Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/943
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dc.contributor.authorKitsios, Fotis-
dc.contributor.authorKamariotou, Maria-
dc.contributor.authorKaranikolas, Panagiotis-
dc.contributor.authorGrigoroudis, Evangelos-
dc.date.accessioned2021-09-23T10:32:27Z-
dc.date.available2021-09-23T10:32:27Z-
dc.date.issued2021-
dc.identifier10.3390/app11178032en_US
dc.identifier.issn2076-3417en_US
dc.identifier.urihttps://doi.org/10.3390/app11178032en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/943-
dc.description.abstractBig data analytics provides many opportunities to develop new avenues for understanding hospitality management and to support decision making in this field. User-generated content (UGC) provides benefits for hotel managers to gain feedback from customers and enhance specific product attributes or service characteristics in order to increase business value and support marketing activities. Many scholars have provided significant findings about the determinants of customers’ satisfaction in hospitality. However, most researchers primarily used research methodologies such as customer surveys, interviews, or focus groups to examine the determinants of customers’ satisfaction. Thus, more studies must explore how to use UGC to bridge the gap between guest satisfaction and online reviews. This paper examines and compares the aspects of satisfaction and dissatisfaction of Greek hotels’ guests. Text analytics was implemented to deconstruct hotel guest reviews and then examine their relationship with hotel satisfaction. This paper helps hotel managers determine specific product attributes or service characteristics that impact guest satisfaction and dissatisfaction and how hotel guests’ attitudes to those characteristics are affected by hotels’ market positioning and strategies.en_US
dc.language.isoenen_US
dc.sourceApplied Sciencesen_US
dc.subjectFRASCATI::Social sciences::Economics and Businessen_US
dc.subjectFRASCATI::Social sciences::Economics and Business::Business and Managementen_US
dc.subject.othercustomer satisfactionen_US
dc.subject.otherinnovation managementen_US
dc.subject.otherhospitalityen_US
dc.subject.otherbig dataen_US
dc.subject.othertext miningen_US
dc.subject.otheronline reviewsen_US
dc.titleDigital Marketing Platforms and Customer Satisfaction: Identifying eWOM Using Big Data and Text Miningen_US
dc.typeArticleen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volume11en_US
local.identifier.issue17en_US
local.identifier.firstpage8032en_US
Appears in Collections:Department of Applied Informatics

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