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<p>Technology transfer plays a critical role in the commercialization of knowledge generated by research organizations, with Technology Transfer Offices (TTOs) serving as key institutional intermediaries in this process. This study evaluates the efficiency, productivity change and influencing factors of efficiency of publicly supported TTOs by The Scientific and Technological Research Council of Türkiye (TÜBİTAK) in Türkiye using a relational multi-period Data Envelopment Analysis (DEA), the Malmquist Productivity Index (MPI) and the GM(1,<i>N</i>) model of Grey Theory. The study covers the period between 2020 and 2022. The inputs are the number of staff and the number of research requests from industry; the outputs are the number of spin-offs, the number of start-ups, the number of applied and granted patents. The results reveal that TTOs in Türkiye have an increasing efficiency and productivity growth from 2020 to 2022. Furthermore, the size of TTOs, the number of contracted university-industry collaboration projects, the age of TTOs and the number of matching activities between researchers and firms organized by TTOs have a positive effect on the efficiency of TTOs. To the best of our knowledge, this study is the first to analyze the performance and influencing factors of efficiency of the publicly supported TTOs using DEA, MPI and GM(1,<i>N</i>) model.</p>

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Performance of publicly supported technology transfer offices in Türkiye: a DEA–MPI–GM(1, N) approach

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  • 出版模式：

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  • 发表日期：

    2026年4月3日

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摘要

Technology transfer plays a critical role in the commercialization of knowledge generated by research organizations, with Technology Transfer Offices (TTOs) serving as key institutional intermediaries in this process. This study evaluates the efficiency, productivity change and influencing factors of efficiency of publicly supported TTOs by The Scientific and Technological Research Council of Türkiye (TÜBİTAK) in Türkiye using a relational multi-period Data Envelopment Analysis (DEA), the Malmquist Productivity Index (MPI) and the GM(1,N) model of Grey Theory. The study covers the period between 2020 and 2022. The inputs are the number of staff and the number of research requests from industry; the outputs are the number of spin-offs, the number of start-ups, the number of applied and granted patents. The results reveal that TTOs in Türkiye have an increasing efficiency and productivity growth from 2020 to 2022. Furthermore, the size of TTOs, the number of contracted university-industry collaboration projects, the age of TTOs and the number of matching activities between researchers and firms organized by TTOs have a positive effect on the efficiency of TTOs. To the best of our knowledge, this study is the first to analyze the performance and influencing factors of efficiency of the publicly supported TTOs using DEA, MPI and GM(1,N) model.