Abstract
PurposeThis study aims to investigate location-based advertising (LBA) in the hospitality sector. Using the elaboration likelihood model (ELM) and expectancy value theories (EVTs) proposes a comprehensive framework to understand the success factors of LBA apps and their consequences.Design/methodology/approachData from 406 hospitality app users were analyzed using structural equation modeling and probabilistic analysis to validate relationships among core variables. Spotlight analysis was also applied to examine the moderating effect of location context quality across varying levels.FindingsResearch indicates that success factors such as personalization, incentives and navigation support enhance user engagement through the ELM. These factors align with user expectations and perceived value (EVT), leading to outcomes like message permission consent and LBA acceptance. Spotlight analysis highlights the moderating role of location contextual quality, suggesting that high relevance amplifies the impact of message value on user attitudes, providing key insights for LBA in hospitality. EVT posits that expected benefits encourage positive behaviors, reinforcing personalization, incentives and contextual relevance as crucial for user acceptance. The probabilistic analysis validates these factors as drivers of both immediate (first-tier) and sustained (second-tier) positive outcomes.Research limitations/implicationsThis study guides hospitality marketers by identifying key app features that drive LBA acceptance. Hospitality apps enhance user engagement and acceptance through personalization, incentives, prior permission and contextual relevance. Based on ELM and EVT, the study's two-tier model captures both immediate and long-term user responses, emphasizing central and heuristic processing. Spotlight analysis underscores the significance of contextual quality and data-driven strategies.Originality/valueLeaning on the foundations of the ELM and EVTs, this study develops a comprehensive theoretical model that enhances the knowledge pertaining to marketing communication in hospitality through the LBA approach. In addition, applying probabilistic analysis provides strategic guidance for decision-makers on key variables to optimize LBA acceptance among app users.