JOURNAL ARTICLE
Applying information ecological theory to analyse the green supply chain management system in universities.
Published In: Expert Systems, 2024, v. 41, n. 5. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Wang, Qi; Zhang, Wenjie; Ma, Lan 3 of 3
Abstract
In order to create higher benefits for enterprises in the university supply chain and make them meet the requirements of sustainable development, this study uses information ecology theory to study the cognitive management and transformation path of the green supply chain. Firstly, the related concepts of university supply chain management and green supply chain management are expounded, and the differences are mainly discussed. Then, the evaluation of supply chain greenness is studied. The fuzzy hierarchical comprehensive evaluation method combining quantitative and qualitative is used to establish the evaluation model. Finally, the proposed evaluation model is tested. The test results show that Suzhou University's greenness fuzzy evaluation score is 58.2 points, which is a medium level. The resource factor scored 61 points, the energy factor scored 52.9 points, the environmental factors scored 59.8 points, the economic factor scored 62.7 points, and the social factor scored 55.5 points. The company has obvious advantages in terms of resources and economy, but the level is not very high. The higher the cost synergy between enterprises and customers, the greater the environmental cost synergy. Therefore, manufacturing enterprises should strengthen communication and cooperation with customers. The higher the cost synergy control of manufacturing and waste recycling enterprises, the greater the synergy effect of environmental cost control. Therefore, increasing cooperation with waste recycling enterprises is conducive to developing environmental cost control and coordinated benefits. The proposed scheme provides some ideas for applying information ecology theory in the university supply chain. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Expert Systems. 2024/05, Vol. 41, Issue 5, p1
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2024
- ISSN:0266-4720
- DOI:10.1111/exsy.13219
- Accession Number:176451530
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