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Purpose This study reviews existing research and current applications of artificial intelligence (AI) in the hospitality and tourism industry. It further proposes a new evaluation framework to inform the susceptibility of AI adoptions. Design/methodology/approach This is a synthesis and evaluation study that qualitatively summarizes and presents findings on AI applications in the hospitality and tourism industry. Current AI applications are rated using a seven-dimensional framework based on Rogers' (2003) diffusion theory. Findings AI adoption susceptibility in the hospitality and tourism industry varies based on the type of AI. Search/booking engines, virtual agents and chatbots rank high in the adoption susceptibility. Research limitations/implications This study bridges innovation diffusion theoretical underpinnings and AI applications. The findings support researchers, developers and managers in evaluating the adoption susceptibility of AI technologies in the hospitality and tourism industry. Originality/value This paper is among the few that focus on assessing AI adoption susceptibility in the hospitality and tourism industry. This paper develops a theory-based framework for systematically evaluating AI innovations in hospitality and tourism.
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Evaluating Nature-Based Tourism Destination Attractiveness with a Fuzzy-AHP Approach
Nature-based tourism attractiveness (NBTA) has yet to be assessed by coupling empirical measurement of supply and demand indicators with simultaneous assessment of tourist and tourism expert perspectives. Based on a guiding principle that the overall attractiveness of a tourism destination should combine the evaluation of existing resources or attractions and their perceived attractiveness, the purpose of this study is to develop and apply a novel methodological approach for assessing tourism attractiveness of nature-based destinations. This approach developed here combines an Analytic Hierarchy Process (AHP) with a Fuzzy Comprehensive Evaluation Method (FCEM). The resulting Fuzzy-AHP approach to NBTA was tested at the Changbai Mountain Biosphere Reserve, a popular nature-based tourism destination in China. The findings confirm that this Fuzzy-AHP approach is a more reliable and comprehensive method for evaluating the destination attractiveness than pre-existing approaches. In addition to theoretical contributions related to the merging of various approaches to assessing destination attractiveness and the development of a tool specific to nature-based tourism destinations, this work will be of interest to decision makers seeking more effective tools for planning, marketing, and developing nature-based tourism destinations.
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- Award ID(s):
- 1828822
- PAR ID:
- 10441828
- Date Published:
- Journal Name:
- Sustainability
- Volume:
- 14
- Issue:
- 13
- ISSN:
- 2071-1050
- Page Range / eLocation ID:
- 7584
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/su14137584
