Online food delivery services and behavioral intention: a meta-analytic structural equation modeling from the UTAUT perspective

Purpose The expanded UTAUT2 model has become a key tool for examining consumer behavior in the online food delivery (OFD) industry. However, prior research has shown mixed results concerning the interrelationships among the UTAUT2 constructs. This study aims to address these inconsistencies by applying a meta-analytic structural equation modeling (MASEM) approach to synthesize findings across multiple studies. Design/methodology/approach A meta-analytic structural equation modeling (MASEM) approach was employed, integrating data from 34 studies with a total sample of 14,539 participants. This method allowed for a comprehensive examination of the relationships among UTAUT2 constructs and their impact on behavioral intention in the OFD context. Findings The results revealed that all predictors, except for effort expectancy, significantly influence behavioral intention. Habit and price value emerged as the strongest determinants, emphasizing the importance of habitual usage and price value perceptions in consumer decision-making. While performance expectancy, facilitating conditions and price value had modest but statistically significant effects, social influence and hedonic motivation played relatively minor roles. Originality/value This study advances the theoretical framework of UTAUT2 in the context of OFD services by providing a synthesized perspective on its constructs. The findings offer practical insights for businesses to refine their strategies by prioritizing key drivers of consumer behavior, thereby enhancing competitiveness in the online food delivery market.

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Publication Details

Journal
Aslib Journal of Information Management
Published
2025-10-27
DOI
https://doi.org/10.1108/ajim-03-2025-0164
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

Online food delivery services and behavioral intention: a meta-analytic structural equation modeling from the UTAUT perspective

Louisa Lee, Heetae Cho, Weisheng Chiu
Aslib Journal of Information Management
Technology Adoption and User Behaviour
article

Online food delivery services and behavioral intention: a meta-analytic structural equation modeling from the UTAUT perspective

Louisa Lee, Heetae Cho, Weisheng Chiu
article en

Abstract

Purpose The expanded UTAUT2 model has become a key tool for examining consumer behavior in the online food delivery (OFD) industry. However, prior research has shown mixed results concerning the interrelationships among the UTAUT2 constructs. This study aims to address these inconsistencies by applying a meta-analytic structural equation modeling (MASEM) approach to synthesize findings across multiple studies. Design/methodology/approach A meta-analytic structural equation modeling (MASEM) approach was employed, integrating data from 34 studies with a total sample of 14,539 participants. This method allowed for a comprehensive examination of the relationships among UTAUT2 constructs and their impact on behavioral intention in the OFD context. Findings The results revealed that all predictors, except for effort expectancy, significantly influence behavioral intention. Habit and price value emerged as the strongest determinants, emphasizing the importance of habitual usage and price value perceptions in consumer decision-making. While performance expectancy, facilitating conditions and price value had modest but statistically significant effects, social influence and hedonic motivation played relatively minor roles. Originality/value This study advances the theoretical framework of UTAUT2 in the context of OFD services by providing a synthesized perspective on its constructs. The findings offer practical insights for businesses to refine their strategies by prioritizing key drivers of consumer behavior, thereby enhancing competitiveness in the online food delivery market.

Aslib Journal of Information Management
Metropolitan University (BD), Sungkyunkwan University (KR)
Openalex Percentile: Top 71%
Technology Adoption and User Behaviour
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