Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers’ capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.

Indonesia, an emerging archipelagic nation, possesses abundant natural resources spanning marine, land (including forests and water sources), and diverse biological riches. The agricultural sector emerges as a pivotal driver of growth across the country, exhibiting extensive distribution. Consequently, there is an urgent imperative for comprehensive research to bolster and optimize the performance of this sector. This study aims to meticulously analyze and scrutinize macroeconomic variables aimed at enhancing Indonesia’s agricultural sector. Through the utilization of a dynamic panel model, the study zeroes in on crucial variables: economic growth in the agricultural sector, farmer terms of exchange, human development index, population density, inflation, average daily wages, and lagged economic growth data from each province in Indonesia. The best model for dynamic panel testing, employing both First Difference Generalized Method of Moments (FD-GMM) and Generalized Method of Moments System (SYS-GMM) approaches, is identified as the SYS-GMM model. This model exhibits unbiased and consistent estimation, as evidenced by the Arellano-Bond (AB) test and Sargan test results. The analysis conducted using this selected model reveals notable findings. Lagging agricultural sector performance, human capital measured by the Human Development Index (HDI), and farmers’ exchange rates are found to significantly and positively influence the economic growth of the agricultural sector. Conversely, inflation exerts a significant and negative impact on sectoral growth. However, wage levels and population density do not demonstrate a significant partial effect on the economic growth of the agricultural sector.

The digitalization of the construction industry is deemed a crucial element in Construction 4.0’s vision, attainable through the implementation of digital twinning. It is perceived as a virtual strategy to surmount the constraints linked with traditional construction projects, thereby augmenting their productivity and effectiveness. However, the neglect to investigate the causal relationship between implementation and construction project management performance has resulted from a lack of understanding and awareness regarding the consequences of digital twinning implementation, combined with a shortage of expertise among construction professionals. Consequently, this paper extensively explores the relationship between digital twinning implementation and construction project management performance. The Innovation Diffusion Theory (IDT) is employed to investigate this relationship, utilizing a quantitative research approach through document analysis and questionnaire surveys. Additionally, partial least squares structural equation modeling (PLS-SEM) with SmartPLS software is employed to deduce the relationship. The results underscore that digital twinning implementation significantly improves construction project management performance. Despite recognizing various challenges in digital twinning implementation, when regarded as moderating factors, these challenges do not significantly impact the established causal relationship. Therefore, this investigation aligns with the national push toward the digitalization of the construction sector, highlighting the positive impacts of digital twinning implementation on construction project management performance. Moreover, this study details the impacts of implementing digital twinning from the construction industry’s perspective, including positive and negative impacts. Afterwards, this paper addresses the existing research gap, providing a more precise understanding and awareness among construction industry participants, particularly in developing nations.

Within the Saudi Arabian banking sector, the quality of work life emerges as a crucial determinant shaping employee performance. This research delves into the nuanced impacts of diverse job quality facets on employee efficacy within this domain. Employing a stratified random sampling methodology, 500 institutions were selected, yielding a 49.6% response rate, or 248 completed surveys, with the active engagement of senior management. Utilizing a quantitative paradigm, the study harnessed descriptive statistics and structural equation modeling (SEM) to elucidate the interplay between job quality dimensions and performance outcomes. The analysis revealed that elements like compensation structures, work-life equilibrium, and growth opportunities substantially influenced employee productivity. In contrast, most job quality facets garnered positive evaluations, and aspects related to wage and compensation exhibited room for enhancement. The research accentuates the imperative of elevating job quality benchmarks within the banking sector to augment employee contentment and performance metrics. This study’s insights advocate for stakeholders and policymakers to champion job quality as a pivotal driver for optimizing organizational effectiveness.

The quality of indoor classroom conditions influences the well-being of its occupants, students and teachers. Especially the temperature, outside acceptable limits, can increase the risk of discomfort, illness, stress behaviors and cognitive processes. Assuming the importance of this, in this quantitative observational study, we investigated the relationship between two environmental variables, temperature and humidity, and students’ basic emotions. Data were collected over four weeks in a secondary school in Spain, with environmental variables recorded every 10 minutes using a monitoring kit installed in the classroom, and students’ emotions categorized using Emotion Recognition Technology (ERT). The results suggest that high recorded temperatures and humidity levels are associated with emotional responses among students. While linear regression models indicate that temperature and humidity may influence students’ emotional experiences in the classroom, the explanatory power of these models may be limited, suggesting that other factors could contribute to the observed variability in emotions. The implications and limitations of these findings for classroom conditions and student emotional well-being are discussed. Recognizing the influence of environmental conditions and monitoring them is a step toward establishing smart classrooms.

Background: The term “corporate culture” is used to describe a company’s long-standing norms and practices, as well as the staff’s views and the anticipated value of their job. Executives may need to adjust their leadership styles to achieve the organization’s goal, which may have consequences for the satisfaction of the workforce. Therefore, it is essential to appreciate the relationship between business ethos, management style, work performance, mental health and employees’ job satisfaction. Methods: Researchers was conducting a cross-sectional survey of Saudi Arabian and Indian employees. Data was be collected using a structured questionnaire. To test the reliability of the data, they will be analysed by “Cronbach’s a and confirmatory factors”. SEM was be used to show the relationships of organizational cultures and leadership behaviour on work performance, mental health and job satisfaction through IBM-SPSS and SmartPLS software. Scope: A corporation with a strong culture and effective leadership shares principles and norms of behaviour with its workers, which should aid them in attaining their goals and objectives. Employees could gain work recognition, mental piece, work performance and job satisfaction when they can accomplish the obligations allotted to them by the company. Results: Corporate culture were significantly (positively) correlated with work performance, mental health and job satisfaction. In the same way, leadership behavior was significantly (positively) correlated with work performance, mental health and job satisfaction. Conclusions: The organisational culture holds significant importance, exerting a substantial influence on the overall well-being and productivity of the work environment. The acknowledgement and acceptance of the organisational ethos by workers can have a significant impact on their work behaviour and attitudes when it comes to communication and promotion. When there is a positive interaction between leadership and employees, the latter are more likely to actively contribute to team collaboration and interaction. Additionally, they are more likely to be motivated to achieve the organization’s assigned mission and objectives. As a result, work performance, mental health, and job satisfaction are enhanced.