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OPINION article

Front. Environ. Sci., 12 July 2022
Sec. Environmental Economics and Management
This article is part of the Research Topic Evolution of Environmental Economics & Management in the Age of Artificial Intelligence for Sustainable Development View all 18 articles

Environmental competitiveness of the economy: Opportunities for its improvement with the help of AI

Anna V. KukushkinaAnna V. Kukushkina1Araz O. MursalievAraz O. Mursaliev1Yuriy A. Krupnov
Yuriy A. Krupnov2*Alexander N. AlekseevAlexander N. Alekseev3
  • 1Moscow State Institute of International Relations (University) of the Ministry of Foreign Affairs Russian Federation, Moscow, Russia
  • 2Financial University under the Government of the Russian Federation, Moscow, Russia
  • 3Plekhanov Russian University of Economics, Moscow, Russia

Introduction

The ecological competitiveness of the economy is a new concept that emerged in the era of the Sustainable Development Goals under the influence of the United Nations (UN) global initiative. The ecological competitiveness of the economy is understood, on the one hand, as a set of conditions created to protect the environment (for example, the predominance of responsible production and consumption practices, the predominance of sustainable communities and territories), and on the other hand, the environmental results achieved (for example, the state of the climate, the level of biodiversity, the purity of water and air), as well as the correlation of these results with other economic systems (AlAbri et al., 2022; Del-Aguila-Arcentales et al., 2022; Martínez and Poveda, 2022).

Every year the environmental competitiveness of the economy increasingly determines the attractiveness of economic systems for:

– Living (which is especially important for aging societies, as it forms their potential to overcome demographic crises) (Wu, 2022);

– Work (attracting and retaining highly qualified personnel, including among migrant workers) (Sabbir and Taufique, 2022);

– Investment (“green” finance is gaining popularity around the world) (Awawdeh et al., 2022);

– International foreign economic cooperation (an example is the introduction of a carbon tax for exporters in the European Union) (Owusu Kwateng et al., 2022).

The problem lies in the uncertainty of the prospects for improving the environmental competitiveness of the economy in the era of artificial intelligence (AI). In this article, a scientific search for a solution to the problem is carried out. The hypothesis of this research is that artificial intelligence improves the environmental competitiveness of the economy. The advanced hypothesis is based on evidence that artificial intelligence (AI) enables automated (“smart”) environmental monitoring, promptly identifying and eradicating violations of environmental legislation, presented in works by Asha et al. (2022), Bakirman (2022), Sasaki et al. (2019).

With the accumulation of experience in “smart” monitoring, it is becoming a preventive measure. Fraga-Lamas et al. (2021), Wilson et al. (2022) also point out in their papers that artificial intelligence (AI) can be used for “smart” organization and management of circular production works, automated and highly-accurate sorting of production and consumption waste. As a result, environmental pollution is reduced.

Philip and Kavitha (2022), Yankovskaya et al. (2022) point out in their works that artificial intelligence (AI) allows developing “green” corporate management, providing intelligent support for managerial decision making. For example, through the selection of directions for business development associated with the lowest ecological costs.

As is noted in the work by Guchhait et al. (2021), artificial intelligence (AI) also supports the development of green finance by automatically sorting and selecting the most ecologically responsible investment opportunities. Further, “smart” environmental tax optimization is possible through an automated search for ways to reduce the environmental tax burden of business, which is particularly topical in the context of the introduction of carbon tax.

The article is aimed at determining the prospects and advantages of improving the environmental competitiveness of the economy with the use of artificial intelligence. The article also contains applied economic policy implications.

The potential of artificial intelligence in improving the environmental competitiveness of the economy

Environmental competitiveness is a special component of the competitiveness of the economic and social system, associated with peculiarities of the management of natural resources (Del-Aguila-Arcentales et al., 2022). It shall be understood to mean the ability of the economic system to use natural resources in the most efficient (sustainable, prudent and environmentally friendly) way, avoiding their depletion with a view to creating the most favourable ecosystem for human life, as well as preserving the heritage for future generations (AlAbri et al., 2022; Wang M. et al., 2022).

The Global Sustainable Competitiveness Index: SolAbility (2022) occupies a central place among the indicators of environmental competitiveness of the economy. Therefore, the research in this article is based on this indicator. It provides full and detailed information of the essence of the ecological competitiveness of the economy, highlighting the following components in its structure and calculating separately:

– Natural capital: Favorable natural environment in the economic system (Congjuan et al., 2022);

– Resource Intensity: Resource efficiency of the economy (Wang N. et al., 2022);

– Social capital: Social cohesion in environmental issues (Popkova et al., 2021);

– Intellectual capital: The level of environmental education and the availability of “green” innovations (Popkova et al., 2018);

– Governance: The level of development of “green” infrastructure and the state regulators’ commitment to environmental priorities (Mahmoodi and Dahmardeh, 2022).

In the works of Adamova et al. (2021), Asha et al. (2022), Li et al. (2021), Ligozat et al. (2022), Sasaki et al. (2019), it is noted that artificial intelligence (AI) has the greatest potential in increasing the environmental competitiveness of the economy in terms of resource efficiency of the economy (through monitoring of resource consumption and automation of resource conservation), intellectual capital (through the generation of “green” innovations) and government regulation (through increasing transparency, accountability and manageability of environmental economics and management).

Dong and Meng (2021), Rana et al. (2021) point out in their works that artificial intelligence (AI) significantly contributes to improving the overall competitiveness of the economy and, in particular, to improving digital competitiveness. Nevertheless, the contribution to the ecological competitiveness of the economy has not been studied much, so it remains unclear what research gap is being filled in this article.

AI’s contribution to ensuring the ecological competitiveness of the economy: An overview of international best practices

This article uses the Global Sustainable Competitiveness Index (SolAbility, 2022), based on five equisignificant indicators of environmental competitiveness, as an empirical research base:

Natural Capital: A specified natural habitat, including the availability of resources and the degree of their depletion;

Social Capital: Health, security, freedom, equality, and life satisfaction that contribute to social advance;

Resource Efficiency: Efficiency of utilization of limited attainable resources;

Intellectual Capital: The ability to create wealth and jobs through innovations and value creation by economic sectors in open (free, global) markets.

Governance Performance: The framework for sustainable development and social well-being, achieved through the equitable distribution of resources, infrastructure, regulation of markets and employment.

To test the hypothesis put forward in the article, the influence of use of big data and analytics [as an artificial intelligence (AI) indicator] is determined according to the assessment of IMD Business School (2022) on the indicators of environmental competitiveness according to the assessment of SolAbility (2022). The study is conducted using the regression analysis method in 2021 on the example of the top 15 countries with the highest environmental competitiveness of the economy (leaders of the SolAbility rating of the same name, 2022). Empirical data and analysis results are presented in Table 1.

TABLE 1
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TABLE 1. The level of artificial intelligence (AI) development and environmental competitiveness of the top 15 economies in the SolAbility rating (2022) in 2021.

The results obtained in Table 1 showed that, firstly, there is a reliable pattern of growth of natural capital and social capital as artificial intelligence (AI) spreads. Thus, the improvement of the position of the sample countries in the IMD rating (2022) according to the use of big data and analytics indicator contributes to the increase of natural capital by 0.20 points (correlation 54.04%, the pattern is reliable at the significance level of 0.05) and the growth of social capital by 0.12 points (correlation 72.75%, the pattern is reliable at the significance level of 0.01). Based on the established regression patterns, it was revealed that at the maximum level of artificial intelligence (AI) development (1st place), an increase in natural capital by 11.75% and social capital by 6.48% is achieved.

Secondly, the spread of artificial intelligence (AI) does not contribute to improving the sustainability of governance, as evidenced by unreliable regression and weak correlation. Thirdly, despite the absence of a sufficiently reliable regression dependence, the close relationship of the remaining indicators with artificial intelligence (AI) is evidenced by a pronounced correlation: with resource intensity (24.12%) and with intellectual capital (41.73%). Consequently, these indicators of the environmental competitiveness of the economy can be improved through the use of AI, but these advantages are not guaranteed (they do not occur in all countries and not in all cases).

The obtained results validate the advanced hypothesis and prove that artificial intelligence opens up new opportunities for improving the environmental competitiveness of the economy. Artificial intelligence allows slowing down/preventing the depletion of natural resources (to preserve natural capital), and supporting social advance through health, security, freedom, equality, and life satisfaction (development of social capital).

Prospects for improving the environmental competitiveness of the economy using AI: Economic policy implications

In this article, it is suggested to focus on those components of this competitiveness that are most closely related to the development of artificial intelligence (AI) in order to maximize the actual contribution of artificial intelligence (AI) in practice, aimed at improving the environmental competitiveness of the economy. The following main (priority) measures are proposed:

– To develop natural capital, it is recommended to use the so-called “AI imagination” to discover new ways of regenerative nature-based management. In this regard, it is necessary to inform artificial intelligence (using a digital code) of the advantages of various practices of ecological economics and management, teach and program it to search for the most optimal combination of business practices that can improve the environmental situation;

– To strengthen social capital, it is proposed to create an even greater number of more “smart” chatbots (both private and public) in order to increase the awareness of communities about current environmental problems and the opportunities available to them to solve these problems through responsible production and consumption practices.

The following additional measures are proposed:

– To increase resource intensity and increase intellectual capital, it is advisable to expand the use of artificial intelligence (AI) in R&D conducted by both research institutes (for the economy as a whole) and individual business structures (for their own needs). This will make it possible to create both universal and unique applied solutions to improve the resource efficiency of environmental economics and management.

The proposed recommendations will allow integrating artificial intelligence (AI) into environmental economics and management practices and thereby increase their scale and their efficiency.

Discussion

The article contributes to the development of the Theory of environmental economics and management by clarifying the role and importance of artificial intelligence (AI) in ensuring the ecological competitiveness of the economy. The increment of scientific knowledge in the article is provided due to the justification that, unlike the assumptions made in the works of Adamova et al. (2021), Asha et al. (2022), Li et al. (2021), Ligozat et al. (2022), Sasaki et al. (2019), the potential artificial intelligence (AI) in improving the environmental competitiveness of the economy is most pronounced in the field of natural and social capital development, and not in relation to the resource efficiency of the economy, intellectual capital and government regulation, as previously assumed in these publications.

As a result of the study, it was possible to prove that artificial intelligence (AI) makes a reliable and stable contribution to the development of natural capital (improving environmental conditions in the economic system and supporting the implementation of SDGs 13-15) and social capital (increasing social cohesion in environmental protection and supporting SDG 11). At the same time, it is observed less pronounced and insufficiently reliable for the global economy as a whole, but perhaps reliable enough in individual countries, AI’ contribution to increasing resource Intensity (improving the resource efficiency of the economy and supporting the implementation of SDG 12) and the development of intellectual capital (increasing the level of environmental education and the availability of “green” innovations and supporting the achievement of SDG 4). Nevertheless, on a global economic scale, no significant AI’ contribution to governance has been identified (increasing the level of development of “green” infrastructure and the commitment of state regulatory authorities to environmental priorities, that is, in support of achieving SDG 9).

Conclusion

So, the hypothesis put forward in the article has been proved: artificial intelligence determines success in slowing down/preventing the depletion of natural resources by 54.04%, and determines social advance by 72.75%. It opens up broad prospects for improving the environmental competitiveness of the economy in the artificial intelligence (AI) era. The theoretical significance of the results obtained in this study lies in the reasoned position that, despite the overall positive contribution to improving the environmental competitiveness of the economy, artificial intelligence (AI) has a significantly different potential in the development of individual components of this competitiveness. This makes it possible to use artificial intelligence (AI) more flexibly and effectively in improving environmental economics and management. The article has also revealed AI’ contribution to improving the environmental competitiveness of the economy in the context of the components of this competitiveness, as well as in the light of the implementation of the Sustainable Development Goals (SDGs).

The empirical value of the article consists in revealing the prospects for improving the environmental competitiveness of the economy in the artificial intelligence (AI) era. In particular, it has been proved that natural capital can be increased by 11.75%, and social capital—by 6.48%. The outlined prospects and the proposed economic policy implications for improving the environmental competitiveness of the economy with the use of artificial intelligence (AI) make it possible to improve the practice of state and corporate management of the environmental economics, focusing the use of artificial intelligence (AI) in the most promising areas.

In conclusion, it is necessary to pay attention to the limitations of the results obtained in the article due to the fact that no significant AI’ contribution to the development of resource intensity, intellectual capital and governance has been identified. The fact that positive and sufficiently reliable connections have not been revealed in this study does not necessary mean that they are actually absent. In future studies, the sample should be expanded to include, in particular, developing countries. In addition, it is advisable to conduct case studies that will help to identify hidden connections between artificial intelligence (AI) and the environmental competitiveness of the economy.

Author contributions

All authors contributed to manuscript writing revision, read, and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: environmental competitiveness of the economy, artificial intelligence (AI), environmental economics and management, sustainable development goals (SDGs), environmental protection

Citation: Kukushkina AV, Mursaliev AO, Krupnov YA and Alekseev AN (2022) Environmental competitiveness of the economy: Opportunities for its improvement with the help of AI. Front. Environ. Sci. 10:953111. doi: 10.3389/fenvs.2022.953111

Received: 25 May 2022; Accepted: 27 June 2022;
Published: 12 July 2022.

Edited by:

Bruno Sergi, Harvard University, United States

Reviewed by:

Elchin Suleymanov, Baku Enginering University, Azerbaijan

Copyright © 2022 Kukushkina, Mursaliev, Krupnov and Alekseev. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yuriy A. Krupnov, yukrupnov@mail.ru

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.