Exploring the Barriers to Public Transport App Adoption Using Innovation Resistance Theory
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Background: The adoption of digital solutions in public transportation has transformed mobility services worldwide. However, resistance to innovation remains a significant challenge, preventing the successful implementation of transport applications. Despite advancements in mobile technology and smart transit solutions, many users remain hesitant to adopt new applications due to various barriers, including information quality concerns.
Objective: This study aims to investigate the relationship between information quality and innovation resistance in the adoption of public transport applications. Utilizing the Innovation Resistance Theory (IRT), this research examines how different resistance factors impact the intention to use transport apps.
Methods: A mixed-methods approach was applied, consisting of a quantitative survey with 443 respondents from an urbanized region and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). Additionally, qualitative insights were gathered through interviews with 30 individuals, analyzed using content analysis.
Results: Findings indicate that information quality significantly reduces innovation resistance, facilitating the adoption of transport applications. Moreover, usage barriers, value barriers, and tradition barriers negatively affect users’ intention to use transportation apps, while risk, image, and complexity barriers show no significant influence.
Conclusion: This study underscores the critical role of information quality in overcoming resistance to innovation in public transportation applications. The findings provide insights for app developers to enhance data accuracy and usability, as well as for policymakers to improve digital transportation services by addressing key resistance factors.
Keywords: Public Transport App, Innovation Resistance, M-Commerce, Intention to Use, Innovation Resistance Theory, Information Quality, PLS-SEM
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