A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes
Abstract This research presents an innovative framework for exploring the phenomenon of greenwashing within the context of domain-specific enterprises that are adapting to diverse institutional landscapes. This is achieved through the deployment of a groundbreaking environmental, social, and governa...
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SpringerOpen
2025-04-01
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| Series: | Future Business Journal |
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| Online Access: | https://doi.org/10.1186/s43093-025-00497-8 |
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| author | Mahdi Ghaemi Asl |
| author_facet | Mahdi Ghaemi Asl |
| author_sort | Mahdi Ghaemi Asl |
| collection | DOAJ |
| description | Abstract This research presents an innovative framework for exploring the phenomenon of greenwashing within the context of domain-specific enterprises that are adapting to diverse institutional landscapes. This is achieved through the deployment of a groundbreaking environmental, social, and governance leadership transition index, specifically designed for climate resilience. The index effectively integrates artificial intelligence and machine learning in conjunction with human cognitive expertise. Additionally, the study utilizes a chrono-convolutional neural network to investigate the dynamics of long-term memory concerning the nexus of innovative green fintech index and sectoral investments, thereby assessing the potential for greenwashing activities. This study also recognizes the varying institutional frameworks and approaches to climate risk management between emerging and developed nations. Adopting the quantile-based method, the long-term total connectedness index is assessed across market states. The analysis incorporates 11 sectoral investment indices from emerging and developed countries, comprising 22 international evolving investments. Temporal convolutional networks are leveraged to evaluate long-term memory under varying market conditions. The investigation highlights significant variances in the accuracy of long-term memory between indices representing emerging and developed markets. Notably, emerging markets exhibit a greater degree of precision about climate-smart initiatives. In particular, the mid-range quantiles of emerging market indices display the highest levels of accuracy across a broad spectrum of investments. These observations imply that developed markets, particularly under extreme economic conditions, may foster more favorable conditions for greenwashing practices. Moreover, a sectoral analysis reveals that, irrespective of market maturity, the energy and utilities sectors demonstrate the lowest propensity for greenwashing, while the information technology sector ranks similarly low in this regard. In contrast, real estate firms reveal a heightened susceptibility to greenwashing within developed markets, whereas their counterpart firms in emerging markets exhibit a markedly lower risk of engaging in such practices. The study offers valuable guidance to policymakers and regulators. Insights can inform targeted interventions promoting climate-resilient investment practices, contributing to sustainable development goals. Fostering reliable, interconnected emerging markets enhances the institutional quality and sustainability transition. Overall, the research provides a crucial perspective for navigating the complex landscape at the intersection of finance, climate resilience, and greenwashing. It illuminates the interplay between market fluctuations, green deception, and sustainable climate investment needs. |
| format | Article |
| id | doaj-art-71fbc570bd4e46e1b21170e8b98251de |
| institution | OA Journals |
| issn | 2314-7210 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Future Business Journal |
| spelling | doaj-art-71fbc570bd4e46e1b21170e8b98251de2025-08-20T01:47:29ZengSpringerOpenFuture Business Journal2314-72102025-04-0111113810.1186/s43093-025-00497-8A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapesMahdi Ghaemi Asl0Faculty of Economics, Kharazmi UniversityAbstract This research presents an innovative framework for exploring the phenomenon of greenwashing within the context of domain-specific enterprises that are adapting to diverse institutional landscapes. This is achieved through the deployment of a groundbreaking environmental, social, and governance leadership transition index, specifically designed for climate resilience. The index effectively integrates artificial intelligence and machine learning in conjunction with human cognitive expertise. Additionally, the study utilizes a chrono-convolutional neural network to investigate the dynamics of long-term memory concerning the nexus of innovative green fintech index and sectoral investments, thereby assessing the potential for greenwashing activities. This study also recognizes the varying institutional frameworks and approaches to climate risk management between emerging and developed nations. Adopting the quantile-based method, the long-term total connectedness index is assessed across market states. The analysis incorporates 11 sectoral investment indices from emerging and developed countries, comprising 22 international evolving investments. Temporal convolutional networks are leveraged to evaluate long-term memory under varying market conditions. The investigation highlights significant variances in the accuracy of long-term memory between indices representing emerging and developed markets. Notably, emerging markets exhibit a greater degree of precision about climate-smart initiatives. In particular, the mid-range quantiles of emerging market indices display the highest levels of accuracy across a broad spectrum of investments. These observations imply that developed markets, particularly under extreme economic conditions, may foster more favorable conditions for greenwashing practices. Moreover, a sectoral analysis reveals that, irrespective of market maturity, the energy and utilities sectors demonstrate the lowest propensity for greenwashing, while the information technology sector ranks similarly low in this regard. In contrast, real estate firms reveal a heightened susceptibility to greenwashing within developed markets, whereas their counterpart firms in emerging markets exhibit a markedly lower risk of engaging in such practices. The study offers valuable guidance to policymakers and regulators. Insights can inform targeted interventions promoting climate-resilient investment practices, contributing to sustainable development goals. Fostering reliable, interconnected emerging markets enhances the institutional quality and sustainability transition. Overall, the research provides a crucial perspective for navigating the complex landscape at the intersection of finance, climate resilience, and greenwashing. It illuminates the interplay between market fluctuations, green deception, and sustainable climate investment needs.https://doi.org/10.1186/s43093-025-00497-8FluctuationsLong-term memorySectoral investmentsClimate-proofing enterprisesInstitutional disparitiesClimate risk management |
| spellingShingle | Mahdi Ghaemi Asl A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes Future Business Journal Fluctuations Long-term memory Sectoral investments Climate-proofing enterprises Institutional disparities Climate risk management |
| title | A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes |
| title_full | A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes |
| title_fullStr | A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes |
| title_full_unstemmed | A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes |
| title_short | A novel AI-driven approach to greenwashing: breakthroughs in the future fit between domain-specific Islamic enterprises with varying developmental progress and ESG landscapes |
| title_sort | novel ai driven approach to greenwashing breakthroughs in the future fit between domain specific islamic enterprises with varying developmental progress and esg landscapes |
| topic | Fluctuations Long-term memory Sectoral investments Climate-proofing enterprises Institutional disparities Climate risk management |
| url | https://doi.org/10.1186/s43093-025-00497-8 |
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