| Title |
Drivers to mitigate climate change in context of manufacturing industry: An emerging economy study |
| ID_Doc |
71674 |
| Authors |
Dwivedi, A; Sassanelli, C; Agrawal, D; Moktadir, MA; D'Adamo, I |
| Title |
Drivers to mitigate climate change in context of manufacturing industry: An emerging economy study |
| Year |
2023 |
| Published |
Business Strategy And The Environment, 32.0, 7 |
| DOI |
10.1002/bse.3376 |
| Abstract |
Business strategy and the environment are becoming increasingly central within the global agenda. In particular, some emerging countries such as India show strong growth in the manufacturing sector while also exhibiting high emission values. This inevitably creates a paradox. Therefore, this study aims to determine the drivers for Indian manufacturing firms to pursue sustainability. The methodologies used in this work is comprised of modified total interpretive structure modeling (m-TISM) that is based on 21 drivers to mitigate climate change and cross-impact matrix multiplication applied to classification (MICMAC) that evaluates the dependence power and driving power of the drivers. The findings from the study reflect that there are nine levels into which the clusters are divided. "greenhouse gas performance" and "encouraging low carbon products" are influenced by all other drivers, while the driver "dynamic transitions in economic and political situation" occupies a mirror position. This last driver has the greatest impact on the achievement of the goal along with "persistent with corporate conventionalities" and "dynamic transitions in economic and political situation." The economic dimension has a key asset in the manufacturing context, but the influence of sustainable technology on the supply side and of the responsible consumption on the demand side cannot be overlooked. Businesses that focus on short-term maximization by not focusing on renewable and circular resources may be uncompetitive in the long-term. |
| Author Keywords |
business strategy; carbon emissions; climate change; drivers; manufacturing industry; m-total interpretive structure modeling |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:000920523600001 |
| WoS Category |
Business; Environmental Studies; Management |
| Research Area |
Business & Economics; Environmental Sciences & Ecology |
| PDF |
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