Publication
Abstract
The digital transformation of small and medium-sized enterprises (SMEs) remains perpetually haunted by a paradoxical state where high initial capital outlays often yield negligible short-term returns, leading to a precarious "transformation interruption." Moving beyond simplistic linear assumptions that dominate much of the current literature, this research synthesizes TOE theory, resource-based views, and dynamic capabilities to construct a "four-helix" long-term mechanism, comprising Driving Force, Conduction, Guarantee, and Iteration, to scrutinize the systemic sustainability of digital value creation. Our empirical journey, which necessitated a transition from traditional panel regressions to a more nuanced mixed-method design including Bootstrap chain mediation and fsQCA to account for the messy realities of organizational flux, examines 1,743 A-share listed SMEs from 2018 to 2023. Findings tentatively reveal a significant U-shaped trajectory between digital intensity and performance, suggesting a theoretical "inflection point" at approximately 24–30 months; however, this duration possibly fluctuates based on the maturity of the digital ecosystem. While dynamic capability and business model innovation emerge as vital chain mediators, arguably facilitating the core value transformation. Their effectiveness is perhaps contingent upon a recursive "Iteration" helix that demands further longitudinal validation. Notably, configuration analysis indicates that four-helix synergy achieves a 68.7% success rate, a stark contrast to single-factor drivers, emphasizing that long-term efficacy is a product of configurational alignment rather than isolated technological adoption. These insights lead us to further thinking about the institutionalization of digital habits, suggesting that future SME resilience relies on a self-driven, dynamically iterative system rather than transient software acquisition.
Keywords
Digital Transformation , Long-term Mechanism , Four-helix Model , SMEs , Configurational Synergy .
Metadata
Disciplines: Intelligent Systems
Subjects: Adaptive Control
Cite This Article
APA Style
Zhang, N. (2026). Research on the long-term mechanism of digital transformation for small and medium-sized enterprises. Journal of Intelligence and Engineering Technology, 1(2), 19-28. https://doi.org/10.70393/6a696574.343133
Acknowledgments
FUNDING
INSTITUTIONAL REVIEW BOARD STATEMENT
DATA AVAILABILITY STATEMENT
INFORMED CONSENT STATEMENT
CONFLICT OF INTEREST
AUTHOR CONTRIBUTIONS
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