Personality traits refer to enduring patterns of emotions, behaviors, and thoughts that shape an individual’s distinct character, influencing how they perceive and engage with their environment. This quantitative study aims to underscore the influence of personal factors and the role of educational institutions in mapping sustainable green entrepreneurial intentions among university students in Saudia Arabia. To examine the impact of personality traits and entrepreneurship education on students’ green initiatives, the research employs a quantitative research method, collecting data through a structured questionnaire survey from 494 participants who enrolled in the entrepreneurship education at King Faisal University. Structural equation modeling via SmartPLS 3 is employed for data analysis. The study reveals significant associations between the need for achievement, proactiveness, risk-aversion, self-efficacy, and entrepreneurship education with green entrepreneurial intentions. Our research findings demonstrate that the inclusion of entrepreneurship education in the curriculum has a noteworthy and favorable influence on the intention to engage in green entrepreneurship (β = −0.105, t = 3.270, p < 0.001). Additionally, it is worth noting that the desire for achievement remains significantly associated with the intention to engage in green entrepreneurship (β = 0.120, t = 3.588, p < 0.000). Furthermore, the proactive behavior of individuals has a positive and constructive impact on the intention to engage in green entrepreneurship (β = 0.207, t = 4.272, p < 0.000). Similarly, the inclination to avoid risk is found to have a beneficial and significant influence on the intention to engage in green entrepreneurship (β = 0.336, t = 4.594, p < 0.000). Lastly, it is worth highlighting that individuals’ belief in their own abilities, referred to as self-efficacy, is positively and significantly linked to the intention to engage in green entrepreneurship (β = 0.182, t = 2.610, p < 0.009). The research carries social, economic, and academic implications by emphasizing the positive contribution of green entrepreneurs to the future. Practical recommendations for policymakers and decision-makers are provided.

Recognizing the importance of competition analysis in telecommunications markets is essential to improve conditions for users and companies. Several indices in the literature assess competition in these markets, mainly through company concentration. Artificial Intelligence (AI) emerges as an effective solution to process large volumes of data and manually detect patterns that are difficult to identify. This article presents an AI model based on the LINDA indicator to predict whether oligopolies exist. The objective is to offer a valuable tool for analysts and professionals in the sector. The model uses the traffic produced, the reported revenues, and the number of users as input variables. As output parameters of the model, the LINDA index is obtained according to the information reported by the operators, the prediction using Long-Short Term Memory (LSTM) for the input variables, and finally, the prediction of the LINDA index according to the prediction obtained by the LSTM model. The obtained Mean Absolute Percentage Error (MAPE) levels indicate that the proposed strategy can be an effective tool for forecasting the dynamic fluctuations of the communications market.

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Madura Island, with more than half of its population, are women encountering socio-economic problems, which eventually create high poverty and unemployment rates. However, the Madurese are also well-known for their resiliency and entrepreneurial characteristics. The effort to solve the issues by empowering the community, women in particular, has been taken seriously primarily by entrepreneurs who were born and raised in the community. Therefore, this research aims to gain insight into the current Madurese entrepreneur’s business pattern and their social concerns in order to propose a strategy to increase productivity as an effort to empower women’s communities. The methodology is qualitative research, which collects data using semi-structured interviews with representatives of the Madurese entrepreneurs in four areas of Madura Island. Their responses are then transcripted and coded for content analysis based on the designed themes. The result shows that they recognise and practise the social entrepreneurship (SE) pattern, although they do not understand the term. Subsequently, the technological application for business operations in general is still limited to the usage of digital technology (DT) for marketing and transaction activities, which helps increase business performance or productivity. Hence, the initiation of technosociopreneurship as a strategy to further develop SE activities with the hope of increasing productivity in empowering women’s communities is proposed. Further research development is advised using quantitative methods for generalisable findings.

The fifth-generation technology standard (5G) is the cellular technology standard of this decade and its adoption leaves room for research and disclosure of new insights. 5G demands specific skillsets for the workforce to cope with its unprecedented use cases. The rapid progress of technology in various industries necessitates a constant effort from workers to acquire the latest skills demanded by the tech sector. The successful implementation of 5G hinges on the presence of competent individuals who can propel its progress. Most of the existing works related to 5G explore this technology from a multitude of applied and industrial viewpoints, but very few of them take a rigorous look at the 5G competencies associated with talent development. A competency model will help shape the required educational and training activities for preparing the 5G workforce, thereby improving workforce planning and performance in industrial settings. This study has opted to utilize the Fuzzy Delphi Method (FDM) to investigate and evaluate the perspectives of a group of experts, with the aim of proposing a 5G competency model. Based on the findings of this study, a model consisting of 46 elements under three categories is presented for utilization by any contingent of 5G. This competency model identifies, assesses, and introduces the necessary competencies, knowledge, and attributes for effective performance in a 5G-related job role in an industrial environment, guiding hiring, training, and development. Companies and academic institutions may utilize the suggested competency model in the real world to create job descriptions for 5G positions and to develop curriculum based on competencies. Such a model can be extended beyond the scope of 5G and lay the foundation of future wireless cellular network competency models, such as 6G competency models, by being refined and revised.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.