An assessment of bank efficiency in Cambodia: A comparison between multi-criteria measurement and the DEA approach

This study provides a comprehensive evaluation of the competitiveness and efficiency of 52 Cambodian commercial banks through the integration of a multi-criteria Enterprise Competitiveness Index (ECI), two-stage Data Envelopment Analysis (DEA), and a Back Propagation Neural Network (BPNN). Grounded in the Resource-Based View (RBV), Dynamic Capability Theory (DCT), and the Resource–Capability–Performance (RCP) framework, the model captures both internal efficiency and broader strategic potential. The ECI offers a multidimensional benchmark encompassing financial, marketing, operational, and human resource dimensions. Two-stage DEA evaluates how effectively banks convert inputs (e.g., advertising, labor quality) into intermediate outputs (e.g., productivity measures) and subsequently into financial performance. A BPNN is incorporated to model non-linear relationships and forecast profitability outcomes with over 85 % prediction accuracy. Findings reveal significant variation in banks' ability to translate operational productivity into financial returns, indicating potential strategic misalignments. Some banks exhibit high resource utilization but fail to achieve commensurate profitability, while others demonstrate strong financial outcomes despite weaker operational foundations. The integration of the ECI and DEA highlights the distinction between technical efficiency and long-term competitiveness, while the BPNN enhances strategic foresight by capturing hidden patterns across performance variables. This multi-method approach offers valuable insights for regulators and managers in emerging financial markets, particularly in addressing governance, resource allocation, and sustainable growth strategies. The study not only fills methodological gaps in traditional banking efficiency models but also provides a robust tool for adaptive strategic planning in Cambodia's rapidly evolving banking landscape.