Sustainability of Management Decisions in a Digital Logistics Network

Unleashing the mechanism between small and medium enterprises, and green financing in China: a pathway toward environmental sustainability and green economic recovery

In this research, we analyzed green finance, small and medium-sized businesses, and financial literacy in China to boost the green economy. Green finance and financial literacy were examined holistically using a rigorous empirical approach and data envelopment analysis to provide the way to advance green economic recovery in this research. According to empirical evidence, green financing impacts SMEs at 0.31, 0.41, and 2.02 on green economic recovery. China's green finance and small businesses contribute significantly to the country's overall green economic revival. A more accurate forecast of green economic recovery was made possible by including other variables such as population expansion, development, and small business development. The analysis used the data envelopment analysis, and the results were solid. Additional hypothetical time-dependent instances demonstrated China's predicted green financing and small business's nexus for 2000 to 2020. The proportion of SMEs is decreasing, and as a result, green financing and financial literacy have increased by an average of 12.5% during this time. China's green financing would fall dramatically if the country's industrial structure is reduced. According to our findings, financial literacy is positively correlated with green economic recovery, while illiteracy is negatively correlated with growth. Finally, the report provides some ideas for China's future green economic recovery.

Renewable energy, industrial upgradation, and import-export quality: green finance and CO2 emission reduction nexus

There has been a steady decline in carbon dioxide emissions in the world's 19 most industrialized nations even as GDP has increased. These nations' efforts to reduce emissions of carbon dioxide, therefore, to reduction of CO₂ and development of renewable energy are the objective of this research. With the years 1995-2019 as a point of reference, we have selected gross domestic product, GDP, RE, industrial upgrading, and import and export as our independent variables. A panel nonlinear autoregressive distributed lag (NARDL) method is utilized to investigate the links between carbon dioxide emission and these independent variables. For the purpose of determining the direction of causation, the panel heterogeneous causality test is used. RE and standards of export and import were shown to be contributing variables in the decrease of carbon dioxide emissions. The environmental Kuznets curve hypothesis was validated by the estimated findings. Increased carbon dioxide emissions are countered by the positive impulses of technological progress, such as R&D development spending and standards of import and export index. Industrial upgrading and emissions of carbon dioxide, gross domestic product and RE, and industrial upgrading and emissions of carbon dioxide, all have a bidirectional causal link. In particular, a one-way causality between gross domestic product and emissions of carbon dioxide, standards of imports and exports, and industrial upgrading, and industrial upgrading and standards of imports and exports is demonstrated. Following the results, policy suggestions are put out.

Sustainability of the regional financial system: a case study of the Northwestern Federal District

Background: This article provides an assessment of the sustainability of Russian regions’ financial systems. The study is based on the methods of generalization and synthesis, correlation-regression analysis, and multivariate classification. Since the structure of the regional financial system is complex, several works are devoted to studying its sustainability issues. The relevance of the study topic is confirmed by the lack of a systematic approach to assessing the integral index of sustainability and the possibility of using various tools in determining the complex indicator. Methods: This  methodology with application of mathematical statistics methods makes it possible to assess the financial system sustainability in four sectors, to include the leading indicators in the assessment, and to identify regions with extreme values of debt burden indicators. The method was tested for the regions of the Northwestern Federal District (NWFD) for the period 2010 - 2019  to classify the regions according to three levels of debt sustainability. Data collection from the 1st January to 30th April 2022 included statistical data from government open internet sources, sectors studied relate to government, and municipal budgets in the NWFD. Authors analyzed regional debt sustainability indicators and identified themes in the field of sustainability studies for the NWFD. Results: An increased level of financial system sustainability was observed among the  NWFD regions in the corporative and personal finance sectors, indicating a significant contribution of businesses and households to maintaining the balance and sustainability of the financial system in Russia as a whole. The results of the study also identified that the NWFD regions belong to three clusters: cluster 1 - high debt sustainability; cluster 2 - medium debt sustainability; and cluster 3 - low debt sustainability. Conclusions: The study results allowed the identification of regions with a constantly high level of debt, financial, and corporative sustainability.

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

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.

Sustainability of the regional financial system: a case study of the Northwestern Federal District

Background: This article provides an assessment of the sustainability of Russian regions' financial systems. The study is based on the methods of generalization and synthesis, correlation-regression analysis, and multivariate classification. Since the structure of the regional financial system is complex, several works are devoted to studying its sustainability issues. The relevance of the study topic is confirmed by the lack of a systematic approach to assessing the integral index of sustainability and the possibility of using various tools in determining the complex indicator. Methods: This  methodology with application of mathematical statistics methods makes it possible to assess the financial system sustainability in four sectors, to include the leading indicators in the assessment, and to identify regions with extreme values of debt burden indicators. The method was tested for the regions of the Northwestern Federal District (NWFD) for the period 2010 - 2019  to classify the regions according to three levels of debt sustainability. Data collection from the 1 ^st January to 30 ^th April 2022 included statistical data from government open internet sources, sectors studied relate to government, and municipal budgets in the NWFD. Authors analyzed regional debt sustainability indicators and identified themes in the field of sustainability studies for the NWFD. Results: An increased level of financial system sustainability was observed among the  NWFD regions in the corporative and personal finance sectors, indicating a significant contribution of businesses and households to maintaining the balance and sustainability of the financial system in Russia as a whole. The results of the study also identified that the NWFD regions belong to three clusters: cluster 1 - high debt sustainability; cluster 2 - medium debt sustainability; and cluster 3 - low debt sustainability. Conclusions: The study results allowed the identification of regions with a constantly high level of debt, financial, and corporative sustainability.

Sustainable development of smart cities and smart territories based on the model of minimizing externalities

The development of conceptual models of a digital city poses numerous challenges for developers. The public sector concept model has become one of the most difficult models to use. When developing algorithms to find a solution, the multidirectional interests of businesses and public institutions are combined. This type of model reflects the most acute and urgent problems faced by megapolises with regard to combining numerous localized services provided to the community in a limited territory. The administrations of both cities and regions (the scale of the smart territories) must make decisions concerning overcoming the barriers existing between the profits of commercial structures, the negative externalities generated by their activities, and the social benefits to the population in the territory under their control. It is necessary to solve this problem to achieve the effective management of enterprises belonging to the segment of long-term participants in various business activities, interacting with the surrounding social and business environment in a complex. This study takes into account the complex structures of the economic processes characteristic of megacities. The periodicity of economic processes is also taken into account. When choosing an optimization criterion, functions reflecting the level of internalization of responsibility for external effects were considered. The authors propose a mathematical model that can be used as part of the management decision support systems software, aiming at taking into account the externalities of a wide range of national, institutional, business, and social activities.

Financial logistics models based on systematic approach improving management solutions

Background: Some firms with good growth opportunities and additional funds could have difficulties accessing external finance. One possible way to enhance their financial inclusion could be an exciting approach to planning the money reserve collected on a firm’s account.

Methods: This article aims to disclose the introduction of financial logistics as the new theoretical field of management science. The authors present, in this paper, the key findings on the development of logistical models of an optimum money reserve calculation taking into account digital transformation and industry 4.0 technologies and optimization methods.

Results: The monetary reserve models are analogies of models of storekeeping in supply chains. The specific area of the theoretical research of logistics is shown in this paper, which could be disclosed as the subject of financial logistics as a science. The authors consider the term “Financial Logistics” based on logistics theory and money demand.

Conclusions: Authors suggest the methodology of studying the nature of both financial and material flows of resources by comparing the relevant formulas. From the researchers’ points of view, financial logistics could be defined as the theory of managing the cash flows based on the logistical models for calculating a corporation’s cash reserve. The authors find it interesting to expand the conditions for calculating financial flows since the uncertainty of external market conditions always influences actual commercial activity.

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

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.

Development of an Algorithm for Regulating the Load Schedule of Educational Institutions Based on the Forecast of Electric Consumption within the Framework of Application of the Demand Response

There is a tendency to increase the use of demand response technology in the Russian Federation along with other developing countries, covering not only large industries, but also individual households and organizations. Reducing peak loads of electricity consumption and increasing energy efficient use of equipment in the power system is achieved by applying demand management technology based on modeling and predicting consumer behavior in an educational institution. The study proposes to consider the possibility of participating in the concept of demand management of educational institutions with a typical workload schedule of the work week. For the study, statistical data of open services and sources, Russian and foreign research on the use of digital and information technologies, analytical methods, methods of mathematical modeling, methods of analysis, and generalization of data and statistical methods of data processing are used. An algorithm for collecting and processing power consumption data and a load planning algorithm were developed, including all levels of interaction between devices. A comparison was made between the values of the maximum daily consumption before and after optimization, as well as the magnitude of the decrease in the maximum consumption after applying the genetic algorithm. The developed algorithm has the ability to scale, which will increase the effect of using the results of this study to more significant values. Load switching helps to reduce peak consumption charges, which often represent a significant portion of the electricity cost.