| Yazarlar (4) |
Mehmet Ali Koseoglu
|
Doç. Dr. Hasan Evrim ARICI
Kastamonu Üniversitesi, Türkiye |
|
Mehmet Bahri Saydam
|
|
Victor Oluwafemi Olorunsola
|
| Özet |
| Purpose: Environmental, social and governance (ESG) scores are compelling for firm strategy and performance. Thus, this study aims to explore ESG scores’ predictive roles on global firms’ diversity scores. Design/methodology/approach: A total of 1,114 global firm-year data from the Thomson Reuters Eikon database was analyzed using machine learning algorithms like rpart, support vector machine, partykit and evtree. Findings: The results reveal a positive association between diversity, resulting in greater comprehensiveness and relevance. Broadly speaking, the two factors with the most significant values for calculating the overall diversity scores of businesses are ESG scores and social scores. ESG scores and environmental scores are the most effective predictors for the diversity pillar and people development scores. In contrast, community and social scores are the most important predictor factors for the inclusion scores. Originality/value: The research is particularly pertinent to managers and investors considering ESG issues while making decisions. The results indicate that leaders and practitioners should prioritize ESG elements and diversity problems to enhance performance. |
| Anahtar Kelimeler |
| Firm diversity | ESG scores | Machine learning algorithms | International firms | M14 |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayımlanan tam makale |
| Dergi Adı | NANKAI BUSINESS REVIEW INTERNATIONAL |
| Dergi ISSN | 2040-8749 |
| Makale Dili | İngilizce |
| Basım Tarihi | 02-2025 |
| Sayı | 1 |
| Doi Numarası | 10.1108/NBRI-06-2023-0055 |
| Atıf Sayıları |
