Shamim, Saqib (2021) Big data management capabilities in the hospitality sector: Service innovation and customer generated online quality ratings. Computers in Human Behavior, 121 (106777). Article Number 106777. ISSN 0747-5632. (doi:10.1016/j.chb.2021.106777) (KAR id:87288)
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Official URL: https://doi.org/10.1016/j.chb.2021.106777 |
Abstract
Despite the wide usage of big data in tourism and the hospitality sector, little research has been done to understand the role of organizations’ capability of managing big data in value creation. This study bridges this gap by investigating how big data management capabilities lead to service innovation and high online quality ratings. Instead of treating big data management as a whole, we access big data management capabilities at the strategic and operational level. Using a sample of 202 hotels in Pakistan, we collected the primary data for big data capabilities, knowledge creation and service innovation; the secondary data about quality rating were collected from Booking.com. Structural equation modelling through Smart PLS was used for data analysis. The results indicated that big data management capabilities lead to high online quality ratings through the mediation of knowledge creation and service innovation. We contribute to the current literature by empirically testing how strategic level big data capabilities enable the firm to add value in innovativeness and positive online quality ratings through acquiring, contextualizing, experimenting and applying big data.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.chb.2021.106777 |
Uncontrolled keywords: | Big data management; Dynamic capabilities; Service innovation; Knowledge creation; Customer generated online quality rating; Hospitality |
Divisions: | Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business |
Depositing User: | Saqib Shamim |
Date Deposited: | 23 Mar 2021 17:32 UTC |
Last Modified: | 05 Nov 2024 12:53 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/87288 (The current URI for this page, for reference purposes) |
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