Analysis of environmental priorities for green project investments using an integrated q-rung orthopair fuzzy modeling

Green energy projects contribute to sustainable economic development of countries with the employment of environmentally friendly energy production strategies. However, environmental priorities should be examined for this situation. Therefore, priority analysis should be executed for the environmental issues while implementing green investment projects. Accordingly, this study aims at proposing a unique decision-making model based on orthopair fuzzy sets and the golden cut degrees for the environmental priorities of green project investments. The main novelty of the study stems from its proposed integrated model by equipping the Multi-SWARA, and TOPSIS based on the q-ROFSs technique with the golden cut. A set of criteria is identified for measuring the green projects’ environmental priorities while several project alternatives are also determined with the supporting literature. Appropriately, the extensions of Multi-SWARA and TOPSIS methods have been applied for weighting and ranking the factors, respectively, in the integrated approach. Additionally, a comparative evaluation is performed with the help of VIKOR method to rank the alternatives. Besides, the sensitivity analysis is applied to illustrate the coherency of the weighting results in the decision-making approach. Accordingly, 5 cases are considered to measure the effects of changing weight results. It is defined that this model is coherent and could be extended for further studies. It is concluded that the reduction of emissions is the most essential item for the environmental priorities of green project investments. Pollution control, waste management and eco-friendly transportation activities are the most critical alternatives. Therefore, this study recommends that investors of green projects should prioritize the strategies of minimizing carbon emissions problem. In this context, investing in renewable energy technologies will help green project investors solve this problem.WOS:0007974148000012-s2.0-8513083050

Evaluating energy financing considerations and sustainable energy innovation with the role of financial development and energy development

[EN] The purpose of the study is to test the role of energy development in energy financing considerations for sustainable energy innovation and financial development. To achieve the study objective, a fuzzy decision-making modeling technique is applied. The results revealed that bank loans are now the main source of financing for innovation and creativity in Chinese business entities. Project-based financing might be replaced with collaborative and sustainable energy innovation (CSI), warranting energy development. Moreover, green financing loan schemes invest both public and private funds in sustainable energy innovation to capitalize on financial development through sustainable energy innovation. The consideration and application of financial consideration for sustainable energy innovation-financing projects or companies are limitless. Providing for screening energy development cooperation proposals with small financial payback hurdle rates might have large opportunity costs. There may be a case for governments to increase industrial growth, improve resource efficiency, and increase factor productivity while tackling climate change. Economic growth in China may have an even greater influence on environmental sustainability than in other countries. On such points, there is a need to pay the attention. If the suggested policy suggestions are implemented successfully, they would help to enhance the scope of financing considerations for sustainable energy innovation to uplift financial development through energy development mechanisms at the corporate level.The research is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program "Priority 2030" (Agreement. 075-152021-1333 dd 30.09.2021).Barykin, SE.; Sergeev, SM.; Mottaeva, AB.; De La Poza, E.; Baydukova, NV.; Gubenko, AV. (2022). Evaluating energy financing considerations and sustainable energy innovation with the role of financial development and energy development. Environmental Science and Pollution Research. 30:6849-6863. https://doi.org/10.1007/s11356-022-22576-x684968633

Sustainability of Management Decisions in a Digital Logistics Network

[EN] Globalization has given a powerful impetus to the development of international commercial activity and logistics management systems taking full advantage of cross-border networking. The solution lies at the intersection of information technologies, technical means of machine-to-machine (M2M) interaction, mobile high-speed networks, geolocation, cloud services, and a number of international standards. The current trend towards creating digital logistics platforms has set a number of serious challenges for developers. The most important requirement is the condition of sustainability of the obtained solutions with respect to disturbances in the conditions of logistics activities caused not only by market uncertainty but also by a whole set of unfavorable factors accompanying the transportation process. Within the framework of the presented research, the problem of obtaining the conditions for the stability of solutions obtained on the basis of mathematical models is set. At the same time, the processes of transferring not only discrete but also continuous material flows through complex structured networks are taken into account. This study contains the results of the analysis of the stability of solutions of differential systems of various types that simulate the transfer processes in network media. Initial boundary value problems for evolutionary equations and differential-difference systems are relevant in logistics, both for the discrete transportation of a wide range of goods and for the quasi-continuous transportation of, for example, liquid hydrocarbons. The criterion for the work of a logistics operator is the integral functional. For the mathematical description of the transport process of continuous and discrete media, a wide class of integrable functions are used, which adequately describe the transport of media with a complex internal rheological structure.The reported study was funded by RFBR according to the research projet No 20-014-00029.Barykin, SE.; Borisoglebskaya, LN.; Provotorov, VV.; Kapustina, IV.; Sergeev, SM.; De La Poza, E.; Saychenko, L. (2021). Sustainability of Management Decisions in a Digital Logistics Network. Sustainability. 13(16):1-15. https://doi.org/10.3390/su13169289S115131

Digital Echelons and Interfaces within Value Chains: End-to-End Marketing and Logistics Integration

[EN] The goals of real business in the context of the digital transformation of international logistics networks and marketing channels have necessitated the application of a scientifically based theoretical approach to the development of a formalized description acceptable for predictive planning based on leading indicators. In the context of globalization and interstate and regional economic unions, this will lead to achieving the maximum end-to-end integration of digital platforms. Based on the analysis, the article presents the integration of digital logistics and marketing approaches with the mathematical models of the ecosystem organization of economic relations. The features of the organization of economic relations between contractors involved in the execution of virtual transactions and the material movement of resources were analyzed. The researchers considered prerequisites for the analytical description of interconnections between the participants of digital platforms in cross border e-commerce. The authors' approach is based on the idea of both a sales funnel in marketing and a conversion funnel in digital transformation. Considering the integration of logistics and marketing, authors offer the definition of business echelons as stages of the consumer value creation. The theoretical contribution of this article consists in constructing a mathematical description of business echelons along the entire value chain. The developed analytical description of business echelons is acceptable both for embedding a digital management support system into various software products, and for conducting in-depth analysis and finding optimal solutions.The research of S.E.B., S.M.S. and I.V.K. is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program Priority 2030 (Agreement 075-15-2021-1333 dated 30 September 2021).Barykin, SE.; Smirnova, EA.; Chzhao, D.; Kapustina, IV.; Sergeev, SM.; Mikhalchevsky, YY.; Gubenko, AV.... (2021). Digital Echelons and Interfaces within Value Chains: End-to-End Marketing and Logistics Integration. Sustainability. 13(24):1-18. https://doi.org/10.3390/su132413929S118132

Bipolar q-ROF hybrid decision making model with golden cut for analyzing the levelized cost of renewable energy alternatives

Energy costs are the key factors regarding the selection of appropriate renewable energy (RWG) alternatives. All costs of a power plant, such as investment, operation, maintenance, and repair are considered in the scope of levelized costs. Therefore, for the effective determination of the selling price of the energy, levelized cost has a guiding role. Because the levelized costs of RWG alternatives develop the sustainable production and energy consumption for the long term, the leading indicators of these costs should be analyzed significantly. Accordingly, in this study, it is aimed to investigate the levelized cost of RWG alternatives by using bipolar q-rung orthopair fuzzy (q-ROF) hybrid decision-making approach. The novelty of this study is to recommend an integrated decision-making model based on bipolar and q-ROFSs with golden cut. At the first stage, bipolar q-ROF multi stepwise weight assessment ratio analysis (M-SWARA) is employed for weighting the selected criteria of levelized costs of RWG alternatives. At the following stage, bipolar q-ROF technique for order preference by similarity to ideal solution (TOPSIS) is considered to rank the alternatives in terms of the levelized cost performance. On the other side, vise kriterijumska optimizacija i kompromisno resenje (VIKOR) model is also considered to rank the alternatives. In addition to this issue, the sensitivity analysis is also performed with four cases comparatively. Hence, consistency, reliability and coherency of the proposed model can be measured. It is identified that capacity loss has the greatest importance regarding the levelized cost of RWG projects. Solar is found as the best clean energy type with respect to the levelized cost management performance. In this context, it would be appropriate for investors to design projects close to the center. This will contribute to increasing the efficiency and productivity of these projectsKey Project of Philosophy and Social Sciences Research of Hubei Provincial Department of Education ; Ministry of Science and Higher Education of the Russian Federatio

An Empirical Analysis of Russian Regions’ Debt Sustainability

This paper investigates the impact of the moderate growth of government borrowing on debt sustainability in 11 Russian regions over about 10 years, starting in 2010. The current study aims to assess the debt sustainability of the Russian region’s budget by determining Euclidean distance budget constraints and cluster analysis. This study is based on the methodology of hierarchical cluster analysis, which makes it possible to isolate regions of accumulation of objects from the aggregate data and combine them into homogeneous segments. The central hypothesis of this study is that by using this method, it is possible to increase the accuracy of the values that limit budget constraints in a region’s financial system. This study, using open data from the Federal State Statistics Service, is based on a database of statistical, financial, and economic indicators of the Russian economy. The calculations include about 45 macroeconomic indicators, which reflect the ratios of socio-economic development of the region’s financial system. The methodology described in the paper for assessing the debt sustainability of budget policy proves the need to calculate six indicators and determine the debt limits for the regions of each cluster. It finds a need to reduce the high debt burden of 46% of the regions belonging to the Northwestern Federal District. Confidence intervals for the debt limit suggest that the negative growth effect of high debt may start from levels of around 5% of the debt-to-GDP ratio and about 43% of the debt-to-revenue ratio. The results indicate that regions with a high level of debt sustainability include St. Petersburg city, the Leningrad region, and the Kaliningrad region. From a state debt policy perspective, the results provide additional arguments for debt reduction for the Republic of Komi, the Republic of Karelia, the Arkhangelsk region, and the Pskov region. The general conclusion of the study boils down to the need to reduce the debt burden of the budgets of some regions of the SFZO, as well as to the need to change the upper limits of debt, which are equally set for all regions by the Budget Code of the Russian Federation, to differentiated values of public domestic debt, taking into account the results obtained in the study

An Empirical Analysis of Russian Regions’ Debt Sustainability

This paper investigates the impact of the moderate growth of government borrowing on debt sustainability in 11 Russian regions over about 10 years, starting in 2010. The current study aims to assess the debt sustainability of the Russian region’s budget by determining Euclidean distance budget constraints and cluster analysis. This study is based on the methodology of hierarchical cluster analysis, which makes it possible to isolate regions of accumulation of objects from the aggregate data and combine them into homogeneous segments. The central hypothesis of this study is that by using this method, it is possible to increase the accuracy of the values that limit budget constraints in a region’s financial system. This study, using open data from the Federal State Statistics Service, is based on a database of statistical, financial, and economic indicators of the Russian economy. The calculations include about 45 macroeconomic indicators, which reflect the ratios of socio-economic development of the region’s financial system. The methodology described in the paper for assessing the debt sustainability of budget policy proves the need to calculate six indicators and determine the debt limits for the regions of each cluster. It finds a need to reduce the high debt burden of 46% of the regions belonging to the Northwestern Federal District. Confidence intervals for the debt limit suggest that the negative growth effect of high debt may start from levels of around 5% of the debt-to-GDP ratio and about 43% of the debt-to-revenue ratio. The results indicate that regions with a high level of debt sustainability include St. Petersburg city, the Leningrad region, and the Kaliningrad region. From a state debt policy perspective, the results provide additional arguments for debt reduction for the Republic of Komi, the Republic of Karelia, the Arkhangelsk region, and the Pskov region. The general conclusion of the study boils down to the need to reduce the debt burden of the budgets of some regions of the SFZO, as well as to the need to change the upper limits of debt, which are equally set for all regions by the Budget Code of the Russian Federation, to differentiated values of public domestic debt, taking into account the results obtained in the study

Smart city perspectives in post-pandemic governance: Externalities reduction policy

[EN] Background: The ongoing COVID-19 quarantine restrictions have caused multiple sharp decreases in activities associated with the movement of large masses of people. The economies of regions and cities that are critically dependent on tourist flows related to various segments have suffered. This research aims to provide an economic-mathematical model of smart cities externalities¿ impact from the point of view of achieving social and environmental goals Methods: The objective of this study was to develop an algorithm for supporting decision-makers. Methods of mathematical modeling, statistical processing of data received in real-time, as well as methods for finding solutions by expansion into dynamic series are used, and the theory of mathematical games is applied. The theoretical mathematical model presented considers the statistical processing of data provided in real time referring to the performance indicators of megacities. Results: The activities of administrations and governments aimed at maintaining stability over the past two years have been aimed at reducing the negative impact of the pandemic. The prospect of returning to normal conditions is complicated by a number of factors. The proposed approach allows the development of the fundamental basis for making administrative decisions within individual megapolises and in environmental policy on a territory of any scale. The developed mathematical model is abstract by definition and is applied by taking into account specific tasks and criteria. Since the tasks of the administration differ depending on the region and country, the choice of criteria is set individually. Conclusions: During the period of isolation, the volume of services in the Hotel - Restaurant- Catering/Café (HORECA) segment has decreased, and personnel has also been lost. The reduced pressure on public infrastructure and the departure of migrants means that, in the long term, this work cannot be restored within a short period of time.The work was supported by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program 'Priority 2030' (Agreement 075-15-2021-1333 dated 30 September 2021). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptDe La Poza, E.; Kalinina, OV.; Barykin, SE.; Sergeev, SM.; Semenova, GN.; Fatkullina, A.; Mikhaylov, A. (2022). Smart city perspectives in post-pandemic governance: Externalities reduction policy. F1000Research. 11(1032):1-12. https://doi.org/10.12688/f1000research.123195.111211103

Digital Logistics Platforms in the BRICS Countries: Comparative Analysis and Development Prospects

The BRICS Group unites the most rapidly developing large countries, the trade and economic interaction between which can make a significant contribution to both the region’s and world’s development. The purpose of this article is to analyze the development of trade and economic interaction and logistics infrastructure in the BRICS countries, as well as to develop an analytical concept of the BRICS Digital Logistics Platform (DLP) as a tool for the BRICS development. The research methodology includes methods for statistical data analysis, a case study of the DLP development in the BRICS countries, an analysis of the existing definitions and methods for developing DLP, and methods of systemic analysis. The research results present the trade and logistics interaction between the BRICS countries. The level of logistics development in these countries is analyzed based on the World Bank Logistics Performance Index. The article highlights the existing restrictions for the expansion of the economic interaction between countries, one of which is the uneven development of the logistics infrastructure. The article states that the BRICS DLP can be a tool for overcoming the limitation of uneven logistics infrastructure and intensifying trade interaction between the BRICS countries. The experience of creating national DLPs in each of the BRICS countries is analyzed. It is shown that the BRICS countries cannot join one of the existing national DLPs because of the risks for the national sovereignty of the participants. Therefore, an original analytical description for the international BRICS DLP is proposed. It will focus on the simplicity and transparency of the interaction between all of the participants of trade and economic interactions at various levels, as well as on the reduction of economic and logistics risks

Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

This paper proposes a novel and secure blockchain hyperledger sawtooth-enabled consortium analytical model for smart educational accreditation credential evaluation. Indeed, candidate academic credentials are generated, verified, and validated by the universities and transmitted to the Higher Education Department (HED). The objective is to enable the procedure of credential verification and analyze tamper-proof forged records before validation. For this reason, we designed and created an accreditation analytical model to investigate individual collected credentials from universities and examine candidates’ records of credibility using machine learning techniques and maintain all these aspects of analysis and addresses in the distributed storage with a secure hash-encryption (SHA-256) blockchain consortium network, which runs on a peer-to-peer (P2P) structure. In this proposed analytical model, we deployed a blockchain distributed mechanism to investigate the examiner and analyst processes of accreditation credential protection and storage criteria, which are referred to as chaincodes or smart contracts. These chaincodes automate the distributed credential schedule, generation, verification, validation, and monitoring of the overall model nodes’ transactions. The chaincodes include candidate registration with the associated university (candidateReg()), certificate-related accreditation credentials update (CIssuanceTrans()), and every node’s transactions preservation in the immutable storage (ULedgerAV()) for further investigations. This model simulates the educational benchmark dataset. The result shows the merit of our model. Through extensive simulations, the blockchain-enabled analytical model provides robust performance in terms of credential management and accreditation credibility problems