Author
Listed:
- Samuel Ogbeibu
- Jude Emelifeonwu
- Vijay Pereira
- Raphael Oseghale
- James Gaskin
- Uthayasankar Sivarajah
- Angappa Gunasekaran
Abstract
With growing climate change concerns, and constant advancements in smart technology, artificial intelligence, robotics, and algorithms (STARA), organisations in emerging economies are becoming more compelled to go green, develop and deploy their STARA capability to boost profits more effectively, and their environmental sustainability (ES). Likewise, with governments increasingly calling for ES, organisations' human resource management (HRM) is further pressured to ensure their programmes aid realisation of environmental objectives without compromising profit maximisation. However, it remains unclear how complementary Green HRM (GHRM) programmes can be supported by organisational STARA capability (OSC) to bolster ES. Accordingly, we investigate how OSC and GHRM programmes predict ES through a time lagged survey design with data from 461 managers of 177 manufacturing organisations in Nigeria. Results indicate that OSC positively predicts all GHRM programmes and ES but dampens the positive relationship between green training, involvement and development (GTID), and ES. Apart from green performance and compensation (GPC), which is a negative predictor, other GHRM programmes positively predict ES. While green recruitment and selection (GRS) and GTID are complementary mediators, GPC plays a competitive mediating role. Policy implications are subsequently discussed.
Suggested Citation
Samuel Ogbeibu & Jude Emelifeonwu & Vijay Pereira & Raphael Oseghale & James Gaskin & Uthayasankar Sivarajah & Angappa Gunasekaran, 2024.
"Demystifying the roles of organisational smart technology, artificial intelligence, robotics and algorithms capability: A strategy for green human resource management and environmental sustainability,"
Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 369-388, February.
Handle:
RePEc:bla:bstrat:v:33:y:2024:i:2:p:369-388
DOI: 10.1002/bse.3495
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