Smart tourism technology continuance, perceived value and resident wellbeing

This study contributes to the ‘inclusive innovation for enhanced local experience in tourism’ agenda by studying the impact of smart tourism technology continuance on resident wellbeing in host cities. Specifically, the study builds on recent work on tourism and resident wellbeing (Lin, Chen & Filieri, 2017; Lin, Cottam & Filieri, working paper) and investigates the role smart tourist apps in facilitating this relationship. Smart tourism technology is defined as “all forms of online tourism applications and information sources such as online travel agents, personal blogs, public websites, company websites, social media, smartphone apps, and so on” (Huang et al., 2017 p. 758). Contemporary research suggests host cities and their residents derive more than economic and socio-cultural benefits from tourism (Paraskevaidis & Andriotis, 2017). Tourism, and offering tips and advice to tourists in particular, has been linked to enhanced resident wellbeing and life satisfaction (Lin, Cottam & Filieri, working paper; Lin, Chen & Filieri, 2017). Drawing on Davis’ (1985) Technology Acceptable Model and Self-Determination Theory (Ryan & Frederick, 1997) this new study investigates the antecedents of smart tourist app use, including general support for tourism activity, and how these technologies enhance residents’ wellbeing in popular travel destinations. Conceptual Framework This paper defines continuance as long-term use (Bhattacherjee 2001; Davis et al. 1989). Users’ decisions to adopt and continue to use specific technologies for a task can be explained by Davis’ (1989) Technology Acceptance Model which draws upon the principles of the Theory of Reason Action (Fishbein & Ajzen, 1975). TAM has been adapted and applied to many different technologies, e.g. spreadsheets, voice mail, object-oriented technologies, online banking and e-learning systems (Straub, Limayem & Karahanna-Evaristo, 1995; Mathiassen, 1991; Hardgrave & Johnson, 2003; Martins, Oliveira & Popovič, 2014; Persico, Manca & Pozzi, 2014). TAM argues technology adoption is based on its perceived usefulness and perceived ease of use. Perceived usefulness is “the prospective user's subjective probability that using a specific application system will increase his or her job performance within an organizational context” (Davis, Bagozzi & Barsaw, 1989, p.985). In other words, it is the degree a person believes using a technology will enhance their job performance. Perceived ease of use is “the degree to which the prospective user expects the target system to be free of effort” (Davis et al.,1989, p.985).When a person believes a technology can enhance their performance without significantly increasing effort the system will be more likely adopted. In essence, technologies considered useful and easy to use have higher adoption rates. Davis’s (1989) arguments have been validated in numerous studies (Hendrickson, Massey & Cronan, 1993; Doll, Hendrickson & Deng, 1998; Adams, Nelson & Todd, 1992). Given these arguments, the following is proposed:H1: Perceived ease of use is positively related to smart tourist technology continuanceH2: Perceived usefulness is positively related to smart tourist technology continuanceMany studies demonstrate the positive impact of helping others on wellbeing (Stukas et al, 2016; Weinstein & Ryan, 2010; Pressman, 2015). Even small acts of kindness have a measurable positive impact on the wellbeing of ‘givers’ (Nelson et al., 2016; Pressman et al., 2015). Giving induced happiness has even been identified in the inhabitants of a rural village disconnected from western culture (Aknin et al., 2015). Stukas et al. (2016) findings support these results, noting enhanced wellbeing levels in volunteers. The studies support the notion that acts of kindness, big or small, enhance well-being. Moreover, in the tourism context, Lin, Cottam & Filieri (working paper) also found residents’ advice-giving and welcoming behavior was identified as positively related to, and a manifestation of, their support for tourism development. As residents that support tourism development are more likely to help travelers it is postulated this support will manifest via engagement with smart tourism apps.H3: Support for tourism development is positively related to smart tourist technology continuanceSelf-determination theory stipulates that freely-exercised prosocial behaviours increase wellbeing by satisfying fundamental psychological needs, e.g. independence, relatedness and competence (Ryan & Frederick, 1997). Significant work has established how helping people enhances one’s wellbeing (Weinstein & Ryan, 2010; Pressman et al., 2015; Stukas et al. 2016. In one example, Stukas et al. (2016) discovered volunteers often experience greater wellbeing, trust, social connectedness and self-efficacy levels. Zhibin, Cottam & Filieri (working paper) found that residents experienced enhanced wellbeing when they engaged in pro-social behaviours to aid tourists, e.g. offering directions, making travelers feel welcome. Moreover, being helpful and welcoming enhanced tourists’ perceived value of their trips as these are intimately tied to the travel experience (Stylidis, Biran, Sit, & Szivas, 2014; Bimonte & Punzo, 2016). Given smart tourism allows for tourists and hosts to interact through ubiquitous, all-encompassing technology (Li et al., 2017) it stands to reason continued usage of smart tourism apps would generate similar effects on resident wellbeing. Thus, it is proposed: H4: Smart tourist technology continuance is positively related to resident wellbeingMethodologyData will be collected in Phuket with local residents completing structured surveys regarding their support for tourism activity and smart tourism app use. Constructs will be measured on a 5-point Likert-type scale where participants note their agreement to pre-developed statements (1 = strongly disagree, 5 = strongly agree). The survey will use three items measuring resident wellbeing adapted from Yolal et al. (2016) and resident’s support for tourism development will be assessed following Nunkoo & So (2015). Partial Least Squares Structural Equation Modeling (PLS-SEM) will applied to estimate the theoretical model, using SmartPLS 2.0 software (Ringle, Wende, & Will, 2005). PLS-SEM assesses the measurement model by testing construct validity and reliability, and evaluates the structural model by testing the relationships between dependent and independent constructs as outlined in the prior conceptual model (Henseler, Ringle, and Sinkovics, 2009). PLS-SEM is suitable for complex models and prediction oriented research, is capable of handling minimal sample sizes and avoids parameter estimation biases during regression analysis (Henseler et al., 2015). ContributionThis paper will contribute to theory by using self-determination theory to explain how residents use smart tourism apps to gain ‘warm glow’ effects which enhances their wellbeing. Furthermore, the TAM model is applied to explain how perceive ease of use and perceived usefulness determines smart tourist technology adoption and continuance. Finally, this paper links support for tourism development with smart tourism app continuance and extends recent findings into the smart tourism context. In practice, these findings will allow both local and national governments to better understand, and generate policy which considers, the mental health benefits and life-satisfaction smart tourist activity can contribute to local communities. Thus, tourism can have a greater impact than simply economic and socio-cultural development