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1412. Two-stage DEA model to evaluate corporate efficiency in sustainability
Invited abstract in session TA-51: Corporate finance risk management, stream Risk management in finance.
Tuesday, 8:30-10:00Room: M5 (building: 101)
Authors (first author is the speaker)
| 1. | Kristina Sutiene
|
| Department of Mathematical Modeling, Kaunas University of Technology | |
| 2. | Clara Vaz
|
| Research Centre in Digitalization and Intelligent Robotics, Instituto Politécnico de Bragança | |
| 3. | Raminta Vaitiekuniene
|
| Department of Finance; Sustainable Economics research group, Vilnius University; Kaunas University of Technology |
Abstract
The relationship between environmental, social, and corporate governance (ESG) and corporate financial performance (CFP) has been widely explored and continues to be an active area of research. Two main directions could be revealed. Investor-centric studies seek to directly link ESG to CFP using benchmarks and adopting a portfolio accordingly, while corporate-focused research explores different elements of performance like innovation and operational efficiency to understand the impact of ESG initiatives on CFP. These studies commonly employ correlation analysis, mediating factors, or regression analysis to disclose those patterns. Notably, some studies employ Data Envelopment Analysis (DEA) to assess corporate efficiency by minimizing their resources and maximizing ESG. We contribute to this field by using a benefit-of-the-doubt (BoD) model based on the DEA, which is used to calculate a composite indicator of ESG for manufacturing corporates. Then, in the second stage of this model the panel regression is used to identify elements of CFP and their significance for the ESG outcome. The results of corporate ESG efficiency is discussed in a view of corporate operating country, region and development level. The research has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-PD-22-23.
Keywords
- Sustainable Development
- Data Envelopment Analysis
- OR in Sustainability
Status: accepted
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