This study aims to examine the mediating role of institutional trust (IT) between perceived corruption and subjective well-being (SWB) using data from 1566 households in a developing country. It deploys ordinary least square (OLS) and an ordered logit model within the generalized structural equation model. Results show that individuals who perceived no corruption in a country report more IT and higher levels of SWB. Furthermore, the direct effects of good governance, perceived IT, and the absence of corruption on SWB is also positive. Moreover, satisfaction with hospital services also improves happiness and life satisfaction levels. This study improves and validates how corruption is assessed to support future measures that reduce its harmful effects. Moreover, the masses must have widespread awareness about the critical nature of corruption and IT relative to well-being. This study also highlights the need to develop strong institutions to improve trust and minimize corruption.

Weather and climate services are essential tools that help farmers make informed choices, such as choosing appropriate crop varieties. These services depend considerably on the availability of adequate investments in infrastructure related to weather forecasting, which are often provided by the State in most countries. Zimbabwean farmers generally have limited access to modern weather and climate services. While extensive attempts have been made to investigate farmers’ socioeconomic factors that influence access to and use of weather and climate services, comparative political economy analysis of weather and climate service production and use is limited. To address this knowledge gap, this study examines the production, dissemination, and usage of modern seasonal weather services through a political economy analysis perspective. The findings of this study highlight considerable discrepancies in access and use of seasonal weather forecasts between male and female farmers, those who practise African Traditional Religions versus Christians, and the minority group (Ndau tribe) and the majority group (Manyika tribe). This result suggested the presence of social marginalization. For example, minority Ndau members living in remote areas with limited radio signals and a weak mobile network have limited access to modern seasonal weather forecasts, forcing them to rely much more on indigenous weather forecasts. Further, due to unequal power relations, a greater proportion of male farmers participated in agricultural policy formation processes than their female counterparts. To promote inclusive development and implementation, deliberate efforts need to be made by State authorities to incorporate adherents of African traditional religions, members of minority tribes and female farmers in agricultural policymaking processes, including seasonal weather forecast delivery policies. Further, the study suggests the relaxation or elimination of international sanctions on Zimbabwe by the European Union, United Kingdom and the United States of America, given that they are considerably affecting marginalized groups of farmers in their climate change adaptation practices, including the use of modern weather and climate services. The vast majority of these marginalized farmers never benefitted from the land reform programme and were also not responsible for the design and implementation of this programme which triggered these sanctions.

In recent years, China’s economy has undergone rapid development. Increased disposable income and the rapid expansion of Internet-based financial services have positioned China as the largest market for luxury goods. Gen Z, the youngest demographic within emerging markets, is expected to play a pivotal role as the primary driver of the luxury market. However, while China’s luxury market continues to exhibit a high growth rate, this growth has gradually decelerated in comparison to the previous two years according to researchers. This presents a significant challenge for the luxury industry, as maintaining and enhancing the global growth trend has become a pressing concern where consumer behavior is concerned. The second key issue addressed in this study revolves around the concepts of compulsive buying and brand addiction, which can lead individuals, particularly Gen Z, to develop an addiction to luxury consumption. This study is based on an integrated model of conspicuous consumption, social comparison, and impression management theory. The key variables are materialism, brand consciousness, status-seeking, peer pressure, and collectivism to predict the luxury consumption model with debt attitude introduced as a moderating variable to study consumer behaviour in this age group. A non-probability sampling method and 480 people were selected as research samples. Quantitative analysis was used in this study, and SPSS and Smart PLS were used as data analysis tools. Structural equation model (SEM) using partial least squares method was used to determine the relationship of the variables and the moderating effect of debt attitude. The results showed that brand consciousness, status seeking, debt attitude and materialism had the strongest relationship with luxury consumption. Debt attitude as a moderating factor has a significant impact on the hypothesized relationship of the model. This paper provides empirical evidence for research on Gen Z’s luxury consumption, which has practical implications to marketers, luxury companies, local luxury brands and credit institutions.

In Industry 4.0, the business model innovation plays a crucial role in enabling organizations to stay competitive and capitalize on the opportunities presented by digital transformation. Industry 4.0 is driven by digitalization and characterized by integrating various emerging technologies. These technologies can potentially change traditional business models and create new value propositions for customers. This paper aims to analyze and review the research papers through a bibliometric approach scientifically. The data were extracted from reputable Clarivate Web of Science (WoS) Core Collection sources from 2010 to 2023 (June). However, the publication started in 2018 for the research fields. The results show that scientific publications on research domains have increased significantly from 2020. VOSviewer, R Language, and Microsoft Excel were utilized for analysis. Bibliometric and Scientometric approaches conducted to determine and explore the publication patterns with significant keywords, topical trends, and content clustering better discussions of the publication period. The visualization of the data set related to research trends of Industry 4.0 in relation to Business Model Innovation resulted in several co-occurrence clusters namely: 1) Business Model Innovation; 2) Industry 4.0; 3) Digital transformation; and 4) Technology implementation and analysis. The study results would identify worldwide research trends related to the research domains and recommendations for future research areas.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

This study aims to analyse the current state of library and information science (LIS) education in South Korea and identify educational challenges in building a sustainable library infrastructure in the digital age. As libraries’ role expands in a rapidly changing information environment, LIS education must evolve. Using topic modelling techniques, this study analysed course descriptions from 37 universities and identified 10 key topics. The analysis revealed that, while the current curricula cover both traditional library science and digital technology topics, focus on the latest technology trends and practical, hands-on education is lacking. Based on these findings, this study suggests strengthening digital technology education by incorporating project-based learning; integrating emerging technologies, such as data science and artificial intelligence; and emphasising community engagement and soft skills development. This study provides insights into improving LIS education to better align with the digital era’s evolving demands.