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Unpacking the Regulatory Ambiguity Mechanism: Implications for Industry‐Level Digital Transformation

Karin Väyrynen et al.

Information Systems Journal2025https://doi.org/10.1111/isj.12595article
AJG 4ABDC A*
Weight
0.48

Abstract

The relationship between digital transformation and regulation is complex and bidirectional: regulation both drives and responds to changes in the technology landscape. Moreover, regulatory efforts to shape industry‐level digital transformation often produce unwanted outcomes. Existing theories are insufficient for examining this complex relationship between regulation and digital transformation. Our case study of the Finnish taxi industry illustrates these complexities. The industry underwent a legal reform intended to legalise Uber‐type solutions while restricting certain other solutions. By drawing on the notion of regulatory ambiguity and mechanism‐based explanation, we show how ambiguity arises from the imprecise regulation in connection with conflicting regulation and technological uncertainties. We model the regulatory ambiguity mechanism consisting of the interconnected elements that, by affecting each other and working together, drive unintended changes in the technology landscape. We theorise regulatory ambiguity as a condition that emerges when regulations are imprecise, inconsistent, or evolving. This ambiguity shapes the technology landscape and related industry‐specific practices, impacting digital transformation. Our research contributes to the literature on digital transformation and on the regulation of technology. We identify and analyse the regulatory ambiguity mechanism, providing information systems (IS) researchers with a novel framework to examine the role of regulation in digital transformation. We also conceptualise regulatory impact as a lens for future IS research.

5 citations

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https://doi.org/https://doi.org/10.1111/isj.12595

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@article{karin2025,
  title        = {{Unpacking the Regulatory Ambiguity Mechanism: Implications for Industry‐Level Digital Transformation}},
  author       = {Karin Väyrynen et al.},
  journal      = {Information Systems Journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/isj.12595},
}

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.