Psychological capital is recognized as a positive and unique factor that plays a crucial role in human resource development and performance management. It has the potential to increase employees’ efforts towards achieving organizational goals and improving their entrepreneurial strategy skills. The objective of this study was to examine the contribution of psychological capital in enhancing the entrepreneurial strategy skills of employees in Saudi universities. The study employed a descriptive approach, specifically utilizing the survey study method. The study sample was intentionally selected from different categories within the study population. Data was collected from 530 participants using two questionnaires. The findings revealed that employees exhibited an average level of psychological capital, while their practice of entrepreneurial strategy skills was rated as poor. The study also demonstrated that psychological capital significantly contributes to enhancing employees’ entrepreneurial strategy skills. Furthermore, statistically significant differences were observed in the psychological capital of employees across certain variables, such as personal and functional aspects. The average level of psychological capital among employees indicates the need for further development in this area. By focusing on enhancing psychological capital, organizations can effectively improve the entrepreneurial strategy skills of their employees. It is clear that investing in the psychological capital of employees can lead to significant improvements in their entrepreneurial strategy skills. This highlights the potential for organizations to foster a more entrepreneurial mindset and approach among their staff members. Additionally, the study’s findings underscore the need to tailor interventions and development programs to address specific aspects of psychological capital that may vary across different employees. Overall, the study emphasizes that psychological capital is a valuable resource that should be nurtured and developed within the organizational context. By doing so, organizations can not only enhance the entrepreneurial strategy skills of their employees but also cultivate a more resilient, motivated, and engaged workforce. This has the potential to contribute to the overall success and innovation of Saudi universities and similar institutions.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.

Renewable energy is gaining momentum in developing countries as an alternative to non-renewable sources, with rooftop solar power systems emerging as a noteworthy option. These systems have been implemented across various provinces and cities in Vietnam, accompanied by government policies aimed at fostering their adoption. This study, conducted in Ho Chi Minh City, Vietnam investigates the factors influencing the utilization of rooftop solar power systems by 309 individuals. The research findings, analyzed through the Partial least squares structural equation modeling (PLS-SEM) model, reveal that policies encouragement and support, strategic investment costs, product knowledge and experience, perceived benefits assessment, and environmental attitudes collectively serve as predictors for the decision to use rooftop solar power systems. Furthermore, the study delves into mediating and moderating effects between variables within the model. This research not only addresses a knowledge gap but also furnishes policymakers with evidence to chart new directions for encouraging the widespread adoption of solar power systems.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

In recent times, there has been a surge of interest in the transformative potential of artificial intelligence (AI), particularly within the realm of online advertising. This research focuses on the critical examination of AI’s role in enhancing customer experience (CX) across diverse business applications. The aim is to identify key themes, assess the impact of AI-powered CX initiatives, and highlight directions for future research. Employing a systematic and comprehensive approach, the study analyzes academic publications, industry reports, and case studies to extract theoretical frameworks, empirical findings, and practical insights. The findings underscore a significant transformation catalyzed by AI integration into Customer Relationship Management (CRM). AI enables personalized interactions, fortifies customer engagement through interactive agents, provides data-driven insights, and empowers informed decision-making throughout the customer journey. Four central themes emerge: personalized service, enhanced engagement, data-driven strategy, and intelligent decision-making. However, challenges such as data privacy concerns, ethical considerations, and potential negative experiences with poorly implemented AI persist. This article contributes significantly to the discourse on AI in CRM by synthesizing the current state, exploring key themes, and suggesting research avenues. It advocates for responsible AI implementation, emphasizing ethical considerations and guiding organizations in navigating opportunities and challenges.

This study explores how public relations (PR) can give universities an edge in today’s competitive landscape. By examining past research, conducting interviews in 10 diverse cities in Vietnam, and analyzing case studies, it reveals the powerful link between PR strategies and student involvement. The research shows that well-crafted PR activities, tailored to different student groups and utilizing digital platforms, significantly impact student perceptions and enrollment decisions. It delves deeper than simply confirming PR’s effectiveness, offering insights into how specific PR tactics can resonate with student needs and expectations. Furthermore, it explores how PR influences student retention, highlighting the long-term benefits for universities. This research is a valuable tool for institutions seeking to thrive. By understanding the power of PR in shaping student decisions, universities can tailor their outreach efforts more effectively. Additionally, the study emphasizes the lasting advantages of a strategic PR approach, contributing to a broader discussion on its importance in higher education. Ultimately, these findings benefit both institutions and students, who can expect improved transparency, engagement, and communication within their academic communities.