جستجوی مقالات مرتبط با کلیدواژه « efficiency » در نشریات گروه « صنایع »

Data Envelopment Analysis (DEA) is a technique used to assess performance and measure the relative efficiency of Decision Making Units (DMUs) through linear programming. In most cases, DEA models evaluate inefficient units on the boundary of the production possibility set using reference points that are not Pareto efficient. Consequently, these models often yield zero weights for multipliers, failing to justify all sources of inefficiency. This paper aims to introduce a model that generates non-zero weights.

Weight restriction methods have primarily addressed the issue of non-realistic weights. We impose constraints on the weights in the proposed model to achieve our objectives.

This paper presents a one-stage method based on the BCC model, incorporating weight restrictions, to evaluate the relative efficiency of decision-making units. The proposed model ensures non-zero weights and prevents dissimilarity between weights while maintaining feasibility. Notably, the proposed model does not require any prior information on weights or the classification of units, reducing the complexity of the problem.

Originality/Value: 

To highlight the strength of the proposed method, the model is implemented on two case studies and compared with the results obtained from standard BCC models and those of Ramon and colleagues. The results indicate the superior performance of the proposed model.

For managers, investors and creditors, it is important to be aware of the continuity of the company. To this end, financial researchers are looking for effective methods to evaluate the company's performance and predict the continuation of its activities in the coming years.

In previous research, the standard data envelopment analysis model has been used to predict corporate bankruptcy. The present study aims to provide a model of data envelopment analysis with semi-positive and negative indicators to predict the bankruptcy of companies operating in the Tehran Stock Exchange. The companies listed on the Tehran Stock Exchange constitute the statistical population of the research. To achieve this goal, a sample consisting of 40 non-bankrupt companies and 20 bankrupt companies in the years 1393 to 1397 were selected. The criterion for selecting bankrupt companies is Article 141 of the Commercial Code.

To combine tax ratios that have a more significant correlation with the financial situation of the company, the combined approach of gray relationship analysis and two-level data envelopment analysis has been used.

Originality/Value:

 First, a two-level data envelopment analysis model for semi-positive and negative indices will be developed, then the correct prediction of bankruptcy with its absence will be examined using the results of the proposed model.

Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance indicators. This is despite the fact that DEA is one of the most effective tools for measuring and evaluating efficiency. Nevertheless, identifying the relationship between efficiency estimates and commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring.

 In this paper, the DEA super-efficiency formula is tested in two profitability models. Four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, were calculated with a developed profitability model; besides, the growth rate of assets was calculated with main profitability model and all the aforementioned ratios addressed a significant association with efficiency estimates.

In this study, the DEA super-efficiency formula is tested in two profitability models for 15 banks for two years. The correlation obtained is generally low. However, the four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, in the EPM model and asset growth rate in the CPM model have a significant relationship with performance estimates. Finally, the results indicate poor credit quality in Iranian banks in 1397-1397.

In this study, for the first time, the nature of the relationship between performance and key performance indicators has been estimated. DEA technique has been used to purposefully identify criteria for analyzing financial ratios.

Implementing a credit rating system considering banks' deferred claims is one of the most important means of controlling credit risk in banks and financial institutions. In the case of banking facilities, the possibility of non-repayment of facilities is one of the most important issues. By identifying various factors that affect the non-repayment of bank facilities, it is possible to provide a framework for reducing and controlling the credit risk of banks and improving the crediting process. The purpose of this paper is to examine the relationship between efficiency and risk in the banking system.

In this research, a sample of 24 companies from the most important legal customers of 11 branches of the Melli Bank of the city of Arak has been studied. 18 variables affecting credit risk were identified in this paper. Among the variables available, 6 variables were selected using the Factor Analysis Technique and Expert judgment (Delphi method), of which 3 were inputs and 3 were formed the outputs

The efficiency and rank of legal firms were obtained with the help of Data Envelopment Analysis models, and then using the Fitch Institute's data and the efficiency of legal clients, the credit rating of each of the legal firms and their qualitative analysis was expressed.

 Accordingly, using the method of data envelopment analysis and data provided by the Fitch Ratings Institute, the credit risk of Arak's Melli Bank's legal customers is assessed and ranked

Strategy is the main source of long-term growth of organizations and if the strategy is not successfully implemented, even if the appropriate strategies are adopted, this process is useless. The purpose of this paper is to propose a comprehensive hybrid model for predicting organizational performance indicators.

In order to achieve the research goal, first, a balanced scorecard as a tool for designing performance evaluation indicators and network data envelopment analysis as a tool for performance evaluation has been used. Then, by matching the Malmquist productivity index with the mentioned hybrid model, the model of progress and regression of organizations in two consecutive periods is presented. Finally, by combining the proposed models and artificial neural networks, a solution is presented to evaluate the performance of 500 bank branches and also to identify their progress and regression.

The obtained results show good accuracy and less computational time of the proposed hybrid models.

The present study can add to the existing knowledge on performance appraisal of enterprises by providing a hybrid model using network data envelopment analysis and balanced scorecard; And the proposed methods can be promising tools for evaluating the performance of organizations, especially big data.