Publication:
On Modeling of Responses Generated by Travel 2.0 Implementation: Fuzzy Rule-Based Systems

dc.authorscopusid57211930065
dc.authorscopusid57211265299
dc.authorscopusid24280759600
dc.contributor.authorBaşaran, M.A.
dc.contributor.authorDoǧan, S.
dc.contributor.authorKantarci, K.
dc.date.accessioned2020-06-21T12:18:12Z
dc.date.available2020-06-21T12:18:12Z
dc.date.issued2020
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Başaran] Murat Alper, Alanya Alaaddin Keykubat University, Alanya, Antalya, Turkey; [Dogan] Seden, Faculty of Tourism, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Kantarci] Kemal, Alanya Alaaddin Keykubat University, Alanya, Antalya, Turkeyen_US
dc.description.abstractPurpose: Web 2.0 applications enable travelers to evaluate several services and assessment attributes. Constructed websites in several languages trigger a new way of data collections resulting in data streams leading to the accumulation of vast amounts of data, called big data. The need for analysis is in high demand. This study aims to construct a model to investigate which single attribute or interrelated ones having an impact on the performances of hotels. Design/methodology/approach: The total number of 1,137 observations collected from the website HolidayCheck.de are used from the hotels in the Bavaria region in 2016. Bavaria is a region where both domestic and foreign travelers mostly prefer to visit. Fuzzy rule-based systems, which is a combination of fuzzy set theory (FST) and fuzzy logic, are used. Although the FST is used to convert linguistically expressed perceptions by travelers into mathematically usable data, fuzzy logic is used to construct a model between service attributes and price-performance (PP) to attain the set of single and interrelated attributes on the assessment of PP. Findings: No single attribute plays a key role in PP assessment. However, two or more interrelated combinations have different impacts on PP. For example, when “Food—Drink” and “Room” moves together from average to good level, PP reaches the highest level of assessment. Research limitations/implications: Accessibility to too much data is difficult. Practical implications: A model can be continuously run so that any changes can be observed during the incoming of data. Social implications: As the consumer reviews and ratings are the crucial source of information for other travelers, hoteliers must monitor and respond them on time in order to deal with the complaints. Originality/value: Travelers’ perceptions or evaluations are treated with a FST that measures the impression of human beings. New modeling enables researchers to observe not only any single attribute but also interrelated ones on the PP. © 2020, Emerald Publishing Limited.en_US
dc.identifier.doi10.1108/IJCHM-03-2019-0279
dc.identifier.endpage1522en_US
dc.identifier.issn0959-6119
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85081753561
dc.identifier.scopusqualityQ1
dc.identifier.startpage1503en_US
dc.identifier.urihttps://doi.org/10.1108/IJCHM-03-2019-0279
dc.identifier.volume32en_US
dc.identifier.wosWOS:000524831800001
dc.identifier.wosqualityQ1
dc.language.isoenen_US
dc.publisherEmerald Group Holdings Ltd.en_US
dc.relation.ispartofInternational Journal of Contemporary Hospitality Managementen_US
dc.relation.journalInternational Journal of Contemporary Hospitality Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBig Dataen_US
dc.subjectFuzzy Rules Based Systemsen_US
dc.subjectFuzzy Seten_US
dc.subjectHotel Attributesen_US
dc.subjectPrice-Performanceen_US
dc.subjectWeb 2.0en_US
dc.titleOn Modeling of Responses Generated by Travel 2.0 Implementation: Fuzzy Rule-Based Systemsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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