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.

This paper aims to explore how to build a sustainable peace and development model for China’s peacekeeping efforts through the application of data-driven methods from UN Global Pulse. UN Global Pulse is a United Nations agency dedicated to using big data and artificial intelligence technologies to address global challenges. In this paper, we will introduce the working principles of UN Global Pulse and its application in the fields of peacekeeping and development. Then, we will discuss the current situation of China’s participation in peacekeeping operations and how data-driven methods can help China play a greater role in peacekeeping tasks. Finally, we will propose a sustainable peace and development model that combines data-driven methods with the advantages of China’s peacekeeping efforts to achieve long-term peace and development goals.

The study builds on Deborah Stone’s foundational work exploring the mechanics of causal narratives and their implications for framing problems, assigning responsibility, and guiding policy solutions. The purpose of this research is to unravel the complexities of causal narratives in contemporary politics and understand their profound influence on public policy and society at large. In the digital age, where information is abundant and the traditional gatekeeping role of media has diminished, causal narratives have become increasingly multifaceted. The study aims to explore how these narratives, influenced by the intersections of natural phenomena, human actions, politics, risk, and media, shape public understanding and policy directions. The study employs an extensive review of existing literature, covering works from political science, media studies, and public policy. This includes analyzing seminal texts like Deborah Stone’s “Policy Paradox” and recent studies on media’s evolving role in political discourse. Today’s causal narratives are multifaceted, influenced by a myriad of factors including political agendas, scientific findings, and media portrayals. In conclusion, the research highlights the dynamic nature of causal narratives in the digital age and their significant impact on public policy and societal outcomes. It underscores the need for nuanced understanding and strategic approaches in crafting and interpreting these narratives.

Fire accidents are one of the serious security threats facing the metro, and the accurate determination of the index system and weights for fire assessment in underground stations is the key to conducting fire hazard assessment. Among them, the type and quantity of baggage, which varies with the number of passengers, is an important factor affecting the fire hazard assessment. This study is based on the combination of subjective and objective AHP (Analytic Hierarchy Process) with the available Particle Swarm Optimisation algorithm PSO (Particle Swarm Optimization) and the perfect CRITIC (Criteria Importance Through Intercriteria Correlation) empowered fuzzy evaluation method on the metro station fire hazard toughness indicator system and its weights were determined, and a fuzzy comprehensive evaluation model of metro station safety toughness under the influence of baggage was constructed. The practical application proves that the method provides a new perspective for the fire risk assessment of underground stations, and also provides a theoretical basis for the prevention and control of mobile fire load hazards in underground stations.