Abstract
Longitudinal field studies are in-depth studies of change processes. They are case studies studying a phenomenon over time and often involve real-time studies of organizational phenomena, with the researcher being present in the organization. Research questions often concern how organizational change emerge, develop, grow, or terminate over time. Before entering the field, a framework for data gathering is critical. Longitudinal field researchers rely heavily on participant observation. To avoid going native, the researcher regularly withdraws from the field back to the academic environment. Analysing longitudinal field data is a challenging task due to the large amounts of data. Central to data analysis is data reduction. It starts with the writing of a narrative of the process. The narrative is divided into basic units of information, using explicit decision rules. The third step is to code incidents. The incidents are finally sorted and recoded. Generation of theory starts while the researcher is still in the field. The starting point for building theory is the incidents, but the interest is in the mechanisms underlying them. The analysis requires identifying sequences and patterns in the events. The theory developed needs to be constantly compared with existing theory.