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 Journal of Statistics and Management Systems cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510
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The Journal of Statistics and Management Systems (JSMS) is a world leading journal publishing high quality, rigorously peer-reviewed original research on theoretical and applied statistics and management systems since 1998. The scope is intentionally broad, but papers must make a novel contribution to the field to be considered for publication. Topics include, but are not limited to, the following: • Statistics • Applied Statistics • Industrial Statistics • Statistical Inference • Interdisciplinary role of Statistics • Actuarial Sciences • Decision Sciences • Managerial Aspects • Management Sciences • Management Information Systems

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Open Access Research Article

The intention of Fintech adoption in TAM perspective: A SEM approach

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pp. 505–514Vol. 26Issue 3April 2023DOI: 10.47974/JSMS-1043XML
Published Online:
31 Mar 2023
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1043
Pages:
505–514

Abstract

Along with the development of the Fintech industry fundamentally during the last decades and the backdrop of the prevailing pandemic situation, the present study examines the intention of Fintech adoption in the perspective of the technology acceptance model (TAM) reflecting the chain relationship among consumer’s trust, attitude, and intention of adoption of Fintech. The analysis through structural equation modeling (SEM), with a sample of 110 respondents, we concluded that consumers’ attitude of adoption of Fintech has a very high and significant impact on the intention of adoption. The impact of trust on the attitude is also significant but not as high as compared to the attitude on intention. Therefore, the companies should work on generating trust to make the chain effective.

Keywords

Subject Classifications

91-02

References

[1] “https://www.statista.com,” 04 2021. [Online]. Available: https://www.statista.com/statistics/719385/investments-into-fintech-companies-globally/. [Accessed 28 06 2021].
[2] Deloitte, “Fintech: On the brink of further disruption,” Deloitte, The Netherlands, 2020.
[3] Research and Markets, “Global FinTech Marketplace Report Analysis 2022: A $225+ Billion Industry by 2027 - Growing Adoption of Non-Bank Option to Manage Money” (2022).
[4] Ernst & Young LLP, “EY | Building a better working world,” Ernst & Young LLP (2022).
[5] E. Gupta, The Future of Fintech in 2023, The Times of India (2023).
[6] F. Davis, A Technology Acceptance Model for Empirically Testing New End-user Information System: Theory and Results, Cambridge, MA: MIT Solan School of Management (1985).
[7] G. C. Moore and I. Benbasat, “Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation,” Information Systems Research, 2(3), pp. 192-222 (1991).
[8] A. Morgan and C. Veloutsou, “Beyond technology acceptance: Brand relationships and online brand experience,” Journal of Business Research, 66(1), pp. 21-27 (2011).
[9] M. A. Daqar, C. Constantinovits, A. Samer and A. Daragmeh, “The role of Fintech in predicting the spread of COVID-19,” Business Perspectives - Banks and Bank Systems, Volume 16, Issue 1 (2021).
[10] A. A. Hogail, “Improving IoT Technology Adoption through Improving Consumer Trust,” MDPI (2018).
[11] R. Roberts, R. Flin, D. Millar and L. Corradi, “Psychological factors influencing technology adoption: A case study from the oil and gas industry,” Technovation (2021).
[12] H. Zhongqing, D. Shuai, L. Shizheng, C. Luting and Y. Shanlin, “Adoption Intention of Fintech Services for Bank Users: An Empirical Examination with an Extended Technology Acceptance Model,” MDPI - Symmetry (2019).
[13] E. Fernando, Suryanto and Surjandy, “Analysis of the Influence of Consumer Behavior Using FinTech Services with SEM and TOPSIS,” International Conference on Information Management and Technology (ICIMTech) (2019).
[14] L.-M. Chuang, C.-C. Liu and H.-K. Kao, “The Adoption of Fintech Service: TAM perspective,” International Journal of Management and Administrative Sciences (IJMAS) - Vol. 3, No. 07 (2021).
[15] K. Lal, S. R. M and R. P, “Factors that Influence the Customer Adoption of Fintech in Hyderabad, India,” International Journal of Recent Technology and Engineering (IJRTE) (2020).
[16] T. Puschmann, “Fintech,” Business & Information Systems Engineering, vol. 59, pp. 69-76 (2017).
[17] S. Christian, T. Wiradinata, C. Herdinata and A. Setiobudi, “Environmental Factors Affecting the Acceleration of Financial Technology (Fintech) Adoption by SMEs in the East Java Region,” Advances in Economics, Business and Management Research (2020).
[18] D. George and M. Mallery, SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 Update, 10th Edition, Boston: Pearson (2010).
[19] J. Gaskin and J. Lim, Master Validity Tool, AMOS Plugin, Gaskination’s StatWiki (2016).
[20] M. W. Browne and R. Cudeck, “Alternative ways of assessing model fit. In Bollen, K.A. & Long, J.S. [Eds.] Testing structural equation models. Newbury Park,” Newbury Park, CA: Sage (1993).
[21] K. G. Joreskog and D. Sorbom, Advances in factor analysis and structural equation models, Lanham: Rowman & Littlefield Publishers (1984).
[22] J. S. Tanaka and G. J. Huba, A fit index for covariance structure models under arbitrary GLS estimation., British Journal of Mathematical and Statistical Psychology, 38(2) (1985).
[23] P. M. Bentler and D. G. Bonet, “Significance Tests and Goodness of Fit in the Analysis of Covariance Structures,” Psychological Bulletin, Vol. 88, No. 3 (1980).
[24] H. W. Marsh and D. Hocevar, “Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups,” Psychological Bulletin, 97(3) (1985).
[25] S. Grima, I. Romanova, J. Spiteri and M. Kudinska, “The Payment Services Directive 2 and Competitiveness: The Perspective of European Fintech Companies,” Eur. Res. Stud. J., vol. 21, no. 2 (2018).
[26] J. L. Arbuckle, Full information estimation in the presence of incomplete data. In G.A. Marcoulides & R.E. Schumacker [Eds.] Advanced structural equation modeling, Mahwah, New Jersey: Lawrence Erlbaum Associates (1996).

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