In a territorial development model such as that of Valencia (Spain), in which limitations, resistance and difficulties are observed as a result of the dualization that it has undergone in these almost 40 years of operation, we ask whether these obstacles have had an effect on the evolution of employment. This is understood as the basic indicator, the primary aim of any action undertaken for development of the territory. To this end, we set out from the methodological articulation of various techniques (survey by means of a pre-coded questionnaire, application of the READI® methodology) based on the primary information collected from the AEDL (Employment and Local Development Agents) technical staff of Valencia province, which showed us their perception of the dualization to which the model is subjected and the difficulties that this generates when carrying out their professional activity. Statistical and documentary sources were also analyzed. With all this, the evolution of employment in these territories over the last five years was studied in order to validate, or not, the initial hypothesis: Whether this reality of the model (duality) responds to short-term or structural parameters.

One significant importance of street vending in South Africa is its role in providing livelihoods and economic opportunities, especially for marginalized and vulnerable populations. However, Street vendors, particularly those selling agricultural commodities, face numerous challenges. Street vending in Moletjie Mmotong is a vital source of income and employment, offering affordable goods and services, including food, clothing, and household items. One potential solution is online selling, but there is limited knowledge about it in the informal sector. This study aims to analyze the factors affecting street vendors’ willingness to sell fruits and vegetables online in Moletjie Mmotong under Polokwane Municipality. Data was collected from 60 street vendors using a questionnaire and simple random sampling. Descriptive statistics identified and described the socio-economic characteristics of the vendors, while a binary logistic regression model analyzed the factors influencing their willingness to sell online. The study found that age, education level, gender, household size, and access to online selling information significantly influenced their willingness to sell online. The findings highlight the potential benefits of online selling for street vendors, such as increased sales and a broader customer base. The study recommends that governments provide training and workshops on online selling, develop educational programs, distribute educational materials, and create marketing strategies to support street vendors in transitioning to online platforms.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.

Photovoltaic systems have shown significant attention in energy systems due to the recent machine learning approach to addressing photovoltaic technical failures and energy crises. A precise power production analysis is utilized for failure identification and detection. Therefore, detecting faults in photovoltaic systems produces a considerable challenge, as it needs to determine the fault type and location rapidly and economically while ensuring continuous system operation. Thus, applying an effective fault detection system becomes necessary to moderate damages caused by faulty photovoltaic devices and protect the system against possible losses. The contribution of this study is in two folds: firstly, the paper presents several categories of photovoltaic systems faults in literature, including line-to-line, degradation, partial shading effect, open/close circuits and bypass diode faults and explores fault discovery approaches with specific importance on detecting intricate faults earlier unexplored to address this issue; secondly, VOSviewer software is presented to assess and review the utilization of machine learning within the solar photovoltaic system sector. To achieve the aims, 2258 articles retrieved from Scopus, Google Scholar, and ScienceDirect were examined across different machine learning and energy-related keywords from 1990 to the most recent research papers on 14 January 2025. The results emphasise the efficiency of the established methods in attaining fault detection with a high accuracy of over 98%. It is also observed that considering their effortlessness and performance accuracy, artificial neural networks are the most promising technique in finding a central photovoltaic system fault detection. In this regard, an extensive application of machine learning to solar photovoltaic systems could thus clinch a quicker route through sustainable energy production.

Since 2019, Togo has resolutely engaged in the decentralization process marked by communalization and elections of municipal councilors. Financial autonomy constitutes an essential lever for the free administration of municipalities, allowing them to ensure decision-making and the implementation of development projects. However, despite a legal and regulatory framework defining taxation specific to local authorities, Togolese municipalities are often perceived as needing more financial resources. This study aims to map the financing mechanisms for decentralization in Togo and analyze their contribution to municipal budgets. By adopting a quantitative approach combining documentary analysis and interviews with 188 experts and practitioners of local finance from various Togolese structures, four main financing mechanisms were identified: local, national, Community, and international. Among these mechanisms, own resources (in particular from the sale of products and services, fiscal and non-fiscal taxes) and state transfers via the Support Fund for Local Authorities emerge as the primary sources of financing for municipalities. However, the study reveals that several instruments of local mechanisms, although institutionally defined, still need to be updated in many municipalities, thus limiting their effectiveness in resource mobilization. These results highlight the importance of optimizing the management of local mechanisms to strengthen municipalities’ financial autonomy and support territories’ sustainable development.

Nationwide integration of AI into the contemporary art sector has taken place since government AI regulations in 2023 to promote AI use. China’s AI integration into industry is ‘ahead’ of other countries, meaning that other countries can learn from these creative professionals. Consequently, contemporary visual artists have devised arts-led sustainable AI solutions to overcome global AI concerns. They are now putting these solutions into practice to maintain their jobs, arts forms, and industry. This paper draws on 30 interviews with contemporary visual artists, and a survey with 118 professional artists from across China between 2023 and 2024. Findings show that 87% use AI and 76% say AI is useful and they will continue to use AI into the future. Findings show professionals have had time to find DIY, bottom-up solutions to AI concerns, including (1) building strong authorship practices, identity, and brand, (2) showing human creativity and inner thinking, (3) gaining a balanced independent position with AI. They want AI regulations to liberalise and promote AI use so they can freely experiment and develop AI. These findings show how humans are directing the use of AI, altering current narratives on AI-led impacts on industry, jobs, and human creativity.

In wealthy nations, biofuel usage has grown in importance as a means of addressing climate change concerns, ensuring energy security, and promoting agricultural development. Because they understand the potential advantages of biofuel for rural development and job creation, governments have created policies and legislation to encourage the production of biofuel. However, the province of Limpopo hasn’t fully taken advantage of the potential to use biofuel production as a vehicle for job development, despite a higher demand for the fuel. There is currently a lack of understanding of the role of biofuel in promoting local development in developing regions. For this reason, this study made use of semi-structured interviews to explore how biofuel production can be used as an instrument for Local Economic Development (LED) in the Limpopo province of South Africa. The research investigated the determinants of empowerment that could impact the commercial feasibility of biofuel production in the province. It also identified the need for human resource development to get workers ready for jobs in Limpopo’s biofuel sector. The results showed that, provided certain conditions were met, the production of biofuel in Limpopo may be a useful instrument for creating local jobs. By highlighting the potential for job creation and the importance of human resource development, this research aims to facilitate evidence-based decision-making that can harness biofuel production for sustainable rural development in the region. The value of this study lies in its contribution to the understanding of biofuel’s role in LED, offering actionable insights for policymakers and stakeholders in Limpopo. 

The study examines the relationship between EPS and the gearing ratios and return on equity (ROE) ratio of 9 public listed firms on the Malaysian Stock Exchange from 2014 to 2022 financial years. The firms are selected at random. From this study it was established that there is a negative relation between EPS and gearing and a positive relation between EPS and ROE. Companies that want to attract more investors need to keep their gearing ratio low and increase the return on equity ratio high. To obtain the benefits of gearing or external funding, there need to be a balance between equity and debts. There is no one optimal balance between debt and equity. This balance is difference for each company and the sector they operate in. It is important for managers of companies to find the optimal balance between debt and equity, unique to their company.