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Consumers' intentions to use online shopping apps: A comparative analysis
Mingqiang He1, Thuy Dung Pham Thi2, Huy Mach Tran3
1Zhejiang Shuren University, No.8 Shuren street, Hangzhou, Zhejiang, China.
Acta Psychologica
|August 16, 2025
Summary
This study found that the Theory of Planned Behavior (TPB) and integrated models best predict online shopping app usage. Enhancing app features and user self-efficacy are key to increasing adoption.
Area of Science:
- Behavioral Economics
- Information Systems
- Consumer Psychology
Background:
- Understanding consumer adoption of online shopping apps is crucial in the digital economy.
- Existing models like TAM and TPB offer insights but may not fully capture adoption drivers.
- Integrating Task-Technology Fit (TTF) can provide a more comprehensive understanding.
Purpose of the Study:
- To empirically compare the predictive power of TAM, TPB, integrated TAM/TPB, and integrated TAM/TTF models.
- To identify key factors influencing consumers' intentions to use online shopping apps.
- To provide practical implications for enhancing online shopping app adoption.
Main Methods:
- Survey data collected from 293 online shopping app users in Vietnam.
- Structural Equation Modeling (SEM) using LISREL 12.
- Comparison of four theoretical models: TAM, TPB, TAM/TPB, and TAM/TTF.
Main Results:
- All four models demonstrated effectiveness in explaining usage intentions.
- The TPB and integrated TAM+TPB models showed the highest explanatory power.
- Self-efficacy and TTF, alongside perceived usefulness and attitude, significantly influenced usage intentions.
Conclusions:
- Integrated models incorporating self-efficacy and TTF offer superior explanatory power for online shopping app usage intentions.
- App characteristics like flexibility, interactivity, and compatibility are vital.
- Developers should focus on improving app features and boosting user self-efficacy to drive adoption.
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