Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Khan, Shebazbano
- Adoption of Fintech Using Structured Equation Model and Multiple Criteria with Specific Reference to India
Abstract Views :146 |
PDF Views:98
Authors
Affiliations
1 Assistant professor, Thakur Institute of Management Studies and Research., IN
2 Associate Professor, Oriental Institute of Management., IN
3 Assistant Professor, MET Institute of Management., IN
1 Assistant professor, Thakur Institute of Management Studies and Research., IN
2 Associate Professor, Oriental Institute of Management., IN
3 Assistant Professor, MET Institute of Management., IN
Source
Journal of Applied Management- Jidnyasa, Vol 14, No 2 (2022), Pagination: 143-160Abstract
Purpose-This study aims at highlighting the intention of adoption of Fintech through Structural Equation Modeling (SEM) in Indian context. Fintech services (FINTECH) play a vital role. Fintech is a boon in times when one had to physically report to the bank, even for simple tasks such as funds transfer. People can now save both time and money when travelling. Senior Citizens and working professionals can now undertake most of their financial transactions online without moving out of their residence.Despite the widespread acceptance of Fintech in everyday life, long-term expansion of Fintech services (FINTECH) is delayed, in part due to online consumers' lack of trust and fear of danger. In order to better comprehend and prioritise FINTECH decision choices, this study investigates trust and risk on a multi-dimensional basis. Design/methodology/approach –Data analysis was undertaken through an advanced statistical techniques such as) multiple criteria decision-making (MCDM) methodologies and Structural Equation Modeling (SEM). Structural Equation Modeling (SEM) is employed to ascertain causal relationships and suitable assignment weightages to variables. The efficiency of the recommended strategy is demonstrated in this study. 207 data will be collected as a sample size. Simple Random sampling will be used for collecting data. Model will be created for this study including dependent, independent, mediating and moderating variable. Findings– This study will be conducted to find the intention of adoption of Fintech services using SEM Model which is based on different variables. Research limitations/implications –This scope of the study is limited to India only. Only Adoption intention of FINTECH is covered using SEM model according to different variables are covered. Practical implications –This research paper has attempted to make an honest endeavour to contribute significantly towards understanding and application of findings pertaining to fintech adoption and usage. These results may be of tremendous utility to banks and financial institutions. It may assist them in conceptualisation and implementation of impactful and successful marketing strategies through meticulous segmentation and targeting of relevant consumers to enhance the usage and acceptance of fintech. 144 Originality/value – The authors in all humility would submit that this research manuscript is unique in terms of deployment of Structural Equation Modeling (SEM) for understanding of customer behaviour in regards to intention to adopt FINTECH Services. Also the relationships between the constructs shown in this research have not been exhibited in any other research paper.Keywords
Adoption, Fintech services, SEM, Risk, Trust, Ease of use, Attitude.Full Text
References
- Gabor, D.; Brooks, S. The Digital Revolution in Financial Inclusion: International Development in the Fintech Era. New Polit. Econ. 2017, 22, 1–14. [Google Scholar] [CrossRef]
- Leong, C.; Tan, B.; Xiao, X.; Tan, F.T.C.; Sun, Y. Nurturing a Fintech Ecosystem: The Case of a Youth Microloan Startup in China. Int. J. Inf. Manag. 2017, 37, 92–97. [Google Scholar] [CrossRef]
- Alt, R.; Beck, R.; Smits, M.T. Fintech and the Transformation of the Financial Industry. Electron. Mark. 2018, 28, 235–243. [Google Scholar] [CrossRef]
- Zavolokina, L.; Dolata, M.; Schwabe, G. The Fintech Phenomenon: Antecedents of Financial Innovation Perceived by the Popular Press. Financ. Innov. 2016, 2, 16. [Google Scholar] [CrossRef]
- Chang, Y.; Wong, S.; Lee, H.; Jeong, S. What Motivates Chinese Consumers to Adopt Fintech Services: A Regulatory Focus Theory; ACM: New York, NY, USA, 2016. [Google Scholar]
- Priem, R.L.; Li, S.; Carr, J.C. Insights and new directions from demand-side approaches to technology innovation, entrepreneurship, and strategic management research. J. Manag. 2012, 38, 346–374. [Google Scholar] [CrossRef]
- Priem, R.L.; Swink, M. A demand-side perspective on supply chain management. J. Supply Chain Manag. 2012, 48, 7–13. [Google Scholar] [CrossRef]
- Hermes, N.; Lensink, R. Does Financial Liberalization Influence Saving, Investment and Economic Growth? Evidence from 25 Emerging Market Economies, 1973; Palgrave Macmillan: Basingstoke, UK, 2008; pp. 47–57. [Google Scholar]
- Nakashima, T. Creating Credit by Making Use of Mobility with Fintech and IoT. IATSS Res. 2018, 42, 61–66. [Google Scholar] [CrossRef]
- Gai, K.; Qiu, M.; Sun, X. A Survey on Fintech. J. Netw. Comput. Appl. 2018, 103, 262–273. [Google Scholar] [CrossRef]
- Yin, H.; Gai, K. An Empirical Study on Preprocessing High-Dimensional ClassImbalanced Data for Classification. In Proceedings of the IEEE International Conference on High PERFORMANCE Computing and Communications, New York, NY, USA, 24–26 August 2015. [Google Scholar]
- Gai, K.; Qiu, M.; Zhao, H. Energy-Aware Task Assignment for Mobile Cyber-Enabled Applications in Heterogeneous Cloud Computing. J. Parallel Distrib. Comput. 2017, 111, 25–38. [Google Scholar] [CrossRef]
- Cuomo, S.; Somma, V.D.; Sica, F. An Application of the One-Factor Hullwhite Model in an Iot Financial Scenario. Sustain. Cities Soc. 2018, 38, 18–20. [Google Scholar] [CrossRef]
- Mishra, S. Financial Management and Forecasting Using Business Intelligence and Big Data Analytic Tools. Int. J. Financ. Eng. 2018, 6, 10–31. [Google Scholar] [CrossRef]
- Du, W.D.; Pan, S.L.; Leidner, D.E.; Ying, W. Affordances, Experimentation and Actualization of Fintech: A Blockchain Implementation Study. J. Strateg. Inf. Syst. 2018. [Google Scholar] [CrossRef]
- Buckley, R.; Arner, D.; Barberis, J. The Evolution of Fintech: A New Post-Crisis Paradigm? Soc. Sci. Electron. Publ. 2015, 47, 1271–1319. [Google Scholar]
- Davis, F.D. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 1986. [Google Scholar]
- Venkatesh, V.; Bala, H. Technology Acceptance Model 3 and a Research Agenda on Interventions. Decis. Sci. 2010, 39, 273–315. [Google Scholar] [CrossRef]
- Zhang, T.; Lu, C.; Kizildag, M. Banking “On-the-Go”: Examining Consumers’ Adoption of Mobile Banking Services. Int. J. Qual. Serv. Sci. 2018, 10, 279–295. [Google Scholar] [CrossRef]
- Stewart, H.; Jürjens, J. Data Security and Consumer Trust in Fintech Innovation in Germany. Inf. Comput. Secur. 2018, 26, 109–128. [Google Scholar] [CrossRef]
- Ryu, H. What Makes Users Willing or Hesitant to Use Fintech?: The Moderating Effect of User Type. Ind. Manag. Data Syst. 2018, 118, 541–569. [Google Scholar] [CrossRef]
- Ng, A.W.; Kwok, B.K.B. Emergence of Fintech and Cybersecurity in a Global Financial Centre: Strategic Approach by a Regulator. J. Financ. Regul. Compliance 2017, 25, 422–434. [Google Scholar] [CrossRef]
- Barakat, A.; Hussainey, K. Bank Governance, Regulation, Supervision, and Risk Reporting: Evidence from Operational Risk Disclosures in European Banks. Int. Rev. Financ. Anal. 2013, 30, 254–273. [Google Scholar] [CrossRef]
- Featherman, M.S.; Pavlou, P.A. Predicting E-Services Adoption: A Perceived Risk Facets Perspective. Int. J. Hum. -Comput. Stud. 2003, 59, 451–474. [Google Scholar] [CrossRef]
- Hong, W.; Zhu, K. Migrating to Internet-Based E-Commerce: Factors Affecting ECommerce Adoption and Migration at the Firm Level. Inf. Manag. 2006, 43, 204–221. [Google Scholar] [CrossRef]
- Chang, Y.; Wong, S.F.; Lee, H.; Jeong, S.P. What Motivates Chinese Consumers to Adopt Fintech Services: A Regulatory Focus Theory. In Proceedings of the International Conference on Electronic Commerce: E-Commerce in Smart Connected World, Suwon, Korea, 17–19 August 2016. [Google Scholar]
- Carlin, B.; Olafsson, A.; Pagel, M. Technology Adoption across Generations: Financial Fitness in the Information Age; Working Paper Series; National Bureau of Economic Research: Cambridge, UK, 2017. [Google Scholar]
- Chau, V.S.; Ngai, L.W.L.C. The Youth Market for Internet Banking Services: Perceptions, Attitude and Behaviour. J. Serv. Mark. 2013, 39, 42–60. [Google Scholar]
- Abbad, M.M. E-Banking in Jordan. Behav. Inf. Technol. 2013, 32, 681–694. [Google Scholar] [CrossRef]
- Akturan, U.; Tezcan, N. Mobile Banking Adoption of the Youth Market. Mark. Intell. Plan. 2012, 30, 444–459. [Google Scholar] [CrossRef]
- Szopiński, T.S. Factors Affecting the Adoption of Online Banking in Poland. J. Bus. Res. 2016, 69, 4763–4768. [Google Scholar] [CrossRef]
- Riquelme, H.E.; Rios, R.E. The Moderating Effect of Gender in the Adoption of Mobile Banking. Int. J. Bank Mark. 2010, 28, 328–341. [Google Scholar] [CrossRef]
- Taylor, S.; Todd, P.A. Understanding Information Technology Usage: A Test of Competing Models. Inf. Syst. Res. 1995, 6, 144–176. [Google Scholar] [CrossRef]
- Zhao, A.L.; Koenig-Lewis, N.; Hammer-Lloyd, S.; Ward, P. Adoption of Internet Banking Services in China: Is It All About Trust? Int. J. Bank Mark. 2010, 28, 26. [Google Scholar]
- Gupta, A.; Arora, N. Consumer Adoption of M-Banking: A Behavioral Reasoning Theory Perspective. Int. J. Bank Mark. 2017, 35, 733–747. [Google Scholar] [CrossRef]
- Shaikh, A.A.; Karjaluoto, H. Mobile Banking Adoption: A Literature Review. Telemat. Inform. 2015, 32, 129–142. [Google Scholar] [CrossRef]
- Hsu, C.L.; Wang, C.F.; Lin, J.C.C. Investigating Customer Adoption Behaviours in Mobile Financial Services. Int. J. Mob. Commun. 2011, 9, 477–494. [Google Scholar] [CrossRef]
- Aboelmaged, M.G.; Gebba, T.R. Mobile Banking Adoption: An Examination of Technology Acceptance Model and Theory of Planned Behavior. Int. J. Bus. Res. Dev. 2013, 2, 35–50. [Google Scholar] [CrossRef]
- Mcknight, D.H.; Chervany, N.L. What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology. Int. J. Electron. Commer. 2001, 6, 35–59. [Google Scholar] [CrossRef]
- Lewis, J.D.; Weigert, A. Trust as a Social Reality. Soc. Forces 1985, 63, 967–985. [Google Scholar] [CrossRef]
- Lee, M.K.O.; Turban, E. A Trust Model for Consumer Internet Shopping. Int. J. Electron. Commer. 2001, 6, 75–91. [Google Scholar] [CrossRef]
- Kesharwani, A.; Singh Bisht, S. The Impact of Trust and Perceived Risk on Internet Banking Adoption in India. Int. J. Bank Mark. 2012, 30, 303–322. [Google Scholar] [CrossRef]
- Malaquias, R.F.; Hwang, Y. An Empirical Study on Trust in Mobile Banking: A Developing Country Perspective. Comput. Hum. Behav. 2016, 54, 453–461. [Google Scholar] [CrossRef]
- Koksal, M.H. The Intentions of Lebanese Consumers to Adopt Mobile Banking. Int. J. Bank Mark. 2016, 34, 327–346. [Google Scholar] [CrossRef]
- Basak, S.K.; Govender, D.W.; Govender, I. Examining the Impact of Privacy, Security, and Trust on the Tam and Ttf Models for E-Commerce Consumers: A Pilot Study. In Proceedings of the 14th Annual Conference on Privacy, Security and Trust (PST), Auckland, New Zealand, 12–14 December 2016. [Google Scholar]
- Hanafizadeh, P.; Behboudi, M.; Abedini Koshksaray, A. Mobile-Banking Adoption by Iranian Bank Clients. Telemat. Inform. 2014, 31, 62–78. [Google Scholar] [CrossRef]
- Park, E.; Kim, H.; Ohm, J.Y. Understanding Driver Adoption of Car Navigation Systems Using the Extended Technology Acceptance Model. Behav. Inf. Technol. 2015, 34, 741–751. [Google Scholar] [CrossRef]
- Sang, S.; Lee, J.D.; Lee, J. E-Government Adoption in Cambodia: A Partial Least Squares Approach. Transform. Gov. People Process Policy 2010, 4, 138–157. [Google Scholar] [CrossRef]
- Riyadh, A.N.; Bunker, D.; Rabhi, F. Barriers to E-Finance Adoption in Small and Medium Sized Enterprises (Smes) in Bangladesh. In Proceedings of the 5th Conference on Qualitative Research in IT, Brisbane, Australia, 17 November 2010. [Google Scholar]
- Shapiro, S.L.; Reams, L.; So, K.K.F. Is It Worth the Price? The Role of Perceived Financial Risk, Identification, and Perceived Value in Purchasing Pay-Per-View Broadcasts of Combat Sports. Sport Manag. Rev. 2018. [Google Scholar] [CrossRef]
- Saleem, Z.; Rashid, K. Relationship between Customer Satisfaction and Mobile Banking Adoption in Pakistan. Int. J. Trade Econ. Financ. 2014, 2, 537–543. [Google Scholar] [CrossRef]
- Srivastava, S.C.; Chandra, S.; Theng, Y.L. Evaluating the Role of Trust in Consumer Adoption of Mobile Payment Systems: An Empirical Analysis. Commun. Assoc. Inf. Syst. 2010, 27, 561. [Google Scholar]
- Semuel, H.; Lianto, A.S. Analisis E-Wom, Brand Image, Brand Trust Dan Minat Beli Produk Smartphone Di Surabaya. J. Manaj. Pemasar. 2014, 8, 7–54. [Google Scholar]
- Lee, K.C.; Chung, N. Understanding Factors Affecting Trust in and Satisfaction with Mobile Banking in Korea: A Modified Delone and Mclean’s Model Perspective. Interact. Comput. 2009, 21, 385–392. [Google Scholar] [CrossRef]
- Siamagka, N.T.; Christodoulides, G.; Michaelidou, N.; Valvi, A. Determinants of Social Media Adoption by B2B Organizations. Ind. Mark. Manag. 2015, 51, 89–99. [Google Scholar] [CrossRef]
- Sikdar, P.; Kumar, A.; Makkad, M. Online Banking Adoption: A Factor Validation and Satisfaction Causation Study in the Context of Indian Banking Customers. Int. J. Bank Mark. 2015, 33, 760–785. [Google Scholar] [CrossRef]
- Khedmatgozar, H.R.; Shahnazi, A. The Role of Dimensions of Perceived Risk in Adoption of Corporate Internet Banking by Customers in Iran. Electron. Commer. Res. 2018, 18, 389–412. [Google Scholar] [CrossRef]
- Bansal, S.K.; Bansal, A.; Blake, M.B. Trust-Based Dynamic Web Service Composition Using Social Network Analysis. In Proceedings of the IEEE International Workshop on Business Applications of Social Network Analysis, Bangalore, India, 15 December 2010. [Google Scholar]
- Zhou, T.; Lu, Y.; Wang, B. Integrating Ttf and Utaut to Explain Mobile Banking User Adoption. Comput. Hum. Behav. 2010, 26, 760–767. [Google Scholar] [CrossRef]
- Malaquias, F.F.D.O.; Hwang, Y. An Empirical Investigation on Disclosure about Mobile Banking on Bank Websites. Online Inf. Rev. 2018, 42, 615–629. [Google Scholar] [CrossRef]