Unmasking The Hidden Costs of Ecotourism: A Green Accounting Decision Support System Using Spatial Macro-Tourist Data
DOI:
https://doi.org/10.35800/jip.v14i1.66913Keywords:
Carrying Capacity, Decision Support System, Ecotourism, Green Accounting, Hidden CostsAbstract
While ecotourism is frequently championed as a sustainable solution, the influx of mass tourism often generates hidden ecological costs that remain unrecorded in conventional accounting frameworks. This study aims to design a spatial Decision Support System (DSS) model that integrates green accounting principles with macro-tourism data. Employing the Simple Additive Weighting (SAW) method, this research evaluates the disparity between tourist volume (14.5 million movements) and community-based accommodation capacities within the ecotourism epicenter of North Sulawesi, Indonesia. Two novel spatial accounting indicators are introduced: the Local Carrying Capacity Ratio (LCCR) and the Estimated Environmental Cost (EEC), monetized in the domestic currency (IDR). The DSS algorithm reveals a sustainability paradox: North Minahasa Regency, despite recording the lowest tourist volume (650,320 visitors), emerges as the most critical ecological zone (preference score of 0.586). This vulnerability is attributed to a severe infrastructure deficit that precipitates an extreme overshoot in carrying capacity (LCCR 26.20). Conversely, Manado City implicitly accrues an annual ecological debt exceeding IDR 24.5 billion driven by emissions and waste. These findings underscore that the omission of macro-spatial metrics from regional balance sheets can result in misguided investment policies. Ultimately, the proposed DSS model offers a strategic framework for local governments to formulate equitable carbon levies and reallocate tourism revenues toward the development of local community infrastructure.
Keywords: Carrying Capacity, Decision Support System, Ecotourism, Green Accounting, Hidden Costs
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