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An ex-ante evaluation of marketing policies to improve itinerary service

Bibliographic Data

ID21699900
AuthorsTsung-Hsien Tsai (0000-0003-0356-6053, National Quemoy University), Chien-Min Chen (National Quemoy University), Chien‐min Chen (0000-0003-0343-8780, National Quemoy University, corresponding author)
Year2021
Volume24
Issue13
Pages1856-1879
Publication date2021-07-03
Open AccessNo
TypeARTICLE
VenueCurrent Issues in Tourism (JOURNAL)
Journal identifiersISSN: 1368-3500 • E-ISSN: 1747-7603
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/13683500.2020.1806792
OpenAlexW3080795516
LanguageEN
References cited82

Tourism activities derived from specific themes are getting popular in the market; nevertheless, extant or novel service content in the itinerary is not always appreciated by tourists. This study aims to propose an analytic tool for evaluating prospective policies so that tourism operators can expect potential effects before official implementation. A stated-preference experiment is utilized to explore tourists’ responses given various scenarios. Eight potential attributes including theme explanation, destination authenticity, activities, events, souvenirs, gastronomy delight, length of itinerary, and monetary cost are examined using Chinese ancient scholar/scholarship as an example. The collected responses are analysed via logit-based choice models. The modelling results show that the latent class model with three segmented groups is capable of explaining respondents’ choices. Each segment of respondents has shown distinct preferences toward the service attributes. The constructed model is then applied to conduct ex-ante evaluations. The simulation of choice probabilities reveals positive effects of conducting service improvement, shows necessity to stay ahead in the market, and also indicates trade-off effects if fees are raised

Advertising · Business · Economics · Ex-ante · Extant taxon · Latent class model · Microeconomics · Political science · Preference · Salient · Scholarship · Tourism · Computer Science · Customer Service Quality and Loyalty · Digital Marketing and Social Media · Diverse Aspects of Tourism Research · Marketing

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