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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/56116D04-A2AB-46F7-A4B2-30512837213F | - |
| Identifier | https://doi.org/10.3390/app11178032 | - |
| Identifier | https://www.mdpi.com/2076-3417/11/17/8032/htm | - |
| Language | en | - |
| Extent | 12 pages | en |
| Title | Digital marketing platforms and customer satisfaction: identifying eWOM using big data and text mining | en |
| Creator | Kitsios Fotios | en |
| Creator | Κιτσιος Φωτιος | el |
| Creator | Kamariotou Maria | en |
| Creator | Karanikolas Panagiotis | en |
| Creator | Grigoroudis Evangelos | en |
| Creator | Γρηγορουδης Ευαγγελος | el |
| Publisher | MDPI | en |
| Content Summary | Big 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 |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2022-10-06 | - |
| Date of Publication | 2021 | - |
| Subject | Customer satisfaction | en |
| Subject | Innovation management | en |
| Subject | Hospitality | en |
| Subject | Big data | en |
| Subject | Text mining | en |
| Subject | Online reviews | en |
| Bibliographic Citation | F. 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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