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dc.contributor.authorAcar, Ayşegül
dc.contributor.authorTürten, Burak
dc.contributor.authorDiker, Ersin
dc.date.accessioned2024-09-30T06:01:01Z
dc.date.available2024-09-30T06:01:01Z
dc.date.issued2024en_US
dc.identifier.citationScopus EXPORT DATE: 30 September 2024 @ARTICLE{Acar2024, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201003812&doi=10.1080%2f1528008X.2024.2386590&partnerID=40&md5=1be136d9730acfc471716d9c368227e5}, affiliations = {Department of Recreation Management, Karabuk University, Karabuk, Turkey; Department of Radio, Television and Cinema, Karabuk University, Karabuk, Turkey; Department of Public Relations, Gümüşhane University, Gümüşhane, Turkey}, correspondence_address = {A. Acar; Department of Recreation Management, Karabuk University, Safranbolu, Karabuk, Turkey; email: aysegulacar@karabuk.edu.tr}, publisher = {Routledge}, issn = {1528008X}, language = {English}, abbrev_source_title = {J. Qual. Assur. Hosp. Tour.} }en_US
dc.identifier.issn1528008X
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85201003812&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=5cb5e4aba52731540225b01cefcf467a
dc.identifier.urihttps://www.tandfonline.com/doi/epdf/10.1080/1528008X.2024.2386590?src=getftr
dc.identifier.urihttps://hdl.handle.net/20.500.12440/6329
dc.description.abstractService robots are becoming more prevalent in the service industry, yet the impact they have on customer experiences is not well-documented. This study identified consumer emotions toward service robots in hotels and restaurants, focusing on how specific attributes of these robots affect consumer emotions. Furthermore, it explored which countries generate the most comments on these service robot attributes and the nature of consumer emotions within these regions. Utilizing sentiment analysis, the study examined 52,513 English-language tweets about hotel and restaurant service robots. Additionally, logistic regression analysis helped quantify the impact of robot attributes–categorized as physical, functional, and relational–on different classes of emotions. The findings reveal that customers of restaurants and hotels were most influenced by the physical and relational attributes of service robots, respectively, with functional attributes having the least impact. The logistic regression analysis offered significant insights into how service robot attributes influence consumer experiences in hotels and restaurants. © 2024 Taylor & Francis Group, LLC.en_US
dc.language.isoengen_US
dc.publisherRoutledgeen_US
dc.relation.ispartofJournal of Quality Assurance in Hospitality and Tourismen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjecthotel and restaurant industry; sentiment analysis; service robots; Twitter; Worden_US
dc.titleAspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industryen_US
dc.typearticleen_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US
dc.departmentFakülteler, İletişim Fakültesi, Halkla İlişkiler ve Tanıtım Bölümüen_US
dc.authorid0000-0002-3973-0639en_US
dc.contributor.institutionauthorDiker, Ersin
dc.identifier.doi10.1080/1528008X.2024.2386590en_US
dc.authorscopusid57219193584en_US


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