for personal computing that directly competes with Microsoft. It was initially developed by a student called Linus Torvalds and later became an open source software. The code is publicly available and anyone can contribute or enhance it. The success of Linux is the constant and continuous updating which is done at a much lower cost than closed source software. Wikipedia gathers thousands of volunteers that constantly write and update content. Although it does not have a hierarchy nor a central authority, the entries are mostly accurate and complete. Volunteers share a strong feeling of community and willingness to contribute towards knowledge without being paid for it. Faced with these creations, large companies such as IBM and Intel have learnt to use the principles of open innovation to enhance their research learning curve. They increased or established collaborations with universities, agencies and small companies to accelerate their processes and launch new services faster. Collaborative innovation network factors Asheim and Isaksen (2002) conclude that innovative network contribute to the achievement of optimal allocation of resources, and promoting knowledge transfer performance. However, there are four factors of collaborative innovation network that differently affect the performance of CoINs. Those factors are: 1. network size: network size is the number of partners such as enterprises, universities, research institutions, intermediaries, and government departments in an innovative network. Previous work reveals that network size has a positive effect on knowledge transfer as it provide the actor (e.g. firm) with two major substantive benefits: one is the exposure to a larger amount of external information, knowledge, and ideas and the other is resource sharing between the actor and its contacts such as knowledge sharing, reduction of transaction costs, complementarities, and scale. 2. network heterogeneity: network heterogeneity refers to differences in the knowledge, technology, ability, and size of members in the network. Firms in a more heterogeneous network have a higher probability to acquire external knowledge resources. When network heterogeneity is higher, getting complementary resources and accelerating the speed of knowledge transfer are easier. 3. network tie-strength: Tie-Strength refers to the nature of a relational contact and includes the degree of intimacy, duration, and frequency; the breadth of topic usually refers to time length, tie depth, emotional intensity, intimacy frequency, and interactive connection. A collaborative innovative network with a high level of tie-strength can provide firms with effective information and knowledge, reduce risk and uncertainty in the innovation process,