Process dynamics of managing interdisciplinary, cross-organizational learning campus in change

Abstract

Purpose – The purpose of this paper is to characterize development processes of eight novel learning environment projects in one university campus in Finland. Design/methodology/approach – This study builds propositions on case study data in an attempt to characterize the distinguished cases. In total, 22 semi-structured interviews were conducted as the primary data collection method. Supporting data includes archives, seminars and workshops. The data were analyzed in ATLAS.ti. Findings – The cases are unique in their processes constituting socio-technical change. They represent two main process types: agile, iterative bottom-up processes and slow, linear, top-down processes. The essence of each project is in balancing in five dimensions of approach, motivation, budget, type of outcome and added value (AMB to AV) process management model: approach scaling from strategic to operational, motivation scaling from space to activity, budget scaling from fixed to seed money, type of outcome scaling from slow and standardized to quick and dirty and added value scaling from research to societal impact. Research limitations/implications – The cases are highly context-dependent and only provide a narrow understanding of a previously little studied area. The main contribution is in highlighting the complexity of the studied phenomenon. Future research could further the subject by, i.e. testing the created model in another context. Practical implications – Transformation from institutionalized learning environments toward campuses facilitating learning flows requires multiple supporting processes. The roles of the campus managers are expanded from measuring, controlling and maintaining the campuses toward identifying, empowering, supporting and enabling user communities to affect their working and learning environments. Originality/value – Managing campuses top-down based on large amounts of data can be supported by bottom-up approaches. This study outlines a systemic framework for supporting both types of processes.