Fuzzy stage characteristic-preserving product life cycle modeling
Fuzzy Sets and Systems
Agent-Based Modelling — Intelligent Customer Relationship Management
BT Technology Journal
International Diffusion of Digital Mobile Technology: A Coupled-Hazard State-Based Approach
Information Technology and Management
Modeling citation behavior in management science journals
Information Processing and Management: an International Journal - Special issue: Informetrics
Advanced Engineering Informatics
The diffusion of mobile phones in India
Telecommunications Policy
Understanding early diffusion of digital wireless phones
Telecommunications Policy
Modified diffusion model with multiple products using a hybrid GA approach
Expert Systems with Applications: An International Journal
Goodness-of-fit testing in growth curve models: A general approach based on finite differences
Computational Statistics & Data Analysis
Using patent data for technology forecasting: China RFID patent analysis
Advanced Engineering Informatics
A stage characteristic-Preserving product life cycle modeling
Mathematical and Computer Modelling: An International Journal
Are there contagion effects in information technology and business process outsourcing?
Decision Support Systems
A Review for the Validation of Social Simulation on Artificial Social Organization
International Journal of Agent Technologies and Systems
Computers and Industrial Engineering
Diffusion of mobile handset features: Analysis of turning points and stages
Telecommunications Policy
The diffusion of mobile telephones: An empirical analysis for Peru
Telecommunications Policy
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The paper identifies 29 models that the literature suggests are appropriate for technological forecasting. These models are divided into three classes according to the timing of the point of inflexion in the innovation or substitution process. Faced with a given data set and such a choice, the issue of model selection needs to be addressed. Evidence used to aid model selection is drawn from measures of model fit and model stability. An analysis of the forecasting performance of these models using simulated data sets shows that it is easier to identify a class of possible models rather than the "best" model. This leads to the combining of model forecasts. The performance of the combined forecasts appears promising with a tendency to outperform the individual component models.