دانلود مقاله ISI انگلیسی شماره 21580
عنوان فارسی مقاله

نقشه دانش پویا : استفاده مجدد از دانش ضمنی خبرگان در صنعت کمیسون انرژی اتمی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
21580 2004 5 صفحه PDF سفارش دهید 2250 کلمه
خرید مقاله
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عنوان انگلیسی
Dynamic Knowledge Map : reusing experts' tacit knowledge in the AEC industry
منبع

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

Journal : Automation in Construction, Volume 13, Issue 2, March 2004, Pages 203–207

کلمات کلیدی
اینترنت - نقشه دانش پویا - کمیسون انرژی اتمی -
پیش نمایش مقاله
پیش نمایش مقاله نقشه دانش پویا : استفاده مجدد از دانش ضمنی خبرگان در صنعت کمیسون انرژی اتمی

چکیده انگلیسی

Much knowledge in the Architecture, Engineering and Construction (AEC) industry is experience-based and tacit. Nevertheless, the typical strategy for knowledge management is focused on computer-based approaches for capturing and disseminating explicit knowledge. AEC firms have been successful at collecting and storing explicit information in enterprise databases, but they are poor at knowledge retrieval and exchange. Consequently, AEC professionals find it difficult to reuse core experts' knowledge for highly knowledge-intensive AEC activities. This situation calls for a method for disseminating tacit knowledge from experts' brains to achieve higher quality AEC projects. The primary purpose of this paper is to set a theoretical foundation for clarifying the contribution of experts' tacit knowledge in the AEC industry. The secondary purpose is to describe the concept for prototype software, Dynamic Knowledge Map, that can assist in the reuse of experts' tacit knowledge. Dynamic Knowledge Map is a Web-based knowledge navigator that searches for experts and facilitates communication with those experts by using internet technology. Higher performance levels theoretically can be achieved while accelerating the knowledge transfer processes. Future research will test the suitability of Dynamic Knowledge Map for tacit knowledge utilization in AEC organizations.

مقدمه انگلیسی

There are two kinds of knowledge: tacit and explicit. According to Polanyi's [1] definition, tacit knowledge is highly personal, context-specific, and therefore hard to formalize and communicate. Tacit knowledge is knowledge housed in the human brain, such as expertise, understanding, or professional insight formed as a result of experience. Explicit knowledge, on the other hand, refers to codified knowledge that is transmittable in formal, systematic language and is easily transferred by using Information Technology (IT). Because of the orientation toward unique projects, much knowledge in the Architecture, Engineering and Construction (AEC) industry is experience-based and tacit. The knowledge needs are dynamic, depending on the task to be performed or the problem to be solved. Nevertheless, the typical strategy for knowledge management is to make knowledge explicit and store it as computer software and databases. It is driven by the exponential advances in IT. Hansen et al. [2] and Johannessen et al. [3] pointed out that IT usefulness is limited to the transfer of explicit knowledge only. Chiti Ho, Chief Technology Officer of 3D/International, also said that the use of IT solutions influences the communication of explicit information only. Therefore, the emphasis on IT may compromise effective tacit knowledge; furthermore, experts' tacit knowledge could be wasted and ignored. As a result, there are numerous problems with knowledge-based system resulting from the nonapplicable conversion of tacit knowledge to explicitly documented knowledge. It is often difficult to extend and enhance a knowledge-based system with additional expert knowledge once the system is fielded. The knowledge-based system works well only if the system contains enough input from human experts. The primary reason that most knowledge-based systems are not well integrated into the AEC process is that it is difficult for project managers to assess the applicability of this technology to the AEC processes [4]. Within the context of rapidly changing technologies and processes, an existing knowledge-based system might no longer seem capable of meeting the increasingly complex knowledge demands in the industry. Although the technical capabilities of knowledge-based systems are expanding, they still fall short of applicability to the AEC processes they are designated to support. On the other hand, some AEC companies have tried to implement a “Lesson Learned” system to record personal tacit experiences [5]. However, those systems require extensive efforts to record tacit experiences. AEC firms have been successful at collecting and storing explicit information in enterprise databases, but they are not always good at tacit knowledge retrieval and sharing. Consequently, AEC professionals find it difficult to access core knowledge for highly knowledge-intensive AEC activities. This situation calls for a method for disseminating tacit knowledge from human experts, especially for use by large AEC firms. The primary purpose of this paper is to set a theoretical foundation for clarifying the contributions of experts' tacit knowledge in AEC industry. The secondary purpose is to describe the concept for prototype software, Dynamic Knowledge Map, to reuse experts' tacit knowledge more productively.

نتیجه گیری انگلیسی

The ideas and theories discussed in this paper are an introduction to issues and solutions for reusing experts’ tacit knowledge in the AEC industry. The goal of this work is to present a coherent and practical way to use tacit knowledge in the industry. Although tacit knowledge is important to success, AEC organizations often give little recognition to it. For the two types of knowledge discussed herein, there are two types of knowledge management strategy: explicit knowledge strategy and tacit knowledge strategy. The theoretical findings show that tacit knowledge strategy seems more appropriate for the AEC industry. However, explicit knowledge should not be ignored. Organizational knowledge bases are both explicit and tacit. AEC professionals should emphasize tacit knowledge and use explicit knowledge in a supporting role. Knowledge bases should not reside in computerized repositories but in human brains.

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