Business Models for Smart Data-Driven Real Estate Management in Higher Education

Paul Grefen (), Rein van den Bosch (), Frank Bosma (), Toine van Vliet () and Robert Vogels ()
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Paul Grefen: TU/e - Eindhoven University of Technology [Eindhoven]
Rein van den Bosch: TU/e - Eindhoven University of Technology [Eindhoven]
Frank Bosma: TU/e - Eindhoven University of Technology [Eindhoven]
Toine van Vliet: TU/e - Eindhoven University of Technology [Eindhoven]
Robert Vogels: TU/e - Eindhoven University of Technology [Eindhoven]

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Abstract: This report presents three business models for smart, data-driven real estate management at an institution for higher education, focusing on lecture halls as a main type of real estate. In the institution, like in many other similar institutions, lecture halls are a scarce resource the use of which needs to be optimized, both for economic and sustainability reasons. To support this optimization, an effort is undertaken in the context of a larger Smart Campus initiative at the institution to support lecture hall management with data-driven decision support. This decision support is based on fusing semi-static enterprise data, more specifically reservation data regarding the use of lecture halls, with dynamic, real-time data from sensors that describes the actual usage of lecture halls. Three business models describe the value of this decision support from the perspective of the stakeholder types that have a customer role: the education management department, more specifically its lecture planning group, the teachers that uses a lecture hall and may need a real-time relocation in case of an exception, and the real estate management department wants to improve its strategic real estate planning. The business models are specified following service-dominant logic in the Business Model Radar (SDBM/R) technique that is part of the BASE/X business engineering approach.

Keywords: Business model; Data-driven Approach; Resource Management; Higher Education (search for similar items in EconPapers)
Date: 2025-09-03
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