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The increase in household wealth, observed at the beginning of the 21st century in Poland, results in dynamic development of sport infrastructure. Playing fields, bicycle paths, swimming pools and recreation centers emerge in publicly accessible places. This generates great demand for sports equipment, which is also fostered by the sport successes achieved by Polish athletes in many disciplines. The subject of this study entails the profitability threshold of an enterprise selling sports equipment on the Internet. Profitability threshold is an enterprise characteristic that does not belong to the categories analyzed via econometric tools. The literature, therefore, lacks studies addressing empirical determination of profitability threshold in an enterprise. This necessitates a model comparison of the company's total costs against the sales revenues. The purpose of this article is to describe the variability mechanism of the total costs in an enterprise, using a stochastic econometric model. Sales revenues have been included in the model equation. This will allow to determine the level of the company's fixed costs as well as calculate the increase in the variable costs the per revenue unit. Positive verification of the empirical model allowed indication of the sales revenues level at which the total costs are covered. This requires comparison of an empirical equation of the cost with a hypothetical equation that assumes equal costs and revenues. By solving such a system of equations, the company's profitability threshold is obtained. Exceedance of the profitability threshold results in the appearance of profit in an enterprise. A procedure for determining the dynamic profitability threshold of an enterprise has been presented as well. This procedure is necessary when a trend occurs in the empirical equation of the total costs. Information on the profitability threshold becomes an important decision-making tool in an enterprise. It indicates the point at which profit on sales can be expected in a period under observation. Additionally, it suggests the use of marketing tools that allow the company to exceed the profitability threshold.

The main objective of this study is to compute margin of safety of hiring decision of agricultural machinery services in Iraq. A cost-volume-profit analysis by using breakeven point technique has been followed to find out the margin of safety by using cross- section data in rice production farms in Alnajaf province. Results showed that the break-even point for different types of original agricultural field machinery were 427, 6.5, and 221 hours for tractor and machinery of soil preparation, farm sprayer, and combine harvester, respectively, while the values of break-even point for different types of used agricultural field machinery were 309, 10, and 319 hours for tractor, farm sprayer, and combine harvester, in that order. Results also pointed out that the negative sign of safety margin of areas of all machineries indicated that there are losses faced by small scale farmers in case of ownership these machineries, and the minimum lose amounted about$ 316116 for original tractor, $52611 for used tractor,$ 220.5 for original farm sprayer, $88 for used farm sprayer,$ 664664 for original combine harvester and $584650 for used combine harvester. The study recommended that it is useful for small scale farmers in Alnajaf province to continue hiring various agricultural machinery services rather than purchase them due to the absence of safety margin of holding areas. Therefore machine stations of agricultural machineries services maybe developed by Iraqi government in the study region to provide these services to the farmers with supported prices.

The effects of the world economic and financial crisis, which began in 2007 and is still in progress, has made increasingly sharp the line of demarcation between those able to access home ownership on the free market, and those unable to do so. For the European Union’s member states, Social Housing (SH) policies include all the initiatives aimed at providing housing support for all the weak segments of the population; these policies have declined differently by different Member States according to their specific needs. In Italy, the growing need for SH accommodation together with the shortage of public resources makes developing forms of Public–Private Partnership (PPP) necessary. Evaluation techniques like Break-Even Analysis and Contribution Margin Analysis are useful in planning interventions including SH initiatives in the context of real estate development or retraining initiatives in PPP (in negotiation processes or in project financing). These kinds of techniques especially allow evaluation of public and private convenience in PPP. In the present work, an assessment procedure has been structured: first the main parameters of a settlement of SH initiative in PPP are defined; subsequently, it is possible to assess the feasibility and the financial balance of the initiative itself. The procedure has been applied to a case study: the interrupted initiative of self-renovation in Via Grotta Perfetta 315 in Rome (Italy).

This book is a comprehensive collection of cost-volume-profit applications. Business professionals, entrepreneurs, business professors, and undergraduate and graduate business students will benefit from this onestop how-to book of formulas, explanations, and examples. The user will find a wide range of topics, from calculating basic breakeven, to dealing with multiple products, mixed costs, changing costs, and changing prices.

While public reports exist about hardwood log and lumber prices, sawmills’ operating costs are proprietary, and few records are publicly available. Operating costs make up a considerable share of a sawmill’s cost structure and are, therefore, crucial for understanding the fiscal health of a given operation. Using the assumption that today’s depressed lumber and residue markets result in sawmills, on average, making no profit and incurring no loss, this study estimated operation costs of a hypothetical 4, 8, and 12 MMBF production hardwood sawmill in the eastern United States producing red oak lumber. Using this knowledge and the Log Recovery Analysis Tool (LORCAT), this study found that a sawmill’s financial well-being is highly dependent on hardwood log and operating costs as well as lumber prices. A 0.1% change in any of these factors will lead to a statistically significant change in profit for a sawmill. For example, with a 12 MMBF/year production sawmill, a 0.1% increase in operating cost would reduce profit by$4,510 but would increase profit $ 4,536 with an operating cost decrease of 0.1%. Similar observations can be made for log cost while lumber prices contribute even more to the volatility of the financial well-being of a sawmill.

Using retroactive disclosures required by Statement of Financial Accounting Standards (SFAS) No. 131, we examine managers' incentives for withholding segment information under SFAS No. 14 and the impact of SFAS No. 131 on analysts' information environment for a sample of firms that previously reported as single-segment firms and initiated segment disclosure with SFAS No. 131. We examine this set of firms because they likely had the strongest incentives to withhold segment information and analysts potentially had the most to gain when these firms were forced to begin providing segment disclosures under SFAS No. 131. We find that these firms used the latitude in SFAS No. 14 to hide profitable segments operating in less competitive industries than their primary operations. However, we find no evidence to suggest that these firms used the latitude in SFAS No. 14 to mask poor performance. In contrast, our results suggest that by withholding segment information, these firms allowed themselves to appear as if they were underperforming their competition when this was not the case. Thus, their decision to withhold segment disclosures under SFAS No. 14 appears to be motivated by a desire to protect profits in less competitive industries. In terms of the impact of SFAS No. 131 on analysts' information environment, our evidence suggests that SFAS No. 131 increased analysts' reliance on public data, but we provide weak evidence to suggest that this shift may have come at the cost of a marginal increase in overall uncertainty and squared error in the mean forecast.

We exploit the change in U.S. segment reporting rules (from SFAS No. 14 to SFAS No. 131) to examine two motives for managers to conceal segment profits: proprietary costs and agency costs. Managers face proprietary costs of segment disclosure if the revelation of a segment that earns high abnormal profits attracts more competition and, hence, reduces the abnormal profits. Managers face agency costs of segment disclosure if the revelation of a segment that earns low abnormal profits reveals unresolved agency problems and, hence, leads to heightened external monitoring. By comparing a hand-collected sample of restated SFAS No. 131 segments with historical SFAS No. 14 segments, we examine at the segment level whether managers' disclosure decisions are influenced by their proprietary and agency cost motives to conceal segment profits. Specifically, we test two hypotheses: (1) when the proprietary cost motive dominates, managers tend to withhold the segments with relatively high abnormal profits (hereafter, the proprietary cost motive hypothesis), and (2) when the agency cost motive dominates, managers tend to withhold the segments with relatively low abnormal profits (hereafter, the agency cost motive hypothesis). Our results are consistent with the agency cost motive hypothesis, whereas we find mixed evidence with regard to the proprietary cost motive hypothesis.

The directional distance function encompasses Shephard's input and output distance functions and also allows nonradial projections of the assessed firm onto the frontier of the technology in a preassigned direction. However, the criteria underlying the choice of its associated directional vector are numerous. When market prices are observed and firms have a profit maximizing behavior, it seems natural to choose as the directional vector that projecting inefficient firms towards profit maximizing benchmarks. Based on that choice of directional vector, we introduce the directional profit efficiency measure and show that, in this general setting, profit inefficiency can be categorized as either technical, for firms situated within the interior of the technology, or allocative, for firms lying on the frontier. We implement and illustrate the analytical model by way of Data Envelopment Analysis techniques, and introduce the necessary optimization programs for profit inefficiency measurement.

Decisive applications, such as control systems and aerial navigation, require a standby system to meet stringent safety, availability, and reliability. The paper evaluates the availability, reliability, and other measures of system effectiveness for two stochastic models in a symmetrical way with varying demand: Model 1 (a two-unit cold standby system) and Model 2 (a two-unit hot standby system). In Model 1, the standby unit needs to be activated before it may begin to function; in Model 2, the standby unit is always operational unless it fails. The current study demonstrates that the hot standby system is more expensive than the cold standby system under two circumstances: a decrease in demand or the hot standby unit’s failure rate exceeding a predetermined threshold. The cold standby system’s activation time is at most a certain threshold, and turning both units on at once is necessary to handle the increasing demand. In that case, the hot standby will be more expensive than the cold standby system. The authors used semi-Markov and regenerative point techniques to analyze both models. They collected actual data from a cable manufacturing plant to illustrate the findings. Plotting several graphs and obtaining cut-off points make it easier to choose the standby to employ.

In recent years, the utilization of renewable energy sources has significantly increased due to their environmentally friendly nature and sustainability. Among these sources, wind energy plays a critical role, and accurately forecasting wind power with minimal error is essential for optimizing the efficiency and profitability of wind power plants. This study analyzes hourly wind speed data from 23 meteorological stations located in Türkiye’s Western Black Sea Region for the years 2020–2024, using the Weibull distribution to estimate annual energy production. Additionally, the same data were forecasted using the Long Short-Term Memory (LSTM) model. The predicted data were also assessed through Weibull distribution analysis to evaluate the energy potential of each station. A comparative analysis was then conducted between the Weibull distribution results of the measured and forecast datasets. Based on the annual energy production estimates derived from both datasets, the revenues, costs, and profits of 10 MW wind farms at each location were examined. The findings indicate that the highest revenues and unit electricity profits were observed at the Zonguldak South, Sinop İnceburun, and Bartın South stations. According to the LSTM-based forecasts for 2025, investment in wind energy projects is considered feasible at the Sinop İnceburun, Bartın South, Zonguldak South, İnebolu, Cide North, Gebze Köşkburnu, and Amasra stations.