Andrea M. Herrmann

When dichotomisation becomes a problem for the analysis of middle-sized datasets

This article aims at illustrating the circumstances in which Qualitative Comparative Analysis (QCA) and its ramifications, fs/QCA and MVQCA, become particularly useful tools of analysis. To this end, we discuss the most pertinent problem which researchers encounter when using QCA: the problem of contradicting observations. In QCA analysis, contradictions arise from the sheer number of cases and the problem of dichotomisation. In order to handle contradictions, the method for analysing middle‐sized‐N situations should therefore be chosen according to two parameters: the size of a dataset, and the need to preserve raw‐data information. While QCA is an apt tool for analysing comparatively small middle‐sized datasets with a correspondingly reduced necessity to preserve cluster information, the opposite holds true for fs/QCA. MVQCA strikes a balance between these two methods as it is most suitable for analysing genuinely middle‐sized case sets for which some cluster information needs to be preserved.

Beyond Regional Clusters: On the Importance of Geographical Proximity for R&D Collaborations in a Global Economy—the Case of the Flemish Biotech Sector

When internal knowledge bases are insufficient for developing innovations, companies tend to collaborate with external R&D partners. According to a long-standing literature on “clusters”, “industrial districts”, “local production systems” and “regional innovation systems”, geographical proximity between innovation partners is considered a precondition for inter-organizational collaborations: proximity is said to facilitate trust, the transfer of tacit knowledge and the intensity of interactions. This article investigates the importance of geographical proximity for R&D collaborations between biotech firms and their innovation partners. Are geographically close innovation partners likely to collaborate more intensely? Studies of the Flemish biotech industry shed light on this question. Regression analyses combined with qualitative interview data reveal that geographical proximity has become less important for inter-organizational collaborations. Owing to lower communication and transportation costs, innovation partners can easily collaborate even when they are not situated close to each other. This leads us to conclude that globalization transforms inter-organizational collaborations.