The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Diffusion of Innovation
Abstract
Diffusion of innovation is the process by which an innovative product spreads within a market. Several models have been proposed to describe this process. According to Rogers' model, the diffusion rate is influenced by product characteristics and diffusion progresses by word of mouth. Moore's crossing‐the‐chasm model focuses on differences between customer segments, and notes that word‐of‐mouth may not necessarily flow from early to later adopters. Both Rogers' and Moore's models offer managerial insights and implications. Diffusion models, such as Bass's model of durable goods sales, are often used to predict the rate of diffusion of innovative products into the market. Intriguing questions still remain regarding global diffusion of products.
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Cites
Stanton, B. F., & Rogers, E. M. (1963) · Journal of Farm Economics · doi:10.2307/1235767 · Cited by 6,675
A new product growth for model consumer durables
Bass, F. M. (1969) · Management Science · doi:10.1287/mnsc.15.5.215 · Cited by 6,008
A Propositional Inventory for New Diffusion Research
Gatignon, H., & Robertson, T. S. (1985) · Journal of Consumer Research · doi:10.1086/209021 · Cited by 1,209
Norton, J. A., & Bass, F. M. (1987) · Management Science · doi:10.1287/mnsc.33.9.1069 · Cited by 932
New Product Diffusion Models in Marketing: A Review and Directions for Research
Mahajan, V., Muller, E., & Bass, F. M. (1990) · Journal of Marketing · doi:10.2307/1252170 · Cited by 915
Why the Bass Model Fits without Decision Variables
Bass, F. M., Krishnan, T. V., & Jain, D. C. (1994) · Marketing Science · doi:10.1287/mksc.13.3.203 · Cited by 838
Morone, J. (1993) · Journal of Engineering and Technology Management · doi:10.1016/0923-4748(93)90075-t · Cited by 745
Fildes, R. (2003) · International Journal of Forecasting · doi:10.1016/s0169-2070(03)00016-5 · Cited by 387
Diffusion of New Products: Empirical Generalizations and Managerial Uses
Mahajan, V., Muller, E., & Bass, F. M. (1995) · Marketing Science · doi:10.1287/mksc.14.3.g79 · Cited by 385
A Meta-Analysis of Applications of Diffusion Models
Sultan, F., Farley, J. U., & Lehmann, D. R. (1990) · Journal of Marketing Research · doi:10.2307/3172552 · Cited by 325
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Social Media as Information Source: Recency of Updates and Credibility of Information
Westerman, D., Spence, P. R., & Van Der Heide, B. (2014) · Journal of Computer-Mediated Communication · doi:10.1111/jcc4.12041 · Cited by 708
The scaling of human interactions with city size
Schläpfer, M., Bettencourt, L. M. A., Grauwin, S., Raschke, M., Claxton, R., Smoreda, Z., West, G. B., & Ratti, C. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2013.0789 · Cited by 356
Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis
Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015) · Computers & Education · doi:10.1016/j.compedu.2014.11.022 · Cited by 333
Review on IT adoption: insights from recent technologies
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Metadata
- Authors
- Di Benedetto, C. A.
- Venue
- Wiley Encyclopedia of Management
- Publisher
- Wiley
- Published
- 2015-01-22
- Pages
- 1-5
- OpenAlex
- W2520915449
- Cited by
- 1,051
- References
- 12
- Type
- reference entry
- Language
- en
- Open access
- closed
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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.
