Integrated modelling approach for an eco-industrial park site selection

Abstract

Inconsistencies of the single multi-criteria decision making (SMCD) methods in criteria weight assessment make them unreliable and have led to the wrong siting of industrial parks, which are often abandoned as brownfields that emit GHG. Eco-industrial parks (EIPs) are replacing brownfields but require robust decision-making tools to weigh and rank suitable locations for industry clusters' synergies. Integrated multi-criteria decision making (IMCDM) to address the weaknesses and strengthen the advantages of SMCDM methods, and a model to overlay criteria weights and spatial data easily and accurately were developed. The spatial criteria data for 2009 and 2019 from Tanjung Langsat Industrial Area were collected and prepared by GIS to test the SMCDM and IMCMD consistency weighting and the model resilience. The SMCDM (AHP, ANP and F-AHP) and the IMCDM weights with the 2009 criteria data identified the entire water bodies around the brownfield as suitable sites, making them inconsistent. The 2019 data with the SMCDM weights identified tiny sites as best, also making them inconsistent. The integrated hierarchy network fuzzy analytic process (HN-FAP) and the hierarchy network analytic process (HNAP) with the 2019 criteria data identified part of the water bodies as suitable making it inconsistent. The hierarchy fuzzy analytic process (H-FAP) and the network fuzzy hierarchy analytic process (NFh-AP) identified larger suitable sites without overlaps making them consistent algorithms. The H-FAP and NFh-AP procedures eliminate the weaknesses and consolidate the strengths, giving optimally consistent criteria weights. The two algorithms' consistency and the model efficiency can use different criteria weights and spatial data inputs from elsewhere for 4IR-driven EIP modelling to help brownfield-EIP stakeholders. Future research would address the reverse ranking of MCDM methods when alternatives are added or removed.