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This paper studies the Critical Success Factors' (CSFs) for the adoption of Digital Payment System in India. There are few studies about the literature on CSFs for the adoption of the digital payment system in the Indian context. This study is an attempt to cover this gap. In this study, we reviewed the theories for adoption model at the individual level used in Information System (IS) and discussed four technology model including "Technology Acceptance Model" (TAM). Ten factors have been identified with extensive literature review and review of selected models namely; Perceived Ease of Use, Perceived functional benefits, Awareness, Availability of Resources, Government as a policy maker, Performance Expectancy, Social Influence, Price Value, Experience & Habit, and Risk-taking ability. An expert from academic industry has been taken as a reviewer or consultant of the selected variables. The CSFs may ensure that they are the predictors and the important factors for adoption of digital payments system in India. The study mainly uses the deductive approach to consider the primary and secondary sources of data. The analyses of these models take into account through Interpretive Structural Modeling (ISM) methodology and develop a model for effective adoption of Digital Payment System in India. The paper also makes future recommendations for further research studies.

This paper is an attempt to study the important factors responsible for successful implementation of digital payment (e-Payment) system in India. Examine the status of e-Payment at Allahabad city (Uttar Pradesh, Indian) and to conduct an analysis of imitation of e-Payment in other regions of India. A qualitative study with extensive literature review, interview and expert opinion was adopted to conduct the study. To analyse the result and to identify the success factor NVivo 11 Pro software is used. With the help of software 13 success factors identify namely: Anonymity, Bank Involvement, Drawer, Infrastructure, Mobility, Parties, Popularity, Range of Payment, Risk, Security, Transfer limit, Transfer mode, and Transfer time for successful implementation of digital payment at Allahabad city. The outcome will be helpful for implementation of digital payment in various other cities of India.

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Purpose – Due to country-wise lockdown and state-wise curfews in COVID-19, people were not able to make offline payments (i.e. cash payments) during purchases in India. So, people are switching their payment behavior from offline to online mode. But, as per the central bank report, the rate of adoption through mobile payments is still slow. The paper focuses on identifying critical barriers to mobile payment systems (MPSs) adoption in India. Innovation resistance theory (IRT) has been used as a base model for barriers, despite the wide range of choices of barriers available in the MPSs context. Additionally, three external variables which are out of the wider coverage of IRT constructs were incorporated in this paper. The study, on the other hand, adds to innovation resistance theory in the frame of reference of MPSs from a theoretical perspective. Interpretive structural modeling (ISM), together with MICMAC analysis is brought into play to analyse the direct and indirect relationship amongst the barriers. Research methodology – ISM approach has been used to establish the relationship among the eight (08) identified barriers, through literature and expert opinions. The key barriers to high driving power are then identified with the help of MICMAC analysis. Findings – The results reveal that value barrier (b2), image barrier (b5) and visibility barrier (b7) are the most significant variables. Interestingly, IRTs’ risk barrier (b3) and privacy barrier (b6) from the literature fall in the lowest level of the ISM model. The majority of the barriers fall under quadrant III of MICMAC analysis, indicating the high driving and dependence power. Research limitations – The developed ISM model is based on the sentiments of five (05) experts, which could be biased and influence the structural model’s final output. Due to COVID-19, data has been collected through online video conferencing mode, this may vary if data will be collected through an offline or face-to-face interview. The proposed model’s key findings aim to assist in explaining the barriers that exist during MPS adoption. Originality/Value – This study is the first attempt to use the ISM approach in conjunction with IRT to detect barriers within MPSs. The result of this paper will guide and motivate the researcher to analyse more critical barriers with IRT to contribute to the theoretical development.