Allameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120320Agility Evaluation by Using Verbal Variables in Fuzzy Logic and Ranking Fuzzy Numbers by Using Central Gravity Point Technique and Topsis
(Case study: Yazd Alloy Steel Company)Agility Evaluation by Using Verbal Variables in Fuzzy Logic and Ranking Fuzzy Numbers by Using Central Gravity Point Technique and Topsis
(Case study: Yazd Alloy Steel Company)1224537FAAliMohagharAliMorvoti SharifabadiSeyed AbdolazizYonesifarJournal Article20101116In this article we try to collect all opinions of previous researchers in agility evaluation field and to provide a new method for evaluating agility by using Fuzzy logic. First, the structure’s agility level is evaluated by using FAI method. Due to the ranking Fuzzy numbers’ role and importance in making decisions, then the Fuzzy numbers are ranked by using central gravity point technique and Topsis. In fact, this leads to identifying those factors which caused the structure agility reduction. This method would help managers in making decisions.In this article we try to collect all opinions of previous researchers in agility evaluation field and to provide a new method for evaluating agility by using Fuzzy logic. First, the structure’s agility level is evaluated by using FAI method. Due to the ranking Fuzzy numbers’ role and importance in making decisions, then the Fuzzy numbers are ranked by using central gravity point technique and Topsis. In fact, this leads to identifying those factors which caused the structure agility reduction. This method would help managers in making decisions.https://jims.atu.ac.ir/article_4537_ae7527c25b518a0d56b2b8e9fcf75076.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Studying the determinants of productivity in Iranian Manufacturing IndustriesStudying the determinants of productivity in Iranian Manufacturing Industries23434538FAMohammad GholiYousefiAsgharMobarakJournal Article20110104The purpose of this paper has been to study the main determinants of productivity in manufacturing industries of Iran. The main emphasize has been on the role of institutions .We have used productivity in two digit manufacturing industries based on ISIC classification as dependent variable ,and expenditures on R&D, ,Manufactured Exports ,Investment on Manufacturing Industries and Square of employment as Firm Size in addition to Institutions for which we have taken the variables such as number of court litigation documents regarding property rights, security and aggression, transparency in law and order and corruption as explanatory variables for the changes in total factor productivity during the Period 1374-1386.The results show that while the coefficients for all other variables were positive and Significant. The coefficients of Institutions were ,however negative and statistically significant for all the institutional variables, indicating that institutions in Iran reduces opportunity and incentive for industrial investment and thereby acting as important hindrance factors for the growth of industrial productivity.The purpose of this paper has been to study the main determinants of productivity in manufacturing industries of Iran. The main emphasize has been on the role of institutions .We have used productivity in two digit manufacturing industries based on ISIC classification as dependent variable ,and expenditures on R&D, ,Manufactured Exports ,Investment on Manufacturing Industries and Square of employment as Firm Size in addition to Institutions for which we have taken the variables such as number of court litigation documents regarding property rights, security and aggression, transparency in law and order and corruption as explanatory variables for the changes in total factor productivity during the Period 1374-1386.The results show that while the coefficients for all other variables were positive and Significant. The coefficients of Institutions were ,however negative and statistically significant for all the institutional variables, indicating that institutions in Iran reduces opportunity and incentive for industrial investment and thereby acting as important hindrance factors for the growth of industrial productivity.https://jims.atu.ac.ir/article_4538_118abd0fc363d8973ecd17cdc897ca63.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327A New Methodology for Solving Multi-criteria Decision Making ProblemA New Methodology for Solving Multi-criteria Decision Making Problem45654539FAMaghsoudAmiriMohsenRahimi Mazrae ShahiHamidTaboliJournal Article20091110This article suggests a new method for solving multi-criteria decision making issues. The method has been designed by simple but rational mathematical logic based on a specific geometric definition of the options. Understandable content as well as algorithm simplicity and simplified process are the rich standing points of the approach. Such problems have always had a brand-new geometric approach whilst the calculations involved in this method are benefiting from the lack of complex and complicated steps and the essential patronized path. Categorizing the enriched method's significances, we may finally come up with the availability of graphical model provided for the users. The users are properly enabled to enlighten presenting a geometric logic.This article suggests a new method for solving multi-criteria decision making issues. The method has been designed by simple but rational mathematical logic based on a specific geometric definition of the options. Understandable content as well as algorithm simplicity and simplified process are the rich standing points of the approach. Such problems have always had a brand-new geometric approach whilst the calculations involved in this method are benefiting from the lack of complex and complicated steps and the essential patronized path. Categorizing the enriched method's significances, we may finally come up with the availability of graphical model provided for the users. The users are properly enabled to enlighten presenting a geometric logic.https://jims.atu.ac.ir/article_4539_83fba946eecc20e1b82f98da56bb9e03.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Designing a Decision Support System for Customer EvaluationDesigning a Decision Support System for Customer Evaluation67844540FAMehdiSeifbarghyCheroZiaei NaghshbandiJournal Article20091214In this paper, a Decision Support System (DSS) is developed in order to evaluate customers. The addressed system can specially be applied in captive markets. This paper extends Chamodrakas et al. [8] in which the customer evaluation in order to customer selection is executed using a fuzzy TOPSIS method. The proposed DSS includes 6 different models and the user can select among them. The system is coded utilizing C# programming language. To present the system performance, some parts of the system are presented along with a numerical problem.In this paper, a Decision Support System (DSS) is developed in order to evaluate customers. The addressed system can specially be applied in captive markets. This paper extends Chamodrakas et al. [8] in which the customer evaluation in order to customer selection is executed using a fuzzy TOPSIS method. The proposed DSS includes 6 different models and the user can select among them. The system is coded utilizing C# programming language. To present the system performance, some parts of the system are presented along with a numerical problem.https://jims.atu.ac.ir/article_4540_3e2af834e6a1260957ac0eddfb8fb8cc.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Application of Artificial Neural Networks in Allocating GrantApplication of Artificial Neural Networks in Allocating Grant851144541FADavoodHoseinpourKhatereHajinouriJournal Article20100117The grant allocation section was one of the subjects that have confronted problems and challenges. Universities and higher education head office as education problems administrators’ encounter. Programs related to grant allocation more than other organizations that is because of the demand ever-increasing for education, ambiguity, diversity of opinions in research priorities, and not being clearly specified in outcomes. So identification of appropriate criteria for grant Hopfield allocation and attempt on theirs optimum allocation by using intelligent systems like artificial neural networks have been necessary that these networks successes in quality improvement in financial decisions. In this research, at first, by grant Hopfild allocation regulation of ministry of since & Allameh tabatabae’i & Tehran & Shahid Beheshti & Amir Kabir universities, those allocation criteria which are confirmed in those universities were appointed. Then, allocation criteria which are appointed from the viewpoint on the assistant in research become identified through completion questionnaires by them. Finally, in order to designing the method of grant Hopfield allocation, patterned outcome criteria enter in MATLAB software and the appropriate pattern obtained through Hopfield network.The grant allocation section was one of the subjects that have confronted problems and challenges. Universities and higher education head office as education problems administrators’ encounter. Programs related to grant allocation more than other organizations that is because of the demand ever-increasing for education, ambiguity, diversity of opinions in research priorities, and not being clearly specified in outcomes. So identification of appropriate criteria for grant Hopfield allocation and attempt on theirs optimum allocation by using intelligent systems like artificial neural networks have been necessary that these networks successes in quality improvement in financial decisions. In this research, at first, by grant Hopfild allocation regulation of ministry of since & Allameh tabatabae’i & Tehran & Shahid Beheshti & Amir Kabir universities, those allocation criteria which are confirmed in those universities were appointed. Then, allocation criteria which are appointed from the viewpoint on the assistant in research become identified through completion questionnaires by them. Finally, in order to designing the method of grant Hopfield allocation, patterned outcome criteria enter in MATLAB software and the appropriate pattern obtained through Hopfield network.https://jims.atu.ac.ir/article_4541_5d8e6309ce4bec6e36276cbf141f8629.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Identify and prioritize the factors affecting SME’S competitiveness of The Sistan and Balouchestan Fishery’s Industrial Cluster using the Analytic Network ProcessIdentify and prioritize the factors affecting SME’S competitiveness of The Sistan and Balouchestan Fishery’s Industrial Cluster using the Analytic Network Process1151394569FAHabibollahSalarzehiJasemDejkamJournal Article20101109Industrial clustering is of a great importance in almost every country throughout the world nowadays. In Iran, accordingly, there has been an increase in the tendency towards industrial clustering in the scientific and decision-making centers as well as the country’s development programs. The unavoidable competitive necessity is the most important issue in clustering and cluster-related policies. In fact, competitiveness is the thermometer of assessing and measuring the success of clustering. The study is devoted to review of literature under “competitiveness”. Next, industrial clusters and competitiveness assessment models in clusters is brought under deeper consideration. Later, Chabahar Fishery’s industrial cluster in the GEM model framework along with its factors used for identifying influential factors in the competitiveness of industrial clusters reviewed is introduced. GEM model is reviewed and applied to identify the important factors on competitiveness in Chabahar Fishery’s industrial cluster. Due to the large number of factors involved, factor prioritization questionnaire s were provided and passed out among experts of the Chabahar Fishery’s Industrial Cluster. Then influential factors were identified and since some of the factors were interrelated, the relative importance of these influential factors was investigated using ANP technique. Here, the prioritization of these factors was done by Super Decision software and in the end based on the acquired results, there have been proposed some strategies for the purpose of increasing competitiveness in Chabahar Fishery’s industrial cluster.Industrial clustering is of a great importance in almost every country throughout the world nowadays. In Iran, accordingly, there has been an increase in the tendency towards industrial clustering in the scientific and decision-making centers as well as the country’s development programs. The unavoidable competitive necessity is the most important issue in clustering and cluster-related policies. In fact, competitiveness is the thermometer of assessing and measuring the success of clustering. The study is devoted to review of literature under “competitiveness”. Next, industrial clusters and competitiveness assessment models in clusters is brought under deeper consideration. Later, Chabahar Fishery’s industrial cluster in the GEM model framework along with its factors used for identifying influential factors in the competitiveness of industrial clusters reviewed is introduced. GEM model is reviewed and applied to identify the important factors on competitiveness in Chabahar Fishery’s industrial cluster. Due to the large number of factors involved, factor prioritization questionnaire s were provided and passed out among experts of the Chabahar Fishery’s Industrial Cluster. Then influential factors were identified and since some of the factors were interrelated, the relative importance of these influential factors was investigated using ANP technique. Here, the prioritization of these factors was done by Super Decision software and in the end based on the acquired results, there have been proposed some strategies for the purpose of increasing competitiveness in Chabahar Fishery’s industrial cluster.https://jims.atu.ac.ir/article_4569_c9c0e484cc4aa0ba375d43f164cd8b22.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Influencing Factors on Export Target Market Selection in Iranian Electrical IndustryInfluencing Factors on Export Target Market Selection in Iranian Electrical Industry1411604570FAZohrehDehdashti ShahrokhHosseinJafariJournal Article20091026One of the most important concepts of international marketing is export target market selection which is the first stage of internationalization process. This paper studies the factors influencing export target market selection in Iranian electrical industry. The factors categorized in 6 dimensions such as politics, market potential, economics, culture, infrastructure and legal and were tested and prioritized from experienced exporter’s perspective. Top managers of exporting companies in the electrical industry were surveyed through census method. The ranking method was used for analyzing the data. The results showed that market potential is the most important dimension in target market selection. Legal, politics, infrastructure, economics are respectively ranked as influential dimensions. Culture dimension is reported ineffective in selecting Iranian electrical industry’s target markets.One of the most important concepts of international marketing is export target market selection which is the first stage of internationalization process. This paper studies the factors influencing export target market selection in Iranian electrical industry. The factors categorized in 6 dimensions such as politics, market potential, economics, culture, infrastructure and legal and were tested and prioritized from experienced exporter’s perspective. Top managers of exporting companies in the electrical industry were surveyed through census method. The ranking method was used for analyzing the data. The results showed that market potential is the most important dimension in target market selection. Legal, politics, infrastructure, economics are respectively ranked as influential dimensions. Culture dimension is reported ineffective in selecting Iranian electrical industry’s target markets.https://jims.atu.ac.ir/article_4570_190ee79232a679a95131e91d26f74e9a.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-802992420120327Data Mining for Occupational Accidents in Construction Industry
Case Study: A Project Oriented OrganizationData Mining for Occupational Accidents in Construction Industry
Case Study: A Project Oriented Organization1611824571FASavizMohammadnabiSinaMohammadnabiJournal Article20091026This study attempted to use data mining as a powerful analytical tool to find patterns for occurrence of accidents from 1845 recorded events in safety data warehouse in one of the largest project-based organizations active in construction industry in Iran between the years 2002 and 2008. High-risk nature of construction industry, Geographic expansion of the projects sites and large number of accidents are the characteristics of this organization. Predicting and preventing models for occurrence of accidents have been proposed in this study by extracting 31 traceable Association rules from recorded events. Extracting the rules, the minimum amount of confidence, support and lift indicators have been set respectively in 73%, 5% and 1 levels.This study attempted to use data mining as a powerful analytical tool to find patterns for occurrence of accidents from 1845 recorded events in safety data warehouse in one of the largest project-based organizations active in construction industry in Iran between the years 2002 and 2008. High-risk nature of construction industry, Geographic expansion of the projects sites and large number of accidents are the characteristics of this organization. Predicting and preventing models for occurrence of accidents have been proposed in this study by extracting 31 traceable Association rules from recorded events. Extracting the rules, the minimum amount of confidence, support and lift indicators have been set respectively in 73%, 5% and 1 levels.https://jims.atu.ac.ir/article_4571_837b613eca3d7f97eb1bf5e25977c50c.pdf