The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry.

Artificial intelligence Facial recognition Organizational information processing theory Travel and tourism industry Value

Journal

Information systems frontiers : a journal of research and innovation
ISSN: 1387-3326
Titre abrégé: Inf Syst Front
Pays: United States
ID NLM: 101685853

Informations de publication

Date de publication:
2023
Historique:
accepted: 14 03 2022
medline: 10 5 2022
pubmed: 10 5 2022
entrez: 9 5 2022
Statut: ppublish

Résumé

This study aims to investigate the role of artificial intelligence (AI) driven facial recognition to enhance a value proposition by influencing different areas of services in the travel and tourism industry. We adopted semi-structured interviews to derive insights from 26 respondents. Thematic analysis reveals the development of four main themes (personalization, data-driven service offering, security and safety, and seamless payments). Further, we mapped the impact of AI- driven facial recognition to enhance value and experience for corporate guests. Findings indicate that AI-based facial recognition can facilitate the travel and tourism industry in understanding travelers' needs, optimization of service offers, and value-based services, whereas data-driven services can be realized in the form of customized trip planning, email, and calendar integration, and quick bill summarization. This contributes to strengthening the tourism literature through the lens of organizational information processing theory.

Identifiants

pubmed: 35529102
doi: 10.1007/s10796-022-10271-8
pii: 10271
pmc: PMC9059456
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1179-1195

Informations de copyright

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.

Déclaration de conflit d'intérêts

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Shivam Gupta (S)

Department of Information Systems, Supply Chain Management & Decision Support, NEOMA Business School, 59 Rue Pierre Taittinger, 51100 Reims, France.

Sachin Modgil (S)

Department of Operations Management, International Management Institute (IMI) Kolkata, 2/4 C, Judges Ct Rd, Alipore, Kolkata, West Bengal 700027 India.

Choong-Ki Lee (CK)

College of Hotel & Tourism Management, Kyung Hee University, 26 Kyungheedae-ro, Hoegi-dong, Dongdaemun-gu, Seoul, South Korea.

Uthayasankar Sivarajah (U)

School of Management, University of Bradford, Richmond Road, Bradford, BD7 1DP UK.

Classifications MeSH