| Yazarlar |
Mehmet Ali Koseoglu
Metropolitan State University, United States |
|
Hasan Evrim Arici
Kastamonu University, Turkey |
|
Mehmet Bahri Saydam
Kastamonu University, Turkey |
|
Victor Oluwafemi Olorunsola
Kastamonu University, Turkey |
| Özet |
| Purpose: The interconnected challenges of climate change and social inclusivity have placed unprecedented pressure on businesses to adopt responsible practices. While previous research has explored the individual impacts of environmental, social, and governance (ESG) performance and diversity initiatives, there remains a dearth of comprehensive investigations into how these factors collectively influence carbon emission scores. Drawing on the legitimacy theory, we explore whether ESG and diversity scores predict global companies' carbon emission scores. As concerns about the environmental impact of businesses grow, understanding the relationships between ESG performance, diversity management, and carbon emissions becomes imperative for sustainable corporate practices. Design/methodology/approach: The primary dataset for this study includes 1,268 worldwide firm-year data for 2021. The sample is subjected to missing data examination as a component of the filtration process. Data preprocessing is performed before machine learning analysis, including verifying missing data. Our research resulted in the final sample, which includes 627 worldwide firm data from 2021. Data regarding all publicly traded companies was obtained from Refinitiv Eikon. Findings: Our findings showed that corporate carbon emission performance in global corporations is influenced by ESG performance and total diversity score. Originality/value: Firms involve in ESG as well as diversity practices to be able to achieve sustainable success. Yet, the forecasting of carbon emissions based on ESG scores and diversity scores remains inadequately established due to conflicting findings and enigmas prevalent in the literature. |
| Anahtar Kelimeler |
| Carbon emission | Diversity | ESG performance | Global companies | Machine learning |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SCOPUS dergilerinde yayımlanan tam makale |
| Dergi Adı | Management Decision |
| Dergi ISSN | 0025-1747 |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2024 |
| Sayı | 1 |
| Doi Numarası | 10.1108/MD-05-2023-0818 |
| Atıf Sayıları |
