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May 17, 2024

Driving factors for the adoption of green finance in green building for sustainable development in developing countries: The case of Ghana

Debrah, C., Chan, A. P. C., Darko, A., Ries, R. J., Ohene, E., & Tetteh, M. O. (2024). Driving factors for the adoption of green finance in green building for sustainable development in developing countries: The case of Ghana. Sustainable Development., 1–22. https://doi.org/10.1002/sd.3022

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Abstract

While there are many motivating factors for green finance (GF) implementation, a comprehensive taxonomy of these variables is lacking in the literature, especially for green buildings (GBs). This study aims to analyze the criticality and interdependence of GF‐in‐GB's driving factors. This study develops a valid set of factors to justify the interrelationships among the drivers. The drivers of GF‐in‐GB are qualitative in nature, and uncertainties exist among them due to linguistic preferences. This study applies the fuzzy Delphi method to validate eight drivers under uncertainties. Fuzzy Decision‐Making Trial and Evaluation Laboratory (FDEMATEL) with qualitative information is used to determine the interrelationships among the drivers. The drivers were grouped under two categories: prominent drivers and cause‐effect drivers. The findings revealed that “increased awareness of GF models in GB” and “preferential capital requirements for low‐carbon assets” are the top two most prominent/important drivers of GF‐in‐GB. In Ghana, the top three cause group drivers are “climate commitment,” “improved access to and lower cost of capital,” and “favorable macroeconomic conditions and investment returns.” Drivers with the highest prominence values have the potential to affect and/or be affected by other drivers; therefore, managers and policymakers should prioritize promoting or pursuing these drivers in the short term. On the other hand, it is important to pay more than equal attention to the drivers with the highest net cause values because they have the largest long‐term impact on the entire system. The theoretical and practical implications of the study are discussed, enhancing understanding and decision‐making in GF‐in‐GB.

Keywords

fuzzy Delphi method; fuzzy DEMATEL; green building; green finance; sustainable development