Stakeholder prioritisation of green sukuk challenges under uncertainty: A mixed-methods study using Bayesian Best–Worst Method
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Abstract (EN)
Green Sukuk is a Shariah-compliant financial innovation designed to fund environmentally sustainable projects, has attracted growing attention as a potential bridge between Islamic finance and global sustainability agendas. However, despite increasing issuances in countries such as Malaysia, Indonesia, and Saudi Arabia, the Green Sukuk market remains limited in scope, uneven in development, and fragmented in governance. This dissertation investigates multidimensional barriers constraining market growth and proposes a structured framework for prioritising and addressing them. This study adopts an integrated methodology that combines systematic and bibliometric literature reviews, expert interviews, and Bayesian Best-Worst Method (BWM) analysis. Literature mapping identifies thematic gaps in conceptual clarity, regulatory coherence, and stakeholder alignment. Qualitative insights from expert interviews uncovered the contextual, institutional, and ethical dynamics shaping the market. The BWM, used here as a probabilistic decision tool, enables nuanced prioritisation of challenges and potential solutions under uncertainty. The findings reveal a set of critical barriers, such as Shariah-Green misalignment, fragmented certification mechanisms, and low investor awareness, that vary in intensity across jurisdictions. The study's triangulated approach allows for the construction of a stakeholder-informed challenge taxonomy and flexible decision framework applicable to emerging and established Islamic finance contexts. By integrating decision science with ethical and institutional analyses, this study offers practical and conceptual insights into the evolving landscape of Islamic green finance.
Author
Mohamed Zakarıa Fodol
Institution

Sakarya University
İslam Ekonomisi ve Finans Bilim Dalı
How to Cite
Mohamed Zakarıa Fodol (Doctorate thesis). Stakeholder prioritisation of green sukuk challenges under uncertainty: A mixed-methods study using Bayesian Best–Worst Method, 2025, Sakarya University.
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