alireza alinezhad

Regional justice, disenfranchisement and sustainable development and reducing the gap between the rich and the poor were among the ideals of the Islamic Revolution, which, despite significant progress, are still considered important issues in the society. Sustainable development is one of the most important strategies of the regional planning system, which has received much attention in recent decades. Sustainable regional development, considering access to natural resources, is proposed in the area of economic and social development of the region. So that the economic development of the region should remain at a level that does not exceed the environmental capacity of the region and lead to the improvement of the quality of human life. This research seeks to identify the sustainable development policies of the deprived areas of Delfan with regard to the available financial resources based on the dynamics of the regional sustainable development system.

This study is an application of system dynamics in sustainable development policies of deprived areas. The system dynamics (SD) is for the purpose of modeling complex systems in order to understand and recognize the situation of the problem for the policy makers and to test and ensure the effectiveness of the proposed policies. Therefore, this study has designed the dynamic model of the sustainable development system of deprived areas and simulated the development of the deprived area of Delfan in a ten-year horizon with the participation of regional development planners in order to identify deprivation policies.

After examining the issue of regional sustainable development and policies to reduce poverty in the deprived and less developed regions of the country, with the participation of the beneficiaries of Delfan regional development in Lorestan province, the issue of sustainable development of the deprived region in three economic subsystems and infrastructures sustainable development of deprived areas, social subsystem of sustainable development of deprived areas and environmental subsystem of sustainable development of deprived areas were identified. The economic subsystem and infrastructures of sustainable development of the deprived area deals with the financial flow of deprivation removal resources and its expenses in the infrastructures. The financial resources for the removal of deprivation in Delfan region, according to the financial resources available to the institution of deprivation removal, are government financial resources and the participation of private sector investors. In accordance with the situation of the deprived area of Delfan and considering the capacities of natural resources, economic investments and entrepreneurship were considered in three sectors of agricultural and animal husbandry entrepreneurship development, tourism service entrepreneurship development and mining entrepreneurship development. Considering the creation of job opportunities and employees in different sectors, the amount of household income and the amount of urban and rural poverty in the region were considered. The social subsystem of the sustainable development of the deprived area deals with the dynamics of the urban and rural population and migration and unemployment and the active workforce in the agriculture and animal husbandry sectors, tourism services and mines. The subsystem of natural resources and environment of the region focuses on the protection of lands, pastures and forests and water resources with regard to economic development. According to the subsystems of the model and the identified factors and relationships of each subsystem, the causal model was designed and the intensifying and moderating loops of the problem were explained.

According to the results of the sensitivity analysis of the model, economic sustainability strategies in the two policy categories of civil infrastructure development and investment in agriculture, tourism services and industry and mining; Social sustainability in four policy categories promotion of public awareness, entrepreneurship development, community-oriented empowerment and encouraging policies for entrepreneurship development and environmental sustainability in three policy categories of adherence to environmental requirements, sustainability of water resources and sustainability of soil resources was identified. In the following, by applying separate and combined strategies according to available financial resources; The behavior of model variables was investigated and compared. The implementation of selected policies shows that by spending financial resources of about 6 thousand billion rials in the region during three years by the institution of deprivation reduction and also the participation of the governorate and other executive bodies of Lorestan province in the development of the region's infrastructure and private sector participation in economic development investment; The increasing trend of urban and rural poverty will decrease after a five-year delay by preserving arable lands, pastures and forests, and the effects of poverty and deprivation will disappear permanently in the region. The proposed applied model of system dynamics in the policy of sustainable development of deprived resions and its efficiency is presented in the deprived resion of Delfan.

Today, all the countries of the world are trying to pay attention to the role of higher education in national development and promotion of knowledge and technology. In fact, it can be said that one of the most valuable resources that society has for progress and development is education. Higher education is actually one of the most effective mechanisms of any country to deal with the biggest challenges of this century.The main goal of this research was to identify dimensions and components for evaluating higher education policies. The current research is an applied-developmental research and its method is mixed exploratory (qualitative and quantitative), which uses the qualitative strategy of thematic analysis to analyze and analyze data and count factors and indicators, and quantitative statistical methods are used to rank them. The data were extracted from document review and related literature and in-depth semi-structured interviews. Interviews with 13 experts in the field of higher education and policy making were conducted in a targeted manner until the stage of theoretical saturation. For validation, three procedures of coding test itself, use of independent coders, and receiving feedback from the interviewees were used. For data analysis, concepts were extracted in three stages. Based on this, 8 relational codes (overarching theme), 26 interpretive codes (organizing theme) and 105 descriptive codes (basic theme) related to the evaluation of higher education policies were identified and extracted and ranked using Friedman variance analysis. The results of the research showed that the components of "educational and cultural factors, legal factors and legal institution" are among the most important effective components in the evaluation of higher education policies, and among them, educational and cultural factors have the first priority.

Today, due to the expansion of organizational competition, the growth of technology, and the increasing demand for customers, organizations that gain a competitive advantage over competitors by adopting scientific strategies can survive. There are various approaches to create a competitive advantage in organizations. On the other hand, in the scientific literature of this field, there is no integrated model that can cover the gap between these approaches. The aim of this paper is to present a new hybrid model for determining organizational competition strategies and criteria through decision-making tools. In this research, brands of dairy products listed in Iran were selected as a case study to demonstrate the application of the methodology. First, competitive strategies were determined through the Delphi method and expert judgment based on the SWOT technique. Then, relying on the SWOT technique, appropriate evaluation criteria were extracted through the fuzzy DEMATEL method. In the next step, each brand was considered as a decision-making unit (DMU). In addition, the output of the fuzzy DEMATEL method formed the initial values (inputs-outputs) of data envelopment analysis (DEA). Finally, after determining DEA weights via analytic network process (ANP), the efficiency of DMUs was measured by the Russell DEA model. The results of DEA showed that based on the strategies of the SWOT technique, 38% of the units under investigation are efficient. Also, the lowest efficiency obtained from the units was 82%, which shows that there is no noticeable dispersion in the efficiency values. In other words, it shows that the performance of all brands of dairy products is at a suitable level. The rest of the results and discussion are presented in detail. Analysis shows that the model of this research can be a suitable model for survival in today’s tight organizational competition in the world.

In light of recent advancements in the modern world, multivariate-multistage quality control patterns are increasingly recognized as vital and indispensable in manufacturing industries. This study delves into the significance and necessity of multivariate-multistage quality control in manufacturing, specifically focusing on motor oil production. As a foundational factor, motor oil quality considerably influences engine performance, lifespan, customer satisfaction, and market positioning.

This research employs deep learning algorithms for monitoring and fault detection in quality components. The primary rationale for opting for deep learning algorithms over conventional statistical methods is the non-normal distribution of data and the large sample sizes, which can lead to inaccurate estimations and unstable analyses. Conversely, the unique capabilities of deep learning algorithms in handling complex data and extracting meaningful features from extensive motor oil production data justify their selection. To bolster accuracy and effective quality control, a combination of deep learning algorithms is utilized, including Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNN), and hybrid models such as LSTM-CNN, as well as Residual Networks (ResNet) with Dense Networks (DenseNet). The LSTM-CNN algorithm is applied to control numerical quality variables and identify temporal and sequential patterns in the data. Meanwhile, ResNet-DenseNet manages and analyzes visual data with non-uniform and intricate distributions.

By integrating LSTM networks, CNNs, and residual connections, these algorithms excel at extracting meaningful features and capturing complex relationships within the data. This enhances performance and efficiency in quality control processes and facilitates intelligent decision-making. Such an approach is adept at uncovering latent patterns and intricate relationships between variables and quality attributes, enhancing quality control procedures and intelligent decision-making. The amalgamation of these algorithmic capabilities enhances the efficacy of quality control processes, outperforming single-algorithm approaches. Additionally, the Bee Colony Clonal Algorithm (BCC) is employed to fine-tune the parameters of the LSTM-CNN and ResNet-DenseNet algorithms. This hybrid approach harnesses the Artificial Bee Colony (ABC) and Genetic Algorithm (GA) strengths, markedly improving the performance of deep learning algorithms in quality control and reducing the time required to achieve desired outcomes. To illustrate the practical applicability of the proposed algorithms, a case study in the motor oil production industry is examined. The proposed LSTM-CNN hybrid algorithm in fault detection demonstrated superior results compared to standalone CNN and LSTM algorithms, achieving performance improvements of approximately 15% and 8%, respectively. Furthermore, the proposed ResNet-DenseNet hybrid algorithm exhibited higher accuracy in visual components, enhancing performance by approximately 10% and 15% compared to ResNet and DenseNet algorithms, respectively.

From both academic and practical standpoints, this research scrutinizes deep learning algorithms' influence on enhancing motor oil quality and efficiency. Advanced data analysis methods, particularly hybrid deep learning algorithms, are employed to identify quality patterns in production data.

In this paper, heat transfer and fluid flow around a solid cylinder wrapped with a porous layer in the channel were studied numerically by computational fluid dynamics (CFD). The homogeneous concentric and eccentric porous medium round a rigid, solid cylinder are supposed at local thermal equilibrium. The transport phenomena within the porous layer, volume averaged equations were employed, however the conservation laws of mass, momentum and energy were applied in the channel. The main purpose of this study is analyzed and compared the heat flux of concentric and eccentric porous layer in Reynolds number range of 1 to 40 and Darcy numbers of 10-2 to 10-6. It is found that with the decline of Darcy number, the vortex length is increased behind the solid cylinder surface. In addition, the heat flux rate of the cylinder is raised with the increase of Reynolds number. Finally, the results showed that the average Nusselt numbers in different Darcy and Reynolds numbers are higher in the eccentric porous layer than in the concentric porous layer. For example, our findings show that in Da=〖10〗^(-5), Re=40 and d=0.07 m, the average Nusselt number in the eccentric porous layer is 7.5% higher than the concentric porous layer.

In recent years, many studies have been conducted about how to select a sustainable supplier so different methods have been proposed for this rigard in fuzzy and deterministic environments. In this article a new model of BWM improved using Rough Sets Theory for Sustainable Supplier Selection (SSS) in the supply chain. One of the advantages of the proposed method is modeling the uncertainty related to personal evaluations and zeroing the subjective judgment error of the decision maker, using the decision table approach. Also, using the concept of conditional entropy in rough sets, the significance of criteria is calculated and the selection of the best and the worst criterion, as well as making pairwise comparisons in the best-worst method, is done respectively. Using this approach, the inconsistency ratio of the best-worst method becomes zero in all stages. Moreover TOPSIS and SAW methods have been used to determine the weight of suppliers and the results have been compared. To illustrate the model and demonstrate its capability, a real SSS case in Iran Khodro Company (IKCO), was examined by three experts in the automotive industry. The results show that the first supplier (ISACO Parts Supply Company) is the best sustainable supplier.

Around the world, various strategies are used to evaluate policies and reduce the problems and immorality caused by the flawed implementation of policies. The main purpose of this study was to identify the dimensions and components and to present a model for evaluating higher education policies based on the general policies of the system in the field of education. The present study is a basic research of its descriptive-analytical method. Data were extracted from related literature and literature and in-depth semi-structured interviews. Interviews were conducted with 13 experts in the field of higher education and policy-making in a purposeful manner until the stage of theoretical saturation. Independent coders were used to receive feedback from the interviewees.To analyze the data, concepts were extracted in three stages. Accordingly, 8 relational codes (inclusive theme), 26 interpretive codes (organizing theme) were identified and extracted from 106 descriptive codes (basic theme) related to the evaluation model of higher education policies based on the general policies of the system in the field of education... To be more confident and do a little method to validate the proposed model, in a wider circle and with more people who are experts, experts and stakeholders in the field of higher education, this section was done and finally using LISREL software The results of the data became useful and purposeful information in order to answer the main questions of the research.

This research intendes to investigate the moderating factors in the successful implementation of the procurement policy in Iran’s state-owned banks.

The research method was applied in terms of purpose and regarding data collection method, it was quantitative. The statistical population included all managers and experts in charge of procurement departments in eight state-owned banks using the country's public procurement policies. The sample size was composed of 151subjects. The researcher-made questionnaires were distributed among the participants after checking validity and reliability; meanwhile, stratified random sampling technique was applied to select the sample.

Path analysis shows that proper structure, effective management, professional competence of employees and quality of laws and regulations have a positive and significant effect on the successful implementation of the procurement policy. In addition, results show that electronic procurement, political turmoil and economic instability, social relations, external organizational supervision, and the intensity of competition moderate the relationships between independent and dependent variables according to the research model.

Originality:

 A large number of studies have been conducted on the success of policy implementation, but none presented a comprehensive framework in this regard. The findings of the current research have identified the factors influencing the successful implementation of the procurement policy in the public sector of Iran, which lacks theoretical precedent in the literature.

The administrative system in the country, due to its wide and effective role in doing things, is one of the important infrastructures of development that neglect or lack of attention to it, irreparable damage in the implementation of programs, satisfaction It will lead the people and prevent the formation of corruption. The purpose of this study is to identify the strategic dimensions affecting the level of health in Iranian government organizations.   Research

The present study is a developmental application in terms of applied type and in terms of combined method is a sequential type that in the qualitative section, the statistical population includes managers, policy experts, experts of regulatory institutions and organizations as well as scientific experts and University related to administrative and organizational health was used and in four stages, an expert panel with 20 experts was reviewed and the data were analyzed using SPSS software and factor analysis. The method of data collection is library, theoretical foundations, background, expert questionnaire and considering that the average of managers and professionals working in government organizations has been determined using the Cochran's 338 formula, the strategic dimensions of administrative health in organizations The Iranian government has been identified. 

The findings of this study show that the strategic dimensions of the organization (creating equal opportunities in employment and promotion, preserving human dignity and rights, fair and equitable behaviors in interaction, distribution and procedures, transparency, participation In decision-making,) and external organization (public oversight, integration of work and life, disproportion between growth rate and salary rate, positive work attitude, media and trust and confidence), is effective in promoting administrative health and innovation. The research is the design of a model for measuring the strategic dimensions of administrative health in government organizations, which has not been found in previous research.

Today, the poultry industry is one of the most important food industries in any country in providing food to the communities. Knowledge of how the production chain works in this industry is essential. The purpose of this paper is to evaluate the performance of 28 active production chains in the Iranian poultry industry and to calculate their relative efficiency and also determines the supply chain pattern for other chains. In order to achieve this goal, non-parametric data envelopment analysis (DEA) method has been used. The relative efficiency of each unit is first calculated with the network DEA approach and then the traditional DEA and the results of the two methods are compared. Finally, the cross-efficiency method is used to rank the efficient units. The results showed that in the network and traditional model, out of 28 production chains under study, 3 and 7 efficient chains, respectively. In models, the minimum efficiency is 63% and 67%, respectively. Given the number of efficient units in the traditional DEA model, it is obvious that the decision to determine the pattern production chain for other production chains is difficult. This study proposes a network DEA model to evaluate the performance of Iranian poultry industry production chains.Keywords: Efficiency, Supply chain, Two-stage DEA, Poultry Industry.JEL Classification: C67, H0, L80

A multi-objective mathematical model is proposed to design a humanitarian logistics network under uncertain conditions. Three objective functions are considered to formulate this problem. The first one minimizes the total costs of logistics activities, the second minimizes the maximum overload of local distribution centers, and the third minimizes the maximum accident loss throughout the distribution of relief items. What is more, different simultaneous decisions are determined, including facility location-allocation, service sharing, relief distribution, truck routing, transferring service, and the evacuation of victims. Owing to the fact that the planning of humanitarian logistics problems is encountered with miscellaneous uncertain factors, such as demand, supply, costs, and capacities of facilities, a robust optimization approach is employed to tackle these challenges. Furthermore, a number of numerical instances are provided to illustrate the validity of the proposed mathematical model.

Sustainable development is not possible without the participation of all segments of society. One of the criteria for the development of countries is the level of womenchr('39')s participation in governing bodies. Despite the empowerment of women and the desire to participate in management, the promotion of women still faces obstacles and challenges. The present qualitative research, using the thematic analysis method, aims to identify the elements of the model of womenchr('39')s promotion to executive positions in Iranian public organizations. The sample consists of 42 female-male managers and women experts who have worked in public sectors. The sampling method is purposeful and theoretical saturation has been used to achieve adequate sampling. The data collection was based on individual and centralized semi-structured interview methods and was analyzed at three stages of descriptive, interpretive and integration coding. According to the findings, the elements of womenchr('39')s promotion model in 4 main themes and 12 sub-themes include: Gender awareness and re-defining of womenchr('39')s identity (thoughtful awareness instead of passive acceptance, re-defining womenchr('39')s identity, empathy instead of self-suppression, role management), political determination (supportive and determined government), jurisprudential and legal reconsideration, the formation of womenchr('39')s parties, the system of equal promotion opportunity (the strategy of selecting the right instead of appointing the affiliated, encouraging promotion instead of persuading the job), collective awakening and national determination (collective awareness, cooperation of reference groups and formation of civil institutions). The results show that the establishment of the proposed model will be possible by creating an interactive space between social actors in the heart of structures. To create such an atmosphere, the formation of human-centered discourse is essential. This discourse has four dimensions: interpersonal discourse, inter-party discourse, competency discourse and social discourse.

In this study Data envelopment analysis is used for the assessment of enterprise resources planning systems of 18 manufacturing companies, to determine whether the defined goals for ERP systems have been able to affect the performance after the implementation of the system. Considering the identification of effective factors in implementing ERP systems and using the previous researches, the performance evaluation criteria of this system were identified. Then, using experts’ views the most important input indicators were ranked by fuzzy DEMATEL and output indicators by ANP. In this ranking, time spent on implementation, the implementation infrastructure, training and user support were identified as top input indicators, and three indicators of productivity increase, proper resource management and user satisfaction were selected as top output indicators. Using selected indicators, the performance of ERP systems of selected companies was evaluated. The results of this research will be useful in identifying the strengths and weaknesses of companies compared to top ones and making their ERP system even better.

The present scenario of supply chain management is full of uncertainty due to the intrinsic complexity of operating environments. A perishable products supply chain is not an exception and is often vulnerable to disruptive incidents throughout all stages from upstream to downstream. To deal with such a challenge, a resilient structure of the supply chain with the capability to recover from or react to disruptions is approached in this study. To secure the supply chain operations, we investigate a set of proactive strategies, including signing contracts with backup suppliers, reserving extra capacity in production facilities, lateral transshipment, and keeping inventory. Using a two-stage stochastic programming model, this study examines the extent to which supply chain responsiveness and resilience are supportive. The proposed model is validated through a numerical example, and managerial insights are derived. The computational results are based on three analyses: (1) extracting the relationship between the cost function and the acceptable service levels, (2) examining the effectiveness of different strategies in managing disruptions, (3) and evaluating the accuracy of the two-stage stochastic programming approach in comparison with other approaches.

One of the main challenges of performance evaluation in organizations and all systems is the irrationality and inaccuracy of the methods and criteria used. Traditional performance evaluation methods are mostly one-level, so they usually fail to provide sufficient feedback to identify inefficient units. Data envelopment analysis is a mathematical programming technique that compares the relative efficiency of several decision-making units based on observed inputs and outputs expressed by a variety of different scales. In practice, since many decision-making units are subdivided into smaller parts, with standard data envelopment analysis models that consider the organization as a whole, logical results are not obtained. Therefore, it would be better to use developed models like the two-stage DEA model to more accurately evaluate under investigation units in these conditions. Moreover, in cases that there are a large number of inputs and outputs, traditional DEA is not very efficient and it may consider a large number of units as efficient one. To deal with the problem, this study uses PROMETHEE method to rank criteria. After that, the efficiency evaluation problem is continued with most important inputs and outputs. Since the available information is usually incomplete and inaccurate, the problem is solved in the gray environment. The findings indicate a significant decrease in the number of identified efficient units which shows the improvement in discrimination power of DEA method. Additionally, the use of uncertain environment has led to more accurate estimates than previous definite models.

Locational decisions, routing and allocation in supply chain management philosophy is undoubtedly one of the most important issues that affect the frequency of the supply chain cost reduction and customer satisfaction. This paper presents an integrated approach to the distribution network. The objective function of the proposed mathematical model consists of minimizing the total costs associated with transportation and warehouse rental costs and also minimize the risk of system. The model has high computational complexity and the exact method of solving it is not possible in a reasonable time. The result is an innovative multi-objective algorithm known as the objective harmony search algorithm is presented. To demonstrate the effectiveness and efficiency of the proposed algorithm to solve the model using the Taguchi method algorithm parameters are adjusted in the best possible rates. Then a random sample of the issues and the performance of the proposed algorithm with NSGA-ǁ and NRGA evaluated.

Abstract Vendor Selection Problem (VSP) has been considered in this paper as an integrated method of Fuzzy Analytic Hierarchy Process (FAHP) and Quality Function Deployment (QFD) in the pharmaceutical company. In QFD method, determining the importance of the "weights" for the customer requirements is an essential and crucial issue. FAHP has been used to determine the importance of the "weights" for Product Designing which incorporates the four important attributes in a pharmaceutical company namely Cost, Standing Supplier, Delivery Time and Quality. The new approach can improve the imprecise ranking of customer requirements and provides a decision tool that facilitates the vendor selection. The most significant advantage of this integrated method is using it as a self-evaluation tool in the organization to determine weaknesses and strengths, so it can help researchers to solve this specific subject for supplier’s selection.

Improving efficiency is one of the most important indicators to evaluate the Organization performance and the most basic and the first step to improve efficiency is measure and evaluate it. So far, little researches has been conducted on the hospitals performance evaluation using the combined of balanced scorecard (BSC) and data envelopment analysis (DEA). But in the researches has found by the researcher; 1. Simple performance of units has calculated using DEA classic models, which have two limitations: a) self-evaluation; and b) a lack of recognition between efficient DMUs; The new VFB-DEA cross efficiency model used in this research eliminates these limitations and makes the evaluation results more reasonable. 2. Conditions of uncertainty are not considered if some performance indicators require human judgment, to overcome this problem, the development of the VFB-DEA cross efficiency   model in fuzzy environment is done by the researchers. This research attempts by using fuzzy data envelopment analysis (FDEA) and BSC to evaluate the public hospitals performance in Mashhad during 2014. In this regard, the indicators used to evaluate the performance of health care in situations in past studies and with health experts, three indicators of Staff satisfaction, capita Education and the cost of medicine and supplies, and three indicators of patient satisfaction and the average length of stay and percentage of bed occupancy, in four perspectives of the balanced scorecards elected as input indicators and output indicators. Then, using a new model VFB-DEA in fuzzy environment, mentioned units were evaluated. The results show in the VFB-DEA model thehospital2is ranked first and the hospital 1 and 6 are the most inefficient hospitals. Given the uncertainty and determination of input and output indicators based on a balanced scorecard, the proposed model is more accurate than the past models and enables managers to make better and more accurate decisions to improve the efficiency of organizations.

The main purpose of this study is performance evaluationof the distribution of petroleum products in a green supply multi-criteria supply chain in the Grey environment. This is a case study of Fars National Iranian Oil Product Distribution Company. Under uncertainty conditions and with green evaluation perspectives, the Grey DEMATEL method is first used to study the causal relationships among the perspectives of the improved balanced scorecards and their effectiveness and weight. Then, by using the analytic network process method, the importance of the sub-criteria is determined. Also, the Grey VIKOR is used to evaluate and rank the products of Fars National Iranian Oil Product Distribution Company. With regard to the purpose of the study and the corresponding perspectives, petrol is ranked in the first place and kerosene stands in last place. The results of the study can help the managers of FNIOPDC and other organizations to improve their ability, reduce their weaknesses, and enhance their performance.

Decision making on buying stock is a complex process. Comparing various companies based on the industry they belong to and the identification of the superior industries through their performance assessment can be a useful guide for stakeholders. Since a set of parameters is considered for decision, in this study beside identification of factors affecting decision-making process and determining input and output parameters affecting the ranking of selected companies that are active in Tehran stock exchange market, data envelopment analysis (DEA) has been used to evaluate the performance of companies in several different industries. This method is a nonparametric method to measure and assess the relative efficiency of decision-making units with multiple inputs and outputs. Identified inputs and outputs include net profit margin, quick ratio, fixed asset turnover, equity rate, return on assets, equity, current debt, current assets, and debt ratios. First, input orientation CCR method is used to determine efficient and deficient companies. Entropy method is used to determine the weights of indicators. Finally, VIKOR method is used to rank efficient companies and with the ranking of inefficient companies, models have been presented to reach the efficiency frontier.

The existence of an active and prosperous capital market is always recognized as one of the signs of international development in the countries. The most important issue faced by investors in these markets is the decision to choose the appropriate securities for investment and formation of optimal portfolio. The rating of companies accepted in stock exchange is a complete mirror of their status and is a measure of investment. This will increase the competitiveness, development and market efficiency. In this research, the top 20 companies listed in Tehran Stock Exchange during the third quarter of 2015 are ranked according to financial ratios. In previous studies, optimal portfolio has been determined using data envelopment analysis models and multi-criteria decision making techniques, but the present study combines these two techniques to evaluate and determine the most efficient portfolio. Accordingly, the performance scores of each model are obtained using one of the data envelopment analysis model and then, the weight of each index is obtained using the network analysis process through multi-criteria decision-making techniques.

By increasing environmental laws and regulations and raising public awareness of environmental protection, companies cannot easily ignore environmental issues if they want to work in global markets and compete with other companies. Green Supply Chain Management has become a proactive approach to enhance environmental performance. Under stakeholder pressures and regulations, firms need to enhance (GSCM) practice, which are influenced by practices such as green purchasing, green design, product recovery, and collaboration with customers and suppliers. As proactive firms adopt GSCM, their economic performance and environmental performance will be enhanced. Hence, GSCM evaluation is very important for any company. One of the techniques that can be used for evaluating GSCM is data envelopment analysis (DEA). Traditional models of data envelopment analysis (DEA) are based upon thinking about production as a “black box”. One of the drawbacks of these models is to omit linking activities the objective of this study to propose network DEA model for evaluating the GSCM in the presence of undesirable outputs. A four-stage supply chain demonstrates the application of the proposed model.

Electronic business is one of the major implications of ICT revolution that has experienced high growth over the past decade. With the expansion of e-commerce, the speed and quality of customer service has also increased which forced companies to control quality components more and ensure the accuracy and timeliness of delivery of goods to meet the growing needs of customers and ultimately their satisfaction. The use of electronic business in business activities requires attention to a series of exogenous and exogenous factors affecting it. Therefore, in order to develop an effective and targeted evaluation system, an assessment of performance of logistics network in the electronic business is required. Data Envelopment Analysis is one of the powerful management techniques that provide managers with tools that can benchmark their company's performance compared with other competitors and decide for future prospects based on its results. In this study, using fuzzy DEA a new method for evaluating the logistics network collaboration in an e-business will be presented. After introducing two optimistic and pessimistic models both of them are solved. Finally, the application of the model is shown with numerical example and the sensitivity analysis of the input and output parameters is also performed.

In this research, in order to manage and control customers credit risk, a combination of two models, including discriminant analysis and data envelopment analysis, is used to detect the existence or absence of an overlap between the two groups. Using a separator hyperplane and assuming n viewing each one with k independent characteristic with the presence of fuzzy data, observations are categorized into two valid customer groups and invalid customers. Variables of this research are selected using the 6C method and using the Delphi method, among 17 selected indicators, 8 effective indicators are confirmed and entered into the research model. These indicators were used for 83 natural customers of a leasing company that benefited from the company during 2014 until 2016. The results show that each observation is definitely in the valid or invalid customer group and with the arrival of the new observation, its credit status is forecasted

In order to survive in today's competitive world, organizations are looking to increase their efficiency and effectiveness. Therefore, they should focus on inputs that are more important than the rest of the inputs in their success. This paper aimed at ranking 7Ms (Management, Man power, Marketing, Material, Machinery, Methods and Money) and their sub-criteria of production in Iran. By improving manufacturing processes, manufacturing organizations create and establish their added value. The Analytic Hierarchy Process (AHP) is a very popular method in decision making process, and its inner dependence extension is used for cases in which criteria or alternatives are not independent enough. In FAHP, each option severity is displayed by fuzzy numbers in relation to criteria. Therefore, a fuzzy judgment matrix is obtained. In this study, Fuzzy AHP tool has been used to rank these inputs. The results are compared with the ideal ranking results and are examined that how different they are.