How Smart Is Your Tourist Attraction?: Measuring Tourist Preferences of Smart Tourism Attractions Via a FCEM-AHP and IPA Approach

Tourism Management 54 (2016) 309e320

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Tourism Management

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How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach

* Xia Wang a, , Xiang (Robert) Li b, Feng Zhen c, JinHe Zhang a a School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China b School of Tourism and Hospitality Management, Temple University, Philadelphia, PA 19122, USA c Department of Urban Planning and Design, Nanjing University, Nanjing 210093, China highlights

The paper examines tourists' key evaluation factors of a smart tourist attraction. We used the FCEM-AHP approach to evaluate tourist preferences of smart tourism attractions. Our ﬁndings shed light on the theoretical investigation and practical development of smart tourist attractions. article info abstract

Article history: Although smart tourism has gained increasing attention, empirical investigations of smart tourist Received 29 January 2015 attraction (STA) from a tourist perspective are still limited. The purpose of this study is to explore a Received in revised form methodological approach of assessing tourist preference of STA, and the strengths and weaknesses of an 2 December 2015 STA accordingly. First, factor analysis was used to determine tourists' key evaluation items of STA. Next, Accepted 3 December 2015 fuzzy comprehensive evaluation method and analytic hierarchy process were applied to the STA eval- Available online xxx uation of Hongshan Zoo, a popular tourist attraction in China. Then, importance-performance analysis was conducted to diagnose the strengths and weaknesses of Hongshan Zoo's STA construction. Findings Keywords: “ ” “ ” “ ” “ Smart tourism suggest that smart information system , intelligent tourism management , smart sightseeing , e- ” “ ” “ ﬁ ” “ ” “ Tourist commerce system , smart safety , intelligent traf c , smart forecasting and virtual tourist attrac- Tourist attraction tions” are tourists' key evaluation factors of STA. This paper extends previous research on smart tourism, Fuzzy comprehensive evaluation method and offers insights into the theoretical investigation and practical development of STA. (FCEM) © 2015 Elsevier Ltd. All rights reserved. Analytic hierarchy process (AHP) Importance-performance analysis (IPA)

1. Introduction applications of smart techniques in tourism have led to fundamental changes in tourist behavior and demand as well as how The rapid development of information and communication tourism industry functions and structures (Buhalis & Law, 2008; technology (ICT) has made the term “smart” quite fashionable Connell & Reynolds, 1999). In the foreseeable future, it seems recently (Caragliu, Del Bo, & Nijkamp, 2011). To date, smart sys- tourism will continue growing and changing significantly tems have been introduced to many areas, including public safety, with smart devices and technologies applied more widely health services, public education, infrastructure construction, and frequently in various tourism sectors (Koo, Joun, Han, & energy-saving, water supply, and environmental protection, aim- Chung, 2013). ing for economic growth, sustainable development, and societal With the increasing influence of smart technologies on the progress (Hall, 2000). Tourism has always been at the forefront tourism industry, more research has been conducted on smart in embracing technological innovations (Gretzel, 2011): the tourism. However, most studies on smart tourism focus on destinations, hotels, restaurants, entertainment, and traffic. In contrast, much less attention has been paid to tourist attractions. What's

* Corresponding author. more, many smart tourism studies stressed the deployment of E-mail addresses: [email protected] (X. Wang), [email protected] complex technological platforms, whereas in-depth research on (X. Li), [email protected] (F. Zhen), [email protected] (J. Zhang). http://dx.doi.org/10.1016/j.tourman.2015.12.003 0261-5177/© 2015 Elsevier Ltd. All rights reserved. 310 X. Wang et al. / Tourism Management 54 (2016) 309e320 smart tourism from a tourist's perspective is fairly limited. Huang, requirements for a mobile tourism application of augmented reality Yuan, and Shi (2012) emphasized that the real sense of smart (Han, Jung, & Gibson, 2013); (7) smart recommendations for tourists, tourism is to focus on tourists' needs by combining the ICT. Koo which investigates personalized destination recommendation et al. (2013) also suggested that the goal of utilizing smart sys- system combining individual preference and GIS data (Martin, tems in tourism is to maximize tourist satisfaction as well as Henk, Jappe, & Marjolijn, 2009), and a smart web-based recom- improve the effectiveness of resource management. Considering mendation system for tourist agenda (Goy & Magro, 2004); and (8) the importance of smart tourism research from a tourist perspec- smart guides, which describes context-based information imple- tive, more research to understand tourist preference of the mentation in smart tourist guide (Park, Hwang, Kim, & Chang, “smartness” of a service provider is warranted. 2007; Smirnov, Kashevnik, Balandin, & Laizane, 2013). This study aims at investigating tourists' preferences of smart The emerging literature of smart tourism-related research has tourism quantitatively in a tourist attraction context. It is hoped mainly addressed topics in the context of destinations and hotels. that this research can shed light on the theoretical investigation of Few studies have been conducted in the setting of tourist attrac- smart tourism on the whole, as well as give useful directions for the tions. Nevertheless, the exploration of the application of smart- diagnosis of strengths and weaknesses of smart tourist attraction phone, smart card, smart recommendations, and smart guides (STA) construction. The rest of the paper is organized as follows: provide useful insights for the understanding of STA, especially for Section 2 reviews the literature related to STA and discusses STA the investigation of tourists' key evaluation factors of STA. evaluation approaches; Section 3 describes the identification of tourist evaluation factors of STA, the study-area selection, data 2.2. “New” tourists in the smart era collection, as well as details about the analytical procedure; Section 4 determines STA evaluation factors using factor analysis. Then the Part of the reason for tourism service providers to develop smart authors conduct the STA assessment of China's Hongshan Zoo using tourism is to improve tourist experiences. Thus, it is critical to fuzzy comprehensive evaluation method (FCEM) and analytic hi- understand “new” tourists and their needs in the smart era for a erarchy process (AHP), and perform importance-performance better understanding of tourists' preferences for STA. Buhalis and analysis (IPA) to diagnose the strengths and weakness of STA in Law (2008) noticed that the development of ICT and particularly Hongshan Zoo; the last section mainly discusses the theoretical and the Internet has produced a “new” breed of tourists who are managerial implications of the findings. becoming more experienced, sophisticated, demanding, and harder to please. They also summarized key tourist demands in the in- 2. Literature review formation era, based on a comprehensive review of published articles on e-tourism, including: (1) pursuing personal travelling 2.1. Smart tourism preferences and schedules; (2) value for time and less willingness to wait or put up with delays; (3) searching for travel-related in- The concept of smart tourism is new both theoretically and formation through the Internet; (4) booking online tickets and practically, emerging from the development of smart cities (Buhalis making room reservations; (5) making online purchases; (6) con- & Amaranggana, 2013). It is defined as an ICT-integrated tourism ducting price comparisons on different travel websites; (7) platform, which integrates tourism sources and ICT, such as artifi- communicating in the virtual travel communities; (8) offering an e- cial intelligence, cloud computing and internet of things (IoT), to complaint handling systems; (9) asking for multimedia service; provide explicit information and satisfactory services to tourists (10) providing mobile facilities and applications such as Wifi, short- based on the development of innovative mobile communication messaging service and multimedia-messaging service. Sevrani and technology (Zhang, Li, & Liu, 2012). Elmazi (2008) also identified several new trends in tourist behavior Up to now, smart tourism-related research has been conducted spurred by ICT development, such as accessing more information in a number of areas, such as: (1) smart tourism and smart city, through the Internet, asking for better service, wanting more spe- which describes the application of the “smart city” concept and cific offers, becoming more knowledgeable, mobile, critical, and technologies into a tourism context (Lamsfus, Martín, Alzua- price sensitive, etc. Sorzabal, & Torres-Manzanera, 2015; Micera, Presenza, Splen- In summary, “new” tourists in the smart era have shown some diani, & Del Chiappa, 2013; Ronay & Egger, 2013; ); (2) smart distinctive needs and behavior patterns from their counterparts in tourism destinations, which analyzes the definition (Zhang et al., the pre-Internet/social media age. They have become more 2012), initiative (Wang, Li, & Li, 2013), conceptualizing framework dependent on information technology, self-service, and personal (Buhalis & Amaranggana, 2013; Zhang et al., 2012), critical tech- reservation tools. They value easier access to information technol- nology (Zhang et al., 2012) and smartness dimensions (Boes, ogy, better value for their money and time, and greater variety, Buhalis, & Inversini, 2015) of smart tourism destinations; (3) flexibility, personalization, and safety. Such changes in tourists' smartphone applications on tourism, which focus on the function- needs and behaviors have also brought challenges to the tourism alities and adoption of smartphone apps (Dickinson et al., 2014; Liu industry and called for the development of “smarter” tourist & Law, 2013), the role of smartphones in mediating the touristic attractions. experience (Wang, Park, & Fesenmaier, 2012), and the key determinants influencing travelers' intentions to adopt smartphone 2.3. From traditional attraction to “smarter” attraction technology to access travel information (No & Kim, 2014); (4) smart hotels, which examines the utilization of information technology in In addition to the demands from “new” tourists in the smart era, the hotel sector (Siguaw, Enz, & Namasivayam, 2000), and the other factors such as environment impacts and technology devel- digital marketing resolutions of smart hotels (Starkov & Safer, opment also made it necessary to bring smartness into traditional 2013); (5)smart cards, which investigates the utilization of smart tourist attractions. cards in the tourism industry (Fleck, 1998; Main & O'Connor, 1998) The notion of “smart tourism” reflects the tourism industry's and meeting industry (Marie, Kasavana, & Knutson, 2000); (6) response to a broader vision of making the world “smarter” e a gamification, augmented reality and smart tourism, which describes global initiative to create more “instrumented, interconnected, and the determinants of recommendations to use augmented reality intelligent systems” through information technology to address technologies (Jung, Chung, & Leue, 2015), and tourists' some of the world's pressing issues and achieve socio-economic X. Wang et al. / Tourism Management 54 (2016) 309e320 311 growth (Wikipedia, 2015). In the tourism arena, many governments application of ICT in the tourism destination. Underlying this and NGOs around the world have been committed to promoting initiative are “the transformation of tourist experience (co-created smart tourism in the form of policies and regulations. Tourist at- value), the changes of destination-marketing strategy (relationship tractions are encouraged, even required, to integrate smart tech- management), and a different view of destination competitiveness nology into their development. From a sustainable development (operant resources, big data)” (Wang et al. 2013, p. 60), which perspective, tourist attractions need to adopt smart techniques and dovetail with the key thrusts of SDL. Compared to conventional become technologically competent, eco-efficient, and environ- tourist attractions, STAs feature co-creation processes, well- mentally innovative in their operations with reference to sustain- connected and well-informed services, diverse and personalized able development. Further, globalization has generated increased products, better value for money and time, social and technological demand for new tourism-related services, such as online reserva- engagement, efficient communication and management, as well as tion services, virtual travel communities, video brochures, smart multiple smart-tourism devices e many of these features are pre- cards, online payment, and so on. In responding to these challenges, cisely what SDL entails. Enlightened by this line of work, SDL can be constructing STAs has been put on investors' and managers' used to understand the context, necessity, and future directions of agendas. STA. As far as technology development is concerned, Zhang et al. Against the above conceptualization, how could traditional (2012) suggested that four forms of ICT are vital for setting up tourist attractions be transformed into STAs? Dang, Zhang, and smart-tourism systems: cloud computing, IoT, mobile communi- Chen (2011) discussed the essential concepts of STA according to cation, and artificial intelligence technology. First, cloud computing the characteristics of tourism-resources conservation, business is a web-based virtualization resource platform and a dynamic data management, tourism development, public service, and decision center (Chen & Deng, 2009). It stimulates information sharing that support. Li, Gao, and Zhao (2011) suggested STA should contain is fundamental to undertaking smart-tourism projects (Buhalis & intelligent IoT, a data warehouse, and cloud computing. These Amaranggana, 2013). Second, IoT could support smart destina- technologies enable a destination to be “smart” in terms of gener- tions in terms of providing information and analysis as well as ating rich and real-time intelligence about tourists' needs and automation and control (Chui, Lof€ fler, & Roberts, 2010). Third, wants and responding to them. Indeed, no matter how complicated mobile communication allows the communication of voice and STA becomes, the ultimate goal is to utilize the system to optimize data over mobile and portable devices (Buhalis & O'Connor, 2005). tourist experience, improve the effectiveness of resource manage- It can be used for mobile booking, online payment, information ment, and maximize both tourist satisfaction and STA competi- access, communicating, and self-entertainment during travelling tiveness (Buhalis & Amaranggana, 2013). Thus, the demand and (Adukaite, Reimann, Marchiori, & Cantoni, 2013). Fourth, artificial behavior of “new” tourists, as key STA stakeholders, have to always intelligence means that a computer-based system has capabilities be the point of departure when designing STAs. This is hence the of problem-solving, storing memory and understanding human focus of the present study. language (Wang, 2004). This technology can be applied to forecast Fig. 1 presents a preliminary conceptual model of structuring tourist flow, evaluate tourism service, handle tourist crowding, STA. At the heart of the conceptualization is SDL, serving as the issue emergency tourism alerts, and so on (Zhang et al., 2012). overarching logic guiding the design and operation of STAs. The The foregoing review suggests that traditional tourist attrac- physical properties (resources, tangibles) of STA, and the techno- tions are challenged to become “smarter” in responding to the logical presentation of STA (in terms of cloud computing, IoT, demand from “new” tourists, environment impacts and technology artificial-intelligence technology, and mobile communication) are development. For academics, the transition of traditional tourist all shaped by “new” tourist demand, which is in turn shaped by attractions into STAs presents an interesting research opportunity. external environmental impacts. The authors now turn to a discussion on the conceptual rationale underlying building and assessing STAs and the key methodological 2.5. FCEM-AHP and IPA approach adopted in this study. Considering the lack of research on the investigation of smart 2.4. Theoretical underpinnings tourism assessment, this paper first uses FCEM-AHP to evaluate STA from a tourist perspective, and then applies IPA to diagnose the Although STA construction appears to be a technical issue, un- strengths and weaknesses of STA. derlying it is a fundamental change of thinking on how tourist at- Fuzzy comprehensive evaluation, based on fuzzy mathematics tractions shall engage and design “value propositions” for their principle, aims to convert fuzzy and qualitative factors into quan- tourists. That is, the application of technology has to have a soul and titative factors by using fuzzy theory (Guo, 2007). FCEM was used in serve a strategic purpose. Wang et al. (2013) discussed the idea of this research because the term of “smart” is ambiguous and the Service-Dominant Logic (SDL) in explaining the rationale behind assessment criteria of STA evaluation items are rather subjective the “smart tourism destination” initiative. SDL was proposed by and qualitative in nature. It is difficult for evaluators to indicate Vargo and Lusch (2004), who argued that marketing theory and their preferences using exact numerical values. FCEM can practice are making a transition from the “goods-dominant” logic adequately handle the inherent uncertainty and imprecision of the toward SDL. Unlike “goods-dominant” logic, which stresses the human decision-making process (Chan & Kumar, 2007), and has importance of producing tangible outputs, completing trans- been shown to be useful in dealing with fuzzy evaluations such as actions, and profit maximization, SDL focuses on the serving pro- the safety guarantee system of reclaimed water quality (Zhou, cess and embraces the notion of value-in-use and co-creation of Zhang, & Dong, 2013), performance system of health, safety and value (Vargo & Lusch, 2004). environment (Li, Liang, Zhang, & Tang, 2015), decision making of oil Thoughts relating to SDL have drawn attention in the tourism spill contingency options (Liu & Wirtz, 2007), etc. field (Li & Petrick, 2008; Saraniemi & Kylanen,€ 2011). Li (2014) Analytic hierarchy process (AHP) was introduced by Saaty elaborated a tourism-grounded understanding of SDL and sug- (1980), and it facilitates an approach to allocate the relative gested that SDL provides a useful theoretical lens in making sense importance of evaluation items based on weights of criteria (Hsu, of emerging tourism-marketing thoughts and practices. Wang et al. Tsai, & Wu, 2009; Saaty, 1980). Thereby, AHP has been commonly (2013) argued that smart tourism development is more than the integrated with FCEM in multi-criteria fuzzy comprehensive 312 X. Wang et al. / Tourism Management 54 (2016) 309e320

Fig. 1. A conceptual model of structuring STAs. evaluation. For example, quality assessment in crisis and emer- 39 naturally designed zoo venues. In 2013, Hongshan Zoo received gency management by Cui (2012), risks evaluation of floor water 3.53 million visitors and was recognized as a 4A tourist attraction inrush by Wang, Yang, Li, and Liu (2012) and real estate investment by the China National Tourism Administration. by Zhang and Yang (2012), all used AHP to calculate weights in the Hongshan Zoo was chosen as the empirical research object fuzzy comprehensive evaluation. This study also applies FCEM-AHP mainly for three reasons. (1) Nanjing was designated as “smart to conduct the hierarchical fuzzy evaluation of STA. tourism pilot city” by China's national tourism authority, and Based on the FCEM-AHP evaluation of STA, this study also Hongshan Zoo is among the first group of tourist attractions to identifies the strengths and weakness of STA via IPA. IPA was practice smart tourism in Nanjing. (2) Compared to other STAs in introduced by Martilla and James (1977), and uses two dimensions, Nanjing, Hongshan Zoo has made obvious progress in terms of “importance” and “performance,” to prioritize the actions or im- providing a web home page, free Wifi, quick response codes, and provements to be considered for effective marketing efforts. Aca- electronic touch screens for tourists to search information. It offers demics and practitioners have widely adopted this simple, yet electronic platforms for tourists to make mobile payments and useful, approach in research fields such as airport and airline ser- online reservations. The park strengthens tourist safety and envi- vices (e.g., Mikulic & Prebezac, 2008, 2011), tourism (e.g., Coghlan, ronmental monitoring using techniques such as radio-frequency 2012; Li, 2012), hotels (e.g., Chu & Choi, 2000; Pan, 2015), banking identification and infrared sensors. In addition, Hongshan Zoo (e.g., Arbore & Busacca, 2011; Matzler, Sauerwein, & Heischmidt, also attempted to use smart devices and technologies to monitor 2003), supermarket retailing (e.g., Vazquez, Rodrıguez-Del tourist flow, handle tourist crowding, offer personal itineraries, and Bosque, Dıaz, & Ruiz, 2001), etc. By referencing the IPA, the cur- provide intelligent self-guided facilities. (3) Many tourists of Hon- rent research investigates tourists' perceptions of “importance” and gshan Zoo are from Nanjing, and they often visit this tourist “performance” of STA evaluation items, and further diagnose the attraction on weekends. Due to the high revisit rate, many tourists advantages and disadvantages of STA. have a good understanding of the smart tourism facilities of Hon- gshan Zoo, which makes it feasible to conduct the research. 3. Methodology 3.3. Data collection 3.1. Identifying evaluation items of STA Data collection was performed in two stages. In the first stage, a It can be argued that up to now, STA has not been subject to paper-and-pencil survey questionnaire was designed for this study. substantial empirical tests as a new concept. Thus, the evaluation The self-administrated questionnaire was in Chinese and contained items of STA were identified from smart tourism and relevant three parts. In Parts 1 and 2, the respondents were asked to rate the studies to provide insights into the core question of this study: how importance (1 ¼ not at all important, 5 ¼ very important) and to quantitatively evaluate STAs? performance (1 ¼ poor, 5 ¼ excellent) of the 38 STA evaluation Based on a comprehensive review of smart tourism and related items according to their travel experience in Hongshan Zoo. These literature, an initial pool of 38 evaluation items of STA was selected. data were used for the factor analysis, FCEM, and IPA. Part 3 was The sources and conceptual premises of these items are summa- designed to collect respondents' sociodemographic information: rized in Table 1. gender, age, education level, monthly income, and occupation (Table 2). A total of 680 questionnaires were distributed in Hon- 3.2. Study site gshan Zoo among a convenience sample of tourists during June 5e18, 2013. The surveys were conducted by four trained graduate Hongshan Zoo was selected as the study area. Covering an area students. The students approached the tourists who were resting of 1026 acres, this zoo is located in the Hongshan Hill of Nanjing, on site, informed them about the study, and indicated that partic- China. It is characterized by a harmonious combination of́ the forest ipation was confidential and voluntary. Those who refused to and animals. There are more than 280 kinds of animals living in the participate in the survey were not approached again. Altogether ́ Table 1 The original evaluation items of STA and the references.

No. Factors Factor description Sources a 1 Tourist attraction home page Tourists are increasingly utilizing digital sources such as tourism websites in their information search and communication exchange. Heung, 2003 ; Kaplanidou a Their travel intentions are strengthened by the website features of a tourism destination. & Vogt, 2006 2 Mobile application Mobile application can improve the quality of customer service in theme or amusement parks by showing the exact location of rides, Hafele, 2011 as cited in Liu checking on waiting times at different attractions, and reserving a place. and Law (2013) 3 Free Wifi Free Wifi allows users to connect mobile devices such as personal digital assistants and mobile phones to the Internet through a Buhalis & Law, 2008 wireless-radio connection. It is now extensively used in hotels, airports, and cafes. a 4 Online information access More travellers have used the Internet as a medium for searching tourism information and planning their trips. Travel information is Law & Leung, 2000 ; now among the most popular and frequently visited information on the Internet. Buhalis & Law, 2008 5 Quick response code Quick response codes can access information about nearby points of interest through mobile devices. GSMA, 2012a 6 Electronic touch screen Electronic touch screen technology can provide services to meet tourists' information needs 24 h a day. Connell & Reynolds, 1999 7 Short-messaging service and Short-messaging service and multimedia-messaging service are very useful for message-transfer at tourism destinations. Flouri & Buhalis, 2004 a multimedia-messaging service 8 Call-service center Along with the development of information technology, more interactive and time-sensitive channels, including the Internet and call- Pan & Fesenmaier, 2001 a service centers, have been widely used to provide useful and timely information for travellers' trip planning. 9 Intelligent-guide system Intelligent-guide system is the natural next step after guide books and audio guides on cassette. It can enhance tourists' experiences and Hornecker & Bartie, 2006 a; provide more or different information for tourists. Buhalis & Law, 2008 a 10 Personal-itinerary design People can design a tour plan with the collaborative tour-planner system in a collaborative manner, and design personal itineraries Kurata & Hara, 2013 309 (2016) 54 Management Tourism / al. et Wang X. according to their own points of interest. 11 E-tourism-recommendation system E-tourism-recommendation technologies can provide valuable information to tourists and help them discover and select the points of Buhalis & Law, 2008 interest that best fit their preferences. 12 Guiding-information service Guiding-information services combine mobile geographic-information system and global positioning system techniques with location- Chu, Lin, Chang, & Chen, a based services to provide tourists with a better trip experience and deeper understanding of the importance of the valuable landscape. 2011 13 E-tour map Using global positioning systems, electronic maps and compasses can collect information from satellites and provide tourists, hikers, and Hawkins, Leventhal, & boaters with exact geographic positions and directions. Oden, 1996 a 14 Smart card (band) A smart card (band) contains personal information on embedded radio-frequency identification chips. It can serve as a driver's license, Marie et al., 2000 car and house keys, passports and medical record all-in-one. Smart cards (bands) are widely used in amusement parks, retail stores, sports stadiums, universities, and health facilities. a 15 Electronic-entrance guard system A mature scenic spot information system should consist of several IoT information systems, including an electronic-entrance guard and Guo, Liu, & Chai, 2014 ticketing system that utilizes radio-frequency identification technology. 16 Smart environment Smart environment is one of the important dimensions of smart-tourism destinations. It is related to energy optimization that leads to Cohen 2012 as cited in sustainable management of available resources. Buhalis & Amaranggana, 2013 17 Tourist-flow monitoring Using mobile positioning data to monitor the space-time movement of tourists and control the tourist flow in real time. Ahas, Aasa, Mark, Pae, & a Kull, 2007 e

18 Crowd handling Using a variety of sensors to control visitor numbers within specific tourism sites according to the carrying capacity. Wu, Yang, Zhang, Dong, 320 Yan, Shan, Li, Wang, & Han, 2012 a 19 Smart education Destinations should not only focus on exploiting new technologies but also should educate their tourists on how to best use these new Komninos, Pallot, & technologies through the smart learning method. Schaffers, 2013 a 20 E-complaint handling Tourism organizations should have an e-complaint handling system to provide channels for tourists' feedback and complaints. Buhalis & Law, 2008 21 Mobile payment Purchasing tourism products through mobile websites and applications is an emerging market. More and more tourists use mobile Huang, Li, & Li, 2013 a devices to plan, purchase, and enhance their travel experiences. 22 Electronic-ticketing system A mature scenic-spot information system should have an electronic-ticketing system that utilizes radio-frequency identification Guo et al., 2014 a technology. 23 Online coupons The use of online coupons is increasing in popularity in the tourism industry. For consumers, online coupons promise substantial savings. Sigala, 2013 a 24 Online booking Using technologies such as Wifi, global navigation satellite systems, geographic information systems and global positioning systems to Wang & Wang, 2010 a; meet tourists' mobile reservation demands. Buhalis & Law, 2008 25 Tourist-flow forecast On the basis of the routes used and tourists' movements, managers of scenic spots can analyze the visiting behavior of tourists, then Yin, Yin, Wang, Wu, & Li, a forecast tourist flow and set early warnings. 2011 26 Festival-activity forecast Using mobile applications, tourist attractions can forecast festivity information to tourists. Wang & Zhu, 2013 a 27 Queuing-time forecast Using mobile applications, tourist attractions can forecast and provide queuing time for tourists. Wang & Zhu, 2013 a 28 Weather forecast Weather plays an important role in tourists' decision-making. Based on context-aware recommender technique systems, tourists can Braunhofer, Elahi, Ricci, & search and obtain weather information for their destinations. Schievenin, 2013 a 29 Electronic toll collection Radio-frequency identification technology can be used for electronic toll collection at scenic spots. Its obvious advantage is no parking Zhang, Zhang, & Huang, toll collection. It can thereby significantly improve the efficiency of the toll station. 2011 a (continued on next page) 313 314 X. Wang et al. / Tourism Management 54 (2016) 309e320

600 questionnaires were collected and 191 invalid responses were & eliminated. A response was deem invalid when the respondent &

García, provided multiple answers to single-choice questions, or when a

& substantial portion of questions in the survey was left unanswered. a a a a The effective response rate is thus 68.2% and a total of 409 valid a a a Law, 2008 Amaranggana, questionnaires were used for the analysis. & & In the second stage, the weight of each item was determined ; Fritz, Susperregui, a using AHP. Although the importance of the evaluation items had Minoh, 2013 ﬁ Linaza, 2005 Guo et al., 2014 Sources Wang, 2013 Buhalis Linaza, Gutierrez, Akehurst, 2009 Buhalis 2013 Guo et al., 2014 Stepchenkova, Mills, Jiang, 2007 2013 Kasahara, Mori, Mukunoki, & been assessed separately using a ve-point Likert-type scale in the ﬁrst stage of data collection, it is necessary to assess the items' relative weights when they are put together in the STA evaluation

rist system. Hence, AHP using pair-wise comparison between items was employed to determine the weight of each item. Following the AHP approach, twenty graduate students major- cation

ﬁ ing in tourism were asked to judge the degree of importance of the connects the ps, and eventually

and far from being STA evaluation items. These judges were chosen for two reasons.

a destination without First, their academic credentials qualify them to evaluate the ” importance of STA items from a researcher perspective. Second, they have all visited at least one of the three “pilot STAs” desig- iors, community residents, and

c situations in tourist attractions. nated by the local government (i.e., Hongshan Zoo, Xuanwu Lake, ﬁ experience “ and Sun Yat-sen Mausoleum) in the previous year. Travel experiences in those pilot STAs is helpful to weight the evaluation items of STAs from a tourist perspective. Two rounds of surveys were conducted to determine the weights of items, and more details will be discussed in Section 3.4.

3.4. FCEM-AHP

According to Cui (2012), the steps for the FCEM-AHP procedure are as follows:

Step 1. Determine the item set of the evaluated object.

The item set of the evaluated object is the various items that can affect the evaluated object, and is deﬁned by U as follows:

U ¼ fu1; u2; u3; …; umg (1)

where ui represents the ith item inﬂuencing evaluated objects. These items usually have different degrees of fuzziness. such as electronic sensors to ensure tourists' safety during their trips in routine situations and helping tourists to

” Step 2. Determine the evaluation set.

The evaluation set is composed of the elements of various comprehensive evaluation results of the evaluated object as set by the evaluators. It is deﬁned by V as follows: smart materials “ .

V ¼ fv1; v2; v3; …; vng (2) infrastructures of the scenic spots through the Internet. security equipment with service facilitiesthrough in a the wireless tourist sensor attraction network. via IoT and realizes intelligent warning and emergency response experience. actually visiting it. This experience within a computer-mediated environment can simulate real visits. an irrelevant, blogs are often perceived to be more credible and trustworthy than traditional marketing communications. technology, wireless local area networks (WLAN) and other technologies. make travel-related decisions through the mediation of computer bulletin boards and networks. escape in the event of a disaster.

where vj represents the jth evaluation result. Appendix A

Step 3. Determine the weight set.

The procedures using AHP to determine the weight set of STA can be summarized as follows. First, the relative significance of different criteria needs to be evaluated by judges according to a c broadcast Using video surveillance systems as sensors to supply real-time information on transportation and traf fi “1e900 scale process (Saaty, 1980)(Table 3), and a judgment matrix can be constructed. Next, the maximum eigenvalue of the judg- ) ment matrix is calculated. The eigenvector of the largest eigenvalue c-safety protection Using fi is the evaluation weight vector A. Finally, a consistency test is used to decrease the subjectivity of judgment and ensure the rationality continued ( of weights. When the consistency ratio (CR) is below 0.1, the con-

Detailed reference information is listed in sistency of the judgment matrix is considered reasonable. Other- 30 Smart vehicle scheduling A mature scenic-spot information system should have a vehicle-scheduling system that utilizes radio-frequency identi No. Factors Factor description 31 Real-time traf 3334 Traf Smart emergency response35 system Virtual A tourism smart experience emergency-response system is a tourism-security37 platform based on IoT and cloud computing. This platform Augmented reality38 Interacting with multimedia-enhanced websites can create a Blogs telepresence of and tourist that allows attractions people to By means of augmented A recent reality, survey the found real that scene tourists trusted is more enhanced websites by with multimedia reviews than personalized professional interactive guides information and to travel agencies, improve the tou 32 Intelligent-environment monitoring IoT technology allows smart scenic spots to sense geographical features, natural disasters, tourist behav 36 Virtual travel community A virtual travel community makes it easier for people to obtain information, maintain connections, develop relationshi a ﬁ Table 1 wise, the matrix must be adjusted until the consistency is satis ed. X. Wang et al. / Tourism Management 54 (2016) 309e320 315

Table 2 Demographics of the sample (N ¼ 409).

Demographic variables Frequency % Demographic variables Frequency %

Gender Monthly income (RMB) Male 201 49.144 Below 1000 22 5.379 Female 208 50.856 1000e3000 57 13.936 Age 3001e5000 89 21.760 Up to 20 45 11.002 5001e10,000 122 29.829 21e30 119 29.095 Above 10,000 119 29.095 31e50 207 50.611 Occupation 51e60 37 9.046 Student 92 22.494 Over 60 1 0.244 Researcher or teacher 87 21.271 Education level Civil servant 56 13.692 Primary school or below 24 5.868 Businessperson 59 14.425 Junior High school 63 15.403 Service worker 47 11.491 Senior High school 76 18.582 Housewife 36 8.802 College 139 33.985 Retired 17 4.156 Graduate school or above 107 26.161 Others 15 3.667

Step 4. Constructing the fuzzy judgment matrix. include: short-messaging service and multimedia-messaging service, call-service center, guiding-information service, smart envi- The fuzzy judgment matrix R can be defined as follows: ronment, e-complaint handling, electronic-ticketing system, 2 3 2 3 festival-activity forecast, electronic-toll collection, augmented re- / R1 R11 R12 R1n ality, and the tourist attraction blog), and eight underlying factors 6 7 6 / 7 6 R2 7 6 R21 R22 R2n 7 with an eigenvalue greater than 1.0 were derived from the rest of R ¼ 4 5 ¼ 4 ««1 « 5 (3) R3 the 28 evaluation items of STA. The value (0.727) of the KMO / R4 Rm1 Rm2 Rmn measure of sampling adequacy indicates the appropriateness of applying factor analysis in this research (Hair, Ortinau, & Bush, where R is the evaluation results of the item set U and Rij is the 2000). Bartlett's test of Sphericity value was 11,001.668 at degree of membership of the ith item ui to the jth evaluation rank vj, p ¼ 0.001 significance level, which showed that a significant cor- fl which re ects the fuzzy relationship of every item. relation existed among at least some of the variables (Kim, Lee, & Hiemstra, 2004). As shown in Table 4, eight main factors accoun- Step 5. Fuzzy comprehensive evaluation. ted for 78.109% of the total variance of STA indicators and were labeled as follows: smart-information system, intelligent-tourism The fuzzy comprehensive evaluation can be obtained by calcu- management, smart sightseeing, e-commerce system, smart lating between the single item weight vector A and the fuzzy safety, intelligent traffic, smart forecast and virtual tourist attrac- judgment matrix R, that is: tion. The reliability for each STA dimension, as assessed by Cron- bach's alpha coefficients, was greater than 0.6, meeting the B ¼ A+R ¼ðb ; b ; /bmÞ (4) 1 2 criterion suggested by Hair et al. (2006). “ where b is the membership degree value of evaluated samples to Of the eight underlying dimensions, smart-information sys- i ” each evaluation standard. The evaluation results are usually tem was considered the most important STA dimension as defined according to the maximum-membership degree principle. perceived by tourists. It accounted for approximately 17.114% of the variance and included attributes such as the homepage of the tourist attraction, free Wifi, online information access, mobile 4. Results application, quick-response code, and electronic touch screen. Factor 2, “intelligent tourism management,” accounted for an 4.1. Results of STA evaluation factors additional 15.813% of the variance, and includes the concepts of smart card (band), electronic-entrance guard system, tourist-flow A principal component analysis with varimax rotation was used monitoring, crowding handling, and smart education. The third to identify the underlying dimensions of STA evaluation items. The factor, “smart sightseeing,” is defined by attributes such as identification of factors and elimination of items were based on the personal-itinerary design, intelligent-guide system, e-tourism criteria suggested by Hair, Black, Babin, Anderson, and Tatham recommendation system, and e-tour map. The fourth factor, “e- (2006): (1) factor loading equal to or greater than 0.50, (2) eigen- commerce system,” is related to concepts such as mobile payments, values equal to or greater than 1.0. online coupons, and online booking. The fifth factor, “smart safety,” According to the results of principal component analysis, ten is depicted by items such as intelligent environment-monitoring, items with factor-loading less than 0.5 were removed (these

Table 3 Scales of relative importance.

Scales of relative importance Meaning

1 Item i is equally important to item j 3 Item i is slightly more important than item j 5 Item i is more important than item j 7 Item i is much more important than item j 9 Item i is substantially more important than item j 2, 4, 6, 8 Intermediate scales 316 X. Wang et al. / Tourism Management 54 (2016) 309e320

Table 4 Results of factor analysis.

Factor Factor loading Eigenvalue Variance explained Alpha Mean Std. deviation Weight

a Smart information system (U1) 4.792 17.114 0.941 0.210 b Tourist attraction home page (U11) 0.860 3.814 1.014 0.313 b Free Wifi (U12) 0.947 3.863 0.900 0.259 b Online information access (U13) 0.965 3.907 0.835 0.184 b Mobile application (U14) 0.812 3.833 0.930 0.123 b Quick-response code (U15) 0.841 4.005 0.813 0.082 b Electronic touch screen (U16) 0.827 3.809 0.830 0.039 a Intelligent tourism management (U2) 4.428 15.813 0.944 0.189 b Smart card (band) (U21) 0.870 3.291 1.428 0.245 b Electronic-entrance guard system (U22) 0.915 3.068 1.445 0.149 b Tourist-flow monitoring (U23) 0.854 3.029 1.412 0.220 b Crowd handling (U24) 0.864 3.279 1.430 0.234 b Smart education (U25) 0.846 3.105 1.648 0.152 a Smart sightseeing (U3) 2.643 9.440 0.812 0.170 b Personal-itinerary design (U31) 0.789 3.501 1.376 0.324 b Intelligent-guide system (U32) 0.648 3.418 1.407 0.270 b E-tourism-recommendation system (U33) 0.872 3.399 1.325 0.219 b E-tour map (U34) 0.838 3.355 1.277 0.187 a E-commerce system (U4) 2.204 7.871 0.774 0.106 b Mobile payment (U41) 0.682 3.323 1.371 0.408 b Online coupons (U42) 0.819 3.279 1.467 0.328 b Online booking (U43) 0.828 3.413 1.512 0.264 a Smart safety (U5) 2.173 7.759 0.744 0.099 b Intelligent-environment monitoring (U51) 0.744 3.421 1.334 0.264 b Travel-safety protection (U52) 0.827 3.156 1.276 0.389 b Smart emergency-response system (U53) 0.731 3.149 1.239 0.346 a Intelligent traffic (U6) 2.094 7.480 0.926 0.093 b Smart vehicle-scheduling (U61) 0.898 3.606 0.834 0.6 b Real-time traffic broadcast (U62) 0.895 3.675 0.918 0.4 a Smart forecast (U7) 1.952 6.971 0.687 0.074 b Tourist-flow forecast (U71) 0.732 2.403 1.316 0.416 b Queuing-time forecast (U72) 0.806 2.741 1.467 0.423 b Weather forecast (U73) 0.764 2.706 1.591 0.161 a Virtual tourist attraction (U8) 1.585 5.661 0.799 0.059 b Virtual tourism experience (U81) 0.870 4.081 1.334 0.529 b Virtual travel community (U82) 0.664 3.638 1.525 0.471 Total variance extracted ¼ 78.109%, KMO ¼ 0.727. Bartlett's test of Sphericity ¼ 11,001.668 (df ¼ 378, p < 0.001). a The first level of the STA evaluation item set. b The second level of the STA evaluation item set. travel safety-protection, and smart emergency-response system. Table 5 Factor 6, “intelligent traffic,” is associated with smart-vehicle Judgment matrix of STA's first-level evaluation factors. fi “ scheduling and real-time traf c broadcasting. Factor 7, smart UU1 U2 U3 U4 U5 U6 U7 U8 Weight forecast,” includes tourist-flow forecasts, queuing-time forecasts, U1 1 9/7 9/8 9/5 9/5 9/4 3/1 9/2 0.210 and weather forecasts. Finally, the last factor represents “virtual U2 7/9 1 9/5 9/5 9/5 9/5 9/4 3/1 0.189 tourist attraction” and is defined by two attributes: the virtual U3 8/9 5/9 1 9/7 3/2 3/1 3/1 9/4 0.170 tourism experience and the virtual travel community. U4 5/9 5/9 7/9 1 1 9/8 3/2 3/2 0.106 U5 5/9 5/9 2/3 1 1 1 9/8 3/2 0.099 U6 4/9 5/9 1/3 8/9 1 1 9/8 9/4 0.093 U7 1/3 4/9 1/3 2/3 8/9 8/9 1 9/7 0.074 4.2. Results of FCEM-AHP U8 2/9 1/3 4/9 2/3 2/3 4/9 7/9 1 0.059

lmax ¼ 8.135, CI ¼ 0.019, RI ¼ 1.41, CR ¼ 0.014 < 0.10. 4.2.1. Determining item set of STA Based on the items identified from literature review and factor analysis, the evaluation item set of STA can be divided into two 4.2.3. Determining the weight set of STA levels. Accordingly, the first and second levels of the STA evaluation The weights of items were determined by two rounds of sur- fi item set of Hongshan Zoo can be constructed, as shown in Table 4. veys. In the rst round, the twenty judges were asked to rate STA items' importance using a 1e9 scale pair-wise comparison method. Then, the weights of the evaluation items of STA were calculated based on the judges' feedback. Next, the statistical results of the 4.2.2. Determining the evaluation set of STA weights were returned to the judges, who again evaluated the The STA evaluation set of Hongshan Zoo is determined as importance of each item. After two rounds of feedback, the weights follows: of the STA evaluation items were determined using MCEAHP software. V ¼fv ; v ; v ; v ; v g 1 2 3 4 5 Based on the comparison result of the judges, the judgment matrix of the STA's first-level evaluation items was obtained where v , v , v , v , v represent excellent, good, moderate, fair, and 1 2 3 4 5 (Table 5). Then the maximum eigenvalue and its corresponding poor, respectively. X. Wang et al. / Tourism Management 54 (2016) 309e320 317 eigenvector of the judgment matrix were calculated to get the forecast, tourist-flow forecast, and virtual tourism experience. weight set A ¼ (0.210, 0.189, 0.170, 0.106, 0.099, 0.093, 0.074, 0.059). These items are likely to receive lower priority due to their rela- A consistency test was further conducted to check the rationality of tively low importance. the weights. As lmax ¼ 8.135, so CR ¼ 0.014 < 0.10. Thus, the judg- The attributes that fall within the upper-right quadrant (“keep ment matrix has satisfactory consistency, indicating that the weight up the good work”) are important items with good performance: set obtained by AHP is reasonable. tourist attraction homepage, mobile payment, online information Following the same procedure, the weight sets of the second- access and travel-safety protection. Those items are the strengths of level evaluation items were also calculated, as shown in Table 4 the Hongshan Zoo's STA building and need to be well-maintained. (See Tables B1eB8 in Appendix B for the calculation process). The indicators appearing in the lower-right quadrant (“possible overkill”) are comparatively less important, but Hongshan Zoo 4.2.4. Constructing the fuzzy judgment matrix of STA performs well on them. These include weather forecast, quick- According to the respondents' assessment of the performance of response code, electronic-entrance guard system, online booking, the STA evaluation items, the fuzzy judgment matrix of Hongshan virtual travel community, intelligent-environment monitoring, e- Zoo: R1, R2, R3, R4, R5, R6, R7, and R8 can be constructed (See tour map, smart emergency-response system, and online coupons. Appendix C). 5. Conclusions and implications 4.2.5. Fuzzy comprehensive evaluation of STA fi By using fuzzy judgment matrixes and the corresponding 5.1. Key ndings weights sets, the result of the second-level fuzzy comprehensive evaluation can be calculated, then the second-level comprehensive The primary objectives of this study are to identify tourist evaluation matrix of Hongshan Zoo (R) can be constructed as preference of STA, and to measure strengths and weaknesses of an follows: STA via FCEM-AHP and IPA. Although exploratory in nature, this 0 1 study offers useful insights into the theoretical investigation and 0:095 0:35 0:381 0:157 0:017 practical development of STA. B C B 0:119 0:054 0:234 0:235 0:358 C First, this study contributes to the understanding of tourist B C B 0:067 0:108 0:253 0:527 0:044 C preferences of STA on the theoretical grounds. While the devel- B C B 0:423 0:41 0:155 0:011 0 C opment of smart tourism is gaining popularity, there has been R ¼ B C B 0:132 0:447 0:374 0:027 0:018 C insufficient research soliciting tourists' opinions when constructing B C B 0:001 0:004 0:058 0:487 0:449 C STA. This research fills this gap in the existing tourism literature @ A 0:044 0:11 0:026 0:727 0:092 regarding which important aspects tourists consider when evalu- 0:13 0:348 0:167 0:306 0:048 ating an STA. Based on a literature review and factor analysis, this research identified 28 key evaluation items of STA and grouped By using assessment matrix R and the corresponding weight them into eight categories: “smart information system”, “intelli- vector A, the result of the first-level fuzzy comprehensive evalua- gent tourism management”, “smart sightseeing”, “e-commerce tion can be obtained by using B ¼ A+R, system”, “smart safety”, “intelligent traffic”, “smart forecast” and “ ” fi B ¼ð0:123; 0:219; 0:238; 0:288; 0:132Þ: virtual tourist attraction . The ndings indicate that tourist preferences of STA are multifaceted, which include not only real-time The results of a fuzzy comprehensive evaluation are usually information access, online booking and tourist-flow forecast defined according to the maximum-membership degree principle. before trip, but also effective tourist attraction management, From vector B, it can be recognized that the membership-degree personalized itinerary design, efficient transport and smart safety values of “excellent”, “good”, “moderate”, “fair,” and “poor” are during trip. In addition, sharing tourism experiences in virtual 0.123, 0.219, 0.238,0.288 and 0.132, respectively. Among them, the tourist attraction after trip is also essential for tourists. membership degree value of “fair” (0.288) is the largest one. Thus, Second, this study provides insights into the approach for the STA evaluation score of Hongshan Zoo is 0.288 (at the level of measuring and identifying the strengths and weaknesses of STA. “fair”). This indicates the STA construction in Hongshan Zoo is still Given the limited literature on quantitative evaluation of STA, it is in the initial stage, and the “smart” level is relatively low. deemed necessary to investigate the evaluation approach of STA. Considering the ambiguous nature of being “smart”, FCEM-AHP is a 4.3. Results of the IPA proper approach to evaluate STA due to its advantage of conducting multi-criteria fuzzy evaluations. Employing the FCEM-AHP, this The “importance” and “performance” matrix of the 28 STA paper conducted the STA assessment of Hongshan Zoo in Nanjing, evaluation items of the Hongshan Zoo was prepared using SPSS China. The result indicates that the smart level of Hongshan Zoo is 21.0. As shown in Fig. 2, the vertical axis represents “importance,” relatively low. Further investigation using IPA shed light on diag- while horizontal axis represents “performance.” Actual mean score nosing the strengths and weaknesses of STA construction in the of weights (0.0357) and performance (3.02) were used as the Hongshan Zoo. Collectively, the methods used in this study are crossing point in constructing the IPA grid. instrumental for quantitative assessments of STAs. The items in the upper-left quadrant (“concentrate here”) of the matrix are the most significant evaluation items of STA with poor 5.2. Managerial implications performance: smart-vehicle scheduling, personal-itinerary design, smart card (band), intelligent-guide system, free Wifi, tourism-flow The findings of this paper will not only contribute to the aca- monitoring, crowd handling, e-tourism recommendation system, demic research of STA, but also chart new directions for the plan- and real-time traffic broadcast. These items represent the weak- ning and construction of STA in practice. nesses of Hongshan Zoo's STA construction and deserve further First, the tourists' preferences of STA identified in the present attention and investments. research are useful for the management of tourist attractions. The items within the lower-left quadrant (“low priority”) Despite the increasing attention of smart tourism gained by tourist include smart education, mobile application, queuing-time attraction practitioners, most focuses have been put on the 318 X. Wang et al. / Tourism Management 54 (2016) 309e320

Fig. 2. Result of IPA. deployment of complex technological facilities. Due to the lack of a 5.3. Limitations and future research directions tourist-centric or tourist-oriented mindset, many smart tourism facilities may not necessarily match visitors' needs. Thus, tourist Several limitations of this study should be acknowledged, which attractions should make an optimal use of smart tourism facilities may provide guidance for future research. First, this study used a by offering the right smart tourism devices and services that suit convenience sample of tourists in Hongshan Zoo to investigate the tourist preference at the right time. In relation thereto, this research evaluation items of STA, which may limit the generalizability of its could help practitioners understand how to make the tourist research findings. It is necessary to investigate if tourists in other attraction smarter according to tourist needs, wants, and prefer- areas or visiting other STAs will respond to the survey in a different ences and, in turn, enhance tourist experience and improve tourist way. In other words, further research could use other tourist at- satisfaction. tractions as the study sites to examine whether the findings from Second, the weights of STA evaluation items in this study can this study are replicable. Second, although more than 400 re- shed light on the construction sequence of STA. The development of spondents participated in the survey, most of them were under 60 STA requires substantial efforts, time and resources. Thus, years of age. Older tourists who are less knowledgeable about smart providing a guideline of key attributes in STA construction is a tourism might have avoided participating in this survey. Thus, timely and important contribution to the industry. The weights of future researchers are advised to investigate senior tourists' views STA evaluation items can inform the managers of the roles these toward STA, with the aim of providing targeted smart services for key items play in STA development. As shown in Fig. 2, the ten most different market segments. Third, the weights of STA evaluation important items preferred by tourists are tourist attraction home- items were judged by twenty graduate students. Ideally, using a page, smart vehicle-scheduling, personal-itinerary design, free more authoritative judge panel with leading researchers and Wifi, smart cards (bands), intelligent-guide system, crowd practitioners could enhance the validity and reliability of the handling, mobile payment, tourist-flow monitoring, and online- research. information access. Those items should be given priority when Today's attractions need to become “smarter” because the way building an effective STA. tourism experiences are designed, delivered, and consumed has X. Wang et al. / Tourism Management 54 (2016) 309e320 319 profoundly changed. This study represents one of the first studies life extension technology workshop, Paris, France. on smart tourist attraction. Considering the central role tourist Han, D. I., Jung, T., & Gibson, A. (2013). Dublin AR: implementing augmented reality in tourism. In Z. Xiang, & L. Tussyadiah (Eds.), Information and communication attractions play in the tourism system (Leiper, 1979), the authors technologies in tourism 2014 (pp. 511e523). Cham, New York: Springer. believe STA represents a fertile ground for future research, which Hsu, T. K., Tsai, Y. F., & Wu, H. H. (2009). The preference analysis for tourist choice of e deserves more scholarly attention. destination: a case study of Taiwan. 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Jin-He Zhang, Ph.D. ([email protected])isa Xia Wang, Ph.D. ([email protected]) is a associate professor at the School of Geographic and Oceanographic professor at the School of Geographic and Oceanographic Sciences, Nanjing University, China. He received his Ph.D. ́ Sciences, Nanjinǵ University, China. She received her Ph.D. degree from Nanjing University, China. His current degree from Nanjing University, China. Her current research interests include tourism planning and manage- research interests include tourist and resident satisfaction, ment, and ecological tourism, and environmental impact Pro-poor tourism, and smart tourism. She has published in of tourism. His articles have appeared in journals such as journals such as Journal of Travel & Tourism Marketing, Asia Asia Paciﬁc Journal of Tourism Research, Acta Geographica Paciﬁc Journal of Tourism Research, Current Issues in Tourism, Sinica, Geographical Research, Journal of Ecology, and Chi- and Chinese Geographical Science. nese Geographical Science.