I am currently working as a Professor in the Data Science & Technology department at K.J. Somaiya Institute of Management, Somaiya Vidyavihar University,Mumbai,India. I completed my Ph.D. from SNDT Women’s University. The title of the thesis is “Consumer Adoption, Trust, and Security Challenges on Mobile Banking: An Indian Study”. I am working as an academician for the past eighteen years. I have published research papers in reputed International ABDC category journals and peer reviewed Scopus /WoS indexed journals.
Technology adoption Fintech Artificial Intelligence Blockchain E-learning
Purpose The purpose of this paper is to identify factors influencing the adoption of mobile banking in India and develop and empirically validate a model explaining the behavioural intention to use mobile banking in the Indian banking sector. Design/methodology/approach In this study, a model is developed and proposed to explain customers’ intention to use mobile banking. The model comprises six constructs, namely, perceived ease of use, computer self-efficacy, social influence, perceived financial cost, security, and trust. The model also describes the relationship between perceived ease of use and computer self-efficacy, as well as that between security and trust. The proposed model was tested by using a survey method, with a sample of 855 bank customers from public, private, foreign, and cooperative banks in India. Structural equation modelling analysis was performed with AMOS 16.0. Findings The proposed theoretical model was found to predict, with statistical significance, the intention to use mobile banking, explaining 76.9 per cent of the variance in the dependent variable. The results found that security, computer self-efficacy, perceived ease of use, and perceived financial cost, in that order of influence, affect customers’ intention to adopt mobile banking. Practical implications The results obtained will help both academic researchers and practitioners explain, understand, and elucidate the status of mobile banking in India, as well as helping them formulate strategies to expedite the use of mobile banking. Originality/value The adoption of mobile banking in India is in a nascent stage compared with developed countries such as the USA, the UK, and Finland, but it is expected to increase or surpass the rate of adoption of internet banking in those countries. Further, only limited research to date has examined the adoption of mobile banking in India, especially the drivers and inhibitors of mobile banking adoption.
Technological progression in mobile phones has increased the popularity of mobile payments. Users can shop online through a mobile device, which is time saving and convenient. Mobile payment systems involve ongoing interactions between users and payment providers. The initial acceptance of mobile payment systems has been studied extensively, but few studies have attempted to understand users’ post-adoption behaviour. This study employs an integrated model with the unified theory of acceptance and use of technology (UTAUT) framework and the expectation confirmation model (ECM), along with two additional constructs: perceived security and trust. The empirical results show that the integrated model has a higher predictive power to explain continuance intentions for using mobile payment systems with significant factors of satisfaction, trust, performance expectancy, and effort expectancy. This study confirmed that the UTAUT model could be extended to explain post-adoption behaviour towards mobile payment systems. The study’s findings have theoretical and practical value to further the understanding of pre- and post-adoption behaviour towards mobile payment systems.
The objective of this study is to measure the e-service quality of internet banking and the relationship with customer satisfaction in India. This study aims to explore the critical factors of e-service quality of internet banking in India and to measure the customers' satisfaction of internet banking on the identified e-service quality dimensions. A survey method was carried out to acquire data from 650 respondents from India. Exploratory and confirmatory factor analysis was used to identify the dimensions of internet banking. Multiple Regression Analysis was used to test the relationship with e-service quality dimensions and customer satisfaction of internet banking. The study uncovered three factors of e-service quality, namely, "Responsiveness," "Efficiency," and "Perceived Credibility". "Responsiveness" found to be the most significant predictor of the e-service quality of internet banking. The study also found that there is a positive relationship exists between e-service quality dimensions and customer satisfaction of internet banking. These findings can be used by banks to improve the service quality of their internet banking service and thereby to satisfy their customers. The findings open up many business opportunities to India as well as other Asian countries. The digital payments industry can concentrate on improving the security of the payment systems, gateways, and payment networks. Advanced technologies can be developed to improve the digital payment systems which offer many business opportunities for creating computers, smartphones, and innovation in internet and security software. The study findings can be used by banks to improve the service quality of internet banking and attract more customers towards using this service. The improvement in service quality comprising of responsiveness, efficiency, and perceived credibility automatically leads to the customer satisfaction of internet banking services, which gives competitive advantages to the banks. This study is an attempt to cover both urban and rural population of India to understand the digital mindset by studying the quality perception of internet banking channel.
Wearable healthcare technologies enable continuous monitoring of wearers' health status and the implementation of preventive measures that significantly improve their health. In recent years, the popularity of wearable fitness devices has skyrocketed. Privacy concerns are a significant impediment to more people using these devices. This study aims to understand the moderating role of privacy concerns on users' intentions to use wearable fitness technologies. The theoretical model for this study integrates the UTAUT2 framework and privacy concerns as a second-order model. The study follows a quantitative research approach, using a questionnaire to collect data. The PLS-SEM model was used to test the theoretical model. The integrated model with the indirect effect of privacy concerns explained higher variance in predicting the behavioral intention to use wearable fitness devices. Price value, performance expectancy, habit, and facilitating conditions all had a significant influence on users' decisions to use wearable fitness devices, while privacy concerns moderated the relationship between UTAUT2 constructs for behavioral intention to use these devices. This study confirmed that the UTAUT2 model could be extended to explain the initial adoption of smart wearable fitness devices. Prior studies investigated the intention to use smart wearable devices, but few addressed privacy concerns associated with wearable fitness devices. This study addressed this gap by investigating the moderating role of privacy concerns on the intention to use wearable fitness devices. The integrated theoretical model developed uncovers users' privacy concerns related to these systems.
The advancement of mobile communication and wireless technologies has made a rapid development in the sector of banking services using their mobile phones. A fine system with great potential has the capacity to attract a huge block of customers to opt for banking services through their mobile phones. The dynamism in the present era of technology, where many other channels are available, this mobile banking system stands alone to attract more customers to come in the net of using mobile banking services. This paper meticulously aims to investigate the factors influencing the intention of the customer to use mobile banking. It suggests an integrated model that incorporates the five antecedents namely, perceived ease of use, compatibility, social influence, security, and perceived cost on its influence on customers' decision to use mobile banking. The study results revealed that compatibility, social influence, and security in their order of influence significantly affect the customers' decision to use mobile banking. The theoretical model is empirically validated and explained 62 percent of the variance in intention to use mobile banking. The implications of this study's findings for the future research and practice are described.
This paper studies the need to integrate trust and Technology acceptance model (TAM) to understand the behaviour intention of the customer to use mobile banking. The present study focuses through literature review on trust related antecedents and technology related constructs and its influence on customer decision. It covers disposition to trust, institution-based trust, cognitive-base trust, security and privacy as five potential antecedents of trust. The study concludes that two technology attributes which are perceived ease of use and perceived usefulness to be beneficial for the usage of mobile banking. It suggests an integrated model that incorporates the five trust antecedents and two technology-related antecedents on its influence on customers’ decision to use mobile banking.
Massive open online courses (MOOCs) have now become mainstream for learning in unprecedented situations, where traditional classroom learning is difficult to conduct. The aim of this study is to understand the factors that lead to the higher education students’ adoption of MOOCs and the barriers that prevent their use. This study proposes a theoretical model for measuring the higher education students’ intention to adopt MOOCs. The PLS-SEM approach was used to test the theoretical model developed for this study with a sample of 312 higher education students. The theoretical model explained 63.1% of the variance in the dependent variable of behavioral intention to use MOOCs. The findings identified that facilitating conditions, perceived usefulness, course flexibility, and job relevance are the factors—in order of their influence—that predict the higher education students’ perceived intention to use MOOCs. The findings of this study contribute to this existing body of knowledge of MOOCs adoption.
Purpose The purpose of this study is to identify the factors that contribute to the continued intention and actual use of GenAI tools among Indian university students. Generative artificial intelligence (GenAI) tools significantly transform and disrupt the education sector, offering substantial opportunities for educators and learners. Previous research has predominantly concentrated on adopting ChatGPT within the education sector; however, the effects of other generative artificial intelligence (AI) tools in education remain insufficiently explored. Furthermore, it examines how AI characteristics such as perceived anthropomorphism, perceived intelligence and perceived technology novelty (TN) influence perceived usefulness and perceived ease of use, which are the predictors of continuance intention. Design/methodology/approach This study develops a theoretical model incorporating AI features as antecedents to the Technology Continuance Theory (TCT). This study uses a cross-sectional survey to collect responses from Indian higher education students. The authors use the PLS-SEM model with SmartPLS 4.0 for analysis. Findings This study tested the applicability of TCT in GenAI usage in education settings. This research empirically proved that perceived intelligence and TN are the antecedents to perceived use and ease of use. From the TCT model, satisfaction and attitude positively influenced continuance intention to use GenAI tools, and continuance intention positively influenced the actual use of GenAI in education. Originality/value This study empirically validated the use of various GenAI tools in the teaching and learning process, contributing to the existing research. This study is one of the earliest to examine the human–AI interaction in an educational setting. This study empirically tested TCT from the perspective of higher education students’ actual use of GenAI tools. The findings of this study offer many practical insights for stakeholders, such as EdTech companies, AI companies, GenAI developers, educators and academic institutions, to implement GenAI tools successfully.
Distributed Shared Memory (DSM) is a collection of nodes or clusters, each with its own memory connected by an interconnected network. The key issue in DSM is keeping the memory pages consistent. It refers to the degree of consistency that has to be maintained for the shared memory data. Maintaining perfect consistency is especially painful when the difference between the latency and/or throughput of memory accesses on the one hand, and the network connecting the machines on which these copies reside on the other, is big. The solution might be to accept less than perfect consistency as the price for better performance. This paper reviews various memory consistency models which are used in different DSM systems.
In recent years, the rapid strides made by artificial intelligence (AI) in the financial services industry have not only reshaped its landscape but have also brought along disruptive innovations. Prominent among them are the robo-advisors (RAs), which have brought in catalytic changes in efficiency, scalability, and personalization in the fintech space. Despite these inherent strengths, the penetration of these algorithm-driven platforms has continued to be suboptimal. The main hindrance to their adoption has been concerns over trust, perceived risks, and lack of human interaction. Against this backdrop, the current study presents an integrative framework of dual-factor theory and the benefit-risk model to identify and focus on the interplay between the push-pull factors, both positive (enablers) and negative (inhibitors), that determine the perceived benefit and perceived risk of RAs, resulting in the willingness and objection to RA usage. By deploying the PLS-SEM analysis on a diverse Indian sample, the study identified and empirically validated perceived anthropomorphism, social influence, and trust as the three distinct enablers that lead to the perceived benefit of employing RAs. The study further highlighted the pivotal role of poor interaction quality and lack of awareness in driving the perceived risk of RAs. By incorporating robo-design features, customer-centric and service factors as antecedents, this study not only contributes to the theoretical discourse on RA adoption research but also provides actionable insights for financial institutions, RA platform developers, and policymakers to improve increased market penetration of these AI-driven financial services in India's rapidly evolving fintech landscape.
I would like to conduct a research study on how culture differs on AI anthropomorphism and its impact on digital banking channels. The aim …
I would like to conduct a research study on how culture differs on AI anthropomorphism and its impact on digital banking channels. The aim …