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Digital marketing platforms and customer satisfaction: identifying eWOM using big data and text mining

Kitsios Fotios, Kamariotou Maria, Karanikolas Panagiotis, Grigoroudis Evangelos

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URIhttp://purl.tuc.gr/dl/dias/56116D04-A2AB-46F7-A4B2-30512837213F-
Αναγνωριστικόhttps://doi.org/10.3390/app11178032-
Αναγνωριστικόhttps://www.mdpi.com/2076-3417/11/17/8032/htm-
Γλώσσαen-
Μέγεθος12 pagesen
ΤίτλοςDigital marketing platforms and customer satisfaction: identifying eWOM using big data and text miningen
ΔημιουργόςKitsios Fotiosen
ΔημιουργόςΚιτσιος Φωτιοςel
ΔημιουργόςKamariotou Mariaen
ΔημιουργόςKaranikolas Panagiotisen
ΔημιουργόςGrigoroudis Evangelosen
ΔημιουργόςΓρηγορουδης Ευαγγελοςel
ΕκδότηςMDPIen
ΠερίληψηBig 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
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2022-10-06-
Ημερομηνία Δημοσίευσης2021-
Θεματική ΚατηγορίαCustomer satisfactionen
Θεματική ΚατηγορίαInnovation managementen
Θεματική ΚατηγορίαHospitalityen
Θεματική ΚατηγορίαBig dataen
Θεματική ΚατηγορίαText miningen
Θεματική ΚατηγορίαOnline reviewsen
Βιβλιογραφική ΑναφοράF. Kitsios, M. Kamariotou, P. Karanikolas, and E. Grigoroudis, “Digital marketing platforms and customer satisfaction: identifying eWOM using big data and text mining,” Appl. Sci., vol. 11, no. 17, Aug. 2021, doi: 10.3390/app11178032.en

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