A hierarchical framework for assessing corporate sustainability performance using a hybrid fuzzy synthetic method-DEMATEL

Ming-Lang Tseng, Kuo-Jui Wu, Li Ma, Tsai Chi Kuo and Fuyume Sai

Technological Forecasting and Social Change, 2019, vol. 144, issue C, 524-533

Abstract: This study constructs a valid and reliable hierarchical framework for assessing corporate sustainability performance. The traditional fuzzy synthetic method considers neither the causal interrelationships among criteria nor how to construct the hierarchical framework. In addition, previous studies have lacked a resource-based view, and few studies have discussed how to construct a hierarchical structure. Therefore, this study integrates the decision-making trial and evaluation laboratory method, exploratory factor analysis and the fuzzy synthetic method to assess corporate sustainability performance. The overall corporate sustainability assessment results for the Taiwanese textile industry are low because this industry needs to improve in social responsibility. However, the economic perspective performs well. This industry needs to focus on 1. the firm's economic activities; 2. stakeholder management; and 3. operational control aspects. The major causal effect criteria are listed in the discussion section. The contributions of this study are 1. a theoretical model to assess corporate sustainability performance and 2. the hybrid method proposed for this assessment.

Keywords: Corporate sustainability performance; Hierarchical framework; Fuzzy synthetic method; DEMATEL; Performance evaluation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162517305723
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:144:y:2019:i:c:p:524-533

DOI: 10.1016/j.techfore.2017.10.014

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().