Scholarlink

<p>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.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Decarbonizing Indonesian hospitals challenges and causal pathways toward sustainable healthcare

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月22日

查看全文
  • 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

摘要

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.

Graphical abstract