Naghmeh alvandi; Rahmat Mirzaei; Mohammad jafar tarokh
Volume 11, Issue 30 , October 2014, , Pages 98-128
Abstract
In this study, first by study different sources, effective factors of successfulimplementation of knowledge management systems have been identified.Then, by means of statistical analysis and SPSS software status ofeach factor in the Tamin Company was evaluated in order to determineis the company ready ...
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In this study, first by study different sources, effective factors of successfulimplementation of knowledge management systems have been identified.Then, by means of statistical analysis and SPSS software status ofeach factor in the Tamin Company was evaluated in order to determineis the company ready to implement this system, or not. The results showthat company is not ready to implement this system so it is necessary forthe company to improve its situation before implementing such system.Among those factors, culture, information and communication technology,have respectively the highest and lowest priorities to make correction.
Mohammad Jafar Tarokh; Rahmat Mirzai; Naghmeh Alvandi
Volume 9, Issue 25 , July 2012, , Pages 51-84
Abstract
Knowledge has widely been acknowledged as one of the mostimportant factors for corporate competitiveness, and we havewitnessed an explosion of IT solutions claiming to provide support forknowledge management. Due to the rapid development of knowledgeand information technology (IT), business environments ...
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Knowledge has widely been acknowledged as one of the mostimportant factors for corporate competitiveness, and we havewitnessed an explosion of IT solutions claiming to provide support forknowledge management. Due to the rapid development of knowledgeand information technology (IT), business environments have becomemuch more complicated. In order to cope with ensuing complications,enterprises ought to incessantly innovate; otherwise, it will be verydifficult for them to survive in the marketplace. Hence, IT can help afirm aiming to gain a competitive advantage. In addition, many studieshave argued that business value comes mainly from intangible assets,such as knowledge. Thus, knowledge workers will be able to replaceclerical workers as the new mainstream of manpower resources, afield in which the development of IT is the major force for change inknowledge management system (KMS). Therefore, based on thedefinition of the six gaps in KMS, this study explores the role andeffect of IT in the implementation of KMS in the IK company. EachGap is discussed and the results of an empirical assessment employedto evaluate them are then reported in order to identify each gap'ssituation in a company and which one has to be improved first.moreover, relationships between KMS and IT are analyzed anddemonstrated by means of the literature reviews, expert interviews andquestionnaire analyses. Furthermore, this study discusses how toenhance the effectiveness and efficiency of implementing KMSthrough appropriate IT tools.
M.J. Tarokh; K. Sharifiyan
Volume 6, Issue 17 , September 2007, , Pages 153-181
Abstract
Financial corporation and banks are sort of organization that due to specialty of their work, are very needy to customer management process ; and data mining is one of the best available tools for them to asses definition and behavior forecast of their customers.
Data mining is improving very fast and ...
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Financial corporation and banks are sort of organization that due to specialty of their work, are very needy to customer management process ; and data mining is one of the best available tools for them to asses definition and behavior forecast of their customers.
Data mining is improving very fast and due to presence of vide range of data using computer is essential. Nets & powerful algorithms are used to emplace of manual analysis to derive knowledge & information from data.
In this paper: “Mellat Bank” and its information bank of different division has been evaluated after data extraction from information bank and noise distortion , k means algorithm and fuzzy - k - means algorithm standard test of cluster's compression were used for customer clustering in groups. Determination of optimum number of clusters is done by applying cluster quality assay function. Afterward was used to determine the quality of gained clusters. Then the value of each cluster was determined through FRM model. At the end of project for clusters analysis and define appropriate strategy for each cluster; the pyramid of customer value was used.
