To achieve the energy transition and carbon neutrality targets, governments have implemented multiple policies to incentivize electricity suppliers to invest in renewable energy. Considering different government policies, we construct a renewable energy supply chain consisting of electricity suppliers and electricity retailers. We then explore the impact of four policies on electricity suppliers’ renewable energy investments, environmental impacts, and social welfare. We validated the results based on data from Wuxi, Jiangsu Province, China. The results show that government subsidy policies are more effective in promoting electricity suppliers to invest in renewable energy as consumer preferences increase, while no-government policies are the least effective. We also show that electricity suppliers are most profitable under the government subsidy policy and least profitable under the carbon cap-and-trade policy. Besides, our results indicate that social welfare is the worst under the carbon cap-and-trade policy. With the increase in carbon intensity and renewable energy quota, social welfare is the highest under the subsidy policy. However, the social welfare under the renewable energy portfolio standard is optimal when the renewable energy quota is low.

This study investigates the impact of digital payment infrastructure accessibility on the social influence of microenterprises in Barranquilla, Colombia, while examining the mediating roles of financial inclusion, digital literacy, social support networks, and collaboration with social innovation initiatives. Employing a mixed-methods approach, the study analyzes data from a sample of 25 microenterprises operating in various sectors. The findings, based on statistical techniques such as multiple regression, path analysis, and structural equation modeling (SEM), provide strong evidence for the positive influence of digital payment infrastructure accessibility on the social relationship of microenterprises. The results also highlight the crucial roles played by financial inclusion and social support networks in mediating this relationship. The study contributes to the growing body of literature on the factors driving the social effect of microenterprises and offers valuable insights for policymakers and practitioners aiming to foster inclusive economic development in the region. The findings suggest that investing in the development and expansion of digital payment systems, alongside efforts to promote financial inclusion and strengthen social support networks, can have far-reaching benefits for microenterprises and their communities.

In the rapidly evolving landscape of digital marketing, the influence of social media on consumer behavior has become a focal point of scholarly inquiry. This study delves into the intricate dynamics between social media interaction and the quality of relationships in the context of s-commerce, examining how these interactions impact customer loyalty and purchase intentions. It is imperative to note that while the study does explore the mediating role, it is not the primary focus. The core objective revolves around understanding the nuanced relationships between social media interaction and relationship quality. This clarification ensures a precise delineation of the research scope and objectives. Furthermore, it is worth emphasizing that while the study delves into customer loyalty, this aspect is not explicitly reflected in the title. However, the examination of loyalty remains an integral component of the research, providing a holistic view of customer behavior in the digital marketplace. By addressing the interplay between social media engagement and relationship quality, this study aims to provide valuable insights for businesses navigating the complexities of s-commerce. Through this research, we seek to illuminate the pivotal role of social media interactions in shaping customer-company relationships, thus offering actionable insights for practitioners and enriching the academic discourse in the field of digital marketing.

This article is devoted to studying the principles of the relationship between democracy and demoethics as tools for transforming the sustainable development of society. The study is based on the assumption that the effective functioning of democracy is associated with such social phenomena as elections and electoral behavior. The study examined electoral behavior and surveyed members of society about the qualities of candidates to which they pay special attention. An analysis of qualitative and quantitative data demonstrating the democratic foundations of elections of members of society was conducted, and an analysis of the choice of voters in the extraordinary elections of the President of the Republic of Kazakhstan by region was conducted. In this study, Bayesian network modeling is experimentally applied to formalize the problem of identifying and analyzing the behavior of virtuous personality traits. A sociological survey of public opinion was conducted using the questionnaire method with the participation of 826 people from all regions of Kazakhstan from May to June 2023. A questionnaire was used to collect data, the main purpose of which was to compare attitudes and find out what values are considered important for people, what norms of behavior are considered acceptable, and to understand what values and norms prevail in society. It is concluded that the concept of demoethics promotes a positive transformation of humanity and helps to form a new leader of virtue, a ruler of the city, capable of making ethical rational decisions that can ensure a balance between the economic, social, and environmental needs of humanity.

The Circular Economy (CE) concept has been recognized as the core strategy that can support sustainable business through technological innovation that enables CE transition by focusing on resource savings. This case study conducts research on business strategy in achieving CE transition in an agroindustry company, by performing SWOT analysis to assess internal and external factors. The SWOT model provides valuable results that an effective strategy could maximize strengths and opportunities, minimize weaknesses and threats in business by boosting circularity on business-critical factors. The CE adoption by agroindustry company mostly focuses on efficient organic waste management, energy-efficient production, and production process. This study case reveals that while technology plays a significant role in advancing CE, there is still a significant need to pay attention to the social aspect in supporting the creation of worker-owned cooperatives by creating space for employee involvement in finding innovations and adopting technology in business transition into CE process. Social innovation through the involvement of employees by sharing CE vision, synergizing and optimizing internal potential, and building up the green innovation culture has created an internal conducive climate to put CE principle into practice. Further result shows that a labor-intensive company’s business strategy prioritizes employment and job security over maximizing profits, which directly leads to the economic welfare and social protection of the business operation that makes an inclusive business.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.