نشریه مدیریت راهبردی در سیستم های صنعتی
پیاپی 57 (پاییز 1400)

One of the most important industries that cause environmental pollution is the cement industry and companies active in this industry. Cement industry in terms of importance, such as steel and petrochemical industries, and always in accordance with national economic and development plans and policies contributed to the performance is satisfactory. The present study aimed to identify barriers to GSC implementation by FD, weight and prioritize them through the FBWM and evaluation, ranking of Abeyek Cement Industries, Isfahan and Tehran regarding the performance of using the GSC with MAPPAC technique. The present study is a field research in terms of applied purpose and in terms of data collection. The present article is exploratory because it seeks to identify barriers to the implementation of green supply chain in the country's cement industry.The present statistical sample and population consisted of 12 logistics senior managers in cement companies. Results of screening by a FD indicated that a native model had five dimensions and thirty four indices. According to results of weighting barriers to GSC implementation dimensions by the FBWM, the support & covering was the most important dimension of the GSC, then the Technological was put in the second place, dimensions the economic, knowledge and environmental were ranked third to fiveth respectively.The cement companies were then evaluated by the proposed model through MAPPAC technique. In the present study, the native model of barriers to the implementation of green supply chain in cement manufacturing industries has been designed.

One of the new approaches that can be used to increase the effectiveness & efficiency of the supply chain is the Shared Value Innovation in the supply chain. The difference between value innovation and shared value innovation is their level of activity. Although some research has emphasized the importance of value innovation in different parts of the organization & to some extent introduces Shared Value Innovation, so far no research has been conducted to provide a framework or model for managing Value Innovation in inter-organizational levels. The main purpose of the present study was to fill this research gap. In this mixture study, semi-structured interviews with petrochemical managers & academic experts were conducted & analyzed using constructive Grounded theory. Samples were selected by purposive sampling, based on the principles of Grounded theory approach. The reliability of the results is confirmed by calculating two evaluation indices. After analyzing the data using MaxQDA software, a framework for managing Shared Value Innovation in the supply chain has been proposed. The proposed theory shows how to achieve Shared Value Innovation through increasing adoption, improving communication, improving collaboration, enhancing trust, enhancing the commitment, enhancing interdependence while maintaining the independence, & simultaneously reducing costs. After designing the theory, its dimensions were evaluated and confirmed by combining the foundation data theory approach with the Delphi method.

In recent years, given the importance of industrial wastewater waste, supply chain stakeholders expect the reverse supply logistics supply chain to be considered. Therefore, the purpose of this study was to identify and prioritize the reverse logistics supply chain of industrial wastewater waste in Gol Gohar Mining and Industrial Company. The research was applied development and was conducted in a mixed way. Using purposive sampling method, 12 experts familiar with the research were identified. In the qualitative section, content analysis was used to code and identify the factors. Fuzzy Dematel was used to prioritize the factors in the quantitative part. The results showed that the factors affecting the reverse logistics supply chain of industrial wastewater include 7 general themes. Commitment to management, environment, cost, flexibility, rules and regulations, social and total quality management. Using Dematel technique, it was determined that management commitment is the most influential factor on other factors and the environment is the most influential factor on other factors, which shows the impact of other factors on this factor

Due to the prevalence of impulse buying behavior among consumers, its academic studies have increased over the last decade. Because of the sales should be high in stores, the study of consumer behavior in impulse buying should be considered by researchers and store managers. The purpose of this paper is to identify the key factors of consumer behavior in impulse buying with emphasis on ethics in sales using fuzzy screening technique and weighting and prioritizing factors using the best-worst fuzzy method. The population and the statistical sample include 15 modeling experts and academic professors who are fluent in impulse buying and marketing topics After a thorough review of the theoretical foundations and research background, 6 dimensions and 40 indicators were identified. The innovation of the present study is that fuzzy logic and multi-attribute decision-building method have been used to identify and prioritize the components of ethics in Impulse buying sales. The results of fuzzy screening showed, ethics factors in sales; physical; social; temporal; regulatory and individual, as selected dimensions of fuzzy screening along with 21 indicators were selected by experts. Also, the results of weighting the dimensions with the best-worst fuzzy technique showed that the ethics factor in sales was the most important dimension of impulse buying and the individual factor was ranked second, and physical, social, temporal and regulatory factors were ranked third to sixth, respectively.

Contemporary supply chains are complex networks of processes that are subject to many disruptions; a resilient supply chain will be able to respond more quickly to changes by creating capabilities. The effect of supply chain network components on each other under conditions of uncertainty contributes to complexity and disruption. The supply chain must be pushed towards a resiliency strategy in order to reduce disruptions and deal with issues that arise from the supply chain. The purpose of this paper is to analyze network processes from supplier to distributor, in proportion to the convergence of processes by a combination of resilience factors in the automotive industry. The design of the proposed scenarios with the combination of effective resilience factors is presented, which is based on the opinion of industry experts and also takes the vulnerable factors and disorders of each level into account. First, the sources of supply chain risks such as disruptions, delays and vulnerabilities are identified and then twenty-four scenarios are designed with a combination of resilience factors of flexibility, visibility, velocity, and visibility. The company''s complex supply chain is simulated based on the system''s past rate and statistical distribution functions, and then the network DEA is used to select the superior scenario. The indicators of each scenario or simulation output are selected based on the DEA, ranking the most efficient scenario. Finally, the relationships between them have been explored using mathematical analysis and the creation of a regression model between the simulation indices and the output of scenarios.

The aim of this study was to identify and prioritize the factors affecting the special value of the brand by emphasizing the performance of the brand in the cosmetics market. The statistical population of the study was all customers of cosmetic products in Tehran in 1397, which were selected by random sampling cluster sampling method. The sample consisted of 550 customers from ten brands (Mibi Lynn, Erben Dicky, Cover Grill, EVon, Relon, E Tod, McLurray, Oriflame, Clinic), which accounted for about 80 percent of the market share. The research data were collected using questionnaires and secondary information and the research hypotheses were tested using structural equation modeling model and analysis of focal correlation and application of SPSS, LISREL, SAS, STATISTICA software at the brand level. The research findings showed that factors such as brand awareness, attitude, surplus price, brand expansion potential, innovation, distribution and access, advantage, advisory advertising and general perception affect brand equity by emphasizing brand performance. Based on brand awareness results and general perception, they have the greatest impact on brand equity in the cosmetics market. The results also showed that the most widely used product among the statistical community is eye, eyebrow, eyelashes and so on. Market share surveys based on the presence of at least one product from a brand in the customer portfolio also show that the three brands of Etude, Loril Group and Rollon have the largest market share, respectively.

Human capital as an intangible asset and an important source of competitive advantage in the banking industry, provides the basis for improving organizational capabilities. In recent years, rapid and diverse changes in business environments and the concern of organizations for competitiveness and survival, led to the introduction and application of concepts such as lean, agile, resilient and green and their combination in various forms. Since the implementation of the above approaches requires their application in human resource management of organizations, the main purpose of this study is to design a model that can use the four approaches of lean, agile, resilient and green as integrated model, in human resources management of the Iranian banking industry.The statistical population of this qualitative study is 12 experts in the field of human resource management of the banking system and university professors, who have been selected for the study by purposive non-probability sampling. Research data were collected through semi-structured interviews with experts and analyzed using the thematic analysis method. The extracted themes are presented in the form of a Integration model of human resource management in the banking industry, consisting of lean, agile, resilient and green approaches, underlying factors, process and consequences.

Planning to empty warehouse cells is one of the most challenging issues in times of crisis. The need for emergency logistics for the efficient use of equipment is of great importance. In this study, a dual-objective planning model of routing and simultaneous scheduling of heterogeneous vehicles (picking containers)It has been suggested to evacuate the courier warehouse cells in emergency situations (non-compliance of the piece with the courier schedule) in order to minimize the movement time and maximize the reliability of the routes due to the congestion of the warehouse corridors. The developed Epsilon constraint method has been used to solve the proposed model. In the proposed model, the possibility of providing service for each warehouse cell that should be emptied by heterogeneous peak containers to logistics /warehouse areas with limited capacity is considered.To demonstrates the performance of the proposed model, the model is run on a random example and the computational results are presented. The results of problem-solving indicate a conflict between the objective functions used. In order to investigate the large-scale model, due to the Np-hard routing issues, three Particle Swarm Algorithms (PSO), Ant Colony (ACO), and Bee Colony (ABC), swarm intelligence algorithms were used and the results were compared with each other. The results of large-scale problem solving to find the best displacement path show better performance of the particle swarm algorithm.

The amount and type of resource allocation and adoption of necessary strategies to effectively provide emergency measures, given the vital role of these centers in the health system, and the ability of these centers to respond effectively to emergency calls is an important element in providing patients' health. Find the most optimal location of emergencies according to the interaction between factors, environmental constraints and different behavioral characteristics of different factors assumed in the problem. In terms of practical and descriptive purpose, with the explanatory modeling approach, which uses expert opinion polls in presenting the model and in implementing the model, which is based on the application of metaherstical algorithm. Combined objective and subjective data Factor and environmental variables are modeled through a combined approach of factor-based simulation and metaheuristic algorithm. The initial time to navigate an initial structure for 40 accident hotspots and 5 stations was 7860, which after genetic optimization and the production of a new list, as well as the jump of ambulances from one station to another, the results reached a number between 2700 and 4000. Using this type of optimization can help speed up activities and reduce costs. Due to the unequal traffic of the points, the time of arrival of the ambulance to the accident hotspots will not be equal, so by changing the deployment points, according to the conditions and specializing the characteristics of ambulances and accident hotspots and combining the list of points, the total travel time can be Reduced accident hotspo

In recent decades, the way of raw material supply and supplier selection in the health supply chain has been an important challenge. The supply chain of the pharmaceutical industry is critical and there is no specific mechanism for selecting pharmaceutical suppliers in the country. Due to increasing environmental and social awareness, choosing a sustainable supplier is one of the priorities of pharmaceutical companies. Therefore, the purpose of this study is to evaluate and select sustainable suppliers in the supply chain of the pharmaceutical company. This research is a descriptive study and is applied in terms of purpose. Research data were collected through a review of literature, interviews with experts and a questionnaire. Supplier evaluation indicators were weighted and prioritized with fuzzy QFD approach. The indicators of strength and financial and technical stability, principles of supply chain agility and managerial capabilities with weights of 0.155, 0.133 and 0.115, respectively, are the most important indicators of sustainable suppliers. Then, the indicators of return policy, history, and applying the principles of green supply chain with weights of 0.059, 0.057 and 0.033 are the least important indicators for assessing the sustainability of suppliers in pharmaceutical companies in accordance with the findings of this study. Also, with VIKOR approach, four suppliers of Barakat Pharmaceutical Company were evaluated and prioritized in accordance with sustainable criteria. Two suppliers with appropriate stability points and two unsustainable suppliers were identified.

The aim of this study is to provide a comparative model and financial ranking of petrochemical companies using dynamic network data envelopment analysis (DNDEA) approach by CCR and AP methods. occurred. In the first step, a relational model including major profit sheet, balance sheet and financial soundness indicators is presented under a dynamic network structure. Then, the dynamic effect of indicators (carriers and relationships) is included to calculate the efficiency scores for these four infrastructures correctly. Then we calculated using the two models and the results were extracted. This research is applied in terms of purpose and its statistical population is petrochemical companies listed on the Tehran Stock Exchange. Based on the research findings, according to the research criteria, efficiency was calculated. Out of 18 petrochemical companies studied, two companies were identified in the CCR method and one company in the AP method as moderately efficient. However, the results show a strong correlation of 71% between the two methods.

Today, due to the complexity and involvement of various factors in the discussion of material selection, manufacturers in the field of competition need a strong and scientific tool that identify all the factors influencing the choice of materials, determine the importance these factors and balance them .In this research, we try to present a fuzzy hybrid approach to identify and prioritize the factors influencing the selection of automotive polymeric materials. For this purpose, after reviewing the experimental records by surveying organizational experts and using fuzzy Delphi technique, we identified and screened the factors of competitive advantage affecting the selection of materials and we weighted and prioritized these factors using fuzzy hierarchical analysis technique. Based on the results obtained by fuzzy Delphi technique, five indicators: economic, technical, environmental, social and technology inclusive of 29 related sub-indicators, identified and Sieved. Then we calculated the importance of indices and sub-indices using fuzzy hierarchical analysis technique. The results showed that the highest importance is related to technical and economic indicators and the least importance is related to technology index. In addition,from the economic index Sub-index the market value, From the technical index Sub-index the weight, From the environmental index Sub-index the recyclability, From the social index Sub-index the health and safety and from the technology index Sub-index the current facilities, obtained the highest degree of importance.