Binary ESG Veto versus Structural Penalization in Technology Portfolio Selection: A Data Modeling Simulation for the Energy Transition

Technology portfolio selection for the energy transition must reconcile value, maturity, organizational readiness, and normative requirements. This paper compares two architectures under identical raw data, input weights, costs, and budget: TREVO, which applies blockwise TOPSIS, TRL-modulated Cobb-Douglas integration, and readiness and success factors; and a managerial benchmark combining global TOPSIS, a binary ESG veto, and 0-1 knapsack selection. A controlled ten-technology problem is evaluated in a base case and 117 distinct pipeline runs over budget and calibration grids. The base portfolios attain a Jaccard index of 0.50, and divergence persists throughout the sensitivity slices. The veto excludes threshold violations but leaves survivors subject to compensatory distance aggregation; TREVO instead imposes a continuous, maturity-dependent penalty on normative-instrumental imbalance. Energy-transition portfolios should therefore distinguish potential from capturable value and disclose the assumptions that generate the selected set.