Dataset for decision-support frameworks for MCDA method selection and emission abatement technology assessment in the maritime sector

This dataset supports:
Xu, K. (2025). Decision-support frameworks for MCDA method selection and emission abatement technology assessment in the maritime sector. [Doctoral Thesis, University of Southampton].

The dataset contains stakeholder-derived priorities for selected emission abatement technologies in the maritime industry. These priorities were generated through a structured decision-making process using the Analytic Hierarchy Process (AHP). The dataset captures the relative importance assigned to each technology by stakeholders based on their pairwise comparison judgments.

The underlying data were collected during a structured stakeholder engagement workshop, which involved three key participants representing different roles in the maritime domain: a ship owner, a ship operator, and a port operator. Each participant contributed their expert judgments on the suitability of various emission abatement technologies for reducing pollutants including NOx, SOx, CO₂, and PM2.5.

The Analytic Hierarchy Process was implemented using AHP-OS, an open-source, web-based software tool tailored for decision analysis. AHP-OS supports individual and group decision-making processes by enabling users to perform pairwise comparisons, calculate consistency ratios (CR), and refine inputs to improve judgment coherence.

Participants received AHP training and were given access to AHP-OS via a shared link, where they completed their individual matrices. The software’s interface allows for real-time feedback on inconsistency, helping users adjust inputs as needed. For aggregation, AHP-OS offers multiple methods (linear, geometric, logarithmic), with this study employing the geometric mean to derive a group consensus, consistent with best practices in group decision-making.