Most real estate decisions are multi-criteria by nature. The obvious means to support such decisions are multi-criteria models, developed in the field of operations research (OR) decades ago and applied in many industries ever since. But not in the real estate sector. Here, OR is still a foreign concept, confined to some exotic niches and academic circles. The aim of this paper is to demonstrate that mathematical decision models can be applied to practical real estate problems and can help to improve decision quality. We use OR for commercial portfolio transactions, which are particularly complex due to the exponential increase in the flow of information, which quickly exceeds the information processing capacity of humans.

The research design follows a mixed-methods approach. Based on literature research and interviews with industry experts, a decision model using Analytical Hierarchy Process (AHP) and Elimination Et Choix Traduisant La Realité (ELECTRE) is designed to prioritise properties from a target portfolio. The model architecture includes measures to reduce human decision-making biases, which is a requirement of Behavioral Operations Research (BOR). Then, data from a medium-sized portfolio transaction in Germany is used to test the model. The result is a list of properties ranked in the order of their alignment with the investment objectives, offering an entirely rational solution. Debriefing interviews with the decision-makers support the assumption that this solution is superior to most bounded rational solutions, which were discussed during the acquisition process.