دانلود مقاله ISI انگلیسی شماره 6071
عنوان فارسی مقاله

انتخاب استراتژی های مدیریت دانش با استفاده از فرایند تحلیل شبکه ای

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
6071 2007 7 صفحه PDF سفارش دهید 4110 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Selecting knowledge management strategies by using the analytic network process
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 32, Issue 3, April 2007, Pages 841–847

کلمات کلیدی
مدیریت دانش - استراتژی مدیریت دانش - تصمیم گیری چند معیاره () - فرایند تحلیل شبکه ای ()
پیش نمایش مقاله
پیش نمایش مقاله انتخاب استراتژی های مدیریت دانش با استفاده از فرایند تحلیل شبکه ای

چکیده انگلیسی

For ensuring the successful implementation of knowledge management, here raises a critical issue of how companies can better evaluate and select a favorable knowledge management strategy before that implementation. However, selecting a proper knowledge management strategy is a kind of multiple criteria decision-making (MCDM) problem required to consider a large number of complex factors. Unlike many traditional MCDM methods that are based on the independence assumption, the analytic network process (ANP) is a relative new MCDM method which can deal with all kinds of dependences systematically. Since the ANP has these advantages, in this paper, we develop an effective method based on the ANP to help companies that need to evaluate and select knowledge management strategies. Additionally, an empirical study is presented to illustrate the application of the proposed method.

مقدمه انگلیسی

As knowledge is taking on an important strategic role (Desouza, 2003, Liao, 2003 and Zack, 1999), numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. 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). The effective management starts with a proper strategy (Gopal & Gagnon, 1995). In order to implement the KM successfully, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy before that KM implementation. However, 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. Generally, selecting what kinds of KM strategies to use depends on the different purposes, the limited resources, and even the preferences of companies. When companies need to evaluate and select KM strategies, they usually face to consider a large number of complex factors. Typically, the multiple criteria decision-making (MCDM) problem is a decision-making problem required to evaluate several alternatives involved in a set of evaluation criteria. Hence, selecting a KM strategy is a kind of MCDM problem, it is better to employ MCDM methods for reaching an effective problem-solving. 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 relative new MCDM method was proposed by Saaty (1996). The ANP is the 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, Karsak et al., 2003, Lee and Kim, 2001, Meade and Presley, 2002, Partovi, 2001, Partovi and Corredoira, 2002, Shang et al., 2004 and Yurdakul, 2004). Since the ANP has these advantages, in this paper, we develop an effective method based on the ANP to help companies that need to select favorable KM strategies. 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, some of the prior literature related to the KM strategy is reviewed. In Section 3, the proposed method based on the ANP is developed. In Section 4, an empirical study is illustrated. Finally, according to the findings of this research, conclusions and suggestions are presented.

نتیجه گیری انگلیسی

The effective management largely starts with a proper strategy. Hence, in order to implement the KM successfully, there has 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, 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 objective and logical manner. Thus, the KM strategy selection is a kind of MCDM problem, and requires MCDM methods to solve it appropriately. Unlike traditional MCDM methods are based on the independence assumption, the ANP is a relative new MCDM method which can deal with all kinds of dependences systematically. For the purpose of helping companies to evaluate and select KM strategies successfully, we have proposed an effective method based on the ANP. The results of this empirical study show that the most desired purpose was to promoting innovation, and the “dynamic-style” KM strategy was preferred. Because our proposed method 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 ANP in KM field. Further, using our suggested analytical procedure, it can effectively handle any problem of selection with multi-faceted criteria.

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