Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email
The continuing evolution of the Internet as a major tool of communication has provided new sender/receiver applications such as email, blogs, forums and Voice over Internet Protocol. Many of these Internet-based communication applications have proven to be very popular amongst consumer groups. But w...
| Main Authors: | , , , |
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| Format: | Journal Article |
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Digital Ecosystems and Business Intelligence Institute
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/62482 |
| _version_ | 1848760859931705344 |
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| author | Wong, David Yap, K. Turner, Bradley Rexha, Nexhmi |
| author_facet | Wong, David Yap, K. Turner, Bradley Rexha, Nexhmi |
| author_sort | Wong, David |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The continuing evolution of the Internet as a major tool of communication has provided new sender/receiver applications such as email, blogs, forums and Voice over Internet Protocol. Many of these Internet-based communication applications have proven to be very popular amongst consumer groups. But when can we expect the diffusion of these new innovations to reach critical mass? The authors seek to determine when peak adoption will be reached for such Internet-based communication applications by examining the diffusion pattern of a mature application – that of email. The authors propose that Bass model parameter estimates for email can serve as an approximation of parameter estimates for other products within the domain of similar Internet-based communication applications. This study drew upon 10 years of diffusion data, and the Bass Model approach was utilised to classify individuals into adopter categories. The results revealed a q/p ratio of 50.7 for the adoption of email; indicating that the imitation effect is greater than the innovation effect in the diffusion of similar Internet-based communication technologies. It was also found that for such technologies, the peak of the noncumulative adoption curve can be expected in 5.4 years after launch. In the case of Twitter, for example, which was launched in September 2006, critical mass is predicted to occur in early-2012. |
| first_indexed | 2025-11-14T10:22:29Z |
| format | Journal Article |
| id | curtin-20.500.11937-62482 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:22:29Z |
| publishDate | 2011 |
| publisher | Digital Ecosystems and Business Intelligence Institute |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-624822018-02-01T05:23:57Z Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email Wong, David Yap, K. Turner, Bradley Rexha, Nexhmi Bass Model Communication Technology Innovation Adoption Diffusion The continuing evolution of the Internet as a major tool of communication has provided new sender/receiver applications such as email, blogs, forums and Voice over Internet Protocol. Many of these Internet-based communication applications have proven to be very popular amongst consumer groups. But when can we expect the diffusion of these new innovations to reach critical mass? The authors seek to determine when peak adoption will be reached for such Internet-based communication applications by examining the diffusion pattern of a mature application – that of email. The authors propose that Bass model parameter estimates for email can serve as an approximation of parameter estimates for other products within the domain of similar Internet-based communication applications. This study drew upon 10 years of diffusion data, and the Bass Model approach was utilised to classify individuals into adopter categories. The results revealed a q/p ratio of 50.7 for the adoption of email; indicating that the imitation effect is greater than the innovation effect in the diffusion of similar Internet-based communication technologies. It was also found that for such technologies, the peak of the noncumulative adoption curve can be expected in 5.4 years after launch. In the case of Twitter, for example, which was launched in September 2006, critical mass is predicted to occur in early-2012. 2011 Journal Article http://hdl.handle.net/20.500.11937/62482 Digital Ecosystems and Business Intelligence Institute restricted |
| spellingShingle | Bass Model Communication Technology Innovation Adoption Diffusion Wong, David Yap, K. Turner, Bradley Rexha, Nexhmi Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title | Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title_full | Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title_fullStr | Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title_full_unstemmed | Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title_short | Predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| title_sort | predicting the diffusion pattern of internet-based communication applications using bass model parameter estimates for email |
| topic | Bass Model Communication Technology Innovation Adoption Diffusion |
| url | http://hdl.handle.net/20.500.11937/62482 |