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Article type: Research Article
Authors: Yadav, Priyankaa | Jain, Anshula | Pathak, Nitishb; * | Sharma, Neelamc
Affiliations: [a] FMS-WISDOM, Banasthali Vidyapith, Rajasthan, India | [b] Bhagwan Parshuram Institute of Technology, New Delhi, India | [c] Maharaja Agrasen Institute of Technology (MAIT), GGSIPU, New Delhi, India
Correspondence: [*] Corresponding author: Nitish Pathak, Bhagwan Parshuram Institute of Technology, New Delhi, India, India. E-mail: nitishpathak@bpitindia.com.
Abstract: The primary aim of the present research is to investigate the factors that precede digital payments and their effect on the behavioural intentions of consumers residing in both rural and urban areas. In this research, different factors, such as perceived usefulness (PU), compatibility (CO), performance expectancy (PE), transaction speed (TS), trust (TR), unavailability of facilitating conditions (UFC), and operational constraints (OC) have been taken from various theories. To collect data, an online survey was administered, and a total of 557 participants provided their responses. The model’s validity and reliability are established using confirmatory factor analysis (CFA), while the hypothetical relationships were analysed using structural equation modelling (SEM) in AMOS. It is concluded that PU, CO, PE, TS, TR, UFC, and OC have impacted the behavioural intentions of both urban and rural users. Moreover, the multi-group analysis is also applied in this research, to know the difference in behaviour of rural and urban users. It is concluded that PU, CO, PE, TS, TR, UFC, and OC have impacted the behavioural intentions of the users. Through the multi-group AMOS analysis, it was discovered that the path from drivers such as TS, CO, TR, and UFC to intent to use showed a difference between the two groups, whereas OC, PE, and PU showed the same path coefficient. Finally, at the end, some managerial implications are made for further study.
Keywords: Digital payment system, transaction speed, trust, compatibility
DOI: 10.3233/IDT-240659
Journal: Intelligent Decision Technologies, vol. 18, no. 3, pp. 2353-2370, 2024
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