Green innovation is becoming more common among researchers and practitioners around the world due to environmental and social issues. Green innovation minimizes wastes and pollution, and also leads to financial gains and better image if implemented effectively. Nowadays, developing countries pay greater emphasis on environmental issues as their manufacturing industries are considered major contributors to pollution. Considering the case of a developing country (Pakistan), the study empirically identified the drivers of green innovation in the manufacturing industry. A hybrid methodology-Fuzzy Delphi method (FDM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC)-was used to develop a novel framework for analyzing the green innovation drivers. At first, green innovation drivers were selected from past studies; they were further screened by applying Fuzzy Delphi approach. The MICAMAC and ISM results indicate that "cost reduction" and "government support" are the most important drivers motivating green innovation implementation in the Pakistani manufacturing industry, while a green image appeared as the least significant driver of green innovation adoption. The study's findings have significant implications for managers and policymakers to develop green strategies for manufacturing sector.
Keywords: Environmental degradation; Green innovation; Interpretive structural modeling; Manufacturing industry; Sustainable development.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.