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A dynamic knowledge management framework for the high value manufacturing industry

A dynamic knowledge management framework for the high value manufacturing industry

Piorkowski, Barry Andrew, Gao, James Xiaoyu, Evans, Richard David and Martin, Nick (2012) A dynamic knowledge management framework for the high value manufacturing industry. International Journal of Production Research, 51 (7). pp. 2176-2185. ISSN 0020-7543 (Print), 1366-588X (Online) (doi:10.1080/00207543.2012.709650)

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Abstract

Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place.

Item Type: Article
Additional Information: [1] Official Journal of the International Foundation for Production Research (IFPR). [2] Special Issue: Knowledge management and supporting tools for collaborative networks.
Uncontrolled Keywords: knowledge management, manufacturing information systems, product planning, life cycle, management knowledge, profit, product, KM, manufacturing
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Pre-2014 Departments: School of Engineering
School of Engineering > Department of Engineering Systems
Related URLs:
Last Modified: 14 Oct 2016 09:21
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/8570

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