{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T11:10:57Z","timestamp":1771845057784,"version":"3.50.1"},"reference-count":80,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2019,2,6]],"date-time":"2019-02-06T00:00:00Z","timestamp":1549411200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["DTA"],"published-print":{"date-parts":[[2019,4,3]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Leisure and tourism activities have proliferated and become important parts of modern life, and the hotel industry plays a necessary role in the supply for and demand from consumers. The purpose of this paper is to develop guidelines for hotel service development by applying a service development approach integrating Kansei engineering and text mining.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The online reviews represent the voice of customers regarding the products and services. Consumers\u2019 online comments might become a key factor for consumers choosing hotels when planning their tourism itinerary. With the framework of Kansei engineering, this paper adopts text mining to extract the sets of Kansei words and hotel service characteristics from the online contents as well as the relationships among Kansei words, service characteristics and these two sets. The relationships are generated by using link analysis, and then the guidelines for hotel service development are proposed based on the obtained relationships.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The results of the present research can provide the hotel industry a comprehensive understanding of hotels\u2019 customers opinions, and can offer specific advice on how to differentiate one\u2019s products and services from competitors\u2019 in order to improve customer satisfaction and increase hotels\u2019 performance in the end. Finally, this study finds out the service development guidelines to meet customers\u2019 requirements which can provide suggestions for hotel managers. The implications both for academic and industry are also drawn based on the obtained results.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>Now, in the internet era, consumers can comment on their hotel living experience directly through the internet. The large amount of user-generated content (UGC) provided by consumers also provides chances for the hospitality industry to understand consumers\u2019 opinions through online review mining. The UGC with consumers\u2019 opinions to hotel services can be continuously collected and analyzed by hoteliers. Therefore, this paper demonstrates how to apply the hybrid approach integrating Kansei engineering and online review mining to hotel service development.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/dta-05-2018-0048","type":"journal-article","created":{"date-parts":[[2019,2,6]],"date-time":"2019-02-06T06:02:47Z","timestamp":1549432967000},"page":"33-57","source":"Crossref","is-referenced-by-count":27,"title":["Applying big data analytics to support Kansei engineering for hotel service 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