University of TehranIndustrial Management Journal2008-58854120120822Assessing Financial Risks of Power Plant Project Based on Three Dimensions ModelAssessing Financial Risks of Power Plant Project Based on Three Dimensions Model1147225610.22059/imj.2012.72256FAEzatAsgharizadehAssociate Prof., Faculty of Management Industrial, University of Tehran, Iran.0000-0001-7048-9065AzitaSaeediM.Sc. Faculty of Management Industrial, University of Tehran, Iran .Journal Article20190806Risk could jeopardize obtaining projects’ goals and risk management can be used for minimizing risks’ negative consequences. On the other hand, by using risk management, projects benefit positive risks’ outcome to optimizing final result. Financial aspect of a project is one of the main criteria uses for evaluating a project‘s success, so managing financial risks has high priority for project management team. As recognizing and assessing the risks is the first step of risk management, several methods have been proposed in different standards. This survey evaluates financial risks of construction a power plant by using a new method of risk assessment which is based on 3 criteria: probability, consequences and risk identification.Risk could jeopardize obtaining projects’ goals and risk management can be used for minimizing risks’ negative consequences. On the other hand, by using risk management, projects benefit positive risks’ outcome to optimizing final result. Financial aspect of a project is one of the main criteria uses for evaluating a project‘s success, so managing financial risks has high priority for project management team. As recognizing and assessing the risks is the first step of risk management, several methods have been proposed in different standards. This survey evaluates financial risks of construction a power plant by using a new method of risk assessment which is based on 3 criteria: probability, consequences and risk identification.https://imj.ut.ac.ir/article_72256_50da0cbe62421727dfba7cb30102959d.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Identify and Rank the Factors Affecting the Formation of the Agility Capabilities (Case study: The Automobile Trading Companies)Identify and Rank the Factors Affecting the Formation of the Agility Capabilities (Case study: The Automobile Trading Companies)15367225710.22059/imj.2012.72257FASeyed MohammadSeyedhosseiniProf. of Industrial Management, Islamic Azad University, Tehran, IranAliRajabzade GhatariAssociate Prof. of Tarbiat Modares University, Tehran, Iran.MahmoodAlborziAssociate Prof. Industrial Management, Islamic Azad University, Tehran, Iran.Seyed MostafaRazaviAssociate Prof., Faculty of Management, University of Tehran, Tehran, Iran.AliRamezniPh.D. Candidate of Industrial Management, Islamic Azad University, Science and Research Branch, Tehran, Iran.Journal Article20190806The present study intended to Identify and rank the factors affecting the formation of the agility capabilities in the automobile industry of Iran. Initially the theoretical principles were discussed. The data gathered in this stage provided us with the possibility to present a conceptual framework for the study. Subsequently, through interviewing with experts, some indices for evaluating the variables in the model were identified. On the following stage, a questionnaire was developed. The questionnaire included 116 items, based on a 7<strong><em>-</em></strong>point Likert scale. After determining the validity and reliability of the questionnaire, 250 experts in automobile industry, chosen by cluster sampling, completed the questionnaire. The results of the research revealed that agility capability, and the internal supply chain of the organizations were less affected by environmental factors than agility enablers. The environmental stimuli by means of agility enablers, supply chain processes, agility capabilities influence organizations. Moreover, using the delta model, the effect of environmental factors on strategic position that an organization finds for itself in the marketplace, was analyzed. And finally, the subsets of the main aspects of the model were prioritized through DEMATEL technique.The present study intended to Identify and rank the factors affecting the formation of the agility capabilities in the automobile industry of Iran. Initially the theoretical principles were discussed. The data gathered in this stage provided us with the possibility to present a conceptual framework for the study. Subsequently, through interviewing with experts, some indices for evaluating the variables in the model were identified. On the following stage, a questionnaire was developed. The questionnaire included 116 items, based on a 7<strong><em>-</em></strong>point Likert scale. After determining the validity and reliability of the questionnaire, 250 experts in automobile industry, chosen by cluster sampling, completed the questionnaire. The results of the research revealed that agility capability, and the internal supply chain of the organizations were less affected by environmental factors than agility enablers. The environmental stimuli by means of agility enablers, supply chain processes, agility capabilities influence organizations. Moreover, using the delta model, the effect of environmental factors on strategic position that an organization finds for itself in the marketplace, was analyzed. And finally, the subsets of the main aspects of the model were prioritized through DEMATEL technique.https://imj.ut.ac.ir/article_72257_699309cfdbdb31241939d9488f87f266.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822A New Mixed Integer Linear Model for Selecting the Most BCC-efficient DMUA New Mixed Integer Linear Model for Selecting the Most BCC-efficient DMU37507225810.22059/imj.2012.72258FAJournal Article20190806Finding a single efficient decision making unit (DMU) as the most efficient unit has interested in some situations, by decision maker (manager). Conventional data envelopment analysis (DEA) assists decision maker in distinguishing between efficient and inefficient units. However, DEA does not provide more information about the efficient DMUs. Hence, several methods were introduced to find the best single efficient DMU. Foroughi [9] introduce a mixed integer linear model for selecting the best decision making unit in constant returns to scale situation. In this paper, we extend this model and formulate a new mixed integer linear model for determining most BCC-efficient DMU by solving only one linear programming which is useful for variable returns to scale situation, so has wider range of application in the management and industrial affairs than previous model. The applicability of proposed model is illustrated, using a real data set consisting 19 facility layout designsFinding a single efficient decision making unit (DMU) as the most efficient unit has interested in some situations, by decision maker (manager). Conventional data envelopment analysis (DEA) assists decision maker in distinguishing between efficient and inefficient units. However, DEA does not provide more information about the efficient DMUs. Hence, several methods were introduced to find the best single efficient DMU. Foroughi [9] introduce a mixed integer linear model for selecting the best decision making unit in constant returns to scale situation. In this paper, we extend this model and formulate a new mixed integer linear model for determining most BCC-efficient DMU by solving only one linear programming which is useful for variable returns to scale situation, so has wider range of application in the management and industrial affairs than previous model. The applicability of proposed model is illustrated, using a real data set consisting 19 facility layout designshttps://imj.ut.ac.ir/article_72258_fe5f26d23cab543c2986ee7b7e1d7154.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Cross AHP/DEA method for ranking Decision Making UnitsCross AHP/DEA method for ranking Decision Making Units51687225910.22059/imj.2012.72259FAMohammadrezaAlirezaeeAssistant Prof. of IUST, Dep. of Mathematics, Tehran, IranSeyed AliRakhshanM.Sc. Student in Applied Mathematics, University of Science and Technology, Tehran, IranMohammadrezaRafiee SaniPh.D. Student in Applied Mathematics, University of Science and Technology, Tehran, IranJournal Article20190806All the basic models in Data Envelopment Analysis divide the Decision Making Units to two categories: efficient and inefficient. So, there is no separation for the efficient units. In The Analytical Hierarchy Process in spite of complete ranking of units, the process of pairwise comparison matrix making is based on experts’ ideas, causes error and inconsistency in resulted matrix. In this paper first we suggest a combined method called cross AHP/DEA method for ranking the units that not only uses the strength of The Analytical Hierarchy Process and Data Envelopment Analysis methods in presenting a rational ranking, but also covers the older methods problems noticeably and then we explained properties and advantages of our method in comparison to other methods. Finally, for better comparison we designed some numerical examples<strong>.</strong>All the basic models in Data Envelopment Analysis divide the Decision Making Units to two categories: efficient and inefficient. So, there is no separation for the efficient units. In The Analytical Hierarchy Process in spite of complete ranking of units, the process of pairwise comparison matrix making is based on experts’ ideas, causes error and inconsistency in resulted matrix. In this paper first we suggest a combined method called cross AHP/DEA method for ranking the units that not only uses the strength of The Analytical Hierarchy Process and Data Envelopment Analysis methods in presenting a rational ranking, but also covers the older methods problems noticeably and then we explained properties and advantages of our method in comparison to other methods. Finally, for better comparison we designed some numerical examples<strong>.</strong>https://imj.ut.ac.ir/article_72259_d437a7bd85a8d631cc5bc347823919c5.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Identifying and Prioritization Institutional Factors Influencing on Choosing Academic Researches Commercialization Strategies in NanotechnologyIdentifying and Prioritization Institutional Factors Influencing on Choosing Academic Researches Commercialization Strategies in Nanotechnology69747226010.22059/imj.2012.72260FAEsmaeelKalantariM.S. Student, Faculty of Entrepreneurship, Tehran University, Iran.MohammadrezaMeygoon PooriAssistant Prof., Faculty of Entrepreneurship, Tehran University, Iran.Journal Article20190806Locating in the world’s twelfth position in nano-science production, Islamic Republic of Iran can achieve a suitable place in the commercialization and wealth creation of nanotechnology. This research aims to identify and prioritize institutional factors influence choosing of academic researches commercialization strategy in nanotechnology. This research is applicable from purpose point of view and is qualitative - quantitative from point of data collection. The statistical population of the qualitative research part are academic experts and of quantitative part are companies active in nanotechnology. Data collection was conducted through interviews in qualitative part and through questionnaire in quantitative part, and also data analysis methods were primary, open, axial and selective coding in qualitative part and confirmatory factor analysis and paired comparison in quantitative part. The findings show that six institutional factors affect choosing academic research commercialization strategies for nanotechnology in Iran which are history background and contracts of university, university culture, supporting institutions, university goals and missions, university’s social capital and university policies in priority order. The six factors have been identified and prioritized in 20 sub-factorsLocating in the world’s twelfth position in nano-science production, Islamic Republic of Iran can achieve a suitable place in the commercialization and wealth creation of nanotechnology. This research aims to identify and prioritize institutional factors influence choosing of academic researches commercialization strategy in nanotechnology. This research is applicable from purpose point of view and is qualitative - quantitative from point of data collection. The statistical population of the qualitative research part are academic experts and of quantitative part are companies active in nanotechnology. Data collection was conducted through interviews in qualitative part and through questionnaire in quantitative part, and also data analysis methods were primary, open, axial and selective coding in qualitative part and confirmatory factor analysis and paired comparison in quantitative part. The findings show that six institutional factors affect choosing academic research commercialization strategies for nanotechnology in Iran which are history background and contracts of university, university culture, supporting institutions, university goals and missions, university’s social capital and university policies in priority order. The six factors have been identified and prioritized in 20 sub-factorshttps://imj.ut.ac.ir/article_72260_9bd61ccd81ace4b1fe95588a7cc636b4.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Contractor Selection Using a Combination of Multi Attribute Utility Theory and "Electre I" Method in MAPNA CoContractor Selection Using a Combination of Multi Attribute Utility Theory and "Electre I" Method in MAPNA Co851087226110.22059/imj.2012.72261FAAliMohaggharAssociate Prof., Faculty of Management, University of Tehran, Iran.KavehKashiMaster of Industrial Management, University of Tehran, Iran.HadiSalamiExpert of Systems Engineering & Productivity in South Zagros Company of Oil &Gas Production.Journal Article20190806The over-increasing speed of development has made the issue and process of contractor selection an important factor in success of industrial projects in the form of desirable quality, cost and time (duration). This paper presents a model for contractor selection in construction projects by combining Multi Attribute Utility Theory (MAUT) and "Electre I" method. In this regard, while studying the background and history of the issue, related criteria and sub-criteria are identified and classified. Then, using views of experts, major criteria and sub-criteria and also their analogous weights are determined. In next step, based on minimum and maximum utility quantities in each sub-criterion and assuming neutrality of viewpoint of decision maker in relation to risk, single sub-criterion utility functions are computed. Using these functions, utility quantities analogous with levels and quantities of criteria in each of the decision alternatives are determined and decision matrix is formed based on these utilities. Then using Electre I method, decision alternatives are ranked. Based on findings of this research, in order to achieve long-term benefits of organizations, the contractor selection shall be done based on a comprehensive set of criteria and sub-criteria. While utilizing strength points of each of the two methods by combining Multi Attribute Utility Theory (MAUT) and Electre I method, an applied model with correct and accurate output for contractor selection in construction projects is developed.The over-increasing speed of development has made the issue and process of contractor selection an important factor in success of industrial projects in the form of desirable quality, cost and time (duration). This paper presents a model for contractor selection in construction projects by combining Multi Attribute Utility Theory (MAUT) and "Electre I" method. In this regard, while studying the background and history of the issue, related criteria and sub-criteria are identified and classified. Then, using views of experts, major criteria and sub-criteria and also their analogous weights are determined. In next step, based on minimum and maximum utility quantities in each sub-criterion and assuming neutrality of viewpoint of decision maker in relation to risk, single sub-criterion utility functions are computed. Using these functions, utility quantities analogous with levels and quantities of criteria in each of the decision alternatives are determined and decision matrix is formed based on these utilities. Then using Electre I method, decision alternatives are ranked. Based on findings of this research, in order to achieve long-term benefits of organizations, the contractor selection shall be done based on a comprehensive set of criteria and sub-criteria. While utilizing strength points of each of the two methods by combining Multi Attribute Utility Theory (MAUT) and Electre I method, an applied model with correct and accurate output for contractor selection in construction projects is developed.https://imj.ut.ac.ir/article_72261_cafaf585a242bca648fd6f1d91470727.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Integrated Interpretive Structural Modeling with Fuzzy Network Analysis to Locating Service Centers (ISN / FANP)Integrated Interpretive Structural Modeling with Fuzzy Network Analysis to Locating Service Centers (ISN / FANP)1091287226210.22059/imj.2012.72262FADarioshMohammadi ZanjiraniAssistant Prof., University of Isfahan, Iran0000-0002-2987-6765GolamrezaAsgariAssistant Prof., University of Malek Ashtar, IranRezaSheikhAssistant Prof., University of Shahrood, Iran.Journal Article20190806Survey conducted suggests that few studies on Locating service centers especially hospitals, have been. Moreover, in the few existing studies, has focus on the use of quantitative indicators. It seems the reason is ambiguous and inaccurateness of qualitative index. This paper attempts to show the ability to deal with the ambiguity within qualitative index by use of fuzzy logic. Also, using network analytic process appropriate response is given. On the issue such as correlations of criteria's and mutual influences between them in choosing the place of an hospital. Since the network analysis process uses the Delphi method for combining experts opinion, So data has changed at mod form, To overcome this problem and developing network analytical process, interpretive structural modeling is used. The results of the proposed methodology in a case study show its favorable ability to execute as a scientific methodology for Locating of services units, although the numerical calculations and time of the fuzzy section will be high.Survey conducted suggests that few studies on Locating service centers especially hospitals, have been. Moreover, in the few existing studies, has focus on the use of quantitative indicators. It seems the reason is ambiguous and inaccurateness of qualitative index. This paper attempts to show the ability to deal with the ambiguity within qualitative index by use of fuzzy logic. Also, using network analytic process appropriate response is given. On the issue such as correlations of criteria's and mutual influences between them in choosing the place of an hospital. Since the network analysis process uses the Delphi method for combining experts opinion, So data has changed at mod form, To overcome this problem and developing network analytical process, interpretive structural modeling is used. The results of the proposed methodology in a case study show its favorable ability to execute as a scientific methodology for Locating of services units, although the numerical calculations and time of the fuzzy section will be high.https://imj.ut.ac.ir/article_72262_def3f0662242982342a74ace0d658f9b.pdfUniversity of TehranIndustrial Management Journal2008-58854120120822Identify Key Factors in the Data Envelopment Analysis (DEA) for Evaluating University Departments by Using Soft System Methodology (SSM)Identify Key Factors in the Data Envelopment Analysis (DEA) for Evaluating University Departments by Using Soft System Methodology (SSM)1291467226310.22059/imj.2012.72263FAMohammadrezaMehreganAssociate Prof. of Management Faculty, University of Tehran, Iran.MohammadAbooyee ArdakanAssociate Prof. of Management Faculty, University of Tehran, Iran.NedaSoltan MohammadiM.Sc. In Industrial Management, Management Faculty, University of Tehran, Iran.Journal Article20190806Performance assessment of organizations and its subsets in order to achieve higher productivity and progress of organization is an undeniable necessity. In the Competitive world of the twenty-first era universities and higher educational institutions are one of the most important service organizations that can play an important role in the progress and development of society. Therefore, performance assessment of higher education system requires a suitable model that is able to provide a clear picture of their efficiency. Data Envelopment Analysis (DEA) is one of the most popular methods of efficacy measurement of organizations, especially in service organizations, but definition of inputs and outputs in DEA, according to disagreement among key stakeholders, and defining an agreed model is not easy. Thus, this study employed seven stages of Peter Chekland's Soft System Methodology (SSM) to identify suitable indicators for evaluating university departments of Management Faculty of Tehran University and finally determined the relative importance of the DEA inputs and outputs indicators by using Analytical Hierarchy Process (AHP).Performance assessment of organizations and its subsets in order to achieve higher productivity and progress of organization is an undeniable necessity. In the Competitive world of the twenty-first era universities and higher educational institutions are one of the most important service organizations that can play an important role in the progress and development of society. Therefore, performance assessment of higher education system requires a suitable model that is able to provide a clear picture of their efficiency. Data Envelopment Analysis (DEA) is one of the most popular methods of efficacy measurement of organizations, especially in service organizations, but definition of inputs and outputs in DEA, according to disagreement among key stakeholders, and defining an agreed model is not easy. Thus, this study employed seven stages of Peter Chekland's Soft System Methodology (SSM) to identify suitable indicators for evaluating university departments of Management Faculty of Tehran University and finally determined the relative importance of the DEA inputs and outputs indicators by using Analytical Hierarchy Process (AHP).https://imj.ut.ac.ir/article_72263_77036b0e57e2daef7397ffacb047e6a9.pdf