Weather is almost inevitable and plays an important role in determining the duration of construction projects. The construction industry ultimately thrives upon the physical input, put in by the labours. The majority of the construction projects are executed in the outdoor environment and hence face a high impact of weather conditions. This study therefore evaluated the influence of weather conditions on construction workers’ productivity in Jos, Plateau State and proceeded to make recommendations geared towards the improvement of construction workers’ productivity in Jos. The study was conducted through the direct observation method. Three hundred and ninety-six (396) works were purposively sampled in selected working sites. The outcome shows that during dry weather, there was considerably less significant productivity of manual excavation. In contrast, a large increase in blockwork and plasterwork productivity was observed with a percentage difference of 33%, 56.3% and 61%, respectively. On the other hand, during wet weather conditions, the labour productivity for manual excavation increases, whereas it decreases for block work and plasterwork with percentages difference of 58%, 40% and 47%, respectively. Besides, relative humidity and wind speed have no impact on labours’ productivity in dry and wet weather. Besides, the temperature has the most decisive impact on workers’ productivity. Moreover, wind speed and humidity have a lower influence on workers’ productivity. The construction industry stakeholder in Jos, Nigeria, would benefit from this study’s recommendations for reducing the influence of weather on the building sector. Besides, the output can be extended to other regions having similar characteristics.

In this paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instead of a couple of features. Information aggregation necessarily leads to information loss, at least to a specific extent. Whether we concentrate on extreme values or middle terms, there can be cases when the most important piece of the puzzle is missing. Although the simple or weighted mean considers all the values there is a drawback: the values get the same weight regardless of their magnitude. One possible solution to this issue is the application of the so-called Ordered Weighted Averaging (OWA) operators. This is a broad class of aggregation methods, including the previously mentioned average as a special case. Moreover, using a proper parameter (the so-called orness) one can express the risk awareness of the decision-maker. Using real-life statistical data, we provide a simple model of the decision-making process of insurance companies. The model offers a decision-supporting tool for companies.

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.

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.