Scale development of perceived eTrust in the hotel industry: The perspective of Internet users

Wang, Liang; Law, Rob; Hung, Kam; Guillet, Basak Denizci

doi:10.1016/j.ijhm.2014.08.005

Cited by 19 publications

(7 citation statements)

References 98 publications

(109 reference statements)

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“…These three dimensions are considered conceptually distinct (Kumar et al, 1995), but reflect a higher order expectation of trusting beliefs. These person-to-person trust dimensions have been successfully used to assess trust in technology (Gefen, 2002;Mayer et al, 1995;Wang and Benbasat, 2005), including in the fields of travel and tourism (Wang et al, 2014;2015;Li et al, 2017).…”

Section: Trust In Intelligent Robotsmentioning

confidence: 99%

“…Lack of trust, consequently, is viewed as the main hurdle of automation in various strategic areas. In the field of tourism and hospitality management, the link between trust and technology adoption has been wellresearched, even though the focus of these research has been primarily on websites and/or mobile applications (Agag and El-Masry 2016;Chen 2006;Wang et al 2014;2015). For example, Kim et al…”

Section: Outcome Of Trusting Beliefsmentioning

confidence: 99%

“…Chang et al (2006) also found the positive role of trust in adoption of location-based services for tourism. Wang et al (2014;2015) attempted to conceptualize and measure eTrust (i.e., trust formed online) and identified the influence of hotel website's characteristics on trust formation. Further, they found that eTrust has a positive effect on online booking intention.…”

Section: Outcome Of Trusting Beliefsmentioning

confidence: 99%

See 2 more Smart Citations

Do travelers trust intelligent service robots?

Tussyadiah

Zach

Wang

2020

Annals of Tourism Research

177

127

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Section: Trust In Intelligent Robotsmentioning

confidence: 99%

Section: Outcome Of Trusting Beliefsmentioning

confidence: 99%

Section: Outcome Of Trusting Beliefsmentioning

confidence: 99%

See 1 more Smart Citation

Do travelers trust intelligent service robots?

Tussyadiah

Zach

Wang

2020

Annals of Tourism Research

177

127

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“…Two formative indicators (eTrust on UGC and eTrust in UGC providers) are examined. For eTrust on UGC, four factors of eTrust on UGC revised from Narangajavana et al (2017) are adopted; for eTrust in UGC providers, three factors from eTrust in UGC providers revised from Narangajavana et al (2017) are incorporated and one item from eTrust-Benevolence (Wang et al, 2014) is used. We adopted the previous questionnaires from Bashir and Madhavaiah (2015) to test users' attitudes toward using SVAs 10.3389/fpsyg.2022.912177 for travel planning.…”

Section: Questionnaire Developmentmentioning

confidence: 99%

Exploring short video apps users’ travel behavior intention: Empirical analysis based on SVA-TAM model

Wang

Cui²,

Zhang³

et al. 2022

Front. Psychol.

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Social media had made significant effect on the tourism and hospitality industry. Among diverse types of social media platforms, short video apps (SVA) represented by TikTok or Douyin had brought great changes to the tourism industry. As new mobile technology platform, short video apps had changed the way for user to obtain travel information, make traveling plans and share the travel experience. Considering the new technology of SVA and the influence in tourism, this research aims to explore the SVA users’ behavior intentions and the adopting of SVA for making travel decision. Therefore, the new SVA-TAM model is proposed based on the technology acceptance model (TAM), including two new variables: electronic word of mouth (eWOM) and electronic trust (eTrust). An online survey was conducted to short video apps users. PLS-SEM was implemented for data and structural equations analysis of the final obtained 302 samples. In terms of the relationship between variables, this study found that user perceptions of SVA on usefulness and ease of use are powerful predictors of attitudes toward using SVA for travel planning, which maintains consistency with the outcome of previous TAM studies. Additionally, eWOM and eTrust positively influence user attitudes toward using SVA for travel planning even for destination decisions. Therefore, the short video apps should be taken into consideration for tourism marketing and destination branding owes to the effect on the potential users’ behavior intentions.

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“…Trust is based on the buyer's expectations that the seller will not have an opportunistic attitude and take advantage of the situation, but will behave in a dependable, ethical and socially appropriate manner, fulfilling his commitments despite the buyer's vulnerability and dependence (Gefen et al, 2003). The concept of trust was introduced by psychologists in 1950s, but despite its importance it has only recently introduced in tourism and hospitality industry (Wang et al, 2014). Trust is even more important for online than for offline retailers, since consumers perceive more risk in e-commerce due to their inability to visit a physical store and examine the product they are interested in buying (Li et al, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

Risks and marketing in online transactions: a qualitative comparative analysis

Παππάς

2016

Current Issues in Tourism

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The article focuses on the perspectives of holidaymakers who have used internet to book a part or the whole spectrum of their holidays' accommodation. Using Qualitative Comparative Analysis (QCA), the research examines the complex relations between product and web vendor risks, and marketing activities on consumer trust, also employing predictive validity. It examines the perspectives of 735 holidaymakers returining to Manchester International Airport, through the use of structured questionnaires. The findings reveal three sufficient configurations dealing with the focus on the impact of price and quality relationships, the influence of product and web-vendor risks on consumer trust, and the importance of marketing for the minimization of perceived risks in online tourism shopping. Theoretically, the study contributes on the understanding of online decisions' complexity, and explores the attributes that affect accommodation e-purchasing and associated linkages.Methodologically, it implements QCA, which is new in tourism and hospitality domain. It also progresses from fit to predictive validity, an analysis that only a handful of studies has implemented in the service industry. IntroductionThere is a growing need for new knowledge, theories and models of Internet consumer behavior due to the evolution of electronic commerce as it becomes a vital aspect of customer relations and marketing strategy (Racherla et al., 2008; Close & Kukar-Kinney, 2010). The online purchasing behavior needs to be further understood hence, it attracts increasing research attention (Mosteller et al., 2014). As several studies have pinpointed, the key to long-term success for e-retailers is to build consumer trust (Pavlou & Fygensen, 2006;Vos et al., 2014), but the latter is negatively influenced by the perceived risks (Hong & Cha, 2013) associated with both products (Ward & Lee, 2000) and web-vendors (Jiang et al., 2008). Thus, it is important to examine the risk factors affecting trust in Internet shopping, while the purchasing intentions of online consumers need to be further investigated.In tourism and hospitality, the Internet has considerably altered consumers' behavior (Wen, 2009;Mendez et al., 2015) since it gave them the opportunity to directly interact and engage with suppliers, tourist destinations, and hotel firms (Buhalis & Law, 2008). Consumers also share experiences directly with other consumers through eWOM (electronic Word of Mouth) (Akehurst, 2009) something that increases the operational complexity in modern business. Social media (e.g. Facebook, YouTube, Twitter) play a significant part on these attributes since they become a major opportunity and challenge for many tourism and hospitality companies, whilst most of those enterprises actively participate in social media information exchange (Sparks, et al., 2013). The Internet has ultimately altered the booking share from which tourist agencies and especially hotels receive their business (Law & Cheung, 2006). Online shopping has changed tourist behavior s...

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Scale development of perceived eTrust in the hotel industry: The perspective of Internet users

Cited by 19 publications

References 98 publications

Do travelers trust intelligent service robots?

Do travelers trust intelligent service robots?

Exploring short video apps users’ travel behavior intention: Empirical analysis based on SVA-TAM model

Risks and marketing in online transactions: a qualitative comparative analysis

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