Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
THE ROLE OF DEMOGRAPHIC CHARACTERISTICS IN PERCEIVED RISK AMONG INBOUND TOURISTS WHO VISIT IRAN
THE ROLE OF DEMOGRAPHIC CHARACTERISTICS IN PERCEIVED RISK AMONG INBOUND TOURISTS WHO VISIT IRAN
3
9
5203
FA
B.
Ranjbarian
Faculty of Administrative Science and Economi
M. R. Jalilvand
Jalilvand
Dept. of New Sciences and Technologies Universit&zw
Journal Article
2010
01
10
Consumer decisions are usually along with a given level of risk. Involvement of the risk element in consumer decisions is more apparent in service contexts, such as the tourist industry, especially as travel and tourism are kinds of decisions with high involvement. Therefore, a number of risks and uncertainties are associated with travel decisions. Of course, instead of actual risk, it is perceived risk that influences travel decisions and the intended tourist destination choice. Generally, tourists make decisions based on their perceptions rather than actual facts. There are seven risks have been identified with regard to travel and tourism; facility, finances, physical, psychology, satisfaction, social, and time risk. This paper investigates tourist perception of risk whilst visiting Isfahan as a tourist destination. In addition, the role of socio-demographic characteristics, including age, gender, nationality, trip purpose, and previous experience, on perceived risk has been investigated. The statistical population of the study is tourists who have visited Isfahan during the research period; August-October, 2009. 224 tourists were selected randomly. Data analysis was based on one-way ANOVA and Spearman correlation using SPSS. An ANOVA test revealed that that the respondent characteristics, such as nationality, gender, previous experience of traveling to Iran and purpose of visit, influenced the perceptions of risk. The results show that age has no impact on tourist perceptions of risk. Respondents who were visiting friends and relatives were more likely to perceive Isfahan as a high-risk destination than others. Women perceived a greater degree of risk than men. Tourists with previous experience perceived lower degrees of risk than first-timers. The perception of associated physical and social risk varied significantly by tourist nationality. The results also indicate that tourists search different information sources to reduce their perceived risks.%looseness=1
Consumer decisions are usually along with a given level of risk. Involvement of the risk element in consumer decisions is more apparent in service contexts, such as the tourist industry, especially as travel and tourism are kinds of decisions with high involvement. Therefore, a number of risks and uncertainties are associated with travel decisions. Of course, instead of actual risk, it is perceived risk that influences travel decisions and the intended tourist destination choice. Generally, tourists make decisions based on their perceptions rather than actual facts. There are seven risks have been identified with regard to travel and tourism; facility, finances, physical, psychology, satisfaction, social, and time risk. This paper investigates tourist perception of risk whilst visiting Isfahan as a tourist destination. In addition, the role of socio-demographic characteristics, including age, gender, nationality, trip purpose, and previous experience, on perceived risk has been investigated. The statistical population of the study is tourists who have visited Isfahan during the research period; August-October, 2009. 224 tourists were selected randomly. Data analysis was based on one-way ANOVA and Spearman correlation using SPSS. An ANOVA test revealed that that the respondent characteristics, such as nationality, gender, previous experience of traveling to Iran and purpose of visit, influenced the perceptions of risk. The results show that age has no impact on tourist perceptions of risk. Respondents who were visiting friends and relatives were more likely to perceive Isfahan as a high-risk destination than others. Women perceived a greater degree of risk than men. Tourists with previous experience perceived lower degrees of risk than first-timers. The perception of associated physical and social risk varied significantly by tourist nationality. The results also indicate that tourists search different information sources to reduce their perceived risks.%looseness=1
https://sjie.journals.sharif.edu/article_5203_d761d3a91ae831d240445c520ba5b2b4.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
APPLICATION OF FUZZY MULTI ATTRIBUTE DECISION MAKING IN DETERMINING CRITICAL PATH USING TIME, COST, RISK AND QUALITY CRITERIA
APPLICATION OF FUZZY MULTI ATTRIBUTE DECISION MAKING IN DETERMINING CRITICAL PATH USING TIME, COST, RISK AND QUALITY CRITERIA
11
17
5204
FA
F.
Golozari
Dept. of Industrial Engineering University of Sc&am
M.
Amiri
Faculty of Management and Accounting Allameh Ta&zwn
Journal Article
2010
02
06
In todays highly competitive business environment, project management ability to schedule activities and monitor progress within strict cost, time and performance guidelines is becoming increasingly important to obtain competitive priorities, such as on time delivery and customization. The most commonly used project management technique is the critical path method which provides an excellent way of calculating the shortest completion time and the critical activities for a project. Sometimes, during the performance of a project, we meet some activities, which because of financial problems or budget shortages are not finished on time. if the activity is not finished on the recent critical path, it causes to change the critical path and other path cause to be delayed the finish time.So,there are several additional parameters that affect the potential criticality of a path. In this paper, an algorithm is introduced which considers not only time factor but also cost, risk and quality criteria to determine the critical path under a fuzzy environment. In this algorithm, first, decision makers allocate time, cost, risk and quality to each activity. According to the lack of data and information, in the proposed algorithm, the ratings of each activity and the weight of each criterion are described by fuzzy triangular numbers and linguistic variables. By adding up triangular fuzzy numbers, the final evaluation value of each criterion for all paths is determined. TOPSIS is a multiple criteria method to identify solutions from a finite set of alternatives that has been widely applied to various sciences to make different decisions. The basic principle is that the chosen alternative should have the shortest distance from the positive ideal solution, and the farthest distance from the negative ideal solution. After adding up triangular fuzzy numbers, using the fuzzy TOPSIS method proposed by the authors in another paper, the critical path is selected. Finally, the numerical example is solved to illustrate the procedure of the proposed method.
In todays highly competitive business environment, project management ability to schedule activities and monitor progress within strict cost, time and performance guidelines is becoming increasingly important to obtain competitive priorities, such as on time delivery and customization. The most commonly used project management technique is the critical path method which provides an excellent way of calculating the shortest completion time and the critical activities for a project. Sometimes, during the performance of a project, we meet some activities, which because of financial problems or budget shortages are not finished on time. if the activity is not finished on the recent critical path, it causes to change the critical path and other path cause to be delayed the finish time.So,there are several additional parameters that affect the potential criticality of a path. In this paper, an algorithm is introduced which considers not only time factor but also cost, risk and quality criteria to determine the critical path under a fuzzy environment. In this algorithm, first, decision makers allocate time, cost, risk and quality to each activity. According to the lack of data and information, in the proposed algorithm, the ratings of each activity and the weight of each criterion are described by fuzzy triangular numbers and linguistic variables. By adding up triangular fuzzy numbers, the final evaluation value of each criterion for all paths is determined. TOPSIS is a multiple criteria method to identify solutions from a finite set of alternatives that has been widely applied to various sciences to make different decisions. The basic principle is that the chosen alternative should have the shortest distance from the positive ideal solution, and the farthest distance from the negative ideal solution. After adding up triangular fuzzy numbers, using the fuzzy TOPSIS method proposed by the authors in another paper, the critical path is selected. Finally, the numerical example is solved to illustrate the procedure of the proposed method.
https://sjie.journals.sharif.edu/article_5204_755109ad79f4d755916eaafefed2ee66.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
OFFERING A MODEL FOR CALCULATING CUSTOMER LIFE TIME VALUE (CLV) IN THE CONSTRUCTION ACHINERY INDUSTRY
OFFERING A MODEL FOR CALCULATING CUSTOMER LIFE TIME VALUE (CLV) IN THE CONSTRUCTION ACHINERY INDUSTRY
19
26
5205
FA
A. Albadvicorresponding
Albadvi
Dept. of Industrial Engineering\r\nTarbiat Modare&zwn
E.
Alikhani
Dept. of Information Technology Engineering -E co&z
Journal Article
2009
07
12
The purpose of this article is to propose a model to calculate customer life time value (CLV) in the construction machinery industry. Researchers have tried to identify and compare different models for calculation of CLV, and, by considering customer behaviour and the nature of the products in the construction machinery industry, have selected the most suitable model. In this study, two sets of CLV models; customer retention-rate based, and customer churn-rate based, were compared with each other and, as construction machinery is a durable product, the set of CLV models based on customer retention-rate was selected for the industry. After that, all the proposed models in this category of retention-rate based models were compared with each other considering the characteristics of the industry, and finally, the model proposed by Gupta was selected for calculation of CLV. The main challenge in using the Gupta model is calculation of the retention rate parameter for the customers. We applied RFM for customer clustering, and defined the optimum number of customer segments using Matlab programming and K-Means algorithm. In this process, we identified and compared the main parameters in RFM clustering and the most important ones were identified. Retention probability for each segment was calculated using actual customer data in two consecutive periods from a real case study in the industry. After the calculation of the retention rate for each segment, and based on the total purchases and profit margins for each customer, customer life time value for each customer was calculated using the Gupta model. The proposed model for customer segmentation, and calculation of the customer life time value was applied to an Iranian construction machinery production company. In addition to customer life time value, the total value for each segment was also calculated, which can be used in strategic market planning. The identification of key customers was also another outcome of this study.
The purpose of this article is to propose a model to calculate customer life time value (CLV) in the construction machinery industry. Researchers have tried to identify and compare different models for calculation of CLV, and, by considering customer behaviour and the nature of the products in the construction machinery industry, have selected the most suitable model. In this study, two sets of CLV models; customer retention-rate based, and customer churn-rate based, were compared with each other and, as construction machinery is a durable product, the set of CLV models based on customer retention-rate was selected for the industry. After that, all the proposed models in this category of retention-rate based models were compared with each other considering the characteristics of the industry, and finally, the model proposed by Gupta was selected for calculation of CLV. The main challenge in using the Gupta model is calculation of the retention rate parameter for the customers. We applied RFM for customer clustering, and defined the optimum number of customer segments using Matlab programming and K-Means algorithm. In this process, we identified and compared the main parameters in RFM clustering and the most important ones were identified. Retention probability for each segment was calculated using actual customer data in two consecutive periods from a real case study in the industry. After the calculation of the retention rate for each segment, and based on the total purchases and profit margins for each customer, customer life time value for each customer was calculated using the Gupta model. The proposed model for customer segmentation, and calculation of the customer life time value was applied to an Iranian construction machinery production company. In addition to customer life time value, the total value for each segment was also calculated, which can be used in strategic market planning. The identification of key customers was also another outcome of this study.
https://sjie.journals.sharif.edu/article_5205_dedcba4fb4a7c8b11766454398807390.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
PRICE AND LEAD-TIME STUDY IN A DECENTRALIZED SUPPLY CHAIN UNDER COMPETITION
PRICE AND LEAD-TIME STUDY IN A DECENTRALIZED SUPPLY CHAIN UNDER COMPETITION
27
41
5206
FA
M.
Afzalabadi
Dept. of Industrial Engineering Sharif Univers&zwnj
H.
Shavandi
Dept. of Industrial Engineering Sharif Univers&zwnj
Journal Article
2009
07
27
In this paper, we study a two-echelon supply chain containing a manufacturer and a number of suppliers who face price and lead time sensitive demand. We use the Stackelberg game for the manufacturer as the leader, and the suppliers as followers. Since making decisions about price and lead time at the supply level is, simultaneously, under horizontal competition, we use the Nash Equilibrium. We assume that custom demand depends on manufacturing price. The proportion of demand the manufacturer assigns to each supplier is dependent on its price and scheduled lead time. The objective of each supplier is to choose the best price and lead time to maximize his/her functional profit. In todays competitive market, price and lead time are two important factors for the success of a company, and many companies use a short lead time as a marketing weapon to have more customers. Price and lead time are also highly interdependent, and some customers are willing to pay higher prices for shorter lead time. So, assessing the impacts of pricing and time performance strategies on demand, and the impacts of capacity decisions and issues related to company operations on these strategies, is very important. In this problem, we use the multiplicative competitive interaction function to model the market share by considering price and scheduled lead time. At first, the manufacturers optimal response is obtained, with regard to the response of the suppliers, and then the decision will be made at the suppliers level. We prove that there is a unique Nash equilibrium for the price and scheduled lead time of suppliers that is obtained by using an iterative algorithm. By numerical study, we will examine the impact of different market characteristics on the price and scheduled lead time determined by each supplier. The impact of the suppliers decision on that of the manufacturer, and its sensitivity analysis, with respect to the market situation, are also analyzed.
In this paper, we study a two-echelon supply chain containing a manufacturer and a number of suppliers who face price and lead time sensitive demand. We use the Stackelberg game for the manufacturer as the leader, and the suppliers as followers. Since making decisions about price and lead time at the supply level is, simultaneously, under horizontal competition, we use the Nash Equilibrium. We assume that custom demand depends on manufacturing price. The proportion of demand the manufacturer assigns to each supplier is dependent on its price and scheduled lead time. The objective of each supplier is to choose the best price and lead time to maximize his/her functional profit. In todays competitive market, price and lead time are two important factors for the success of a company, and many companies use a short lead time as a marketing weapon to have more customers. Price and lead time are also highly interdependent, and some customers are willing to pay higher prices for shorter lead time. So, assessing the impacts of pricing and time performance strategies on demand, and the impacts of capacity decisions and issues related to company operations on these strategies, is very important. In this problem, we use the multiplicative competitive interaction function to model the market share by considering price and scheduled lead time. At first, the manufacturers optimal response is obtained, with regard to the response of the suppliers, and then the decision will be made at the suppliers level. We prove that there is a unique Nash equilibrium for the price and scheduled lead time of suppliers that is obtained by using an iterative algorithm. By numerical study, we will examine the impact of different market characteristics on the price and scheduled lead time determined by each supplier. The impact of the suppliers decision on that of the manufacturer, and its sensitivity analysis, with respect to the market situation, are also analyzed.
https://sjie.journals.sharif.edu/article_5206_d8ad98e73b32baeeae94ba56a3d02f8d.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
title{\r\nCRITICAL SUCCESS FACTORS IN OUTSOURCING OF CONSTRUCTION PROJECTS - CLIENTS \r\nPERSPECTIVE (CASE: TEHRAN MUNICIPALITY)
title{\r\nCRITICAL SUCCESS FACTORS IN OUTSOURCING OF CONSTRUCTION PROJECTS - CLIENTS \r\nPERSPECTIVE (CASE: TEHRAN MUNICIPALITY)
43
51
5207
FA
M.
Sepehri
Graduate School of Management and Economics \r\nSha&z
Journal Article
2009
11
07
keywords{project management, outsourcing, client perspective, contractor, critical success factor.} maketitle begin{abstract} Outsourcing in construction projects has increased considerably in number and volume, as evident in the literature and in practice. Implementing project outsourcing decisions successfully is an important and challenging issue for client organizations. The main criteria are usually to finish the projects by a pre-defined scope, time, budget and quality accepted by the final customer. However, a number of pre-requisites, or critical success factors (CSFs), can help the organization to increase the chance of success. The construction industry is chosen in this study due to its project-based nature, the importance of its success in the industrial development of developing countries, and its frequency and level of outsourcing. Identifying and evaluating critical success factors in this industry will help client organizations to develop an implementation strategy to insure their outsourced projects are accompanied by the needed factors towards overall success.looseness=1 An abstract framework is defined and a model is developed, based on the Pinto and Slevins (1986) classic ten critical project success factors. Detailed interviews are conducted with a selected expert panel. Furthermore, key factors influencing the success of outsourced projects are then evaluated quantitatively using the cases of recent construction projects within Tehran Municipality. A questionnaire is given to the expert in the client organization within the municipality, which is then analyzed statistically. Initial results show that successful implementation of outsourcing strategies in construction projects is strongly influenced by the level of coordination with the contractor, contractor selection, clear project objectives, defined technical tasks and top management support within the clients organization. The results are verified with the expert, showing that such factors, among many others, have a large influence on reaching successful conclusion in outsourcing parts of the whole of construction projects.
keywords{project management, outsourcing, client perspective, contractor, critical success factor.} maketitle begin{abstract} Outsourcing in construction projects has increased considerably in number and volume, as evident in the literature and in practice. Implementing project outsourcing decisions successfully is an important and challenging issue for client organizations. The main criteria are usually to finish the projects by a pre-defined scope, time, budget and quality accepted by the final customer. However, a number of pre-requisites, or critical success factors (CSFs), can help the organization to increase the chance of success. The construction industry is chosen in this study due to its project-based nature, the importance of its success in the industrial development of developing countries, and its frequency and level of outsourcing. Identifying and evaluating critical success factors in this industry will help client organizations to develop an implementation strategy to insure their outsourced projects are accompanied by the needed factors towards overall success.looseness=1 An abstract framework is defined and a model is developed, based on the Pinto and Slevins (1986) classic ten critical project success factors. Detailed interviews are conducted with a selected expert panel. Furthermore, key factors influencing the success of outsourced projects are then evaluated quantitatively using the cases of recent construction projects within Tehran Municipality. A questionnaire is given to the expert in the client organization within the municipality, which is then analyzed statistically. Initial results show that successful implementation of outsourcing strategies in construction projects is strongly influenced by the level of coordination with the contractor, contractor selection, clear project objectives, defined technical tasks and top management support within the clients organization. The results are verified with the expert, showing that such factors, among many others, have a large influence on reaching successful conclusion in outsourcing parts of the whole of construction projects.
https://sjie.journals.sharif.edu/article_5207_4c1b8a7329b7d7984c5c593b47bf339d.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
SELECTION OF E-COMMERCE STRATEGY USING FUZZY ANALYTIC HIERARCHY PROCESS (CASE STUDY: ISFAHAN ALLOY STEEL CO.
SELECTION OF E-COMMERCE STRATEGY USING FUZZY ANALYTIC HIERARCHY PROCESS (CASE STUDY: ISFAHAN ALLOY STEEL CO.
53
62
5208
FA
A.
Sanayei
ITM Research Group University of Isfahan
S.
Fathi
ITM Research Group University of Isfahan
A.R.
Emami
ITM Research Group University of Isfahan
Journal Article
2010
02
03
Advancement of information and communication technologies in the 20th century transformed old fashioned economics into digital economics. As a result, the Internet and Electronic Commerce are outcomes of this transformation. Electronic Commerce provides the convenience of 24 hour shopping is any place across the worldwide, whenever the customer wants it. Electronic Commerce looms large on the horizons of tomorrow, and it promises to transform trade and industry in ways not imagined or comprehended. Today, business managers are using Electronic tools to communicate with customers and suppliers in order to deal with a turbulent competitive environment. How to use e-commerce and make relevant decisions is a strategic choice that enhances organizational competitive advantages. By choosing an appropriate e-commerce strategy that fits environmental, organizational, and inter-organizational factors, including the competitive strategy of the company, managers try to provide benefits for their organizations. Fuzzy logic is a form of many-valued logic or probabilistic logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic; true or false, fuzzy logic variables may have a truth value that ranges in degree between 0 and 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false. The Analytic Hierarchy Process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. This paper uses a fuzzy analytic hierarchical process to choose electronic commerce strategies, considering various factors in the selected organization (Isfahan Alloy Steel Company).The results of the paper show that the electronic commerce strategy associated with purchasing management is the first priority, and electronic commerce strategies associated with customer based expansion and customer services are the next priority.
Advancement of information and communication technologies in the 20th century transformed old fashioned economics into digital economics. As a result, the Internet and Electronic Commerce are outcomes of this transformation. Electronic Commerce provides the convenience of 24 hour shopping is any place across the worldwide, whenever the customer wants it. Electronic Commerce looms large on the horizons of tomorrow, and it promises to transform trade and industry in ways not imagined or comprehended. Today, business managers are using Electronic tools to communicate with customers and suppliers in order to deal with a turbulent competitive environment. How to use e-commerce and make relevant decisions is a strategic choice that enhances organizational competitive advantages. By choosing an appropriate e-commerce strategy that fits environmental, organizational, and inter-organizational factors, including the competitive strategy of the company, managers try to provide benefits for their organizations. Fuzzy logic is a form of many-valued logic or probabilistic logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic; true or false, fuzzy logic variables may have a truth value that ranges in degree between 0 and 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false. The Analytic Hierarchy Process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. This paper uses a fuzzy analytic hierarchical process to choose electronic commerce strategies, considering various factors in the selected organization (Isfahan Alloy Steel Company).The results of the paper show that the electronic commerce strategy associated with purchasing management is the first priority, and electronic commerce strategies associated with customer based expansion and customer services are the next priority.
https://sjie.journals.sharif.edu/article_5208_3e2bcad94d8430023f78349ed9711823.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
ANALYSIS OF THE POSITION OF THINK TANKS ON POLICY MAKING IN IRAN AND SEVERAL OTHER COUNTRIES
ANALYSIS OF THE POSITION OF THINK TANKS ON POLICY MAKING IN IRAN AND SEVERAL OTHER COUNTRIES
63
73
5209
FA
S.
Sohrabpour
Academy of Sciences
M.
Yaghoubi
Academy of Sciences
M.M.
Ghaffari
Academy of Sciences
M.
Shakeri
Academy of Sciences
M.R.
Eslami
Academy of Sciences
E.
Shirani
Academy of Sciences
M.
Pakpour
Institute for Advanced Studies in Basic Science
Journal Article
2010
02
08
While the term think tank originated in the 1950s, such organizations date back to the 19th century. The Institute for Defense and Security Studies (RUSI) was founded in 1831 in London and the Fabian Society in Britain dates from 1884. The Brooking Institution began in Washington in 1916. For most of the 20th century, independent public policy think tanks that performed research and provided advice on public policy were an organizational phenomenon found primarily in the United States, with a much smaller number in Canada and Western Europe. Although think tanks have existed in Japan for some time, they generally lack independence, having close ties to government ministries or corporations. There has been a veritable proliferation of think tanks around the world, beginning in the 1980s, as a result of the force of globalization, the end of the Cold War and the emergence of transnational problems. Two-thirds of all think tanks that exist today were established after 1970 and over half were established since 1980. The impact of globalization on think tank movements is most evident in regions such as Africa, Eastern Europe, Central Asia, and parts of Southeast Asia, where there is a concerted effort by the international community to support the creation of independent public policy research organizations. Today, there are over 4500 of these institutions around the world. Think tanks vary by ideological perspective, source of funding, issue focus and prospective audience. A new trend resulting from globalization is collaboration between think tanks across continents. For instance, the Carnegie endowment for international peace operates offices in Washington D.C., Beijing, Beirut, Brussels and Moscow. The activities of think tanks involve a balance between research, analysis and outreach. The range of activities they engage in include: framing policy issues, researching and writing books, articles, policy briefs, and conducting evaluation of government programs, creating networks and exchanges via workshops, seminars and briefings. This research focuses on the position of think tanks in different areas of policy making in twenty countries. The statistics, information, organization, type of activity, affiliation, objectives, and the national and international places of think tanks in these countries, have been identified. Moreover, the think tanks of the following countries have been analyzed in more detail: Russia, South Korea, Germany, France, USA, Canada, UK and Japan. Then, the existing non-governmental think tanks of Iran have been studied and evaluated. On this basis, a new model is proposed for an appropriate development of Irans think tanks, in order to improve decision-making processes in different areas of the country. The findings of this research indicate that decision-making and policy-making are mainly undertaken by think tanks, particularly in developed countries. Finally, our studies show that the think tanks of Iran are still at the early stages of development and have not yet established their correct and appropriate role, although they are staffed by efficient and skilled manpower. This issue calls for more funding and persuasion on the part of statesmen.
While the term think tank originated in the 1950s, such organizations date back to the 19th century. The Institute for Defense and Security Studies (RUSI) was founded in 1831 in London and the Fabian Society in Britain dates from 1884. The Brooking Institution began in Washington in 1916. For most of the 20th century, independent public policy think tanks that performed research and provided advice on public policy were an organizational phenomenon found primarily in the United States, with a much smaller number in Canada and Western Europe. Although think tanks have existed in Japan for some time, they generally lack independence, having close ties to government ministries or corporations. There has been a veritable proliferation of think tanks around the world, beginning in the 1980s, as a result of the force of globalization, the end of the Cold War and the emergence of transnational problems. Two-thirds of all think tanks that exist today were established after 1970 and over half were established since 1980. The impact of globalization on think tank movements is most evident in regions such as Africa, Eastern Europe, Central Asia, and parts of Southeast Asia, where there is a concerted effort by the international community to support the creation of independent public policy research organizations. Today, there are over 4500 of these institutions around the world. Think tanks vary by ideological perspective, source of funding, issue focus and prospective audience. A new trend resulting from globalization is collaboration between think tanks across continents. For instance, the Carnegie endowment for international peace operates offices in Washington D.C., Beijing, Beirut, Brussels and Moscow. The activities of think tanks involve a balance between research, analysis and outreach. The range of activities they engage in include: framing policy issues, researching and writing books, articles, policy briefs, and conducting evaluation of government programs, creating networks and exchanges via workshops, seminars and briefings. This research focuses on the position of think tanks in different areas of policy making in twenty countries. The statistics, information, organization, type of activity, affiliation, objectives, and the national and international places of think tanks in these countries, have been identified. Moreover, the think tanks of the following countries have been analyzed in more detail: Russia, South Korea, Germany, France, USA, Canada, UK and Japan. Then, the existing non-governmental think tanks of Iran have been studied and evaluated. On this basis, a new model is proposed for an appropriate development of Irans think tanks, in order to improve decision-making processes in different areas of the country. The findings of this research indicate that decision-making and policy-making are mainly undertaken by think tanks, particularly in developed countries. Finally, our studies show that the think tanks of Iran are still at the early stages of development and have not yet established their correct and appropriate role, although they are staffed by efficient and skilled manpower. This issue calls for more funding and persuasion on the part of statesmen.
https://sjie.journals.sharif.edu/article_5209_090327a70f621f14f8b2cff89254689f.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
AN EMPIRICAL INVESTIGATION INTO RELATIONSHIP BETWEEN SUPPLY CHAIN VULNERABILITY DRIVERS AND DIFFERENT RISKS IN SUPPLY CHAIN OF IRAN AUTOMOTIVE INDUSTRY
AN EMPIRICAL INVESTIGATION INTO RELATIONSHIP BETWEEN SUPPLY CHAIN VULNERABILITY DRIVERS AND DIFFERENT RISKS IN SUPPLY CHAIN OF IRAN AUTOMOTIVE INDUSTRY
75
85
5210
FA
M.
Iravani
Dept. of Industrial Engineering\r\nTarbiat Modare&zwn
S.H.
Zegordi
Dept. of Industrial Engineering\r\nTarbiat Modare&zwn
Journal Article
2009
08
24
Due to rapid global changes in the recent years, most life conditions have also changed. Accordingly, conditions that are affecting supply chains have also changed. Managers meet unknown conditions and new risks and it is necessary to prepare themeselves for efficient management. Today, supply chain risk management has gained considerable attention in academic and industrial environments. New concept of supply chain vulnerability has been introduced in recent decade and several studies have been accomplished. However, most of them concentrated on a theoretical view of risk and vulnerability and only a few of them empirically investigated these concepts. All researchers believe that both concepts of risk and vulnerability are dependent on the context of study. Because other research has been undertaken in countries which have completely different conditions in comparison with Iran (geographical, political, economical, etc), their results cannot be used in Iran, and this shows the necessity of undertaking such research in this area. The main purpose of this research is to investigate the relationship between supply chain vulnerability and supply chain risk. In this paper, supply chain risks are studied in more detail. An appropriate classification for Iran automotive supply chain risks is introduced, and the literature is expanded by introducing five new drivers of vulnerability. All of these were done by semi-structured interviews with specialists and also by considering the special conditions of Iran. After introducing risks and vulnerabilities, it is necessary to illustrate their relationship, because, in the practitioners point of view, it is difficult to distinguish between these concepts. The major objective of this research is the examination of the relationship between drivers of supply chain vulnerability and different types of supply chain risk. In other words, we can say that in this article, the main assumption is based on drivers of supply chain vulnerability, which lead to increased exposure to supply chain risk. This assumption is examined through empirical study with a research survey in the Iran automotive supply chain and by conducting semi-structured interviews with specialists (academicians and practitioners). Finally, the result is validated by statistical methods. Overall, the findings provide support for the hypothesis that supply chain characteristics or design variables (vulnerabilities drivers) influence exposure of the involved firms to the results of supply chain disruption. The results show that the drivers which are introduced in this article play a greater role in describing risk variance than others introduced in the literature. Totally, more than 30% of supply chain risks are explained by 10 drivers of supply chain vulnerabilities considered in this article. This shows that for supply chain risk management, managers should recognize their supply chain vulnerability drivers and manage them efficiently. Because these drivers play an important role in increasing exposure to risks, the efficient management of those drivers helps managers in making final decisions.
Due to rapid global changes in the recent years, most life conditions have also changed. Accordingly, conditions that are affecting supply chains have also changed. Managers meet unknown conditions and new risks and it is necessary to prepare themeselves for efficient management. Today, supply chain risk management has gained considerable attention in academic and industrial environments. New concept of supply chain vulnerability has been introduced in recent decade and several studies have been accomplished. However, most of them concentrated on a theoretical view of risk and vulnerability and only a few of them empirically investigated these concepts. All researchers believe that both concepts of risk and vulnerability are dependent on the context of study. Because other research has been undertaken in countries which have completely different conditions in comparison with Iran (geographical, political, economical, etc), their results cannot be used in Iran, and this shows the necessity of undertaking such research in this area. The main purpose of this research is to investigate the relationship between supply chain vulnerability and supply chain risk. In this paper, supply chain risks are studied in more detail. An appropriate classification for Iran automotive supply chain risks is introduced, and the literature is expanded by introducing five new drivers of vulnerability. All of these were done by semi-structured interviews with specialists and also by considering the special conditions of Iran. After introducing risks and vulnerabilities, it is necessary to illustrate their relationship, because, in the practitioners point of view, it is difficult to distinguish between these concepts. The major objective of this research is the examination of the relationship between drivers of supply chain vulnerability and different types of supply chain risk. In other words, we can say that in this article, the main assumption is based on drivers of supply chain vulnerability, which lead to increased exposure to supply chain risk. This assumption is examined through empirical study with a research survey in the Iran automotive supply chain and by conducting semi-structured interviews with specialists (academicians and practitioners). Finally, the result is validated by statistical methods. Overall, the findings provide support for the hypothesis that supply chain characteristics or design variables (vulnerabilities drivers) influence exposure of the involved firms to the results of supply chain disruption. The results show that the drivers which are introduced in this article play a greater role in describing risk variance than others introduced in the literature. Totally, more than 30% of supply chain risks are explained by 10 drivers of supply chain vulnerabilities considered in this article. This shows that for supply chain risk management, managers should recognize their supply chain vulnerability drivers and manage them efficiently. Because these drivers play an important role in increasing exposure to risks, the efficient management of those drivers helps managers in making final decisions.
https://sjie.journals.sharif.edu/article_5210_f96e7b7ced038ef826b08f5897760797.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
DECISIVE FACTORS IN ADOPTION OF INTERNET BANKING ؛(CASE STUDY: EGHTESAD NOVIN BANK)
DECISIVE FACTORS IN ADOPTION OF INTERNET BANKING ؛(CASE STUDY: EGHTESAD NOVIN BANK)
87
98
5211
FA
P.
Hanafizadeh
Faculty of Management and Accounting Allameh Ta&zwn
J.
Asadi
Faculty of Management and Accounting Allameh Ta&zwn
H.R.
Khedmatgozar
Dept. of IT management\r\nIranian Research Institut&z
Journal Article
2009
09
12
Internet Banking (IB) is the term used for the new age banking system. Actually, IB is revolutionizing the banking industry and is no longer seen as merely an additional delivery channel. Despite the advantages of IB, recent views suggest that IB may not achieve the levels of transformation as predicted. Due to this fact, adoption has become one of the discussed topics in the research area of this banking delivery channel. Knowing the determinants on IB adoption could help banking companies improve their service to attract more users. This research has been conducted to find decisive factors in the adoption and usage of IB through a developed technology acceptance model. Based on this model, the application of this technology is dependent on behavioral intention, which is, in turn, affected by perceived usefulness, perceived ease of use, perceived self-efficacy and perceived risk. The questionnaire used in this study was distributed to Eghtesad Novin Bank customers and 381 effective responses were received. Then, the gathered data were analyzed using a three step method, consisting of the Chi squire test, a correlation test and regression analysis. The findings of the study indicate that perceived usefulness, perceived ease of use and perceived self-efficacy have positive effects on the adoption of IB. Despite research hypotheses, perceived risk has a beneficial effect on the adoption of IB. Moreover, behavioral intention has a positive impact on the utilization of this service. The managerial implications of the study are that, with information and training courses, the banks should provide conditions under which bank customers feel that the use of IB service is easy and is easily accessible. Advertising through mass media, newspapers, bank websites and other media, printing information brochures and help booklets can introduce the advantages and ease of use of IB compared with traditional banking. Bank managers can also increase the confidence and self-efficacy of customers using IB services by computer and Internet training courses for traditional banking customers and using demonstrations to teach them how to use this service.
Internet Banking (IB) is the term used for the new age banking system. Actually, IB is revolutionizing the banking industry and is no longer seen as merely an additional delivery channel. Despite the advantages of IB, recent views suggest that IB may not achieve the levels of transformation as predicted. Due to this fact, adoption has become one of the discussed topics in the research area of this banking delivery channel. Knowing the determinants on IB adoption could help banking companies improve their service to attract more users. This research has been conducted to find decisive factors in the adoption and usage of IB through a developed technology acceptance model. Based on this model, the application of this technology is dependent on behavioral intention, which is, in turn, affected by perceived usefulness, perceived ease of use, perceived self-efficacy and perceived risk. The questionnaire used in this study was distributed to Eghtesad Novin Bank customers and 381 effective responses were received. Then, the gathered data were analyzed using a three step method, consisting of the Chi squire test, a correlation test and regression analysis. The findings of the study indicate that perceived usefulness, perceived ease of use and perceived self-efficacy have positive effects on the adoption of IB. Despite research hypotheses, perceived risk has a beneficial effect on the adoption of IB. Moreover, behavioral intention has a positive impact on the utilization of this service. The managerial implications of the study are that, with information and training courses, the banks should provide conditions under which bank customers feel that the use of IB service is easy and is easily accessible. Advertising through mass media, newspapers, bank websites and other media, printing information brochures and help booklets can introduce the advantages and ease of use of IB compared with traditional banking. Bank managers can also increase the confidence and self-efficacy of customers using IB services by computer and Internet training courses for traditional banking customers and using demonstrations to teach them how to use this service.
https://sjie.journals.sharif.edu/article_5211_eaacdc3995e7839e8106a85e7a7f5840.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
PROJECT SELECTION BASED ON OPTIMAL RESOURCE ALLOCATION USING ANP-GP APPROACH
PROJECT SELECTION BASED ON OPTIMAL RESOURCE ALLOCATION USING ANP-GP APPROACH
99
111
5212
FA
S.Fazli
Fazli
Imam Khomeini International University
S.S.Madani
Madani
Imam Khomeini International University
Journal Article
2010
01
17
Lack of resources is one of the problems of todays organizations, having a special character in each period of time. Project selection stands for the priority of projects and allocation of organization resources only for those projects that have gotten the greatest priority, and from which, due to selection and allocation, organization profit will be maximum. Different factors can have an effect, including quantitative and qualitative criteria, and projects have been selected and given priority because of them. It is worth mentioning that there is an interdependent relationship between those criteria, and taking this relationship into account can have an effect on the conditions of priority and selection. The objective of this paper is to present a systematic method that considers interdependent relations among criteria, the projects that have been given priority due to these relations and the organization resources that are allocated to projects with the greater priority. In this paper, interdependence relations among criteria are determined using an analytic network process to find the projects that have been given priority. In the next step, the organizations resources among the projects given the greatest priority are allocated using zero-one goal programming. The result of the questioned model of performance in the studied organization was in the following manner: Six criteria were selected in the use of the model, and, due to expert viewpoints, the interdependence relations among the criteria were identified. Due to taking priorities from the analytic network process, the model of zero-one goal programming is formulized in such a way that by solving this model from among seven projects, the questioned five projects have been selected, and resources are allocated from these five projects.
Lack of resources is one of the problems of todays organizations, having a special character in each period of time. Project selection stands for the priority of projects and allocation of organization resources only for those projects that have gotten the greatest priority, and from which, due to selection and allocation, organization profit will be maximum. Different factors can have an effect, including quantitative and qualitative criteria, and projects have been selected and given priority because of them. It is worth mentioning that there is an interdependent relationship between those criteria, and taking this relationship into account can have an effect on the conditions of priority and selection. The objective of this paper is to present a systematic method that considers interdependent relations among criteria, the projects that have been given priority due to these relations and the organization resources that are allocated to projects with the greater priority. In this paper, interdependence relations among criteria are determined using an analytic network process to find the projects that have been given priority. In the next step, the organizations resources among the projects given the greatest priority are allocated using zero-one goal programming. The result of the questioned model of performance in the studied organization was in the following manner: Six criteria were selected in the use of the model, and, due to expert viewpoints, the interdependence relations among the criteria were identified. Due to taking priorities from the analytic network process, the model of zero-one goal programming is formulized in such a way that by solving this model from among seven projects, the questioned five projects have been selected, and resources are allocated from these five projects.
https://sjie.journals.sharif.edu/article_5212_a3a50066fcdf4e318925aec37b9898f0.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
A NEURAL NETWORK APPROACH FOR SELECTING EVALUATION CRITERIA AND\r\nAPPLICATION OF DATA MINING IN DETERMINING SUPPLIERS CREDIT LEVELS\r\n(CASE STUDY: ISOICO)
A NEURAL NETWORK APPROACH FOR SELECTING EVALUATION CRITERIA AND\r\nAPPLICATION OF DATA MINING IN DETERMINING SUPPLIERS CREDIT LEVELS\r\n(CASE STUDY: ISOICO)
113
120
5213
FA
H.
Karimi
Dept. of Industrial Engineering\r\nSharif Univers&zwn
N. Salmasi
Salmasi
Dept. of Industrial Engineering\r\nSharif Univers&zwn
Journal Article
2010
01
19
Nowadays, with quick development of telecommunication technologies, companies are able to find their uppliers, as well as their options for partnering in business, easier than before in different countries. Based on the increase in the number of potential suppliers and their information, supplier management sections in companies have a long list of suppliers to choose from, and loads of information to process. Thus, proper methods should be adopted in order to evaluate the suppliers. On useful method is creating credit levels, and ranking suppliers based on their past cooperation with a company. For implementing such a method, a tool which makes it possible to analyze a data base and find the rules and patterns, such as data mining, is needed. Data mining can be performed by several techniques and algorithms. These techniques have different applications and each of them offer the best performance in a special situation. In this study, to achieve better results, different data mining algorithms, such as; C5.0, CART, CHAID and QUEST for classification, K-MEANS, KOHONEN and TWO-STEP for clustering, GRI and APRIORI for association rule mining (ARM) and the neural network (NN) technique, for determining the effective criteria to evaluate suppliers are used. Also, the CRISP-DM framework has been used for standardizing the process of data mining. Two indexes - calculation time and model error- have been used to evaluate the algorithms performance in training and testing data sets. In this research, neural network techniques are used to determine the significant evaluation criteria. A method is proposed to weigh the selected criteria, as well as comparing them among different data mining algorithms, to find the best technique. The techniques are applied to data gathered from ISOICO, an Iran Shipbuilding and Offshore Industries Complex Company, as a case study. The proposed method has three main phases: 1. data gathering and selecting effective evaluation criteria 2. calculating combined scores, and 3. determining features of credit levels. In phase1, all available attributes of suppliers are collected in a database. Several primary processes, such as cleaning, correcting, and categorizing, are performed to prepare the information for efficient application of data mining techniques. In this phase, attributes that are not important enough are omitted or merged together for creating more effective attributes. At the end of this phase, from 40 recorded attributes of each supplier, 30 are selected or are created by combination. All 30 selected attributes in 5 categories (key criteria, reception, quality and technical, finance, and delivery of goods) are evaluated and effective criteria are identified, without human decision and only by applying neural network techniques. The criterion for effectiveness in a neural network should have at least 5% effect on selecting the winner supplier. As a result, 18 effective criteria on selecting the winner are identified. In phase 2, after determining effective criteria, the combined scores for all suppliers are calculated. In order to calculate these scores, criteria scales are assimilated and the weights of the impacts of criteria are determined. To assimilate different criteria scales, it is assumed that these scores belong to the interval of (0,100). In this approach, the criteria which are regarded in % style are not changed but, in others, the best value is regarded as 100. Other criteria get a value proportional to the number of values of the corresponding variable of ttributes. In order to determine each criterions weight, several metrics, including the companys preference, the significance of criterion in literature, the separation capability of the criterion value, dependence or independence of the criterion, and existence of similar criterion, are considered. Finally, the combined scores of each supplier are calculated by multiplying synchronized values by weight of criteria. In phase 3, firstly, suppliers information is allocated to their corresponding credit levels. For this purpose, the number of credit levels and their corresponding score intervals are needed to be determined. In the proposed method, by assuming every 25% as a credit level, 4 levels are considered. Thus, suppliers information is assigned to their credit levels by a proportion of their combined score. Having assigned the identified information, it is possible to determine features of each credit level by applying data mining techniques, creating decision tree or if-then rules. The results show that k-means techniques offer the fastest performance (0.11s) in the relevant area of study. Also, the a priori technique offers the least model errors because its result is a rule set of equal type.
Nowadays, with quick development of telecommunication technologies, companies are able to find their uppliers, as well as their options for partnering in business, easier than before in different countries. Based on the increase in the number of potential suppliers and their information, supplier management sections in companies have a long list of suppliers to choose from, and loads of information to process. Thus, proper methods should be adopted in order to evaluate the suppliers. On useful method is creating credit levels, and ranking suppliers based on their past cooperation with a company. For implementing such a method, a tool which makes it possible to analyze a data base and find the rules and patterns, such as data mining, is needed. Data mining can be performed by several techniques and algorithms. These techniques have different applications and each of them offer the best performance in a special situation. In this study, to achieve better results, different data mining algorithms, such as; C5.0, CART, CHAID and QUEST for classification, K-MEANS, KOHONEN and TWO-STEP for clustering, GRI and APRIORI for association rule mining (ARM) and the neural network (NN) technique, for determining the effective criteria to evaluate suppliers are used. Also, the CRISP-DM framework has been used for standardizing the process of data mining. Two indexes - calculation time and model error- have been used to evaluate the algorithms performance in training and testing data sets. In this research, neural network techniques are used to determine the significant evaluation criteria. A method is proposed to weigh the selected criteria, as well as comparing them among different data mining algorithms, to find the best technique. The techniques are applied to data gathered from ISOICO, an Iran Shipbuilding and Offshore Industries Complex Company, as a case study. The proposed method has three main phases: 1. data gathering and selecting effective evaluation criteria 2. calculating combined scores, and 3. determining features of credit levels. In phase1, all available attributes of suppliers are collected in a database. Several primary processes, such as cleaning, correcting, and categorizing, are performed to prepare the information for efficient application of data mining techniques. In this phase, attributes that are not important enough are omitted or merged together for creating more effective attributes. At the end of this phase, from 40 recorded attributes of each supplier, 30 are selected or are created by combination. All 30 selected attributes in 5 categories (key criteria, reception, quality and technical, finance, and delivery of goods) are evaluated and effective criteria are identified, without human decision and only by applying neural network techniques. The criterion for effectiveness in a neural network should have at least 5% effect on selecting the winner supplier. As a result, 18 effective criteria on selecting the winner are identified. In phase 2, after determining effective criteria, the combined scores for all suppliers are calculated. In order to calculate these scores, criteria scales are assimilated and the weights of the impacts of criteria are determined. To assimilate different criteria scales, it is assumed that these scores belong to the interval of (0,100). In this approach, the criteria which are regarded in % style are not changed but, in others, the best value is regarded as 100. Other criteria get a value proportional to the number of values of the corresponding variable of ttributes. In order to determine each criterions weight, several metrics, including the companys preference, the significance of criterion in literature, the separation capability of the criterion value, dependence or independence of the criterion, and existence of similar criterion, are considered. Finally, the combined scores of each supplier are calculated by multiplying synchronized values by weight of criteria. In phase 3, firstly, suppliers information is allocated to their corresponding credit levels. For this purpose, the number of credit levels and their corresponding score intervals are needed to be determined. In the proposed method, by assuming every 25% as a credit level, 4 levels are considered. Thus, suppliers information is assigned to their credit levels by a proportion of their combined score. Having assigned the identified information, it is possible to determine features of each credit level by applying data mining techniques, creating decision tree or if-then rules. The results show that k-means techniques offer the fastest performance (0.11s) in the relevant area of study. Also, the a priori technique offers the least model errors because its result is a rule set of equal type.
https://sjie.journals.sharif.edu/article_5213_2795633895fbdb4dd6ed5110a212b9fc.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
QUANTIFYING RISK ANALYSIS USING DATABASE IN INDUSTRIAL INVESTMENT PROJECTS BY TOPSIS METHOD
QUANTIFYING RISK ANALYSIS USING DATABASE IN INDUSTRIAL INVESTMENT PROJECTS BY TOPSIS METHOD
121
127
5214
FA
A.
Taklif
Islamic Azad University, Qazvin
B.
Abbasi
Dept. of Industrial Engineering\r\nSharif Univers&zwn
A. A.
Najafi
Dept. of Industrial Engineering\r\nK.N. Toosi Univers
Journal Article
2010
02
03
A common problem in different stages of an operational project is the frequent delays in the completion of such projects. The main reason is the existence of risks and internal and external uncertainties. Overcoming these shortcomings requires the design of a program to effectively manage risks and uncertainties, in order to minimize their impact on the objectives of the project. Risk management in industrial investment plans is a process to identify potential risks and the probabilities of their actual occurrences and consequences. By selecting control procedures, suitable methods are proposed to make the execution of projects as secure and reliable as possible . In order to quantitatively analyze the existing risks in industrial investment projects, the utilization of a database supported by the Topsis algorithm is suggested in this paper. The database information is classified in the following two categories, i.e. information of investment plan and knowledge database. The first category is related to the information of the project under investigation. After completion of the project, part of the results derived from the project is transferred to the knowledge database for future projects. In the knowledge database, in addition to the information of these projects, the relevant data regarding other projects, together with related industrial standards and the necessary information, will be saved. Gradually, and with more information gathered in the database, the reliability of the solutions can be established using statistical analysis. The designed model in this paper has eight phases, and a case study on one of the industrial plans related to refrigerator manufacturers is carried out. Data collection and the results of risk assessment for industrial plans in the knowledge database provide the capability of analyzing the risk of new plans. In addition to the creation of such a database in any industrial organization, governmental institutions and service providers can benefit from having access to these databases.
A common problem in different stages of an operational project is the frequent delays in the completion of such projects. The main reason is the existence of risks and internal and external uncertainties. Overcoming these shortcomings requires the design of a program to effectively manage risks and uncertainties, in order to minimize their impact on the objectives of the project. Risk management in industrial investment plans is a process to identify potential risks and the probabilities of their actual occurrences and consequences. By selecting control procedures, suitable methods are proposed to make the execution of projects as secure and reliable as possible . In order to quantitatively analyze the existing risks in industrial investment projects, the utilization of a database supported by the Topsis algorithm is suggested in this paper. The database information is classified in the following two categories, i.e. information of investment plan and knowledge database. The first category is related to the information of the project under investigation. After completion of the project, part of the results derived from the project is transferred to the knowledge database for future projects. In the knowledge database, in addition to the information of these projects, the relevant data regarding other projects, together with related industrial standards and the necessary information, will be saved. Gradually, and with more information gathered in the database, the reliability of the solutions can be established using statistical analysis. The designed model in this paper has eight phases, and a case study on one of the industrial plans related to refrigerator manufacturers is carried out. Data collection and the results of risk assessment for industrial plans in the knowledge database provide the capability of analyzing the risk of new plans. In addition to the creation of such a database in any industrial organization, governmental institutions and service providers can benefit from having access to these databases.
https://sjie.journals.sharif.edu/article_5214_b87bc14b8c1ce2ed687b90a465776934.pdf
Sharif University of Technology
Sharif Journal of Industrial Engineering & Management
2676-4741
28
1
2012
07
22
A METHOD FOR DETERMINING REAL OPTION INPUT PARAMETERS IN THE IRANIAN PETROLEUM INDUSTRY: THE CASE OF SOUTH PARS GAS FIELD PROJECTS
A METHOD FOR DETERMINING REAL OPTION INPUT PARAMETERS IN THE IRANIAN PETROLEUM INDUSTRY: THE CASE OF SOUTH PARS GAS FIELD PROJECTS
129
137
5215
FA
M. A.
Nasiri
System Management and Productivity Group\r\nAmirka&am
A.M.
Kimiagari
Dept. of Industrial Engineering and Management s&am
Journal Article
2010
02
16
Business conditions are fraught with uncertainty and risks. These uncertainties hold with them valuableinformation. When uncertainty becomes resolved through the passage of time, managers can make the appropriate mid-course corrections through a change in business decisions and strategies. Real options incorporate this learning model, akin to having a strategic road map, while traditional analyses that neglect this managerial flexibility will grossly undervalue certain projects and strategies. Industry analysts, experts, and academics all agree that real options provide significant insights to project evaluation that traditional types of analysis, like the discounted cash flow approach, cannot provide. On the other hand, the nature of some industries, such as oil & gas, is very critical, and every delay in making decisions or wrong decisions causes irretrievable loss. Because of this characteristic, the usage of this approach has increased in this field over the years. For economic evaluation of the oil & gas project with the real options approach, we need to estimate some input parameters, such as risk free interest rate ($r_f$), discounted rate and volatility. Among them, the volatility of the cash flow is the most important, but estimation of that is very complicated since most projects are done for the first time and, consequently, there is no historical data for project values. In many cases, the projects are also irreversible. In this paper, we have tried to facilitate the use of this approach in Iranian oil & gas industries. Different methods for volatility estimation have been investigated and a new method has been proposed. We used the profitability index as a creditable financial index for applying Monte Carlo simulation for volatility estimation. In addition, a method for determination of risk free interest rate ($r_f$) and discounted rate has been introduced. Then, we investigate the accuracy of the mentioned techniques by applying an option to defer in our case study.
Business conditions are fraught with uncertainty and risks. These uncertainties hold with them valuableinformation. When uncertainty becomes resolved through the passage of time, managers can make the appropriate mid-course corrections through a change in business decisions and strategies. Real options incorporate this learning model, akin to having a strategic road map, while traditional analyses that neglect this managerial flexibility will grossly undervalue certain projects and strategies. Industry analysts, experts, and academics all agree that real options provide significant insights to project evaluation that traditional types of analysis, like the discounted cash flow approach, cannot provide. On the other hand, the nature of some industries, such as oil & gas, is very critical, and every delay in making decisions or wrong decisions causes irretrievable loss. Because of this characteristic, the usage of this approach has increased in this field over the years. For economic evaluation of the oil & gas project with the real options approach, we need to estimate some input parameters, such as risk free interest rate ($r_f$), discounted rate and volatility. Among them, the volatility of the cash flow is the most important, but estimation of that is very complicated since most projects are done for the first time and, consequently, there is no historical data for project values. In many cases, the projects are also irreversible. In this paper, we have tried to facilitate the use of this approach in Iranian oil & gas industries. Different methods for volatility estimation have been investigated and a new method has been proposed. We used the profitability index as a creditable financial index for applying Monte Carlo simulation for volatility estimation. In addition, a method for determination of risk free interest rate ($r_f$) and discounted rate has been introduced. Then, we investigate the accuracy of the mentioned techniques by applying an option to defer in our case study.
https://sjie.journals.sharif.edu/article_5215_ef447fd5d62197a7115e15ef039ef6aa.pdf