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.
The role of technology in stimulating economic growth needs to be reexamined considering current heightened economic conditions of Asian developing Economies. This study conducts a comparative analysis of technology proxied by R&D expenditures alongside macroeconomic variables crucial for economic growth. Monthly time-series data from 1990 to 2019 were analyzed using a vector error correction model (VECM), revealing a significant impact of technology on the economic growth of India, Pakistan, and the Philippines. However, in the cases of Indonesia, Malaysia, Thailand, and Bangladesh, macroeconomic indicators were found more crucial to their economic growth. Results of Granger causality underlined the relationship of R&D expenditures and macroeconomic variables with GDP growth rates. Sensitivity analyses endorsed robustness of the results which highlighted the significance and originality of this study in economic growth aligned with sustainable development goals (SDGs) for developing countries.
The role of agriculture in greenhouse gas emissions and carbon neutrality is a complex and important area of study. It involves both carbon sequestration, like photosynthesis, and carbon emission, such as land cultivation and livestock breeding. In Shandong Province, a major agricultural region in China, understanding these dynamics is not only crucial for local and national carbon neutrality goals, but also for global efforts. In this study, we utilized panel data spanning over two decades from 2000 to 2022 and closely examined agricultural carbon dynamics in 16 cities of the Shandong Province. The method from the Intergovernmental Panel on Climate Change (IPCC) was used for calculating agricultural carbon sinks, carbon emissions, and carbon surplus. The results showed that (1) carbon sink from crops in the Shandong Province experienced growth during the study period, closely associated with the rise in crop yields; (2) a significant portion of agricultural carbon emissions was attributable to gastrointestinal fermentation in cattle, and a reduction in the number of stocked cattle led to a fall in overall carbon emissions; (3) carbon surplus underwent a significant transition in 2008, turning from negative to positive, and the lowest value of carbon surplus was noticed in 2003, with agriculture sector reaching the carbon peak; (4) the spatial pattern of carbon surplus intensity distinctly changed before and after 2005, and from 2000 to 2005, demonstrating spatial aggregation. This research elucidates that agriculture in Shandong Province achieved carbon neutrality as early as 2008. This is a pivotal progression, as it indicates a balance between carbon emissions and absorption, highlighting the sector’s ability in maintaining a healthy carbon equilibrium.
This study analysed the behaviour of both economic and financial profitability of credit unions belonging to segment 1 in Ecuador, as well as its determinants. For this purpose, data from the financial statements of a sample of 30 credit unions between 2016 and 2022 were used by means of a multiple linear regression methodology using panel data with fixed effects after applying the Hausman test. The findings of this research showed that current liquidity and non-performing loans have a negative and significant effect on both economic and financial profitability while the past due portfolio has a positive and significant impact on the generation of profitability of the financial institutions under study. In addition, it was revealed that the rate of outflow absorption has a negative relationship with economic profitability but a positive relationship with financial profitability. Unlike previous research in the Ecuadorian context, this research is pioneering in presenting results that indicate that the determinants traditionally considered for nonfinancial institutions and banks are also valid for credit unions, even though they are organisations with different characteristics from the rest.
Poverty is a key challenge to socioeconomic development globally. However, the degree to which distance from a market contributes to poverty remains unclear. To provide insights into this relationship, we quantified the relationships between distance from markets and the per capita income of rural and urban people in China based on data from 29 provinces and 2651 counties. Our results illustrate the existence of a “geographical curse”; that is, a large separation between producers and consumers can exacerbate poverty for less-affluent rural residents, who pay a larger proportion of their income to send their products to market and to purchase goods from those markets. Programs to alleviate poverty should therefore consider seeking solutions associated with reducing the impact of that distance, such as subsidizing the transport of goods, improving the transportation infrastructure, supporting innovative business practices, and balancing the locations of producers and their markets.
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