Agricultural loan efficiency in centralized bank supply chains with fairness concern: a DEA-based analysis

Abstract

PurposeDue to the rapid development and innovation in the Internet-based technology, conventional banks are under pressure and have to compete with Internet-based finance. This has made banks adopt measures to improve operational efficiency and reduce input and increase output.Design/methodology/approachThe authors had proposed a two-stage fairness concern efficiency model based on the classical theory of data envelopment analysis (DEA) and performed an empirical study to measure agricultural loan efficiency in the 20 major Chinese banks.FindingsThe findings of the empirical analysis are as follows: (1) peer-induced fairness concern has no impact on deposit efficiency in a centralized bank supply chain; (2) The China Merchants Bank (CMB) has the third lowest deposit efficiency; (3) monotonicity of loan efficiency with input allocation depends on a bank's ownership structure; (4) efficiency ranks are strongly affected by the fairness concern; (5) most Chinese banks show a low agricultural loan efficiency.Originality/valueThis paper contributes to the literature in several ways. First, to the best of the authors’ knowledge, this is the first attempt to analyze agricultural loan efficiency for a bank supply chain system with the fairness concern. This work reveals the hidden factor that restricts loan efficiency of Chinese banks. Second, the proposed fairness concern two-stage DEA model has shown good ability for full ranking. It can provide a new perspective to the classical DEA literature for ranking decision-making units (DMUs). Third, the authors have demonstrated empirical bank efficiency for the 20 major Chinese banks.