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Improving environmental decision-making in environmental business-management using big data and AI
Environmental business management is a special direction in the management of entrepreneurship within the framework of environmental legislation and corporate environmental responsibility. Despite the high importance for society (determines the contribution of business to the implementation of the SDGs) and business (forms loyalty to it), there are some difficulties in the area of environmental business management for two reasons, both of which (according to the hypothesis put forward in this article) can be overcome through the use of Big Data and AI (Lubis et al., 2019; Colvin et al., 2020).
The first reason is due to the fact that enterprises face a shortage of information about current ecological problems, ongoing initiatives to protect the environment and available opportunities to join them. Big Data make it possible to automatically collect, systematize and provide enterprises with all the necessary information (Popkova et al., 2020; Lamolinara et al., 2022; Mikac et al., 2022).
The second reason is that information about the state and protection of the environment has a large volume and is subject to constant changes. Processing and analysis of this information is not available for most enterprises, especially small and medium-sized ones. Artificial intelligence allows to quickly and accurately process a large amount of information and provide intelligent support for environmental decision-making in environmental business management (Parvathi Sangeetha et al., 2022; Popkova et al., 2022; Tian, 2022).
The purpose of the article is to substantiate the prospects and develop recommendations for improving environmental decision-making in environmental business-management using Big Data and AI. The originality of the article lies in providing clear justifications for the key role of technologies in the optimization of environmental decision-making in environmental business management in the AI era.