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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118388


    Title: Proximity and Cluster Effects: The Case of Emerging Biotechnology Innovation Networks
    Authors: Chen, Shih-Hsin;Chen, Duen-kai
    Date: 2019-10-17
    Issue Date: 2020-03-24 12:10:24 (UTC+8)
    Abstract: Literature maintains that proximity has strong impacts on enhancing interactive
    learning and innovation in the clusters (Howells, 2002). Spatial proximity (distance)
    can be important sources of knowledge spillover, but other dimensions of proximities
    (cognitive, institutional, organizational and social dimensions) are equally important
    (Boschma, 2005; 15. Boschma, R., and K. Frenken. 2010; Omobhude and Chen
    2019). However, what is less clear is how do interactions occur in the networks to
    develop linkage between actors and how do cluster effects enhance the
    collaborations in emerging high-tech sectors? To explore the associations that
    regional cluster brought to enhance the formation of R&D networks in the emerging
    high-tech sector, this paper examines the R&D collaboration network of
    biotechnology industry in Taiwan between 1998 and 2017. Combining more than 50
    interviews and applying social network analysis on a longitudinal dataset gathered
    from financial reports of 180 emerging biotechnology firms who have initiated public
    offering (IPO) in Taiwan, this paper aims to explore the R&D collaboration networks
    between the actors in the innovation system to understand whether cluster effects
    would enhance the R&D collaborations in the high-tech science-based sectors.
    Comparing the networks of the firms in this group, a shift from relative sparseness in
    1998-2007 to connectedness in 2008-2017 can be readily observed. The finding of
    this paper suggest that while the nascent sector stays in a small size, geographical
    proximity is not the most important factor to determinate the networking
    establishments between the actors in the innovation system. In contrast, the
    technological distance, the fit of specialties and the mutual complementary of the
    business is the key factor to drive the formation of collaboration networks and
    alliances in the biotechnology sector- a science-based sector. To further enhance the
    collaboration network in a nascent science-based sector, cluster effects through
    policy intervention attempting to stimulate the collaboration networks between the
    actors may not be the mostly efficient enhancement. Instead, the strength of local
    knowledge base, shorten the technological distance, and enhance the mutual
    complementary between the actors would be most important enhancements to
    strengthen the local collaboration networks and the knowledge transfer in the
    networks. Future technology policy to promote emerging sectors needs to focus on
    building the capabilities of the local sector, taking into account the distinct structural
    features of local innovation context, rather than copying policy models from the
    successful experiences from other sectors or from other countries.
    Appears in Collections:[Department of Innovative Information and Technology] Proceeding

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