| Summary: | 碩士 === 國立東華大學 === 自然資源與環境學系 === 102 === Tourists’ choice of tourist destination and their tourism behaviors are mainly affected by destination image. If we can understand the formation of destination image and the tourism behavior elements generated from influences of such image, we’ll be able to design recreational activities that satisfy tourists’ demands. This paper makes a research on Taroko National Park, which is representative of natural resources, historical culture and tourism. It adopts factor analysis as theassessment method to extract factors concerning tourists’ cognition of the destination (Taroko National Park) image (e.g. cognitive factors, emotional factors and unique factors), uses cluster analysis to divide different groups of destination images, and further utilizes cross-over analysis to investigate different national park destination image groups’ differences in tourism behavior, experience quality and social and economic backgrounds. Then, travel cost method is used to construct a model of national park’s recreational demands, and above-described destination image groups are integrated into the model. The appropriate On-Site Poissonmodel of count data model is utilized to estimate the model of Taroko National Park’s recreational demand; factors affecting such demands are also analyzed. Finally, contingent behavior approach is used to establish model ofTaroko National Park’s tourism demands; four kinds of schemes that enhance Taroko National Park travel quality are proposed: “improving infrastructure”, “increasing service quality”, “strengthening profession of interpretation” and “intensifying environmental management”. Under these four schemes, Panel recreational demand model is adopted to analyze relevant factors that influence tourists’ recreational needs; different national park destination image groups’ differences in recreational benefit, price flexibility and income elasticity are further estimated. This study obtained four empirical results.First, a cluster analysis identified four clustered segments for five destination image factors in which the multi-purpose image seekers were found to be the most important segment. Second, destination image clusters differ significantly in terms of national park demands.Third,the “natural-attraction image clusters” has the highest CS values than other destination image clusters.Fourth, “travel quality enhancement scheme” can significantly increase economic benefits of Taroko National Park. Especially, “improvement in service quality” makes the greatest contribution to recreational benefit enhancement. Results of this study will not only help Taroko National Park know tourists’ recreational demand behaviors in the park and formulate tourism destination marketing strategies, but also assist in national park recreation resource management and planning as well as budget allocation.
|
|---|
