This study explores the interconnected roles of organizational atmosphere, psychological capital, work engagement, and psychological contract on the work performance. Structural equation modeling and moderated mediation analyses were conducted to test the hypothesized relationships. Methodologically, the study employed a stratified random sampling of 369 faculty members across various disciplines. Key findings reveal that both organizational atmosphere and psychological capital have a significant positive impact on work engagement, which in turn, enhances work performance. Work engagement acted as a mediator in these relationships. Moreover, the psychological contract was found to moderate the relationship between work engagement and work performance, indicating that the engagement-performance link is stronger when employees perceive their psychological contract has been fulfilled. The implications of this research are multifaceted. Theoretically, it contributes to organizational behavior literature by integrating psychological contracts into the engagement-performance narrative. Practically, it provides actionable insights for university administrators, suggesting that investments in a supportive organizational atmosphere and the development of faculty psychological capital are likely to yield improvements in engagement and performance. The study also underscores the importance of effectively managing psychological contracts to maximize employee output.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.

This study evaluates the sustainability and ethical practices of Kerry Logistics Network Limited (KLN), a prominent logistics service provider headquartered in Hong Kong. Using normative ethical theories, stakeholder analysis, and the Circle of Sustainability framework, this research examines KLN’s alignment with global sustainability standards, particularly the United Nations Sustainable Development Goals (SDGs). The findings reveal that KLN has achieved significant milestones in environmental management, such as reducing greenhouse gas emissions by 11% from 2021 to 2022 through the deployment of electric trucks and incorporating renewable energy in warehouse operations. KLN has also enhanced social responsibility and governance practices by implementing fair labor policies and establishing a rigorous code of conduct, ensuring compliance with ethical guidelines across its supply chain. However, the study identifies areas for improvement, including biodiversity actions, battery recycling processes, and transparency in stakeholder engagement. Emphasizing the importance of third-party validation, this paper underscores KLN’s leadership in the logistics industry and provides insights for other companies aiming to improve sustainability performance through comprehensive, verifiable practices.

This contribution questions young people’s access to digital networks at the scale of intermediate cities in Saint-Louis. Thus, it analyzes the prescriptions of digital actors responsible for the development of digital economy in relation with the orientations of the Senegal Digital 2025 strategy. This is a pretex to highlight the gaps between official political discourses and the level of deployment of digital infrastructures. The study highlights the need to repoliticize the needs of populations for broadband and very high-speed connections to promote local initiatives for youth participation in Saint-Louis. Indeed, datas relating to access and use of the Internet by young people reveal inequalities linked to household income, the disparity of infrastructure and digital equipment, and the discontinuity in neighborhood development, but also to the adaptability of the internet service marketed. Through urban and explanatory sociology mobilized through the approach of young people’s real access to the Internet, our analyzes have shown at the scale of urban neighborhoods the impact of the actions recommended by those involved in the development of populations’ access to Internet. The result is that the majority of young people are forced to access the Internet through medium-speed mobile networks.

The study aims to investigate the impact of digital leadership on sustainable competitive advantage, digital talent, and knowledge workers. Additionally, it explores the mediating role of digital talent (DT) and knowledge workers (KW) in the relationship between digital leadership (DL) and sustainable competitive advantage (SC), using the Technology Acceptance Model (TAM) as its theoretical foundation. The researchers employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine survey data from 784 employees working in Egyptian travel agencies and tour operators. The results demonstrate that DL significantly enhances SC, DT, and KW. Moreover, DT and KW were shown to positively contribute to SC and serve as partial mediators in the relationship between DL and SC. The findings highlight the crucial role of developing DT and creating an environment that embraces technological acceptance and innovation. This approach amplifies the strategic effectiveness of DL, ultimately contributing to long-term organizational success.

The improper disposal of litter by tourists poses a significant threat to tourism destinations worldwide, including in Indonesia. To mitigate marine litter, promoting eco-friendly behavior (EFB) among tourists is essential. This study applies the extended Theory of Planned Behavior (TPB), which posits that an individual’s behavior is driven by their attitudes, subjective norms, and perceived behavioral control, to better understand the factors influencing eco-friendly behavioral intentions. In this research, ecological consciousness and ecological knowledge were added to the traditional TPB framework to gain deeper insights into tourist behavior. Data were collected through a structured questionnaire from 876 visitors to Lake Singkarak, Indonesia. The findings demonstrate that the inclusion of ecological consciousness and ecological knowledge significantly enhances the predictive power of the TPB model in explaining eco-friendly behavioral intentions. Based on these results, raising public awareness, improving government management, and enhancing the quality of lake attractions are recommended to encourage responsible tourism. These measures can reduce litter and conserve lake habitats, ultimately contributing to the sustainability of tourism in the region.