Sustainable financial infrastructure and governance: A fuzzy multi-criteria decision-making analysis of open service innovation in unstable economies

Open service innovation in the banking industry has led to sustainable competitive advantages for the economies of developed countries. This approach can also be advantageous for banks in developing countries grappling with unstable economic conditions, such as high inflation, economic sanctions, and low growth. Therefore, it is crucial to identify and present a model of key criteria for open service innovation within the banking sector of developing countries facing economic instability. In this context, several MCDM techniques, along with fuzzy set theory, were employed to identify the most significant criteria for open service innovation in the banking sector. Initially, the Entropy method and TOPSIS were used to select leading banking experts and gather their insights on the criteria for open service innovation. Subsequently, fuzzy DEMATEL and fuzzy ANP were applied to determine the interrelationships and relative weights of the open service innovation criteria. A dataset comprising the opinions of banking experts in Iran, which serves as a case study of a developing country, was used to evaluate the effectiveness of the proposed model. Four primary criteria and twelve sub-criteria were identified from the literature to assess open service innovation in the banking industry. The findings indicate that environmental factors are of utmost significance, followed by organisational, interaction, and resource factors, respectively. In summary, our results reveal the necessity of designing a policy framework that aligns financial infrastructure with sustainable governance. This includes highlighting the role of regulatory sandboxes in fostering innovation while ensuring compliance, the importance of data governance in maintaining trust and stability in the financial system, and the impact of AI implementation and AI-driven algorithms in driving open innovation within an unstable banking and economic system. Policymakers should incentivise investment in advanced technologies like AI, machine learning, and blockchain to enhance financial system resilience and transparency. Strengthened regulatory frameworks should align financial governance with ESG principles, ensuring transparency and sustainability. Regulatory sandboxes and innovation clusters can foster collaboration between banks, fintech companies, and regulators, enhancing trust and compliance. Strict data governance frameworks aligned with global standards are essential to balancing innovation with privacy.

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Publication Details

Journal
Sustainable Futures
Published
2025-02-10
DOI
https://doi.org/10.1016/j.sftr.2025.100485
Citations
12
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
24.87
Controls
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article

Sustainable financial infrastructure and governance: A fuzzy multi-criteria decision-making analysis of open service innovation in unstable economies

Homa Molavi, Lihong Zhang, Mohammad Khanbaei
12 citations
Sustainable Futures
Sharing Economy and Platforms
24.87
article

Sustainable financial infrastructure and governance: A fuzzy multi-criteria decision-making analysis of open service innovation in unstable economies

Homa Molavi, Lihong Zhang, Mohammad Khanbaei
article en
12 citations

Abstract

Open service innovation in the banking industry has led to sustainable competitive advantages for the economies of developed countries. This approach can also be advantageous for banks in developing countries grappling with unstable economic conditions, such as high inflation, economic sanctions, and low growth. Therefore, it is crucial to identify and present a model of key criteria for open service innovation within the banking sector of developing countries facing economic instability. In this context, several MCDM techniques, along with fuzzy set theory, were employed to identify the most significant criteria for open service innovation in the banking sector. Initially, the Entropy method and TOPSIS were used to select leading banking experts and gather their insights on the criteria for open service innovation. Subsequently, fuzzy DEMATEL and fuzzy ANP were applied to determine the interrelationships and relative weights of the open service innovation criteria. A dataset comprising the opinions of banking experts in Iran, which serves as a case study of a developing country, was used to evaluate the effectiveness of the proposed model. Four primary criteria and twelve sub-criteria were identified from the literature to assess open service innovation in the banking industry. The findings indicate that environmental factors are of utmost significance, followed by organisational, interaction, and resource factors, respectively. In summary, our results reveal the necessity of designing a policy framework that aligns financial infrastructure with sustainable governance. This includes highlighting the role of regulatory sandboxes in fostering innovation while ensuring compliance, the importance of data governance in maintaining trust and stability in the financial system, and the impact of AI implementation and AI-driven algorithms in driving open innovation within an unstable banking and economic system. Policymakers should incentivise investment in advanced technologies like AI, machine learning, and blockchain to enhance financial system resilience and transparency. Strengthened regulatory frameworks should align financial governance with ESG principles, ensuring transparency and sustainability. Regulatory sandboxes and innovation clusters can foster collaboration between banks, fintech companies, and regulators, enhancing trust and compliance. Strict data governance frameworks aligned with global standards are essential to balancing innovation with privacy.

Sustainable FuturesVol. 9
Islamic Azad University, Science and Research Branch (IR), University of Manchester (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Sharing Economy and Platforms
24.87
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