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Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background

Mariani, M., Di Fatta, G. and Di Felice, M. (2019) Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background. IEEE Access, 7. pp. 8195-8208. ISSN 2169-3536

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To link to this item DOI: 10.1109/ACCESS.2018.2887300

Abstract/Summary

User-generated content and online reviews are becoming an increasingly relevant source of information for online customers that use them for purchasing decisions. This study examines the impact of services attributes and consumers’ cultural background on customer satisfaction with services in an online setting using big data. First, almost half a million Expedia.com hotel online reviews related to hotel properties located in five different countries (United States, United Kingdom, Italy, Spain, Russia) were retrieved. Second, the resulting dataset was used to investigate if and to what extent the overall customer satisfaction with a service is affected by the evaluation of specific hotel services attributes (operationalized based on an established typology of attributes) and by the consumers’ cultural background (operationalized by means of Hoftstede’s framework). A comprehensive multivariate regression analysis is carried out to test the literature-driven hypotheses formulated. In particular, the analysis reveals that critical service attributes such as hotel condition, room comfort, service and staff, and cleanliness positively affect the overall online satisfaction ratings. The cultural dimensions of power distance, individualism and uncertainty avoidance negatively affect overall online satisfaction, while long-term orientation and indulgence positively affect online satisfaction. Masculinity seem not to play a significant role. We also observe that reviews’ text length exerts a negative impact on online ratings. Theoretical and practical implications are discussed.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > Leadership, Organisations and Behaviour
ID Code:81391
Publisher:IEEE

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