Abstract

PurposeThis study aims to explore modern learning (ML) scenarios in Dutch higher education towards 2030 and corresponding consequences for facility management (FM) and corporate real estate strategies (CRES) of universities of applied sciences (UAS).Design/methodology/approachThe designing an accommodation strategy model is used to retrieve the match between demand and supply in real estate of Dutch UAS for both present and future. Application of this model resulted in a scenario-planning session with six education experts to determine future demand in education towards 2030. Subsequently, corporate real estate (CRE) managers of nine Dutch UAS were interviewed concerning this subject (one per UAS).FindingsThe results show that CRES of Dutch UAS is only partly aligned to consequences of ML scenarios towards 2030. Most UAS have real estate portfolios that are only partially flexible, so changes in qualitative and quantitative demand due to ML scenarios are not easy to adapt to. The consequences for FM and real estate of the ML scenarios “institute learning” and “mass customization” seem manageable for Dutch UAS, whereas the other ML scenarios, namely, “navigator” and “natural learning”, would create major portfolio problems.Originality/valueThere is an ongoing interest in developments in higher education combined with FM and CRES and its alignment with the corporate vision. Previous studies into modern ways of learning mainly focused on the past and present. However, this study is explorative and explores possible future ML scenarios. These scenarios can contribute to awareness amongst UAS in The Netherlands and abroad regarding their long-term vision. Moreover, these scenarios will help Dutch UAS facility and CRE managers to develop a more future-proof strategic real estate strategy aligned with the corporate vision.

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