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Across the world, many universities are dealing with a pressure on resources, caused by both organisational developments and ageing campuses. Space utilization studies have a strategic role, providing information on how space is being used, thereby informing decisions about the type and scale of facilities that are needed.

This study reports on the space use measurements conducted at TU Delft over the past five years, complemented by their use to make decisions about the university's real estate portfolio.

The education spaces of the university are found to perform well in terms of frequency rates and can be improved in terms of occupancy rates. The information helped to support short- and long-term decision-making. The study places of the university have a satisfactory occupancy in some types of study places, while in others there is room for improvement. More research is needed here to understand the relationship between space norms and space use.

The space utilization studies have supported discussions with the student council and decision makers on which interventions are required and which current facilities meet students' needs best.

Not much space utilisation studies are reported in the academic literature, and those that do have several limitations. This study may serve as a best practice for benchmarking by other universities and as evidence in other research for the planned and actual use of university facilities.

To plan the future university campus, campus executives need decision-making support from theory and practice. Matching the static campus (supply) with the dynamic (demand) - while safeguarding spatial quality and sustainability - requires management information from similar organizations. This study presents an evidence-based briefing approach to support decision-makers of individual universities with management information when making decisions for their future campus.

For the proposed evidence-based briefing approach, the continuous Designing an Accommodation Strategy (DAS) framework is used in a mixed-method research design to evaluate the past to plan for the future. Five campus themes and three campus models (solid, liquid, and gas) are introduced to describe the development and diversification of university campuses and their impact across different university building types. Based on this theoretical framework, first, qualitative interview data are analyzed to understand which standards campus managers expect; second, a quantitative project database is used to demonstrate what is actually realized.

The findings demonstrate that remote working and online education will become more common. Academic workplaces and learning environments are more adaptive to changes than laboratory spaces. The analyses reveal different effective space use strategies to meet the current demand: they include space-efficient mixed-use buildings, and mono-functional generic educational and office spaces. These results show that operationalized evidence-based briefing can help design the future campus.

The study adds knowledge during a critical (post-COVID) period when decision-makers need evidence from others to adapt their campus management strategies to hybrid and sustainable ambitions.

The purpose of this study is to generate knowledge about the use of smart campus tools to improve the effective and efficient use of campuses. Many universities are facing a challenge in attuning their accommodation to organisational demand. How can universities invest their resources as effectively as possible and not in space that will be poorly utilized? The hypothesis of this paper is that by using smart campus tools, this problem can be solved.

To answer the research question, previous survey at 13 Dutch universities was updated and compared with a survey of various universities and other organizations. The survey consisted of interviews with structured and semi-structured questions, which resulted in a unified output for 27 cases.

Based on the output of the cases, the development of smart campus tools at Dutch universities was compared to that of international universities and other organizations. Furthermore, the data collection led to insights regarding the reasons for initiating smart campus tools, user and management information, costs and benefits and foreseen developments.

Although the use of smart tools in practice has gained significant momentum in the past few years, research on the subject is still very technology-oriented and not well-connected to facility management and real estate management. This paper provides an overview of the ways in which universities and organizations are currently supporting their users, improving the use of their buildings and reducing their energy footprint through the use of smart tools.

Corporate real estate management (CREM) is complex due to an increasing number of real estate (RE) added values and the tensions between them. RE managers are faced with trade-offs: to choose a higher performance for one added value at the cost of another. CREM research mainly deals with trade-offs in a hypothetical sense, without looking at the characteristics of the RE portfolio nor the specific context in which trade-offs are made. The purpose of this paper is to further develop the concept of real estate value (REV) optimisation with regard to tensions between decreasing CO₂ emissions and supporting user activities.

Mixed method study. REV optimisation between user activities and energy efficiency for police stations in the Netherlands built between 2000 and 2020 is analysed. This is complemented by interviews with an RE manager and senior user of police stations and analysis of policy documents.

The characteristics of the police station portfolio indicate no correlation between user activities and energy efficiency for the case studied. This is complemented by interviews, from which it becomes clear that there was in fact little tension between supporting user activities and energy efficiency. The performances of these two different added values were optimised separately.

This study combines different scales (building and portfolio level) with different types of data: portfolio analysis, document analysis and interviews. This creates a comprehensive image of whether and how the Netherlands police optimised the two RE values.