Sep 2026· Asia Pacific Journal of Marketing and Logistics· 0 citations· 61 references
Abstract
This study aims to examine how food quality and value are associated with revisit intention and loyalty in online food delivery through information credibility and technological congruence, and whether consumer innovativeness and restaurant familiarity condition these relationships.
Cross-sectional survey data from 506 US consumers with recent delivery-only restaurant experience were analyzed using partial least squares structural equation modeling. Importance-performance map analysis (IPMA) and fuzzy-set qualitative comparative analysis (fsQCA) provided complementary importance-performance and configurational evidence.
Food quality and value were indirectly associated with both outcomes through information credibility. Both indirect relationships through technological congruence were supported for revisit intention, but only the food quality relationship was supported for loyalty. Consumer innovativeness conditioned the food quality relationships, whereas restaurant familiarity conditioned the relationships between technological congruence and both outcomes. Information credibility had the greatest total IPMA importance, and fsQCA identified multiple configurations centered on food quality, value, and information credibility.
The study identifies an asymmetry across outcomes in the roles of information credibility and technological congruence in online food delivery (OFD) postadoption behavior. Information credibility provides a consistently supported pathway across revisit intention and loyalty, whereas technological congruence is more consistently associated with revisit intention and selectively associated with loyalty. Integrating source credibility, congruence, and diffusion of innovation perspectives clarifies how information credibility and technology fit operate differently across outcomes and under relationship-specific boundary conditions.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
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