Data-driven natural capital accounting model in Indonesia: Impacts of environmentally related economic activities on ecological processes and services

Abstract

In this study, natural capital accounting (NCA) is enhanced by constructing a data-driven hierarchical model that can help improve policy decision-making. NCA enables the management and transparency of natural capital and ecological processes and services, resulting in better societal activities and well-being in Indonesia's regions; however, it does not account for environmentally related economic activities that may negatively influence natural capital, processes and services. In this study, a data-driven approach is used to address this issue. Valid attributes are identified, and a thorough NCA hierarchical model that incorporates synchronized accounting on ecology, environment-related economic activities and societal well-being is developed. This approach utilizes content and bibliographic analyses, the entropy weighted method (EWM) and the fuzzy Delphi method (FDM), which are used to validate the data-driven NCA measurements. Exploratory factor analysis (EFA) is utilized to cluster the measurements and assess their reliability. The fuzzy decision-making trial and evaluation laboratory (FDEMATEL) is used to construct the NCA hierarchical structure by considering the cause-and-effect interrelationships among attributes. The valid prioritized attributes are determined, and a hierarchical structure is built to support government decision-making processes. The findings suggest that water resource accounting, forestry production, raw material extraction, resource allocation management and resource consumption management are the criteria that fluctuate the most for practitioners and governments.