The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
The digital transformation of business models in the creative industries: A holistic framework and emerging trends
Abstract
This paper examines how digital technologies facilitate business model innovations in the creative industries. Through a systematic literature review, a holistic business model framework is developed, which is then used to analyse the empirical evidence from the creative industries. The research found that digital technologies have facilitated pervasive changes in business models, and some significant trends have emerged. However, the reconfigured business models are often not ‘new’ in the unprecedented sense. Business model innovations are primarily reflected in using digital technologies to enable the deployment of a wider range of business models than previously available to a firm. A significant emerging trend is the increasing adoption of multiple business models as a portfolio within one firm. This is happening in firms of all sizes, when one firm uses multiple business models to servedifferent markets segments, sell different products, or engage with multi-sided markets, or to use different business models over time. The holistic business model framework is refined and extended through a recursive learning process, which can serve both as a cognitive instrument for understanding business models and a planning tool for business model innovations. The paper contributes to our understanding of the theory of business models and how digital technologies facilitate business model innovations in the creative industries. Three new themes for future research are highlighted.
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Digital transformation: A multidisciplinary reflection and research agenda
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2019.09.022 · Cited by 5,720
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Identifying Digital Transformation Paths in the Business Model of SMEs during the COVID-19 Pandemic
Priyono, A., Moin, A., & Putri, V. N. A. O. (2020) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.3390/joitmc6040104 · Cited by 702
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Clauss, T., Kraus, S., Kallinger, F. L., Bican, P. M., Brem, A., & Kailer, N. (2021) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2020.07.003 · Cited by 363
Metadata
- Authors
- Li, F.
- Venue
- Technovation
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 92-93
- Pages
- 102012
- ISSN
- 0166-4972 (ISSN-L)
- OpenAlex
- W2781782698
- Cited by
- 733
- References
- 86
- FWCI
- 49.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Funders
- Economic and Social Research Council (RES-185-31-0017)
- Research Councils UK (EP/K039857/1, EP/G066019/1)
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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.