2026-10-10T15:28:58Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33997621 2026-09-25T17:22:22Z category_7 category_734 category_61 category_106 portal_5 item_type_3 month_year_09_2026

<p>Classification of intelligent approval.</p> Jiaqi Wang (369548) Yali Wang (332169) Medicine Biological Sciences not elsewhere classified Developmental Biology Science Policy universally applicable methods sustainable development goals strengthen relevant legislation progressively expanded based lagged supervisory regime 38 tertiary indicators fuzzy comprehensive evaluation evaluation results indicated dedicated evaluation committee analytic hierarchy process leverage digital platforms smart cities development ineffective public supervision inadequate staff service government service transformation smart cities digital government evaluation object oriented transformation due process digital governance xlink "> value guidance valuable role targeted strategies several potential several challenges service standards prominent problems oriented transition literature research institutional norms future research explosive application determining first delphi method also contribute algorithmic decision <div><p>In the context of smart cities development and digital governance, administrative intelligent approval plays an effective and valuable role in government service transformation. However, the explosive application of technology has led to several challenges of approval quality such as inconsistent with due process, weak error correction mechanism of algorithmic decision-making and lagged supervisory regime, which hinder the service-oriented transformation. Therefore, it is essential to evaluate the quality of intelligent approval using rigorous, rational, and universally applicable methods, which may not only enhance the service standards of digital government and advance smart cities development toward maturity, but also contribute to achieving the Sustainable Development Goals. In the stage of evaluation indicator system construction, determining first-level indicators including legality, rationality, satisfaction and supervision by Delphi Method. Then the corresponding 10 secondary indicators and 38 tertiary indicators are progressively expanded based on value guidance, institutional norms, literature research and cases. In the stage of applying, Taiyuan in China is taken as the evaluation object and implemented through Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation. The evaluation results indicated that although the overall quality shows good, there are several potential and prominent problems, including insufficient specific modes, inaccessible the right to a hearing, inadequate staff service, ineffective public supervision and the lack of transparency, and the targeted strategies are proposed for improving the approval quality. Additionally, future research will establish a dedicated evaluation committee, leverage digital platforms more extensively, and strengthen relevant legislation and theoretical support.</p></div> 2026-09-25T17:22:13Z Dataset Dataset 10.1371/journal.pone.0354902.t001 https://figshare.com/articles/dataset/_p_Classification_of_intelligent_approval_p_/33997621 CC BY 4.0