Share:


An asset value evaluation for docking finance lease problems in the peer-to-peer platform

    Jiang Qu Affiliation
    ; Hongwei Liu   Affiliation
    ; Hui Zhu Affiliation
    ; Hongming Gao   Affiliation

Abstract

The convenience and rapidity of financial leasing modes in the peer-to-peer (P2P) platform enable small and medium-sized enterprises (SMEs) to solve financing problems. The core of risk management in the P2P platform is to improve the quality of the docking assets. Therefore, the purpose of this paper is to establish a financial leasing value model of debt cession with an optimal economic pattern and an analysis of the risk assessment to improve the management of the asset value docking quality of both parties. For the transaction price of the leased assets in a P2P platform, this paper establishes multi-periodic, continuous, and variable models of the leased assets value evaluation, taking rent, lease term, and interest as independent variables. The paper proves that the price of the leased assets is related to the interest force, the rent per period, and the numbers of payments and changes in rent when other factors remain unchanged. Our results prove that the risk of the P2P platform docking finance lease and the transfer of the creditor’s rights investment mode are low. The proposed scheme is verified through hypothesis testing and model simulation. When the lease term is longer and the interest rate is higher, the difference between the two function surfaces is larger. Thus, the business model of financial leasing in the P2P platform has more obvious business advantages. It provides better business macro direction and business micro-management guidance for the leasing industry, P2P platforms and financial leasing companies.


First published online 21 December 2020

Keyword : P2P platform, financial leasing, asset value evaluation, finance lease docking, risk management

How to Cite
Qu, J., Liu, H., Zhu, H., & Gao, H. (2021). An asset value evaluation for docking finance lease problems in the peer-to-peer platform. Journal of Business Economics and Management, 22(1), 236-256. https://doi.org/10.3846/jbem.2020.13380
Published in Issue
Jan 27, 2021
Abstract Views
1380
PDF Downloads
845
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Azar, Y., Bartal, Y., Feuerstein, E., Fiat, A., Leonardi, S., & Rosen, A. (1999). On capital investment. Algorithmica, 25(1), 22–36. https://doi.org/10.1007/PL00009281

Bachmann, A., Becker, A., Buerckner, D., & Funk, B. (2011). Online peer-to-peer lending: A literature. Journal of Internet Banking and Commerce, 16, 1–18.

Ceyhan, S., Shi, X., & Leskovec, J. (2011). Dynamics of bidding in a P2P lending service: Effects of herding and predicting loan success. In Proceedings of the 20th international conference on World wide web (pp. 547–556). ACM. https://doi.org/10.1145/1963405.1963483

Chen, X., Zhou, L., & Wan, D. (2016). Group social capital and lending outcomes in the financial credit market: An empirical study of online peer-to-peer lending. Electronic Commerce Research and Applications, 15, 1–13. https://doi.org/10.1016/j.elerap.2015.11.003

Dai, W., Dong, Y., & Zhang, X. (2016). Competitive analysis of the online financial lease problem. European Journal of Operational Research, 250(3), 865–873. https://doi.org/10.1016/j.ejor.2015.10.020

El-Yaniv, R., Kaniel, R., & Linial, N. (1999). Competitive optimal on-line leasing. Algorithmica, 25(1), 116–140. https://doi.org/10.1007/PL00009279

El-Yaniv, R., & Karp, R. M. (1997). Nearly optimal competitive online replacement policies. Mathematics of Operations Research, 22(4), 814–839. https://doi.org/10.1287/moor.22.4.814

Freedman, S., & Jin, G. Z. (2017). The information value of online social networks: lessons from peerto-peer lending. International Journal of Industrial Organization, 51, 185–222. https://doi.org/10.1016/j.ijindorg.2016.09.002

Fenwick, M., McCahery, J. A., & Vermeulen, E. P. (2018). Fintech and the financing of SMEs and entrepreneurs: From crowdfunding to marketplace lending. In D. Cumming & L. Hornuf (Eds.), The economics of crowdfunding (pp. 103–129). Palgrave Macmillan. https://doi.org/10.1007/978-3-319-66119-3_6

Galloway, I. (2009). Peer-to-peer lending and community development finance. Community Investments, 21(3), 19–23.

Guo, Y., Zhou, W., Luo, C., Liu, C., & Xiong, H. (2016). Instance-based credit risk assessment for investment decisions in P2P lending. European Journal of Operational Research, 249(2), 417–426. https://doi.org/10.1016/j.ejor.2015.05.050

Gao, G. X., Fan, Z. P., Fang, X., & Lim, Y. F. (2018). Optimal stackelberg strategies for financing a supply chain through online peer-to-peer lending. European Journal of Operational Research, 267(2), 585–597. https://doi.org/10.1016/j.ejor.2017.12.006

Herrero-Lopez, S. (2009). Social interactions in P2P lending. In Proceedings of the 3rd Workshop on Social Network Mining and Analysis (p. 3). ACM. https://doi.org/10.1145/1731011.1731014

Herzenstein, M., Dholakia, U. M., & Andrews, R. L. (2011). Strategic herding behavior in peer-to-peer loan auctions. Journal of Interactive Marketing, 25(1), 27–36. https://doi.org/10.1016/j.intmar.2010.07.001

Karp, R. M. (1992, August). On-line algorithms versus off-line algorithms: How much is it worth to know the future?. In Proceedings of the IFIP 12th World Computer Congress on Algorithms, Software, Architecture – Information Processing ‘92 (Vol. 1, pp. 416–429). North-Holland Publishing Co.

Janda, K., & Svárovská, B. (2010). Investing into microfinance. Journal of Business Economics and Management, 11(3), 483–510. https://doi.org/10.3846/jbem.2010.24

Larrimore, L., Jiang, L., Larrimore, J., Markowitz, D., & Gorski, S. (2011). Peer to peer lending: The relationship between language features, trustworthiness, and persuasion success. Journal of Applied Communication Research, 39(1), 19–37. https://doi.org/10.1080/00909882.2010.536844

Lee, E., & Lee, B. (2012). Herding behavior in online P2P lending: An empirical investigation. Electronic Commerce Research and Applications, 11(5), 495–503. https://doi.org/10.1016/j.elerap.2012.02.001

Liang, Z., Wang, W., & Li, S. (2012). Decomposition valuation of complex real options embedded in creative financial leases. Economic Modelling, 29(6), 2627–2631. https://doi.org/10.1016/j.econmod.2012.09.001

Lin, M., Prabhala, N. R., & Viswanathan, S. (2013). Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending. Management Science, 59(1), 17–35. https://doi.org/10.1287/mnsc.1120.1560

Lin, X., Li, X., & Zheng, Z. (2017). Evaluating borrower’s default risk in peer-to-peer lending: evidence from a lending platform in China. Applied Economics, 49(35), 3538–3545. https://doi.org/10.1080/00036846.2016.1262526

Lotker, Z., Patt-Shamir, B., & Rawitz, D. (2008a). Rent, lease or buy: Randomized algorithms for multislope ski rental. In Proceedings of the 25th Symposium on Theoretical Aspects of Computer Science (STACS). https://arxiv.org/abs/0802.2832

Lotker, Z., Patt-Shamir, B., & Rawitz, D. (2008b). Ski rental with two general options. Information Processing Letters, 108(6), 365–368. https://doi.org/10.1016/j.ipl.2008.07.009

Ferreira, F. A. F., Spahr, R. W., Gavancha, I. F. M. D. (2013). Readjusting trade-offs among criteria in internal ratings of credit-scoring: An empirical essay of risk analysis in mortgage loans. Journal of Business Economics and Management, 14(4), 715–740. https://doi.org/10.3846/16111699.2012.666999

Milanesi, G. S. (2016). Simple and complex option valuation in financial leasing. Estudios Gerenciales, 32(138), 25–34. https://doi.org/10.1016/j.estger.2015.08.004

Puro, L., Teich, J. E., Wallenius, H., & Wallenius, J. (2011). Bidding strategies for real-life small loan auctions. Decision Support Systems, 51(1), 31–41. https://doi.org/10.1016/j.dss.2010.11.016

Sonenshein, S., Herzenstein, M., & Dholakia, U. M. (2011). How accounts shape lending decisions through fostering perceived trustworthiness. Organizational Behavior and Human Decision Processes, 115(1), 69–84. https://doi.org/10.1016/j.obhdp.2010.11.009

Wang, H., Greiner, M., & Aronson, J. E. (2009). People-to-people lending: The emerging e-commerce transformation of a financial market. In Value creation in e-business management (pp. 182–195). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03132-8_15

Yan, J., Yu, W., & Zhao, J. L. (2015). How signaling and search costs affect information asymmetry in P2P lending: The economics of big data. Financial Innovation, 1(1), 19. https://doi.org/10.1186/s40854-015-0018-1

Yang, X., Zhang, W., Zhang, Y., & Xu, W. (2012). Optimal randomized algorithm for a generalized skirental with interest rate. Information Processing Letters, 112(13), 548–551. https://doi.org/10.1016/j.ipl.2012.04.006

Zhao, H., Liu, Q., Zhu, H., Ge, Y., Chen, E., Zhu, Y., & Du, J. (2018). A sequential approach to market state modeling and analysis in online p2p lending. IEEE Transactions on Systems, Man, and Cybernetics: Systems. https://doi.org/10.1109/TSMC.2017.2665038

Zhang, K., & Chen, X. (2017). Herding in a P2P lending market: Rational inference OR irrational trust? Electronic Commerce Research and Applications, 23, 45–53. https://doi.org/10.1016/j.elerap.2017.04.001