انتخاب استراتژی های مدیریت دانش با استفاده از رویکرد ترکیبی ANP و DEMATEL
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|6085||2008||8 صفحه PDF||سفارش دهید||4190 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 35, Issue 3, October 2008, Pages 828–835
Numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. The KM strategy selection is a kind of multiple criteria decision-making (MCDM) problem, which requires considering a large number of complex factors as multiple evaluation criteria. A robust MCDM method should consider the interactions among criteria. The analytic network process (ANP) is a relatively new MCDM method which can deal with all kinds of interactions systematically. Moreover, the Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a visual structural model, but also can be used as a way to handle the inner dependences within a set of criteria. Hence, this paper proposes an effective solution based on a combined ANP and DEMATEL approach to help companies that need to evaluate and select KM strategies. Additionally, an empirical study is presented to illustrate the application of the proposed method.
In the knowledge economy, a key source of sustainable competitive advantage relies on the way to create, share, and utilize knowledge (Desouza, 2003). For reacting to an increasingly rival business environment, many companies emphasize the importance of knowledge management (KM), and base the KM strategy on their unique resources and capabilities. According to Kamara, Anumba, and Carrillo (2002), KM is the organizational optimization of knowledge to achieve enhanced performance through the use of various methods and techniques. Also, KM is a systemic way to manage knowledge in the organizationally specified process of acquiring, organizing and communicating knowledge (Benbya, Passiante, & Belbaly, 2004). Today, KM and related strategy concepts are promoted as important components for organizations to survive (Martensson, 2000). More importantly, the effective KM largely begins with a proper KM strategy. Hence, in order to implement the KM successfully, there is a critical issue of how companies can better evaluate and select a favorable KM strategy. However, the KM strategy selection usually involves subjective and qualitative judgment. In particular, choosing KM strategies is a strategic issue (Bierly & Chakrabarti, 1996), which is restricted by resource needs, realistic support, time requirements, and conformity with expected outcomes or business purposes. In this sense, the treatment of KM strategy selection is required to handle several complex factors in a better sensible and logical manner. Thus, the KM strategy selection is a kind of mu1tiple criteria decision-making (MCDM) problem, and requires MCDM methods to solve it appropriately. Many traditional MCDM methods are based on the additive concept along with the independence assumption, but each individual criterion is not always completely independent (Leung et al., 2003 and Shee et al., 2003). For solving the interactions among elements, the analytic network process (ANP) as a relatively new MCDM method was proposed by Saaty (1996). The ANP is a mathematical theory that can deal with all kinds of dependence systematically (Saaty, 2004). The ANP has been successfully applied in many fields (Agarwal and Shankar, 2002, Chung et al., 2005, Coulter and Sarkis, 2005, Kahraman et al., 2006, Karsak et al., 2003, Lee and Kim, 2001, Meade and Presley, 2002, Niemira and Saaty, 2004, Partovi, 2001, Partovi and Corredoira, 2002, Partovi, 2006, Shang et al., 2004, Tesfamariam and Lindberg, 2005 and Yurdakul, 2004). However, the treatments of inner dependences in those ANP works were not complete and perfect. Indeed, the Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a visual structural model (Gabus and Fontela, 1972, Gabus and Fontela, 1973, Fontela and Gabus, 1976 and Hori and Shimizu, 1999), but also can be used as a wise way to handle the inner dependences within a set of criteria. As the ANP and the DEMATEL have these advantages, this paper proposes an effective solution based on a combined ANP and DEMATEL approach to help companies that need to select a favorable KM strategy. Also, an empirical study is presented to illustrate the application of the proposed method. The rest of this paper is organized as follows. In Section 2, an evaluation framework is proposed. In Section 3, evaluation methods are presented. In Section 4, an empirical study is illustrated. Finally, according to the findings of this research, conclusions and suggestions are depicted.
نتیجه گیری انگلیسی
As knowledge is taking on an important strategic role, numerous companies are expecting their KM to be performed effectively in order to leverage and transform the knowledge into competitive advantages. More importantly, the successful KM starts with a proper KM strategy that is produced through a robust evaluation method. However, the KM strategy selection is a kind of MCDM problem, which requires considering a large number of complex factors as multiple evaluation criteria. Although numerous creditable works are devoted to the study of how to build a KM strategy and to execute the KM successfully, few of those have provided methods which can systematically evaluate and model complex factors of the KM strategy. Dealing with the MCDM problem of this KM strategy selection, it is better to employ MCDM methods for reaching an effective problem-solving. The ANP is a relatively new MCDM method which can deal with all kinds of interactions systematically, unlike traditional MCDM methods which are based on the independence assumption. Moreover, the DEMATEL not only can be used as a way to handle the inner dependences within a set of criteria, but also can produce more valuable information for making decisions. Hence, this paper proposes a solution based on a combined ANP and DEMATEL approach to help companies that need to evaluate and select KM strategies. The results of this study show that the most desired purpose was “Activating information”, and “Personalization strategy” was preferred. Because the proposed solution can handle the effects of dependences, it is relatively useful and makes the evaluation result to be more reasonable. Additionally, this study has contributed to extend practical applications of both ANP and DEMATEL in KM field. Furthermore, using the suggested analytical procedure, it can effectively handle any problem of selection with multi-faceted factors. However, there are some limitations, such as the assessment scales of the ANP and the DEMATEL are not unified. Therefore, in order to promote and deepen continuing research in future, it is worthwhile to investigate more cases and exemplary companies in order to uncover invaluable new study issues. Additionally, the assessment scale is required to improve its user-friendliness.