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Cited by 288

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Artificial intelligence and big data in tourism: a systematic literature review

Samara, Dimitra, Magnisalis, Ioannis, Peristeras, Vassilios·2020·Journal of Hospitality and Tourism Technology

Abstract

Purpose: This paper aims to research, identify and discuss the benefits and overall role of big data and artificial intelligence (BDAI) in the tourism sector, as this is depicted in recent literature. Design/methodology/approach: A systematic literature review was conducted under the McKinsey’s Global Institute (Talwar and Koury, 2017) methodological perspective that identifies the four ways (i.e. project, produce, promote and provide) in which BDAI creates value. The authors enhanced this analysis methodology by depicting relevant challenges as well. Findings: The findings imply that BDAI create value for the tourism sector through appropriately identified disseminations. The benefits of adopting BDAI strategies include increased efficiency, productivity and profitability for tourism suppliers combined with an extremely rich and personalized experience for travellers. The authors conclude that challenges can be bypassed by adopting a BDAI strategy. Such an adoption will stand critical for the competitiveness and resilience of existing established and new players in the tourism sector. Originality/value: Besides identifying the benefits that BDAI brings in the tourism sector, the research proposes a guidebook to overcome challenges when introducing such new technologies. The exploration of the BDAI literature brings important implication for managers, academicians and consumers. This is the first systematic review in an area and contributes to the broader e-commerce marketing, retailing and e-tourism research.

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Crossref · 10.1108/jhtt-12-2018-0118

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Metadata

Authors
Samara, D., Magnisalis, I., & Peristeras, V.
Venue
Journal of Hospitality and Tourism Technology
Publisher
Emerald
Published
2020-05-29
Volume
11
Issue
2
Pages
343-367
ISSN
1757-9880 (ISSN-L)
OpenAlex
W3034283122
Cited by
288
References
2
FWCI
3.16
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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