Borrower switching behaviour on a P2P lending platform: a study of switching path analysis technique

被引:0
作者
Akbar, Rasyidi Faiz [1 ]
Sukoco, Badri Munir [2 ]
Nadia, Fiona Niska Dinda [3 ]
机构
[1] Univ Airlangga, Dept Management, Surabaya, Indonesia
[2] Univ Airlangga, Postgrad Sch, Dept Management, Surabaya, Indonesia
[3] Airlangga Univ, Postgrad Sch, Human Resource Dev Program, Surabaya, Indonesia
来源
COGENT BUSINESS & MANAGEMENT | 2024年 / 11卷 / 01期
关键词
Online P2P lending; financial services; borrower switching; micro finance; financial inclusion; Business; Management and Accounting; Finance; Economics; PEER; INFORMATION; MIGRATION; COMPANY; LENDERS; FINTECH; QUALITY; TRUST;
D O I
10.1080/23311975.2024.2422562
中图分类号
F [经济];
学科分类号
02 ;
摘要
Despite borrower disloyalty being a concern, path decisions must still be analysed. Using the switching path analysis technique, this study analysed the triggers, determinants, and consequences of borrower switching. A non-probability sampling method was employed for this analysis. Specifically, snowball sampling was used to collect data because of limited access to Indonesian peer-to-peer lending (P2P) borrowers in borrower lending groups. Snowball sampling was used to recruit more P2P lending borrowers in Indonesia. The sampling method included 31 participants. The findings revealed the following: (1) triggers (situational, influential, and reactional); (2) switching determinants (push, pull, and swayer); and (3) consequences of switching (ir-path or re-path). This study contributes to the service literature by providing a sequential process lens to address how borrowers switch or stop with one P2P lending provider. The findings provide practitioners with data that will allow them to learn how borrowers switch and prevent them from switching.
引用
收藏
页数:20
相关论文
共 50 条
  • [31] A rejection inference technique based on contrastive pessimistic likelihood estimation for P2P lending
    Xia, Yufei
    Yang, Xiaoli
    Zhang, Yeying
    ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS, 2018, 30 : 111 - 124
  • [32] Can Investors on P2P Lending Platforms Identify Default Risk?
    Hu, Rongcai
    Liu, Meng
    He, Pingping
    Ma, Yong
    INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2019, 23 (01) : 63 - 84
  • [33] Proof of Concept of Blockchain Integration in P2P Lending for Developing Countries
    Mbodji, Fatou Ndiaye
    Mendy, Gervais
    Mbacke, Ahmath Bamba
    Ouya, Samuel
    E-INFRASTRUCTURE AND E-SERVICES FOR DEVELOPING COUNTRIES (AFRICOMM 2019), 2020, 311 : 59 - 70
  • [34] Detection of Defaulters in P2P Lending Platforms using Unsupervised Learning
    Mukherjee, Partha
    Badr, Youakim
    2022 IEEE INTERNATIONAL CONFERENCE ON OMNI-LAYER INTELLIGENT SYSTEMS (IEEE COINS 2022), 2022, : 48 - 52
  • [35] Why Do So Many Online P2P Lending Platform in China Turn Bad: Scenario Analysis Viewpoint
    Jing, Ran-zhe
    2018 INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATIONS AND MECHATRONICS ENGINEERING (CCME 2018), 2018, 332 : 673 - 677
  • [36] Lender Trust on the P2P Lending: Analysis Based on Sentiment Analysis of Comment Text
    Niu, Beibei
    Ren, Jinzheng
    Zhao, Ansa
    Li, Xiaotao
    SUSTAINABILITY, 2020, 12 (08)
  • [37] Public Perception of Online P2P Lending Applications
    Khan, Sahiba
    Singh, Ranjit
    Baker, H. Kent
    Jain, Gomtesh
    JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH, 2024, 19 (01): : 507 - 525
  • [38] Voluntary disclosure in P2P lending: Information or hyperbole?
    Wang, Chao
    Wang, Junbo
    Wu, Chunchi
    Zhang, Yue
    PACIFIC-BASIN FINANCE JOURNAL, 2023, 79
  • [39] P2P lending in China: Role and prospects for the future
    Hsu, Sara
    Li, Jianjun
    Bao, Hong
    MANCHESTER SCHOOL, 2021, 89 (05) : 526 - 540
  • [40] Ripple effects of borrower's default decisions on P2P markets
    Lu, Yong
    Gao, Qiang
    Hou, Liya
    Hu, Yanni
    Huang, Jian
    INTERNATIONAL JOURNAL OF FINANCIAL ENGINEERING, 2021, 8 (02)