Currently, there is a unique situation in the global economy, industrial eras coexist together, there is interaction and transformation of financial systems simultaneously within the framework of Industry 4.0 and Industry 5.0. New, digital resources are entering the economy, intellectual capital is becoming virtual, artificial intelligence is increasingly finding its application in the structure of financial support. Financial intermediation in developing countries is also subject to global trends, the active development of new instruments for developing economies is especially important. The aim of the study is to identify effective ways to develop financial intermediation in Industry 5.0 for the economies of developing countries. Based on the results of the study on the development of financial institutions mediation revealed a problem related to the lack of reasonable tools that could be used to improving the efficiency of the financial intermediaries market, proposed the main directions of such a process: mobilization of savings, distribution financial assets, payment system, risk management and control over market agents involved in financial operations.

Global transformational processes associated with the geopolitical fragmentation of the world, changes in supply chains, and the emergence of threats to food, energy, logistics security, etc. have impacted the increase in the freight traffic volumes through the Ukraine-European Union (Ukraine-EU) land border section. In this context, the transport and logistics infrastructure on this section of the border was inadequate for the growing demand for international freight transport, leading to huge economic, social, and environmental damage to all participants in foreign trade. The aim of this paper is to study the efficiency of the functioning of the transport and logistics infrastructure on the Ukraine-EU border section. The taxonomy used in the paper made it possible to look into economic, security, geopolitical, logistics, transport, legal, and political factors shaping the freight traffic volumes, structure, and routes; their key trends and impact on the generation of freight traffic are described. Statistical analysis of freight traffic by border sections and with respect to border crossing points allowed the identification of bottlenecks in the functioning of the transport and logistics infrastructure and outlining ways to address them. The results of the study will be helpful both to researchers working on the issues of freight transport and to policymakers involved in transport and border infrastructure development.

Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

Islamabad’s 2019 ban on single-use plastic shopping bags aimed to reduce plastic waste, but compliance is limited. This study evaluates the effectiveness of the ban as well as other factors in curtailing plastic bag use in Islamabad. Regression modeling within a rational choice framework analyzed survey data from 406 retailers across 18 selected urban and rural markets. We found that the subjective belief that a fine was unlikely (β = −16.10; t = −3.90; p < 0.001), likely (β = −24.99; t = −4.95; p < 0.001), or very likely (β = −43.84; t = −4.07; p < 0.001) for selling bags versus very unlikely was significantly associated with lower usage. Additionally, older retailer age (β = −0.25; p < 0.001) and more education (β = −0.77; p < 0.01) were associated with lower plastic bag usage. Business registration (β = −3.94; p < 0.10) and trade membership (β = −4.04; p < 0.05) also decreased use. Rural location (zone II: β = 13.28; p < 0.001) and plastic bags stock availability (β = 16.75; p < 0.001) increased use. Awareness, viewing bags as “Good”, unlikely fines and lack of substitutes lowered use. Results provide insights to inform more effective policies for reducing plastic waste.

Governments intervene in the housing market via implementing various monetary, fiscal, foreign exchange and credit policies. By this, the housing market undergoes cycles of boom and bust as well as significant swings in value added and housing prices. Therefore, the main goal of this research is to consider the effect of the government’s change on the monetary and financial policy’s impact on the business cycles of the housing sector during the period of 1978–2020. On the other hand, we estimate the impact of monetary and fiscal policies on housing business cycles concerning government’s change. To calculate housing business cycles (boom and busts), the housing value added were initially de-trended using the Hodrick–Prescott filter. This paper takes a novel use of the threshold regression model with government’s change as threshold variable. According to the study’s findings, there are three threshold effects (two threshold levels or three regimes) of monetary and fiscal policy on housing business cycles. For instance, the money supply coefficient in the first regime was −1.68, indicating that the effect of monetary policy in this regime is countercyclical. in the second and third regimes, it was 0.19 and 0.03, respectively; indicating its alignment with the housing business cycle. Regarding the estimated models, we may derive several interesting conclusions. In first regime, the money supply is countercyclical and government expenditure is pro-cyclical. This means that monetary policy exacerbates recession and fiscal policy weakens it. in the second and third regimes, the money supply is pro-cyclical and government expenditure is countercyclical. As a result, while formulating their monetary policies, governments should give the housing sector more consideration. Additionally, when putting this policy into practice, the housing sector has to be carefully examined.