Open Access

ARTICLE

An Extended Fuzzy-DEMATEL System for Factor Analyses on Social Capital Selection in the Renovation of Old Residential Communities

Guoshuai Sun^1,2,3, Xiuru Tang¹, Shuping Wan^2,*, Jiao Feng⁴

1 School of Economics and Management, Liaoning University of Technology, Jinzhou, 121001, China
2 School of Information Management, Jiangxi University of Finance and Economics, Nanchang, 330032, China
3 Post-Doctoral Research Center, Zhongda Construction Co., Ltd., Guangzhou, 510280, China
4 School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, China

* Corresponding Author: Shuping Wan. Email:

(This article belongs to the Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2023, 134(2), 1041-1067. https://doi.org/10.32604/cmes.2022.021981

Received 16 February 2022; Accepted 13 April 2022; Issue published 31 August 2022

Abstract

China has been promoting the renovation of old residential communities vigorously. Due to the financial pressure of the government and the sustainability of the renovation of old residential communities, public-private partnerships (PPP) have already gained attention. The selection of social capital is key to improving the efficiency of the PPP model in renovating old residential communities. In order to determine the influencing factors of social capital selection in the renovation of old residential communities, this paper aims to find an effective approach and analyze these factors. In this paper, a fuzzy decision-making and trial evaluation laboratory (fuzzy-DEMATEL) technique is extended and a more suitable system is developed for the selection of social capital using the existing group decision-making theory. In the first stage, grounded theory is used to extract the unabridged key influencing factors for social capital selection in the renovation of old residential communities. Secondly, by considering the impact of expert weights, the key influencing factors are identified. The interactions within these influencing factors are discussed and the credibility of the results is verified by sensitivity analysis. Finally, these key influencing factors are sorted by importance. Based on the results, the government should focus on a technical level, organizational management abilities, corporate reputation, credit status, etc. This study provides the government with a theoretical basis and a methodology for evaluating social capital selection.

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Keywords

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