Antecedents to free revealing valuable knowledge in intellectual property appropriation regimes: An empirical study.

Martin Finkenzeller

Publikation: KonferenzbeitragKonferenzposter


Knowledge and the way it is shared via various channels among different people can be an important competitive advantage (Bartlett, 2013), but once this valuable knowledge is shared with others the information gets a public good and might therefore get disvalued (von Hippel, 2008). This is especially the case in online communities, in which the flow of information is difficult to control. Today there exist a number of these communities focusing on the development of business ideas, potentially bringing them to the market. The concept behind it is that you get the chance to share your business idea with the online community and collaboratively work on it supported by a number of experts from different fields. That way entrepreneurs can get feedback on their ideas, establish important contacts for further business and gain reputation in the start-up community. Yet these platforms, like many other platforms that rely on the free revealing of valuable knowledge, face one major problem: Users are holding back ideas and knowledge to prevent them from being stolen. In fact there mostly are neither law-based nor norms-based systems that protect intellectual property and could hinder users stealing ideas. Research Question Derived from that problem, I decided to investigate the following research question: Under which conditions are individuals more likely to reveal personally valuable knowledge in appropriation regimes? To underline the relevance of our project some related papers are listed in the following: - Norms-Based Intellectual Property Systems: The Case of French Chefs (Fauchart & von Hippel, 2008) - Profiting from voluntary information spillovers: how users benefit by freely revealing their innovations (Harhoff, Henkel, von Hippel, 2003) - The Seven IP Commandments of a Crowdsourcing Community: How Self-Organized Norms-Based IP Systems Overcome Imitation Problems (Bauer, Franke, Tuertscher, 2014)
PublikationsstatusVeröffentlicht - 2014