In recent years, the Internet of Things (IoT) has grown to be an essential part of the development of tourism, with an increasing number of IoT solutions being applied in tourism-related industries such as hospitality and transportation. Despite increasing academic investigations of the role of IoT in the tourism industry from the traveller’s perspective, most studies have focused on the traveller’s behaviour, experiences, and satisfaction. It is not clear how IoT affects traveller subjective well-being which is a quintessential element of individual decision-making in particular tourism markets. Therefore, the purpose of this study was to propose a theoretically integrated approach to understanding the influences of IoT on traveller subjective well-being in the context of city breaks. In doing so, the present study explored the factors and the extent to which IoT affect city break traveller subjective well-being on the basis of task-technology fit theory, expectation confirmation model, and Hofstede’s culture theory. A quantitative method was adopted in this study. Empirical data were collected from 2077 city break travellers, 1008 in the UK and 1069 in China. An integrated model was tested using the structural equation modelling (SEM) approach. The findings of the study revealed that the main factors that determine city break traveller subjective well-being towards the use of IoT are a combination of technological, emotional, personal, and contextual attributes. These findings contribute to the theoretical development of innovative technologies and traveller subjective well-being in general as well as enrich the literature regarding city break tourism. In addition, the study discusses some practical implications for the marketing of city break tourism with the use of IoT.
Investigating the influence of Internet of Things (IoT) on tourists’ subjective well-being: evidence from British and Chinese tourists in the context of city break
Hu, M. (Author). 6 Dec 2022
Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)