Student Debt Trap on P2P Lending Platforms: A Structural Equation Modeling Approach

The rise of Peer-to-Peer (P2P) lending platforms has provided students with alternative financing options. However, this convenience comes with the risk of over-indebtedness, which can have long-term financial repercussions. This study explores the factors contributing to student over-indebtedness on P2P lending platforms. Specifically, it examines the roles of financial stress and repayment behaviors in exacerbating this issue. The primary aim of this research is to understand how financial stress and repayment behaviors influence student over-indebtedness. A Structural Equation Modeling Approach was employed, using purposive sampling to select student participants. The findings indicate that financial stress significantly and positively influences student over-indebtedness on P2P Lending platforms. Similarly, repayment behavior also has a significant positive effect on student over-indebtedness on P2P Lending platforms. The study highlights the critical need for targeted financial education and support mechanisms to help students manage their finances effectively and avoid the pitfalls of over-indebtedness on P2P lending platforms.

Authors

Institutions

Publication Details

Journal
Nusantara Science and Technology Proceedings
Published
2025-05-06
DOI
https://doi.org/10.11594/nstp.2025.4712
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Student Debt Trap on P2P Lending Platforms: A Structural Equation Modeling Approach

Nanik Hariyana, Fani Khoirotunnisa, Tri Kartika Pertiwi, Corina Joseph et al.
Nusantara Science and Technology Proceedings
FinTech, Crowdfunding, Digital Finance
article

Student Debt Trap on P2P Lending Platforms: A Structural Equation Modeling Approach

Nanik Hariyana, Fani Khoirotunnisa, Tri Kartika Pertiwi, Corina Joseph, G. Oka Warmana, Amalya Diva Andriyani
article en

Abstract

The rise of Peer-to-Peer (P2P) lending platforms has provided students with alternative financing options. However, this convenience comes with the risk of over-indebtedness, which can have long-term financial repercussions. This study explores the factors contributing to student over-indebtedness on P2P lending platforms. Specifically, it examines the roles of financial stress and repayment behaviors in exacerbating this issue. The primary aim of this research is to understand how financial stress and repayment behaviors influence student over-indebtedness. A Structural Equation Modeling Approach was employed, using purposive sampling to select student participants. The findings indicate that financial stress significantly and positively influences student over-indebtedness on P2P Lending platforms. Similarly, repayment behavior also has a significant positive effect on student over-indebtedness on P2P Lending platforms. The study highlights the critical need for targeted financial education and support mechanisms to help students manage their finances effectively and avoid the pitfalls of over-indebtedness on P2P lending platforms.

Nusantara Science and Technology Proceedings
University of Pembangunan Nasional Veteran Jawa Timur (ID), Universiti Teknologi MARA (MY)
Openalex Percentile: Top 77%
FinTech, Crowdfunding, Digital Finance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Student Debt Trap on P2P Lending Platforms: A Structural Equation Modeling Approach — Nanik Hariyana, Fani Khoirotunnisa, et al. · Nusantara Science and Technology Proceedings (2025) | TGRS Research Map | TGRS