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Learning while (re)configuring: Business model innovation processes in established firms
Open accessAbstract
This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: "drifting" starts with an emphasis on experiential learning and shifts later to cognitive search; "leaping," in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning.
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“BMI takes place through a learning process in which discovery via experimentation is more appropriate than conventional analytical approaches (McGrath, 2010) or more cognitiveoriented approaches (Berends, Smits, Reymen, & Podoynitsyna, 2016;Martins, Rindova, & Greenbaum, 2015;Tikkanen, Lamberg, Parvinen, & Kallunki, 2005).”
From Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs? (2019) · cites this paper as Berends, Smits, Reymen, & Podoynitsyna, 2016
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“Berends et al. (2016) defined four elements of BMI: (a) conceptualizing new ideas, (b) creating new BMs, (c) adapting the BM after it is in operation, and (d) experimenting to learn about and validate the model.”
From Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs? (2019) · cites this paper as Berends et al. (2016)
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Metadata
- Authors
- Berends, H., Smits, A., Reymen, I., & Podoynitsyna, K.
- Affiliations
- Eindhoven University of Technology (NL)
- Radboud University Nijmegen (NL)
- Corresponding author
- Berends, Hans
- Venue
- Strategic Organization
- Publisher
- SAGE Publications
- Published
- 2016-02-28
- Volume
- 14
- Issue
- 3
- Pages
- 181-219
- ISSN
- 1476-1270 (ISSN-L)
- 1741-315X
- PMC
- PMC5447949
- OpenAlex
- W2313929078
- Cited by
- 274
- References
- 92
- Citations by year
- 2026: 14 · 2025: 25 · 2024: 23 · 2023: 27 · 2022: 50 · 2021: 42 · 2020: 40 · 2019: 23 · 2018: 18 · 2017: 12
- FWCI
- 42.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Strategic Organization (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- TU/e Research Portal (submittedVersion)
- Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
- TU/e Research Portal (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- University of Liverpool
- European Regional Development Fund
- Interreg
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Innovation
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Management and Organizational Studies
- Keywords
- business model innovation, organizational learning, experiential learning, cognitive search, incumbent firms, innovation pathways, radical innovation, business model development, organizational change
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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