نشریه مدیریت راهبردی در سیستم های صنعتی
پیاپی 48 (تابستان 1398)

Today, given the globalization of the business world, companies expanded their activities beyond the geographical boundaries of countries and continents, and entered into global markets. For this reason, on the one hand, the competitive advantage of organizations has increased, on the other hand, the supply chain is expanding and communication with its various sectors has increased. By increasing these connections and expanding supply chains, companies have become more vulnerable to risks and disruptions. Over the years, there have been many methods for evaluating and selecting suppliers, but the point that is often neglected is the segmentation of suppliers in this process. The purpose of this research is to provide an approach to supplier segmentation. Indicators of this research have been studied in two dimensions of capability and willingness. In this research, suppliers of one of the major dairy companies of Mazandaran province are evaluated using the best-worst method and these suppliers are segmented according to the selected criteria. According to the results, most of suppliers are placed in the first and fourth regions, which the results and analysis can be helpful to improve the organizations studied.

Decisions on the process of assessment and selection of suppliers should be made by examining all possible options, otherwise the organization will encounter many problems during the implementation and implementation phases.The purpose of the present study was to determine the indifference points of assessors of the water and wastewater company in Zanjan province.The method of this study was descriptive. The data of this study is related to supplier assessment of one of the projects of the city water and wastewater company Zanjan province.The data was collected based on the views of 10 experts with at least a bachelor's degree and at least 5 years of work experience in the company based on the "supplier assessment form".The data has been analyzed using the 2014 version of MATLAB software.A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method.TOPSIS-GA = 2 and TOPSIS-PSO = 3 and AHP-GA = 2 and AHP-PSO = 3. A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method.

Data envelopment analysis (DEA) is a methodology for assessing the performances of a group ‎of decision making units (DMUs) that utilize multiple inputs to produce multiple outputs. It ‎measures the performances of the DMUs by maximizing the efficiency of every DMU, ‎respectively, subject to the constraints that none of the efficiencies of the DMUs can be less ‎than one. The efficiencies measured in this way are referred to as optimistic efficiencies or the ‎best relative efficiencies. The way to measure the optimistic efficiencies of the DMUs is ‎referred to as self-evaluation. If a DMU is self-evaluated to have an efficiency score of one, ‎then it is said to be DEA efficient; otherwise, the DMU is said to be non-DEA efficient. ‎There is a comparable approach which uses the concept of inefficiency frontier for ‎determining the worst relative efficiency score that can be assigned to each DMU. DMUs on ‎the inefficiency frontier are specified as DEA-inefficient, and those that do not lie on the ‎inefficient frontier, are declared to be DEA-non-inefficient. In this paper, we argue that both ‎relative efficiencies should be considered simultaneously, and any approach that considers ‎only one of them will be biased. For measuring the overall performance of the DMUs, we ‎propose to integrate both efficiencies in the form of an interval, and we call the proposed ‎DEA models for efficiency measurement the bounded DEA models. In this way, the ‎efficiency interval provides the decision maker with all the possible values of efficiency, ‎which reflect various perspectives.

The supply chain is a dynamic system that includes all activities related to the creation and delivery of a product, from the raw material stage to the final customer. Sapco's supply chain management needs future decisions and the design of new capacities with a comprehensive and interconnected approach. One of the management tools based on this approach is the system's dynamic knowledge. This science has the ability to simulate the supply chain, with the help of this simulation, the uncertain outcomes of decisions are revealed. An analysis of the fluctuations in the behavior of customer orders can provide a key role in predicting customer demand, sales, timely delivery, sales staff adjustments, and other factors. In this paper, the dynamic analysis of the order system in the supply chain with the dynamics of the system is examined. In this paper, based on the principles of the dynamics of the system, following the statement of the ordering system problem in the supply chain, the hypotheses that give rise to the problem are explained; then the dynamic model related to the problem of fluctuations in the ordering system of presentation It will be. first, the main variables were identified and their relationships were formulated in the form of Ali rings, then, by designing the main model, in the form of flow accumulation chart, was simulated in the software. After designing and simulating the final model, validation tests and sensitivity analysis were performed on the model that showed the validity of the model.

The purpose of this research is to provide a sustainable supply chain model with an emphasis on behavioral factors for food products in Kermanshah province. . This research is based on the purpose. On the other hand, it is a non-experimental type of research. Study of the subject literature through library study such as books, journals, dissertations, articles, etc., was collected through a questionnaire of required data, then by statistical methods, the data were analyzed. have taken. Regarding the subject of this research, the study population consists of directors and staff related to supply chain in Kermanshah food companies, which number is 90 people. Data analysis using structural equation modeling and PLS software revealed that the training environment, innovation, motivation, empowerment of staff, mutual respect and mutual trust, and teamwork have a positive and significant effect on the sustainable supply chain with three indicators Environmental, social and economic. KEYWORDS: Sustainable Supply Chain, Behavioral Factors, Structural Equations, Food Industry.

This research examines the role of open innovation intermediaries in facilitating communication between industrial enterprises (technology applicants) and technology-centric companies (technology providers). There is always a lot of challenges for technology exchanges and the needs of the industry. In the meantime, institutional existence is important to facilitate the process of technology exchange to increase interactions. However, as past experiences show, intermediary institutions in our country have not functioned well, and technological exchanges do not have the desired conditions. To this end, the purpose of this study is to provide a model for setting up such an institution. The method used in this study is quantitative. Initially, the functions of the intermediate entity were extracted and then, using the fuzzy Delphi technique, the proper functioning of an intermediary entity in the country was identified and divided. In the following, we study the effectiveness and effectiveness of the relationship between the factors using the fuzzy demilitarization technique and have been investigated using the Fuzzy Network Analysis Technique for weighting and prioritizing.

Despite the numerous benefits of globalization and the emergence of advanced technologies, they have put the sustainable supply chain in subject to the social, economic, environmental risks. The aim of this study is to develop a new approach to identify and prioritize the risks involved in sustainable supply chain by using the failure mode and effect analysis (FMEA) technique. In this way, the fuzzy sets theory is applied to calculate the risk priority numbers with regard to the fuzzy importance coefficients of risk factors including probability of occurrence, severity and detectability for each risk factor. However, proposed approaches have a computational inefficiency in ranking the fuzzy priority numbers. The fuzzy weighted geometric mean and linear programming model is used in a different way to determine the fuzzy risk priority numbers and then the fuzzy preference relations is applied to compare these numbers for prioritizing sustainability risk factors. Risk factors of the sustainable supply chain in the battery industry are identified and then prioritized by the cross-functional team by using the proposed method. The results show that the approach is capable to provide similar results than other ones with a high computational performance.

The rapid advancement of technology in the present competitive environment has encouraged many organizations to expand their NPD activities across organizational boundaries. In recent years, the joint creation method has been used as one of the most successful and effective approaches to the development of competitive advantages, especially in large organizations. Suppliers and some of the leading international organizations are expanding their activities towards each other and in accordance with the literature of creation and value extraction for both sides jointly and simultaneously. Joint creation means the active participation of the supplier in some activities of the organization, one of the most fundamental principles of this emerging view.Contrary to previous research in this paper, in addition to a integrated look at the factors affecting the performance of the process of joint creation with suppliers, the relative value of each factor, taking into account their impact on each other, has been examined.for this purpose, firstly, main factors effecting of joint invention performance are identified. Then these factors classified and organized in a decision model. Because of hierarchical and mutual affects between the factors, analytical network process (ANP) model is proposed. Using the model, ranking of the factors achieved. The Delphi technique is used to identify the most important performance metrics and the ANP has been used to assess the priority of the criteria. The results show that R & D, production, supplier-related propulsion forces and end-of-life management have the most importance and poor status, and Provided some ways to improve them.