Exploring Service Quality and Consumer Acceptance of Autonomous Convenience Stores
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Background: Automation is revolutionizing retail operations, leading consumers to increasingly interact with advanced retail technologies. While there have been studies on the influence of service quality on consumer acceptance, research examining the service quality of hybrid services and consumer acceptance in automated retail is limited.
Objective: This study aims to examine consumer acceptance of automated retail stores.
Methods: This study tested a proposed model by surveying 101 consumers and using a questionnaire for hypothesis testing. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the effect of e-service quality dimensions on technology acceptance (perceived ease of use, perceived usefulness, and behavior intention) in the context of unmanned automated retail stores.
Results: The findings reveal that information quality positively affects perceived ease of use, while system quality positively affects perceived usefulness.
Conclusion: This study generates new insights by incorporating e-service quality dimensions from the E-Service Quality model into the Technology Acceptance Model. Additionally, the results highlight the growing importance of seamless digital experiences and reliable systems in shaping user perceptions and behavioral intentions. These findings offer practical implications for retailers aiming to enhance customer satisfaction and adoption of unmanned retail technologies through improved service design and digital infrastructure. Future research can further explore other influencing factors such as trust, perceived risk, and user demographics to better understand the evolving dynamics of consumer-technology interaction in automated retail environments.
Keywords: artificial intelligence; autonomous convenience store; consumer acceptance; e-service quality; technology acceptance model
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