Strategic Performance Evaluation Using the Interval Malmquist Index for Institutional Assessment

This study proposes an advanced framework for performance evaluation by extending the Malmquist Productivity Index (MPI) to accommodate interval data, addressing the inherent uncertainty and imprecision frequently encountered in institutional assessments.In many contexts, input-output data are often reported as intervals rather than precise values, which poses significant challenges for evaluating productivity changes.The extended MPI model allows for a more comprehensive analysis of performance by incorporating such interval data, thus providing a robust mechanism for assessing both progress and regression in the productivity of Decision-Making Units (DMUs).A case study on university departments is employed to demonstrate the practical application of this interval-based model.The results highlight notable variations in efficiency and technological advancement, offering valuable insights for institutional decision-makers.The proposed methodology enhances the accuracy of performance evaluation in dynamic and uncertain environments, making it a powerful tool for strategic planning and policy formulation.Furthermore, it is suggested that this interval-based approach offers a significant improvement over traditional models by accounting for the uncertainty present in real-world data.The study contributes to the broader field of strategic performance analytics by advancing the methodological understanding of productivity analysis, offering a more nuanced and reliable framework for institutional assessment.