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Copyright of Ekonomske Ideje i Praksa is the property of Centar za Izdavacku Delatnost Ekonomskog Fakulteta u Beogradu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change, increased government efforts towards sustainable economic growth, and all types of resource constraint have raised concern among academics and practitioners about the path to follow for keeping firms' competitive advantage in such a dynamic environment. The purpose of the paper is to explore how firms operating in the agricultural sector have understood the need to identify and follow the best practitioners in the market, performing a benchmarking analysis aimed at providing insights on firms' financial sustainability. As the literature has not sufficiently addressed the problem of firms' financial sustainability operating in the Romanian Agriculture sector, we provide some empirical evidence related to the before and post-pandemic periods. The benchmarking analysis is developed using the Data Envelopment Analysis (DEA) method, which measures firms' efficiency in terms of financial performance. Overall, the results suggest there is still much work to be done, and firms operating in the agricultural sector show high variation in terms of productivity from the perspective of financial indicators. The results are even more relevant in the context of the current COVID-19 pandemic, showing that only a part of the firms analyzed have developed their own dynamic capabilities that help them effectively find solutions to adjusting to the volatility of the market in a short timeframe. [ABSTRACT FROM AUTHOR]

Environmental performance indicators are key to monitoring the sustainability of production processes. In the salmon industry, there is a growing concern about the excess of nutrients that have accumulated at the bottom of marine ecosystems and the negative externalities of those nutrients on the environment. In this paper, we measure environmental performance in the salmon industry in Chile by applying a set of data envelopment analysis (DEA) models. In these models, we incorporate pollutants as undesired outputs of the production process. Our data start in the years of the ISA virus outbreak and continue into the subsequent years of recovery in which stricter sanitary norms were implemented. All the models suggest a negative trend in both average technical and environmental efficiencies during the ISA virus outbreak and a subsequent increase in efficiency scores in the following years. A gap can be observed between environmental and technical efficiency measures, a gap that widened during the first years of the regulatory change and decreased at the end of the period. We argue that these findings offer preliminary evidence that environmental performance improved because of the new regulations. [ABSTRACT FROM AUTHOR]

It has been proven that developing urban rail transit (URT) is the key to solving the traffic problems in big cities, and transport efficiency is essential for scientific line planning and construction, operation management and sustainable development of urban rail transit. This paper focuses on the transport efficiency of the URT network and adopts shadow efficiency theory creatively to combine factors of passengers, capacity, and efficiency effectively. A quantitative calculation method of system utility based on "double time penalty" is proposed. According to the characteristics of Beijing URT, this paper puts forward a single optimization strategy and combinatorial optimization strategy and analyzes the results with DEA. The simulation of Beijing subway network proves the availability of the method and its optimization effects. [ABSTRACT FROM AUTHOR]

The article contains a regression model for assessing the average value of the efficiency of the scale of operations by leasing companies in Ukraine, which is built on the basis of DEA analysis. To determine the factors that cause a statistically significant impact on performance indicators obtained on the basis of DEA analysis, the authors use the appropriate regression models for panel data. To assess the efficiency of the scale of Ukrainian leasing companies for the analyzed period, the input-oriented DEA model with variable VRS and sustainable CRS scale effects was used. A statistical sample of the performance indicators of 21 leasing companies in Ukraine was formed, which was obtained from their financial and accounting statements for 2019-2020. Due to the significant sensitivity of SE scale efficiency to input and output variables, it was proposed to use an average scale efficiency value based on eight different DEA models. It is noted that if the CCR model determines the success of the management of a leasing company in the transformation of input resources into the output ones, then the efficiency of scale evaluates the correctness of choosing the scale of the leasing company. The analysis showed that the efficiency of the scale of the lessor’s activities in most cases depends on determinants such as administrative costs, fixed assets, and net profit of such companies. The obtained results indicate that with the increase in the size of the leasing company, the efficiency of the scale of their active operations decreases, since with an increase in the size of fixed assets and the volume of administrative costs, the average efficiency of the scale of their activities decreases. It is shown that the greater the net profit, the closer leasing companies work to the optimal scale of activity for them, which is determined by the volume of long-term receivables of the lessor and the size of his assets.

Copyright of Exacta is the property of Exacta - Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article proposed a series of input-oriented DEA (data envelopment analysis) models with variable VRS (variable returns to scale) and constant CRS (constant returns to scale) scale effects to assess the performance of Ukrainian leasing companies. Based on the obtained DEA models, an efficiency analysis of these companies scale of operation was also conducted. Performance assessments based on the DEA methodology were obtained using the Efficiency Measurement System (EMS) package. The analysis showed that the assessment of the leasing companies’ performance based on DEA models is sensitive to the choice of input and output variables. Therefore, to obtain a comprehensive assessment of efficiency, we used the average of the corresponding technical efficiency values for different sets of input and output variables. Current liquidity ratios, receivables, aggregate assets and profitability ratios, namely net income, net income and other operating income, were used as output variables in the various DEA models. The input variables were total assets, administrative expenses and other operating expenses, fixed assets and intangible assets, cost of goods sold and other expenses. It has been argued that input-oriented DEA models are more suitable for analyzing the effectiveness of the leasing business, as the management of such companies has much more capability to control inputs such as labor, costs, interest rate policy, equity, etc. than output (the amount of leasing agreements, company income, etc.). To obtain performance estimates based on DEA models, a statistical sample was formed based on the accounting and financial statements of domestic leasing companies participating in the Ukrainian Association of Lessors for 2019 and 2020. Analysis based on the obtained DEA models showed that, despite the high growth rates of leasing operations in the second half of 2020, leasing companies demonstrated a bit higher efficiency in 2019. [ABSTRACT FROM AUTHOR]

It has been proven that developing urban rail transit (URT) is the key to solving the traffic problems in big cities, and transport efficiency is essential for scientific line planning and construction, operation management and sustainable development of urban rail transit. This paper focuses on the transport efficiency of the URT network and adopts shadow efficiency theory creatively to combine factors of passengers, capacity, and efficiency effectively. A quantitative calculation method of system utility based on “double time penalty” is proposed. According to the characteristics of Beijing URT, this paper puts forward a single optimization strategy and combinatorial optimization strategy and analyzes the results with DEA. The simulation of Beijing subway network proves the availability of the method and its optimization effects.