The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence
Open accessAbstract
Artificial intelligence (AI) has been altering industries as evidenced by Airbnb, Uber and other companies that have embraced its use to implement innovative new business models.Yet we may not fully understand how this emerging and rapidly advancing technology influences business model innovation.While many companies are being made vulnerable to new competitors equipped with AI technology, this study attempts to focus on the proactive side of the use of AI technology to drive business model innovation.Describing AI technology as the catalyst of business model innovation, this study sheds light on contingent factors shaping business model innovation initiated by the emerging technology.This study first provides a brief overview of AI, current issues being tackled in developing AI and explains how it transforms business models.Our case study of two companies that innovated their business models using AI shows its potential impact.We also discuss how executives can create an innovative AI-based culture, which rephrases the process of AI-based business model innovation.Companies that successfully capitalize on AI can create disruptive innovation through their new business models and processes, enabling them to potentially transform the global competitive landscape.
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(1993) · Cited by 7,856
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.220 · Cited by 6,542
Business model innovation: Opportunities and barriers
Chesbrough, H. (2010) · Long Range Planning · doi:10.1016/j.lrp.2009.07.010 · Cited by 3,850
Reinventing Your Business Model
Johnson, M., Christensen, C. M., & Kagermann, H. (2008) · Harvard business review · Cited by 2,379
Probabilistic machine learning and artificial intelligence
Ghahramani, Z. (2015) · Nature · doi:10.1038/nature14541 · Cited by 1,995
Foss, N. J., & Saebi, T. (2017) · Journal of Management · doi:10.1177/0149206316675927 · Cited by 1,907
The Netflix Recommender System: Algorithms, Business Value, and Innovation
Gomez-Uribe, C. A., & Hunt, N. (2016) · ACM Transactions on Management Information Systems · doi:10.1145/2843948 · Cited by 1,418
Business model innovation through trial-and-error learning
Sosna, M., Trevinyo-Rodríguez, R. N., & Velamuri, S. R. (2010) · Long Range Planning · doi:10.1016/j.lrp.2010.02.003 · Cited by 1,054
State-of-the-Art Speech Recognition with Sequence-to-Sequence Models
Chiu, C.-C., Sainath, T. N., Wu, Y., Prabhavalkar, R., Nguyen, P., Chen, Z., Kannan, A., Weiss, R. J., Rao, K., Gonina, E., et al. (2018) · 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2018.8462105 · Cited by 1,043
Strategic Development of Business Models
Wirtz, B. W., Schilke, O., & Ullrich, S. (2010) · Long Range Planning · doi:10.1016/j.lrp.2010.01.005 · Cited by 682
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Artificial Intelligence and Business Value: a Literature Review
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022) · Information Systems Frontiers · doi:10.1007/s10796-021-10186-w · Cited by 1,046
Artificial intelligence and industrial innovation: Evidence from German firm-level data
Rammer, C., Fernández, G. P., & Czarnitzki, D. (2022) · Research Policy · doi:10.1016/j.respol.2022.104555 · Cited by 489
Artificial intelligence (AI) in strategic marketing decision-making: a research agenda
Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., Laughlin, P., Machtynger, J., & Machtynger, L. (2020) · The Bottom Line · doi:10.1108/bl-03-2020-0022 · Cited by 363
Value creation and value capture for AI business model innovation: a three-phase process framework
Åström, J., Reim, W., & Parida, V. (2022) · Review of Managerial Science · doi:10.1007/s11846-022-00521-z · Cited by 195
Next-generation business models for artificial intelligence start-ups in the healthcare industry
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Metadata
- Authors
- Lee, J., Suh, T., Roy, D., & Baucus, M.
- Venue
- Journal of Open Innovation: Technology, Market, and Complexity
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 5
- Issue
- 3
- Pages
- 44
- ISSN
- 2199-8531 (ISSN-L)
- OpenAlex
- W2963377100
- Cited by
- 441
- References
- 24
- FWCI
- 40.73
- Type
- journal article
- Language
- en
- Open access
- gold
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- Lee, J., Suh, T., Roy, D., & Baucus, M. (2019). Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence. Journal of Open Innovation: Technology, Market, and Complexity. https://doi.org/10.3390/joitmc5030044
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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.
