Michael Weinhardt & Isabell Stamm: Drawing Samples for the Longitudinal Study of Entrepreneurial Groups from Process-Generated Data: A Proposal Based on the German Register of Companies. [Abstract]
The growing interest in entrepreneurial groups as collective actors of entrepreneurship raises questions of how and with what kind of data this unit of analysis can be studied. While sampling and access to data on individual entrepreneurs (self-employed) or their business ventures (formal firms) rest upon established routines, a methodological discussion about identifying and sampling entrepreneurial groups is still in its infancy. In this article, we look at process-generated data as a potential linchpin to study entrepreneurial groups. More particularly, this article critically reflects upon the opportunities and challenges of the German Commercial Registry (CR) to function as a sampling frame and data source for an examination of entrepreneurial groups. This reflection includes a discussion about the key characteristics of entrepreneurial groups in order to derive minimal criteria that the data needs to provide, an evaluation of the CR following a data source study approach, and finally an assessment of the error proneness of this data and its consequences for the study of entrepreneurial groups. On this basis, we propose a sampling strategy of entrepreneurial groups with CR data. As such, this article contributes to a general methodological discussion of process-generated data, as it extends and practically applies the concept of a data source study. It also contributes to a methodological discussion about entrepreneurial groups as it offers a procedure to deal with varying group boundaries and the intertwinement of group and business activity typical for this social unit of analysis.