Holistic Decision Matrices

HOLISTIC DECISION MATRICES: TRANSLATING REQUIREMENTS INTO A PRACTICAL TOOL This dataset is part of a master’s thesis by Arno Vanderroost at Ghent University, under the supervision of promotor Dr. Ir. Arnold Janssens and Dr. Ir. Arch. Eline Himpe, and supervisor, Ir. Arch. Luca Maton. This thesis develops and validates essential requirements for a holistic decision-making framework to guide energy renovations in heritage buildings, enabling stakeholders to achieve outcomes that respect heritage values while meeting modern performance standards. As part of the thesis, these decision matrices were developed in Excel, addressing the defined holistic requirements. By applying well-established multi-criteria decision-making (MCDM) methods, these matrices are able to provide real-time decision support, allow for iterative updates, deliver a total score for each renovation strategy, support flexible criteria weighting (relative importance) and enable for multiple preferred strategies through ranking. Five matrix variants were developed, combining different MCDM methods to suit various project scales. All decision matrices (DM) follow the same structure: First, the weighting of criteria importance is determined either by verbal agreement (DM1), a simplified binary pairwise comparison (DM2) or the Analytic Hierarchy Process (DM3-5). Next, renovation strategies are scored using either a five-level qualitative scale (DM1-6), direct quantitative data (DM4) or intervals for uncertain data (DM5). Finally, the ranking of renovation strategies is automatically calculated using the following aggregation methods: Weighted Sum Model for qualitative data (DM1-3) TOPSIS for quantitative data (DM4) TOPSIS Grey for uncertain data (DM5) The holistic decision matrices serve as a practical bridge between MCDM’s well-established theory and the complex reality of energy renovations in heritage buildings. 22/05/2025 Arno Vanderroost