Examining the Factors Contributing to Fintech Peer-to-peer Lending Adoption
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Background: Peer-to-peer (P2P) lending platform is one of key disruptive business models in financial technology. It bridges lenders and borrowers directly. Researchers have studied the leverage mechanism behind the P2P lending platform.
Objective: This research proposes an enhanced technology acceptance model (TAM) to investigate how consumers embrace P2P lending platforms using quality of service and perceived risk as drivers of trust.
Methods: This research uses structural equation modeling (SEM) to test the hypothesised connections between the latent variables.
Results: The findings show that users' trust, perceived usefulness, and perceived ease of use in P2P lending platforms significantly influence attitudes towards adoption. Meanwhile, consumers' perceived risk in using P2P lending platforms is unaffected by the quality of service.
Conclusion: The estimated model is consistent with the results shown in previous studies. The findings of the current research are useful for fine-tuning platform marketing plans and putting strategic goals into actions. For future research, we suggest including more variables to better understand the adoption intention of P2P lending platforms.
Keywords: Adoption intention, Peer-to-peer lending, Structural equation modeling, Technology acceptance model
A. Milne and P. Parboteeah, "The Business Models and Economics of Peer-to-Peer Lending,” SSRN Electron. J., 2016, doi: 10.2139/ssrn.2763682.
H. Zhao, Y. Ge, Q. Liu, G. Wang, E. Chen, and H. Zhang, "P2p lending survey: platforms, recent advances and prospects,” ACM Trans. Intell. Syst. Technol., vol. 8, no. 6, pp. 1–28, 2017.
R. Kurniawan, "Examination of the Factors Contributing To Financial Technology Adoption in Indonesia using Technology Acceptance Model: Case Study of Peer to Peer Lending Service Platform,” in 2019 International Conference on Information Management and Technology (ICIMTech), Aug. 2019, vol. 1, pp. 432–437, doi: 10.1109/ICIMTech.2019.8843803.
M. Rosavina, R. A. Rahadi, M. L. Kitri, S. Nuraeni, and L. Mayangsari, "P2P lending adoption by SMEs in Indonesia,” Qual. Res. Financ. Mark., vol. 11, no. 2, pp. 260–279, 2019, doi: 10.1108/QRFM-09-2018-0103.
F. D. Davis, "A technology acceptance model for empirically testing new end-user information systems: Theory and results,” Massachusetts Institute of Technology, 1985.
M. M. Rahman, M. F. Lesch, W. J. Horrey, and L. Strawderman, "Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems,” Accid. Anal. Prev., vol. 108, pp. 361–373, 2017.
S. R. Das, "The future of fintech,” Financ. Manag., vol. 48, no. 4, pp. 981–1007, 2019.
G. Dorfleitner, L. Hornuf, M. Schmitt, and M. Weber, "Definition of FinTech and Description of the FinTech Industry,” in FinTech in Germany, Cham: Springer International Publishing, 2017, pp. 5–10.
A. F. Carmona et al., "Competition issues in the area of financial technology (Fintech),” Policy Dep. Econ. Sci. Qual. Life Policies Eur. Parliam., 2018.
A. E. Omarini, "Peer-to-Peer Lending: Business Model Analysis and the Platform Dilemma,” Int. J. Financ. Econ. Trade, pp. 31–41, 2018, doi: 10.19070/2643-038x-180005.
Q. Yang and Y.-C. Lee, "Critical factors of the lending intention of online P2P: moderating role of perceived benefit,” in Proceedings of the 18th Annual International Conference on Electronic Commerce: e-Commerce in Smart connected World, 2016, pp. 1–8.
S. Lee, "Evaluation of Mobile Application in User's Perspective: Case of P2P Lending Apps in FinTech Industry.,” TIIS, vol. 11, no. 2, pp. 1105–1117, 2017.
N. Zhang and W. Wang, "Research on Balance Strategy of Supervision and Incentive of P2P Lending Platform,” Emerg. Mark. Financ. Trade, vol. 55, no. 13, pp. 3039–3057, 2019.
I. Ajzen and M. Fishbein, "The prediction of behavior from attitudinal and normative variables,” J. Exp. Soc. Psychol., vol. 6, no. 4, pp. 466–487, 1970.
Z. Hu, S. Ding, S. Li, L. Chen, and S. Yang, "Adoption intention of fintech services for bank users: An empirical examination with an extended technology acceptance model,” Symmetry (Basel)., vol. 11, no. 3, p. 340, 2019.
N. T. K. Lien, T.-T. T. Doan, and T. N. Bui, "Fintech and Banking: Evidence from Vietnam,” J. Asian Financ. Econ. Bus., vol. 7, no. 9, pp. 419–426, 2020.
N. Singh and N. Sinha, "How perceived trust mediates merchant's intention to use a mobile wallet technology,” J. Retail. Consum. Serv., vol. 52, p. 101894, 2020.
M. Hubert, M. Blut, C. Brock, R. W. Zhang, V. Koch, and R. Riedl, "The influence of acceptance and adoption drivers on smart home usage,” Eur. J. Mark., vol. 53, no. 6, pp. 1073–1098, 2019, doi: 10.1108/EJM-12-2016-0794.
J. Khlaisang, T. Teo, and F. Huang, "Acceptance of a flipped smart application for learning: a study among Thai university students,” Interact. Learn. Environ., vol. 29, no. 5, pp. 772–789, 2021, doi: 10.1080/10494820.2019.1612447.
S. Min, K. K. F. So, and M. Jeong, "Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model,” J. Travel Tour. Mark., vol. 36, no. 7, pp. 770–783, 2019.
S. A. Raza, A. Umer, and N. Shah, "New determinants of ease of use and perceived usefulness for mobile banking adoption,” Int. J. Electron. Cust. Relatsh. Manag., vol. 11, no. 1, pp. 44–65, 2017.
J. A. Kumar, B. Bervell, N. Annamalai, and S. Osman, "Behavioral Intention to Use Mobile Learning: Evaluating the Role of Self-Efficacy, Subjective Norm, and WhatsApp Use Habit,” IEEE Access, vol. 8, pp. 208058–208074, 2020, doi: 10.1109/ACCESS.2020.3037925.
J. D. Lewis and A. Weigert, "Trust as a Social Reality,” Soc. Forces, vol. 63, no. 4, pp. 967–985, Jan. 1985, doi: 10.2307/2578601.
R. M. Al-dweeri, Z. M. Obeidat, M. A. Al-dwiry, M. T. Alshurideh, and A. M. Alhorani, "The impact of e-service quality and e-loyalty on online shopping: moderating effect of e-satisfaction and e-trust,” Int. J. Mark. Stud., vol. 9, no. 2, pp. 92–103, 2017.
H.-S. Ryu and K. S. Ko, "Sustainable Development of Fintech: Focused on Uncertainty and Perceived Quality Issues,” Sustainability, vol. 12, no. 18, p. 7669, 2020.
C. Gronroos, "A Service Quality Model and its Marketing Implications,” Eur. J. Mark., vol. 18, no. 4, pp. 36–44, 1984, doi: 10.1108/EUM0000000004784.
A. Parasuraman, V. A. Zeithaml, and L. L. Berry, "A conceptual model of service quality and its implications for future research,” J. Mark., vol. 49, no. 4, pp. 41–50, 1985.
E. W. Anderson, C. Fornell, and D. R. Lehmann, "Customer satisfaction, market share, and profitability: Findings from Sweden,” J. Mark., vol. 58, no. 3, pp. 53–66, 1994.
O. O. Jaiyeoba, T. T. Chimbise, and M. Roberts-Lombard, "E-service usage and satisfaction in Botswana,” African J. Econ. Manag. Stud., vol. 9, no. 1, pp. 2–13, Jan. 2018, doi: 10.1108/AJEMS-03-2017-0061.
D. Goutam and B. Gopalakrishna, "Customer loyalty development in online shopping: An integration of e-service quality model and commitment-trust theory,” Manag. Sci. Lett., vol. 8, no. 11, pp. 1149–1158, 2018.
H.-S. Chen, B.-K. Tsai, and C.-M. Hsieh, "Determinants of consumers' purchasing intentions for the hydrogen-electric motorcycle,” Sustainability, vol. 9, no. 8, p. 1447, 2017.
A. R. Ghotbabadi, S. Feiz, and R. Baharun, "The relationship of customer perceived risk and customer satisfaction,” Mediterr. J. Soc. Sci., vol. 7, no. 1 S1, p. 161, 2016.
P. G. Schierz, O. Schilke, and B. W. Wirtz, "Understanding consumer acceptance of mobile payment services: An empirical analysis,” Electron. Commer. Res. Appl., vol. 9, no. 3, pp. 209–216, May 2010, doi: 10.1016/j.elerap.2009.07.005.
H. Ko, J. Jung, J. Kim, and S. W. Shim, "Cross-Cultural Differences in Perceived Risk of Online Shopping,” J. Interact. Advert., vol. 4, no. 2, pp. 20–29, Mar. 2004, doi: 10.1080/15252019.2004.10722084.
S. M. Ho, M. Ocasio-Velázquez, and C. Booth, "Trust or consequences? Causal effects of perceived risk and subjective norms on cloud technology adoption,” Comput. Secur., vol. 70, pp. 581–595, 2017.
C. A. Gumussoy, A. Kaya, and E. Ozlu, "Determinants of mobile banking use: an extended TAM with perceived risk, mobility access, compatibility, perceived self-efficacy and subjective norms,” in Industrial Engineering in the Industry 4.0 Era, Springer, 2018, pp. 225–238.
P. K. Senyo and E. L. C. Osabutey, "Unearthing antecedents to financial inclusion through FinTech innovations,” Technovation, vol. 98, p. 102155, 2020.
V. L. Johnson, A. Kiser, R. Washington, and R. Torres, "Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services,” Comput. Human Behav., vol. 79, pp. 111–122, 2018.
H. S. Ryu, "What makes users willing or hesitant to use Fintech?: the moderating effect of user type,” Ind. Manag. Data Syst., vol. 118, no. 3, pp. 541–569, 2018, doi: 10.1108/IMDS-07-2017-0325.
R. C. MacCallum, K. F. Widaman, S. Zhang, and S. Hong, "Sample size in factor analysis.,” Psychol. Methods, vol. 4, no. 1, p. 84, 1999.
K. S. Taber, "The use of Cronbach's alpha when developing and reporting research instruments in science education,” Res. Sci. Educ., vol. 48, no. 6, pp. 1273–1296, 2018.
N. Luo, M. Zhang, and D. Qi, "Effects of different interactions on students' sense of community in e-learning environment,” Comput. Educ., vol. 115, pp. 153–160, 2017.
T. A. Brown, Confirmatory factor analysis for applied research. Guilford publications, 2015.
B. M. Byrne, Structural Equation Modeling With Lisrel, Prelis, and Simplis. New York, NY, USA: Psychology Press, 1998.
L. Hu and P. M. Bentler, "Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,” Struct. Equ. Model. a Multidiscip. J., vol. 6, no. 1, pp. 1–55, 1999.
M. W. Browne and R. Cudeck, "Alternative ways of assessing model fit,” Sociol. Methods Res., vol. 21, no. 2, pp. 230–258, 1992.
P. M. Bentler and D. G. Bonett, "Significance tests and goodness of fit in the analysis of covariance structures.,” Psychol. Bull., vol. 88, no. 3, p. 588, 1980.
P. M. Bentler, "Comparative fit indexes in structural models.,” Psychol. Bull., vol. 107, no. 2, p. 238, 1990.
J. O. Berger and T. Sellke, "Testing a point null hypothesis: The irreconcilability of p values and evidence,” J. Am. Stat. Assoc., vol. 82, no. 397, pp. 112–122, 1987.
P. K. Chopdar, N. Korfiatis, V. J. Sivakumar, and M. D. Lytras, "Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology,” Comput. Human Behav., vol. 86, pp. 109–128, 2018.
N. K. Malhotra, J. Agarwal, and G. Shainesh, "Does Country or Culture Matter in Global Marketing? An Empirical Investigation of Service Quality and Satisfaction Model with Moderators in Three Countries BT - Emerging Issues in Global Marketing: A Shifting Paradigm,” J. Agarwal and T. Wu, Eds. Cham: Springer International Publishing, 2018, pp. 61–91.
D. Zunino, F. F. Suarez, and S. Grodal, "Familiarity, creativity, and the adoption of category labels in technology industries,” Organ. Sci., vol. 30, no. 1, pp. 169–190, 2019.
R. R. Suryono, I. Budi, and B. Purwandari, "Detection of fintech P2P lending issues in Indonesia,” Heliyon, vol. 7, no. 4, p. e06782, 2021.
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