Designing a real-time data streaming technique for enhancing the effectiveness of destination selection
Year: 2016
Type: dissertation
Abstract: The effectiveness of tour destination selection is dependent on pre-visit information \nsources. As competition increases in the tourism industry, destination \norganisations need to improve current destination selection processes. Research \non current processes indicate that information sources accessed by potential \ntourists when making travel decisions may not be a true reflection of what the \ndestination is offering. Any negative difference between perceived images during \npre-visit and real images during the actual visit may result in poor destination \nreputation and dissatisfied customers. \nThis research addresses this gap by improving the process of destination selection \nusing a real-time data streaming mediation technique as an additional pre-visit \ninformation source. The researcher adopted a social-technologist research \nparadigm and a design-science approach. The research process was executed in \nthree phases; the first phase focused on gathering knowledge on destination \nselection and pre-visit information sources. The findings in Phase 1 were used in \nPhase 2 to develop and test the performance of a prototype. Phase 3 involved the \nevaluation of the prototype tool in a real-world setting. \nOne of the main outcomes of this research is the development of a destination \nselection framework using real-time data streaming mediation and a tool \n(http://www.tourcamportal.com) as proof of concept. This research has shown that \nreal-time images are valuable pre-visit information sources when making travel \ndecisions. Real-time images authenticate destination attractions, provide real-time \navailability of destinations, reduce speculations on destination attractions, and \nprovide actual representations of destinations. The findings of this study contribute \nthe body of knowledge and practice in the tourism sector and provide new areas \nfor further research.
Author: Stanley Muturi Githinji
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2578794644