A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Rethinking Green Supply Chain Management Practices Impact on Company Performance: A Close-Up Insight
Manufacturing organisations have contributed to a poor living environment via unsustainable practices in the production process and the entire service delivery operation. More importantly, the health performance of manufacturing employees may also be affected by unsustainable production practices in the industry. Therefore, the green supply chain management (GSCM) practice has become a topical issue in recent decades due to its significant impact on the ecosystem at large. Via green practices, various performances have been achieved in organisations; meanwhile, the relationships between the practices and performance metrics in most developing countries are unclear, although there have been supposed general submissions. In addition, the study of relationships in a leading business conglomerate in developing nations is rare. Therefore, this paper investigated relationships between GSCM practices and performance metrics in a leading manufacturing organisation in Africa by using a close-up study approach with data collected from 154 respondents. The data were analysed using multiple methods such as factor analysis to consolidate the measured variables; correlation, multiple regression analysis with stepwise estimation, and structural equation modelling (SEM) were used to examine the relationships between GSCM practices and performance. The results of these analyses revealed that environmental performance is significantly predicted by the measure of the organisation’s commitment to GSCM vision, while financial performance is significantly impacted by eco-centric consumption and education. This study concludes that inhouse-drafted strategies based on the insight from the study will facilitate the optimisation of GSCM practices.
Rethinking Green Supply Chain Management Practices Impact on Company Performance: A Close-Up Insight
Manufacturing organisations have contributed to a poor living environment via unsustainable practices in the production process and the entire service delivery operation. More importantly, the health performance of manufacturing employees may also be affected by unsustainable production practices in the industry. Therefore, the green supply chain management (GSCM) practice has become a topical issue in recent decades due to its significant impact on the ecosystem at large. Via green practices, various performances have been achieved in organisations; meanwhile, the relationships between the practices and performance metrics in most developing countries are unclear, although there have been supposed general submissions. In addition, the study of relationships in a leading business conglomerate in developing nations is rare. Therefore, this paper investigated relationships between GSCM practices and performance metrics in a leading manufacturing organisation in Africa by using a close-up study approach with data collected from 154 respondents. The data were analysed using multiple methods such as factor analysis to consolidate the measured variables; correlation, multiple regression analysis with stepwise estimation, and structural equation modelling (SEM) were used to examine the relationships between GSCM practices and performance. The results of these analyses revealed that environmental performance is significantly predicted by the measure of the organisation’s commitment to GSCM vision, while financial performance is significantly impacted by eco-centric consumption and education. This study concludes that inhouse-drafted strategies based on the insight from the study will facilitate the optimisation of GSCM practices.
Rethinking Green Supply Chain Management Practices Impact on Company Performance: A Close-Up Insight
Lekan Damilola Ojo (author) / Onaopepo Adeniyi (author) / Olajide Emmanuel Ogundimu (author) / Olasunkanmi Ososanmi Alaba (author)
2022
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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