Shahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220An Integrated Multi-Objective Model for Project Portfolio Selection and Risk Response Actions PlanningAn Integrated Multi-Objective Model for Project Portfolio Selection and Risk Response Actions Planning93287157FAGhasemMokhtariAssistant Professor, University of Qom.YounesHasanzadehMSc., University of Qom.Journal Article20190918 Project portfolio selection and risk response selection are two issues that have been considered disjointedly by the researchers. In this study, an integrated mathematical model is presented for the above-mentioned problems. A situation is noticed in which, in the stage of selecting the project portfolio, some of the proposed projects are facing risks, and some actions can be planned to mitigate these risks. With regard to the fact that implementing these responses requires resources and changes the risk of the portfolio, it is essential to consider the selection of responses at the stage of portfolio selection. A bi-objective mathematical model is proposed, whose first objective is to maximize the profit earned from selected projects, and its second objective is to minimize portfolio risk. Profit variance is considered as a measure of portfolio risk. A numerical example, illustrates the model application and the difference between the integrated and non-integrative approaches. Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to solve the model. Project portfolio selection and risk response selection are two issues that have been considered disjointedly by the researchers. In this study, an integrated mathematical model is presented for the above-mentioned problems. A situation is noticed in which, in the stage of selecting the project portfolio, some of the proposed projects are facing risks, and some actions can be planned to mitigate these risks. With regard to the fact that implementing these responses requires resources and changes the risk of the portfolio, it is essential to consider the selection of responses at the stage of portfolio selection. A bi-objective mathematical model is proposed, whose first objective is to maximize the profit earned from selected projects, and its second objective is to minimize portfolio risk. Profit variance is considered as a measure of portfolio risk. A numerical example, illustrates the model application and the difference between the integrated and non-integrative approaches. Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to solve the model.https://jimp.sbu.ac.ir/article_87157_f02131f00cdda3f75eb8b32a5e6fe902.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220An Investigation on the Factors Affecting the Success of Knowledge Transfer Process in Inter-Firm Collaborations (Case: Pharmaceutical Firm Collaborations)An Investigation on the Factors Affecting the Success of Knowledge Transfer Process in Inter-Firm Collaborations (Case: Pharmaceutical Firm Collaborations)336087158FANimaMokhtarzadehAssistant Professor, University of Tehran.Seyed MoustafaRazaviAssociate Professor, University of Tehran.HadiNilforooshanAssistant Professor, University of Shahid Beheshti.MaryamFagheiPh.D Student, University of Tehran.Journal Article20190918 Today, competitive advantage of organizations depends mostly on their access to knowledge resources. Rapid development of knowledge and expansion of knowledge resources among different organizations make it difficult for organizations to access knowledge on their own. This obliges organizations to cooperate with each other in order to acquire their knowledge needs. Statistics indicate an increase in strategic collaboration with the aim of acquiring knowledge, especially in knowledge-based industries such as the pharmaceutical industry. There is an extensive literature on factors affecting the processes of knowledge transfer and learning in collaborations; however, so far no comprehensive study has been done in this regard. This study aimed to identify and investigate factors affecting the success of knowledge transfer and learning in strategic collaborations between Iranian pharmaceutical companies. Following the detailed review of previous studies, ten factors affecting the knowledge transfer process were extracted and categorized into two categories: factors at the level of organization, and factors at the level of cooperation. Finally, the importance of them was explained using the opinions of managers of some pharmaceutical companies engaged in strategic cooperation. Results indicate that "Organizational strategy" is the most influential factor and "social capital" is the most important factor. Today, competitive advantage of organizations depends mostly on their access to knowledge resources. Rapid development of knowledge and expansion of knowledge resources among different organizations make it difficult for organizations to access knowledge on their own. This obliges organizations to cooperate with each other in order to acquire their knowledge needs. Statistics indicate an increase in strategic collaboration with the aim of acquiring knowledge, especially in knowledge-based industries such as the pharmaceutical industry. There is an extensive literature on factors affecting the processes of knowledge transfer and learning in collaborations; however, so far no comprehensive study has been done in this regard. This study aimed to identify and investigate factors affecting the success of knowledge transfer and learning in strategic collaborations between Iranian pharmaceutical companies. Following the detailed review of previous studies, ten factors affecting the knowledge transfer process were extracted and categorized into two categories: factors at the level of organization, and factors at the level of cooperation. Finally, the importance of them was explained using the opinions of managers of some pharmaceutical companies engaged in strategic cooperation. Results indicate that "Organizational strategy" is the most influential factor and "social capital" is the most important factor.https://jimp.sbu.ac.ir/article_87158_03f09407a274eca5093cec672440c884.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220Development of Multi Objective Multi Period Closed-Loop Supply Chain Network Model Considering Uncertain Demand and CapacityDevelopment of Multi Objective Multi Period Closed-Loop Supply Chain Network Model Considering Uncertain Demand and Capacity619587159FASadeghFeizollahi*Ph.D. student, Departmant of Management, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.HeirshSoltanpanahAssistant Professor, Departmant of Management, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.HiwaFarughiAssistant Professor, Department of Industrial Engineering, University of Kurdistan.AyubRahimzadehAssistant Professor, Department of Industrial Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.Journal Article20190918 Today, the discussion about the reuse of consumer products has particular importance. Since the closed loop supply chain is not only streaming but also includes reverse flow, companies are successful that integrate between direct and reverse supply chain. This paper model is multi-objective, multilevel, multi-disciplinary, and single-product in uncertain conditions. The objective functions of the model include minimizing costs, increasing the revenues from the recycled product, reducing the negative environmental effects of production, transportation and recycling of the product. To solve the problem, the approach TH, which is a method for converting multi-objective functions to single-objective, has been used. Numerical examples have been designed and solved for validating the proposed model. To study the application of the model, a case study was conducted on trolleys product in one of the hospitals industry companies in Tehran. To assess the effect of changes in the parameters affecting the improvement of objectives, sensitivity analysis on budget parameters, production capacity and uncertainty coefficient have been made. The results show the significant impact of production and budget on increasing the profit from recycled parts as well as the effect of fuzzy demand coefficient on the objective of cost and environmental effects which is increasing. Today, the discussion about the reuse of consumer products has particular importance. Since the closed loop supply chain is not only streaming but also includes reverse flow, companies are successful that integrate between direct and reverse supply chain. This paper model is multi-objective, multilevel, multi-disciplinary, and single-product in uncertain conditions. The objective functions of the model include minimizing costs, increasing the revenues from the recycled product, reducing the negative environmental effects of production, transportation and recycling of the product. To solve the problem, the approach TH, which is a method for converting multi-objective functions to single-objective, has been used. Numerical examples have been designed and solved for validating the proposed model. To study the application of the model, a case study was conducted on trolleys product in one of the hospitals industry companies in Tehran. To assess the effect of changes in the parameters affecting the improvement of objectives, sensitivity analysis on budget parameters, production capacity and uncertainty coefficient have been made. The results show the significant impact of production and budget on increasing the profit from recycled parts as well as the effect of fuzzy demand coefficient on the objective of cost and environmental effects which is increasing.https://jimp.sbu.ac.ir/article_87159_c851819c15942e6830b94b7e27d9c49f.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220Analysis of Causal Relationships between Green Productivity Indicators with Fuzzy Cognitive Mapping ApproachAnalysis of Causal Relationships between Green Productivity Indicators with Fuzzy Cognitive Mapping Approach9711987160FAMehdiNikshapooriMSc. Student, University of Hormozgan.TayebehAbbasnejadAssistant professor, University of Hormozgan.RezaAhmadi KahnaliAssociate Professor, University of Hormozgan.Journal Article20190918Green productivity is a sustainable development approach. The purpose of this study is to identify green productivity Indicatorsand to determine the relationships between Indicatorsto present the model through fuzzy cognitive mapping. The fuzzy cognitive mapping method used in this research is based on the Rodriguez-Repcio and et al. (2007) automated FCM. The statistical population of the study included all the experts of Plastonic Company. Green productivity indicators were identified through Literature review. Fuzzy cognitive mapping was created Using four matrices, Initial Influence Matrix, fuzzified Influence Matrix, Strength of Influence Relationships Matrix, Final Matrix of Influence and the software Mental Modeler. The cognitive mapping represents the relationships between the green productivity Indicatorsand the weights among them. According to the model, four policy or scenarios were designed in software to identify the relative changes of each indicator. Finally, the fourth scenario with the most positive impact on other indicators was selected as the best scenario among the designed scenarios.Green productivity is a sustainable development approach. The purpose of this study is to identify green productivity Indicatorsand to determine the relationships between Indicatorsto present the model through fuzzy cognitive mapping. The fuzzy cognitive mapping method used in this research is based on the Rodriguez-Repcio and et al. (2007) automated FCM. The statistical population of the study included all the experts of Plastonic Company. Green productivity indicators were identified through Literature review. Fuzzy cognitive mapping was created Using four matrices, Initial Influence Matrix, fuzzified Influence Matrix, Strength of Influence Relationships Matrix, Final Matrix of Influence and the software Mental Modeler. The cognitive mapping represents the relationships between the green productivity Indicatorsand the weights among them. According to the model, four policy or scenarios were designed in software to identify the relative changes of each indicator. Finally, the fourth scenario with the most positive impact on other indicators was selected as the best scenario among the designed scenarios.https://jimp.sbu.ac.ir/article_87160_c3cfda7ea76c135a8b68735100f58987.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220A Multi-Objective Robust Optimization Logistics Model in Times of Crisis under UncertaintyA Multi-Objective Robust Optimization Logistics Model in Times of Crisis under Uncertainty12114787161FANavidNikjooM.Sc., Mazandaran University of Science and Technology.NikbakhshJavadianAssociate Professor, Mazandaran University of Science and Technology.Journal Article20190918Every year, the crisis in human societies is growing up in type, number and severity, so today crisis management is considered an important topic for research and research in all countries. In this study, a proposed multi-objective mathematical model under uncertainty conditions. The model seeks to find the optimal facility location and allocation of goods between the facility and the allocation of injured to hospitals also Looking for an optimal route to bring human resources to damaged areas to achieve goals such as reducing costs, distributing goods and fair medical assistance between areas, and reducing the time that aid troops arrive in damaged areas.The existing model focuses on the severity of incident uncertainty and this uncertainty in the severity of the accident, which causes uncertainty about the amount of demand for goods and manpower, and the amount of damage and injuries is based on a scenario-based method based approach Robust optimization in the model and because of the multi-purpose of the model, with the help of one of the single-purpose methods, the model is made single-purposeand finally, the model in this study was solved in a case study to prove its accuracy and effectiveness was investigated.Every year, the crisis in human societies is growing up in type, number and severity, so today crisis management is considered an important topic for research and research in all countries. In this study, a proposed multi-objective mathematical model under uncertainty conditions. The model seeks to find the optimal facility location and allocation of goods between the facility and the allocation of injured to hospitals also Looking for an optimal route to bring human resources to damaged areas to achieve goals such as reducing costs, distributing goods and fair medical assistance between areas, and reducing the time that aid troops arrive in damaged areas.The existing model focuses on the severity of incident uncertainty and this uncertainty in the severity of the accident, which causes uncertainty about the amount of demand for goods and manpower, and the amount of damage and injuries is based on a scenario-based method based approach Robust optimization in the model and because of the multi-purpose of the model, with the help of one of the single-purpose methods, the model is made single-purposeand finally, the model in this study was solved in a case study to prove its accuracy and effectiveness was investigated.https://jimp.sbu.ac.ir/article_87161_fd5f36b69014cdbb629b7458f490e5c3.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220Performance Optimization of Industrial Units in Crisis Considering Economic Resilience Factors: A Case Study of a Petrochemical PlantPerformance Optimization of Industrial Units in Crisis Considering Economic Resilience Factors: A Case Study of a Petrochemical Plant14918387162FAShimaPahsapourPhD. Student, University of Tehran.AliBozorgi AmiriAssistant Professor, University of Tehran.Seyed FaridGhaderiProfessor, University of Tehran.Journal Article20190918Organizations usually confront with disruptive incidents. The ability of an organization to reduce the losses caused by these incidents is referred to economic resilience. In this research, the performance of a petrochemical plant is investigated in case of a crisis. At first, based on a comprehensive literature review, a conceptual framework for organizational economic resilience is developed. A structured questionnaire is provided and distributed among the staff of a petrochemical plant as a real case study. Then, an uncertain Data Envelopment Analysis (DEA) model is employed to identify the efficient units of the petrochemical plant. At the end, a sensitivity analysis is performed to examine the importance of each factor in building economic resilience in the plant. This is the first study that presents an integrated qualitative-quantitative approach including a conceptual model for economic resilience and a DEA model in uncertain conditions in the whole supply chain of a petrochemical plant.Organizations usually confront with disruptive incidents. The ability of an organization to reduce the losses caused by these incidents is referred to economic resilience. In this research, the performance of a petrochemical plant is investigated in case of a crisis. At first, based on a comprehensive literature review, a conceptual framework for organizational economic resilience is developed. A structured questionnaire is provided and distributed among the staff of a petrochemical plant as a real case study. Then, an uncertain Data Envelopment Analysis (DEA) model is employed to identify the efficient units of the petrochemical plant. At the end, a sensitivity analysis is performed to examine the importance of each factor in building economic resilience in the plant. This is the first study that presents an integrated qualitative-quantitative approach including a conceptual model for economic resilience and a DEA model in uncertain conditions in the whole supply chain of a petrochemical plant.https://jimp.sbu.ac.ir/article_87162_60dc504c1b81d5b86534d0d314330afe.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98748420190220A Hybrid Approach to Asses Contributing Factors in Supply Chain Competitiveness in Rubber IndustryA Hybrid Approach to Asses Contributing Factors in Supply Chain Competitiveness in Rubber Industry18521287163FASaeidSadeghi DarvazehPh.D Student, Allameh Tabataba'i University.AbbasShoulAssistant Professor, Vali-e-Asr University, Rafsanjan.NedaRasouliM.A., University of Tehran.Journal Article20190918 The main aim of this research is to asses contributing factors in supply chain competitiveness in rubber industry. To this point, first, using the extended review in literature of competitiveness, components were identified and conceptual model of research was presented. Data were collected from managers and experts of 5 Iranian rubber manufacturers. To analyze the data and testing the proposed model in statistical phase of research, partial least squares (PLS) method, and to prioritizing contributing factors in supply chain competitiveness a hybrid approach was used and Path coefficients of PLS and weights of BWM and FUZZY AHP were combined. The results of statistical phase of research indicate that “supply chain partnership”, “knowledge management process capability”, “green supply chain management”, and “supplier segmentation” have a significant positive effect on supply chain competitiveness. The results of prioritizing contributing factors in supply chain competitiveness using MCDM methods indicate that “partnership in finance” is the most important factor in supply chain competitiveness and after that, “knowledge application” and “partnership in R&D” were located in second and third priority. Finally some practical strategies for managers are discussed and some suggestions for future research are provided. The main aim of this research is to asses contributing factors in supply chain competitiveness in rubber industry. To this point, first, using the extended review in literature of competitiveness, components were identified and conceptual model of research was presented. Data were collected from managers and experts of 5 Iranian rubber manufacturers. To analyze the data and testing the proposed model in statistical phase of research, partial least squares (PLS) method, and to prioritizing contributing factors in supply chain competitiveness a hybrid approach was used and Path coefficients of PLS and weights of BWM and FUZZY AHP were combined. The results of statistical phase of research indicate that “supply chain partnership”, “knowledge management process capability”, “green supply chain management”, and “supplier segmentation” have a significant positive effect on supply chain competitiveness. The results of prioritizing contributing factors in supply chain competitiveness using MCDM methods indicate that “partnership in finance” is the most important factor in supply chain competitiveness and after that, “knowledge application” and “partnership in R&D” were located in second and third priority. Finally some practical strategies for managers are discussed and some suggestions for future research are provided.https://jimp.sbu.ac.ir/article_87163_af95d5ed0335d288642ddf5c336eb76e.pdf