AJAArab J. Admin.1110-54532663-4473The Arab Journal of AdministrationLeague of Arab States, Arab Administrative Development OrganizationCairo, Egypt10.21608/aja.2025.405547.1902879Research ArticleNavigating Digital Currency Regulation: Implications for International Collaboration Effectiveness “Evidence from the UAE”AldabbaghTamadhert.aldabbagh@cu.ac.aeAssistant Professor, Human Resources Management Department, Business Administration College, City University AjmanUnited Arab Emirates08202528012026022026072025082025461391402This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
This study examines how regulatory frameworks, market dynamics, and international collaboration effectiveness (ICE) are related in the context of digital currency regulation. Quantitative investigation revealed strong positive correlations between regulatory frameworks, market dynamics, and ICE, highlighting their importance in promoting efficient cross-border collaboration. The study also points out drawbacks such as the possible neglect of other significant elements and the dependence on quantitative methodologies. Future studies should investigate more factors and use mixed-method approaches to better comprehend the complexity of regulating digital currencies. The findings highlight the significance of legal frameworks and market factors in influencing international collaboration and fostering innovation. Policymakers are encouraged to adjust regulatory strategies to navigate the changing financial technology environment, promoting stability while supporting growth and advancement in the worldwide digital economy. This study provides valuable insights into current debates surrounding the regulation of digital money and its impact on international cooperation.
The United Arab Emirates (UAE) has become a significant player in the rapidly evolving financial technology (FinTech) landscape, with a commitment to using digital currencies to stimulate economic growth and promote financial inclusivity. The global nature of banking necessitates international collaboration and standards to navigate digital currency ecosystems. Effective collaboration between governments and regulators is needed to address interoperability and cross-border transaction issues (Arner et al., 2020; Fernández-Villaverde & Sanches, 2018). Cooperative initiatives and regulatory structures exist, yet challenges persist, hindering standardized protocols. Addressing these in the UAE is vital to its ambition to be a dominant FinTech hub (Cong & Mayer, 2022).
Challenges arise from multiple factors: regulatory frameworks for clear guidance (Dow, 2019); technological infrastructure for secure, seamless transactions; market characteristics (consumer behavior, investor sentiment); and multinational partnerships to tackle transnational issues and align with global standards (Cunha et al., 2021). Independent factors include legal frameworks, technical infrastructure, market dynamics, and foreign alliances. Regulatory agility can moderate outcomes by mitigating constraints on innovation (Ospina et al., 2021).
Study objectives:
Investigate the influence of regulatory frameworks on digital currency norms and international collaboration effectiveness.Examine the role of technological infrastructure on digital currency norms and international collaboration effectiveness.Assess the impact of market dynamics on digital currency norms and international collaboration effectiveness.Investigate the role of international partnerships on digital currency norms and global collaboration effectiveness.Examine the moderating role of regulatory agility on the relationship between regulatory frameworks and digital currency norms and international collaboration effectiveness.Conceptual ReviewOverview of FinTech in the UAE
FinTech in the UAE is driven by economic stability, technological infrastructure, and regulation (Zarrouk et al., 2021). Frameworks for FinTech laws underscore risk management (Al Suwaidi et al., 2022). The UAE fosters innovation through supportive environments (Schilirò, 2021). Digital currencies prompt shifts in monetary systems (Dow, 2019) and align with CBDC trends (Cunha et al., 2021), aiming for efficiency, transparency, and inclusivity.
International Digital Currency Regulation Cooperation and Standards
International cooperation is critical to govern digital currencies across borders, mitigating AML/CFT risks and enabling knowledge sharing (He et al., 2017; Kakavand et al., 2017; Adrian & Mancini-Griffoli, 2021). Regulatory standards enhance transparency and consumer trust, ensure AML/KYC compliance, and reduce fragmentation (Tallberg & Zürn, 2019; Gabor & Brooks, 2020).
Previous Research on Digital Currency Regulation Factors
Key determinants: regulatory frameworks (Carapella & Flemming, 2020; Engert & Fung, 2017; Mancini-Griffoli et al., 2018); technology infrastructure (Janssen et al., 2020; Kakavand et al., 2017; Truby, 2018); market dynamics (Chiu et al., 2023); and international cooperation (Singer, 2017; Tallberg & Zürn, 2019). Alignment of regulation with fast-evolving technology is essential.
Persistent Issues with UAE Regulation of Digital Currency
Issues include interoperability and cross-border transaction frictions (Krimmer et al., 2021; Protopappas et al., 2020; Viñuela et al., 2020); regulatory gaps and lagging legislation (Bossu et al., 2020; Lee et al., 2021); and technological limits (scalability, security, privacy) plus supervisory expertise needs (Ilham et al., 2019; Janssen et al., 2020; Auer et al., 2020).
Regulatory Agility as a Moderating Variable
Regulatory agility stresses adaptive, timely policy adjustments and stakeholder engagement to balance innovation and risk (Cumming et al., 2019; Bossu et al., 2020; Lee et al., 2021). It mitigates risks, improves efficiency, and supports investor trust (Viñuela et al., 2020; Krimmer et al., 2021; Protopappas et al., 2020). Recent work highlights agility in fintech contexts (Al Najdawi et al., 2024; Alzoubi et al., 2025; Kurdi et al., 2025; Shwedeh, 2024a, 2024b; Shwedeh, Nour, et al., 2024; Shwedeh, Yas, et al., 2024; H. Yas et al., 2024; N. Yas et al., 2024).
The Problem of the Study
The study asks: To what extent do regulatory frameworks and market dynamics influence the effectiveness of international collaboration in digital currency regulation? Sub-questions address how legal frameworks and market dynamics facilitate or hinder cooperation and their synergistic effects.
Objectives of the StudyAnalyze the relationship between regulatory frameworks and international collaboration effectiveness.Explore the impact of market dynamics on cooperation in regulating digital assets.Determine interconnections among legal frameworks, market factors, and collaboration effectiveness.Provide policy recommendations to enhance stability and innovation in the global digital economy.Research HypothesesRegulatory frameworks on digital currency norms significantly influence the effectiveness of international collaboration.Technology infrastructure significantly influences digital currency norms and effectiveness in international collaboration.Market dynamics significantly relate to digital currency norms and international collaboration effectiveness.International partnerships significantly impact digital currency norms and global collaboration effectiveness.Regulatory agility significantly moderates the relationship between regulatory frameworks and digital currency norms and international collaboration effectiveness.Application of Institutional Theory to Digital Currency Regulation
Institutional theory explains how formal and informal institutions shape regulatory behavior (Hinings et al., 2018; Janssen et al., 2020). Regulatory frameworks are influenced by governmental, industry, and social pressures. Understanding these dynamics helps craft adaptive responses, promote innovation, and ensure stability (Kakavand et al., 2017; Kiff et al., 2020; Van Zanten & Van Tulder, 2018).
Methodology
A survey of individuals in the UAE financial sector and fintech/cryptocurrency businesses was conducted. Measurement items:
ICE (6 items) from Cunha et al. (2021); Schilirò (2021).Regulatory framework (4 items) from Engert & Fung (2017); Mancini-Griffoli et al. (2018).Regulatory agility (4 items) from Bossu et al. (2020); Cumming et al. (2019); two items (RA3, RA4) were removed for low loadings.Technology infrastructure (4 items) from Arner et al. (2020); Fernández-Villaverde & Sanches (2018).Market dynamics (4 items) from Carapella & Flemming (2020).International partnership (4 items) from Chiu et al. (2023); Singer (2017); Tallberg & Zürn (2019).
Analysis used SEM (PLS-SEM) with measurement and structural model assessments (Benjamin et al., 2006). Validities (convergent, discriminant) were checked using AVE, CR, Fornell–Larcker, and HTMT. Multicollinearity was assessed via VIF (Dormann et al., 2013). Effect sizes (f2) and explained variance (R2) were reported.
Analysis Presentation
Construct validity met AVE > 0.5 and CR > 0.7 after removing RA3 and RA4. Discriminant validity satisfied Fornell–Larcker and HTMT (< 0.9). VIF < 5 indicated no multicollinearity. R2 for ICE = 0.763 (adjusted), explained by IP, MD, RA, TI, and RF. RF showed the largest f2 (3.392).
Research Frameworks
Assessing Measurement Model
Measurement Model Assessment
Construct
Items
Item Loadings
CR
AVE
Discriminant Validity
ICE
Ice_01
0.818
0.934
0.785
YES
Ice_02
0.925
Ice_03
0.876
Ice_04
0.916
Ice_05
0.892
IP
ip_01
0.564
0.800
0.631
YES
ip_02
0.979
ip_03
0.785
MD
md_01
0.951
0.893
0.903
YES
md_02
0.950
RA
ra_01
0.931
0.824
0.814
YES
ra_02
0.872
RF
rf_01
0.903
0.899
0.744
YES
rf_02
0.906
rf_03
0.897
rf_04
0.733
TI
ti_01
0.879
0.892
0.698
YES
ti_02
0.932
ti_03
0.919
ti_04
0.556
Source: Results from sample survey data analyzed using AMOS.
Fornell–Larcker Criterion
ICE
IP
MD
RA
RF
TI
ICE
0.849
0.607
0.702
0.656
0.840
0.728
IP
0.870
0.816
0.853
0.629
0.802
MD
0.868
0.690
0.711
0.801
RA
0.877
0.650
0.684
RF
0.864
0.722
TI
0.922
Diagonal values are square roots of AVE. Source: Results from sample survey data analyzed using AMOS.
HTMT Correlations
ICE
IP
MD
RA
RF
TI
IP
0.674
MD
0.769
0.517
RA
0.716
0.258
0.770
RF
0.691
0.704
0.790
0.715
TI
0.788
0.873
0.867
0.741
0.786
RA × RF
0.484
0.193
0.242
0.251
0.488
0.277
All HTMT values < 0.9 indicate discriminant validity. Source: Results from sample survey data analyzed using AMOS.
Variance, Effect Sizes, and VIF
Construct
R2
R2 (adj.)
f2
VIF
ICE
0.772
0.763
—
—
IP
—
—
2.933
—
MD
—
—
1.097
—
RA
—
—
2.168
—
RF
—
—
1.073
—
TI
—
—
3.932
—
RA × RF
—
—
1.308
—
Source: Results from sample survey data analyzed using AMOS.
Analysis Findings
Significant positive relationships with ICE: RF (β = 0.473, T = 8.668, p < 0.05), MD (β = 0.126, T = 2.588, p < 0.05), RA (β = 0.351, T = 6.694, p < 0.05). H1, H3, and H5 supported. Non-significant: TI (β = -0.07, T = 1.524, p = 0.127) and IP (β = 0.027, T = 0.946, p = 0.344), so H2 and H4 not supported. Interaction RA × RF is significant (β = -0.066, T = 3.511, p < 0.05).
Structural Model Assessment
Hypothesis Testing
Hypothesis
Relationship
β
STD
T stat
p-value
H1
RF → ICE
0.473
0.055
8.668
0.000
H2
TI → ICE
-0.070
0.046
1.524
0.127
H3
MD → ICE
0.126
0.049
2.588
0.010
H4
IP → ICE
0.027
0.029
0.946
0.344
H5
RA → ICE
0.351
0.052
6.694
0.000
H6
RA × RF → ICE
-0.066
0.019
3.511
0.000
Source: Results from sample survey data analyzed using AMOS.
Discussion
Support for H1, H3, and H5 underscores the importance of robust regulatory frameworks, adaptive market dynamics, and regulatory agility in fostering international collaboration (Adrian & Mancini-Griffoli, 2021; Arner et al., 2020). Non-support for H2 and H4 suggests technology infrastructure alone may not enhance collaboration, warranting further study into digital literacy, cybersecurity, and interoperability (Gabor & Brooks, 2020; Kakavand et al., 2017).
Theoretical and Practical Implications
Institutional theory frames how regulatory institutions, market participants, and technology interact (Hinings et al., 2018; Kiff et al., 2020). Practically, regulators should craft clear, adaptive rules, engage stakeholders, and align with technological progress to bolster legitimacy and stability (Kakavand et al., 2017; Van Zanten & Van Tulder, 2018).
Study’s Limitations
Focus on selected variables may omit cultural, geopolitical, and organizational factors. Quantitative design limits depth; mixed methods could add richness. Longitudinal work could track regulatory evolution and collaboration impacts.
Conclusions
Regulatory frameworks and market dynamics are pivotal for international collaboration in digital currency regulation. Future research should broaden variables, apply mixed methods, and adopt longitudinal designs to inform adaptive, innovation-supportive policies.
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