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Digital Sustainable Finance Capability and SME Resilience Under Polycrisis (Research Square)

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Research paperResearch SquareOctober 202632 pages48 min readCharbel Salloum, Renato Pereira, Hajer Jarrar, Andrej PřívaraOriginal source
Key number
8,184 observations
Total firm-year observations p.2
What changed
31%
Reconfiguration mediation share p.2
Largest segment
1,439 firms
AIM-listed firms in sample p.2

Summary

  • The study analyzes a panel of 1,439 UK AIM-listed SMEs across 8,184 firm-year observations from 2016 to 2025 to evaluate the impact of digital sustainable finance capability on business resilience.p.2
  • A one-standard-deviation increase in lagged digital sustainable finance capability is associated with a 0.309-standard-deviation improvement in SME resilience during shock windows.p.20
  • Resource reconfiguration intensity acts as a mediator, accounting for approximately 31% of the total capability effect on resilience.p.2
  • Lagged digital sustainable finance capability shows no statistically significant impact on reducing the risk of firm delisting, returning a hazard ratio of 0.998.p.21

Key insights

  1. Digital sustainable finance capability functions as an integrated higher-order construct combining digital operations, digital finance, data analytics, and sustainability credibility.p.10
  2. Lagged capability positively influences the intensity of resource reconfiguration (b = 0.304, SE = 0.020, p < .001) as shock windows open.p.20
  3. Resource reconfiguration directly enhances SME resilience during shock windows (b = 0.311, SE = 0.011, p < .001).p.20
  4. Adversity severity amplifies the capability-to-reconfiguration path (interaction b = 0.081, SE = 0.017, p < .001), demonstrating higher value for rapid reallocation during severe macro-financial shocks.p.20
  5. The mechanism provides performance stability on intensive operational margins rather than serving as protection against firm delisting or total exit.p.22
  6. Multiple imputation and complete-case benchmark models yield highly consistent direct effect estimates (0.215 vs. 0.213), validating the missing data treatment.p.21

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