Abstract
China‘s ecotourism market has grown rapidly in the past decade and there has been a growing interest among Chinese ecotourists in taking overseas ecotourism trips. Despite the market size and potential, little has been known about the characteristics of the Chinese ecotourism market, in
particular, Chinese ecotourists‘ destination selection behaviour. Choosing an international travel destination often involves a complex decision process of which prediction of travel intention is one of the key issues facing ecotourism. Drawn from the Country Image literature and the Theory of Planned Behavior, this paper proposes a conceptual framework in which a number of
important factors are identified. It is hoped that this conceptual framework can help ecotourism marketers and operators develop a comprehensive understanding of Chinese ecotourists‘ travel intentions towards an international ecotourism destination, such as Australia.
particular, Chinese ecotourists‘ destination selection behaviour. Choosing an international travel destination often involves a complex decision process of which prediction of travel intention is one of the key issues facing ecotourism. Drawn from the Country Image literature and the Theory of Planned Behavior, this paper proposes a conceptual framework in which a number of
important factors are identified. It is hoped that this conceptual framework can help ecotourism marketers and operators develop a comprehensive understanding of Chinese ecotourists‘ travel intentions towards an international ecotourism destination, such as Australia.
Original language | English |
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Pages | 2 |
Number of pages | 1 |
Publication status | Published - 17 Jul 2016 |
Event | The 6th Advances in Hospitality, Tourism Marketing and Management Conference: New Trend, Latest Version, and Creative Idea - Guangzhou, China Duration: 14 Jul 2016 → 17 Jul 2016 |
Conference
Conference | The 6th Advances in Hospitality, Tourism Marketing and Management Conference |
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Country/Territory | China |
City | Guangzhou |
Period | 14/07/16 → 17/07/16 |