Routine action networks: An architectural study of spatial layouts and performativity in outpatient clinics.

SOCIAL networks; SOCIAL network analysis; OPEN spaces; INTERPERSONAL relations; ECOLOGICAL niche

Social network analysis offers powerful ways to investigate personal relationships, however, to date little work has explored the more routinized, impersonal work processes present in bureaucratic organizations. Asking whether network analysis has insights to offer into routine work, this paper investigates a data set of direct observations of diagnostic care processes in ten outpatient clinics of two different hospitals. Instead of networks of agents, this study constructs so called action networks, tying together sequences of tasks into networks structures. Following the strong social networks tradition of considering contexts, this paper examines the architectural layout of a setting as key variable. Drawing in particular on ecological approaches to the study of networks by focusing on variability, it is hypothesized that the spatial configuration of clinics is associated with performativity, i.e., a more varied set of sequences to emerge within more open-plan layouts. Results indicate that this is the case, showing how different sets of routines emerge in different types of layout depending on their spatial openness. Variability in routinization is also found between doctors, nurses and clerks, highlighting ecological niches. Network density as well as edge-weighted centralization turned out to be useful metrics for performativity. The work presented contributes to the study of bureaucratic organizations, making a case that social network methods can be fruitfully applied to impersonal, routinized and rule-driven relations. • Action networks tie sequences of routine actions into network structures. • Action networks allow studying impersonal relations in bureaucratic organizations. • Physical space of outpatient clinics acts as network context. • Open and highly visible layouts are associated with more variation in routines. • Network density and edge-weighted centralization can capture routine variability. [ABSTRACT FROM AUTHOR]

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