FinTech adoption in the UAE: total interpretive structural modeling of drivers and challenges
Maryam Meraj et al.
What the paper says
Purpose This study aims to investigate the hierarchical structure of drivers and challenges influencing the adoption of financial technologies (FinTech) in the United Arab Emirates, providing a novel perspective on the interdependencies among these factors. Design/methodology/approach Adopting a qualitative research approach, this study combines an extensive literature review with expert insights. Using Total Interpretive Structural Modeling (TISM), it develops hierarchical models to elucidate the drivers and challenges of FinTech adoption. In addition, a MICMAC (Cross-Impact Matrix Multiplication) analysis assesses the driving and dependence power of each variable. Findings The findings identify customer technical expertise (V3) as the pivotal driver for FinTech adoption in the UAE, necessitating robust technical capital and disruptive business models to sustain technological advancement. Conversely, significant challenges such as a lack of incubation and innovation hubs (C7), stringent regulatory approval processes (C4) and a nascent FinTech ecosystem (C6) hinder growth. These hierarchical relationships reveal complex interdependencies critical for effective FinTech adoption. Originality/value This paper makes a distinctive contribution by integrating fragmented insights into a cohesive framework that addresses both the drivers and challenges of FinTech adoption. By applying TISM and MICMAC methodologies, it uncovers the hierarchical interdependencies among these factors, advancing theoretical understanding and offering practical implications for policymakers, regulators and financial institutions. The study’s structured approach provides actionable insights for fostering FinTech innovation and navigating the challenges unique to the UAE’s financial landscape.
3 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.32 × 0.4 = 0.13 |
| M · momentum | 0.57 × 0.15 = 0.09 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.