Knowledge risks in organizational networks: An exploratory framework

https://doi.org/10.1016/j.jsis.2011.11.001Get rights and content

Abstract

In a networked environment, it is essential for organizations to share knowledge among themselves if they want to achieve the global objectives such as collaborative innovation and increased effectiveness and efficiency of operations. However, sharing knowledge is not risk-free. An organization might lose its competitive edge if it shares too much or certain key knowledge. In addition, an organization might suffer if its intellectual property is improperly handled by its business partners. While the literature has touted the value of knowledge sharing within networks, there is a conspicuous absence of studies examining the risks of sharing knowledge. To address this gap, we develop an exploratory framework that categorizes knowledge-sharing risks across multiple dimensions. Such a framework is a structured approach to knowledge risk management and complements the practice-based approach to knowledge risk management that is presented in (Marabelli and Newell, 2012). Our framework outlines the various kinds of knowledge risks that organizations are facing. We use a combination of knowledge-based and transaction cost theories to show how knowledge risk impacts knowledge transfer among entities in the network, the whole network, and the risk mitigation options.

Highlights

► Reviews issues connected with risks due to knowledge sharing in networks. ► Develops an exploratory framework to categorize knowledge-sharing risks. ► Investigates how the risk of knowledge sharing affects both the decision to start the sharing and its evolution. ► Shows the implications for knowledge sharing and risk management.

Section snippets

Knowledge sharing is not risk-free

Today’s competitive environment calls for organizations to focus on their core capabilities (Gupta et al., 2009). To this end, most organizations participate in networks to satisfy their ancillary needs. Some organizations (e.g., Amazon, Dell) also rely on their networks for their core needs. For example, Amazon relies on the logistical capabilities of its business partners (e.g., UPS, FedEx) to attain its core business objectives.

As organizations become more dependent on these networks, it is

Networks

The term ‘network’ is often used casually (Cova et al., 2010). Various kinds of networks are postulated (Cova et al., 2010), such as alliance network (Baum et al., 2000); alliance partners (Becerra et al., 2008); business net (Möller and Svahn, 2006); cluster (Liao, 2010); collaborative or cooperative arrangement (Provan et al., 2007); co-opetition (Li et al., 2011); external knowledge sourcing (Carayannopoulos and Auster, 2010); innovation outsourcing (Baloh et al., 2008); inter-organizational

A framework for classifying knowledge risks

Different types of knowledge risk may have similar probability distributions of risk; however, the perceived risks and transaction costs connected with different approaches towards management of that risk may be considerably different. Thus, the impact on knowledge transfer is different for different types of risk. In light of this, the proposed framework of risks (Table 1) classifies them according to five dimensions: the nature of collaboration; the nature of the network; proximity; the type

Implications for knowledge sharing and risk management

In addition to the importance of identifying and classifying risks and proper mitigation activities, the main issue is how the organization manages these risks in the long run and how the structure of its cooperation evolves over time. Obviously, firms engage in knowledge sharing because they need certain knowledge that is not available in their own organization. The main alternative to sharing knowledge within a network would be to acquire this knowledge via the market by, for example, hiring

Conclusion

This paper has reviewed issues connected with risks due to knowledge sharing in networks. Its contribution is in the classification of such risks and the development of a common language for knowledge risk management. It investigated how the type of knowledge risk affects the perceived risk of knowledge sharing and the transaction costs of sharing/risk mitigations; this influences both the decision to begin knowledge sharing and its evolution. Nevertheless, while the framework can help in

Acknowledgments

We would like to thank the editor-in-chief Bob Galliers and both reviewers, and authors, of the complementary paper, Marco Marabelli and Sue Newell, for their thoughtful comments and ideas that considerably improved the paper. All errors and omissions remain solely our responsibility.

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