TROPICAL GEOGRAPHY ›› 2019, Vol. 39 ›› Issue (2): 278-287.doi: 10.13284/j.cnki.rddl.003111

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Preference Structure of Tourism Destination Image: Based on the Q-Method

Lin Yuxia and Lin Bishu   

  1. (School of Management, Xiamen University, Xiamen 361005, China)
  • Online:2019-03-05 Published:2019-03-05

Abstract:

There are similarities and differences among different groups in destination image preferences. They can significantly influence the tourism destination marketing. Finding out what kind of tourism destination image people like, and the compatibility in different kinds of destination images makes sense especially to marketers. They can conduct targeted publicity and tourism product development according to the market demand preference, making tourism products more marketable. In addition, the compatibility in destination image preference has a significant meaning in the design of tourism routes. Students and working adults constitute an important part of the tourism market. Thus, it is of great significance to study the preference of these young groups. Knowing and producing what they prefer would be a great incentive to turn potential tourists into actual tourists. The present study uses the Q technique to verify the structure and compatibility of tourism destination image preferences, in order to provide suggestions for the design of tourism destination images and tourism routes. Q skill is a type of research method that can extract and describe subjective points of view. The method is a system with rigorous quantitative and quantitative analysis. It holds the view that subjective point of view possesses a certain structure. Thus, the Q-method can be used to conduct a qualitative and quantitative research on tourism destination image, which can help to break through the bottleneck of destination image research. Taking the students and the working group as the main research participants, the paper classified this young-group’s preferences of tourist destination image based on the Q-method. The P sample of this article included undergraduates, graduates, and working people, so it had a certain universality. A total of 106 questionnaires were distributed, but the effective sample amount was 82. The study results showed that there are five kinds of typical tourist destination image preference structures, and there exists incompatibility between the different kinds of tourism destination images. The five kinds of preference structures were named Natural Ecotourism, City Tourism, Natural and Cultural Tourism, Wandering Tourism, and Adventure Tourism. The classification could explained 55% of the variance. The characteristics of these preference structures are as follows: 1) The Natural Ecotourism people prefer natural resources but didn’t like culture resources and challenging tourism activities; 2) the City Tourism people turned out to be quite different than the first one, they prefer tourism activities in modern cities and other activities related to nature; 3) the Natural and Cultural Tourism people, female dominated, liked both cultural and natural tourism, but didn’t like rural tourism, as well as some extreme tourism activities; 4) the Wandering people preferred quiet places to enjoy; 5) while the Adventure Tourism people pursuit refreshing feelings and stimulating activities. Different kinds of preference structures for tourism destination images have different enlightening meanings to tourism marketing practices, which are provided at the end of this paper. In addition, a consensus statements analysis showed that these groups do not like massive cultural experiences. However, relaxing and interactive cultural experiences can improve the appeal of cultural destinations to the youth market. The five types of preference structures have high degree of differentiation, and the corresponding characteristics are significant. The results of the study have high reference value for both travel destination image marketing and tourism circuit design.

Key words: tourism destination image, preference structure, marketing, Q-method