Decarbonizing Indonesian hospitals challenges and causal pathways toward sustainable healthcare
Year: 2026
Type: article
Abstract: The decarbonization of hospital infrastructure is a pivotal element in advancing climate-resilient healthcare systems, especially in developing regions. This study employs the Bayesian Best–Worst Method (BWM) to systematically identify and prioritize key barriers hindering hospital decarbonization in Banten Province, Indonesia. A total of 14 barriers were evaluated by domain experts based on their perceived criticality and interrelationship, using expert judgment aggregated through a Bayesian framework. The results highlight high initial investment costs (B7) as the most significant barrier, characterized by the highest mean weight (0.142) and dominant D − R value, indicating its status as a root cause requiring urgent intervention. Other top-ranked barriers include energy-inefficient devices (B4), lack of supportive regulation (B3), and absence of decarbonization targets (B2), reflecting systemic and institutional constraints. The integration of D-R analysis with Bayesian weights enables a robust mapping of barrier typologies and facilitates the development of quadrant-based strategic recommendations. Implications for Banten Province include the need for green financing schemes, regulatory reform, energy-efficient procurement standards, and enhanced capacity building in sustainable hospital management. The study contributes to the growing body of research in sustainable healthcare by offering a transparent, replicable prioritization method, while also acknowledging contextual limitations such as sample representativeness and evolving policy landscapes. These findings provide a practical decision-support tool for policymakers aiming to accelerate low-carbon transitions in the healthcare sector.
Source: Discover Sustainability
Authors: Asep Marfu, Agung Purwanto, Dwi Atmanto, Henita Rahmayanti, Arita Marini, Desy Safitri, Vera Julia, Leola Dewiyani, Rezeqi Hardam Saputro, Nindhita Priscillia Muharrani, Septantri Shinta Wulandari, Anna Sofia Atichasari, Samlibry Adhitia, Catur Wahyu Prasetyo, Sandhi Prasetiawan, Daiman Daiman
Language: English
Subfield: Urban Studies
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W7162142148
