Institutional, Financial and Digital Aspects of the Ethical Entrepreneurship Structure in Ecological Economics

Abstract

The relevance of the research is due to the role of ethical entrepreneurship in a green economy, the increasing need for an ethical justification of the attitude to nature, the transition to the production and consumption of environmentally friendly products in the conditions of the growing global environmental danger of the formation of a technogenic type of economic development. The main characteristics of ethical entrepreneurship and its practical role in a green economy are highlighted. It is shown that the driving forces of the global green economy agenda are governments, investors, society (consumers), central banks. The structure of ethical entrepreneurship is presented as a set of strategic analysis institutions, financial institutions, business models and digital platforms that form management decisions for sustainable development and ESG implementation. It is shown that the financial assessment of the ESG strategy is based on the perception of the environmental component of entrepreneurial ethics as an image element of business culture and a form of environmental responsibility. The authors proposed to consider the digital platform as an information and economic structure that ensures the organization of algorithmic effective interaction of its participants at the expense of its own information infrastructure. It is stated that the ecosystem's supply chain is fragmented, and therefore it is necessary to create a digital platform to unite all participants in responsible investing in the ESG format. The universal possibilities of digital twins with the mutual influence of the subjects of the ethical entrepreneurship system are given. The possibilities of creating a "digital twin" of state policy and business policy for regulating the ecological type of financing ecosystems in the context of strategies for sustainable growth of the national economy, regions and industries based on optional modeling are identified.