فصلنامه مطالعات مدیریت صنعتی
پیاپی 66 (پاییز 1401)

Soft OR from pluralist paradigm has effective approaches to structure and improve problem situations with different stakeholders’ worldviews and conflict of interests. The approaches, structure and improve messy situations. In this study, we used Soft System Methodology (SSM) as a popular soft approach at two levels. First, we applied Soft System Methodology process (SSMp) to plan the systemic intervention process in the employee promotion System of an oil and gas company. Then, Soft System Methodology content (SSMc) was used to investigate the content of the company's employee promotion system that caused employees’ dissatisfaction. By considering managers’ and employees’ worldviews, three root definitions were made. At this phase, fair condition to present different points of view was applied. So, employees with different organizational power levels expressed their opinions openly. Finally, stakeholders’ participation through the discussion helped to build an agreed model and a root definition, and agreed actions for addressing defects of the employee promotion system were proposed.

Nowadays, due to the pollution that businesses and various industries impose to the environment, the adoption of strategies and policies by governments to improve the environmental performance of the supply chain has received more attention. The green supply chain will have many benefits, such as saving energy resources, reducing pollutants, and so on. Government intervention to develop these chains takes various forms, such as subsidies, taxes, licensing, and advertising. In this study, two manufacturers with green and non-green supply chains compete in a competitive market and sell their products through a joint retailer, and the government intervenes as a leader in the stackelberg game. These chains are designed based on the selection of agent-based pricing and wholesale pricing methods in four different models. In these models, the government advertises for green products in the first and second models and imposes taxes on the producer of non-green products in the third and fourth models, seeking to maximize social welfare and improving the environment. In order to analyze and compare the models, the game theory approach was used. The results show that in general, government intervention improves the environmental situation and social welfare, and in the case of advertising has a better effect on the overall market trend and also on social welfare than the tax imposing strategy.

Estimating the revenue efficiency of entities under evaluation is one of the most important evaluations that can give valuable information about organizations provided that the output prices are known . In this research, a new definition of optimal scale size ( OSS ) based on maximizing the average revenue efficiency (ARE) is presented . Also , the ARE is defined in both convex and non - convex sets, which is independent of returns to scale and the assumption that the vector of input-output prices of units is uniform . Next, due to the presence of uncertain data in many real applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs , and approaches are provided to calculate it . Finally , the proposed method is used in an experimental example and the ARE is calculated for a data set of postal areas in Iran .

Supplier Segmentation is one of the key activities of supplier relationship management (SRM) for companies with a large number of suppliers. It involves dividing the suppliers into a manageable number of segments, to formulate SRM strategies for the various segments, rather than for each individual supplier. Supplier segmentation has attracted a great deal of attention in recent decades. The purpose of the current study is to provide a systematic review of supplier segmentation researches to determine the future trend of this research area. For this purpose, a systematic literature review and citation network analysis are used simultaneously. After determining the search protocol and criteria for selecting articles, 48 articles were finally selected. Selected articles were evaluated and analyzed according to the steps of a systematic literature review and citation analysis. The results of the study indicate that researchers have welcomed the portfolio approach, decision-making techniques, and two-dimensional model of profit and supply risk in supplier segmentation research. A comprehensive analysis of the studies made it possible to distill the future research trend. This research area requires further study involving the supply chain paradigms, the impact of supplier segmentation on performance, and the analysis of the supplier relationship management as a whole, with supplier segmentation being one of its components.

Management and warehousing operations are one of the essential parts of manufacturing and service organizations. Warehousing is one of the main components of the organization's activities, which has a high cost and deserves more attention from researchers in this field. This research has investigated the storage problem based on the clustering of items, taking into account all the factors affecting the storage of products in warehouse with bulky and varied products. The main objective of this research is to reduce Transport costs of collecting and delivering orders and more efficient use of storage space. The K-mean technique is used for solving the clustering problem and the Generalized Allocation mathematical programming model has been used to solve the problem of assigning categories of items to storage locations. This is an integer programming model with the goal of minimizing transportation costs of collecting and delivering orders.This research has been able to provide a comprehensive approach in clustering and allocation of items by identifying and considering the effective indexes and using the generalized allocation math planning model and formulating the actual conditions of the problem and solving it in an optimal way. Companies managers can use this model to reduce their inventory costs. Using of clustering in the allocation of storage sites to the warehouse items and then their mathematical modeling is innovation of present research. The proposed model was implemented at Mashhad Housebuilding Company. A number of simulated problems are solved from the actual problem with the GAMS software for validation.

Integration of supply chain decisions reduces costs and delivery time to customers, but uncertainty in supply chain offending parameters, including demand, disrupts this integration. This demand uncertainty has led to an increase in interest in the use of probabilistic planning and simulation models in supply chain modeling. Therefore, the overall purpose of this study was to model and develop a multi-level, multi-product, multi-period supply chain network model with conflicting objectives such as cost minimization, delivery time minimization, and maximizing system-wide reliability. The supply chain network under study had 4 levels or subsystems of suppliers, manufacturers, distributors and retailers. In this study, it was assumed that demand is random and follows a probabilistic distribution function. Therefore, the simulation technique was used to estimate costs including shipping costs and lost sales costs and other costs. After developing a multi-objective model, for the studied problem, scenario building was done based on different perspectives on inventory levels (minimum inventory, maximum inventory and average inventory level) and based on each scenario, values related to the objectives were estimated. In the end, based on the Parthian answers obtained for each case of the model, based on Vickor decision-making method, the final ranking of the answers and selection of the best case from the proposed model was performed. The results showed that the second scenario, ie considering the average inventory level, was selected as the best solution for the described model

In this research, a model for a stable closed loop supply chain with economic, social and environmental considerations, along with the risk arising from uncertainty in parameters, is presented. Random programming has been used for modeling this problem and also using the scale of value Exposure to conditional risk is measured by risk. The purpose of this model is to maximize network design benefits, reduce unemployment and increase job opportunities resulting from the construction of facilities and minimize the production of carbon produced through intranets, production centers, recycling, repair, re-production. Other goals include minimizing the risk posed by uncertainty in transportation costs and customer demand. In the end, in order to demonstrate the efficiency of the model, an example is solved with certainty and uncertainty with the risk measurement criterion, and the pareto optimal solutions are compared. The results of this study indicate that, with increasing risk, the profit from the supply chain network has decreased and should be costlier to face the risk.