Research on performance evaluation of public administration departments based on Rao-Stirling diversity algorithm

This investigation delves into public administration sector performance, leveraging the Rao-Stirling diversity algorithm, traditionally utilized in assessing the interdisciplinarity of scientific research.The study repurposes this algorithm for public management, enabling the quantification and nuanced analysis of diversity in policy execution and service provision.Initially, we establish a suite of pivotal public management performance metrics encompassing service quality, efficacy of policy implementation, and equity in resource distribution, segmenting these into various evaluative dimensions.Subsequently, the Rao-Stirling algorithm is employed to dissect the variances and synergies across these dimensions and their cumulative effect on overall performance.The results illuminate the complex web of interrelations among distinct administrative functions and services, offering profound implications for enhancing public management's efficiency and effectiveness.Moreover, the study critically assesses the Rao-Stirling algorithm's applicability and constraints in gauging public management performance, thus contributing novel insights and methodological recommendations for future inquiries within this domain.