نشریه مدیریت صنعتی
سال سیزدهم شماره 40 (بهار 1400)

Energy saving regarding its high share in energy consumption of industries has a significant impact on the growth and development of countries. This study aims to evaluate the performance of Iran's electricity generation, transmission, and distribution processes.

By using a network data envelopment analysis (DEA) model, the overall efficiency scores, and efficiency scores of production, transmission, and distribution processes are calculated. The network structure considers the main and surplus inputs (fuel consumption costs, internal consumption, transmission substation capacity, power transmission lines length, transformers capacity, low and medium voltage network length), intermediate sizes (net power generation, gross power generation, and delivered energy), desirable (nominal power, actual power, and delivered energy) and undesirable outputs (environmental pollutants, and energy losses).

An algorithm based on a multi-objective programming model is presented to evaluate network performance and simultaneously to evaluate processes efficiency. The proposed algorithm is used to evaluate 16 electricity areas in Iran.

The results showed that Tehran, Khorasan, Khuzestan, and Zanjan are the most efficient areas.

In this study, a bank loan allocation is examined in-depth with one of the methods derived from emancipatory operational research, and by conducting in-depth interviews with experts in this field, identifies the views and contradictions between them.

In order to deeply review with a critical approach, this process of perceiving and reflecting the (hidden) views of stakeholders using 12 border questions in the form of 2 "Is" states in terms of facts and what is now and "ought to be" state. It explores the concept of values and what should ideally exist.

According to the findings, the banking decision-makers' approach should be turning to create shared value, changes in the obsolete banking statute seem necessary, and the central bank system should be working independently. Furthermore, unconventional powers of government and governance have caused injustice in the allocation of loans, and despite the existence of multiple grievance systems, the response to the complaints is too slow. Besides, some sub-systems also have significant weaknesses: credit rating, management evaluation system, the authority of provincial and regional managers, the customer evaluation system, the allocation of credit, and scientific and technological support teams.

This study's results provide suggestions arising from the exploration and understanding of stakeholder boundary judgments (initial judgments about the system and an overview of it) to redesign and implement critical changes in Iran's bank loan allocation system.

Nowadays, the capital market is considered an important source of financing for companies and if a suitable model for portfolio selection by considering different preferences of investors is designed, the existing capital can be directed to this market and support domestic products. This study develops the Markowitz model to consider the non-financial preferences of investors in addition to financial indicators.

Range Adjusted Measure (RAM) and Conditional Value at Risk (CVaR) model on Cross-efficiency were applied respectively to measure the Corporate Social Responsibility (CSR) score and risk, and then the multi-objective portfolio optimization model was proposed using the LP-Metric method.

Single-objective and multi-objective models (LP-Metric) with different powers were implemented in GAMS software. Examining the performance of these models using the Sharpe ratio showed that the single-objective models of maximizing returns and minimizing risk have the highest performance and the single-objective model of maximizing social responsibility have the lowest performance, respectively. The proposed model also meets at least 74.5 percent of the triple and contradictory goals according to the Sharpe ratio.

While the proposed model optimizes the three objective functions simultaneously and establishing a trade-off between these conflicting goals, has obtained a good Sharpe score compared to other models and market portfolio and a suitable portfolio on a Pareto Front has been selected and introduced among the companies with maximum return and minimum risk that have a high score of social responsibility, and if the model is applied with more powers, it will provide more companies and scenarios to investors.

The purpose of this study is to develop and improve the multilayer fuzzy cognitive maps in structuring and analysis of problems with high dimensions by providing a quantitative framework.

In this study, the Self-Organizing Map method and Graph Theory and Matrix Approach has been combined in the multilayer fuzzy cognitive maps approach. Based on this approach, problem structuring is done by clustering and creating a multilayer structure for cognitive mapping.

The developed method in the present study has been used to analyze the problem of sustainable supply chain management achievement in the petrochemical industry. According to the results of data analysis based on the presented approach, "cooperation in the supply chain", "organizational development" and "management commitment to sustainable development" are the most effective factors in enabling sustainable supply chain management.

Based on the method presented in the present study, the problem is modeled by clustering components and creating a multilayer structure for cognitive mapping. The method presented in the present study can model problems with a large number of intervening variables. The proposed method in this study can model problems with a high number of variables.

The main purpose of this research is to develop a scenario-based model to deal with the design and planning decisions of supply chain networks considering uncertainty in both quantity and quality of the returned products at their end of life era.

In this approach by the help of scenarios and operation research, a mixed-integer linear programming model is applied and profit maximization is chosen to be the target of this model which integrates multi - products and multi - periods of times with different time horizons. In this model, several flows of products between entities like factories, storages, distribution/recycling/disposal centers and costumers have been taken into account that is according to the variety of entities in the network. The uncertainty associated with the quantity and quality of the used products in the reverse network which is directly affected by customers’ usage and sorting results in recycling centers, respectively, have been taken into account as the main cause of the uncertainty.

Of the main findings of this research which was the applicability of these kinds of approaches in real case problems, have been approved in an acceptable time and has shown that this approach can be used in cases with mathematical functions predicting their uncertainty behavior.

Finally, the model is deployed in Steel industry of Iran with real data from factories and market to examine the model in utilizing potential locations for different entities by considering the costs, especially the lost costumers. As predicted, increase in quality of return will reduce the need for raw material and as a result, will increase the profit of the entire chain and increase in the quantity of returned might need to build more entities that would reduce the profit of the entire chain and even unprofitable at all.

Risk management in organizations is a major process, one of the sub-processes of which is the risk assessment. The simplest assessment methods have introduced risk as a function of the probability of occurrence and the severity. Using this definition, various methods for risk assessment have been developed. The development of these methods has introduced an indicator called the total efficient risk priority number (TERPN) in which more effective factors were considered to determine the importance of the risks. In addition to its many advantages, this indicator has limitations that if they are handled, it can have better performance in terms of effectiveness and efficiency, and the present study aims to eliminate these limitations.

The proposed method is a step-by-step process consisting of 11 for risk assessment in which after identifying risk areas, risks, corrective and, preventive measures the process is performed using a combined method with data envelopment analysis.

To validate the proposed method with a sample example, it was found that this method selects risks that, based on both the TERPN index and the proposed index, causes a further reduction in the level of intolerable risks by 3.8%. Regarding the cost of corrective and preventive measures, it can be seen that based on the prioritization of the proposed method, the cost will be reduced by about 26.8% compared to the former method.

In order to evaluate the risk, in addition to maintaining the positive features of the TERPN method, this research method eliminates the limitations and in the major implementation of the risk management process, it is possible to achieve a higher level of productivity (effectiveness and efficiency).

The purpose of this paper is to evaluate the efficiency of decision-making units using the goal programming model of data envelopment analysis with restriction weight and ranking of units with a unique method in Ghavamin Bank.

In this study, the classical CCR model was used to determine the management efficiency of provincial branches in Ghavamin Bank. To increase the discriminative power of efficient and inefficient decision-making units, a combination of goal programming models with Weight restriction was used and a new model called goal programming of data envelopment analysis with Weight restriction was presented.

Based on the output values of the classical CCR model, 16 out of 32 decision-making units became efficient and 16 units became inefficient. In the next step, for more separability of the units, the goal programming model of data envelopment analysis with Weight restriction was used. The results of the first-order Euclidean norm became 7 efficient and the rest inefficient out of 32 decision-making units, and the results of the infinite Euclidean norm became 1 of 32 efficient units and the rest of the decision-making units inefficient.

The results showed that the goal programming model of data envelopment analysis with Weight restriction related to infinite Euclidean norm in separating and ranking efficient decision-making units from inefficient has a high discriminate power compared to the classical CCR model and the first-order Euclidean norm.