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Keywords = total assets turnover (TAT)

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16 pages, 625 KiB  
Article
Artificial Neural Network for Classifying Financial Performance in Jordanian Insurance Sector
by Rania Al Omari, Rami S. Alkhawaldeh and Jamil J. Jaber
Economies 2023, 11(4), 106; https://doi.org/10.3390/economies11040106 - 29 Mar 2023
Cited by 8 | Viewed by 2833
Abstract
Over the past few decades, financial performance has attracted researchers’ attention, especially in the insurance sector. Insurance is a tool for the growth and sustainability of both rising and developing economies. It promotes economic stability for people, organizations, and governments by taking on [...] Read more.
Over the past few decades, financial performance has attracted researchers’ attention, especially in the insurance sector. Insurance is a tool for the growth and sustainability of both rising and developing economies. It promotes economic stability for people, organizations, and governments by taking on risk and spreading it across the market. We intend to classify insurance companies’ financial performance in Jordan’s Amman Stock Exchange (ASE). The sample size is 15 out of 22 selected insurance firms from 2008 to 2020. We apply the Multi-Layer Perceptron (MLP) model for the detection of (high/low) total asset turnover (TAT) as output, while we select the subrogation (SB), claims paid (CP), market capitalization (MC), and total shareholders’ equity (SE) as input to the MLP model. The performance of the MLP model is evaluated using different criteria, namely the false positive rate (FP rate), false negative rate (FN rate), F-measure, precision, and accuracy (ACC). The results show that MLP is efficient and performs well in multiple criterion tests through iteration growth. Based on our knowledge, the paper assesses the financial performance of Jordanian insurance firms, which has not been investigated previously. Furthermore, this study gives valuable information to regulators and policymakers to improve asset management efficiency in the insurance sector. Full article
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22 pages, 1615 KiB  
Article
Determinants of Return-on-Equity (ROE) of Biogas Plants Operating in Poland
by Dariusz Kusz, Iwona Bąk, Beata Szczecińska, Ludwik Wicki and Bożena Kusz
Energies 2023, 16(1), 31; https://doi.org/10.3390/en16010031 - 21 Dec 2022
Cited by 10 | Viewed by 4252
Abstract
Poland has a large potential for biogas production from agricultural sources and food waste. This potential is still poorly used. There are many reasons for this state of affairs. We can indicate both the policy of the state towards renewable energy sources (RES) [...] Read more.
Poland has a large potential for biogas production from agricultural sources and food waste. This potential is still poorly used. There are many reasons for this state of affairs. We can indicate both the policy of the state towards renewable energy sources (RES) with a small amount of energy from biogas contracted at auctions, investment risk, and especially low return on investment in the absence of investment support. An important reason is also the limited state budget. The purpose of this work was to determine the endogenous factors that determine ROE, the direction of the impact of these factors, as well as the strategy of biogas plants in shaping the ROE level. The DuPont model was used in the analysis of ROE changes. We used the deviation method to determine the impact of the various factors on ROE. Against the background of the energy sector in Poland, the value of ROE in the examined biogas plants should be considered satisfactory, and in 2020 it was, on average, 13.9%. The decrease from 17.2% in 2019 occurred despite the increase in energy prices and the increase in the net profit margin (NPM). It resulted from the reduction of ROE’s financial leverage through external capital. A high level of debt characterized the examined biogas plants, and the pursuit of risk reduction and debt reduction negatively impacts on ROE. This may indicate the need for state investment support at the plant construction stage or low-interest investment loans to develop biogas plants. In addition, using only price guarantees under the feed-in tariffs, with dynamic changes in costs, may bring the industry a relatively high investment risk compared to other RES, where the operational costs during the lifetime are low, as it is in PV or wind systems. Full article
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