Diversified Filtering Mechanism for Evaluation Indicators of Urban Road Renewal Schemes

Author:

Du Juan1ORCID,Liu Bing1,Wu Yimeng1,Li Xiufang2,Sugumaran Vijayan34ORCID

Affiliation:

1. SILC Business School, Shanghai University, 20 Chengzhong Road, Jiading, Shanghai 201800, China

2. Shanghai Tunnel Engineering Co., Ltd., 1099 Wanping South Road, Xuhui, Shanghai 200032, China

3. School of Business Administration, Oakland University, Rochester, MI 48309, USA

4. Center for Data Science and Big Data Analytics, Oakland University, Rochester, MI 48309, USA

Abstract

As global urban infrastructure renewal progresses, the urgent need for sustainability-driven urban renewal intensifies amidst resource scarcity and environmental concerns. Effective evaluation and decision making regarding urban road renewal schemes are prerequisites for their successful implementation. However, variation in the prioritization of indicators in project evaluations and the poor adaptability of existing frameworks hinder the quick assessment of diverse projects. To address this issue, this paper proposes a scheme evaluation framework with embedded renewal project features comprising four modules. Following the initial construction of a sustainability-driven evaluation system, an indicator-filtering mechanism combining the Latent Dirichlet Allocation (LDA) model with a text similarity algorithm is developed. The Entropy Weight-–TOPSIS method is then employed to derive the final optimal decision based on selected indicators. Applying the decision framework to the G15 Jialiu Widening and Reconstruction Project in Shanghai, China, indicators are reduced by 48.3%, with the optimal scheme decision consistent with the traditional Entropy Weight–TOPSIS method. The framework is robust and enhances decision efficiency, filling theoretical gaps in existing indicator-filtering mechanisms.

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality Project

Publisher

MDPI AG

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