A two-step profit efficiency evaluation method based on predicted performance, with an application to Chinese commercial banks

Abstract

Purpose

The purpose of this study is to evaluate the profit efficiency of decision-making units (DMUs) based on predicted future information to solve the lag problem of improvement benchmarks given by the traditional profit efficiency model.

Design/methodology/approach

This paper proposes a two-step profit efficiency evaluation method. The first step predicts the future input and output information of DMUs through the past time-series data, obtaining a likely production possibility set (PPS) and profit frontier for the next period. The second step calculates DMUs' profit efficiency based on the predictions obtained in the first step and provides predictive benchmarking for DMUs.

Findings

The empirical results show that the proposed method yields good solutions for the lag problem of benchmarks given in ex-post evaluation, enabling bank managers to use predicted future information to achieve better improvement. Besides, compared with the technical efficiency measure, profit efficiency can better reflect the financial situation of DMUs and give the specific gap between the evaluated and optimal DMU.

Practical implications

For bank managers, the authors' new technique is advantageous for grasping the initiative of development because this technique accounts for the future development of the whole industry and sets forward-looking targets. These advantages can help banks improve in a more favorable direction and improve the asset management ability of banks.

Originality/value

This paper combines the data envelopment analysis (DEA) profit efficiency model with performance prediction and proposes a new two-step profit efficiency model, filling a gap in previous studies.

Citation

Wu, J., Liu, Q. and Zhou, Z. (2023), "A two-step profit efficiency evaluation method based on predicted performance, with an application to Chinese commercial banks", Kybernetes, Vol. 52 No. 12, pp. 5811-5828. https://doi.org/10.1108/K-03-2022-0407