A Game-Theoretic and Double-Frontier DEA Approach with Combined Weighting for Evaluating Converged Media Centers

Abstract

In the context of media convergence, evaluating the construction effectiveness of converged media centers has become crucial. Taking the converged media center as the research object, this paper divides the evaluation into three dimensions: institutional construction evaluation (input perspective), convergence effect evaluation (output perspective), and operational efficiency evaluation (input-output relationship). The respective index systems for institutional construction and convergence effect are established, and a comprehensive evaluation algorithm integrating subjective and objective assessments is proposed. A depersonalized AHP method is designed to optimize subjective weights, the CRITIC method is employed to calculate objective weights, and game theory is applied to combine them, yielding comprehensive evaluation weights. Based on corresponding indicator data, the evaluation results for institutional construction and convergence effect are obtained. For operational efficiency, an evaluation model based on double-frontier stochastic DEA is proposed, with input and output indicators being the first-level indicators of the two systems. Optimal efficiency and worst efficiency are calculated from the optimal and worst frontiers, respectively, and unified via the geometric mean method to obtain comprehensive efficiency. Compared with traditional DEA, this method effectively distinguishes the relative efficiency among decision-making units with an efficiency of 1. Pearson correlation test results of comprehensive efficiency values under different risk levels show a strong positive correlation, indicating the model's feasibility and stability. Finally, a case study of 36 converged media centers verifies the applicability of the proposed evaluation method, providing a new approach for the assessment of converged media centers.