Low-Code Platforms as Drivers of Organizational Agility in Post-Pandemic Small Businesses

• Abiodun Okunola

  Ladoke Akintola University Technology

  Author

The COVID-19 pandemic exposed the fragility of small businesses’ operational models while simultaneously accelerating their need for rapid digital adaptation. Low-code platforms have emerged as accessible tools enabling non-technical staff to build applications, yet empirical evidence linking their adoption to measurable organizational agility in post-pandemic SMEs remains fragmented. This study addresses the gap by developing and validating a predictive framework that quantifies the contribution of low-code platform capabilities to organizational agility. Using a mixed-methods design combining survey data from 412 SMEs across Malaysia and Indonesia with structural equation modeling, the research identifies process automation depth, citizen developer empowerment, and integration flexibility as the strongest predictors of agility. The proposed model achieves 89.4% accuracy in classifying SMEs as high-agility versus low-agility adopters, significantly outperforming baseline digital maturity assessments (72.1%). Key findings reveal that low-code adoption alone is insufficient; agility gains materialize only when platforms are embedded within structured process governance and internal capability-building. The study contributes a replicable assessment framework for SME administrators and advances dynamic capabilities theory by operationalizing low-code platforms as tangible enablers of sensing, seizing, and reconfiguring organizational resources in post-crisis contexts.

• PDF

Copyright (c) 2026 Abiodun Okunola (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.