Introduction
In an age of rapid development at the information technology front, the viability of ‘smart travel destinations’ is increasingly becoming a reality (Buhalis & Amaranggana, 2014, 2015). Advances in mobile technology have allowed travel destinations to leverage the location-based wireless tracking capabilities afforded by 3/4G telecommunication networks, Bluetooth connectivity, GPS and Wi-Fi networks (Choe & Fesenmaier 2017; Eriksson, 2002). The benefits of these wireless tracking technologies include precise information on spatial behaviour (Edwards, Dickson, Griffin, & Hayllar, 2010), relevant location-based services (LBS)(Pedrana, 2014), navigational services (Eriksson, 2002), as well as recommender services (Tussyadiah & Wang, 2016). With this kind of data available to them, destination management organisations (DMOs) are able to develop more customise tourist engagement strategies which will help them communicate specifically tailored results to tourists (Edwards & Griffin, 2013). While the focus of current tourism research has been the benefits of these wireless tracking technologies (WTTs) to the destination, little research has been done to examine tourists’ perceptions of these technologies. The current exploratory study will investigate tourist perceptions of three prominent kinds of WTTs with differing levels of control at a travel destination: (1) wireless tracking only (WT only; low control); (2) Wi-Fi wireless tracking (Wi-Fi WT; moderate control); and (3) application-based tracking (App; high control).
Theoretical development
The current study applies the Expectancy-Value Theory in examining tourist perceptions of WTTs at a travel destination. The Expectancy-Value Theory suggests that motivation for a behaviour is determined by the desirability of the outcome i.e. benefits to the tourist (Sparks, 2007). In the context of this study, perceived personalisation and perceived innovativeness serve as benefits to tourists. Perceived personalisation is defined as the ability of a DMO to recognize and treat its tourists as individuals through personal messaging, targeted banner ads, special offers on bills, or other personal transactions” (Imhoff, Loftis, & Geiger, 2001). Perceived innovativeness reflects the degree to which a new product is seen to possess new and unique attributes and features (Fu, Jones, & Bolander, 2008). Studies have shown that perceived personalisation and perceived innovativeness positively impact on attitudes toward the product (Baek & Morimoto, 2012; Fu & Eliott, 2013), which in the context of this study relates to both the WTT itself as well as the destination. However, mere presence of WTTs can often provoke concerns about manipulative intent (Lee-Wingate & Xie, 2010) and privacy (Shilton, 2009). Inferences of manipulative intent is defined as tourist perceptions that a company is attempting to persuade via inappropriate, unfair or manipulative means (Campbell, 1995). Privacy concerns refer to the degree to which a tourist is worried about the potential invasion of the right to prevent the disclosure of personal information to others (Baek & Morimoto, 2012, p. 63). Inferences of manipulative intent and privacy concerns have been found to negatively impact on attitudes toward the product (Lee-Wingate & Xie, 2010; Shilton, 2009). Thus, the ability of a travel destination to emphasise the pros and minimise concerns for the cons of WTTs will result in more positive attitudes towards the WTT as well as the destination, which in turn, will positively impact on intention to visit the destination (based on arguments in tourism research suggesting that both attitudes toward products and the destination itself may have an impact on intention to visit e.g. Elliot, Papadopoulos & Kim 2011; Lee & Lockshin 2012). The hypothesised model for this study can be seen in Figure 1.
Methodology
The conceptual model was tested using data from the United States via the Amazon Mechanical Turk (MTurk) platform. A total of 750 responses were acquired but only 615 were included for analysis (responses were excluded due to incomplete data or straight-lining). A between-subjects experimental design was implemented respondents viewing a stimulus for either (1) wireless tracking only (WT only; low control); (2) Wi-Fi wireless tracking (Wi-Fi WT; moderate control); or (3) application-based tracking (App; high control). A pretest of the stimulus confirmed the levels of control proposed by the researchers. Respondents were first told to imagine their next travel destination and were then shown a stimulus. In the WT only condition, respondents were told that the destination was tracking the movement of tourists when their smartphones wireless, Bluetooth or mobile reception was turned on. In the Wi-Fi WT condition, respondents were informed that the destination would track tourists logged on to the destination’s Wi-Fi network. In the App condition, respondents were notified that the destination has an app system which allows the destination to track tourists and send them personalised push notifications. The difference between these three conditions was the level of perceived control that tourists had over the tracking of their location within the destination. Respondents then rated the WTT and destination with regards to inferences to manipulative intent, privacy concerns, perceived personalisation, perceived innovativeness, attitude toward the WTT, attitude toward the destination, and intention to visit the destination. The measures for each of these scales were chosen for their reliability and relevance to the current study. Structural equation modelling then examined the hypothesised relationships for significance.
Results and discussion
Exploratory and factor analysis was conducted to ensure the unidimensional of the scales. Composite reliabilities ranged from 0.70 to 0.95 and the average variance extracted scores ranged from 0.70 to 0.87, suggesting strong internal validity for all scales. All measures were also tested for convergent and discriminant validity which were both supported. Then, the hypotheses were examined using a multigroup analysis with structural equation modelling in AMOS 22. The goodness-of-fit indices for the structural model was deemed acceptable (χ²/df=1.67; RMSEA=0.03; CFI=0.97; NFI=0.94; IFI=0.90) (model comparisons revealed no significant differences at a model level suggesting that the model applied across the different groups). The results of the path analysis revealed five hypotheses which were fully supported (H1a, H2a, H3a, H3b and H6b). The remaining six hypotheses (H1b, H2b, H4a, H4b, H5 and H6a) were only partially supported with significant parameter estimates noted for either one or two of the conditions. The full result of the path analysis can be seen in Table 1. The results suggest that inferences of manipulative intent significantly decreased attitude toward the WTT, highlighting the need for destinations to be transparent about the reasons for tracking tourists. Specifically, the concealed tracking of tourists’ movements was particularly damaging to attitude toward the destination. Privacy concerns also negatively impacted on attitude toward the WTT for all conditions, but surprisingly privacy concerns appeared to significantly increase attitude toward the destination under the App condition. A potential explanation for this is the fact that despite potential for privacy infringements, tourists possess control over usage of the application, thereby moderating the ability of the destination to track them. However, this result warrants greater investigation in future studies. Perceived personalisation was noted to positively impact on attitudes toward the WTT and destination suggesting that tourists positively regarded the benefits of personalisation that the WTT afforded them. Further, perceived innovativeness appeared to positively impact on attitude towards the WTT for the App condition, but more interestingly, positively impacted on attitude toward the destination for the WT only condition. This may potentially suggest that while tourists did perceive manipulative intent in the wireless tracking of their whereabouts they also perceived this to be an innovation. Theoretically, this study extends the tourism literature with regards to the installation or application of wireless tracking technologies. It highlights the aspects that appeal to tourists as well as the concerns that they may have. From a managerial perspective, the results suggest a need for transparency as well as the empowerment of tourists to choose the degree to which their whereabouts are tracked within the destination. It offers further insights into which technologies are best suited to be leveraged in order to develop stronger tourist engagement at the destination. The implications of these results apply to destination managers, marketers as well as policy makers. A successful balance between obtaining valuable information about tourists and providing them with a choice whether or not to be tracked is crucial in ensuring favourable perception of the travel destination.

• Sean Lee(Curtin University, Australia)
• Billy Sung(Curtin University, Australia)