An Investigation on the Efficiency of Research Collaborations: Data Envelopment Analysis and Stochastic Frontier Analysis on Bio-technology R&D Projects
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Collaborative research and development (R&D) has been encouraged based on the belief that knowledge spill-over is mutually beneficial for partners. Although the benefits are supported by science and technology policy research, the risk of R&D collaboration has not been extensively discussed. Two independent studies suggest that there are risks associated with the overuse of collaborative research frameworks. Two sets of R&D collaboration data were analyzed: between the national bio-technology research program and 1) Data Envelop Analysis (DEA), and 2) between Stochastic Frontier Analysis (SFA). In the case of SFA, output measures were integrated into a single output, with weights extracted from research programme managers’ responses to the questionnaire. While the DEA result demonstrated the inefficiency of collaborative research, SFA did not. Unlike previous research highlighting risks associated with disclosing proprietary R&D and potential conflict of interest, our study indicates that the transaction’s social cost affects collaborative research efficiency. Therefore, governments promoting R&D collaborations should be carefully managed, and policy makers must reconsider the strict conditions governing compulsory collaborative R&D programs.
Abstract
Collaborative research and development (R&D) has been encouraged based on the belief that knowledge spill-over is mutually beneficial for partners. Although the benefits are supported by science and technology policy research, the risk of R&D collaboration has not been extensively discussed. Two independent studies suggest that there are risks associated with the overuse of collaborative research frameworks. Two sets of R&D collaboration data were analyzed: between the national bio-technology research program and 1) Data Envelop Analysis (DEA), and 2) between Stochastic Frontier Analysis (SFA). In the case of SFA, output measures were integrated into a single output, with weights extracted from research programme managers’ responses to the questionnaire. While the DEA result demonstrated the inefficiency of collaborative research, SFA did not. Unlike previous research highlighting risks associated with disclosing proprietary R&D and potential conflict of interest, our study indicates that the transaction’s social cost affects collaborative research efficiency. Therefore, governments promoting R&D collaborations should be carefully managed, and policy makers must reconsider the strict conditions governing compulsory collaborative R&D programs.
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