Drivers and inhibitors of consumers adoption of AI-driven drone food delivery services

Title

Drivers and inhibitors of consumers adoption of AI-driven drone food delivery services

Creator

Nunkoo R.; Pillai R.; Sivathanu B.; Rana N.P.

Description

This study sheds light on the determinants of consumers adoption of artificial intelligence-driven drone food delivery service (AI-driven DFDS) using a mixed-methods approach. Interviews with hospitality industry professionals revealed several drivers and inhibitors of AI-driven DFDS adoption. Using these findings, we developed a theoretical model AI-driven DFDS adoption based on the premise of the behavioral reasoning theory and innovation resistance theory. The model was tested using data collected from 1240 consumers. The results suggest that drones relative advantage, perceived ubiquity, social influence, and green image positively influence attitudes and adoption. Risk, usage, and experience barriers have an adverse influence on attitudes and adoption. Consumers openness to new technology has a positive influence on reasons for using AI-driven DFDS. The research makes an important theoretical contribution to research on the adoption of AI-driven DFDS. The study also provides important practical implications for marketers and industry professionals. 2024 Elsevier Ltd

Source

International Journal of Hospitality Management, Vol-123

Date

2024-01-01

Publisher

Elsevier Ltd

Subject

Artificial intelligence; Drone; Food delivery; Mixed methods

Coverage

Nunkoo R., Department of Management, University of Mauritius, Reduit, Mauritius, School of Tourism and Hospitality, University of Johannesburg, South Africa, Kyung Hee University, Campus, 26 Kyungheedae-ro, Dongdaemun-gu, South Korea, Griffith Institute for Tourism, Griffith University, Gold Coast, Australia, Copenhagen Business School, Denmark; Pillai R., Department of Management, Pune Institute of Business Management, Maharashtra, Pune, India; Sivathanu B., School of Business and Management, Christ University, Karnataka, Bengaluru, 560074, India; Rana N.P., Queen's Business School, Queen's University Belfast, Riddel Hall, 185 Stranmillis Road, Belfast, BT9 5EE, United Kingdom, Jaipuria Institute of Management Lucknow, Vineet Khand, UP, Lucknow, 226010, India

Rights

Restricted Access

Relation

ISSN: 2784319; CODEN: IJHMD

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1016/j.ijhm.2024.103913

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203665918&doi=10.1016%2fj.ijhm.2024.103913&partnerID=40&md5=83ba7360cc5a1866a35813b07f9a1ed0