New Perspectives on the Causes of Stagnation and Decline in the Sharing Economy: Application of the Hybrid Multi-Attribute Decision-Making Method

Against the backdrop of global economic changes and rapid technological innovation, the sharing economy model is gradually transforming the operational mechanisms of traditional industries. However, some industries have experienced stagnation and recession during this transition, leading to market development constraints. The necessity of this study lies in filling the gap in the existing literature by conducting an in-depth analysis of the critical factors contributing to industrial stagnation and recession in the sharing economy. This study aims to provide concrete countermeasures for businesses and policymakers. The novelty of this research study lies in integrating multiple key variables affecting industrial development, including green production concepts, the circular economy, large-scale production, high-quality product demand driven by industrial automation, the sharing economy, and smart production. By employing multi-criterion decision-making methods, we quantitatively assess the impact of these factors more accurately. This study employs the Multi-Attribute Decision-Making (MADM) model, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP) to form D&ANP for analytical research. Highly automated industries are selected as the research subjects. The DEMATEL technique is used to construct the Influential Network Relationship Map (INRM), while the ANP concept is incorporated to develop the D&ANP model. Through the D&ANP method, influential weights are calculated and combined with industry-specific assessments of the suitability of potential causes (or attributes) contributing to economic stagnation and recession to determine the average performance values for each industry. These values are further compared with benchmark suitability performance values to distinguish ideal and non-ideal conditions across industries facing economic stagnation and recession. The analysis results indicate that different industries are influenced by varying factors, requiring strategic adjustments based on their unique development environments. Accordingly, this study provides industry-specific recommendations to optimize business models and resource allocation, mitigate the risks of economic stagnation and recession, and promote sustainable industrial development and economic recovery. The findings of this study not only contribute to empirical research on the impact of the sharing economy on industrial development but also serve as a decision-making reference for businesses. By offering strategic insights, enterprises can better respond to market dynamics, enhance competitiveness, and ensure long-term stable growth.

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Publication Details

Journal
Mathematics
Published
2025-03-24
DOI
https://doi.org/10.3390/math13071051
Citations
4
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
8.29
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New Perspectives on the Causes of Stagnation and Decline in the Sharing Economy: Application of the Hybrid Multi-Attribute Decision-Making Method

C. W. Liu, Hsu-Hua Lee, Chien‐Hua Chen, Li-Han Kao et al.
4 citations
Mathematics
Sharing Economy and Platforms
8.29
article

New Perspectives on the Causes of Stagnation and Decline in the Sharing Economy: Application of the Hybrid Multi-Attribute Decision-Making Method

C. W. Liu, Hsu-Hua Lee, Chien‐Hua Chen, Li-Han Kao, Wen-Tsung Wu
article en
4 citations

Abstract

Against the backdrop of global economic changes and rapid technological innovation, the sharing economy model is gradually transforming the operational mechanisms of traditional industries. However, some industries have experienced stagnation and recession during this transition, leading to market development constraints. The necessity of this study lies in filling the gap in the existing literature by conducting an in-depth analysis of the critical factors contributing to industrial stagnation and recession in the sharing economy. This study aims to provide concrete countermeasures for businesses and policymakers. The novelty of this research study lies in integrating multiple key variables affecting industrial development, including green production concepts, the circular economy, large-scale production, high-quality product demand driven by industrial automation, the sharing economy, and smart production. By employing multi-criterion decision-making methods, we quantitatively assess the impact of these factors more accurately. This study employs the Multi-Attribute Decision-Making (MADM) model, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP) to form D&ANP for analytical research. Highly automated industries are selected as the research subjects. The DEMATEL technique is used to construct the Influential Network Relationship Map (INRM), while the ANP concept is incorporated to develop the D&ANP model. Through the D&ANP method, influential weights are calculated and combined with industry-specific assessments of the suitability of potential causes (or attributes) contributing to economic stagnation and recession to determine the average performance values for each industry. These values are further compared with benchmark suitability performance values to distinguish ideal and non-ideal conditions across industries facing economic stagnation and recession. The analysis results indicate that different industries are influenced by varying factors, requiring strategic adjustments based on their unique development environments. Accordingly, this study provides industry-specific recommendations to optimize business models and resource allocation, mitigate the risks of economic stagnation and recession, and promote sustainable industrial development and economic recovery. The findings of this study not only contribute to empirical research on the impact of the sharing economy on industrial development but also serve as a decision-making reference for businesses. By offering strategic insights, enterprises can better respond to market dynamics, enhance competitiveness, and ensure long-term stable growth.

MathematicsVol. 13(7)
Tamkang University (TW), National Dong Hwa University (TW)
Openalex Percentile: Top 3%
Sharing Economy and Platforms
8.29
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