近年来，我国科研产业在研发数量上快速发展，实现了对欧美发达国家的快速赶超，但成果转化能力仍然远远落后世界先进水平。其中根据国家知识产权局发布的《高校专利转化现状调查研究》，高校专利申请总数占全国的11.9%，但真正实现产业化的科技成果却只有5%左右，转化实践表现不佳。因此提升高校的成果转化能力，是我国创新科技产业发展绕不开的核心问题之一。本文通过模糊集定性比较分析（fsQCA）方法，从集合关系的角度结合传统定性研究和定量研究的优势，解释高校的科研成果转化能力的影响因素组合、不同影响因素组合间的复杂关系、构成组合的多个前因条件变量的重要程度等问题，找到促进高校成果转化能力提升的最优解。根据现有研究文献，本文选择了国家科研支持力度、社会科研基础、高校自身研究规模、高校自身研究能力和国际交流参与程度这5个前因变量，并将高校成果转化得分作为结果变量进行模糊集定性对比分析。在完成数据的收集、校准、充分性和必要性分析、稳健性检验等工作后，本文基于实证结果给出了影响高校科技成果转化能力的实证结论。根据fsQCA分析，国家科研支持力度和高校自身研究规模组成了高校较高的成果转化能力的覆盖度最高的条件组合，社会科学素养基础和高校科研能力同样在一些组态中起到核心条件作用，国际交流参与程度指标则通常为边缘条件，影响相对有限。对此，本文得出的启示是在我国社会科学素养基础尚不完善、国际交流环境不够充分且短期内难以改变时可以适当提高国家科研支持力度和高校科研规模发展的优先级，更大可能地提高高校成果转化能力。本文的创新之处在于通过组态分析的视角，采用fsQCA这一有别于传统定性和定量研究的新方法对高校成果转化能力进行分析，揭示了影响高校成果转化能力的多种条件组合，并结合我国目前国情最终得出了有实际意义的参考建议。
China has achieved rapid growth in the area of R&D and catches up with the developed countries in Europe and America. However, our conversion ability of scientific and technological achievements is still far behind the world-advanced level. According to the “Research on the Patent Transformation in Universities” published by CNIPA, the number of patent applications in universities accounted for 11.9% of Chinese total applications, while the industrialization rate was less than 5%. Therefore, it is vital important to improve universities’ transformation ability of scientific and technological achievements in China.This paper utilizes the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method to combine the advantages of traditional qualitative and quantitative research from the perspective of set relations, exploring the topics such as the combination of influencing factors, the complex relationship between different influencing factor combinations, and the different importance of multiple antecedent conditional variables and etc., to find the optimal solution to promote the research result conversion in universities.Inspired by existing literature, this paper selects five antecedent variables, i.e., national research support, societal foundation of scientific research, university’s own research scale, university’s research capability and international exchange participation, and uses the university research achievement conversion score as the result variable to perform fsQCA. After data collection, calibration, sufficiency and necessity analysis, and robustness testing, this paper reaches empirical conclusions on the conversion ability of research achievements in universities.The fsQCA suggests that the combination of national scientific research support and the university’s own research scale constitute the condition with the highest coverage of higher achievement conversion capabilities of universities. The societal foundation of scientific research and research capabilities of universities also serve as core conditions in certain configurations. However, international exchange participation is only a peripheral condition, effecting limited impacts. Based on these findings, this paper suggests that given that societal foundation of scientific research is not well-rounded; the international exchange environment is not sufficient, and they both are difficult to change in the short term, it is possible to appropriately raise the priority of national scientific research support university’s scientific research scale to improve the conversion ability of universities.The innovation of this paper mainly lies in the analysis of universities’ research achievements conversion ability through the perspective of configuration analysis, using fsQCA, a new method that is different from traditional qualitative and quantitative research, to reveal the combination of conditions that affect the ability of university research achievements conversion. Combining the findings with the current status in China, this paper offers practical suggestions on the conversion of university research achievements.Key words: Universities’ Ability of Converting Research Achievements; fsQCA; National and Universities’ Investments; Social Environment
