فصلنامه مطالعات مدیریت صنعتی
پیاپی 62 (پاییز 1400)

It’s more than one decade that industrial development based on the structure of industrial clusters as a new strategy has been planned and administrated by developed industrialized countries. Considering the importance of the role of industrial clusters in economic development programs, providing solutions to improve, progress and development of clusters has always been a concern for researchers and specialists.The aim of this study is to provide a mechanism for pricing process of the product in this industrial-economic phenomenon; So that the structure of the proposed model is defined based on mechanisms and activities of the components of industrial clusters. The proposed pricing process is presented based on the concept of Stackelberg game theory and tariff pricing strategy, and in order to solve the model in production level of cluster, a meta-heuristic genetic algorithm is used. Finally, the performance and efficiency of the proposed model is studied in the form of a numerical example, and using the parameter tuning Taguchi method the optimal value of the model variables are presented. Based on the obtained results, the optimal wholesale price of cluster’s products are determined and each manufacturer select the appropriate tariff based on its optimal demand.

Nowadays, more successful businesses are those that keep their customers satisfied and in addition to the macro level of their policies, also pay serious attention to the micro level and details of the market. In this article, in order to study the influential factors in the mobile phone market, the dynamic system method with the discrete event method has been used in combination.In this paper, the first two mobile companies Hamrahe Aval and Irancell as the basic players in the Iranian mobile phone market are considered as two rivals. Since in recognizing and analyzing the influential factors on market share, operational and strategic levels affect each other, after specifying the impressive factors at each level, from the discrete event approach at the operational level, and the dynamic system approach at the strategic level and their combination has been used to indicate a compound model of the mobile phone market.Based on findings any change in the operational and strategic levels of each competitor will have a serious influence on the rate of increase / reduce of willingness on their services and the consequently increase or decrease in customers. On the other hand, it indicates how a more specified level of detail can be noticed by combining discrete event simulation methods and a dynamic system.In comparison the suggested combined model investigates more details of events than simple simulation models, so, it can be used to examine different ways for decision-making.

As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research gap, this paper examines how SCQM capabilities and SCQM performance can influence firm innovation and operational performance, and how they interact with each other. For this purpose, the information of managers and experts active in the food industry in Golestan province was collected and analyzed through a questionnaire. Research findings show that SCQM practices have a positive effect on SCQM capabilities. Another result is that SCQM methods do not have a positive effect on the operational performance of food industries in Golestan province. This finding is significantly different from some previous studies. We also found that SCQM capabilities do not have a positive effect on innovation performance.

Because of the dissemination of impulse buying behavior in consumers its academic studies have increased over the last decade. Because in large stores, sales have to be increased, the behavior of consumers in impulse buying to be taken into account by the researchers and managers of the stores. The purpose of this paper is agent–based simulation impulse buying behavior consumer (customers) considering the discount, the optimal time of customer presence in stores from the point of view the store managers and learning from previous buying. The population and the statistical sample of the present study include 15 academic professors who are expert in impulse buying and marketing topics. The present study is executive in terms of purpose. It is mathematical in terms of data type and modeling method. This model examines the existing reality of consumer buying behavior to develop impulse buying models in the agent-based simulation environment by Netlogo software. After reviewing the theoretical foundations and research background 5 dimensions and seventeen indicators have been identified by fuzzy screening method. The results showed that the factors considered in this study describe the impulse buying behavior of consumers as an economic analysis based on consumer relations and customer-product relationship. This achievement by simulating customer behavior at the time of purchase strives to provide valuable information for managers shareholders and store decision makers.

Data envelopment analysis is auseful method to measurement unified rational and operational and environmental efficiency a supply chain. Supply chain management divisions produce two types outputs based on economic activities and inputs separate into two categories under natural and managerial disposability. The current paper propose a new Data Envelopment Analysis based model to efficiency assessment a supply chain under investment on certain types of inputs to new technologic innovation. In hence, dual-role factors controls cleanup costs of flaring gas and the amount electricity consumptions of power plants also dual-role indices improve expertise in transmission entities. A real case study on Iran power industry is presented to demonstrate the applicability of the proposed model. To demonstrate the capability of the proposed approach this framework is implemented for the performance evaluation of a supply chain identified by oil and gas companies, power plants, transmissions companies, dispatching companies and final consumers in Iran.

This paper presents a global supplier selection model for the textile and clothing industry using a fuzzy multi-criteria group decision making approach. Then, the order quantity of each supplier is determined by a mathematical programming model. In the first step, a group fuzzy analysis hierarchical process approach is used to obtain the overall weight of the criteria and sub-criteria and then modified VIKOR is developed in order to calculate the vendor rating. In doing so, a modified VIKOR method with fuzzy-random data is extended due to the existence of both qualitative and quantitative criteria. The qualitative criteria are considered by fuzzy linguistic modeling and quantitative criteria from random data are formulated in a stochastic environment (based on historical data of suppliers). In the second step, a nonlinear programming model is developed to to determine the purchasing quantities from suppliers with multi-sourcing strategy. Finally, using a numerical study, the deployment of the above model is done in the clothing industry and crucial parameters are discovered by sensitivity analysis. Our findings indicate the critical role of customer’s demand and assigned capacity of suppliers in procurement plan.

Today, in order to maximize the productivity, sales and profits of factories, various factors must be considered. One of these factors is energy saving, which leads to success in any businesses. Another important factor is rework in the production process, which reduces waste and optimal use of resources. In this research, a linear mathematical programming model has been developed for a multi-stage production system considering energy consumption and the possibility of rework. The objective function of the model is calculated from a combination of energy costs and raw material costs, and the proposed model has three categories of balance constraints, demand constraints and time constraints. The balance constraints, the task of calculating the number of raw materials required and the amount of input materials to each part of the production stage, the demand constraints are the task of calculating the number of final products, and the inventory and time constraints are also the task of calculating the time available to the production of each product. A hypothetical production system is flow shop. To understand the proposed model better, a logical example is designed and solved and analyzed using GAMS software . In the current situation , energy consumption is one of the concerns of policy make rs in the fields of production and industry , and therefore this research with the propo sed model , helps decision makers in manufacturing industries to ensure optimal ene rgy consumption , optimal decisions in adopt multi - stage rework and production conditions .