Collaborative Change: Environmental Jolt, Network (Re)Design and Firm Performance

Motivated by the need to understand which are the underlying forces that trigger network evolution, we develop a multilevel theoretical and empirically testable model to examine the relationship between changes in the external environment and network change. We refer to network change as the dissolution or replacement of an interorganizational tie, adding also the case of the formation of new ties with new or preexisting partners. Previous research has paid scant attention to the organizational consequences of quantum change enveloping entire industries in favor of an emphasis on continuous change. To highlight radical change we introduce the concept of environmental jolt. The September 11 terrorist attacks provide us with a natural experiment to test our hypotheses on the antecedents and the consequences of network change. Since network change can be explained at multiple levels, we incorporate firm-level variables as moderators. The empirical setting is the global airline industry, which can be regarded as a constantly changing network of alliances. The study reveals that firms react to environmental jolts by forming homophilous ties and transitive triads as opposed to the non jolt periods. Moreover, we find that, all else being equal, firms that adopt a brokerage posture will have positive returns. However, we find that in the face of an environmental jolt brokerage relates negatively to firm performance. Furthermore, we find that the negative relationship between brokerage and performance during an environmental jolt is more significant for larger firms. Our findings suggest that jolts are an important predictor of network change, that they significantly affect operational returns and should be thus incorporated in studies of network dynamics.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.