Impact of Tourists’ Perceived Value on Behavioral Intention for Mega Events-Comparison between Inbound and Domestic Tourists at Hangzhou G20 Summit

 

NA CUI

Business Department, Ningbo Polytechnic, Beilun District, Ningbo, China

HONGAN DONG

Business Department, Ningbo Polytechnic, Beilun District, Ningbo, China

YUE HE

Business Department, Ningbo Polytechnic, Beilun District, Ningbo, China

 

 

 

ABSTRACT

The purpose of the study is to exam the relationship between inbound and domestic tourists’ perceived value and behavioral intention toward the Hangzhou G20 Summit. The study also investigates similarities and differences between inbound and domestic tourists’ perceived value on behavioral intention toward the Hangzhou G20 Summit. Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) based on 1120 questionnaires data (403 inbound-tourist questionnaires, 717 domestic-tourist questionnaires) are utilized to exam the model fit and hypothesis testing.

The findings of the empirical study indicate that: (1) There is a significant relationship between tourist’s perceived value and behavioral intention. (2) Utilitarian value, enjoyment value, novelty value, service value, social value and convenience value have significant effects on inbound and domestic tourists’ behavioral intentions. (3) The cultural exploration value only significantly affects the inbound tourists’ behavioral intention while the event attraction value only significantly affects the domestic tourists’ behavioral intention. Finally, the study discussed the implications of findings, which are also conductive to the successful hosting of mega events in China, including the further development of G20 Summit tourism resources.

Key Words:  Hangzhou G20 Summit     Mega Event       Tourists’ Perceived Value      Tourists’ Behavioral Intention

 

 

1      INTRODUCTION

Event tourism is defined as “the systematic planning, development and marketing of festivals and special events as tourist attractions, catalysts, and image builders” (Getz &Wicks, 1993). Event tourism has become one of the fastest growing products in the world tourism market (Nicholson and Pearce, 2001). As Getz (2008) concludes, event tourism studies and related research are still in the early stage of development. Previous event tourism studies mainly focused on suppliers and management, and there is a lack of customer-oriented research, such as research on customer behaviour, motivation and demand (Li & Petrick, 2006).

According to Getz (2008), exiting literature on event tourism can be divided into four categories: business events; sport events; festivals and cultural celebrations; and Olympics, world’s fairs and other mega-events. Within the last category, the Olympics have tended to receive the greatest attention by researchers and a substantial amount of materials is available on the topic. There are only few studies done on tourism related mega event of G20 summit. Even though the case study of empirical component relates to the Hangzhou G20 summit, the intention is to create knowledge that can be applied to the wider classification of mega-events.

Many empirical studies examined tourists’ perceived value of mega-events and developed measuring scales (Petrick, 2002; Sánchez et al., 2006; Getz, 2008). However, no study has further investigated the mega-event tourists’ perceived value (TPV) of mega-event such as G20 summit. The existing mega-event studies focus on similarities and differences between inbound and domestic tourists’ perceived value on behavioral intention toward the Hangzhou G20 Summit. A majority of mage-events studies was conducted in developed countries (Lee et al., 2007; Cole & Chancellor, 2009) and only few studies were done in developing countries where events are now becoming important economic and social-cultural venues. Moreover, not many event studies were conducted in the Asian context.

The Hangzhou G20 Summit which aims to build an innovative, invigorated, interconnected and inclusive global economy, held on September fourth-fifth in Hangzhou, was a huge success, attracting unprecedented 2 million visitors, providing huge economic, social and cultural benefits, and having a profound impact on the host city, regional economy and tourism industry. Tourists’ behavioral intention (TBI) partially reflects the impact of mega-event tourism, especially the potential impact, and it is thus necessary to theoretically determine the relationship between TPV and TBI, such as how TBI is affected by TPV. On the other hand, the Hangzhou G20 summit comprised both temporary and permanent attractions with the latter including Hangzhou Olympic and International Expo Center. Every country has its own ideas about the further development of G20 summit tourism resources. Therefore, an in-depth study on the both inbound-tourist TPV and domestic-tourist TPV for the Hangzhou G20 summit will have great theoretical and practical significance to the sustainable development of mega events in China, including the further development of G20 summit tourism.

 

2      LITERATURE REVIEW

a.     Mega-events

Mega-event is a short-term large-scale event, which requires building infrastructure and long-term use-planning after hosting the event, but often carries long-term debts (Roche, 1994). Horne and Manzenreiter (2006) explain three reasons for mega-events expanding worldwide: (1) the development of satellite technology that creates global audience for events; (2) the formation of a sport-media-business alliance; and (3) the creation of valuable promotional opportunities for host regions. Lee and Taylor (2005) maintain that mega-events create national pride and cohesiveness, promote international business, and increase international awareness. Mega-events also improve destination image that influences visitor behavioral intentions (e.g., visiting the destination) (Lee et al., 2005). Lee et al. (2014) in their study of the Expo 2010 Shanghai China conclude that the successful mega-events develop positive attitudes toward the host country or city, generate positive word-month, and encourage revisit intentions. Other studies on mega-events emphasize the importance of mega-events in improving local infrastructure, providing foreign capital and transferring technological knowledge (Birkendorf, 2009), generating employment (Kasimati, 2003), increasing exports (Rose & Spiegel, 2011), and creating lasting economic growth in the host country (Birkendorf, 2009).

 

b.     Perceived value theories and studies

Since the mid-1990s, research on the theory of customer perceived value has gradually become a hot field in the research on tourism, and played an important role in improving the competitiveness of tourism enterprises and promoting the sustainable development of the tourism industry (Li, Cheng & Zhong, 2009). Petrick’s study (2004) found that tourist perceived value can effectively enhance the market share of a tourism enterprise and function as the predictor of tourists’ behavioral intention such as tourists’ revisit intention. Consumers’ perception and evaluation are the basis of participation and also the premise of event activities and the sustainable development event tourism (Getz, 2008). Perceived value is the consumers’ overall assessment of the utility of a product based on perceptions of what is received and what is given, and researchers often combine psychological study methods and service marketing features to measure the customers’ subjective evaluation (Zeithaml, 1988). In addition, some scholars believe that the value that a product or service provides for customers is the fusion of multiple values, rather than certain single value. Sheth (1997) puts forward the model of consumption values, which divides customer perceived value into functional value, social value, emotional value, cognitive value and situational value. While Sweeney (2001) proposed four interrelated dimensions of customers’ perceived value: utility price, quality factor, emotional value and social value. In the field of tourism research, measuring scales have been developed. For example, Petrick (2002) developed a scale for measuring the perceived value of a leisure service (SERV-PERVAL) according to the five dimensions of quality, emotional response, monetary price, behavioral price and reputation, and Sánchez et al. (2006) developed a scale for the perceived overall value of the purchase of a tourism product named GLOVAL, which has six dimensions of the functional value of the travel agency, functional value of the contact personnel of the travel agency, functional value of the tourism product, functional value price, emotional value and social value.

 

c.     Relationship between perceived value and behavioral intention

Tourist’s behavioral intention (TBI) has been viewed as an important research topic both in academia and the tourism industry. A number of researchers found that customers’ PV is positively related with word-of-mouth (WOM), recommendation behavior, and revisit intention (Oliver, 1997; Chen & Chen,2010). Chen and Chen (2010) found that the higher the value tourists perceive, the more positive IBIs they show. TBI could be viewed as tourist loyalty and brings good WOM referrals (SooCheong & Feng, 2007). Previous studies have investigated how tourists’ motivations influence their attitudes and behavioral intentions and subsequently determine their actual behaviors. In recent studies, TBI was measured by 1) positive WOM, 2) recommendations to others, 3) repurchase intention, and 4) high tolerance to a price premium (Zeithaml et al., 1996). TBI study has also focused increasingly on tourists’ previous experiences. The previous literature has confirmed the effects of tourists’ satisfaction, the quality of the tourism experience and past experiences on TBI (Chen & Chen, 2010). Previous studies have recognized that perceived value and satisfaction as the antecedents of behavioral intentions (Chen & Tsai, 2007). Research studies suggested that perceived value may be a better predictor of repurchases intentions than satisfaction (Chen & Chen, 2010). The study of Lee et al. (2007) found that perceived value is the best predictor of behavioral intentions. In the field of TPV research, there has been little study on G20 summit, and there has been little research on the effect of TPV on TBI in research on mega-event tourism. However, it is vital to scientifically measure TPV for mega events and analyse its effect on the perceived evaluation and TBI of related events because tourists’ perceived evaluation of tourism events and participative behavior will directly affect their future behavior, such as participation intention and making recommendations.

 

3       HYPOTHESES

Based on the above review, previous studies have found that perceived value (PV) is the best predictor of behavioral intention (BI) and subsequently determines their actual behavior. The present study adopts eight dimensions as the antecedents of TPV: event attraction (EA), cultural exploration (CE), enjoyment value (EV), utilitarian value (UV), novelty value (NV), public service value (PV), social value (SV) and convenience value (CV), which was developed based on previous tourism and marketing studies as well as focus groups. To get a clear understanding of the effect of TPV dimensions on TBI, it was hypothesized that TPV dimensions significantly affected TBI, and subsequently determines their actual behaviors. Therefore, the following 16 hypotheses are proposed on the basis of above literature analyses:

 

H_1:  EA is positively related to the domestic TBI.

H_2:  EA is positively related to the inbound TBI.

H_3:  CE is positively related to the domestic TBI.

H_4:  CE is positively related to the inbound TBI.

H_5:  EV is positively related to the domestic TBI.

H_6:  EV is positively related to the inbound TBI.

H_7:  UV is positively related to the domestic TBI.

H_8:  UV is positively related to the inbound TBI.

H_9:    NV is positively related to the domestic TBI.

H_10:  NV is positively related to the inbound TBI.

H_11:  PV is positively related to the domestic TBI.

H_12:  PV is positively related to the inbound TBI.

H_13:  SV is positively related to the domestic TBI.

H_14:  SV is positively related to the inbound TBI.

H_15:  CV is positively related to the domestic TBI.

H_16:  CV is positively related to the inbound TBI.

 

4     Research Methodology

 

a.     Instrument development

The TPV scale was developed based on literature reviews (Petrick, 2002; Duman & Mattila, 2005; Huang & Huang,2008; Zhang & Lu, 2010; Wang et al., 2011) as well as focus group interviews. Five focus group was conducted in Hangzhou to identify the visitors’ perceived value of Hangzhou G20 summit. Each group consisted 10 visitors and lasted for an average of 50 minutes. Some items were generated from focus group results, which were then combined with measurements from previous research.  Two pilot studies were conducted with 50 respondents, respectively, to reduce and refine the TPV items with factor analysis and reliability tests. The TBI was measured by modifying scales developed by Baker and Crompton (2000), Bigne (2001), Silva and Alwi (2006) and Sudhahar, Israel, Britto, and Selvam (2006). All items were optimized by tourism experts who had attended the Hangzhou G20 summit. A formal questionnaire was written based on pilot study and reliability test.

A questionnaire was designed as the survey instrument including all constructs of the proposed model to investigate the hypotheses of interest. The questionnaires were provided in two different languages: Chinese and English. The questionnaire was initially written in English, and then translated into Chinese by bilingual event researchers. The questionnaire was divided into three parts: (1) tourist demographic and behavior characteristics; (2) TPV dimensions, items included were event attraction (EA), cultural exploration (CE), enjoyment value (EV), utilitarian value (UV), novelty value (NV), public service value (PV), social value (SV) and convenience value (CV); (3) TBI dimensions; Questions with a five-point Likert scale ranging from ‘very unimportant’ to ‘very important’ were used to measure TPV dimensions and TBI.

 

b.     Data Collection

Surveys were not allowed to be conducted at the Hangzhou Olympic Sports Expo Center site for security reasons. To improve the scientificity and reference value of the survey, Self-administered survey was conducted at eleven major survey sites, namely Hangzhou Xiaoshan International Airport and Ten Scenes of West Lake between 3^rd and 6^th of Sep, 2016.  Population was defined as all visitors to the Hangzhou G20 summit and random sampling was used, ensuring that all four days and all part of programs (day and night) were evenly covered.

The study was conducted at the Xiaoshan International Airport, only departing tourists were surveyed as they would be in a better position to express their views based on their experiences with several aspects of the Hangzhou G20 summit. During day, tourists were approached at the Ten Scenes of West Lake and asked to participate in the survey. The tourists were approached and briefly explained the purpose of the research, and subsequently they identified themselves as visitors to the Hangzhou G20 summit, and agreed to participate in the survey, were asked to complete the questionnaire. The evening program of G20 concert titled “Hangzhou, A living Poem” consisted of a symphony concert and gala on water starting at 9:15 and, thus, a different approach to data collection was used. In order not to disturb visitors during the main event, the questionnaire was randomly handed out at the entrance and completed questionnaires were collected during the break or after the main event at the exits.

All respondents had visited the Hangzhou G20 summit. A total of 1284 questionnaires were distributed (449 inbound-tourist questionnaires and 835 domestic-tourist questionnaires) and 1127 questionnaires were collected back. Seven questionnaires were incomplete and removed from the study. As a result, 1120 questionnaires (403 inbound-tourist questionnaire, 717 domestic-tourist questionnaire) were used in final analyses with giving a response rate of 87.2%.

 

c.     Methods

Statistical product and service solutions (SPSS) 23.0 and analysis of moment structure (AMOS )23.0 were used to analyse the data. The analytical method included reliability analysis, validity analysis, confirmatory factor analysis (CFA), and the path analysis. Measurement Model assessments and reliability test are achieved by using factor analysis for testing reliability and validity. SEM is adopted for structural model assessment; it provides an overall test of model fit and individual parameter estimate tests simultaneously.

  

5      EMPIRICAL RESULTS

 

a.     Respondents’ profile

The respondents’ profiles are presents in Table 1. There were almost an equal number of males and females in the two sample groups. Both domestic and inbound tourists were represented by young visitors from age group of 20-29 and 30-39, accounting for 51.5% and 48.8% respectively. In terms of the occupation, the following three types hold a relatively higher proportion, namely, white collars, students and government/state employees. As for the educational level, the biggest group among the domestic tourists, accounting for 36.7%, is the one who have achieved their bachelor degree, while most inbound tourists had bachelor degree (42.4%) or master degree (27.5%). Most tourists stated that they would like to participate in tourism groups or travel with relatives, friends and families. In respect of the monthly income, the income level of the inbound tourists was higher than that of the domestic tourists. Meanwhile, the domestic tourists came from all over the mainland of China, while the inbound tourists came from 46 countries, and most were Europeans and Americans.

 

Table 1 Respondents’ Characteristics (N=1120)

Variables		Characteristics		DT	IT
				Percent N=717	Percent N=403
Gender		Male		52.2	52.3
		Female		47.8	47.7
Age(years)	Younger than 20			21.1	13.5
		20-29		27.7	21.8
		30-39		23.8	27.0
		40-49		18.7	21.0
		50 and older		8.7	16.7
Occupation		White collars		29.1	27.2
		Students		20.3	19.1
		Professionals		11.6	12.8
		Self-employed		7.2	8.1
		Government/state employees		13.7	13.8
		Sales/services		5.6	6.1
		Wholesales		2.1	3.0
		Housewives		1.6	2.1
		Others		8.8	7.8
Education		Middle/high school or below		33.5	13.4
		College		22.4	16.7
		Bachelor		36.7	42.4
		Postgraduate and above		7.4	27.5
Travel pattern		Attend tourism group		39.3	45.2
		With relatives/friends		16.2	19.5
		Family Trip		18.6	13.2
		Personal travel		17.7	15.6
		Others		8.2	6.5
Monthly income			Below 2000	37.1	28.0
		2000-5000		49.3	34.6
		5000-10000		10.1	18.3
		Above 10000		3.5	19.1

Note: DT (domestic tourist); IT (inbound tourists); the unit of IT monthly income is USD;

The unit of DT monthly income is yuan (RMB).

 

b.     Validity and reliability analyses of the sample

At first, suitability test of the application of factor analysis to the scale is conducted, as shown in Table 2. KMO value of the sample is 0.897 (>0.5) and the significance probability under Bartlett’s test of sphericity is 0.000 (<0.05). the above two values represent that the data are suitable for factor analysis.

 

 

Table 2 KMO and the Results of Bartlett’s Test of Sphericity

Testing item			Testing results
KMO sample measure			.897
Bartlett's test of sphericity		Approximate chi-square value	29487.781
		Degree of freedom	810
		Significance level	0.000

 

 

 

 

 

 

 

factor analysis was performed on the data prior to further analysis (Lee et al., 2008). In factor analysis, the common factor is extracted by using the method of principal component extraction and then the method of varimax orthogonal rotation is adopted to rotate the common factor extracted from the questionnaire, and the factor loading matrix after rotation is obtained eventually (Swarbrooke & Horner, 2007). From the results of the analysis shown in Table 3. There are 9 factors which are available to be extracted from these 43 items. The 9 common factors extracted by using the method of principal component extraction during factor analysis are named respectively EA, CE, EV, UV, NV, PV, SV, CV and TBI. As can be seen from the results of factor analysis, the factor loading of these 9 factors both for IT and DI are all greater than 0.5, and the accumulated variance contribution rate is 81.7% for IT and 79.1% for DI respectively.

 

Table 3 Rotating Component Matrix

Note: DT (domestic tourist); IT (inbound tourists).

 

c.     Confirmatory factor analysis

A confirmatory factor analysis (CFA) is first used to confirm the factor loadings of the nine constructs and to access the model fit. The model adequacy was assessed by the fit indices suggested by Hair, Anderson, Tatham and Black (1998). Convergent validity of CFA results should be supported by item reliability, construct reliability, and average variances extracted (Chan & Baum, 2007). As shown in Table 4, Cronbach’s α coefficient ranged between 0.789 and 0.942 for both IT and DT, and the composite reliability range between 0.794 and 0.931 for both IT and DT. Both models’ data reliability and composite reliability were good with value exceeding 0.70. The average extracted variances of all constructs range between 0.582 and 0.861 for both IT and DT, which are above the suggested value of 0.5. These indicate that the two measurement models have good convergent validity. Therefore, the two hypothesized measurement models are reliable and meaning to test the structural relationships among the constructs.

 

Table 4 Test of Reliability and Validity

                          Note: F1-F8, tourists’ perceived value dimensions.

 

d.     Path analysis and hypothesis test

Structural equation modelling using AMOS23.0 was used to test the hypothesized model. This study examined the structural model with one exogenous construct (IBI) and eight endogenous constructs (EA, CE, EV, UV, NV, PV, SV and CV). The fitting indices, the estimates of path coefficients and the p-value test were examined for the two models. Because the two sample sizes were large, the chi-square test was abandoned (Wu, 2009). Table 5 summarized the fit indices of the domestic-tourist and inbound-tourist structural models, and showed the main results of the estimate of the two proposed models. It suggests that both domestic-tourist and inbound-tourist hypothesized models fit the empirical data well.

 

Table 5 Overall Goodness of Fit Model

Note: DT (domestic tourist); IT (inbound tourists).

 

Table 6 summarized all the standardized path coefficients estimated in the domestic-tourist and inbound-tourist models. In the domestic-tourist model, the results shown in figure 1 indicated that the standardized path coefficients from EA (H₁: β = .467, p < .001), EV (H₅: β = .369, p < .001), UV (H₇: β = .373, p < .001), NV (H₉: β = .398, p < .001), PV (H₁₁: β = .354, p < .001), SV (H₁₃: β = .276, p < .001), and CV (H₁₅: β = .302, p < .001) to TBI were positive and significant, thus supporting the hypotheses H₁, H₅, H₇, H₉, H₁₁, H₁₃ and H₁₅. However, CE (H₃: β = .098, p > .05) does not have a direct effect on TBI, the hypothesis H₃ was rejected. On the contrary, in the inbound-tourist model, the results showed in figure 1 estimated that the standardized path coefficients from CE (H₄: β = .479, p < .001), EV (H₆: β = .382, p < .001), UV (H₈: β = .421, p < .001), NV (H₁₀: β = .298, p < .001), PV (H₁₂: β = .343, p < .001), SV (H₁₄: β = .254, p < .001), and CV (H₁₆: β = .312, p < .001) to TBI were positive and significant, thus supporting the hypotheses H₄, H₆, H₈, H₁₀, H₁₂, H₁₄ and H₁₆. However, EA (H₂: β = .102, p > .05) does not have a direct effect on TBI, the hypothesis H₂ was rejected.

 

Table 6 Path Coefficients of the Hypothesis Model

Note: F1-F8, TPV dimensions; D, latent variables of TBI; C.R., critical ratio; ***represent p-value<0.001

 

 

 

Note: F1-F8, TPV dimensions; D, latent variables of TBI; left figure: domestic tourist sample; right figure: inbound tourist sample; ***represent p-value<0.001; *represent p-value>0.05

                                                               Figure 1: Structural model

 

The above results show that IBI was significantly affected by TPV at the Hangzhou G20 summit. Specifically, EV, UV, NV, PV, SV and CV were common factors that positively influenced TBI for both domestic-tourist and inbound-tourist samples. The effect of EA (.467) was greatest among all the eight influencing variables in domestic-tourist model, followed by NV (.398) UV (.373), EV (.369) and PV (.354). While CE (.479) has the largest direct effect on TBI in inbound-tourist model, followed by UV (.421), EV (.382), PV (.343) and CV (.312). EA only had a significant influence on domestic TBI, while CE only had a significant influence on inbound TBI. This reflected the differences in travel motivations and behavioral decision making in different marketing segments. The main reason of inbound tourists visiting the Hangzhou G20 summit was unique cultural and life experience. By contrast, the purposes of domestic tourists were seeking knowledge, novelty and enjoyment.

The SEM analysis showed that UV had the stronger influence on TBI at the Hangzhou G20 summit for both domestic and inbound tourists. Thus, UV had was regarded as another primary factor affecting IBT for two samples. Path analysis indicated that the coefficients of the measurement indicators corresponding to UV were relatively higher than others, demonstrating that mega-event tourists paid more attention to spiritual benefits (e.g. seeking knowledge, experience, and information). These desires are major difference between mega-event tourists and other tourists, such as recreational tourists and cultural tourists. Additionally, EV and PV were also important factors that affected IBT for both domestic and inbound tourists.

6      DISCUSSION AND IMPLICATIONS

Destination managers at Hangzhou, understand the benefits of event tourism and, thus, the importance of studying tourists’ perceived value on behavioral intentions This study reveals that tourist perceived value plays an important role in tourist behavioral intention. Therefore, the destination managers at Hangzhou need to consider how value, and of course the related constructs, affect behavioral intentions. This study also identifies the differences between domestic-tourists and inbound-tourists’ samples and analyzed the reasons for the differences, aiming to help destination adopting corresponding marketing strategies in accordance with different segment markets, attract tourists to revisit and achieve word-of-mouth marketing for destination and to provide a reference for further studies of the field of tourist perceived value as well.

On the whole, there are several suggestions of this study that are put forward for the sustainable development of Hangzhou G20 summit tourism.

Firstly, attractiveness of Hangzhou cultural heritage should be designed and highlighted according to tourists’ perceived value. To start with, the function of historical and cultural knowledge of Hangzhou cultural heritage should be address. Sufficient publicity of the connotation, history and culture of heritage by setting cultural heritage itself as a medium to impart knowledge can trigger tourists’ thoughts and reflections through their knowledge about and contact with the “things”, thus further stimulating their desire for knowledge and then seeking for an in-deep understanding of heritage tourism attractions. Then, enough attention should be paid to the experiential factors of cultural and heritage tourism. Many means, such as sound, light and shadow, images, texts and others can be used to create a different cultural heritage tourism experience for tourists coming to visit in Hangzhou (Wang & Leou,2015). Finally, supporting services of Hangzhou world heritage sites should be perfected, such as adding guidelines to scenic spots, free guides, etc. these services can make it convenient for tourists to visit and know about the cultural heritage.

Secondly, Hangzhou unique and artistic lifestyle should be highlighted from various kinds of aspects such as scenic spot planning, route design, product development and so on during the sustainable of development of Hangzhou G20 summit, allowing tourists to experience the differences of Hangzhou from other places. In the process of such kind of experience, tourists can gain aesthetic pleasure during their sightseeing, experience the colorful life by contacting with others, realize and improve oneself through active limitation of other roles in their life. Hangzhou lifestyle tourism development strategy can be based on topic tourism such as taste of Hangzhou, silk road tour, Hangzhou tea culture tour, Hangzhou traditional art tour, intangible cultural heritage tour and so on.

Thirdly, tourism resource integration for creating competitive and attractive products. Visitors can enjoy idyllic leisure and endless explorations through region-based tourism integration. Such as for a cultural experience, visitors can take the route starting from China Silk Museum and continue to Hangzhou Cuisine Museum and China Academy of Art before an evening of shopping and enjoying local delicacies on Hefang Street which has been restored to its former Song Dynasty-era glory; visitors can also go on a tour featuring the Xixi Culture Creative Industry Park, Xixi Wetland, Alibaba and Hikvision. In addition, the village (wuyuan, xidi, hongcun) and other core resources to integrate the city (Shanghai), lake (Hangzhou), water (Thousand Island Lake) and mountains (Huangshan), which can become the world’ golden tourist line shining pearl by five regional tourism integration.

Fourthly, improve the structure of tourism business, specific products and services for different kinds of groups. It is feasible to attract inbound tourists especially from western countries by increasing visibility and awareness of Hangzhou in the international arena, diversified products and developing international tourism agencies and operators. We should rely on Hangzhou’s unique and unique DNA, charming landscape, deep history and culture, living people living to attract the inbound tourists. While for domestic tourists, we should more focus on leisure and organic products. Education programs, international interpretation identification system, diversified payment, safety environment and tourism transportation service system are considered to improve quality of public service related to tourism. At last, ecological protection, infrastructure construction and internationalization are also important for Hangzhou tourism.

 

 

REFERENCES

Baker, D. A. & Crompton, J.L. (2000), ‘Quality, satisfaction, and behavioural intentions’, Annals of Tourism Research, 27(3):785-804.

Birkendorf, T. (2009), ‘The economic growth effects of the 2008 Olympic Games in Beijing’, IEE Working paper, Institute of Development Research and Development Policy, January 2.

Bigne J.E. Sánchez, M.I. & Sánchez, J. (2001), ‘Tourism image, evaluation variables and after purchase behavior: Inter-relationship’, Tourism Management, 22(6):607-616.

Chan, J.K.L.& Baum, T. (2007), ‘Ecotourists’ perception of ecotourism experience in lower Kinabatangan, Sabah, Malaysia’, Journal of Sustainable Tourism, 15(5):574-590.

Chen, C.F.& Tsai, D. (2007), ‘How destination image and evaluative factors affect behavioural intentions?’, Tourism Management, 28(1):1115-1122.

Chen, C.F.& Chen, F.S. (2010), ‘Experience quality, perceived value, satisfaction and behavioural intentions for heritage tourists’, Tourism Management, 31(1):29-35.

Cole, S.T. & Chancellor, H.C. (2009), ‘Examining the festival attributes that impact visitor experience, satisfaction and re-visit intention’, Journal of Vacation Marketing, 15(4):323-333.

Duman, T. & Mattila, A.S. (2005), ‘The role of affective factors on perceived cruise vacation value’, Tourism Management, 26(2):311-323.

Getz, D. (2008), ‘Event Tourism: Definition, Evolution and Research’, Tourism Management.

Hair, J.F. Anderson, R.E. Tatham, R.L. & Black, W.C. (1998), Multivariate data analysis, (5^th edition), NJ: Prentice Hall.

Horne, J.D.& Manzenreiter, W. (2006), ‘An introduction to the sociology of sports mega-events’, The Sociological Review, 54(2):1-24.

Huang, Y.L.& Huang, Z.F. (2008), ‘A study on the Structural Equation Model and its application to tourist perception for agri-tourism destinations: Talking southwest minority areas as an example’, Geographical Research, 27(6):1455-1465.

Kasimati, E. (2003), ‘Economic aspects and the Summer Olympics: A review of related research’, International Journal of Tourism Research, 5(6);433-444.

Li, X. & Petrick, J.F. (2006), ‘A review of festival and event motivation studies’, Event Management, 9(4):239-245.

Lee, C.K. Lee, Y.K. &Lee, B.K. (2005), ‘Korea’s destination image formed by the 2002 World Cup’, Annals of Tourism Research, 32(4):839-858.

Lee, C.K &Taylor, T. (2005), ‘Critical reflections on the economic impact assessment of a mega-event: The case of 2002 FIFA World Cup’, Tourism Management, 26(4):595-603.

Lee, S.Y. Petrick, J.F.& Crompton, J. (2007), ‘The roles of quality and intermediary constructs in determining festival attendees’ behavioural intention’, Journal of Travel Research, 45(4):402-412.

Lee, C.T. Yang, S.C.& Lo, H.Y. (2008), ‘Customer satisfaction and customer characteristic in festival activity: A case of 2006 Kenting Wind Chime Festival’, International Journal of Culture, Tourism and Hospitality Research, 2(3):234-249.

Nicholson, R.E.& Pearce, D.G. (2001), ‘Why do people attend events: A comparative analysis of visitor motivations at Four South Island events’, Journal of Travel Research, 39(4), pp.41-48.

Oliver, R.L. (1997), Satisfaction: A behavioural perspective on the consumer (5^th edition), New York, NY: McGraw-Hill.

Petrick, J. F. (2002), ‘Development of a multi-dimensional scale for measuring the perceived value of a service’, Journal of Leisure Research, 34(20):119-134.

Petrick, J. F. (2004), The roles of quality, value, and satisfaction in predicting cruise passengers’ behavioural intentions, Journal of Travel Research, (42):397-407.

Roche, M. (1994), ‘Mega-events and urban policy’, Annals of Tourism Research, 21(1): 1–19.

Rose, A.K. & Spiegel, M.M. (2011), ‘The Olympic effect’, The Economic Journal, 121(553):652-677.

Sheth, J. N. (1997), ‘Why we buy what we buy: a theory of consumption values’, Journal of Business Research, 22(2):159-170.

Sweeney, J.C. (2001), ‘Consumer perceived value: the development of a multiple item scale’, Journal of Retailing, 77(2):203-220.

Sánchez, J. Callarisa, L. Rodriguez, R.M et al. (2006), ‘Perceived value of the purchase of a tourism products’, Tourism Management, 27(3):394-409.

Silva, R.V.D.& Alwi, S.F.S. (2006) ‘Cognitive, affective, attributes and conative, behavioural responses in retail corporate branding’, Journal of Product & Brand Management, 6(15):293-305.

SooCheong, J. & Feng, R.M. (2007), ‘Temporal destination revisit intention: The effects of novelty seeking and satisfaction’, Tourism Management, 28(2):580-590.

Sudhahar, J.C., Israel, D., Britto, A.P.& Selvam, M. (2006), ‘Service loyalty measurement scale: A reliability assessment’, American Journal of Applied Sciences, 4(3):1814-1818.

Swarbrooke, J.& Horner, S. (2007), Consumer behavior in tourism (1^st edition), London, England: Routledge.

Wang, C.H, Lu, L. Xia, Q.Y. (2011), ‘Tourists’ perception value and behavior intention in mega-events based on structural equation model: A case study of domestic tourists in 2010 Shanghai World Expo’, Geographical Research, 30(4):735-746.

Wang, Xin. & Leou, C.H. (2015), ‘A study of tourism motivation, perceived value and destination loyalty for cultural and heritage tourists’, International Journal of Marketing Studies, 7(6):83-91.

Wu, Minglong. (2009) ‘Structural Equation Modelling-Operation and Usage of AMOS’, Chongqing: Chongqing University Press.

Zhang, H.M.& Lu, L. (2010), ‘Impact of tourist involvement on destination image: Comparison between inbound and domestic tourists’, Acta Geographical Sinica, 65(12):1613-1623.

Zeithaml, V. (1988), ‘Consumer perception of price quality and value: a means-end model and synthesis of evidence’, Journal of Marketing, 52(3):58-63.

Zeithaml, V.A. Berry, L.L. & Parasuraman, A. (1996), ‘The behavioural consequences of service quality’, Journal of Marketing, 60(2):31-46.