JOURNAL OF INDUSTRIAL MANAGEMENT STUDIES
Year:2019 | Volume:16 | Issue:51 |Papers Count:10

Supply chain collaboration has been recognized as a potential business differentiator and a source of creating competitive advantage. One of the most common collaborations in the supply chain is vendor managed inventory. In this paper, a two echelon supply chain with one vendor, multi retailers and multi products under VMI contract is investigated. After producing, the products are sent to retailers cyclically (i. e., retailer1-retailer2-retailer1 for a two retailer system) and there are n deliveries to each retailer in a single production setup. Due to uncertainty of the warehouse capacity for both echelons of the chain, and also the changing market conditions, stochastic constraints of warehouse capacity and budget are considered for both echelons. The principle aim of the paper is to minimize the total cost of the supply chain by optimizing the order quantity of each product for each retailer. At the end a numerical example of the model is solved by GAMS24. 1. 2 software. The sensitive analysis on the partnerؘ s parameters cleared that the parameters of the vendor is more effective to mitigate the total cost of the supply chain.

In today's competitive and global economy, the life and activity of the organization is determined by the ability to compete and adopt the most appropriate policy against environmental changes. In this regard, the knowledge about the performance of all aspects of the organization is vital for management decisions. Although extensive studies has been carried out in evaluating the performance of organizations through the balanced scorecard (BSC), but there are defects such as focusing on a one-way causality, ignoring the replacement between indexes and between the four-way, and equality between weighted value of indexes. In the present study, focusing on the casual relationships between factors and also between the direction and strength of these relationships, we tried to improve the balanced scorecard method. To do this, first all the relationships between the four dimensions of BSC were determined using fuzzy cognitive map, and it was then used to obtain a network structure, which was used later to create a network data envelopment analysis (NDEA) model. Finally, this model was used to evaluate the performance in Maskan Bank of Fars province. The results show that between 82 branches investigated, 15 branches were efficient and the others inefficient.

Within two recent decades, the complexity of business environment, dynamics, uncertainty and higher environmental fluctuations, concepts such as globalization and increasing competition made many changes in the equations ruling on the industries supply chain. In such conditions, the businesses must make themselves ready for encountering the continuous flow of challenges such as economic crises, sanctions, exchange rate and prices fluctuations, limitations of manufacturing system or natural disasters. “ Resiliency” is one of strategies for dealing with such challenges. The present study aims to review the studies based on the strategic position of pharmaceutical industry as a part of society’ s health system and present here the resilient supply chain model. For this purpose, in addition to contemplating in the literature review, interview to the experts and using Delphi method, the resilient elements and indices of supply chain were identified and extracted, and a questionnaire was designed and provided to the population of pharmaceutical industry. The results were analyzed using structural Equations modeling technique and Lisrel software, and the proposed model of research was accepted upon explaining the associations between factors. This model studied the relationship between elements such as drivers, vulnerabilities, capabilities and empowerments of supply chain and their effect on each other. Summary of study indicates that the managers of pharmaceutical industries through making or using the capabilities and strengthening the empowerments can reduce the factors that make the companies susceptible for the disruption, and achieve the required resiliency to deal with them.

In this paper, decisions about different phases of crisis management cycle are modeled in the form of an integrated mathematical programming model based on the assumption of the real situation of the crisis. Goals are minimizing the number of injured people who are not serviced and minimizing the cost of relief supplies in affected areas. Simultaneous optimization of locating problems of relief bases, allocation of resources, distribution and delivery of relief supplies and evacuation of injured (pre and post-crisis situations) are among the innovations of this research. Therefore, scenarios based on existing faults (four faults) in region one of city of Tehran are considered. In this study, first, we present a binary integer programming model. To validate the model, the Epsilon Constraint method in software environment of GAMS with the Cplex solver has been used to solve the problem in small scale. To solve the problem in large scale, we have investigated a case study using the data of relief bases in region one of Tehran city. The case study was also investigated using non-dominant sorting Genetic approach. The results of the research show that the non-dominant sorting Genetic approach can solve the model with the least error than the exact solution and in less time.

Purpose of this research is to study criteria of sustainable supply chains in petrochemical industry. The research approach was both explorative and explanatory by using mixed methodologies for collection and analysis of data. It started with qualitative meta-synthesis of criteria of sustainable supply chains in former publications by using MAXQDA software. Afterwards, the identified criteria were quantitatively analyzed based on Delphi-fuzzy, DEMATEL and analytic network process (ANP) methodologies. Therefore, in this step the questionnaires was completed by 23 experts of Petrochemical industry, who were selected by purposive sampling. In total, fifteen criteria of sustainable supply chains were identified and classified. In the quantitative analysis, the three criteria of "organization & corporate-centric", "environmental management" and "environmental pressures" were rated as the most critical criteria. This study highlights the importance of criteria as well as the strength of interrelationships among criteria of sustainable supply chains in petrochemical industry. The research results can be beneficial for decision makers to prioritize their resources, actions, and strategies in steering supply chains sustainable development.

Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, inputs and outputs of reginal power companies are selected with artifitial neural network. The application of neural network in the selection of inputs and outputs of reginal power companies is not a precedent in the literature and it is considered the main advantage of the proposed method. In order to train two layers MLP neural network, after presenting of error resilience, learning method was used. After neural network training, neural network performance is examined by using the test set. RMSE value for 15 test set equals 0/0269 which reflects the high accuracy of training network. The Sensitivity Analysis of the studied parameters which are the same inputs and outputs of Data Envelopment Analysis, with ten percent increase of parameter, compared to the prior one was carried out and output relative error average for neural network parameters was calculated. Based on the output relative error average, inputs and outputs were determined. By comparing the efficiency scores of regional electricity companies before and after reducing the number of variables, it is noticed that the number of efficient companies during the above four periods decreased from 50 percent to 11 percent. Finally, the neural network application in inputs and outputs selection of the regional electricity companies was unprecedented in the literature and this is the main advantage of this method.

The purpose of this study is to investigate the impact of two important component of strategic cost management (SCM) (executional cost management and structural cost management) on financial performance. For this purpose, one specific context is investigated, namely environmental costs. The environmental costs reflect an ‘ executional’ aspect aimed at managing, controlling and optimizing costs for a given environmental strategy, but also a ‘ structural’ aspect based on their influence on the firm's cost structure notably in terms of product design, raw materials used and operational process design. Survey data have been collected on a sample of 126 Esfahan’ s manufacturing firms. In order to analyze the research hypotheses Pearson correlation matrix and the structural equation model were used. According to the research findings, tracking of environmental costs and implementation of environmental initiatives have significant effects on financial performance. Executional cost management (the tracking of environmental costs) and structural cost management (the implementation of environmental initiatives) are related to each other and they act together to contribute to financial performance. Finally, through improving the current cost structure and providing new initiatives regarding cost structure, the tracking of environmental costs has influence on financial performance.

Environmental concerns have spurred an interest in studying green supply chain. Nowadays, governmental and non-governmental organizations consider environmental management as a strategic requirement having numerous benefits. Therefore, they effort to increase customers' satisfaction and market share considering external factors like environmental consequences in addition to internal factors. In this paper, a bi-objective mixed integer programming model is developed to identify the optimal location for manufacturers and disassembly sites in a green supply chain network designed to address the role of the reliability (failures and operating) of facilities and vehicles to ensure effective stream among supply chain network, the objective functions are defined as total cost minimization, and total co2 emissions minimization. Besides, uncertainties on the network design are investigated through two-stage stochastic programming, with respect to the fact that the model is non-linear and bi-objective, at first, an approach is presented to linearize it and then the proposed bi-objective mathematical model is solved as a single-objective one by compromise programming method. The effectiveness of the proposed model is demonstrated by using of a numerical example derived from a real case.

In this study, a multi-objective mathematical model is developed to optimize the distribution network in a three level supply chain based on the inventory location-models with the aim of locating distribution centers. also, appropriate allocation of customers in order to maximize coverage of the demand, increasing sales through discount policies and ultimately improving the transportation system by selling the package of products agaainst individual sales is considered. On the other hand, the policy of selling pakages, Increases the total sales and their profit margin by creating appropriate price for the customrers. Due to the circumstances, each distribution center has specific reliability level which the proposed model try to maximize it. In order to make the model more realistic, some parameters have been considered under conditions of uncertainty and robust planning techniques have been used to solve it, finally, to validate the presented model, and instance according to real-world problems were solved by GAMS software. The Results are presented in details

This paper addresses the issue of horizontal strategy formulation, an essential part of corporate-level strategy, based on sharing resources among businesses. Therefore, in this study, a model was developed to evaluate the opportunities for sharing resources among businesses in order to facilitate strategic decision-making at the corporate-level. In line with the mentioned goal for designing a comprehensive model, literature was reviewed extensively and variables extracted from literature review and experience of industry experts were used to determine relationship between them in the form of dynamic approach leading to the creation of a dynamic model to evaluate sharing resources. This model includes affective factors on the process of sharing resources and their interaction that shows the dynamics of these factors over time. Model validity was done in the system dynamic approach via validation tests and computer simulations. Based on the obtained results, the validity of the model was confirmed for making decisions on resource sharing in multi-business firms