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<p>Technology transfer offices (TTOs) play a crucial role in the commercialization of the knowledge created by research institutions. This study aims to empirically analyze the performance of TTOs in science and technology parks (STPs) in Turkiye and the factors that affect their performance. There is no evidence in the literature regarding the performance and factors affecting the performance of this type of TTOs. The performance of TTOs was evaluated using multi-criteria decision-making (MCDM) methods. The ranks of the TTOs are determined using the VIKOR (Vise Kriterijumsa Optimizacija I Kompromisno Resenje) method, and the weights of the performance criteria were determined using a comprehensive weighting approach that includes fuzzy MCDM, Entropy method, and LOPCOW (Logarithmic Percentage Change-Driven Objective Weighting) method. To examine the affecting factors of TTO performance, Beta regression was employed. The size of TTO funds variable was found to have the highest weight among all criteria. The performance of 22 STP TTOs was assessed, and Yıldız TTO was found to be the best one. A sensitivity analysis was conducted to determine the impact of VIKOR threshold values. Additionally, the age of TTO, size of STP, R&amp;D project intensity in STP, and TTO support were found to significantly affect the performance of STP TTOs.&#xa0;</p>

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Evaluating the Performance of Transfer Offices Using MCDM Approaches

  • 期刊论文

  • 发表日期：

    2025年1月10日

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  • Önder Belgin,
  • Başak Apaydin Avşar,
  • Coşkun Çekiciler

摘要

Technology transfer offices (TTOs) play a crucial role in the commercialization of the knowledge created by research institutions. This study aims to empirically analyze the performance of TTOs in science and technology parks (STPs) in Turkiye and the factors that affect their performance. There is no evidence in the literature regarding the performance and factors affecting the performance of this type of TTOs. The performance of TTOs was evaluated using multi-criteria decision-making (MCDM) methods. The ranks of the TTOs are determined using the VIKOR (Vise Kriterijumsa Optimizacija I Kompromisno Resenje) method, and the weights of the performance criteria were determined using a comprehensive weighting approach that includes fuzzy MCDM, Entropy method, and LOPCOW (Logarithmic Percentage Change-Driven Objective Weighting) method. To examine the affecting factors of TTO performance, Beta regression was employed. The size of TTO funds variable was found to have the highest weight among all criteria. The performance of 22 STP TTOs was assessed, and Yıldız TTO was found to be the best one. A sensitivity analysis was conducted to determine the impact of VIKOR threshold values. Additionally, the age of TTO, size of STP, R&D project intensity in STP, and TTO support were found to significantly affect the performance of STP TTOs.