Consumer Adoption of Location-Based Marketing in The Hospitality Industry: A Systematic Literature Review

Abstract

Consumer is the king of market. Companies have revised their policies, products, processes keeping the changing demands of consumers in centre. The hospitality sector has shifted from being relatively slow to adopt technology to rapidly embracing digital, automated, and smart systems especially since COVID-19. Location-based technologies have been widely adopted to determine where a person is and then deliver marketing based on that location. While the hospitality industry has normalized location-based marketing (LBM), the evidence of why consumers actually adopt it is scattered across disconnected literatures on hotel technology, tourism applications, and food delivery platforms. This systematic literature review synthesizes the empirical evidence on consumer LBM adoption in hospitality sectors, maps the theoretical domain of the field and highlights the major drivers and barriers to adoption. A systematic search of the Web of Science Core Collection was conducted following PRISMA 2020 guidelines, yielding 1,301 records, of which 74 empirical studies published between 2015 and 2025 were retained and synthesised through thematic narrative analysis. The Technology Acceptance Model and its extensions (27%) and UTAUT2 (12%) are the most dominant theories, with perceived usefulness (41%) and perceived ease of use (34%) the most studied predictors. Trust (23 %), social influence (27 %), hedonic value (26 %), and privacy concern (16 %) are recurring in the literature. In hospitality, LBM implementation differs from generic technology acceptance in a triad of trust-personalisation-privacy where personalisation increases privacy concerns and engenders trust, and trust is the decisive mediator of the net effect on adoption. Methodologically, the field is heavily skewed to structural equation modelling (74%) and quantitative cross-sectional designs (91%), with evidence from the United States (23%) and China (16%), and hotels (31%) and tourism (27%) dominating sectoral coverage. Major gaps are in cross-sector comparison, non-Western geographic representation, longitudinal designs and post-adoption behaviour. The review distils theoretical and practical implications for researchers and for hospitality managers grappling with the trade-off between personalized relevance and location data privacy.