More ways to Rome: The agglomeration and firm productivity relationship through a configurational lens

A recent stream of studies demonstrates that agglomeration heterogeneously affects firms. There are many heterogeneous and interacting conditions in the firm-agglomeration relation, ranging from variations in size, age, degree of innovativeness, automation, resources used, networks exploited, and managerial styles applied in firms, to sectoral and occupational composition, and regional contexts of agglomeration (either specialization, diversity, or a mixture of these). To deal with this plethora of conditions this chapter suggests a reorientation for future agglomeration studies by employing configurational theory and analysis preceding or alongside more traditional regression techniques. In this chapter, we employ a configurational toolset (fsQCA) that explores the potentials of heterogeneous firm- and agglomeration-level conditions related to firm productivity in direct comparison to a previously employed econometrical analysis. This comparison shows that a well-defined configurational analysis is able to accurately select the conditions that matter significantly in the econometrical analysis. It is argued that when research aims to explore relevant dimensions in the firm-agglomeration relation (‘what relates significantly to productivity?’), the advantages of QCA are found in its sensitivity to detect interacting conditions and dimensions even when they are empirically rare. QCA does not (yet) directly contribute to identifying causal effects compared to some econometric methodological applications (‘what causes productivity?’), but we show that the exploratory function of QCA is ideal for mapping complex prior knowledge, suggesting which (combinations of) ways lead to Rome.