Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
ROBUST OPTIMIZATION OF THE PORTFOLIO SELECTION PROBLEM USING WEIGHTED CONDITIONAL VALUE AT-RISK APPROACH
ROBUST OPTIMIZATION OF THE PORTFOLIO SELECTION PROBLEM USING WEIGHTED CONDITIONAL VALUE AT-RISK APPROACH
3
10
5269
FA
A.
Ghahtarani
Dept. of Industrial Engineering \nK.N. Toosi University of Technology
A.A.
Najafi
Dept. of Industrial Engineering \nK.N. Toosi University of Technology
Journal Article
2012
02
21
In this paper, we develop a robust model for the portfolio selection problem under uncertainty conditions. We construct a robust model, whose risk measure is weighted conditional value at-risk (WCVaR). WCVaR is a combination of the conditional value at-risk (CVaR) with several tolerance levels. We use combinations of the conditional value at-risk (CVaR) measures to get some approximations of the tail Ginis mean difference, with the advantage of being computationally much simpler than the Ginis measure itself.The studied model is SSD consistent and LP computable. In stochastic dominance, uncertain returns (modeled as random variable) are compared by the point wise comparison of some performance functions constructed from their distribution functions. The first performance function is defined as the right-continuous cumulative distribution function, and it defines first degree stochastic dominance (FSD). The second function is derived from the first, and it defines second degree stochastic dominance (SSD). WCVaR is a safety measure with uncertain returns. To handle the parameter uncertainty problem, there is a recent research trend in the development of new robust optimization approaches. Traditional optimization methods require full knowledge of parameters to allow transformation to a stochastic program. From full information, assumptions of parameters following specific known distributions can sometimes be too strong and their validity criticized. The last approach of robust optimization proposes a robust formulation that is linear, applicable, deterministically solvable, and extendable to discrete optimization without the loss of feasibility of solution. Another advantage of the model is its ease in controlling the level of conservatism. In this paper, we apply this approach and develop the robust weighted conditional value at-risk in a portfolio selection problem. We also show the performance of robust optimization in the flexibility of financial markets.
In this paper, we develop a robust model for the portfolio selection problem under uncertainty conditions. We construct a robust model, whose risk measure is weighted conditional value at-risk (WCVaR). WCVaR is a combination of the conditional value at-risk (CVaR) with several tolerance levels. We use combinations of the conditional value at-risk (CVaR) measures to get some approximations of the tail Ginis mean difference, with the advantage of being computationally much simpler than the Ginis measure itself.The studied model is SSD consistent and LP computable. In stochastic dominance, uncertain returns (modeled as random variable) are compared by the point wise comparison of some performance functions constructed from their distribution functions. The first performance function is defined as the right-continuous cumulative distribution function, and it defines first degree stochastic dominance (FSD). The second function is derived from the first, and it defines second degree stochastic dominance (SSD). WCVaR is a safety measure with uncertain returns. To handle the parameter uncertainty problem, there is a recent research trend in the development of new robust optimization approaches. Traditional optimization methods require full knowledge of parameters to allow transformation to a stochastic program. From full information, assumptions of parameters following specific known distributions can sometimes be too strong and their validity criticized. The last approach of robust optimization proposes a robust formulation that is linear, applicable, deterministically solvable, and extendable to discrete optimization without the loss of feasibility of solution. Another advantage of the model is its ease in controlling the level of conservatism. In this paper, we apply this approach and develop the robust weighted conditional value at-risk in a portfolio selection problem. We also show the performance of robust optimization in the flexibility of financial markets.
https://sjie.journals.sharif.edu/article_5269_97b669d7702652e9535b19b5912ea324.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
Multiple response optimization, non-dominated solutions, artificial neural networks, epsilon constraint, genetic algorithm.
Multiple response optimization, non-dominated solutions, artificial neural networks, epsilon constraint, genetic algorithm.
11
19
5270
FA
M.
Bashiri
Dep. of Industrial Engineering Shahed University
A.
Farshbaf-Geranmayeh
Dep. of Industrial Engineering Shahed University
Journal Article
2012
02
21
Simultaneous optimization of multiple response problems is an important problem in manufacturing cases. Polynomial regression is a common method for finding the relationship between controllable factors and responses. Some researchers have showed that artificial neural networks have better performance when the relationships are far too complex. In the multiple response problems, determination of non-dominated solutions is more valuable than finding only one solution as an optimum treatment, while this solution is one of the obtained non-dominated solutions. Unlike other existing research into using neural networks for multiple response problems, in the proposed method, responses are assumed as inputs, and controllable factors are assumed as targets of the neural network. This kind of input and target definition for neural networks helps us to determine non-dominated solutions by employing a neural network, an epsilon constraint technique and a genetic algorithm. The proposed method includes three major steps: 1) modeling the relation between responses and controllable factors by employing a neural network, 2) finding non-dominated solutions using an epsilon constraint and a genetic algorithm, 3) sieving solutions obtained from the last step and determining strong non-dominated solutions. For showing the efficiency of the proposed method, non-dominated solutions for a numerical example from the literature are determined by using the proposed approach. Comparing the results shows that obtained non-dominated solutions obtained by the proposed method for the example, are often better than other research results for the same example.
Simultaneous optimization of multiple response problems is an important problem in manufacturing cases. Polynomial regression is a common method for finding the relationship between controllable factors and responses. Some researchers have showed that artificial neural networks have better performance when the relationships are far too complex. In the multiple response problems, determination of non-dominated solutions is more valuable than finding only one solution as an optimum treatment, while this solution is one of the obtained non-dominated solutions. Unlike other existing research into using neural networks for multiple response problems, in the proposed method, responses are assumed as inputs, and controllable factors are assumed as targets of the neural network. This kind of input and target definition for neural networks helps us to determine non-dominated solutions by employing a neural network, an epsilon constraint technique and a genetic algorithm. The proposed method includes three major steps: 1) modeling the relation between responses and controllable factors by employing a neural network, 2) finding non-dominated solutions using an epsilon constraint and a genetic algorithm, 3) sieving solutions obtained from the last step and determining strong non-dominated solutions. For showing the efficiency of the proposed method, non-dominated solutions for a numerical example from the literature are determined by using the proposed approach. Comparing the results shows that obtained non-dominated solutions obtained by the proposed method for the example, are often better than other research results for the same example.
https://sjie.journals.sharif.edu/article_5270_1c335db0883d48f6f547d71f92c8df6e.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
MONITORING MULTIVARIATE-ATTRIBUTE PROCESSES BASED ON THE BOOTSTRAP TECHNIQUE
MONITORING MULTIVARIATE-ATTRIBUTE PROCESSES BASED ON THE BOOTSTRAP TECHNIQUE
21
27
5271
FA
A.
Amiri
Dep. of Industrial Engineering Shahed University
M. H
Doroudyan
Dep. of Industrial Engineering Shahed University
Journal Article
2012
05
20
Nowadays, in many production and service environment, the quality of a product or process is represented by two or more quality characteristics. Therefore, multivariate and multi-attribute control charts have been widely developed by many authors, separately. Sometimes, the quality of a product or a process is represented by correlated variables and attribute quality characteristics. For example, in plastic manufacturing companies, the number of defects in one product, as an attribute, has a correlation with the weight of the product, as a variable quality characteristic. To the best of our knowledge, there is no method to monitor this type of quality characteristic. Note that monitoring correlated variables and attribute quality characteristics separately, without considering the correlation structure, leads to increasing the overall probability of Type I error in the control chart. An appropriate approach in designing control charts is defining confidence limits. There are some methods to etermine confidence limits for correlated random data, such as described by Bonferoni (Hayter and Tsui, 1994) and Sidak (1967). But, the first method requires large samples, which lead to less application, and the second has a weakness in neglecting the correlation between quality characteristics. In this paper, we propose two methods to monitor multivariate-attribute processes, based on the bootstrap technique (Jhun et al. 2007), which has none of the drawbacks of the mentioned methods (Bonferoni and Sidak). In the first method, new confidence limits for multivariate-attribute quality characteristics are presented by using the bootstrap technique. In the second method, the bootstrap technique is used to determine confidence limits for EWMA control statistics, which are used for correlated attribute and variable quality characteristics. Finally, these confidence limits are used to monitor the process. Based on the signal rule, whenever each control chart signals, the process will be out-of-control and the corresponding quality characteristic is introduced as the source of variation. This research is performed in Phase II, thus, it is assumed that the distributions of quality characteristics are known based on Phase I analyses. The obtained results confirms the efficiency of the proposed method compared to the traditional method based on the accuracy of probability of Type I error, especially under small values of Type I error probability.
Nowadays, in many production and service environment, the quality of a product or process is represented by two or more quality characteristics. Therefore, multivariate and multi-attribute control charts have been widely developed by many authors, separately. Sometimes, the quality of a product or a process is represented by correlated variables and attribute quality characteristics. For example, in plastic manufacturing companies, the number of defects in one product, as an attribute, has a correlation with the weight of the product, as a variable quality characteristic. To the best of our knowledge, there is no method to monitor this type of quality characteristic. Note that monitoring correlated variables and attribute quality characteristics separately, without considering the correlation structure, leads to increasing the overall probability of Type I error in the control chart. An appropriate approach in designing control charts is defining confidence limits. There are some methods to etermine confidence limits for correlated random data, such as described by Bonferoni (Hayter and Tsui, 1994) and Sidak (1967). But, the first method requires large samples, which lead to less application, and the second has a weakness in neglecting the correlation between quality characteristics. In this paper, we propose two methods to monitor multivariate-attribute processes, based on the bootstrap technique (Jhun et al. 2007), which has none of the drawbacks of the mentioned methods (Bonferoni and Sidak). In the first method, new confidence limits for multivariate-attribute quality characteristics are presented by using the bootstrap technique. In the second method, the bootstrap technique is used to determine confidence limits for EWMA control statistics, which are used for correlated attribute and variable quality characteristics. Finally, these confidence limits are used to monitor the process. Based on the signal rule, whenever each control chart signals, the process will be out-of-control and the corresponding quality characteristic is introduced as the source of variation. This research is performed in Phase II, thus, it is assumed that the distributions of quality characteristics are known based on Phase I analyses. The obtained results confirms the efficiency of the proposed method compared to the traditional method based on the accuracy of probability of Type I error, especially under small values of Type I error probability.
https://sjie.journals.sharif.edu/article_5271_36ac2db5a0c900356f59cef0c85b6c67.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
DEVELOPMENT OF DECISION SUPPORT TOOL FOR SUPPLY CHAIN COORDINATION,USING CONTRACTS AND VMI
DEVELOPMENT OF DECISION SUPPORT TOOL FOR SUPPLY CHAIN COORDINATION,USING CONTRACTS AND VMI
29
39
5272
FA
S. K.
Chahrsooghi
Dept. of Industrial Engineering\nTarbiat Modares University
I.
N. Kamalabadi
Dept. of Industrial Engineering\nTarbiat Modares University
S.
Hematyar
Dept. of Industrial Engineering\nPayame Noor University
Journal Article
2012
04
29
Coordinating supply chains is an effective way to improve channel performance. A supply chain involves managing various resources (such as inventory, money and information) between disparate but dependent SC members. The conflicting objectives and lack of information between SC members may often cause uncertainties in SC. Hence, some coordination mechanism is necessary, which may motivate the members to achieve coordination. The purpose of this paper is to describe a decision support tool base on a contract in a two-level supply chain with VMI partnership. VMI facilitate the application of contracts, since information sharing in VMI partnerships allows the supplier to obtain actual sales data in a timely manner. The supplier may suggest some contracts to the retailer, according to business situations, and, in this case, the decision support tool can help all SC members to determine decision variable contracts for different scenarios. This tool is comprised of an analytical module; an extension of the classical newsboy problem, in which different cases of coordination are discussed, and a simulation module. The output of the analytical module becomes an input for simulation to quantify performance measures. The improvement in performance measures, after satisfying the objectives of all SC members, helps in realizing coordination in SC. In simulation, stochastic demand and price dependency are considered. The model proposed in this paper acts as a decision making tool; planning and estimating the decision variables of sales rebate and buyback contracts prior to the realization of the actual demand. Then, a comparison of different contracts is carried out based on expected profits. To demonstrate the use of the tool, a numerical example is presented. The range of buyback price and rebate is determined based on inequalities of the analytical module. Various performance measures are presented and, then, the module is quantified by simulation. The simulation module helps the decision makers chose an appropriate type of contract and answer various what if questions.
Coordinating supply chains is an effective way to improve channel performance. A supply chain involves managing various resources (such as inventory, money and information) between disparate but dependent SC members. The conflicting objectives and lack of information between SC members may often cause uncertainties in SC. Hence, some coordination mechanism is necessary, which may motivate the members to achieve coordination. The purpose of this paper is to describe a decision support tool base on a contract in a two-level supply chain with VMI partnership. VMI facilitate the application of contracts, since information sharing in VMI partnerships allows the supplier to obtain actual sales data in a timely manner. The supplier may suggest some contracts to the retailer, according to business situations, and, in this case, the decision support tool can help all SC members to determine decision variable contracts for different scenarios. This tool is comprised of an analytical module; an extension of the classical newsboy problem, in which different cases of coordination are discussed, and a simulation module. The output of the analytical module becomes an input for simulation to quantify performance measures. The improvement in performance measures, after satisfying the objectives of all SC members, helps in realizing coordination in SC. In simulation, stochastic demand and price dependency are considered. The model proposed in this paper acts as a decision making tool; planning and estimating the decision variables of sales rebate and buyback contracts prior to the realization of the actual demand. Then, a comparison of different contracts is carried out based on expected profits. To demonstrate the use of the tool, a numerical example is presented. The range of buyback price and rebate is determined based on inequalities of the analytical module. Various performance measures are presented and, then, the module is quantified by simulation. The simulation module helps the decision makers chose an appropriate type of contract and answer various what if questions.
https://sjie.journals.sharif.edu/article_5272_cfcbb008f925f273e54518534bda9ab4.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
PRODUCTION PLANNING MODEL FOR CLOSED-LOOP SUPPLY CHAIN WITH UNCERTAINTY AND INVENTORY ANALYSIS
PRODUCTION PLANNING MODEL FOR CLOSED-LOOP SUPPLY CHAIN WITH UNCERTAINTY AND INVENTORY ANALYSIS
41
50
5273
FA
A.
Taheri Moghadam
Dept. of Industrial Engineering\nShahed University
R.
Sahraeian
Dept. of Industrial Engineering\nShahed University
Journal Article
2012
05
19
Green supply chain management (GSCM) has been growing in recent years with interest from both academia and industry. A preponderance of special issues devoted to this topic in leading operations and supply chain management (SCM) journals attests to this trend. The closed loop supply chain (CLSC) is a branch of GSCM which includes recycling and remanufacturing activities for reasons of environment protection. CLSC has attracted growing attention in recent years, due to the scarcity of natural resources and increased environmental concerns. In this paper, a multi period model is proposed which contains production planning and inventory control in a closed loop system. This model is developed from the work of Shi et al. (2011), which considers return flow and uncertainty for production planning in a closed loop system. In the proposed model, we have added inventory control, pricing, land filling, recycling and out sourcing (manufacturing, remanufacturing and return) to the former model. Since this model considers inventory control, it should be a multi period model. For decreasing the complexity of the model, in this paper, it is assumed that only one product can be produced. But, it can be used for multi products too. It is assumed that a percentage of used products can be remanufactured but all can be recycled. The genetic algorithm (GA) is suggested for solving the proposed model. Some random examples are solved by GA for illustrating the proposed model and the solving approach. For evaluating the solving approach, one of the models constraints is eliminated and the example solved without that constraint. Hence, the upper limit of the objective function is defined. The results show that the solving approach has a maximum average error of 3.59 percent. Note that the upper limit of the objective function is infeasible for the original example. Hence, GA is an appropriate approach for solving the proposed model.
Green supply chain management (GSCM) has been growing in recent years with interest from both academia and industry. A preponderance of special issues devoted to this topic in leading operations and supply chain management (SCM) journals attests to this trend. The closed loop supply chain (CLSC) is a branch of GSCM which includes recycling and remanufacturing activities for reasons of environment protection. CLSC has attracted growing attention in recent years, due to the scarcity of natural resources and increased environmental concerns. In this paper, a multi period model is proposed which contains production planning and inventory control in a closed loop system. This model is developed from the work of Shi et al. (2011), which considers return flow and uncertainty for production planning in a closed loop system. In the proposed model, we have added inventory control, pricing, land filling, recycling and out sourcing (manufacturing, remanufacturing and return) to the former model. Since this model considers inventory control, it should be a multi period model. For decreasing the complexity of the model, in this paper, it is assumed that only one product can be produced. But, it can be used for multi products too. It is assumed that a percentage of used products can be remanufactured but all can be recycled. The genetic algorithm (GA) is suggested for solving the proposed model. Some random examples are solved by GA for illustrating the proposed model and the solving approach. For evaluating the solving approach, one of the models constraints is eliminated and the example solved without that constraint. Hence, the upper limit of the objective function is defined. The results show that the solving approach has a maximum average error of 3.59 percent. Note that the upper limit of the objective function is infeasible for the original example. Hence, GA is an appropriate approach for solving the proposed model.
https://sjie.journals.sharif.edu/article_5273_3312e454be17dbed65f9d793d8adc80f.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
THE RELATIONSHIP BETWEEN GOVERNMENT ADMINISTRATION PERFORMANCE AND CITIZEN RELATIONSHIP MANAGEMENT
THE RELATIONSHIP BETWEEN GOVERNMENT ADMINISTRATION PERFORMANCE AND CITIZEN RELATIONSHIP MANAGEMENT
51
61
5274
FA
H.
Havaeji
Dept. of Industrial Engineering\nTarbiat Modares University
A.
Albadvi
Dep. of Industrial Engineering Tarbiat Modares University
Journal Article
2012
06
17
In recent decades, the lasting relationship between citizens and governments has consistently been paid attention to by top managers of the government. In cooperation between a government and its citizens, the government recognizes the needs of the citizens and, consequently, can offer a better response to them. Thus, it may be better to consider a government as a part of the social body, which should meet its peoples needs and requirements. This study suggests an approach in order to use citizen ideas in improving government administration performance, and to develop a direct relationship between citizens and top managers of the government, based on existing literature. Specifically, our aim is to design a model by which a government can hear the voice of its citizens. Citizens can put forward suggestions and point out administration performance deficiencies to the government and, subsequently, governments will invite citizens to control their administration performance. Researchers designed a conceptual model and then refined it using the answers for 451 completed questionnaires collected from nine areas of the Iran territory development plan. The results show the direction of government strategies moving towards citizen needs, including establishing a seamless, integrated and coordinated relationship between citizen and government managers, by integrating citizens suggestions and criticisms, and using citizens opinions in improving government administration performance. Hence, the use of citizens suggestions by governments in decision making (citizen being seen), and by paying attention to citizens criticisms and conveying their voices to top managers (citizen being heard) seems to be the way forward to answer citizen needs in todays modern communities. In addition, this study discovers that before promoting Citizen Relationship Management, it is essential to first investigate effective directions in establishing Citizen-Government Relationships. The results could be empirically helpful for governments to consider citizen opinion being seen and heard as a requirement and a necessity in todays dynamic communities.
In recent decades, the lasting relationship between citizens and governments has consistently been paid attention to by top managers of the government. In cooperation between a government and its citizens, the government recognizes the needs of the citizens and, consequently, can offer a better response to them. Thus, it may be better to consider a government as a part of the social body, which should meet its peoples needs and requirements. This study suggests an approach in order to use citizen ideas in improving government administration performance, and to develop a direct relationship between citizens and top managers of the government, based on existing literature. Specifically, our aim is to design a model by which a government can hear the voice of its citizens. Citizens can put forward suggestions and point out administration performance deficiencies to the government and, subsequently, governments will invite citizens to control their administration performance. Researchers designed a conceptual model and then refined it using the answers for 451 completed questionnaires collected from nine areas of the Iran territory development plan. The results show the direction of government strategies moving towards citizen needs, including establishing a seamless, integrated and coordinated relationship between citizen and government managers, by integrating citizens suggestions and criticisms, and using citizens opinions in improving government administration performance. Hence, the use of citizens suggestions by governments in decision making (citizen being seen), and by paying attention to citizens criticisms and conveying their voices to top managers (citizen being heard) seems to be the way forward to answer citizen needs in todays modern communities. In addition, this study discovers that before promoting Citizen Relationship Management, it is essential to first investigate effective directions in establishing Citizen-Government Relationships. The results could be empirically helpful for governments to consider citizen opinion being seen and heard as a requirement and a necessity in todays dynamic communities.
https://sjie.journals.sharif.edu/article_5274_8c184f29868ce55be8921dca8386bc1b.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
STRATEGY DEVELOPMENT FOR CUSTOMER SATISFACTION OF AIRLINE FLIGHTS BASED ON GREY SYSTEMS (CASE STUDY: IRANIAN AIRLINE INDUSTRIES)
STRATEGY DEVELOPMENT FOR CUSTOMER SATISFACTION OF AIRLINE FLIGHTS BASED ON GREY SYSTEMS (CASE STUDY: IRANIAN AIRLINE INDUSTRIES)
63
79
5283
FA
M.R.
Gholamian
School of Industrial Engineering\n Iran University of Science & Technology
S.
Dolatkhah
School of Industrial Engineering\n Iran University of Science & Technology
Journal Article
2012
07
17
By development of information technology, nowadays one of the most important issues in competitive markets is the growth of customer satisfaction and loyalty. As yet many researches are performed in customer satisfaction but a few researches are carried on uncertainty conditions. Meanwhile, most of the uncertainty modeling has been manipulated by fuzzy mathematics. While fuzzy mathematics can not to be responsible into the type of uncertainties in such problems and make the invalid and unfavorable results. Fuzzy mathematics rely on the cognitive uncertainty established based on experiences that having a clear intension without a clear extension. The aim of this uncertainty modeling is that to make a cognitive expression of objects using membership definitions and linguistic propositions. But often sufficient information and experiences were needed to develop such membership functions; whilst in some uncertainty problems even such information and experiences are not available to be used to develop membership functions. Essentially, because of poor information and small samples, object intension is unclear and only a range of object extension can be handled. This is the subject of the other type of uncertainty named grey set theory. In this study, this type of uncertainty is used in customer satisfaction issue; since having an unclear intension with a clear extension is more sensible observed in this issue and hence it seems that grey set theory is more responsible than fuzzy theory in this issue. Therefore, a framework for strategy development in customer satisfaction is introduced such that initially the importance of customer requirements are extracted in QFD by quantitative Kano used with grey numbers and also grey TOPSIS. On the other hand, a method is presented for ranking technical requirements based on SAW and grey number. Finally, these two models were used in House of Quality in QFD. The developed model was examined in airline industry and the obtained results are analyzed. The research finding illustrates that the safety of flight is the first and punctuality in flight is the second rank of the priority needs of passengers and also loyalty program & many travel is approximately unknown for passengers that should be attended by airlines.
By development of information technology, nowadays one of the most important issues in competitive markets is the growth of customer satisfaction and loyalty. As yet many researches are performed in customer satisfaction but a few researches are carried on uncertainty conditions. Meanwhile, most of the uncertainty modeling has been manipulated by fuzzy mathematics. While fuzzy mathematics can not to be responsible into the type of uncertainties in such problems and make the invalid and unfavorable results. Fuzzy mathematics rely on the cognitive uncertainty established based on experiences that having a clear intension without a clear extension. The aim of this uncertainty modeling is that to make a cognitive expression of objects using membership definitions and linguistic propositions. But often sufficient information and experiences were needed to develop such membership functions; whilst in some uncertainty problems even such information and experiences are not available to be used to develop membership functions. Essentially, because of poor information and small samples, object intension is unclear and only a range of object extension can be handled. This is the subject of the other type of uncertainty named grey set theory. In this study, this type of uncertainty is used in customer satisfaction issue; since having an unclear intension with a clear extension is more sensible observed in this issue and hence it seems that grey set theory is more responsible than fuzzy theory in this issue. Therefore, a framework for strategy development in customer satisfaction is introduced such that initially the importance of customer requirements are extracted in QFD by quantitative Kano used with grey numbers and also grey TOPSIS. On the other hand, a method is presented for ranking technical requirements based on SAW and grey number. Finally, these two models were used in House of Quality in QFD. The developed model was examined in airline industry and the obtained results are analyzed. The research finding illustrates that the safety of flight is the first and punctuality in flight is the second rank of the priority needs of passengers and also loyalty program & many travel is approximately unknown for passengers that should be attended by airlines.
https://sjie.journals.sharif.edu/article_5283_6269f06972b866a5bf699b0c32ef6b22.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
APPLICATION OF BUSINESS INTELLIGENCE AND CUSTOMER RELATIONSHIP MANAGEMENT IN -MUNICIPALITIES: CASE STUDY OF ICT ORGANIZATION OF ISFAHAN MUNICIPALITY SECTI?
APPLICATION OF BUSINESS INTELLIGENCE AND CUSTOMER RELATIONSHIP MANAGEMENT IN -MUNICIPALITIES: CASE STUDY OF ICT ORGANIZATION OF ISFAHAN MUNICIPALITY SECTI?
81
88
5268
FA
S.
N. Isfahani
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
H.
Safaiepour
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
M.J. Tarokh
Tarokh
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
Journal Article
2011
04
11
Business intelligence refers to computer-aided techniques for the discovery and analysis of business data. It aims at supporting better business decision making. At the present time, with the development of information systems, organizations are moving toward an optimum use of information, and expanding information to applicable knowledge in order to achieve more business intelligence. Business intelligence and customer relationship management systems are playing a critical role in the creation and development of value added techniques for organizations. As a result, municipalities, as the main organizations in city management, are moving towards the development of a powerful information technology infrastructure. They provide an appropriate business intelligence research area, due to their enthusiasm for development, their access to a large number of customers and the complexity of their relationship with them, i.e. citizens. Among all revenue sources, the imposition and reconstruction section has attracted municipalities, such as that of Esfahan, as a source of more capital development. This research aims at determination of the hidden behavioral patterns of citizens in the imposition and reconstruction section by means of data mining methods. In order to achieve this, data related to landowner payment status, which is land, landowner specifications and their yearly payment details for the last seven years, are analyzed. The main objective of this research is to understand factors affecting citizens being good or bad, regarding payment of impositions. Accordingly, in this case study, initial steps for the achievement of business intelligence are analyzed using the K-Mean algorithm. K-Mean is a clustering method for grouping similar objects in the same group. Considering various specifications of land and land owner, citizens are clustered into five account sets of: very good, good, half good, bad and very bad, based on payment delay. Consequently, most effective factors affecting citizen imposition payment behavior are determined for future predictions. This is achieved by means of neural network and decision tree methods. The results of the two approaches were not exactly similar; however, both suggested two similar factors as the most influential in predicting customer payment behavior. These two factors can be considered in a further customer relationship management plan, with respect to higher business values over time.
Business intelligence refers to computer-aided techniques for the discovery and analysis of business data. It aims at supporting better business decision making. At the present time, with the development of information systems, organizations are moving toward an optimum use of information, and expanding information to applicable knowledge in order to achieve more business intelligence. Business intelligence and customer relationship management systems are playing a critical role in the creation and development of value added techniques for organizations. As a result, municipalities, as the main organizations in city management, are moving towards the development of a powerful information technology infrastructure. They provide an appropriate business intelligence research area, due to their enthusiasm for development, their access to a large number of customers and the complexity of their relationship with them, i.e. citizens. Among all revenue sources, the imposition and reconstruction section has attracted municipalities, such as that of Esfahan, as a source of more capital development. This research aims at determination of the hidden behavioral patterns of citizens in the imposition and reconstruction section by means of data mining methods. In order to achieve this, data related to landowner payment status, which is land, landowner specifications and their yearly payment details for the last seven years, are analyzed. The main objective of this research is to understand factors affecting citizens being good or bad, regarding payment of impositions. Accordingly, in this case study, initial steps for the achievement of business intelligence are analyzed using the K-Mean algorithm. K-Mean is a clustering method for grouping similar objects in the same group. Considering various specifications of land and land owner, citizens are clustered into five account sets of: very good, good, half good, bad and very bad, based on payment delay. Consequently, most effective factors affecting citizen imposition payment behavior are determined for future predictions. This is achieved by means of neural network and decision tree methods. The results of the two approaches were not exactly similar; however, both suggested two similar factors as the most influential in predicting customer payment behavior. These two factors can be considered in a further customer relationship management plan, with respect to higher business values over time.
https://sjie.journals.sharif.edu/article_5268_389bf8c94571e2a8a48fc53155261709.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
A NEW APPROACH FOR PORTFOLIO PERFORMANCE EVALUATION IN MVS MODELING VIA DATA ENVELOPMENT ANALYSIS: (CASE STUDY: IRAN STOCK MARKET)
A NEW APPROACH FOR PORTFOLIO PERFORMANCE EVALUATION IN MVS MODELING VIA DATA ENVELOPMENT ANALYSIS: (CASE STUDY: IRAN STOCK MARKET)
89
99
5275
FA
E.
Alinezhad
Dept. of Industrial Engineering\nYazd University
Y.
Zare Mehrjerdi
Dept. of Industrial Engineering\nYazd University
Journal Article
2011
06
28
People, during their lifetime, make investment decisions in various areas including real estate, gold, stocks, and bonds, and these decisions have an internal relationship between them that is unbreakable. The link between these decisions lies in the risks taken and the return on investments for the selected market. Decision making, with regard to investments, is one of the most difficult and complicated subjects in management and investment analysis. Generally speaking, an efficient portfolio is a portfolio with a specified return amount and the lowest possible risk level. The content of this article suggests that to find an efficient frontier, instead of using the Markowitz mean-variance (MV) model, we can use the Mean-Variance-Skewness model (MVS). This paper introduces a practical model for evaluation of an efficient portfolio based upon the MVS model using a Data Envelopment Analysis approach. The main idea of this approach is to evaluate the performance of a set of funds by taking into account expected returns, variance and skewness, and synthesizing them in a numerical value via an input oriented data envelopment analysis model. The DEA technique is a multi criterion decision making tool for making appropriate and sound decisions. In this technique, we can, at the same time as using some input and output variables, calculate and separate the efficiency of a set of efficient company stocks from inefficient ones. In addition, the optimal portfolio among the efficient companies can be determined using the information obtained. The high point of this research is efficient frontier generation through projecting the stocks on the frontier without actually generating the frontier at all, and then determining the efficiency of the stocks. As a case study, this model was implemented for the top 37 companies in Irans stock markets. The results obtained from the model execution indicate that the stocks of three companies; Saipa, Alborz Daru and Tehran Cement, are the most appropriate for portfolio selection, due to their appropriateness of returns and variance of stocks, as well as their skewness positivity.
People, during their lifetime, make investment decisions in various areas including real estate, gold, stocks, and bonds, and these decisions have an internal relationship between them that is unbreakable. The link between these decisions lies in the risks taken and the return on investments for the selected market. Decision making, with regard to investments, is one of the most difficult and complicated subjects in management and investment analysis. Generally speaking, an efficient portfolio is a portfolio with a specified return amount and the lowest possible risk level. The content of this article suggests that to find an efficient frontier, instead of using the Markowitz mean-variance (MV) model, we can use the Mean-Variance-Skewness model (MVS). This paper introduces a practical model for evaluation of an efficient portfolio based upon the MVS model using a Data Envelopment Analysis approach. The main idea of this approach is to evaluate the performance of a set of funds by taking into account expected returns, variance and skewness, and synthesizing them in a numerical value via an input oriented data envelopment analysis model. The DEA technique is a multi criterion decision making tool for making appropriate and sound decisions. In this technique, we can, at the same time as using some input and output variables, calculate and separate the efficiency of a set of efficient company stocks from inefficient ones. In addition, the optimal portfolio among the efficient companies can be determined using the information obtained. The high point of this research is efficient frontier generation through projecting the stocks on the frontier without actually generating the frontier at all, and then determining the efficiency of the stocks. As a case study, this model was implemented for the top 37 companies in Irans stock markets. The results obtained from the model execution indicate that the stocks of three companies; Saipa, Alborz Daru and Tehran Cement, are the most appropriate for portfolio selection, due to their appropriateness of returns and variance of stocks, as well as their skewness positivity.
https://sjie.journals.sharif.edu/article_5275_c489853b541e68dd565cfc7987de5cf1.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
PRESENTING A HEURISTIC ALGORITHM FOR INTEGRATED PRODUCT MIX-OUTSOURCING PROBLEM UNDER THEORY OF CONSTRAINT
PRESENTING A HEURISTIC ALGORITHM FOR INTEGRATED PRODUCT MIX-OUTSOURCING PROBLEM UNDER THEORY OF CONSTRAINT
101
107
5276
FA
E.
Mehdizadeh
Dept. of Industrial and Mechanical Engineering\n Qazvin Branch,Islamic Azad Univer
S.
Jalili
Dept. of Industrial and Mechanical Engineering\n Qazvin Branch,Islamic Azad Univer
M.
Eghbali
Dept. of Industrial and Mechanical Engineering\n Qazvin Branch,Islamic Azad Univer
Journal Article
2012
02
18
Determining the production rate of each product in order to maximize the throughput is important for production systems. This problem is called the product mix (PM) problem. In most cases, due to insufficient production resources, companies tend to obtain some of their products from external resources. Given this, PM, with the decision to outsource production, a combined and integrated product mix-outsourcing problem (IPMO) is formed. Here, the main question is how much of each product should be produced internally and how much should be outsourced. One of the most famous methods for solving the IPMO problem is the theory of constraints (TOC). TOC offers a five step methodology for the identification of organizational constraints and their elevation. The methodology is described as follows: (1) Identify the systems constraint(s) (2) Decide how to exploit the systems constraint(s) (3) Subordinate everything else to the above decision (4) Elevate the systems constraint(s), and (5) If, in the previous steps, a constraint has been broken, go back to step1.In step1, the system bottleneck is dentified. In step 2, the scheduler decides how to use the bottleneck in order to maximize the throughput. In step 3, the bottleneck schedule (drum) is developed and, through backward and forward scheduling, other work centers are scheduled. In step 4, necessary improvements are considered in order to promote the bottleneck performance. And, finally, step 5 indicates the dynamic nature of the TOC. The product mix is determined through the first two steps of the TOC. In this study, we will introduce a simple and heuristic method based on TOC to solve IPMO problems in multi-bottleneck mode. First, it is shown, by an example, that available heuristic algorithms for solving the IPMO problem do not necessarily lead to optimum and even feasible solutions. Then, the proposed algorithm is compared with existing methods in the literature in single and multi-bottleneck modes, and it is indicated that the proposed algorithm is able to achieve appropriate solutions
Determining the production rate of each product in order to maximize the throughput is important for production systems. This problem is called the product mix (PM) problem. In most cases, due to insufficient production resources, companies tend to obtain some of their products from external resources. Given this, PM, with the decision to outsource production, a combined and integrated product mix-outsourcing problem (IPMO) is formed. Here, the main question is how much of each product should be produced internally and how much should be outsourced. One of the most famous methods for solving the IPMO problem is the theory of constraints (TOC). TOC offers a five step methodology for the identification of organizational constraints and their elevation. The methodology is described as follows: (1) Identify the systems constraint(s) (2) Decide how to exploit the systems constraint(s) (3) Subordinate everything else to the above decision (4) Elevate the systems constraint(s), and (5) If, in the previous steps, a constraint has been broken, go back to step1.In step1, the system bottleneck is dentified. In step 2, the scheduler decides how to use the bottleneck in order to maximize the throughput. In step 3, the bottleneck schedule (drum) is developed and, through backward and forward scheduling, other work centers are scheduled. In step 4, necessary improvements are considered in order to promote the bottleneck performance. And, finally, step 5 indicates the dynamic nature of the TOC. The product mix is determined through the first two steps of the TOC. In this study, we will introduce a simple and heuristic method based on TOC to solve IPMO problems in multi-bottleneck mode. First, it is shown, by an example, that available heuristic algorithms for solving the IPMO problem do not necessarily lead to optimum and even feasible solutions. Then, the proposed algorithm is compared with existing methods in the literature in single and multi-bottleneck modes, and it is indicated that the proposed algorithm is able to achieve appropriate solutions
https://sjie.journals.sharif.edu/article_5276_bafa13788643bf92a5bb8d45d9267623.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
A TABU SEARCH-BASED ALGORITHM WITH DIVERSIFICATION STRATEGY FOR DYNAMIC FACILITY LAYOUT PROBLE
A TABU SEARCH-BASED ALGORITHM WITH DIVERSIFICATION STRATEGY FOR DYNAMIC FACILITY LAYOUT PROBLE
109
117
5277
FA
N.
Bozorgi
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
M.
Abedzadeh
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
Journal Article
2012
02
18
The facility layout problem is determination of the position of a department in a specific facility. The simplest case of a facility layout problem is FLP with equal size departments, where the amount of material flowing between pairs of departments does not change during the planning horizon. This problem is called the static facility layout problem (SFLP), with equal size departments, and was modeled by Koopmans and Beckmann as a quadratic assignment problem (QAP). The dynamic facility layout problem (DFLP) is a well-researched problem to find the positions of departments on a plant floor for multiple periods (material u{fb02}ow between departments change during the planning horizon). The change in material flow between pairs of departments in consecutive periods may require the rearrangement of departments during the planning horizon, in order to keep material handling costs low. The objective of our research is to minimize the sum of the material handling and rearrangement costs. Because of the combinatorial structure of the problem, only small sized problems can be solved in reasonable time using exact techniques. As a result, construction and improvement heuristics are developed for the proposed problem. So, in this paper, a tabu search heuristic, with a diversification strategy that includes frequency-based memory, penalty function and dynamic tabu list size, are developed to solve the dynamic facility layout problem with equal departments. The frequency-based memory structure is used to memorize the trace of repeated movement, and the dynamic tabu list is applied to give variation to the search space. The implementation of the proposed method is demonstrated using some benchmark problems and the results are discussed in detail. Computational experiments show that the proposed heuristic out-performed heuristics presented in the literature, with respect to solution quality.
The facility layout problem is determination of the position of a department in a specific facility. The simplest case of a facility layout problem is FLP with equal size departments, where the amount of material flowing between pairs of departments does not change during the planning horizon. This problem is called the static facility layout problem (SFLP), with equal size departments, and was modeled by Koopmans and Beckmann as a quadratic assignment problem (QAP). The dynamic facility layout problem (DFLP) is a well-researched problem to find the positions of departments on a plant floor for multiple periods (material u{fb02}ow between departments change during the planning horizon). The change in material flow between pairs of departments in consecutive periods may require the rearrangement of departments during the planning horizon, in order to keep material handling costs low. The objective of our research is to minimize the sum of the material handling and rearrangement costs. Because of the combinatorial structure of the problem, only small sized problems can be solved in reasonable time using exact techniques. As a result, construction and improvement heuristics are developed for the proposed problem. So, in this paper, a tabu search heuristic, with a diversification strategy that includes frequency-based memory, penalty function and dynamic tabu list size, are developed to solve the dynamic facility layout problem with equal departments. The frequency-based memory structure is used to memorize the trace of repeated movement, and the dynamic tabu list is applied to give variation to the search space. The implementation of the proposed method is demonstrated using some benchmark problems and the results are discussed in detail. Computational experiments show that the proposed heuristic out-performed heuristics presented in the literature, with respect to solution quality.
https://sjie.journals.sharif.edu/article_5277_58b11e09c28324a3074da7b6c9d9ff7d.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
TIME DEPENDENT VEHICLE ROUTING PROBLEM IN MULTIGRAPHS
TIME DEPENDENT VEHICLE ROUTING PROBLEM IN MULTIGRAPHS
119
127
5278
FA
M.
Setek
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
M.
Habibi
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
H.
Karimi
Dept. of Industrial Engineering\nK. N. Toosi University of Technology
Journal Article
2012
04
03
In classical time dependent routing problems, it is assumed there is a unique edge between two nodes. In other words, these are designed based on a simple graph. However, for many urban areas, where there is complex urbanism and different traffic constraints, the traditional VRP viewpoint is not very suitable. In this article, a novel extension of the time dependent vehicle routing problem (TDVRP) is studied, where more than one edge between the depot and customers, and between customers, is possible. For this purpose, this paper proposes a model called the Time Dependent Vehicle Routing Problem in Multigraphs. The multigraph is a graph which is allowed to have multiple edges or parallel edges. Today, many of the transportation networks are defined in multiple graphs. Particularly, the model for studying vehicle routing problems in large cities can be useful. This model is designed, based on the Malandranki and Daskin (1992) proposed model for TDVRP. This formulation minimizes total travel time. The time dependent vehicle routing problem is an extension of vehicle routing problem and since VRP is a NP-hard problem, TDVRP is also NP-hard. For this reason, heuristics is used usually to solve these problems. In here, a tabu search (TS) algorithm is suggested for solving the proposed model. The main feature of the proposed heuristic is random selection between two switching strategies at every stage of neighborhood search. These two strategies are binary switching and reverse switching. This feature improves the algorithm performance. Finally, computational results of the proposed Tabu search algorithm, and the exact solution, using a CPLEX solver in GAMS V23.5 software, on 99 random instances, are compared. These instances cover a good range of different problems. This result presents the efficiency of the proposed algorithm in the computational time and quality of the solution.
In classical time dependent routing problems, it is assumed there is a unique edge between two nodes. In other words, these are designed based on a simple graph. However, for many urban areas, where there is complex urbanism and different traffic constraints, the traditional VRP viewpoint is not very suitable. In this article, a novel extension of the time dependent vehicle routing problem (TDVRP) is studied, where more than one edge between the depot and customers, and between customers, is possible. For this purpose, this paper proposes a model called the Time Dependent Vehicle Routing Problem in Multigraphs. The multigraph is a graph which is allowed to have multiple edges or parallel edges. Today, many of the transportation networks are defined in multiple graphs. Particularly, the model for studying vehicle routing problems in large cities can be useful. This model is designed, based on the Malandranki and Daskin (1992) proposed model for TDVRP. This formulation minimizes total travel time. The time dependent vehicle routing problem is an extension of vehicle routing problem and since VRP is a NP-hard problem, TDVRP is also NP-hard. For this reason, heuristics is used usually to solve these problems. In here, a tabu search (TS) algorithm is suggested for solving the proposed model. The main feature of the proposed heuristic is random selection between two switching strategies at every stage of neighborhood search. These two strategies are binary switching and reverse switching. This feature improves the algorithm performance. Finally, computational results of the proposed Tabu search algorithm, and the exact solution, using a CPLEX solver in GAMS V23.5 software, on 99 random instances, are compared. These instances cover a good range of different problems. This result presents the efficiency of the proposed algorithm in the computational time and quality of the solution.
https://sjie.journals.sharif.edu/article_5278_b9a588ff16a8be240e8c9d9dbe3902cd.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
GWMA AND DGWMA CONTROL CHARTS FOR ATTRIBUTE QUALITY CHARACTERISTICS
GWMA AND DGWMA CONTROL CHARTS FOR ATTRIBUTE QUALITY CHARACTERISTICS
129
138
5279
FA
M.
Esmaieli
Dept. of Industrial Engineering\nAl-Zahra University
H.
Nikzaad
Dept. of Industrial Engineering\nAl-Zahra University
R.
Anjomshoaa
Dept. of Industrial Engineering\nAl-Zahra University
Journal Article
2012
06
23
Nowadays, statistical methods play a significant role in reducing waste and improving product quality at various stages of the product life cycle. Statistical process control (SPC), as the application of statistical methods, has been applied most frequently to monitor and control a process to ensure that it operates at its full potential to produce the conforming product. Moreover, control charts, known as Shewhart charts, are considered the most important tool in SPC. However, it has been shown that memory control charts, such as the Exponentially Weighted Moving Average (EWMA) control chart, can detect small shifts in a process faster than the Shewhart control chart. In other words, due to the added adjustment parameter, the memory control chart performs much better than the Shewhart control chart in monitoring small shifts of the process mean. The weighted moving average (GWMA) control chart is a generalization of the EWMA control chart. In recent years, the GWMA and the Double Generally Weighted Moving Average (DGWMA) control charts have demonstrated their higher efficiency compared to the EWMA control chart and the Double Exponentially Weighted Moving Average (DEWMA) control chart. Moreover, these charts are often designed for monitoring variable quality characteristics under normal distribution assumption. Attribute quality characteristics, which are based on counting the numbers of nonconformity with binomial distribution, or the numbers of nonconformity with Poisson distribution, have many applications in statistical process control. In this paper, we design the GWMA control chart and the DGWMA control chart for attribute quality characteristics and consider the effect of changing the parameters of charts on their false alarm rates. In addition, the performances of these charts are compared to each other (the EWMA control chart and the DEWMA control chart) using Monte Carlo simulation. Based on the results, it is seen that these new control charts also perform well in detecting small shifts when the attribute quality characteristics are monitored.
Nowadays, statistical methods play a significant role in reducing waste and improving product quality at various stages of the product life cycle. Statistical process control (SPC), as the application of statistical methods, has been applied most frequently to monitor and control a process to ensure that it operates at its full potential to produce the conforming product. Moreover, control charts, known as Shewhart charts, are considered the most important tool in SPC. However, it has been shown that memory control charts, such as the Exponentially Weighted Moving Average (EWMA) control chart, can detect small shifts in a process faster than the Shewhart control chart. In other words, due to the added adjustment parameter, the memory control chart performs much better than the Shewhart control chart in monitoring small shifts of the process mean. The weighted moving average (GWMA) control chart is a generalization of the EWMA control chart. In recent years, the GWMA and the Double Generally Weighted Moving Average (DGWMA) control charts have demonstrated their higher efficiency compared to the EWMA control chart and the Double Exponentially Weighted Moving Average (DEWMA) control chart. Moreover, these charts are often designed for monitoring variable quality characteristics under normal distribution assumption. Attribute quality characteristics, which are based on counting the numbers of nonconformity with binomial distribution, or the numbers of nonconformity with Poisson distribution, have many applications in statistical process control. In this paper, we design the GWMA control chart and the DGWMA control chart for attribute quality characteristics and consider the effect of changing the parameters of charts on their false alarm rates. In addition, the performances of these charts are compared to each other (the EWMA control chart and the DEWMA control chart) using Monte Carlo simulation. Based on the results, it is seen that these new control charts also perform well in detecting small shifts when the attribute quality characteristics are monitored.
https://sjie.journals.sharif.edu/article_5279_230139f08b7c4477fc1808610e7421db.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
THE EFFECT OF KNOWLEDGE MANAGEMENT ON ORGANIZATIONAL PERFORMANCE USING THE BALANCED SCOR
THE EFFECT OF KNOWLEDGE MANAGEMENT ON ORGANIZATIONAL PERFORMANCE USING THE BALANCED SCOR
139
147
5280
FA
M.
Fathian
Dept. of Industrial Engineering\nIran University of Science and Technology
P.
Akhavan
Dept. of Industrial Engineering\nMalek Ashtar University
S.
Cheraghali
Dept. of Industrial Engineering\nIran University of Science and Technology
Journal Article
2011
12
31
Today, communities and organizations are seeking sustainable competitive advantages. Under these conditions, organizations which identify customer need and adapt themselves with the customer, are more successful. To achieve this objective, knowledge can create a sustainable competitive advantage. In this regard, knowledge management, as a useful approach, plays a key role in organizations to develop their intelligence capital and innovation, and promote their performance. Knowledge management is an insightful subject developed over decades, which, in recent years, has emerged in marketing society. Knowledge management is a field that can create integrity in identification, storing, assessment, marketing and involvement of the entire companys assets. In other words, it is a collection of processes that governs the creation, dissemination, and utilization of knowledge. In recent years, various organizations have focused on knowledge management, and many of them, such as manufacturers and service providers, consider it a key factor in achieving competitive advantages in the market and increasing productivity.The Balanced Scorecard is a strategic performance management tool that is used extensively in organizations to align business activities to the vision and strategy of the organization, improve internal and external communication, and monitor organization performance. A Balanced Scorecard approach, generally, has four perspectives: financial, customer, internal processes, learning and growth.In this research, on the one hand, we consider the main activities of knowledge management and, on the other hand, the four perspectives of the balanced scorecard, and then, study the relationship between them. The main purpose of this study to evaluate the usefulness of knowledge management on organization performance improvement, based on balanced scorecard.The research method employed in this study uses a questionnaire for data gathering. The statistical society used in this research includes the managers and experts of various industries in Tehran.The data analysis done by SPSS and Minitab shows that knowledge management has a significant impact on rganizational performance
Today, communities and organizations are seeking sustainable competitive advantages. Under these conditions, organizations which identify customer need and adapt themselves with the customer, are more successful. To achieve this objective, knowledge can create a sustainable competitive advantage. In this regard, knowledge management, as a useful approach, plays a key role in organizations to develop their intelligence capital and innovation, and promote their performance. Knowledge management is an insightful subject developed over decades, which, in recent years, has emerged in marketing society. Knowledge management is a field that can create integrity in identification, storing, assessment, marketing and involvement of the entire companys assets. In other words, it is a collection of processes that governs the creation, dissemination, and utilization of knowledge. In recent years, various organizations have focused on knowledge management, and many of them, such as manufacturers and service providers, consider it a key factor in achieving competitive advantages in the market and increasing productivity.The Balanced Scorecard is a strategic performance management tool that is used extensively in organizations to align business activities to the vision and strategy of the organization, improve internal and external communication, and monitor organization performance. A Balanced Scorecard approach, generally, has four perspectives: financial, customer, internal processes, learning and growth.In this research, on the one hand, we consider the main activities of knowledge management and, on the other hand, the four perspectives of the balanced scorecard, and then, study the relationship between them. The main purpose of this study to evaluate the usefulness of knowledge management on organization performance improvement, based on balanced scorecard.The research method employed in this study uses a questionnaire for data gathering. The statistical society used in this research includes the managers and experts of various industries in Tehran.The data analysis done by SPSS and Minitab shows that knowledge management has a significant impact on rganizational performance
https://sjie.journals.sharif.edu/article_5280_afbc5add6f0820bf34c6c75c2dbb6fca.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
30
1.2
2014
06
22
INTEGRATED MODEL FOR EVALUATING LEVEL OF READINESS IN E-BUSINESSES OF INDUSTRIAL SMES FOR ATTENDANCE IN E-MARKETS
INTEGRATED MODEL FOR EVALUATING LEVEL OF READINESS IN E-BUSINESSES OF INDUSTRIAL SMES FOR ATTENDANCE IN E-MARKETS
158
149
5281
FA
R.
Shafei
Faculty of Management\nUniversity of Kurdistan
Journal Article
2012
04
16
SMEs can constitute an important source of local supply and service provision to economics sections. They usually have extensive local knowledge of resources, supply patterns and purchasing trends. Developing countries also represent a huge, largely untapped market for these corporations. SMEs can play a much bigger role in developing national economies, alleviating poverty, participating in the global economy and partnering with larger corporations. They do, however, need to be promoted. Such support requires commitments by and between governments, business and civil society. Increasingly, SMEs are achieving and sustaining competitive advantages using ICT that are propelling and accelerating the globalization of businesses. The growth of the Internet has created a global, cost-effective platform for businesses to communicate and conduct commerce. The Internet is making it possible for SMEs to enjoy the benefits that were once only afforded to larger businesses. The literature on macro e-readiness assessment has taken two approaches. The first group of studies undertakes a quantitative assessment, whereby countries are assigned numerical scores depending on how well they have performed on specific components of the e-readiness measure. One of the most important social capabilities in this subject is the extent of using e-commerce by these firms. Small and medium enterprises play a vital role in the expansion of adopting e-business for their capabilities. In this study, we survey the extent of e-business readiness of the industrial SMEs of Kurdistan, Kermanshah and Hamadan provinces and their related factors as a key factor in revealing the above concept. The research method is descriptive, and the sample included 156 firms. Those corporations were divided into two categories. The results show the level of e-readiness of group one, which was in the lower level of initial use of e-business. In regard to the findings, technology infrastructures have the highest effect on e-readiness for those firms.
SMEs can constitute an important source of local supply and service provision to economics sections. They usually have extensive local knowledge of resources, supply patterns and purchasing trends. Developing countries also represent a huge, largely untapped market for these corporations. SMEs can play a much bigger role in developing national economies, alleviating poverty, participating in the global economy and partnering with larger corporations. They do, however, need to be promoted. Such support requires commitments by and between governments, business and civil society. Increasingly, SMEs are achieving and sustaining competitive advantages using ICT that are propelling and accelerating the globalization of businesses. The growth of the Internet has created a global, cost-effective platform for businesses to communicate and conduct commerce. The Internet is making it possible for SMEs to enjoy the benefits that were once only afforded to larger businesses. The literature on macro e-readiness assessment has taken two approaches. The first group of studies undertakes a quantitative assessment, whereby countries are assigned numerical scores depending on how well they have performed on specific components of the e-readiness measure. One of the most important social capabilities in this subject is the extent of using e-commerce by these firms. Small and medium enterprises play a vital role in the expansion of adopting e-business for their capabilities. In this study, we survey the extent of e-business readiness of the industrial SMEs of Kurdistan, Kermanshah and Hamadan provinces and their related factors as a key factor in revealing the above concept. The research method is descriptive, and the sample included 156 firms. Those corporations were divided into two categories. The results show the level of e-readiness of group one, which was in the lower level of initial use of e-business. In regard to the findings, technology infrastructures have the highest effect on e-readiness for those firms.
https://sjie.journals.sharif.edu/article_5281_56ec5d902784a6066b89ef2f0df1e00a.pdf