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Cited by 559

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Business model innovation – state of the art and future challenges for the field

Open access
Spieth, Patrick, Schneckenberg, Dirk, Ricart, Joan E.·2014·R&D Management

Abstract

Business model innovation is receiving increased attention in corporate practice and research alike. We propose in this article a role‐based approach to categorize the literature and argue that the respective roles of explaining the business, running the business, and developing the business can serve as three interrelated perspectives to present an overview of the current business model innovation field and to accommodate the selected contributions of this special issue. We refer to contributions from entrepreneurship, innovation and technology management, and corporate strategy to explicate the three elaborated perspectives and to summarize the main contents of the special issue articles. We conclude by reflecting on main theoretical challenges for studies on business model innovation which stem from the uncertain boundaries of the phenomenon, and we propose some theoretical stances and analytic levels to develop future avenues for research.

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Metadata

Authors
Spieth, P., Schneckenberg, D., & Ricart, J. E.
Venue
R&D Management
Publisher
Wiley
Published
2014-05-20
Volume
44
Issue
3
Pages
237-247
ISSN
  • 0033-6807 (ISSN-L)
  • 1467-9310
OpenAlex
W2106155612
Cited by
559
References
5
FWCI
117.50
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Business model innovation – state of the art and future challenges for the field. https://app.cochat.ai/papers/10.1111/radm.12071
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Spieth, P., Schneckenberg, D., & Ricart, J. E. (2014). Business model innovation – state of the art and future challenges for the field. R&D Management. https://doi.org/10.1111/radm.12071

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.