Objectives: The unprecedented COVID-19 pandemic has intensified the stress on blood banks and deprived the blood sources due to the containment measures that restrict the movement and travel limitations among blood donors. During this time, Malaysia had a significant 40% reduction in blood supply. Blood centers and hospitals faced a huge challenge balancing blood demand and collection. The health care systems need a proactive plan to withstand the uncertain situation such as the COVID-19 pandemic. This study investigates the psychosocial factors that affect blood donation behavior during a pandemic and aims to propose evidence-based strategies for a sustainable blood supply. Study design: Qualitative design using focus group discussion (FGD) was employed. Methods: Data were acquired from the two FGDs that group from transfusion medicine specialists (N = 8) and donors (N = 10). The FGD interview protocol was developed based on the UTM Research Ethics Committee’s approval. Then, the data was analyzed using Nvivo based on the General Inductive Approach (GIA). Results: Analysis of the text data found that the psychology of blood donation during the pandemic in Malaysia can be classified into four main themes: (i) reduced donation; (ii) motivation of donating blood; (iii) trends of donation; and (iv) challenges faced by the one-off, occasional, and non-donors. Conclusions: Based on the emerging themes from the FGDs, this study proposes four psycho-contextual strategies for relevant authorities to manage sustainable blood accumulation during the pandemic: (1) develop standard operating procedure for blood donors; (2) organize awareness campaigns; (3) create a centralized integrated blood donors database; and (4) provide innovative Blood Donation Facilities.

The global Testing, Inspection, and Certification (TIC) service market is experiencing significant growth, driven by rising demand for high-quality and safety-related TIC services across various industries. This research aims to redesign a position map and strategy for Indonesian TIC State-Owned Enterprises (SOEs) in the Red Ocean competition. This systematic literature review analyzed 17 journals. The results show that the Indonesian TIC SOEs are intensively competing in the Red Ocean competition. In designing the position map in the Red Ocean competition, the SOEs must use technology in their operational activities to implement good corporate governance, collaborative strategies, resource management, and leadership styles aligned with the organizational culture.

Human settlement patterns in the South are clearly inequitable and dysfunctional, with tenure insecurity remaining a significant issue. Consequently, there has been a dramatic increase in housing demand driven by rising household sizes and accelerated urbanization. Local governments have a clear mandate to ensure socio-economic development and promote democracy, which necessitates ongoing consultations and renegotiations with citizens. This paper critically examines the de-densification of informal settlements as a pivotal strategy to enhance the quality of life for citizens, all while maintaining essential social networks. Governments must take decisive action against pandemics by transforming spaces into liveable settlements that improve livelihoods. A qualitative method was employed, analyzing data drawn from interviews to gain insights into individual views, attitudes, and behaviors regarding the improvement of livelihoods in informal settlements. The study utilized a simple random sampling technique, ensuring that every individual in the population selected had an equal opportunity for inclusion. Semi-structured interviews were conducted with twenty community members in Cornubia, alongside discussions with three officials from eThekwini Municipality and KwaZulu Natal (KZN) Provincial Department of Human Settlements. Data was analyzed using thematic analysis, and the findings hold substantial benefits for the most disadvantaged citizens. Therefore, municipalities have an obligation to transform urban areas by reducing inequality, bolstered by national government policy, to achieve a resilient, safe, and accessible urban future. The evidence presented in this paper underscores that local governments, through municipalities, must prioritize de-densifying informal settlements in response to pandemics or hazards. It is vital to leverage community-driven initiatives and reinforce networks within these communities. The paper calls for the establishment of a socially centered government through the District Development Model (DDM), emphasizing socio-economic transformation as a pathway to enhance community quality of life.

Background and introduction: The East and Southeast Asian newly industrialized economies have shown spectacular economic development by their export-oriented development policies during recent decades, which resulted in not only economic wealth but enabled them to be technology exporters and investors. Their products, their flagship brands today are well-known and recognized throughout the world. It is not surprising that the Hungarian government—by its Hungarian Eastern Opening strategy—intended to focus on these economies, even though that with most of them there were intensive and broad co-operation in the fields of business, investment, culture, education and tourism. The new strategy gave a focus on increasing the diplomatic and trade relationship with the wider region, new embassies and trade representation offices were opened or re-opened in several locations with the view of intensifying the business and the people-to-people contacts. Even though the pandemic of Covid 19 and the energy crisis caused disruption in international trade, it can be said the trade and investment relations with these economies have still been growing, especially on the import side. The prospects of the growth of Hungarian exports to these destinations are modest which is hindered by the huge geographic distance, the peculiar consumer preferences, the merely different market conditions and the sharp competition. Objective: The aim of this paper to illustrate by statistical figures the state of the trade and investment relations between Hungary and the Republic of Korea, Taiwan, Singapore and Thailand. Methodology: Bibliographic and data analysis, focusing on the relevant international and Hungarian literature and databases, especially the trade and investment statistics of the Hungarian Central Statistical Office (HCSO/KSH).

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.