New face of platform capitalism in lodging industry: Who and where adopts platform-led loyalty tools?

Authors: Napierała, T., Tomczyk, A.T.

Journal: Tourism Economics

Publication Date: 01/01/2026

eISSN: 2044-0375

ISSN: 1354-8166

DOI: 10.1177/13548166261421402

Abstract:

Our study aims to identify segments of the lodging market influenced by platform capitalism, with a focus on the adoption of platform-led, AI-supported loyalty and marketing tools. The empirical objective is to examine the site-specific and situational factors that influence the variability in hoteliers’ willingness to adopt AI-supported loyalty and marketing tools offered by Online Travel Agents (OTAs), as exemplified by the Booking.com’s Genius programme. The analysis focusses on hotels, motels, and guesthouses that operate in Poland in 2024. The Random Forest Classifier was employed to identify feature-based impacts and spatial patterns in the adoption of OTA-led AI-supported loyalty and marketing tools. The findings suggest that the most popular hotels, located in metropolitan areas, offering higher-priced services and demonstrating greater awareness and knowledge of digital marketing and revenue management, are most likely to adopt OTA-led AI-supported loyalty and marketing tools.

https://eprints.bournemouth.ac.uk/41782/

Source: Scopus

New face of platform capitalism in lodging industry: Who and where adopts platform-led loyalty tools?

Authors: Napierała, T., Tomczyk, A.

Journal: Tourism Economics

Publication Date: 03/02/2026

Volume: 0

Issue: 0

Pages: 1-25

Publisher: SAGE

eISSN: 2044-0375

ISSN: 1354-8166

DOI: 10.1177/13548166261421402

Abstract:

Our study aims to identify segments of the lodging market influenced by platform capitalism, with a focus on the adoption of platform-led, AI-supported loyalty and marketing tools. The empirical objective is to examine the site-specific and situational factors that influence the variability in hoteliers’ willingness to adopt AI-supported loyalty and marketing tools offered by Online Travel Agents (OTAs), as exemplified by the Booking.com’s Genius programme. The analysis focusses on hotels, motels, and guesthouses that operate in Poland in 2024. The Random Forest Classifier was employed to identify feature-based impacts and spatial patterns in the adoption of OTA-led AI-supported loyalty and marketing tools. The findings suggest that the most popular hotels, located in metropolitan areas, offering higher-priced services and demonstrating greater awareness and knowledge of digital marketing and revenue management, are most likely to adopt OTA-led AI-supported loyalty and marketing tools.

https://eprints.bournemouth.ac.uk/41782/

Source: Manual