Relationships between technology attachment, experiential relationship quality, experiential risk and experiential sharing intentions in a smart hotel

Journal of Hospitality and Tourism Management 37 (2018) 42–58

Contents lists available at ScienceDirect

Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm

Relationships between technology attachment, experiential relationship quality, experiential risk and experiential sharing intentions in a smart hotel

T

Hung-Che Wua,∗, Ching-Chan Chengb a b

Business School, Nanfang College of Sun Yat-sen University, No. 882 Wenquan Avenue, Conghua District, Guangzhou City, Guangdong Province, 510970, China Department of Food and Beverage Management, Taipei University of Marine Technology, No. 212, Yen Ping N. Rd., Sec. 9, Taipei City, 111, Taiwan

A R T I C LE I N FO

A B S T R A C T

Keywords: Technology attachment Experiential relationship quality Experiential risk Experiential sharing intentions

This study aims to examine the relationships among the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions. The findings of this study are based on structural equation modeling (SEM) and hierarchical regression analysis (HRA) of a convenience sample of 525 guests during check out from the LINQ Hotel & Casino in Las Vegas, indicating that the proposed model fits the data. The analysis results contribute to the services marketing theory by providing additional insights into the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions. The results of this study will also assist smart hotel management in developing and implementing market-oriented service strategies to increase the dimensions of technology attachment and the dimensions of experiential relationship quality, decrease experiential risk and create experiential sharing intentions.

1. Introduction Market observation indicates the development of a new model for running a business in the hospitality industry, referred to as smart hotels. This model is specifically distinguished by new information and communication technologies (ICT). The concept of smart hotels is relatively new and can be considered as an innovative solution in tourism. The hospitality industry represents, beyond any doubt, one of these economy sectors which take an increasingly intensive advantage of the available ICT. It plays a particular role and is seen as the key factor of smart hotels' effective functioning. It not only allows improved management effectiveness and higher efficiency of functioning, but also facilitates achieving such service level which, in the times of technological advancement in daily life, can lead to much better satisfaction of the demanding guests (Jaremen, Jędrasiak, & Rapacz, 2016). A smart hotel is an intelligent hotel with a range of information technologies working together to let the guests have an honorable and convenient vacation environment. It allows guests to have a profound image about not only the hotel, but also the city and the country. Moreover, it can increase guest loyalty and repurchase rates as well. Accordingly, developing a smart hotel is critical for the hospitality industry in practice (Lai & Hung, 2017). Returning to the term of a smart hotel, it is worth paying attention to the fact that it is used more by practitioners than theorists. A smart hotel is usually encountered in the subject literature ∗

and in the opinions of hospitality industry specialists. As a result, the idea of smart hotels does not stand for a theoretical concept, created as a result of scientific thought development, describing the functioning of a hotel enterprise. Instead, it is rather a practical business model which adapts new information and communication technologies in the hospitality business. In accordance with its assumptions, hotel competitiveness depends on supporting its operations by applying technological solutions (Jaremen et al., 2016). Smart technology for hotels provides an arsenal of options to not only provide a wow factor for guests, but also make the property run more efficiently. With over 85% of the traveling population owning a smartphone or tablet, prospective guests are incorporating their mobile experiences into their lives at an increasing level. It only makes sense for hotels to follow suit and satisfy the guest need in the more intimate, mobile environment, enabling them to personally enhance their quality of stay in the hotel (D'Amico, 2016). When the benefits from adopting new smart technologies or norms are high, such as may be the case during a period of rapid environmental change (Potts, 2013), experiential sharing intentions evolve and rapidly become dominant in the hospitality industry (Kang & Namkung, 2016; Sotiriadis & Sotiriadis, 2017). According to Brown, Altman, and Werner (2012), place attachment is the positive bond developed from behavioral, cognitive and affective ties between an individual or groups and their socio-physical environments. The developmental theory of place attachment attempts to bring

Corresponding author. E-mail addresses: [email protected] (H.-C. Wu), [email protected] (C.-C. Cheng).

https://doi.org/10.1016/j.jhtm.2018.09.003 Received 1 March 2018; Received in revised form 27 August 2018; Accepted 12 September 2018 1447-6770/ © 2018 Published by Elsevier Ltd on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

(e.g. Bock et al., 2016; Hertlein & Twist, 2018; Kim, Jun, Han, Kim, & Kim, 2013; Kim et al., 2015; Li, 2014; Trub & Barbot, 2016) propose that technology attachment has been considered to be a multi-dimensional construct. Personalized hotel technology experiences will become increasingly important, not only for operating efficiency, but also for attracting more guests to stay. D'Amico (2016) describes that the hotel's property can be run more efficiently using smart technology. According to Jaremen et al. (2016), several well-known examples of smart hotels can be quoted here: The Upper House in Hong Kong (the guests receive iPod Touch at check-in, loaded with a set of games, music and information about the hotel for their own use); Novotel München Messe (the guests are greeted by both the real and a virtual receptionist, the hotel provides information and communication systems equipped in touchscreens, through the use of which guests can easily find the tourist information they need; Crowne Plaza in Copenhagen (owing to the application of new technologies, has become neutral in terms of CO2 emission, the entire energy used in it originates from renewable sources (e.g. bicycles propelled by the power of muscles of the guests working out in the hotel fitness club 2), Blow Up Hall, Poznań, the hotel guests receive iPhones, instead of keys or cards, which they use which to enter their rooms. The above listed hotels represent the examples of an effective implementation of new information and communication technologies in their functioning. These smart technologies may make guests feel emotionally attached to the smart hotel. Sigala (2018) indicates that technology attachment has been found to lead to new forms of technostress and anxiety influencing life satisfaction, well-being, workplace productivity, social and work relations. However, to the best of our knowledge, none of the studies focus on applying the dimensions of place attachment in the measurement of the dimensions of technology attachment (technology dependence, technology identity, technology affection and technology social bonding) in the hotel industry. Liu, Guo, and Lee (2011) indicate that relationship quality comprises two dimensions, trust and satisfaction, which are each considered as an “emotional state that occurs in response to an evaluation of these interaction experiences”. According to Chen, Petrick, and Shahvali (2016) and Jung and Soo (2012), customers strengthen their relationship with and come to trust a product and/or service when they enjoy a positive experience. Also, customers who have a pleasant experience generally agree that the service provider has exceeded their expectations, leading to the creation of a satisfying relationship (Rajaobelina, 2018). Marketers face the challenge of how to allocate resources across different channels (Baxendale, Macdonald, & Wilson, 2015; Mahrous & Hassan, 2017). Indeed, customer experiences differ from one channel to the next and consideration must be made for each (Verhoef et al., 2009). With customers open to multiple channel experiences (Stein & Ramaseshan, 2016), the relationship between customer experience and relationship quality varies based on the channels used. In general, when customers enjoy a positive experience, they strengthen their relationship with and come to trust and feel satisfied with an organization (Jung & Soo, 2012; Wong, Wu, & Cheng, 2015; Wu, 2017; Wu, Wei, Tseng, & Cheng, 2018e). Although the dimensions of relationship quality have been extensively conducted (e.g. Abdul-Rahman & Kamarulzaman, 2012; Kim & Cha, 2002; Pepur, Mihanović, & Arnerić, 2011; Rashid, Abu, & Ahmad, 2011), none of the studies focus on experiential relationship quality and its dimensions (experiential trust and experiential satisfaction) in the hotel industry. Paulssen and Fournier (2007) indicate that consumer attachment has an influence on trust and satisfaction. Although some studies have demonstrated the links between place attachment and place satisfaction (e.g. Yüksel et al., 2010), further research is warranted to investigate the relationship between these two constructs. Evidence suggests that place attachment, conceptualized as place dependence, place identity (Prayag & Ryan, 2012) and place affection (Yüksel et al., 2010) may be a predictor of satisfaction. Wu, Cheng, and Ai (2018a, 2018b) and Wu, Cheng, Chen, and Hong (2018c) identify that the following pre-

together attachment theories in psychology (e.g. Bowlby, 1982) and theories of place. According to this theory, place attachment emerges from social interactions and one's evaluation of the environment. Place attachment has been considered as a developmental process in which experiences in a place are internalized at the unconscious level and subjectively manifested into an attachment to the place (Morgan, 2010). It is a meaningful construct at the end of a tourist trip, when all tourism experiences are complete. From the perspective of people–environment interactions, place attachment would thus represent an overall connection or bond between a person and a location (Tuan, 1980). Place attachment has been studied extensively in tourism (e.g. Ramkissoon, Weiler, & Smith, 2012, 2013c; Ramkissoon, Smith, & Weiler, 2013a, 2013b; Chen, Dwyer, & Firth, 2014; Ram, Björk, & Weidenfeld, 2016; Ramkissoon, Smith, & Kneebone, 2014; Veasna, Wu, & Huang, 2013; Yüksel, Yüksel, & Bilim, 2010). Studying tourists' attachment to national parks and recreational areas to predict pro-environmental behavior dominates the existing research tradition (e.g. Hwang, Lee, & Chen, 2005; Ramkissoon, Smith, & Weiler, 2013b; Tonge, Ryan, Moore, & Beckley, 2015). According to Ramkissoon et al. (2014), place attachment has often been conceptualized as consisting of multiple dimensions. In general, place attachment includes place dependence (Stokols & Shumacker, 1981), place identity (Vaske & Kobrin, 2001; Walker & Chapman, 2003), place social bonding (Kyle, Mowen, & Tarrant, 2004), and, relatively more recently, place affection (Halpenny, 2010; Ramkissoon et al., 2013b, 2013a). Place dependence, place identity, place affection and place social bonding reflect the range of feelings individuals associate with specific environments and, as such, warrant further investigation for their application in recreation and tourism research (Kyle, Graefe, & Manning, 2005; Lee & Shen, 2013; Ramkissoon et al., 2013b, 2013a). Recent studies in the hospitality literature have indicated that the concept of place attachment is a useful one in understanding aspects of consumer behavior (Alansari, 2016). It has, for example, been reported that an individual's emotional and functional attachment to a specific recreational place is related to a variety of behavioral outcomes, such as trust and satisfaction levels (Lee, 2015), authenticity (Ram et al., 2016), perceived crowding (Kyle, Bricker, Graefe, & Wickham, 2004) and tourist loyalty (Qiu, 2014). Previous studies have suggested that place attachment is a critical antecedent of behavioral intentions (Halpenny, 2010; Lee & Shen, 2013). People visit particular places on the basis of specific memories, images, associations and emotional attachments to places and meanings (Schama, 1996). Accordingly, viewing a film can create a strong emotional attachment to a place, leading to the intention to share that place (Lee & Shen, 2013; Wong & Lai, 2015). The literature on the interaction of place attachment and technology is limited (Oz, 2014). In Stals' (2012) study in the field of human-technology interaction, he builds the theoretical background on place attachment concepts and studies on how technology influences city experience. In addition, he proposes that design fictions (i.e. fictional devices) can be used to enhance and share user experience by the use of location and context aware devices and prospective new mobile apps. The research itself is a phenomenographic work that is based on interviews and map evaluations, making the research mostly qualitative and subject to interpretation. Farrelly (2013) investigates the nature of the relationship between people and places, how people use the place attachment information, the influences of mobile devices on place attachment and the potential of enhancing place attachment by making use of location-based services. Although dimensions of place attachment have been studied in the hotel industry (Hosany, Prayag, Van Der Veen, Huang, & Deesilatham, 2017; Io, 2018; Tlili & Amara, 2016), little research has been conducted on technology attachment (Roy, Ponnam, & Mandal, 2017). Ismail, Hsan, and Mustapha (2018) and Roy et al. (2017) refer to technology attachment as an emotional attachment to a smart phone application. The work of Roy et al. (2017), introduces the term “smart phone attachment” and describes it as a bond between a person and a smart phone that differs in strength. Several researchers 43

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

“an affective bond or link between people and specific places”. Brown, Smith, and Assaker (2016) identify that place attachment is a multidimensional concept. According to Jiang, Ramkissoon, Mavondo, and Feng (2017), place attachment comprises place dependence, place identity, place affection and place social bonding to reflect the range of feelings an individual holds when connected with a particular setting. Yi, Fu, Jin, and Okumus (2018) conceptualize place dependence as an individual's functional reliance on the toured environment. Moore and Graefe (1994) associate place dependence with the perceived strength of association between a person and a specific place - the degree to which occupants perceive themselves to be dependent on a particular place. Wynween, Kyle, and Sutton (2012) refer to place identity as the cognitive connection depicting the symbolic link between a person and a place. Cheng, Ng, Chan, and Givoni (2012) indicate that place identity emerges through an accumulation of experience with a place. The physical and social attributes at natural attractions may give rise to a strong sense of place identity (Gu & Ryan, 2008) involving not only localized experiences but also specific memories about how others feel about the place (Therkelsen, Halkier, & Jensen, 2010). Jorgensen and Stedman (2001) and Kals and Maes (2002) conceptualize place affection as the emotional bonds individuals share with settings. The affective connection between people and places is well documented. Place affection has been understood as an emotional bond with or affective attachment to a particular setting, which can be treated as a part of place identity or as a separate dimension (Yüksel et al., 2010). Ramkissoon et al's. (2012) reference to place social bonding as an interpersonal relationship which occurs in a place (and is less established in the literature as a subconstruct of place attachment), appears to be largely cognitive. Scannell and Gifford (2010) present that place social bonding reflects the importance of people's experiences derived from social interactions at a particular place. The specific settings of the place share the meanings attributed to them by the individuals' social environment.

purchase trust is increased due to a cumulative effect of ongoing experiential satisfaction. This intimates that satisfaction has a direct influence on trust. However, the relationships between the dimensions of technology attachment and the dimensions of experiential relationship quality are yet to be established in the hotel literature. Riege (2005) suggests that people normally share their knowledge if they trust that the knowledge they share bring benefits for them and for the whole organization. Jin, Lee, and Cheung (2010) argue that satisfaction influences customers' intentions to share their knowledge. Cheung, Lee, and Lee (2013) identify that user satisfaction exhibits an influence on people's intentions to share knowledge in an online community of practice. However, the concept of experiential sharing intentions remains sparse in the hotel industry. Also, none of the hospitality literature focuses on the effect of the dimensions of experiential relationship quality on experiential sharing intentions. Perceived risk is a threat to successful marketing because it causes consumers to focus on the potential loss of resources (Salam, Rao, & Pegels, 2003), and perceptions of uncertainty can negatively impact purchasing behavior (Jin, Line, & Merkebu, 2016). Öhman (2017) proposes that an individual's perceived risk related to his or her personal experiences will vary. However, no studies focus on the concept of experiential risk in the hotel industry. People will be satisfied and their intentions to share will be increased when they find their expectations are fulfilled (Cheung et al., 2013). In general, the predictive strength of satisfaction on sharing intentions decreases when perceived risk increases. Namely, perceived risk has a negative moderating effect on the satisfaction-sharing intention relationship (Cheung et al., 2013). However, no hospitality literature focuses on examining whether experiential risk plays a moderating role in influencing the negative relationship between experiential satisfaction and experiential sharing intentions. However, as mentioned above, very few studies investigate technology and experiential issues in the smart hotel context even though the relevant issues of the dimensions of place attachment and the dimensions of relationship quality have been explored in tourism (e.g. Ramkissoon et al., 2013a, 2013b, 2013c, 2014, 2012; Choi & Cai, 2017; Hopeniene & Rutelione, 2016; Loureiro & Cunha, 2017; Rajaobelina, 2018; Veasna et al., 2013). Based on the aforementioned review, there is still a lack of understanding of the relationships the relationships among the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions in the smart hotel context. Accordingly, this study attempts to examine the relationship between experiential sharing intentions and their relevant constructs: technology dependence, technology identity, technology affection, technology social bonding, experiential trust, experiential satisfaction and experiential risk perceived by smart hotel guests. This study contributes to smart hotel management and marketing literature from an academic and managerial perspective. New insights into the dimensions which guests consider important when assessing technology attachment and experiential relationship quality, and the effect that the dimensions of experiential relationship quality have on important attitudinal and behavioral constructs are provided. Currently, no previous studies on smart hotel guest experiences have used a conceptual research model to synthesize the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions in a path model. Understanding these relationships will equip hospitality marketers and administrators with information they can apply in developing and implementing services marketing strategies, to provide guests with a high quality experience in a smart hotel.

2.2. Technology attachment The concept of technology is interpreted as a dynamic synthesis of guests' experience, which includes the availability and accessibility of tangible technology such as personal computers, software and Internet connections (Van Dijk, 2006), as well as technology-related intangible assets, such as know-how, copyrights on technical materials like computer software, technical manuals and automated databases (Reilly, 2015, pp. 37–50). As technology's presence grows increasingly concrete in global societies, so too do people's relationships with the devices they keep close at hand from day to day (Bodford, Kwan, & Sobota, 2017). According to Suh, Kim, and Suh (2011), technology attachment is generally defined as an emotional bond or connection between individuals and their technology. When people are emotionally attached to their technology, they become more engaged in using the technology and enjoy the interaction with it more (Li, Browne, & Chau, 2006). Increases in engagement and enjoyment while using a technology can result in better performance on tasks involving that technology (BurtonJones & Straub, 2006). Only a few studies have applied the concept of place attachment in a technological context. For example, Farnham et al. (2009) find that the standardized measures of place attachment and psychological sense of community meaningfully predict the likelihood of technology adoption and usage in a café. Virtual worlds can be currently accessed from the comfort of one's home on a personal computer, presenting an alternative world that can be perceived as very real to its users, and changing the traditional ways of recreation and travel. Therefore, it is possible to identify whether it is possible to become attached to a virtual place (Plunkett, 2011). Perlaviciute and Steg (2014) describe that place attachment has been considered to be an important psychological factor to explain people's evaluations and acceptability of energy technologies in their close environment. Shao and Liu (2017) propose a way to assess

2. Related concepts and hypotheses 2.1. Place attachment Hidalgo and Hernandez (2001, p. 274) define place attachment as 44

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

understanding, and subsequently promoting, quality relationships. Many studies consider relationship quality as a meta-construct comprising several distinct and related dimensions, while several empirical studies consider relationship quality as a pure single construct (Dorsch, Swanson, & Kelley, 1998). However, there is no unified definition of relationship quality. Relationship quality has been conceptualized as a construct consisting of several components. In the prior studies, trust and satisfaction are the most examined aspects of relationship quality (e.g. Crosby, Evans, & Cowles, 1990; Gul, 2014; Knutson, Elsworth, & Beck, 2006; Rahmani-Nejad, Firoozbakht, & Taghipoor, 2014). Trust is one of the most widely examined and accepted concepts in relationship marketing (e.g. Verma, Sharma, & Sheth, 2016). Gul (2014) defines trust as a belief of one party that the other party will be fulfilling their needs and wants. Trust is an important mediating factor between customer behavior before and after purchasing a product and/or service which can lead to long-term behavioral intentions and strengthen the relationship between the two parties (Singh & Sirdeshmukh, 2000). Fournier and Mick (1999) define satisfaction as the fulfilment of customers' requirements or needs. Satisfaction is a reflection of being content with such a product and/or a service. It is the assessment of the experience of interacting with a service provider up to the present time, and is used by customers to predict future experience (De Ruyter & Wetzels, 2000).

the place attachment via modern virtual reality technology, in searching for a better way to assess the term, thereby helping practitioners to better identify and protect the elements that contribute to place attachment. According to Pedró (2012), people's emotional attachment to technology is inevitably having an impact on their cognitive development as they process information and communicate in different ways via multiple channels. People become attached to technological fixes because technology provides a cluster of promises: advances in science and technology perfectly generate all desired improvements in ecology and environment, solve energy problems, and bring people a better life in general (Li, 2017). In terms of the existing literature, technology attachment has been widely believed to be multi-dimensional. For example, Kim et al. (2013) identify that self-connection, social connection, brand supportive behavior, self-efficiency and life satisfaction are believed to comprise technology attachment. Li (2014) argues that technology attachment consists of IT confirmation, perceived usefulness, perceived ease of use and IT playfulness. Kim et al. (2015) indicate that customization, control, autonomy, attachment, presence and enjoyment constitute technology attachment. Bock et al. (2016) suggest that usefulness, anxious attachment, addiction and continuous use 24 h/day are dimensions of technology attachment. Trub and Barbot (2016) propose that technology attachment consists of refuge and burden. Roy et al. (2017) find that technology attachment comprises connection and prominence. Hertlein and Twist (2018) identify that technology attachment is made up of avoidance and anxiety. However, none of the studies focus on the concept of technology attachment as a way to extend the scope of place attachment. Accordingly, this study proposes four dimensions of technology attachment: technology dependence, technology identity, technology affection and technology social bonding. First, technology dependence is referred to as the way specific facilities and other functional aspects of a smart hotel satisfy guests' requirements (Yüksel et al., 2010). It is premised on the functional qualities of the smart hotel or how well the smart hotel functionally satisfies guests' needs or goals when compared with alternatives. Second, Jaskiewicz (2015) defines technology identity as a contribution of attributes of a technology to a guest's self-concept. In the case of technology identity, it is expected that technology identity would predict a higher aesthetic appraisal of a smart hotel's technology. Third, Kals and Maes (2002) refer to technology affection as an emotional bond which is developed between a guest and the technology. Technology affection may be used to describe the emotions of a guest towards a particular technology and not considered to be a distinct concept from technology attachment. Fourth, technology social bonding has been conceived as social ties developed through shared experiences of technology (Mesch & Manor, 1998). It focuses on guests' experiences derived from social interactions using technology in a smart hotel (Scannell & Gifford, 2010). Technology social bonding reflects the importance of social relationships and the context within which they occur. The specific settings of the technology share the meanings attributed to them by the guests' social environment (Ramkissoon et al., 2013b). Based on the aforementioned review, the dimensions of technology attachment (technology dependence, technology identity, technology affection and technology social bonding) should attract more attention in the smart hotel context.

2.4. Experiential relationship quality In an experiential relationship, individuals' unique first-hand experiences with an organization could turn into their satisfaction or dissatisfaction with the organization (Golan, 2015; Vibber & Kim, 2015). This is because relationships require time and efforts to maintain, whether individuals feel that the distribution of rewards is equitable and outweighs the cost reflecting the extent to which they feel satisfied (Stafford & Canary, 1991). In general, experiential relationship holders are influenced by the same information as well as their experiences (Grunig & Hung-Baesecke, 2015; Wan & Schell, 2007). According to Tam and Kim (2017), experiential relationship holders have generally reported a more positive relationship quality. Experiential relationship holders could be more active in sharing their first-hand experiences with an organization. Their active sharing of experiences could be contagious, also affecting other individuals' relationship with organizations (Vibber & Kim, 2015). In the hospitality industry, experience positively influences trust (Bowden-Everson, Dagger, & Elliott, 2013) and satisfaction (Ali, Amin, & Cobanoglu, 2016). When customers enjoy a positive experience, they strengthen their relationship with and come to trust an organization (Chen et al., 2016; Jung & Soo, 2012). To understand the relationship quality between guests and smart hotels based on the guests' perspectives, this study proposes a new construct, experiential relationship quality, and refers to Skarmeas, Katsikeas, Spyropoulou, and Salehi-Sangari (2008) and Tam and Kim (2017) and defines it as a guest's higher levels of experiential trust in and experiential satisfaction with a smart hotel using smart technology. Tam and Kim (2017) propose that experiential relationship quality has been considered to be a multi-dimensional construct. In this study, experiential relationship quality is proposed to comprise experiential trust and experiential satisfaction (e.g. Wu & Cheng, 2013, 2017, 2018a, 2018b, 2018c; Wu & Ai, 2016; Wu & Li, 2017). Referring to Wu (2017), this study defines experiential trust as a willingness to depend on a product and/or service based on the belief or expectation resulting from the credibility, benevolence, and ability of the performance of a smart hotel throughout the service experience using smart technology. In general, experiential trust helps customers feel in control even in situations where the quality of service is hard to grasp (Wu, 2017). Wu (2017) identifies that experiential trust has been increasingly playing an important role in the hospitality industry. Anderson, Fornell, and Lehmann (1994) propose that satisfaction is the overall evaluation of the purchased products and/or services based on previous experiences.

2.3. Relationship quality Holmlund and Törnroos (1997, p. 9) define perceived relationship quality as “the joint cognitive evaluation of business interactions by significant individuals in both organizations of the (customer-supplier) dyad. A high-quality relationship suggests that the customer believes in the service provider's future performance because the level of past performance has satisfied the customer's expectation (Wong & Sohal, 2002). Dutton, Deane, and Bullen (2018) identify that assessing relationship quality is critical to gathering the best evidence possible for 45

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

H3. Technology affection positively influences experiential trust.

Mano and Oliver (1993) describe that in the post consumption experience, product-elicited affect is highly correlated with satisfaction. According to several researchers (Kao, Huang, & Wu, 2008; Wu, Cheng, & Hong, 2017; Wu, Li, & Li, 2018d), experiential satisfaction is conceived of on the basis of the concept of service satisfaction, though it extends beyond service satisfaction in that it focuses on customers' overall evaluation of their experiences after consumption. Accordingly, from an experiential perspective, experiential satisfaction reflects the satisfaction experienced from the service content associated with a specific transaction. Customers compare their experiences with their prior expectations, which cause positive or negative disconfirmation. The emotional responses resulting from positive or negative disconfirmation form the basis for consumer satisfaction or dissatisfaction (Bigné, Andreu, & Gnoth, 2005). Therefore, herein the concept of experiential satisfaction is proposed based on an experiential perspective and it is defined as the result of consumers' evaluation of the contents presented by service providers (Kao et al., 2008). Consistent with the developmental theory of place attachment (Morgan, 2010), this study hypothesizes the dimensions of place attachment as antecedents of trust and satisfaction. For example, Manturuk, Lindblad, and Quercia (2017) describe that dimensions of place attachment may generate feelings of trust towards one's neighbors. Lee (2015) proposes that trust is influenced by the dimensions of place attachment. Ramkissoon et al. (2013b) and Stefaniak, Bilewicz, and Lewicka (2017) identify that increased dimensions of place attachment enhance trust. Several studies show that place attachment, conceptualized as place dependence, place identity (Prayag & Ryan, 2012) and place affection (Ramkissoon et al., 2013b; Yüksel et al., 2010) could be significantly predictive of visitors' satisfaction. Several studies (e.g. Budruk & Stanis, 2013; Campón-Cerro, Baptista Alves, & Hernández-Mogollón, 2015; Loureiro, 2014; Tlili & Amara, 2016) find that the dimensions of place attachment are antecedents of overall satisfaction, indicating that the dimensions of place attachment influence satisfaction. Some evidence also suggests that place social bonding may exert an influence on place satisfaction (Ramkissoon et al., 2013b). Chen, Wu, and Huan (2011) and Ramkissoon et al. (2013b) propose that satisfaction is dependent on dimensions of place attachment. Rastbod and Aflatounian (2016) suggest that dimensions of place attachment have a strong effect on place satisfaction of people in cinemas. The place dependence, place identity, place affection, and place social bonding are the dimensions of place attachment which have a positive effect on place satisfaction of visitors in cinemas. Sıvalıoğlu and Berköz (2016) observe that as the overall dimensions of place attachment increase, the overall satisfaction also increases. Several researchers (e.g. Farnham et al., 2009; Perlaviciute & Steg, 2014; Ramkissoon et al., 2013b; Roy et al., 2017; Shao & Liu, 2017) have developed the dimensions of technology attachment by applying the concept of the dimensions of place attachment. Numerous studies (e.g. Crosby et al., 1990; Kim, Lee, & Yoo, 2006; Rafiq, Fulford, & Lu, 2013; RahmaniNejad et al., 2014; Wray, Palmer, & Bejou, 1994) have found that trust and satisfaction are the most examined aspects of relationship quality. Based on the aforementioned review, it is evident that previous studies have focused on the effects of the dimensions of place attachment (place dependence, place identity, place affection, and place social bonding) on the dimensions of relationship quality (trust and satisfaction) (Payton, Fulton, & Anderson, 2005; Rastbod & Aflatounian, 2016; Tlili & Amara, 2016). However, to the best of our knowledge, none of the studies focus on examining technology attachment with its four dimensions (technology dependence, technology identity, technology affection and technology social bonding), and its role in predicting the dimensions of experiential relationship quality (experiential trust and experiential satisfaction) in the smart hotel context. Consequently, the following hypotheses are developed:

H4. Technology social bonding positively influences experiential trust. H5. Technology satisfaction.

dependence

positively

influences

experiential

H6. Technology identity positively influences experiential satisfaction. H7. Technology affection positively influences experiential satisfaction. H8. Technology social bonding positively influences experiential satisfaction. Lin and Ding (2005) present that satisfaction causes long-term stability of relationships and indicates trust. According to Mosavi and Ghaedi (2012), the purchaser's overall satisfaction with the purchasing experience is proposed to have a positive impact on his or her trust of the service provider. Shpëtim (2012) emphasizes that satisfaction significantly influences customers' trust in particular service providers. Evidence outlined by Kennedy, Ferrell, and LeClair (2001) indicates that satisfaction is an antecedent of trust in the service provider (Ha, Janda, & Muthaly, 2010). Several researchers (Delgado-Ballester & Munuera-Aleman, 2001; Shpëtim, 2012; Singh & Sirdeshmukh, 2000) propose that satisfaction positively influences trust; therefore, trust reflects satisfaction levels. Selnes (1998) indicates that satisfaction drives trust, as satisfaction is a manifestation of the other party's ability to meet relational norms. Bansal, Irving, and Taylor (2004) show in their model that when satisfaction is treated as an antecedent of trust, the path coefficient is significant. Accordingly, the following hypothesis is proposed: H9. Experiential satisfaction positively influences experiential trust. 2.5. Experiential sharing intentions Patterson and Spreng (1997) define sharing intentions as ordinary intentions that are interlocked, processing which does not seem to additionally burden neural areas associated with representing mental states. According to Hasanov and Beaumont (2016), sharing intentions are an amalgam of singular intentions that provide a possible means for consensus making and cooperation in a particular context. Accordingly, sharing intentions are the backbone that encloses the processes of social belonging and accomplishment of a deliberate goal. Experiences are the building blocks of people's lives, and are essential to their well-being. Indeed, people spend their significant time and money engaging in experiences, both ordinary and extraordinary (Bhattacharjee & Mogilner, 2013). One reason experiences are so central to well-being is that they are often shared with others, thus contributing to the value and happiness humans derive from their social relationships (Leary & Baumeister, 2000). In general, sharing experiences can happen in two ways. First, people can participate in experiences jointly with others. Experiencing an event with another person (vs. alone) can heighten enjoyment of that experience by facilitating social belonging and connection (Ramanathan & McGill, 2007). Second, people can tell others who were not present about their experiences. Telling others about an experience after it has ended can boost people's positive affect and sense of meaning (Lambert et al., 2013), their satisfaction with the experience (Gilovich, Kumar, & Jampol, 2015), and their feelings of closeness and trust with their audience (Beike, Brandon, & Cole, 2016; Reis et al., 2010). Based on the definitions above, this study proposes a novel notion, experiential sharing intentions, and refers to Kwon, Pen, and Mai (2015) to define it as a guest's desire to share his or her success and failure of experiences to family or friends. Holste and Fields (2010) find that both affect-based trust and cognition-based trust positively relate to willingness to share tacit knowledge and willingness to use tacit knowledge. Trojanowski and Kułak (2017) indicate that trust has an influence on one's intention to use smart technology for purchases. Holste and Fields (2010) identify that

H1. Technology dependence positively influences experiential trust. H2. Technology identity positively influences experiential trust. 46

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Wu, Wei, Tseng, and Cheng (2018e) define experiential risk as the uncertainty that consumers face when they cannot predict all of the consequences associated with their purchasing experiences. However, the experiential risk construct remains scarce in the hospitality industry. When perceived risk exceeds individual tolerance levels, consumers often manage to reduce the negative effect of risk by such methods as obtaining additional information (Martins, Oliveira, & Popovič, 2014), switching to substitutes with low levels of risk (Yüksel & Yüksel, 2007) or careful evaluations of alternatives and product trials (Cho & Lee, 2006). These actions may lead to a decrease in the predictive power of satisfaction on sharing intentions because satisfaction can be susceptible, especially with the presence of the increased attractiveness of alternative suppliers that reduces attitudinal shifts and causes deleterious effects on the strength of satisfaction (Yang, 2017). Sarkar, Au, and Law (2013) point out that at a theoretical level, perceived risk plays a role in moderating the negative relationship between satisfaction and sharing intentions. Tam (2012) and Leppäniemi et al. (2017) identify that perceived risk plays a role in moderating the relationship between satisfaction and sharing intentions in a service context. Cheung et al. (2013) and Currás-Pérez and Sánchez-García (2012) indicate that intentions to share knowledge have been regarded not only as dependent on satisfaction, but also moderated by perceived risk. Cheung et al. (2013) and Tuu, Olsen, and Linh (2011) examine the collective moderating effect of perceived risk on the relationship and find that perceived risk along with taking satisfaction into consideration explained around 50 percent of the variance in sharing intentions. Huy Tuu, Ottar Olsen, and Thi Thuy Linh (2011) and Jin et al. (2010) describe that perceived risk is a barrier in the forming of sharing intentions with a negative moderating effect on the relationship between satisfaction and sharing intentions. Accordingly, the following hypothesis is proposed:

trust is identified as a necessary prerequisite for knowledge sharing. Chen, Hsueh-Liang, and Chin-Chung (2014) find that community trust has an influence on knowledge sharing intention. Cohen and Prusak (2001) and Rutten, Blaas-Franken, and Martin (2016) identify that high levels of trust can cause better knowledge sharing intentions. Andrews and Delahaye (2000) believe that an individual's evaluation of the trustworthiness of another actor, together with that actor's appropriateness and credibility, form psychosocial filters that allow or inhibit an individual's knowledge sharing intentions. Malik, Hiekkanen, Dhir, and Nieminen (2016) identify that trust has an influence on sharing intentions. As a result, this study proposes the following hypothesis: H10. Experiential trust positively influences experiential sharing intentions. Previous studies have shown that satisfaction influences people's intentions to share their knowledge (Cheung & Lee, 2007; Jin et al., 2010). For instance, online community people are more likely to share their knowledge if they have positive levels of satisfaction using the online communities (Cheung & Lee, 2007). Leppäniemi, Karjaluoto, and Saarijärvi (2017) find that satisfaction is a significant determinant of customers' willingness to share information with an organization. Cheung et al. (2013) argue that satisfaction affects people's intentions to share knowledge in an online community of practice. Park (2005) indicates that satisfaction is widely applied to measure the success of information technologies. When an individual is satisfied with the content or functions of a technology used for sharing information, he or she is likely to have a positive attitude and continued intentions to share information via the technology (He & Wei, 2009). According to studies of virtual communities (Park & Chung, 2011), satisfaction is emphasized as a variable influencing intentions, flow experience and loyalty. Thus, the following hypothesis is proposed: H11. Experiential satisfaction positively influences experiential sharing intentions.

H12. Experiential risk has a negative moderating effect on the relationship between experiential satisfaction and experiential sharing intentions.

2.6. Experiential risk 2.7. Conceptual model Milan, Bebber, and Eberle (2015) define perceived risk as the probability of the customer suffering from some kind of financial lost caused by additional costs, future costs with the maintenance of the product and/or the lack of guarantee or replacement in the case of problems with the product. Jin et al. (2016) identify that perceived risk is a threat to successful marketing because it causes consumers to focus on the potential loss of resources, and perceptions of uncertainty can negatively influence purchasing behavior. From a constructionist viewpoint, risk is socially constructed and is interpreted differently across different social structures and cultures (Douglas & Wildavsky, 1982); the experience or perception of risk can be contested, incorporated, and transformed (Williams & Baláž, 2013). In contrast, from a post-modernistic perspective, the existence of threat stimuli is insignificant as the experience or perception of risk continues even when the component of threat has been withdrawn. It is the aftermath of experience that significantly shapes, transforms, and influences how consumers perceive risk (Yang & Nair, 2014). Ruan, Li, and Liu (2017) propose that perceived risk is considered to be manifested in people's tendency to consider their actual experience, thus helping organizations and destinations evaluate the impacts of crises or disasters. Chang (2008) and Hamilton-Webb, Manning, Naylor, and Conway (2017) indicate that experience is important for motivating people to take adaptive action against risks of booking a hotel through influencing risk perception. Epstein, Pacini, Denes-Raj, and Heier (1996) conceptualize experiential risk as neither rule-based, logical assessments nor fully fledged affective responses; it is an output of experiential processing that is holistic, based on learned associations, slow to change, relatively crudely differentiated and integrated, and involving concrete images, metaphors, and narratives. Alternatively, Wu and Cheng (2018d) and

Ramkissoon, Weiler, and Smith (2013c) describe that the dimensions of place attachment (place dependence, place identity, place affection and place social bonding) are antecedents of place satisfaction. Payton et al. (2005) find that increasing the dimensions of place attachment directly increases trust. Chinomona and Dubihlela (2014) present that satisfaction is a key antecedent of trust. Arokiasamy (2013) proposes that satisfied customers are more likely to share their fortunate experiences with a particular organization with other people. Malik et al. (2016) present that trust levels relate to users’ photo sharing intentions on Facebook. Cheung et al. (2013) and Currás-Pérez and Sánchez-García (2012) argue that sharing intentions have been considered not only to be dependent on satisfaction, but also moderated by perceived risk. Such a sequence informed the theoretical model of this study. Fig. 1 shows the model and hypothesized relationships. 3. Research methodology 3.1. Questionnaire and pre-test This study adapted the measurement items from previous studies and all scales included multiple items. Three questions from the study of Ramkissoon et al. (2013c) measure technology dependence. Based on the studies of Ramkissoon et al. (2013c) and Yi et al. (2018), three items were developed to assess technology identity. Three measures based on the study of Ramkissoon et al. (2013c) were devised to assess technology affection and, based on the studies of Ramkissoon et al. (2013c) and Zhang, van Dijk, Tang, and Berg (2015), four items were designed to measure technology social bonding. Three questions were used to 47

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Moderating effect Fig. 1. Proposed model.

measurement items for each factor. It represents an important step in scale development. Second, confirmatory factor analysis (CFA) with maximum likelihood estimation was conducted to validate the measurement scales of the constructs (Hair, Black, Babin, & Anderson, 2010). The reliability and validity measures were tested. Next, structural equation modeling (SEM) (LISREL 8.7) and hierarchical regression analysis (HRA) (SPSS 21.0) were performed to test the proposed model and hypotheses. The maximum likelihood procedure was used to estimate both the measurement and structural models. Commonly used model fit indices were examined for model fit.

measure experiential trust based on Wu (2017). Four questions based on Wu and Li (2017) were used to measure experiential satisfaction. Based on Ferrer, Klein, Persoskie, Avishai-Yitshak, and Sheeran (2016) and Wu and Cheng (2018d), six questions were used to measure experiential risk. Seven questions were developed to assess experiential sharing intentions based on Jolaee, Md Nor, Khani, and Yusoff (2014) and Kwon, Peng, and Mai (2015). All construct items were measured using seven-point Likert-type scales anchored by “strongly disagree” (1) and “strongly agree” (7). The content-based validity of the instrument was initially established by sending it to 12 experts, including five hotel managers and eight assistant and associate professors from the USA, all of whom specialized in hospitality marketing. To ensure clarity, a pilot study was conducted where questionnaires were distributed to 40 people who had stayed in the smart hotels to seek feedback on the design. Based on this feedback, several minor changes were made in order to tailor the questionnaire to the target audience.

3.3. Sample design and data collection Empirical data were collected from the LINQ Hotel & Casino in Las Vegas. The hotel rooms control in this surveyed hotel is provided through the smart technology, which is the WeChat app partnered up with Caesars Entertainment. Guests are able to use an app inside WeChat to control lighting, thermostats and curtains. When guests first arrive in the hotel room, they are required to download the latest version of the Wechat app. Once they reach their rooms, they will be prompted to scan a room-specific QR code that will direct them to follow the specific room they are in on Wechat. This effectively turns their smartphone into a remote, using WeChat as a platform to give hotel guests control of all the room's functions. It also goes a step further to allow guests to customize how they want to interact with the room (Hwei, 2015). Owing to limited time and manpower, data were collected using convenience sampling of guests during check out, aged over 18 years, who experienced the relevant in-room services using the WeChat app on the smartphone between October 15 and December 15, 2017. The surveyors were trained to approach respondents, informing them about the purpose of the survey in advance before they were given the questionnaire. After the respondents agreed that they were willing

3.2. Data analysis The SPSS 21.0 and LISREL 8.7 statistical programs were utilized for data analysis. A two-step approach was used to validate the scales and examine the dynamic relationships among the constructs of the study. First, exploratory factor analysis (EFA) with varimax rotation was employed to purify the items. EFA was conducted as the first step, since the dimensions of technology attachment and the dimensions of experiential relationship quality are still new and under-researched areas (Bodford et al., 2017; Brown et al., 2016). Although most of the measurement items were adapted from previous studies, the reliability, validity and applicability of these items in the smart hotel context remain unknown. In line with Devellis (2012), EFA is used to extract the right number of latent variables and identify the underlying 48

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

enough. The BTS was also significant at low significance level (0.000). To extract the factors, Principal axis factoring method was used by applying the constraint of higher than one eigenvalue for each factor (Malhotra & Birks, 2007). Moreover, only variables with loadings of at least 0.50 were included in the analysis. After EFA was conducted, a total of 29 items loaded properly on the factors. One item (i.e. to associate special people in my life using the smart technology provided by this smart hotel) from technology social bonding, one item (i.e. a really nice day to stay in the smart hotel) from experiential satisfaction and two items (i.e. to share accommodation experiences that might be useful to others and to always share positive things about accommodation experiences with other people) from experiential sharing intentions were removed from this study respectively since they did not load on any of the factors and their factor loading values were under 0.50. Therefore, the final factors including technology dependence, technology identity, technology affection, technology social bonding, experiential satisfaction, experiential trust, experiential risk and experiential sharing intentions consisted of three, three, three, three, three, three, six and five items, respectively. The total variance explained is thus 63.85%, which is above the suggested threshold of 60% (Hinkin, 2005). Cronbach's alpha (α) was used to analyze the reliability of the instruments. Reliability over 0.80 is good; reliability in the range of 0.70 is acceptable; and reliability less than 0.60 is considered poor (Hair et al., 2010). The Cronbach's coefficient α estimates for the eight variables were greater than the 0.70 considered acceptable. The EFA results satisfied the requirement for the reliability coefficient of the measurement scales, revealing high internal consistency (Hair et al., 2010).

Table 1 Demographic profile of sample (N = 525). Demographic characteristics

Options

Frequency

Percentage

Gender

Male Female Single Married 18–27 28–37 38–47 48–57 58 or above Secondary school or below High school Vocational/technical school College or university Graduate school or above Management/administrative staff White collar Professional Salesperson Service staff Housewife Student Self-employed Unemployed Retired Other < 25,000 25,000–39,999 40,000–54,999 55,000–69,999 70,000–84,99 9 85,000–99,999 100,000–149,999 ≥150,000

283 242 295 230 152 163 83 75 52 56 78 94 215 82 113

53.90 46.10 56.19 43.81 28.95 31.05 15.81 14.29 9.90 10.67 14.86 17.90 40.95 15.62 21.52

78 66 54 91 52 21 27 9 6 8 27 43 82 64 78 85 97 49

14.86 12.57 10.29 17.33 9.90 4.00 5.14 1.71 1.14 1.52 5.14 8.19 15.62 12.19 14.86 16.19 18.48 9.33

Marital status Age

Educational level

Occupation

Annual income (US$)

4.3. Convergent and discriminant validity of the measures A variance inflation factor (VIF) value greater than 10 is usually considered problematic (Hair et al., 2010). In this study, the VIF values for all eight variables of this study ranged between 1.12 and 3.74. Accordingly, the data can be assumed to be free of the problem of multicollinearity. Using LISREL 8.7., CFA was conducted to examine the sample validity. Table 2 indicates the CFA results. The composite reliability (CR) and average variance extracted (AVE) were calculated manually to measure construct reliability and convergent validity. According to Hair et al. (2010), the acceptable value of CR is 0.70 and above. Therefore, all of the eight constructs had good reliability. For assessing construct validity, each construct was considered to possess convergent validity if a construct had 0.50 or greater values of AVE (Fornell & Larcker, 1981). The measure indicated convergent validity because the values of AVE were greater than the common target of 0.50, ranging from 0.59 to 0.65 for all constructs (Fornell & Larcker, 1981; Hair et al., 2010). In addition, the measure was considered to display discriminant validity because the values of AVE for each construct were greater than the squared correlations (see Table 3; Lichtenstein, Netemeyer, & Burton, 1990). According to the CFA results, the constructs examined in this study were acceptable in terms of convergent and discriminant validity, and could be conducted using SEM for further path analysis.

to respond to the questionnaire, they were given the questionnaires to fill in. The questionnaire was self-completed by the guests, with assistance available if required. The respondents were required to complete and return the questionnaire to the surveyors on the spot. To ensure confidentiality, the names of study participants were not required and the surveyors ensured that all survey respondents' responses would remain completely confidential and anonymous. In total, 560 completed questionnaires were received, of which 525 were usable. Thirtyfive questionnaires were discarded due to excessive missing data. 4. Results 4.1. Sample profile Table 1 provides the demographic profile of the respondents who participated in this study. Most respondents were male (53.90%), single (56.19%), and aged between 28 and 37 years (31.05%). The majority of respondents held a college or university degree (40.95%), and worked for management and/or administration (21.52%). The respondents’ average annual income mainly ranged between US$100,000 and US $149,999 (18.48%).

4.4. Results of the measurement model test The overall fit of the measurement models was found to be adequate (see Table 4). The Chi-square/df ratios (2.52) were lower than the suggested threshold (e.g. less than 3.0; Carmines & Mclver, 1981). The root mean square error of approximation (RMSEA) value (0.04) was lower than 0.08, indicating adequate fit (Hari et al., 2010). Moreover, all other indices (e.g. CFI, GFI, IFI and NFI estimates) were greater than the recommended threshold of 0.90 (Hair et al., 2010). Moreover, the AGFI estimate was above the recommended threshold of 0.80 (Joreskog & Sorbom, 1989).

4.2. EFA EFA was applied to the captured responses corresponding to attributes. Before establishing the factor structure, initially the correlation matrix was checked to find its suitability for factor analysis. The sample size adequacy for factor analysis was determined by The Kasier-MeyerOlkin Measure of Sampling Adequacy (KMO) value, which was found to be more than 0.91 (Kaiser, 1974). Also, the test statistic for Bartlett's Test of Sphericity (BTS) (Bartlett, 1954) value was found to be big 49

TD1. For the activities I enjoy the most, the setting and environments of the smart technology provided by this smart hotel are the best. TD2. For what I like to do, I could not imagine anything better than the settings and facilities of the smart technology provided by this smart hotel. TD3. I enjoy staying in this smart hotel and its environment using smart technology more than any other hotels. TI1. I feel that the smart technology provided by this smart hotel is a part of me. TI2. I identify strongly with the smart technology provided by this smart hotel. TI3. Using the smart technology provided by this smart hotel says a lot about who I am. TA1. I am very attached to the smart technology provided by this smart hotel. TA2. I feel a strong sense of belonging to this smart hotel and its settings/facilities of the smart technology. TA3. Enjoying everything using the smart technology provided by this smart hotel means a lot to me. TSB1. Many of my friends/family prefer to use the smart technology provided by this smart hotel over many other hotels. TSB2. The time spent on the smart technology provided by this smart hotel allows me to bond with my friends/family. TSB3. My friends/family would be disappointed if I were to start using other settings and facilities of the smart technology provided by other hotels. ET1. This smart hotel really takes care of my needs as a customer. ET2. I am sure that the technology device provided by this smart hotel would do everything to satisfy my demands. ET3. I have great confidence in the smart technology provided by this smart hotel. ES1. Staying in this smart hotel goes beyond my expectations. ES2. I really like this trip to this smart hotel. ES3. It is worthwhile to stay in this smart hotel. ER1. I am concerned about development of the smart technology provided by this smart hotel. ER2. I am very happy to get the smart device provided by this smart hotel. ER3. I am very confident that I will get the smart device provided by this smart hotel. ER4. My first reaction when I hear of someone getting the smart technology in the hotel is “that could be me someday.” ER5. I would be lying if I said “there is no chance of me getting the smart device provided by this smart hotel.” ER6. It is easy for me to imagine myself getting the smart device provided by the smart hotel in the future. ESI1. I intend to keep sharing my accommodation experiences. ESI2. I plan to share my accommodation experiences with other people. ESI3. I will share my accommodation experiences with other people in the near future. ESI4. All things considered, I will share my accommodation experiences in the near future. ESI5. I would strongly recommend my accommodation experiences to other people.

Technology dependence (α = 0.80)

50

a. Items with factor loadings of less than 0.50 were deleted based on measurement scale refinement procedure. Note: * p<0.001.

Experiential sharing intentions (α = 0.83)

Experiential risk (α = 0.86)

Experiential satisfaction (α = 0.82

Experiential trust (α = 0.80)

Technology social bonding (α = 0.81)

Technology affection (α = 0.77)

Technology identity (α = 0.76)

Items

Factor (Cronbach's alpha)

Table 2 Measurement model and confirmatory factor analysis.

0.80* 0.79* 0.80* 0.82* 0.78* 0.81* 0.80* 0.78* 0.76* 0.73* 0.77* 0.78* 0.84* 0.80* 0.79* 0.75* 0.81*

0.64

0.59

0.65

0.63

0.65

0.62

0.90

0.90

0.85

0.84

0.85

0.83

0.81

3.48 3.56 3.37 3.49 3.56 3.34 2.39 2.50 2.57 3.58 3.68 3.34 3.38 3.36 3.37 3.38 3.53

3.53 3.65 3.44 3.25 3.50 3.48 3.40 3.36 3.22 3.51 0.59

3.41

Mean

0.79* 0.77* 0.75* 0.79* 0.79* 0.78* 0.80* 0.80* 0.80* 0.82*

0.84

CR

3.39

0.64

AVE

0.78*

0.83*

Standardized factor loadings

0.88 0.78 0.74 0.77 0.79 0.82 0.66 0.70 0.73 0.87 0.77 0.86 0.86 0.91 0.87 0.77 0.83

0.74 0.82 0.79 0.77 0.75 0.78 0.76 0.76 0.78 0.77

0.78

0.70

SD

H.-C. Wu, C.-C. Cheng

Journal of Hospitality and Tourism Management 37 (2018) 42–58

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Table 3 Descriptive statistics and correlation of study variables. Variables

M

SD

1

2

3

4

5

6

7

8

1. 2. 3. 4. 5. 6. 7. 8.

3.44 3.46 3.46 3.35 3.47 3.46 2.51 3.41

0.52 0.53 0.60 0.58 0.57 0.57 0.55 0.49

1.00 0.09 0.27 0.21 0.26 0.23 −0.24 0.41

1.00 0.40 0.29 0.55 0.62 −0.30 0.38

1.00 0.55 0.24 0.51 −0.36 0.37

1.00 0.22 0.45 −0.22 0.42

1.00 0.50 −0.46 0.43

1.00 −0.44 0.74

1.00 −0.51

1.00

Technology dependence Technology identity Technology affection Technology social bonding Experiential trust Experiential satisfaction Experiential risk Experiential sharing intentions

Note: Squared correlations of paired constructs are on the off-diagonal.

experiential risk) significantly correlates with experiential sharing intentions (β = −0.08, p < 0.05), therefore hypothesis 12 is supported. This result demonstrates that the inclusion of experiential risk has decreased the effect of experiential satisfaction on experiential sharing intentions. This indicates that experiential risk acts as a moderating variable in such relationships.

4.5. Results of structural equation analyses The results of the structural model test are presented in Table 4 and reveal an adequate fit to the data (RMSEA = 0.04, SRMR = 0.03, CFI = 0.98, GFI = 0.93, IFI = 0.97, NFI = 0.98, AGFI = 0.90). The chisquare (x2/df) ratio of 2.48 was lower than the suggested criterion (x2/ df < 3).

5. Discussion 4.6. Research hypothesis test The literature is not conclusive on how experiential sharing intentions can be developed and sustained in an integrated framework in the smart hotel context. Accordingly, this study provides an approach of the dimensions of experiential relationship quality to activate the building process of experiential sharing intentions in the context of smart hotel management. This study develops a research framework of experiential sharing intentions to further discuss their relationships with the dimensions of technology attachment, the dimensions of experiential relationship quality and experiential risk. The model was tested using the data from guests who stayed in the LINQ Hotel & Casino of Las Vegas. The related literature was reviewed to generate a theoretical model of the factors above. The purpose of this study is to examine the relationships among the dimensions of technology attachment (technology dependence, technology identity, technology affection and technology social bonding), the dimensions of experiential relationship quality (experiential trust and experiential satisfaction), experiential risk and experiential sharing intentions. First, the statistical results show that the dimensions of technology attachment, i.e. technology identity, technology affection and technology social bonding, have a positive effect on experiential trust. These findings are consistent with the propositions of Kang, Manthiou, Sumarjan, and Tang (2017), Payton et al. (2005) and Roy et al. (2017) that customers who are securely attached to the use of smart phone applications experience higher levels of trust. Accordingly, the dimensions related to technology attachment play a critical role in influencing perceptions of trust (Roy et al., 2017). However, the statistical result reveals that the positive effect of technology dependence on experiential trust is insignificant. There are two reasons for this discrepancy. First, there are competing influences in technology dependence on the same experiential trust. Second, even though the majority of guests enjoy staying in the smart hotel and its environment using smart technology more than any other hotels, they feel staying in the smart hotel cannot go beyond their expectation. Second, the study

To test the hypotheses in the conceptual research model using SEM and HRA, the results are given in Tables 5 and 6. In addition, the results of the full model in this study are shown in Fig. 2. Hypotheses 1, 2, 3, 4 and 9 propose that technology dependence, technology identity, technology affection, technology social bonding and experiential satisfaction positively influence experiential trust. The hypotheses are partially supported. The results indicate that technology identity (β = 0.37, p < 0.001), technology affection (β = 0.19, p < 0.01), technology social bonding (β = 0.16, p < 0.05) and experiential satisfaction (β = 0.31, p < 0.001) have a positive influence on experiential trust. However, the effect of technology dependence (β = 0.05, p = n.s.) on experiential trust is not supported. These five variables explain 63.50% of the variance in experiential trust. Hypotheses 5, 6, 7 and 8 predict that technology dependence, technology identity, technology affection and technology social bonding positively influence experiential satisfaction. The hypotheses are partially supported, indicating the effects of technology dependence (β = 0.19, p < 0.01), technology identity (β = 0.33, p < 0.001) and technology affection (β = 0.31, p < 0.001). However, the effect of technology social bonding (β = 0.09, p = n.s.) on experiential satisfaction is not supported. These four variables explain 52.80% of the variance in experiential satisfaction. Hypotheses 10 and 11 postulate that experiential trust and experiential satisfaction positively influence experiential sharing intentions. The results fully support the hypotheses, revealing that experiential trust (β = 0.44, p < 0.001) and experiential satisfaction (β = 0.61, p < 0.001) have a positive influence on experiential sharing intentions. Both of the variables explain 36.41% of the variance in experiential sharing intentions. Hypothesis 12 assumes that experiential risk moderates the negative relationship between experiential satisfaction and experiential sharing intentions. The interacting variable (experiential satisfaction x Table 4 Results of the measurement and structural model tests. Model

x2/df

P

RMSEA

SRMR

CFI

GFI

IFI

NFI

AGFI

Measurement model Structural model - Overall model Recommended value

2.52 2.48 < 3.00

0.00 0.00 –

0.040 0.037 < 0.08

0.031 0.030 ≤ 0.08

0.98 0.98 > 0.90

0.94 0.93 > 0.90

0.97 0.97 > 0.90

0.98 0.98 > 0.90

0.89 0.90 ≥ 0.80

Notes: P = P-value, RMSEA = Root Mean Square Error of Approximation, SRMR = Standardized Root Mean Residual, CFI = Comparative Fit Index, GFI = Goodness-of-fit Index, IFI = Incremental Fit Index, NFI = Normed Fit Index, AGFI = Adjusted Goodness-of-fit Index. 51

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Table 5 Hypothesis test results.

H1: H2: H3: H4: H5: H6: H7: H8: H9: H10: H11:

Hypothesized path

Standardized estimate

t-value

Hypothesis supported

Technology dependence → Experiential trust Technology identity → Experiential trust Technology affection → Experiential trust Technology social bonding →Experiential trust Technology dependence → Experiential satisfaction Technology identity → Experiential satisfaction Technology affection → Experiential satisfaction Technology social bonding → Experiential satisfaction Experiential satisfaction → Experiential trust Experiential trust → Experiential sharing intentions Experiential satisfaction → Experiential sharing intentions

0.05 0.37*** 0.19** 0.16* 0.19** 0.33*** 0.31*** 0.09 0.31*** 0.44*** 0.61***

0.82 9.35 2.99 2.46 2.96 8.49 8.14 1.55 7.60 11.03 16.21

No Yes Yes Yes Yes Yes Yes No Yes Yes Yes

Notes: * p<0.05; ** p<0.01; *** p<0.001.

contentions of several studies (Cheung et al., 2013; Currás-Pérez & Sánchez-García, 2012) that perceptions of risk weaken the relationship between overall satisfaction and intentions to share their accommodation experiences. Accordingly, hotels that attempt to improve their market share by discounting price might run the serious risk of having a negative impact on satisfaction and sharing intentions (Carev, 2008).

Table 6 Results of a hierarchical regression analysis for hypothesis 12. Experiential sharing intentions Independent variable

Model 1

Experiential satisfactiona Experiential riskb Experiential satisfaction x Experiential risk Intercepts R-Square F-value

0.46 *** −0.22 *** −0.08* 1.68 0.317 121.411

6. Implications 6.1. Implications for academic research This study contributes to the smart hotel literature because it is the first empirical study to explore the relationships among the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions. First, the statistical results show that technology identity, technology affection and technology social bonding play important roles in increasing perceptions of confidence in the smart technology provided by the smart hotel. Second, the empirical results reveal that technology dependence, technology identity and technology affection play critical roles in influencing perceptions of experiential satisfaction towards smart hotels. Third, the study finding reveals that experiential satisfaction has a positive influence on experiential trust. The positive relationship identified between experiential satisfaction and experiential trust may be interpreted as the higher the experiential satisfaction as perceived by smart hotel guests, the higher the confidence guests have in the smart technology provided by the smart hotel. Accordingly, high levels of experiential trust result from high levels of perceptions of experiential satisfaction with the adoption of technology in the hotel industry (Luse, 2018; Wu, 2017; Wu, Ai, & Cheng, 2016). Fourth, the study finding shows that the moderating role of experiential risk on the negative relationship between experiential satisfaction and experiential sharing intentions is significant. This result may be attributed to the view that experiential risk together with experiential satisfaction may completely moderate the negative effect of perceptions on experiential sharing intentions in the smart hotel context. Finally, the statistical result reveals that experiential trust and experiential satisfaction positively influence experiential sharing intentions. Experiential trust and experiential satisfaction are important drivers of experiential sharing intentions. Therefore, as suggested in this study, experiential trust and experiential satisfaction should be included when assessing experiential sharing intentions in the smart hotel context. The analysis of the relationships between the proposed hypotheses enhances the establishment of generalizations across the relevant streams of research and includes existing gaps in the smart hotel literature.

Note. * p<0.05, ** p<0.01, *** p<0.001. a Independent variable. b Moderating variable.

finding indicates that experiential satisfaction has a positive effect on experiential trust. This result agrees with the contentions of Goh, Jiang, and Tee (2016) and Lee, Barker, and Kandampully (2003) that satisfaction has a strong influence on trust in the adoption of technology in the hotel industry. Third, the statistical results reveal that technology dependence, technology identity and technology affection have a positive influence on experiential satisfaction. These findings concur with the propositions of several studies (Io, 2018; Prayag & Ryan, 2012; Rasli, Danjuma, Yew, & Igbal, 2011) that in determining attachment dimensions in technology-based hotels, satisfaction will suffice. In addition, these results suggest that the magnitude of the relationships between the different dimensions of technology attachment and experiential satisfaction differs. However, the statistical result shows that technology social bonding has an insignificant and positive influence on experiential satisfaction. There are two reasons for this discrepancy. First, technology social bonding is a necessary but not sufficient condition for forming experiential satisfaction. Second, the time spent on the smart technology provided by the smart hotel may not allow guests to bond with their friends/family even though they really like to stay in the smart hotel. Fourth, the empirical result shows that experiential trust and experiential satisfaction positively influence experiential sharing intentions. This finding is consistent with the contention of Mittendorf (2017) that how trust in renters and perceived risk of renters influence the providers’ intentions to share a particular type of accommodation – single room vs. entire apartment. Understanding the drivers of the sharing intentions is key – not only for accommodation providers, but also for researchers investigating services in the sharing economy. Also, this result concurs with the contention of Zemke, Chen, Raab, and Zhong (2017) that a pleasant physical environment should lead to satisfied guests, who might revisit the property in the future and share positive evaluations of the property with other people. Finally, the statistical result shows that experiential risk moderates the negative relationship between experiential satisfaction and experiential sharing intentions. This finding agrees with the

6.2. Practical implications The practical implications of this study can be summarized into four areas. First, the study findings provide smart hotel management with an 52

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Fig. 2. The structural model.

guests’ friends/family prefer the smart hotel over many other kinds of hotels. Second, the empirical finding shows that experiential satisfaction has a positive effect on experiential trust. Smart hotel management should realize that experiential satisfaction is considered as an important determinant of experiential trust. To enable guests to stay loyal to the smart hotel, smart hotel management should make them feel satisfied based on their experience with the smart hotel. Third, experiential trust and experiential satisfaction positively influence experiential sharing intentions. Smart hotel management should put more effort into ensuring that guests have great confidence in smart technology and their stay in the smart hotel goes beyond their expectations so that they are happy to share their accommodation experiences with other people. Fourth, the study result indicates that experiential risk moderates the negative relationship between experiential satisfaction and experiential sharing intentions. This result indicates that guests may believe that their perceptions of experiential sharing intentions will be high when the smart hotel provides them with high levels of perceptions of experiential satisfaction. In addition, if experiential risk perceived by guests is high, this may contribute to low perceptions of experiential satisfaction, which in turn lead to low levels of perceptions of experiential sharing intentions. Experiential sharing intentions may not only depend on experiential satisfaction, but also on experiential risk, if guests believe that experiential risk is being decreased. Accordingly, this result can be attributed to one fact that guests will strongly recommend their accommodation experiences to other people after they are satisfied with their smart technology provided by easily imagining

improved understanding of the relationships between the dimensions of technology attachment and the dimensions of experiential relationship quality. The study results reveal that technology identity, technology affection and experiential satisfaction have a positive effect on experiential trust. To increase perceptions of experiential trust, smart hotel management should enable guests to identify strongly with the smart technology, feel a strong sense of belonging to the smart hotel and its settings/facilities of the smart technology, and like their trips to the smart hotel. Also, the study finding indicates that technology social bonding has a positive effect on experiential trust. To take care of the guests' needs, smart hotel management should allow guests to bond with their friends/family based on their time spent on the smart technology provided by the smart hotel. Moreover, the study findings show that technology dependence, technology identity and technology affection positively influence experiential satisfaction. Smart hotel management should invest more resources in the increase of technology dependence, technology identity and technology affection which is useful to enable guests to feel that their stay in the smart hotel is satisfactory. However, the study result shows that the positive effect of technology dependence on experiential trust is insignificant. To enable guests to trust smart technology provided by the smart hotel, smart hotel management should allocate more resources to make them enjoy staying in the smart hotel and its environment using smart technology more than any other hotels. In addition, the study result shows that the positive effect of technology social bonding on experiential satisfaction is insignificant. To increase perceptions of experiential satisfaction, smart hotel management should adopt measures (e.g. increase the setting and environments of the smart technology) to make many of 53

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

themselves getting the smart device provided by the smart hotel in the future.

Bodford, J. E., Kwan, V. S., & Sobota, D. S. (2017). Fatal attractions: Attachment to smartphones predicts anthropomorphic beliefs and dangerous behaviors. Cyberpsychology, Behavior, and Social Networking, 20(5), 320–326. Bowden-Everson, J. L. H., Dagger, T. S., & Elliott, G. (2013). Engaging customers for loyalty in the restaurant industry: The role of satisfaction, trust, and delight. Journal of Foodservice Business Research, 16(1), 52–75. Bowlby, J. (1982). Attachment and loss: Retrospect and prospect. American Journal of Orthopsychiatry, 52(4), 664–678. Brown, B. B., Altman, I., & Werner, C. M. (2012). Place attachment. In S. J. Smith (Ed.). International encyclopedia of housing and home (pp. 183–188). San Diego, CA: Elsevier. Brown, G., Smith, A., & Assaker, G. (2016). Revisiting the host city: An empirical examination of sport involvement, place attachment, event satisfaction and spectator intentions at the London Olympics. Tourism Management, 55, 160–172. Budruk, M., & Stanis, S. A. W. (2013). Place attachment and recreation experience preference: A further exploration of the relationship. Journal of Outdoor Recreation and Tourism, 1(2), 51–61. Burton-Jones, A., & Straub, D. W., Jr. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246. Campón-Cerro, A. M., Baptista Alves, H. M., & Hernández-Mogollón, J. M. (2015). Attachment as a factor in generating satisfaction with, and loyalty to, rural tourism destinations. Tourism & Management Studies, 11(1), 70–76. Carev, D. (2008). Guest satisfaction and guest loyalty study for hotel industryUnpublished master’s thesis. Rochester, NY: Rochester Institute of Technology. Carmines, E. G., & Mclver, J. P. (1981). Analyzing models with observable variables. In G. W. Bohrnstedt, & E. F. Borgatta (Eds.). Social measurement: Current issues (pp. 65– 115). Beverly Hills, CA: Sage. Chang, H. S. (2008). Increase hotel customer value by reducing relevant perceived risk in Taiwan. Journal of Hospitality Marketing & Management, 16(4), 324–342. Chen, N., Dwyer, L., & Firth, T. (2014a). Effect of dimensions of place attachment on residents' word-of-mouth behavior. Tourism Geographies, 16(5), 826–843. Cheng, V., Ng, E., Chan, C., & Givoni, B. (2012). Outdoor thermal comfort study in a subtropical climate: A longitudinal study based in Hong Kong. International Journal of Biometeorology, 56(1), 43–56. Chen, H. L., Hsueh-Liang, F., & Chin-Chung, T. (2014b). The role of community trust and altruism in knowledge sharing: An investigation of a virtual community of teacher professionals. Journal of Educational Technology & Society, 17(3), 168–179. Chen, C. C., Petrick, J. F., & Shahvali, M. (2016). Tourism experiences as a stress reliever: Examining the effects of tourism recovery experiences on life satisfaction. Journal of Travel Research, 55(2), 150–160. Chen, W. X., Wu, W. C., & Huan, T. C. (2011). Safari tourism: A case study of tourist loyalty. In S. F. Chen (Vol. Ed.), Advances in hospitality and leisure: Vol. 7, (pp. 49–70). Bingley, UK: Emerald. Cheung, C. M. K., & Lee, M. K. O. (2007). Understanding user intention to continue sharing knowledge in virtual communities. Paper presented at Proceedings of the fifteenth European conference on information systems (ECIS), st. Gallen, Switzerland. Cheung, C. M. K., Lee, M. K. O., & Lee, Z. W. (2013). Understanding the continuance intention of knowledge sharing in online communities of practice through the post – knowledge - sharing evaluation processes. Journal of the Association for Information Science and Technology, 64(7), 1357–1374. Chinomona, R., & Dubihlela, D. (2014). Does customer satisfaction lead to customer trust, loyalty and repurchase intention of local store brands? The case of Gauteng Province of South Africa. Mediterranean Journal of Social Sciences, 5(9), 23–32. Choi, S. H., & Cai, L. A. (2017). The role of relationship quality in integrated destination marketing. Journal of Travel & Tourism Marketing, 35(5), 541–552. Cho, J., & Lee, J. (2006). An integrated model of risk and risk-reducing strategies. Journal of Business Research, 59(1), 112–120. Cohen, D., & Prusak, L. (2001). In good company: How social capital makes organizations work. Boston, MA: Harvard Business School Press. Crosby, L. A., Evans, K. R., & Cowles, D. (1990). Relationship quality in services selling: An interpersonal influence perspective. Journal of Marketing, 54(3), 68–81. Currás-Pérez, R., & Sánchez-García, I. (2012). Satisfaction and loyalty to a website: The moderating effect of perceived risk. EsicMarket Economic and Business Journal, 141, 183–207. De Ruyter, K., & Wetzels, M. G. (2000). The impact of perceived listening behavior in voice-to-voice service encounters. Journal of Service Research, 2(3), 276–284. Delgado-Ballester, E., & Luis Munuera-Alemán, J. (2001). Brand trust in the context of consumer loyalty. European Journal of Marketing, 35(11/12), 1238–1258. Devellis, R. F. (2012). Scale development: Theory and applications (3rd ed.). Thousand Oaks, CA: Sage. Dorsch, M. J., Swanson, S. R., & Kelley, S. W. (1998). The role of relationship quality in the stratification of vendors as perceived by customers. Journal of the Academy of Marketing Science, 26(2), 128–142. Douglas, M., & Wildavsky, A. (1982). Risk and culture: An essay on the selection of technological and environmental dangers. Berkeley, CA: University of California Press. Dutton, H., Deane, K. L., & Bullen, P. (2018). Distal and experiential perspectives of relationship quality from mentors, mentees, and program staff in a school-based youth mentoring program. Children and Youth Services Review, 85, 53–62. D'Amico, M. (2016). Smart hotel technology trends: Creating the ultimate personalized experience. Retrieved October 30, 2017, from https://www.danacommunications.com/ smart-hotel-technology-trends/. Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive–experiential and analytical–rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390–405. Farnham, S. D., McCarthy, J. F., Patel, Y., Ahuja, S., Norman, D., Hazlewood, W. R., et al. (2009, April). Measuring the impact of third place attachment on the adoption of a place-based community technology. Paper presented at the SIGCHI conference on

7. Limitations and future research Although this study has yielded new insights into the subject matter mentioned above, it still has some limitations, which could be used as future research opportunities. First, as an exploratory analysis into the relationships among the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions, the generalizability of the findings can be enhanced in future studies involving larger samples and different smart hotels. This study does not focus on examining the effects of demographic factors on the dimensions of technology attachment, the dimensions of experiential relationship quality, experiential risk and experiential sharing intentions perceived by smart hotel guests. Future studies should consider perceptions of those variables using demographic factors such as gender, marital status, age, educational level, occupation and annual income. Second, the cross-sectional design used in this study limits the ability of observing changing patterns of subjects across time, which may have caused misidentification of the relationships between independent and dependent variables. This limits strong assertions about the ordered structure of the model even if we strictly follow the literature in developing such a structure. Future studies will benefit from the collection of longitudinal and experimental data to measure the direction of causality among relationships more precisely. Acknowledgments The authors would like to acknowledge undergraduate students in the University of Nevada – Las Vegas, for their assistance of questionnaire distribution. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jhtm.2018.09.003. References Abdul-Rahman, M., & Kamarulzaman, Y. (2012). The influence of relationship quality and switching costs on customer loyalty in the Malaysian hotel industry. Procedia-Social and Behavioral Sciences, 62, 1023–1027. Alansari, A. E. (2016). Factors influencing place attachment to middle-eastern restaurants in the United States: A case study. International Design Journal, 6(4), 49–54. Ali, F., Amin, M., & Cobanoglu, C. (2016). An integrated model of service experience, emotions, satisfaction, and price acceptance: An empirical analysis in the Chinese hospitality industry. Journal of Hospitality Marketing & Management, 25(4), 449–475. Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of Marketing, 58(3), 53–66. Andrews, K. M., & Delahaye, B. L. (2000). Influences on knowledge processes in organizational learning: The psychosocial filter. Journal of Management Studies, 37(6), 797–810. Arokiasamy, A. R. A. (2013). The impact of customer satisfaction on customer loyalty and intentions to switch in the banking sector in Malaysia. Journal of Commerce, 5(1), 14–21. Bansal, H. S., Irving, P. G., & Taylor, S. F. (2004). A three-component model of customer commitment to service providers. Journal of the Academy of Marketing Science, 32(4), 234–250. Bartlett, M. S. (1954). A note on the multiplying factors for various X2 approximations. Journal of the Royal Statistical Society. Series B (Methodological), 16(2), 296–298. Baxendale, S., Macdonald, E. K., & Wilson, H. N. (2015). The impact of different touchpoints on brand consideration. Journal of Retailing, 91(2), 235–253. Beike, D. R., Brandon, N. R., & Cole, H. E. (2016). Is sharing specific autobiographical memories a distinct form of self-disclosure? Journal of Experimental Psychology: General, 145(4), 434–450. Bhattacharjee, A., & Mogilner, C. (2013). Happiness from ordinary and extraordinary experiences. Journal of Consumer Research, 41(1), 1–17. Bigné, J. E., Andreu, L., & Gnoth, J. (2005). The theme park experience: An analysis of pleasure, arousal and satisfaction. Tourism Management, 26(6), 833–844. Bock, B. C., Thind, H., Fava, J. L., Walaska, K., Barnett, N., Rosen, R., et al. (2016). Development of the mobile phone attachment scale. Paper presented at the 49th Hawaii international conference on system sciences (HICSS), Koloa, Hawaii.

54

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Technology, 29(4), 383–394. Jin, N., Line, N. D., & Merkebu, J. (2016). The impact of brand prestige on trust, perceived risk, satisfaction, and loyalty in upscale restaurants. Journal of Hospitality Marketing & Management, 25(5), 523–546. Jolaee, A., Md Nor, K., Khani, N., & Md Yusoff, R. (2014). Factors affecting knowledge sharing intention among academic staff. International Journal of Educational Management, 28(4), 413–431. Joreskog, K. G., & Sorbom, D. (1989). Lisrel 7: A guide to the program and applications. Chicago, IL: SPSS Inc. Jorgensen, B., & Stedman, R. (2001). Sense of place as an attitude: Lakeshore owners' attitudes toward their properties. Journal of Environmental Psychology, 21(3), 233–248. Jung, L. H., & Soo, K. M. (2012). The effect of brand experience on brand relationship quality. Academy of Marketing Studies Journal, 16(1), 87–98. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. Kals, E., & Maes, J. (2002). Sustainable development and emotions. In P. Schmuck, & W. Schultz (Eds.). Psychology of sustainable development (pp. 97–122). Norwell, MA: Kluwer. Kang, J., Manthiou, A., Sumarjan, N., & Tang, L. (2017). An investigation of brand experience on brand attachment, knowledge, and trust in the lodging industry. Journal of Hospitality Marketing & Management, 26(1), 1–22. Kang, J. W., & Namkung, Y. (2016). Restaurant information sharing on social networking sites: Do network externalities matter? Journal of Hospitality & Tourism Research, 40(6), 739–763. Kao, Y. F., Huang, L. S., & Wu, C. H. (2008). Effects of theatrical elements on experiential quality and loyalty intentions for theme parks. Asia Pacific Journal of Tourism Research, 13(2), 163–174. Kennedy, M. S., Ferrell, L. K., & LeClair, D. T. (2001). Consumers' trust of salesperson and manufacturer: An empirical study. Journal of Business Research, 51(1), 73–86. Kim, W. G., & Cha, Y. (2002). Antecedents and consequences of relationship quality in hotel industry. International Journal of Hospitality Management, 21(4), 321–338. Kim, C. K., Jun, M., Han, J., Kim, M., & Kim, J. Y. (2013). Antecedents and outcomes of attachment towards smartphone applications. International Journal of Mobile Communications, 11(4), 393–411. Kim, W. G., Lee, Y. K., & Yoo, Y. J. (2006). Predictors of relationship quality and relationship outcomes in luxury restaurants. Journal of Hospitality & Tourism Research, 30(2), 143–169. Kim, K., Schmierbach, M. G., Chung, M. Y., Fraustino, J. D., Dardis, F., & Ahern, L. (2015). Is it a sense of autonomy, control, or attachment? Exploring the effects of in-game customization on game enjoyment. Computers in Human Behavior, 48, 695–705. Knutson, B., Elsworth, J., & Beck, J. (2006). Restaurant discounts for seniors: Perceptions of the mature market. Cornell Hospitality Quarterly, 47(1), 61–74. Kwon, K. J., Peng, N., & Mai, D. (2015). Why do people share knowledge through online social network. In E. W. Wan, & M. Zhang (Vol. Eds.), Asia-Pacific advances in consumer research: Vol. 11, (pp. 325–). Duluth, MN: Association for Consumer Research. Kyle, G., Bricker, K., Graefe, A., & Wickham, T. (2004a). An examination of recreationists' relationships with activities and settings. Leisure Sciences, 26(2), 123–142. Kyle, G., Graefe, A. R., & Manning, R. (2005). Testing the dimensionality of place attachment in recreational settings. Environment and Behavior, 37(2), 285–303. Kyle, G., Mowen, A., & Tarrant, M. (2004b). Linking place preferences with place meaning: An examination of the relationship between place motivation and place attachment. Journal of Environmental Psychology, 24(4), 439–454. Lai, W. C., & Hung, W. H. (2017). Constructing the smart hotel architecture–A case study in Taiwan. Paper presented at the 17th international conference on electronic business (ICEB), Dubai, UAE. Lambert, N. M., Gwinn, A. M., Baumeister, R. F., Strachman, A., Washburn, I. J., Gable, S. L., et al. (2013). A boost of positive affect: The perks of sharing positive experiences. Journal of Social and Personal Relationships, 30(1), 24–43. Leary, M. R., & Baumeister, R. F. (2000). The nature and function of self-esteem: Sociometer theory. Advances in Experimental Social Psychology, 32, 1–62. Lee, J. S. (2015). Analysis of place attachment and trust in residential communityDeveloping strategies for the revitalization of intimacy zone. Journal of the Korean Housing Association, 26(1), 53–60. Lee, S. C., Barker, S., & Kandampully, J. (2003). Technology, service quality, and customer loyalty in hotels: Australian managerial perspectives. Journal of Service Theory and Practice, 13(5), 423–432. Lee, T. H., & Shen, Y. L. (2013). The influence of leisure involvement and place attachment on destination loyalty: Evidence from recreationists walking their dogs in urban parks. Journal of Environmental Psychology, 33, 76–85. Leppäniemi, M., Karjaluoto, H., & Saarijärvi, H. (2017). Customer perceived value, satisfaction, and loyalty: The role of willingness to share information. International Review of Retail Distribution & Consumer Research, 27(2), 164–188. Li, Y. (2014). Information technology attachment and continuance. Paper presented at the 18th Pacific Asia conference on information systems (PACIS), chengdu, China. Li, H. (2017). Spaceship earth and technological utopianism: Liu Cixin's ecological science fiction. Tamkang Review, 47(2), 17–32. Li, D., Browne, G. J., & Chau, P. Y. (2006). An empirical investigation of web site use Using a commitment-based model. Decision Sciences, 37(3), 427–444. Lichtenstein, D. R., Netemeyer, R. G., & Burton, S. (1990). Distinguishing coupon proneness from value consciousness: An acquisition-transaction utility theory perspective. Journal of Marketing, 54(3), 54–67. Lin, C. P., & Ding, C. G. (2005). Opening the black box: Assessing the mediating mechanism of relationship quality and the moderating effects of prior experience in ISP service. International Journal of Service Industry Management, 16(1), 55–80. Liu, C. T., Guo, Y. M., & Lee, C. H. (2011). The effects of relationship quality and switching barriers on customer loyalty. International Journal of Information

human factors in computing systems, Boston, MA. Farrelly, G. (2013). Putting locative technology in its sense of place. Paper presented at 2013 IEEE international symposium on technology and society (ISTAS): Social implications of wearable computing and augmediated reality in everyday life, Toronto, Canada. Ferrer, R. A., Klein, W. M., Persoskie, A., Avishai-Yitshak, A., & Sheeran, P. (2016). The Tripartite Model of Risk Perception (TRIRISK): Distinguishing deliberative, affective, and experiential components of perceived risk. Annals of Behavioral Medicine, 50(5), 653–663. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. Fournier, S., & Mick, D. G. (1999). Rediscovering satisfaction. Journal of Marketing, 3(4), 5–23. Gilovich, T., Kumar, A., & Jampol, L. (2015). A wonderful life: Experiential consumption and the pursuit of happiness. Journal of Consumer Psychology, 25(1), 152–165. Goh, S. K., Jiang, N., & Tee, P. L. (2016). The impact of brand trust, self-image congruence and usage satisfaction toward smartphone repurchase intention. International Review of Management and Marketing, 6(3), 436–441. Golan, G. J. (2015). The integrated approach to public diplomacy. In G. J. Golan, S. U. Yang, & D. F. Kinsey (Eds.). International public relations and public diplomacy: Communication and engagement (pp. 417–440). New York, NY: Peter Lang Publishing. Grunig, J. E., & Hung-Baesecke, C. J. F. (2015). The effect of relationships on reputation and reputation on relationships: A cognitive, behavioral study. In E. J. Ki, J. N. Kim, & J. A. Ledingham (Eds.). Public relations as relationship management: A relational approach to the study and practice of public relations (pp. 63–113). New York, NY: Routledge. Gul, R. (2014). The relationship between reputation, customer satisfaction, trust, and loyalty. Journal of Public Administration and Governance, 4(3), 368–387. Gu, H., & Ryan, C. (2008). Place attachment, identity and community impacts of tourism – the case of a Beijing Hutong. Tourism Management, 29(4), 637–647. Hair, J. F. J., Black, W. C., Babin, B. J., & Anderson, R. F. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson Education. Ha, H. Y., Janda, S., & Muthaly, S. K. (2010). A new understanding of satisfaction model in e-re-purchase situation. European Journal of Marketing, 44(7/8), 997–1016. Halpenny, E. (2010). Pro-environmental behaviors and park visitors: The effect of place attachment. Journal of Environmental Psychology, 30(4), 409–421. Hamilton-Webb, A., Manning, L., Naylor, R., & Conway, J. (2017). The relationship between risk experience and risk response: A study of farmers and climate change. Journal of Risk Research, 20(11), 1379–1393. Hasanov, M., & Beaumont, J. (2016). The value of collective intentionality for understanding urban self-organization. Urban Research & Practice, 9(3), 231–249. Hertlein, K. M., & Twist, M. L. (2018). Attachment to technology: The missing link. Journal of Couple & Relationship Therapy, 17(1), 2–6. He, W., & Wei, K. K. (2009). What drives continued knowledge sharing? An investigation of knowledge-contribution and-seeking beliefs. Decision Support Systems, 46(4), 826–838. Hidalgo, M. C., & Hernandez, B. (2001). Place attachment: Conceptual and empirical questions. Journal of Environmental Psychology, 21(3), 273–281. Hinkin, T. R. (2005). Scale development principles and practices. In R. A. Swanson, & E. F. Holton (Eds.). Research in organizations: Foundations and methods of inquiry (pp. 161–179). San Francisco, CA: Berrett-Koehler Publishers. Holmlund, M., & Törnroos, J. A. (1997). What are relationships in business networks? Management Decision, 35(4), 304–309. Holste, J. S., & Fields, D. (2010). Trust and tacit knowledge sharing and use. Journal of Knowledge Management, 14(1), 128–140. Hopeniene, R., & Rutelione, A. (2016). Relationship quality in tourism: A case of local tourism cluster in Lithuania. Lex Localis – Journal of Local Self-Government, 14(2), 225–249. Hosany, S., Prayag, G., Van Der Veen, R., Huang, S., & Deesilatham, S. (2017). Mediating effects of place attachment and satisfaction on the relationship between tourists' emotions and intention to recommend. Journal of Travel Research, 56(8), 1079–1093. Huy Tuu, H., Ottar Olsen, S., & Thi Thuy Linh, P. (2011). The moderator effects of perceived risk, objective knowledge and certainty in the satisfaction-loyalty relationship. Journal of Consumer Marketing, 28(5), 363–375. Hwang, S. N., Lee, C., & Chen, H. J. (2005). The relationship among tourists' involvement, place attachment and interpretation satisfaction in Taiwan's national parks. Tourism Management, 26(2), 143–156. Hwei, L. (2015). Control your hotel room via a WeChat app? It's possible. Retrieved December 17, 2017, from https://vulcanpost.com/136211/wechat-ayla-networksturns-phone-remote-hotel-room-future/. Io, M. U. (2018). The relationships between positive emotions, place attachment, and place satisfaction in casino hotels. International Journal of Hospitality & Tourism Administration, 19(2), 167–186. Ismail, N. F., Hsan, M. H., & Mustapha, E. E. (2018). Technology use, emotional connection and their relationship: A literature review. Journal of Theoretical and Applied Information Technology, 96(1), 127–139. Jaremen, D., Jędrasiak, M., & Rapacz, A. (2016). The concept of smart hotels as an innovation on the hospitality industry market-case study of Puro Hotel in Wrocław. Economic Problems of Tourism, 36(4), 65–75. Jaskiewicz, M. (2015). Place attachment, place identity and aesthetic appraisal of urban landscape. Polish Psychological Bulletin, 46(4), 573–578. Jiang, Y., Ramkissoon, H., Mavondo, F. T., & Feng, S. (2017). Authenticity: The link between destination image and place attachment. Journal of Hospitality Marketing & Management, 26(2), 105–124. Jin, X. L., Lee, M. K. O., & Cheung, C. M. K. (2010). Predicting continuance in online communities: Model development and empirical test. Behavior & Information

55

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

Ram, Y., Björk, P., & Weidenfeld, A. (2016). Authenticity and place attachment of major visitor attractions. Tourism Management, 52, 110–122. Ramkissoon, H., Smith, L. D. G., & Kneebone, S. (2014). Visitor satisfaction and place attachment in national parks. Tourism Analysis, 19(3), 287–300. Ramkissoon, H., Smith, L. D. G., & Weiler, B. (2013a). Relationships between place attachment, place satisfaction and pro-environmental behaviour in an Australian national park. Journal of Sustainable Tourism, 21(3), 434–457. Ramkissoon, H., Smith, L. D. G., & Weiler, B. (2013b). Testing the dimensionality of place attachment and its relationships with place satisfaction and pro-environmental behaviours: A structural equation modelling approach. Tourism Management, 36, 552–566. Ramkissoon, H., Weiler, B., & Smith, L. D. G. (2012). Place attachment and pro-environmental behaviour in national parks: The development of a conceptual framework. Journal of Sustainable Tourism, 20(2), 257–276. Ramkissoon, H., Weiler, B., & Smith, L. D. G. (2013c). Place attachment, place satisfaction and pro-environmental behaviour: A comparative assessment of multiple regression and structural equation modelling. Journal of Policy Research in Tourism, Leisure and Events, 5(3), 215–232. Rashid, S., Abu, N. K., & Ahmad, R. H. R. (2011). Influence of relationship quality on hotel guests' loyalty: A case study of a malaysian budget hotel. Canadian Journal on Scientific and Industrial Research, 2(6), 220–229. Rasli, A., Danjuma, I., Yew, L. K., & Igbal, M. J. (2011). Service quality, customer satisfaction in technology-based universities. African Journal of Business Management, 5(15), 6541–6553. Rastbod, S., & Aflatounian, Z. (2016). The relationship of place attachment and the satisfaction of visitors in cinema multiplex (case study: Pardis Melat and Koorosh, Tehran, Iran). Space Ontology International Journal, 5(3), 15–23. Reilly, R. F. (2015). Valuation of technology-related intangible assets. Insights, Summer. Reis, H. T., Smith, S. M., Carmichael, C. L., Caprariello, P. A., Tsai, F. F., Rodrigues, A., et al. (2010). Are you happy for me? How sharing positive events with others provides personal and interpersonal benefits. Journal of Personality and Social Psychology, 99(2), 311–329. Riege, A. (2005). Three-dozen knowledge-sharing barriers managers must consider. Journal of Knowledge Management, 9(3), 18–35. Roy, S., Ponnam, A., & Mandal, S. (2017). Comprehending technology attachment in the case of smart phone-applications: An empirical study. Journal of Electronic Commerce in Organizations, 15(1), 23–43. Ruan, W. Q., Li, Y. Q., & Liu, C. H. S. (2017). Measuring tourism risk impacts on destination image. Sustainability, 9(9), 1501–1515. Rutten, W., Blaas-Franken, J., & Martin, H. (2016). The impact of (low) trust on knowledge sharing. Journal of Knowledge Management, 20(2), 199–214. Salam, A. F., Rao, H. R., & Pegels, C. C. (2003). Consumer-perceived risk in ecommerce transactions. Communications of the ACM, 46(12), 325–331. Sarkar, S. K., Au, N., & Law, R. (2013). Analysing ecotourists' satisfaction in socialisation and knowledge sharing intentions via social media. In Z. Xiang, & I. Tussyadiah (Eds.). Information and communication technologies in tourism 2014 (pp. 313–326). Cham: Springer. Scannell, L., & Gifford, R. (2010). The relations between natural and civic place attachment and pro-environmental behavior. Journal of Environmental Psychology, 30(3), 289–297. Schama, S. (1996). Landscape and memory. London, UK: Fontana. Selnes, F. (1998). Antecedents and consequences of trust and satisfaction in buyer-seller relationships. European Journal of Marketing, 32(3/4), 305–322. Shao, Y., & Liu, B. (2017). Place attachment assessment system in contemporary urbanism. Procedia Engineering, 198, 152–168. Shpëtim, Ç. (2012). Exploring the relationships among service quality, satisfaction, trust and store loyalty among retail customers. Journal of Competitiveness, 4(4), 16–35. Sigala, M. (2018). New technologies in tourism: From multi-disciplinary to anti-disciplinary advances and trajectories. Tourism Management Perspectives, 25, 151–155. Singh, J., & Sirdeshmukh, D. (2000). Agency and trust mechanisms in consumer satisfaction and loyalty judgments. Journal of the Academy of Marketing Science, 28(1), 150–167. Skarmeas, D., Katsikeas, C. S., Spyropoulou, S., & Salehi-Sangari, E. (2008). Market and supplier characteristics driving distributor relationship quality in international marketing channels of industrial products. Industrial Marketing Management, 37(1), 23–36. Sotiriadis, M. D., & Sotiriadis, M. D. (2017). Sharing tourism experiences in social media: A literature review and a set of suggested business strategies. International Journal of Contemporary Hospitality Management, 29(1), 179–225. Stafford, L., & Canary, D. J. (1991). Maintenance strategies and romantic relationship type, gender and relational characteristics. Journal of Social and Personal Relationships, 8(2), 217–242. Stals, S. (2012). Personal relationship with the city. Eindhoven, the Netherlands: Eindhoven University of Technology. Stefaniak, A., Bilewicz, M., & Lewicka, M. (2017). The merits of teaching local history: Increased place attachment enhances civic engagement and social trust. Journal of Environmental Psychology, 51, 217–225. Stein, A., & Ramaseshan, B. (2016). Towards the identification of customer experience touch point elements. Journal of Retailing and Consumer Services, 30, 8–19. Stokols, D., & Shumacker, S. A. (1981). People in places: A transactional view of settings. In J. Harvey (Ed.). Cognition, social behavior, and the environment (pp. 441–448). Hillsdale, NJ: Erlbaum. Suh, K. S., Kim, H., & Suh, E. K. (2011). What if your avatar looks like you? Dual-congruity perspectives for avatar use. MIS Quarterly, 35(3), 711–729. Sıvalıoğlu, P., & Berköz, L. (2016). Relationship between place attachment and user satisfaction at some national parks in Turkey. ITU A|Z, 13(1), 171–181.

Management, 31(1), 71–79. Loureiro, S. M. C. (2014). The role of the rural tourism experience economy in place attachment and behavioral intentions. International Journal of Hospitality Management, 40, 1–9. Loureiro, S. M. C., & Cunha, N. P. D. (2017). Wine prestige and experience in enhancing relationship quality and outcomes: Wine tourism in Douro. International Journal of Wine Business Research, 29(4), 434–456. Luse, D. (2018). Technology readiness and customer satisfaction in luxury hotels: A case study of Vietnam. International Journal of Entrepreneurship, 22(3), 1–23. Mahrous, A. A., & Hassan, S. S. (2017). Achieving superior customer experience: An investigation of multichannel choices in the travel and tourism industry of an emerging market. Journal of Travel Research, 56(8), 1049–1064. Malhotra, N., & Birks, D. (2007). Marketing research: An applied approach. London, UK: Prentice Hall. Malik, A., Hiekkanen, K., Dhir, A., & Nieminen, M. (2016). Impact of privacy, trust and user activity on intentions to share Facebook photos. Journal of Information, Communication and Ethics in Society, 14(4), 364–382. Mano, H., & Oliver, R. L. (1993). Assessing the dimensionality and structure of the consumption experience: Evaluation, feeling, and satisfaction. Journal of Consumer Research, 20(3), 451–466. Manturuk, K. R., Lindblad, M. R., & Quercia, R. G. (2017). A place called home: The social dimensions of homeownership. New York, NY: Oxford University Press. Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. Mesch, G., & Manor, O. (1998). Social ties, environment perception and local attachment. Environment and Behavior, 30(4), 504–519. Milan, G. S., Bebber, S., & Eberle, D. (2015). Information quality, distrust and perceived risk as antecedents of purchase intention in the online purchase context. Journal of Management Information System and E-Commerce, 2(2), 111–129. Mittendorf, C. (2017). How trust and risk influence sharing intentions on Airbnb. Paper presented at the 21st Pacific-Asia conference on information systems (PACIS 2017). Malaysia: Langkawi Island. Moore, R. L., & Graefe, A. R. (1994). Attachments to recreation settings: The case of rail trail users. Leisure Sciences, 16(1), 17–31. Morgan, P. (2010). Towards a developmental theory of place attachment. Journal of Environmental Psychology, 30(1), 11–22. Mosavi, S. A., & Ghaedi, M. (2012). A survey on the relationship between trust, customer loyalty, commitment and repurchase intention. African Journal of Business Management, 6(36), 10089–10098. Öhman, S. (2017). Previous experiences and risk perception: The role of transference. Journal of Education, Society and Behavioural Science, 23(1), 1–10. Oz, B. K. (2014). Examining place attachment from a foursquare perspectiveUnpublished master’s thesis. Ankara, Turkey: Middle East Technical University. Park, H. S. (2005). The effect of user's satisfactions and intentions to use the system on the service quality: Concentrated on property management system in hotel. Korean Journal of Hospitality Administration, 14, 171–189. Park, M. Y., & Chung, K. H. (2011). The antecedents and consequences of user satisfaction in virtual community: Focused on college students. Korean Research Academy of Distribution and Management Review, 14(1), 77–99. Patterson, P. G., & Spreng, R. A. (1997). Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-to-business, services context: An empirical examination. International Journal of Service Industry Management, 8(5), 414–434. Paulssen, M., & Fournier, S. (2007). Attachment security and the strength of commercial relationships: A longitudinal study (working paper No. 2007-14). Boston, MA: Boston University. Payton, M. A., Fulton, D. C., & Anderson, D. H. (2005). Influence of place attachment and trust on civic action: A study at Sherburne national wildlife refuge. Society & Natural Resources, 18(6), 511–528. Pedró, F. (2012). Connected minds: Technology and today's learners. OECD. Pepur, M., Mihanović, Z., & Arnerić, J. (2011). Interdependence between relationship quality dimensions. Croatian Operational Research Review, 2(1), 255–263. Perlaviciute, G., & Steg, L. (2014). Contextual and psychological factors shaping evaluations and acceptability of energy alternatives: Integrated review and research agenda. Renewable and Sustainable Energy Reviews, 35, 361–381. Plunkett, D. (2011). On place attachments in virtual worlds. World Leisure Journal, 53(3), 168–178. Potts, R. (2013). Hominin evolution in settings of strong environmental variability. Quaternary Science Reviews, 73, 1–13. Prayag, G., & Ryan, C. (2012). Antecedents of tourists' loyalty to Mauritius: The role and influence of destination image, place attachment, personal involvement and satisfaction. Journal of Travel Research, 51(3), 342–356. Qiu, H. L. (2014). Impacts of tourist destination image on place attachment and tourist loyalty. Computer Modelling and New Technologies, 18(11), 651–656. Rafiq, M., Fulford, H., & Lu, X. (2013). Building customer loyalty in online retailing: The role of relationship quality. Journal of Marketing Management, 29(3/4), 494–517. Rahmani-Nejad, L., Firoozbakht, Z., & Taghipoor, A. (2014). Service quality, relationship quality and customer loyalty (case study: Banking industry in Iran). Open Journal of Social Sciences, 2(4), 262–268. Rajaobelina, L. (2018). The impact of customer experience on relationship quality with travel agencies in a multichannel environment. Journal of Travel Research, 57(2), 206–217. Ramanathan, S., & McGill, A. L. (2007). Consuming with others: Social influences on moment-to-moment and retrospective evaluations of an experience. Journal of Consumer Research, 34(4), 506–524.

56

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng

for cruise tourists: The case of Hong Kong. Tourism Management, 66, 200–220. Wu, H. C., Cheng, C. C., & Ai, C. H. (2018b). An empirical analysis of green switching intention in the airline industry. Journal of Environmental Planning and Management, 61(8), 1438–1468. Wu, H. C., Cheng, C. C., Chen, Y. C., & Hong, W. (2018c). Towards green experiential loyalty: Driving from experiential quality, green relationship quality, environmental friendliness, green support and green desire. International Journal of Contemporary Hospitality Management, 30(3), 1374–1397. Wu, H. C., Cheng, C. C., & Hong, W. (2017). An assessment of zoo visitors' revisit intentions. Tourism Analysis, 22(3), 361–375. Wu, H. C., & Li, T. (2017). A study of experiential quality, perceived value, heritage image, experiential satisfaction, and behavioral intentions for heritage tourists. Journal of Hospitality & Tourism Research, 41(8), 904–944. Wu, H. C., Li, M. Y., & Li, T. (2018d). A study of experiential quality, experiential value, experiential satisfaction, theme park image, and revisit intention. Journal of Hospitality & Tourism Research, 42(1), 26–73. Wu, H. C., Wei, C. F., Tseng, L. Y., & Cheng, C. C. (2018e). What drives green brand switching behavior? Marketing Intelligence & Planning, 36(6), 694–708. Wynween, C., Kyle, G., & Sutton, S. (2012). Natural areas visitors' place meaning and place attachment ascribed to a marine setting. Journal of Environmental Psychology, 32(4), 287–296. Yang, F. X. (2017). Effects of restaurant satisfaction and knowledge sharing motivation on eWOM intentions: The moderating role of technology acceptance factors. Journal of Hospitality & Tourism Research, 41(1), 93–127. Yang, C. L., & Nair, V. (2014). Risk perception study in tourism: Are we really measuring perceived risk? Procedia - Social and Behavioral Sciences, 144, 322–327. Yi, X. L., Fu, X. X., Jin, W. M., & Okumus, F. (2018). Constructing a model of exhibition attachment: Motivation, attachment, and loyalty. Tourism Management, 65, 224–236. Yüksel, A., & Yüksel, F. (2007). Shopping risk perceptions: Effects on tourists' emotions, satisfaction and expressed loyalty intentions. Tourism Management, 28(3), 703–713. Yüksel, A., Yüksel, F., & Bilim, Y. (2010). Destination attachment: Effects on customer satisfaction and cognitive, affective and conative loyalty. Tourism Management, 31(2), 274–284. Zemke, D. M. V., Chen, Y. S., Raab, C., & Zhong, Y. (2017). Hotel design, guest satisfaction, and behavioural intentions. Anatolia: An International Journal of Tourism and Hospitality Research, 28(3), 338–350. Zhang, Y., van Dijk, T., Tang, J., & Berg, A. E. (2015). Green space attachment and health: A comparative study in two urban neighborhoods. International Journal of Environmental Research and Public Health, 12(11), 14342–14363.

Tam, J. L. M. (2012). The moderating role of perceived risk in loyalty intentions: An investigation in a service context. Marketing Intelligence & Planning, 30(1), 33–52. Tam, L., & Kim, J. N. (2017). Conceptualising and measuring relationship as public diplomacy outcome: Development of the relationship assessment of diplomatic interaction outcome (RADIO) scale. Communication Research and Practice, 3(3), 215–232. Therkelsen, A., Halkier, H., & Jensen, O. (2010). Branding Aalberg: Building community or selling place? In A. Go, & M. Kavatatzis (Eds.). Towards effective place brand management: Branding European cities and regions (pp. 136–155). Cheltenham, UK: Edward Elgar. Tlili, H. T., & Amara, D. (2016). Towards emotional experience and place attachment as tourist satisfaction attributes. Journal of Business & Economic Policy, 3(3), 108–119. Tonge, J., Ryan, M. M., Moore, S. A., & Beckley, L. E. (2015). The effect of place attachment on pro-environment behavioral intentions of visitors to coastal natural area tourist destinations. Journal of Travel Research, 54(6), 730–743. Trojanowski, M., & Kułak, J. (2017). The impact of moderators and trust on consumer's intention to use a mobile phone for purchases. Journal of Management and Business Administration, 25(2), 91–116. Trub, L., & Barbot, B. (2016). The paradox of phone attachment: Development and validation of the young adult attachment to phone scale (YAPS). Computers in Human Behavior, 64, 663–672. Tuan, Y. F. (1980). Rootedness versus sense of place. Landscape, 24, 3–8. Tuu, H. H., Olsen, S. O., & Linh, P. T. T. (2011). The moderator effects of perceived risk, objective knowledge and certainty in the satisfaction-loyalty relationship. Journal of Consumer Marketing, 28(5), 363–375. Van Dijk, J. A. (2006). Digital divide research, achievements and shortcomings. Poetics, 34(4), 221–235. Vaske, J., & Kobrin, K. (2001). Place attachment and environmentally responsible behavior. The Journal of Environmental Education, 32(4), 16–21. Veasna, S., Wu, W. Y., & Huang, C. H. (2013). The impact of destination source credibility on destination satisfaction: The mediating effects of destination attachment and destination image. Tourism Management, 36, 511–526. Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). Customer experience creation: Determinants, dynamics and management strategies. Journal of rRetailing, 85(1), 31–41. Verma, V., Sharma, D., & Sheth, J. (2016). Does relationship marketing matter in online retailing? A meta-analytics approach. Journal of the Academy of Marketing Science, 44(2), 206–217. Vibber, K., & Kim, J. N. (2015). Diplomacy in the globalized world: Focusing internally to build relationships externally. In G. J. Golan, S. U. Yang, & D. F. Kinsey (Eds.). International public relations and public diplomacy: Communication and engagement (pp. 131–146). New York, NY: Peter Lang Publishing. Walker, G. J., & Chapman, R. (2003). Thinking like a park: The effects of sense of place, perspective-taking, and empathy on pro-environmental intentions. Journal of Park and Recreation Administration, 21(4), 71–86. Wan, H. H., & Schell, R. (2007). Reassessing corporate image-an examination of how image bridges symbolic relationships with behavioral relationships. Journal of Public Relations Research, 19(1), 25–45. Williams, A. M., & Baláž, V. (2013). Tourism, risk tolerance and competences: Travel organization and tourism hazards. Tourism Management, 35, 209–221. Wong, J. Y., & Lai, T. C. (2015). Celebrity attachment and behavioral intentions: The mediating role of place attachment. International Journal of Tourism Research, 17(2), 161–170. Wong, A., & Sohal, A. (2002). An examination of the relationship between trust, commitment and relationship quality. International Journal of Retail & Distribution Management, 30(1), 34–50. Wong, J., Wu, H. C., & Cheng, C. C. (2015). An empirical analysis of synthesizing the effects of festival quality, emotion, festival image and festival satisfaction on festival loyalty: A case study of Macau Food festival. International Journal of Tourism Research, 17(6), 521–536. Wray, B., Palmer, A., & Bejou, D. (1994). Using neural network analysis to evaluate buyer-seller relationships. European Journal of Marketing, 28(10), 32–48. Wu, H. C. (2017). What drives experiential loyalty? A case study of Starbucks coffee chain in Taiwan. British Food Journal, 119(3), 468–496. Wu, H. C., & Ai, C. H. (2016). Synthesizing the effects of experiential quality, excitement, equity, experiential satisfaction on experiential loyalty for the golf industry: The case of Hainan Island. Journal of Hospitality and Tourism Management, 29, 41–59. Wu, H. C., Ai, C. H., & Cheng, C. C. (2016a). Synthesizing the effects of green experiential quality, green equity, green image and green experiential satisfaction on green switching intention. International Journal of Contemporary Hospitality Management, 28(9), 2080–2107. Wu, H. C., & Cheng, C. C. (2013). A hierarchical model of service quality in the airline industry. Journal of Hospitality and Tourism Management, 20, 13–22. Wu, H. C., & Cheng, C. C. (2017). What drives green advocacy? A case study of leisure farms in Taiwan. Journal of Hospitality and Tourism Management, 33, 103–112. Wu, H. C., & Cheng, C. C. (2018a). An empirical analysis of green experiential loyalty: A case study. Journal of International Food & Agribusiness Marketing. https://doi.org/10. 1080/08974438.2018.1482484. Wu, H. C., & Cheng, C. C. (2018b). An empirical analysis of tourists' switching intention: The case of Jiufen. Journal of China Tourism Research, 14(2), 193–220. Wu, H. C., & Cheng, C. C. (2018c). What drives experiential loyalty toward smart restaurants? The case study of KFC in Beijing. Journal of Hospitality Marketing & Management, 27(2), 151–177. Wu, H. C., & Cheng, C. C. (2018d). What drives supportive intentions towards a dark tourism site? International Journal of Tourism Research, 20(4), 458–474. Wu, H. C., Cheng, C. C., & Ai, C. H. (2018a). A study of experiential quality, experiential value, trust, corporate reputation, experiential satisfaction and behavioral intentions

Hung-Che Wu is an Associate Professor at Business School in Nanfang College of Sun Yat-sen University, China. He holds his PhD from Lincoln University in marketing and has published his works in the International Journal of Bank Marketing, Journal of International Food & Agribusiness Marketing, Marketing Intelligence & Planning, Journal of Destination Marketing and Management, Tourism Management, Journal of Environmental Planning and Management, Journal of the Knowledge Economy, Industrial Management & Data System, Journal of Organizational Change Management, Innovative Marketing, Journal of Travel Research, Tourism Review International, Tourism Analysis, International Journal of Economics and Financial Issues, Tourism Planning and Development, Journal of Tourism, Hospitality & Culinary Arts, Journal of Quality Assurance in Hospitality & Tourism, Journal of Convention and Event Tourism, Asia Pacific Journal of Marketing and Logistics, Event Management, Journal of Foodservice Business Research, Journal of Hospitality Marketing & Management, Asia Pacific Journal of Tourism Research, International Journal of Tourism Research, International Journal of Tourism Sciences, British Food Journal, Multimedia Tools and Applications, International Journal of Contemporary Hospitality Management, International Journal of Tourism & Hospitality Administration, Journal of Hospitality and Tourism Management, International Journal of Economics and Financial Issues, Journal of China Tourism Research, Tourism and Hospitality Research, and Journal of Hospitality & Tourism Research, among others. He is currently working as an editor-in-chief for Probe – Business Management and the editorial board members for the International Journal of Business and Systems Research, Probe - Environmental and Waste Management, Probe Business Management (OA Journal), Environments (OA Journal), Sensors (OA Journal), Foods (OA Journal), Composite Materials Research, Environment and Social Psychology, Sustainability (OA Journal), Cognitive Neuroscience Journal, Cogent Business & Management, Tourism Analysis, Journal of Hospitality Management and Tourism, International Business Research, Journal of Tourism & Hospitality, International Journal of Business and Management, International Journal of Marketing Studies, Journal of Hospitality and Tourism Research, Science Journal of Business and Management, and Business and Management Studies. His research interests include green marketing, hospitality management, service quality, customer satisfaction and consumer behavior. Dr. Hung-Che Wu is the corresponding author and can be contacted at: [email protected]

57

Journal of Hospitality and Tourism Management 37 (2018) 42–58

H.-C. Wu, C.-C. Cheng Ching-Chan Cheng is an Associate Professor at Department of Food and Beverage Management in Taipei University of Marine Technology, Taiwan. He holds his PhD in hospitality and tourism service quality from Chung Hua University and has published his works in the Journal of China Tourism Research, Asia Pacific Journal of Marketing and Logistics, International Journal of Bank Marketing, Marketing Intelligence & Planning, Journal of International Food & Agribusiness Marketing, Tourism Management, Event Management, International Journal of Tourism & Hospitality Administration, Journal of Environmental Planning and Management, Journal of Convention and Event Tourism, Asia Pacific Journal of Tourism Research, Journal of Hospitality Marketing & Management, International Journal of Contemporary Hospitality Management, Tourism Analysis, Journal of Hospitality and Tourism Management, Tourism Review

International, International Journal of Hospitality Management, International Journal of Tourism Research, Total Quality Management & Business Excellence, Romanian Journal of Economic Forecasting, and Current Issues in Tourism, among others. His research interests include services marketing, consumer behavior and total quality management.

58