This study aims to develop a framework that helps organizations to fulfill their environmental and social responsibility amid constraints in selecting which stakeholders’ interest comes first and the essential to have an evolved strategic planning that can accommodate broader systemic planning and practice that will yield authenticity in business sustainability with components of environmental worldview of its leaders and organizational learning in the framework. This research uses the method of literature review with the data from interviews and content analysis of the report from one organization that has successfully implemented social and environmentally friendly practices. Based on an in-depth review of literatures on worldview, organizational learning, and strategic planning, and with empirical study from one organization, a conceptual framework by combination of the existing concepts is produced to enable an integration of theories in a range of possible actions for organizations to achieve sustainable development. The result from this research’s framework will allow further study to be carried out in the future to verify associations between existing concepts or variables within the framework, and to produce next empirical results in supporting those theories being reviewed in this paper.

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.

In the past, Sabah has often been reported as Malaysia’s poorest state, with the recorded highest incidence of absolute poverty among all the other states. The consumption patterns of households in Sabah have been significantly impacted by such circumstances. This further draws light on the adverse impact on the broader economy, as low levels of spending may restrict demand for products and services, stifling economic growth. The understanding of households’ consumption functions based on the Permanent Income Hypothesis (PIH) will advance knowledge in identifying the key factors that influence the households’ spending decisions. Pointing out the scant number of past studies done within this very context, and focusing on the Sabah state in particular, further motivated this study, this paper aims to develop a conceptual framework that can estimate and examine the households’ consumption functions in Sabah. As such, the methodology of drawing upon narrative reviews from research in the past will be used in this paper to develop the conceptual framework. The result of this study built upon the framework developed will help in identifying the factors that explain the households’ consumption patterns, in particular, whether the function estimated will be consistent with the Permanent Income Hypothesis (PIH). It is hoped that the conceptual framework built will aid in providing valuable empirical insight for policymakers in designing effective policies that can uplift households that are living in poverty.

Increasing populations in cities have created challenges for the urban environment and also public health. Today, lacking sport participation opportunities in urban settings is a global concern. This study conceptualizes and develops a theoretical framework that identifies factors associated with effective urban built environments that help shape and reshape residents’ attitude toward sport activities and enhances their participation. Based on a comprehensive review of literature and by following the Stimulus-Organism-Response (SOR) theory and attitude change theory, a four-factor measurement model is proposed for studying urban built environment, including Availability, Accessibility, Design, and Safety. Further examinations are made on how these factors are channeled to transform residents’ attitudes and behavior associated with participating in sport activities, with Affordability as a moderator. Discussions are centered around the viability of the developed framework and its application for future research investigations.