Factors affecting consumer intentions and actual behavior: A case of food delivery applications

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Customers and food vendors communicate directly through mobile devices. Consumers easily purchase pre-prepared meals via food delivery applications, no matter where they are, even at the convenience of their residences. Therefore, this paper aims to analyze the determinants that affect customers’ propensity to purchase and their actual behavior in the setting of food delivery applications. The impact that subjective norms have on consumers’ attitudes toward food ordering via food delivery applications is also examined. The theory of reasoned action and prospect theory are the two basic theories that this study draws on. A convenience sample approach was used to gather data from 288 consumers in Vietnam who placed meal orders using food delivery applications. The data collection was conducted using Google Forms. The results indicated that consumers’ attitude toward purchasing food via food delivery applications positively influenced their buying propensity (β = 0.191, p = 0.001). Similarly, the findings also highlighted that consumers’ subjective norm positively affected both their attitude (β = 0.417, p = 0.000) and their inclination to purchase (β = 0.258, p = 0.000). Likewise, discount framing emerged as the most influential factor affecting purchase intentions (β = 0.262, p = 0.000). Furthermore, customers’ intentions significantly contributed to their actual behavior in acquiring pre-prepared meals through food delivery applications (β = 0.556, p = 0.000). Ultimately, the study offered suggestions for executives, identified limits, and proposed avenues for future research.

Acknowledgment
The author acknowledges Industrial University of Ho Chi Minh City that supported this study.

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  • JEL Classification (Paper profile tab)
    M10, M30, M31
  • References
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  • Tables
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  • Figures
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    • Figure 1. Research model
    • Figure 2. PLS results
    • Table 1. Respondent demographics
    • Table 2. Measurement scales results
    • Table 3. Cross loadings
    • Table 4. Results of hypotheses testing
    • Conceptualization
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