Evolutionary theories of organizational change aim at finding processes that introduce structural variations in organizational variables and the conditions under which they can survive and be reproduced. However, the theory is limited by the lack of knowledge on interactions between organizations and the stability of interaction patterns over time. In this study, we use the network of interorganizational labor flows and tools and concepts from network science to inform the study of organizational evolution at the level of sector dynamics, in particular along the dimensions of connectivity and stability of labor flow patterns. We use a unique Swedish longitudinal register on employment in the Stockholm Region from 1990 to 2003. We find that the network is characterized by positive sector assortativity, and the public sector is relatively more tightly connected than the private one. A stability analysis shows that public organizations survive longer time in the dataset, and movements within publicly-owned organizations are the most stable while movements within the private sector are least stable. A network backbone overlap analysis shows that movements within the public sector are structurally stable over larger periods, while the ones within the private sector change quickly after a few years. We also find that the distributions for degree, interorganizational flows and betweenness centrality are highly skewed and "fat"-tailed; the public sector consistently has fatter tails than the private sector in all distributions. Implications for our understanding of how publicly and privately owned organizations are connected and react to external shocks are discussed.
Keywords: Assortativity; Centrality; Interorganizational labor flows; Labor market dynamics; Network backbone overlap; Network science; Network stability; Sector dynamics.