Modelling and forecasting the diffusion of innovation - A 25-year review

@article{citeulike:2382493, abstract = {The wealth of research into modelling and forecasting the diffusion of innovations is impressive and confirms its continuing importance as a research topic. The main models of innovation diffusion were established by 1970. (Although the title implies that 1980 is the starting point of the review, we allowed ourselves to relax this constraint when necessary.) Modelling developments in the period 1970 onwards have been in modifying the existing models by adding greater flexibility in various ways. The objective here is to review the research in these different directions, with an emphasis on their contribution to improving on forecasting accuracy, or adding insight to the problem of forecasting. The main categories of these modifications are: the introduction of marketing variables in the parameterisation of the models; generalising the models to consider innovations at different stages of diffusions in different countries; and generalising the models to consider the diffusion of successive generations of technology. We find that, in terms of practical impact, the main application areas are the introduction of consumer durables and telecommunications. In spite of (or perhaps because of) the efforts of many authors, few research questions have been finally resolved. For example, although there is some convergence of ideas of the most appropriate way to include marketing mix-variables into the Bass model, there are several viable alternative models. Future directions of research are likely to include forecasting new product diffusion with little or no data, forecasting with multinational models, and forecasting with multi-generation models; work in normative modelling in this area has already been published.}, author = {Meade, Nigel and Islam, Towhidul }, booktitle = {Twenty five years of forecasting}, citeulike-article-id = {2382493}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.01.005}, journal = {International Journal of Forecasting}, keywords = {diffusion, forecasting}, number = {3}, pages = {519--545}, posted-at = {2008-02-20 13:59:32}, priority = {2}, title = {Modelling and forecasting the diffusion of innovation - A 25-year review}, url = {http://dx.doi.org/10.1016/j.ijforecast.2006.01.005}, volume = {22}, year = {2006} }

TY - JOUR ID - citeulike:2382493 L3 - citeulike-article-id:2382493 TI - Modelling and forecasting the diffusion of innovation - A 25-year review T2 - Twenty five years of forecasting JF - International Journal of Forecasting VL - 22 IS - 3 SP - 519 EP - 545 N2 - The wealth of research into modelling and forecasting the diffusion of innovations is impressive and confirms its continuing importance as a research topic. The main models of innovation diffusion were established by 1970. (Although the title implies that 1980 is the starting point of the review, we allowed ourselves to relax this constraint when necessary.) Modelling developments in the period 1970 onwards have been in modifying the existing models by adding greater flexibility in various ways. The objective here is to review the research in these different directions, with an emphasis on their contribution to improving on forecasting accuracy, or adding insight to the problem of forecasting. The main categories of these modifications are: the introduction of marketing variables in the parameterisation of the models; generalising the models to consider innovations at different stages of diffusions in different countries; and generalising the models to consider the diffusion of successive generations of technology. We find that, in terms of practical impact, the main application areas are the introduction of consumer durables and telecommunications. In spite of (or perhaps because of) the efforts of many authors, few research questions have been finally resolved. For example, although there is some convergence of ideas of the most appropriate way to include marketing mix-variables into the Bass model, there are several viable alternative models. Future directions of research are likely to include forecasting new product diffusion with little or no data, forecasting with multinational models, and forecasting with multi-generation models; work in normative modelling in this area has already been published. KW - diffusion KW - forecasting AU - Meade, Nigel AU - Islam, Towhidul PY - 2006/// UR - http://dx.doi.org/10.1016/j.ijforecast.2006.01.005 ER -