Driving location-based advertising success in hospitality apps: a synergistic analysis approach

Purpose This 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/approach Data 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. Findings Research 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/implications This 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/value Leaning 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.

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Publication Details

Journal
International Journal of Contemporary Hospitality Management
Published
2025-08-08
DOI
https://doi.org/10.1108/ijchm-06-2024-0913
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
4.20
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article

Driving location-based advertising success in hospitality apps: a synergistic analysis approach

Seyed Rajab Nikhashemi, Khaldoon Nusair, Michele Chiariello, Usamah F. Alfarhan et al.
1 citations
International Journal of Contemporary Hospitality Management
Digital Marketing and Social Media
4.20
article

Driving location-based advertising success in hospitality apps: a synergistic analysis approach

Seyed Rajab Nikhashemi, Khaldoon Nusair, Michele Chiariello, Usamah F. Alfarhan, Ali Tarhini
article en
1 citations

Abstract

Purpose This 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/approach Data 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. Findings Research 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/implications This 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/value Leaning 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.

International Journal of Contemporary Hospitality ManagementVol. 37(9)
Oxford Brookes University (GB), Northern Kentucky University (US), Florida Gulf Coast University (US), Vistula School of Hospitality (PL), Sultan Qaboos University (OM)
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Digital Marketing and Social Media
4.20
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