. First, the study identifies the key drivers and results of tourist satisfaction as well as their relationships, thus representing a significant step forward in the explanations of tourist satisfaction. Second, the case study of Guilin evaluates these effects in a Chinese context. The empirical results of this study provide reliable

403

evidence that tourist expectations, destination image, perceived quality, and perceived value are four important factors influencing tourist satisfaction. First, the path coefficient between tourist expectations and tourist satisfaction was significant with the total effect of tourist expectations on tourist satisfaction, including the direct effect of expectations on satisfaction plus the indirect effect of expectations on satisfaction through perceived quality, being 0.44 (see Table 3), indicating that tourist expectations have a strong positive relationship with tourist satisfaction. This finding is consistent with that of Fornell et al.[4] Second, the destination image exercised the strongest total effect on tourist satisfaction among the four antecedent constructs. In addition to the direct positive effect on tourist satisfaction, destination image also affected tourist satisfaction through the constructs of tourist expectations, perceived quality, and perceived value. These results are very similar to the results of Bosque et al.[6] and Bigné et al.[16] Third, perceived quality and perceived value are two significant predictors of tourist satisfaction. Perceived quality was found to influence tourist satisfaction both directly and indirectly, confirming the results of Gallarza and Saura[13]. The perceived value, in addition to having a direct, positive association with tourist satisfaction, also played a crucial intervening role in the relationship between perceived quality and tourist satisfaction. This perspective is similar to studies indicating that perceived value is a mediator between perceived quality and tourist satisfaction[13,57]. The structural equation model also indicated that tourist satisfaction has a negative effect on tourist complaints and a positive effect on tourist loyalty, which provides empirical supports for the findings of Fornell et al.[4] and Hirschman[37]. Finally, the negative coefficient relating tourist complaints and tourist loyalty implies ineffective handling of tourists’ complaints. Thus, Guilin should take more measures to turn complaining tourists into loyal tourists. The major findings of this study have the following important implications for destination managers and marketers: (1) Strengthen tourist expectation management Given the positive relationship between tourist expectations and tourist satisfaction, destination marketers need to be more concerned about the management of tourist expectations. Expectations play a significant

404

role in the consumer decision-making process, with this role being even more important for tourists due to the intangibility of tourism services. Expectations are also a benchmark of tourist satisfaction. If expectations are not matched by actual performance, tourists will magnify this discrepancy and become dissatisfied. Thus, expectations can be a “double-edged sword”. Destinations should enhance expectation management, while improving their performance to meet those expectations to improve tourist satisfaction. (2) Build a favorable destination image The destination image exercises a stronger total effect on tourist satisfaction than the other three antecedents discussed in this study; thus, the image should be carefully developed by the destination managers. As indicated, the destination image can be measured by three indicators, the destination brand, nature and culture, and entertainment. Thus, the destination image can be built by improving these three aspects. (3) Implement a total quality management strategy Since the perceived quality has the most important direct effect on tourist satisfaction, destination managers should particularly focus on the control of performance quality. The tourism industry naturally has many factors which affect the evaluation of quality, and a single unpleasant incident can lead to a negative overall evaluation, depending on how important the effect is for tourists. Hence, managers must implement a total quality management strategy and should make sure that all parties have good coordination and cooperation. (4) Provide a multidimensional perceived value As a direct antecedent of tourist satisfaction, perceived value should be viewed as a strategic objective by destination managers. In addition, this paper along with prior studies[11,13,58] generally suggest that perceived value should be measured by multidimensional items including price, time, and effort. Thus, managers should analyze perceived value in a holistic manner, instead of excessive concentration on economic utility. In addition, to give tourists more value, destination managers should design products and itineraries to reduce tourists’ time and effort. (5) Handle tourist complaints effectively As a direct consequence of dissatisfaction, tourist complaints provide destinations with opportunities to improve management performance. However, poor handling of complaints will increase tourist frustration and dissatisfaction, and harm the reputation of the

Tsinghua Science and Technology, June 2009, 14(3): 397-406

destination. Considering the important benefits and costs of tourist complaints, managers should develop convenient ways for tourists to communicate their dissatisfaction and take appropriate measures to resolve tourist complaints. (6) Understand tourist loyalty Although the importance of tourist loyalty has been generally acknowledged, tourist loyalty should not be merely understood as repeat purchases of tangible products. Due to the variations of tourist motivations, availability of family finances, and limitations of travel time, tourist satisfaction with their experience at a destination does not guarantee their return. However, satisfied tourists will recommend the destination to others which can be viewed as another aspect of loyalty. In this sense, marketers should understand tourist loyalty in a holistic way combining the behavioral and affective dimensions. Three limitations in this study should be discussed to guide future research. First, this empirical study of tourist satisfaction was tested in a specific setting, Guilin. Hence, the results may not be easily generalized. Therefore, similar studies are needed for other destinations to produce a more robust tourist satisfaction model. Second, this study was conducted in the off-season in Guilin, so further studies are needed to determine if the cause-and-effect relationships in this tourist satisfaction model vary with the seasons. Future research should compare conclusions in a longitudinal study to investigate the dynamic characteristics of these relationships. Third, the use of convenience sampling is a limitation. In the future, random sampling or other techniques should be used to improve the sampling reliability. Despite these limitations, this paper presents an effective framework for investigating the causes and results of tourist satisfaction for a destination. The methodology and the findings are of value to the tourism industry and to researchers of tourist behavior. Acknowledgements The authors express their gratitude to the Guilin and the Yangshuo Tourism Bureaus for their assistance in data collection.

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