Knowledge sharing in research communities has been considered indispensable to progress in science. The aim of this paper is to analyze the mechanisms restricting knowledge sharing in science. It considers three categories of academia–industry knowledge transfer and a range of individual and contextual variables as possible predictors of knowledge-sharing restrictions.,A unique empirical data sample was collected based on a survey among 212 life science researchers affiliated with universities and other non-profit research institutions. A rich descriptive analysis was followed by binominal regression analysis, including relevant checks for the robustness of the results.,Researchers in academia who actively collaborate with industry are more likely to omit relevant content from publications in co-authorship with other academic researchers; delay their co-authored publications, exclude relevant content during public presentations; and deny requests for access to their unpublished and published knowledge.,This study informs policymakers that different types of knowledge-sharing restrictions are predicted by different individual and contextual factors, which suggests that policies concerning academia–industry knowledge and technology transfer should be tailored to contextual specificities.,This study contributes new predictors of knowledge-sharing restrictions to the literature on academia–industry interactions, including outcome expectations, trust and sharing climate. This study augments the knowledge management literature by separately considering the roles of various academic knowledge-transfer activities in instigating different types of knowledge-sharing restrictions in scientific research.

中文翻译：

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生命科学中的知识共享限制：学术界-行业知识转移中的个人和因地制宜的因素

研究社区中的知识共享被认为是科学进步必不可少的。本文的目的是分析限制科学知识共享的机制。它考虑了学术界的三类：行业知识转移以及一系列个体和情境变量，这些知识可能是知识共享限制的预测因素。基于对大学附属的212名生命科学研究者和其他非生命科学研究者的一项调查，收集了一个独特的经验数据样本。营利性研究机构。在二项式回归分析之后进行了丰富的描述性分析，包括对结果稳健性的相关检查。学术界与行业积极合作的研究人员更有可能忽略与其他学术研究人员合着的出版物中的相关内容；延迟其共同出版的出版物，在公开演讲中排除相关内容；这项研究告知政策制定者，不同类型的知识共享限制是由不同的个人和背景因素预测的，这表明有关学术界，行业知识和技术转让的政策应适合于上下文的特殊性。本研究为有关学术界与产业界互动的文献提供了知识共享限制的新预测因子，其中包括成果期望，信任和共同氛围。