Enhancing Technology Acceptance through User Experience Evaluation: Comparative Analysis of Banking Website Versus Mobile Application

Dasharathraj K. Shetty, Jumleena Bhagawati, Shreya Shetty, Lewlyn L.R. Rodrigues*, Arun Kumar, Prithvi Tilwani, Manjunath K. Vanahalli, B. Kishore, Anuradha Rao, M. Namesh, Shreyansh Chaabra, Krishnamoorthi Makkithaya, Nithesh Naik, Girish Nair

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Despite the high rate of technology adoption in banking services, there is still a void in the literature on technology adoption and diffusion in this area, and hence, the purpose of this paper is to analyze the comparative user behavior of two different banking platforms, namely Banking Websites and Mobile Applications in India. The theoretical underpinning for the empirical validation is the Technology Acceptance Model (TAM). The research is based on the quantitative analysis with a sample size of 304 and 411 customers in the aforementioned banking platforms respectively. The Structural Equation Modelling (SEM) has been adopted as the technique of analysis. Results indicate that among the ten variables of study behavioral intention, dependability, efficiency, and perspicuity have similar effect on the technology acceptance, and rest of the variables differ in their impact with respect to the two platforms under comparison. Implication of the study is that both the platforms need to focus on the aforementioned variables during the system design as they are crucial in connection to the actual usage of the system. The outcome of this research could be of use to academicians, system designers, and application developers.

Original languageEnglish
Pages (from-to)154@166
JournalEngineered Science
Volume19
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Physical and Theoretical Chemistry
  • Chemistry (miscellaneous)
  • General Materials Science
  • Energy Engineering and Power Technology
  • Artificial Intelligence
  • Applied Mathematics

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