Integrating the Triple Bottom Line in Sustainability Assessments: MCDA and Monetization Perspectives

Integrating the triple bottom line (TBL) into sustainability assessment is a methodological challenge. Environmental, social, and economic dimensions are typically evaluated through separate life cycle approaches, each relying on heterogeneous metrics, different uncertainty levels, and value judgements. This thesis investigates how Multi-Criteria Decision Analysis (MCDA), fuzzy logic, and monetization approaches can be combined to improve sustainability evaluations. The theoretical section reviews key MCDA methods focusing on the Analytic Hierarchy Process (AHP) and its capabilities and limitations in integrating diverse indicators and stakeholder preferences. TOPSIS and PROMETHEE methods are analysed to highlight methodological differences and to show how mathematical structures influence outcomes. Fuzzy logic is introduced to represent epistemic uncertainty, qualitative judgements, and linguistic preferences. Three monetization approaches (MF-GDP, True Price, and CE Delft) are tested to provide complementary economic perspectives. However, monetization methods are not yet standardized and remain sensitive to modelling assumptions and valuation choices. Social monetization, in particular, faces major conceptual and ethical challenges. Three case studies apply the proposed methods: i) the selection of applications for cellulose nanofibre-reinforced composites (MPAS), ii) a comparative evaluation of sunscreen formulations, iii) and national electricity markets in four countries. Results show both convergence and method-dependent differences in MCDA rankings, while fuzzy AHP and monetization consistently identify stable alternatives. Overall, the results indicate that AHP remains a transparent and structured foundation for integrating the TBL, while fuzzy logic extends the ability to represent uncertainty and non-quantitative evaluations. Monetization offers a complementary economic perspective that can support comparative decision-making for relevant stakeholders.