No size fits all - Exploring Entrepreneurship Measurement using Big Data, rare Events and Ecosystems

Abstract

Entrepreneurship is one major factor influencing the world we live in. At that, the relationship between entrepreneurship and this world is an interdependent one and entrepreneurial activity in any given territory is an inherently economic geographical process. As a highly multidisciplinary research field, entrepreneurship has been analysed for decades, yet as the world progresses, the entrepreneurial phenomena evolve as well. Sophisticated research needs outstanding data. Plenty manifestations of entrepreneurship are not or not sufficiently covered by such data. There is a need to explore new methods and approaches for data on entrepreneurship to tackle unsolved issues and address newly developing phenomena. Some entrepreneurial events are so rare it is difficult to get quantitative data on them, making them dominated by qualitative case studies. Moreover, other areas in entrepreneurship are so complex, that reliable comparable data need a broad and coordinated approach. This thesis addresses these issues as such, that it contributes to a more complete empirical data body, and it expands the understanding how bespoke methodology leads to phenomenon specific empirical data and ultimately to place based policies and is thus overall advancing entrepreneurship research.