Benchmarking the Operational Efficiency of China’s Peer-to-Peer Lending Platforms Based on Data Envelopment Analysis
Ao Liu, Xudong Deng, Zeping Tong, Yajuan Wang, Liang Ren
Available Online June 2018.
- https://doi.org/10.2991/icmess-18.2018.49How to use a DOI?
- Peer-to-peer lending; Efficiency evaluation; Data envelopment analysis; Benchmarking
- As a new financial loan model, peer-to-peer (P2P) lending has been widely spread across the world since emerging, especially in China. However, it often involves risk events, including difficult cash withdrawal, escaping with money, financial fraud, and trouble management etc. Therefore, how to evaluate its operational efficiency and determine a good platform plays a vital role in the operation of P2P lending platforms, which is also valuable for inexperienced lenders. In this paper, a data envelopment analysis (DEA) method was applied for measuring operational efficiency so as to separate efficient and inefficient P2P platforms in China. The results indicated that on the basis of the CCR model, the ratio of efficient and inefficient units in 60 platforms was 40% and 60% respectively; and the average of technical, pure technical and scale efficiencies of inefficient units were 0.700, 0.842, 0.800 respectively, which demonstrated that most of the difference between in efficient and inefficient units lies in the return to scale. The results also suggested the efficient benchmarking targets to guide inefficient units toward the efficient units.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Ao Liu AU - Xudong Deng AU - Zeping Tong AU - Yajuan Wang AU - Liang Ren PY - 2018/06 DA - 2018/06 TI - Benchmarking the Operational Efficiency of China’s Peer-to-Peer Lending Platforms Based on Data Envelopment Analysis BT - 2018 2nd International Conference on Management, Education and Social Science (ICMESS 2018) PB - Atlantis Press SP - 216 EP - 221 SN - 2352-5398 UR - https://doi.org/10.2991/icmess-18.2018.49 DO - https://doi.org/10.2991/icmess-18.2018.49 ID - Liu2018/06 ER -