Management standards serve as an effective knowledge diffusion channel, considering that they offer comprehensive scientific and practical knowledge for many different stakeholders. This research aims to study the potential of management standards to diffuse knowledge, especially within the scientific community. Therefore, it analyzes the relationship between management standards and the academic literature. It focuses on international management standards, namely ISO 14001 and ISO 9001 and their ‘European counterparts’ EMAS and the EFQM Excellence model. We tested whether scientific publications, which address these international and European management standards, are more likely to lead to follow-up research than comparable scientific publications measured by the impact on average forward citations. Hence, we applied a negative binominal regression model on bibliometric data. Findings show that publications addressing ISO 14001 alone or in combination with other standards lead to higher average forward citations than the comparison group. In conclusion, international management standards foster the academic research progress of the topics addressed by the respective standard. Our research implies the importance of monitoring standards for the scientific community and suggests Standard Setting Organizations to foster actively the research progress.

Young companies need support concerning decisions related to intellectual properties. Entrepreneurs can resort to a menu of strategies, not only patenting. First, we explore the literature on standardisation and patenting and relate it to entrepreneurship to identify the internal and external influencing factors as well as the motives and risks related to decision making. Then, we conduct five case studies to explore these influencing factors, while trying to reconstruct the decision making process. We find five main factors: technology, resources, knowledge protection vs. knowledge diffusion, need for partnerships, and pace of innovation. Companies should use patents when their technology is patentable and knowledge protection is perceived essential. Standardisation is suitable when knowledge diffusion is more important than protection, and companies look for establishing new partnerships. These insights are integrated into a decision tree that provides guidance to young entrepreneurs to make an informed decision regarding intellectual properties.

Finding new industry partners poses a challenge to many public research organizations. This article explores how statistical classification can support partner selection at the example of the Fraunhofer Society in Germany, Europe's largest public organization for applied research. We use internal cooperation data and feature sets based on unstructured data, i.e., text and industry codes, both of which describe business activities of firms. An important advantage of this data is that it is available for most companies in Germany, even small and medium enterprises, which allows for an almost complete screening of the market, in contrast to using other data sources, e.g., patents. In addition, we also include economic variables linked to firms, as turnover, number of employees/managers and firm age. We report the performance of various classification techniques such as logistic regression, support vector machines, and random forests in our dataset for diverse combinations of feature sets. Results show that simple methods with fewer parameters remain competitive in comparison to complex ones. Overall, the performance of most classifiers is high enough to support the decision process of finding new industry partners for public research.

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