The Impact of Digital Channel Transformation on Agility in Customer Service Resolution for SMEs Post-COVID-19

• Abbas Ahsun

  Texas University

  Author

The COVID-19 pandemic catalysed an unprecedented migration of small and medium-sized enterprises (SMEs) toward digital customer service channels, yet the relationship between specific channel transformation patterns and resolution agility remains inadequately theorised and empirically tested. This study addresses the gap by developing and validating a predictive framework that models how digital channel adoption configurations influence customer service resolution agility in post-pandemic SMEs. Drawing on a cross-national dataset of 491,636 SME technology adoption records and a structured synthesis of empirical evidence from 230 micro and small enterprise owners, the research employs Random Forest, XGBoost, and ensemble machine learning models alongside qualitative comparative analysis. The Random Forest model achieved the highest predictive performance (Test R² = 0.6249), with production-oriented digital infrastructure emerging as a stronger predictor of resolution agility than customer-facing consumption technologies. The integrated framework demonstrated 89.4% classification accuracy in distinguishing high-agility from low-agility SMEs based on channel transformation profiles. Key findings indicate that service agility functions as a mediating mechanism through which digital channel capabilities translate into sustained customer service continuity. The study concludes that SME managers should prioritise foundational digital infrastructure and workforce upskilling over superficial channel proliferation, and offers a replicable framework for diagnosing channel-agility alignment.

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Copyright (c) 2026 Abbas Ahsun (Author)

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