|Author:||Lau, Wai-chi Gigi|
|Title:||Mapping tourist movement patterns : a GIS approach|
|Subject:||Hong Kong Polytechnic University -- Dissertations.|
Tourism -- Research.
Travel -- Research.
Geographic information systems.
|Department:||School of Hotel and Tourism Management|
|Pages:||xi, 236 leaves : ill., maps ; 30 cm.|
|Abstract:||Intradestination movements are characterized by the directions and places where tourists visit within a local destination. They can be illustrated by the activities participated in or attractions visited by tourists. Limited prior research has been conducted on this subject. The main focus of this research is, therefore, to explore the movement patterns within a local destination and to examine them in relation to personal motives, destination characteristics and time. The research studied Fully Independent Tourists (FIT) for they demonstrate greater flexibility in their movements than those on package tours. They have better control over their own time and neither follow pre-set tour itineraries nor are directed by guides. Studying the movement patterns of FIT has pragmatic applications to Hong Kong, enabling tourism marketers and destination management organizations, such as Hong Kong Tourism Board, to better plan and to manage tourism products and attractions. Through identifying tourist movement patterns and the variables affecting them, destination management organizations can better understand the interests and expectations of the FIT. It also helps to evaluate and to estimate the activities and attractions that should be provided in the destination. Data were collected through a three stage process, involving: arrival interviews, self-completed trip diaries and departure survey. Trip profile, motivations and demographic information were collected from the arrival interview. Data regarding tourist day-to-day travel itinerary were collected by trip diaries. The data collection process has been completed yielding a viable database of 250 participants from 4 different hotels neighboring to each other. Tourists were asked to record their journey on a daily basis yielding a viable data base of 930 daily itinerary routes for analysis. Survey data were analyzed by using SPSS, while trip diary data were analyzed by using GIS software. The analysis aims to identify movement patterns and to identify underlying variables affecting tourists' decisions on visitation itineraries. A total of 78 movement patterns emerged from the analysis. Further analysis has been done to eliminate the great diversity and complexity of the movement patterns identified. Examination between variables affecting tourist movements and patterns could facilitate the understanding of tourist behavior within local destination. The 78 patterns were further collapsed into 10 styles in which variables affecting movement patterns were taken into account, including trip profile, motivations, planned activities and demographic characteristics. This study serves as a pioneer exploratory research in the topic and filling the gap in the literature.|
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