Analysis of continuance intention towards construction project management apps via FTA–BN

This study investigates the factors influencing the continuous usage intention of Construction Project Management Applications (CPMApps) in Taiwan. Despite global digitalisation trends, CPMApps have seen limited long-term adoption in the local construction industry. To address this, this study employs a hybrid approach combining fault tree analysis (FTA) and Bayesian network (BN) to identify and quantify factors affecting user retention. FTA is used to build a hierarchical structure across three dimensions: APP interface, APP functionality, and customer service. This structure is converted into a BN for probabilistic analysis using expert-weighted and user-based performance evaluations data, and conditional and posterior probabilities were calculated. Results show a low overall posterior probability to continue using the CPMApps (3.8%), primarily due to poor interface usability, weak functionality, and backend inefficiencies. Contractors show higher retention intention, while supervisors report the lowest. Findings were qualitatively cross-checked against project management information system user feedback, providing supplementary contextual support for the identified failure modes. The study recommends improvements in interface design, data integration, and backend support, and calls for future research to explore external factors such as digital literacy and practices. These noteworthy findings offer practical guidance for developers and policymakers to enhance CPMApp adoption and long-term sustainability.