Discovering complex interdependencies in organizational settings

Abstract

PurposeThe paper's aim is twofold: to display how the application of social network analysis techniques to observational data provides researchers with a unique set of data to make sense of the dynamics of organizational settings; to contribute to knowledge on group design, self‐managing teams, and processes of technology diffusion.Design/methodology/approachThe paper focuses on the findings of qualitative research, recently published, that were conducted in a major Italian clothing company producing garments for the top‐end market. Observation, ethnographic interviews and analysis of documents for data collection were employed. Coding procedures and social network analysis techniques were used to analyse data.FindingsThe long presence in the field allowed for the building of two grounded theories. One deals with the process of Computer Aided Design technology diffusion into a small group and it connects a number of variables usually studied separately in the literature. The second accounts for the enactment of spontaneous self‐managing practices in a group formally designed as a manager‐led team.Research limitation/implicationsThe grounded theories are formulated for specific social settings and future research could benefit from replications in different contexts to capture other phenomena leading to different categories to be integrated into the theories or to corroborate them.Originality/valueThe paper derived enacted network data from the direct and prolonged observation of actors as opposed to self‐reported network data. This allowed clarification of the actual content and the quality of the interactions among actors, and to move beyond their quantification, thus enhancing the comprehension of the impact of network relationships upon organizational behaviour.