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A SERVICE-DOMINANT LOGIC FOR DIGITAL TRANSFORMATION RESEARCH AND PRACTICE: SYSTEMATIC REVIEW, RESEARCH AGENDA, AND IMPLEMENTATION ROADMAP

Susan Stead et al.

International Journal of Innovation Management2025https://doi.org/10.1142/s1363919625300028article
AJG 2
Weight
0.46

What the paper says

The interdisciplinary nature of digital transformation requires a shift from theorizing within disciplinary silos to leveraging theory in a way that helps bridge disciplinary boundaries. This study seeks to contribute to this objective by demonstrating that service-dominant logic (S-D logic) as a meta-theory has strong potential to connect IS, service, innovation, and marketing scholars as well as practitioners in understanding and shaping digital transformation. For this purpose, we conduct a computational literature review and create a map of the S-D logic research landscape. Based on this map, we assess how the S-D logic can help address some of the key gaps in our understanding of digital transformation leading to a cross-disciplinary agenda for future research. We argue that an S-D logic perspective on digital transformation can also be informative for practitioners involved in digital transformation activities, whom we equip with an actionable roadmap for implementation.

4 citations

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https://doi.org/https://doi.org/10.1142/s1363919625300028

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@article{susan2025,
  title        = {{A SERVICE-DOMINANT LOGIC FOR DIGITAL TRANSFORMATION RESEARCH AND PRACTICE: SYSTEMATIC REVIEW, RESEARCH AGENDA, AND IMPLEMENTATION ROADMAP}},
  author       = {Susan Stead et al.},
  journal      = {International Journal of Innovation Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1142/s1363919625300028},
}

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A SERVICE-DOMINANT LOGIC FOR DIGITAL TRANSFORMATION RESEARCH AND PRACTICE: SYSTEMATIC REVIEW, RESEARCH AGENDA, AND IMPLEMENTATION ROADMAP

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Evidence weight

0.46

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

F · citation impact0.37 × 0.4 = 0.15
M · momentum0.60 × 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.