This study aims at analyzing the consumers’ perception towards online purchasing bakery goods on subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM). Convenience sampling was used and the final sample of respondents was made of 344 participants, with an effective recovery rate of 96%, who bought bakery goods on the LINE social platform in Nantou County. Descriptive statistics, confirmatory factor analysis, and SEM structural equation model were used to test the research hypothesis. The results show that after adding external variables to the technology acceptance model (TAM), the application of purchasing bakery goods online is significant; the consumers’ behavior of purchasing bakery goods online, subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM) have cause-and-effect relationships. This research concludes that it is easy, helpful, and worthy to use the Internet to buy bakery goods.

As the second most polluting industry in the world, the fashion industry has a critical impact on the environment. The development of sustainable fashion is conducive to reducing the environmental pollution caused by the fashion industry. China has the largest consumer market in the world, and the Chinese government and major companies have made considerable contributions to the sustainable development of the fashion industry. However, research regarding young women’s attitudes towards this topic remains under-explored. This study interviewed 30 young women of different ages from different places in China. Based on the theory of planned behavior (TPB), a semi-structured interview was used as a data collection method, and thematic analysis was adopted for data analysis. This paper discusses young Chinese female consumers’ attitudes towards sustainable fashion and analyzes the motivating factors and hindrance factors affecting the consumption intentions of young Chinese female consumers towards sustainable fashion. The research found that young Chinese female consumers generally hold a positive and supportive attitude towards sustainable fashion. Consumers’ perceptions of sustainable fashion, their self-perceptions, and their level of green awareness all significantly impact their attitudes and purchase intentions toward sustainable fashion. Consumers feel low social pressure, and Chinese society demonstrates a high level of acceptance and praise for sustainable concepts. However, the lack of purchasing channels and choices for sustainable fashion in China and the high cost of sustainable fashion products discourage consumers from making purchases. This study will be beneficial as a reference when the Chinese government makes sustainable policies to guide consumers toward sustainable fashion consumption. This study helps enterprises select target markets in China and formulate sustainable fashion marketing strategies and targeted advertising. This study contributes to increasing consumer awareness of sustainable fashion, as well as providing reference and reflective value when consumers purchase sustainable fashion products. Finally, this study will help promote the development process of sustainable fashion in Chinese society, make contributions to reducing the waste of social resources, promoting the recycling of resources, and improving social conditions, and put forward specific solutions and feasible suggestions for the development of sustainable fashion in Chinese society.

The effective allocation of resources within police patrol departments is crucial for maintaining public safety and operational efficiency. Traditional methods often fail to account for uncertainties and variabilities in police operations, such as fluctuating crime rates and dynamic response requirements. This study introduces a fuzzy multi-state network (FMSN) model to evaluate the reliability of resource allocation in police patrol departments. The model captures the complexities and uncertainties of patrol operations using fuzzy logic, providing a nuanced assessment of system reliability. Virtual data were generated to simulate various patrol scenarios. The model’s performance was analyzed under different configurations and parameter settings. Results show that resource sharing and redundancy significantly enhance system reliability. Sensitivity analysis highlights critical factors affecting reliability, offering valuable insights for optimizing resource management strategies in police organizations. This research provides a robust framework for improving the effectiveness and efficiency of police patrol operations under conditions of uncertainty.

The introduction of artificial intelligence (AI) marks the beginning of a revolutionary period for the global economic environments, particularly in the developing economies of Africa. This concept paper explores the various ways in which AI can stimulate economic growth and innovation in developing markets, despite the challenges they face. By examining examples like VetAfrica, we investigate how AI-powered applications are transforming conventional business models and improving access to financial resources. This highlights the potential of AI in overcoming obstacles such as inefficient procedures and restricted availability of capital. Although AI shows potential, its implementation in these areas faces obstacles such as insufficient digital infrastructure, limited data availability, and a lack of necessary skills. There is a strong focus on the need for a balanced integration of AI, which involves aligning technological progress with ethical considerations and economic inclusivity. This paper focuses on clarifying the capabilities of AI in addressing economic disparities, improving productivity, and promoting sustainable development. It also aims to address the challenges associated with digital infrastructure, regulatory frameworks, and workforce transformation. The methodology involves a comprehensive review of relevant theories, literature, and policy documents, complemented by comparative analysis across South Africa, Nigeria, and Mauritius to illustrate transformative strategies in AI adoption. We propose strategic recommendations to effectively and ethically utilize the potential of AI, by advocating for substantial investments in digital infrastructure, education, and legal frameworks. This will enable Africa to fully benefit from the transformative impact of AI on its economic landscape. This discourse seeks to offer valuable insights for policymakers, entrepreneurs, and investors, emphasizing innovative AI applications for business growth and financing, thereby promoting economic empowerment in developing economies.

According to official data, modern Russia has the lowest unemployment rate. However, there is still a huge contingent of hidden unemployment, many times higher than the official level. This situation is paradoxically combined with an acute and continuously growing shortage of qualified production personnel. Using a lot of factual material, the author reveals the causes of this phenomenon. The main one is the depopulation of the indigenous population, which is being replaced by people of other ethnic groups with the lowest qualification level. At the same time, due to the destruction (“optimization”) of the education system, the intellectual and qualification level of the indigenous population is continuously decreasing. The other is the various types and waves of growing emigration of “brains” and “golden hands.” As a result, for more than thirty years, the contingent of old engineering and technical personnel has exhausted itself, while new ones have not been trained in the required volume and quality. A huge personnel “hole” has formed. The author proposes to close this “hole” on the basis of a radical reorientation of the entire Russian education system, starting with kindergarten, school, etc. It is also necessary to reformat the public consciousness accordingly, especially the mass consciousness of young people.

The Middle East and North Africa (MENA) region faces unique challenges and opportunities in integrating sustainability into sovereign credit assessments. This research study examines environmental, social, and governance (ESG) factors embedded in the lending policies of jurisdictional institutions in MENA. By analyzing existing literature and case studies, we identify key drivers and barriers to ESG integration in sovereign lending. Our findings suggest a growing recognition of sustainability’s importance in financial stability and credit, driven by global climate guarantees and local socio-economic development. However, challenges such as data availability, regulatory frameworks, and market acceptance persist. This paper provides an overview of current practices, highlights best practices, and offers recommendations to enhance ESG integration in sovereign debt reviews in the MENA region. The study concludes that a robust ESG framework is necessary to accurately reflect the long-term risks and opportunities associated with sovereign debt, ultimately contributing to sustainable economic growth regionally.