Drivers of Continuance Intention for Borrowing Using Digital Lending Applications: An Expectancy Confirmation Model Approach
Year: 2025
Type: article
Study design: Observational Study
Abstract: The rapid demand for credit, combined with advancements in Financial Technology (FinTech), has prompted the widespread adoption of Digital Lending Applications (DLAs), offering borrowers greater flexibility and access compared to traditional banking and microfinance services. Despite their growing popularity, concerns about high interest rates, hidden fees and usability issues may discourage continued usage. This study investigates how Perceived Cost (PC) and factors from the Expectancy Confirmation Model (ECM), including Perceived Usefulness (PU), Confirmation of Expectation (CONF) and Satisfaction (SAT), influence borrowers’ intentions to continue using DLAs. A survey-based methodology was employed, with purposive sampling yielding 349 valid responses from several states in India. We analysed the collected data using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) via IBM AMOS SPSS 23.0. The results we found show that despite perceived cost affecting user behaviour, borrowers prioritise overall platform functionality and user experience as opposed to the cost of credit services. We suggest that management of expectations is important in enhancing user satisfaction, which is key to promoting long-term engagement. These findings offer practical insights for FinTech providers seeking to improve retention and for policymakers striving to create a supportive regulatory environment for digital lending. Future research could extend this work by exploring pre-adoption behaviour, cross-cultural differences and the long-term impact of DLAs on financial well-being.
Source: SDMIMD Journal of Management
Authors: Naomy Nasambu, S. Santhosh Kumar
Institution: Cochin University of Science and Technology
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408949025