Managing Knowledge Distribution to Prevent Product Imitation and Counterfeiting

Managing Knowledge Distribution to Prevent Product Imitation and Counterfeiting

Gergana Vladova (University of Potsdam, Germany), Julian Bahrs (University of Potsdam, Germany) and Norbert Gronau (University of Potsdam, Germany)
Copyright: © 2012 |Pages: 17
DOI: 10.4018/jiit.2012040102
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Product piracy poses an existential threat to many companies. Juristic property rights, which are currently dominantly discussed, do not suffice to combat this threat. The rise in cases of piracy and increasing professionalism of the counterfeiter, give ground for effective prevention methods. Based on gaps of existing approaches, the authors evaluate how knowledge modeling could design preventive measures. They develop a new approach which makes information and knowledge leaks transparent, analyzable, and controllable. The approach is based on interactions and transfers of information and knowledge between departments of a company with internal and external business partners. For this purpose, a modeling process for knowledge-intensive business interactions is used and modified. Choosing dynamic assessment questions establishes the level of risk of information and knowledge on piracy and prioritizes company specific measures. In addition, the procedure reappraises companies’ existing modes of prevention. Based on this analysis, the method helps to develop and rank measures to hinder the theft of information by pirates. The approach fills the gap in known concepts of protection, which are used only after a case of piracy has taken place. The approach also adds a new perspective in knowledge management.
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1. Challenges For Enterprise Knowledge Management

Currently, enterprise knowledge management faces two basic functional challenges: the conception and realization of processes, systems and actors with the aim of a better use of an enterprise’s intellectual resources.

Beginning with the conception and realization of knowledge management solutions, an enterprise has to take into account all existing official and unofficial knowledge and information transfer structures and practices. For responsible knowledge manager it is thus important to know in detail the existing structure, with all its positive and negative traits. This is already essential in the analysis phase, but is of even more importance during the concept implementation, when new or transformed concepts meet existing structures in practice.

It is important to involve all relevant actors in decisions regarding the implementation of appropriate organizational and technical measures. Knowledge management practice shows that concepts which have been implemented top-down often remain unaccepted by the employees. In contrast, concepts which take into account existing structures and processes usually enjoy acceptance and confidence after their implementation.

Another important aspect of the development of successful knowledge management approach is the difference between knowledge and information. Information is not dependent on a person and can simply be externalized, e.g., through recording on medium or through written documents. In contrast, knowledge is always dependent on a person, it is personal, context specific, and as a result of this it is difficult to communicate. It is also difficult to externalize, and its externalization is possible only with content loss (Davenport & Prusak, 1998). The transfer of knowledge and information must be planned and organized in different ways and according to their own specific rules.

Process-oriented knowledge management offers different instruments which can be used during the analysis and concept generation. In particular, the weaknesses (and strengths) of existing knowledge intensive business processes can be analyzed in order to develop better strategies and guidelines for the transfer and use of knowledge and information.

Researchers and practitioners in the field of enterprise knowledge management currently focus on strategies and instruments to make knowledge and information available to all members of an organization. However, this strategy fails to consider some important aspects, e.g., the importance of knowledge as a competitive advantage for enterprises. An enterprise thus also needs a set of rules to be aware of information and knowledge flows and means to their control.

In general, an enterprise’s goal with regard to the free flow of knowledge and information are to ensure smooth processes and routines, to enable efficient cross-departmental cooperation and to establish a common understanding of the enterprise culture and organizational structure. Enterprises are, however, still left with the problem of the transfer of too much information, which could essentially complicate and delay the process flow (information overload). Furthermore, knowledge drains could put the enterprise in danger of losing its competitive advantage with regard to information or knowledge. Thus, the enterprise should recognize the difference between deliberate or unintentional knowledge transfers and act accordingly. Furthermore, the appropriate use of existing unconscious knowledge and information flows also belongs to the field of knowledge management.

For all the reasons mentioned above, this article will present a method for the concept of knowledge management strategies and measures, which refers explicitly to the risks of knowledge and information transfer during the analysis and concept processes. The challenge is to identify all existing conscious or unconscious knowledge flows, in order to find out whether they are complete and precise, which information and knowledge transfers are still missing, and which are disturbing the normal flow of the process. The main goal is to proactively control information and knowledge flow. The method is based on established approaches within business process oriented knowledge management and adds new perspectives to these approaches. We use business process management practices in order to model and analyze knowledge intensive processes. To be more specific, we use the Knowledge Modeling and Description Language (KMDL) (Gronau, 2012) and include new aspects to this modeling and analysis method.

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