Technological forecasting is premised on a certain orderliness of the innovation process. Myriad studies of technological substitution, diffusion, and transfer processes have yielded conceptual models of what matters for successful innovation. Yet most technological forecasts key on limited empirical measures quite divorced from those innovation process models. We glean a number of concepts from various innovation models, then present an array of bibliometric measures that offer promise of operationalizing these concepts.Judicious combination of such bibliometrics with other forms of evidence offers an enriched form of technological forecasting that we name "innovation forecasting." This provides a good means to combine technological trends, mapping of technological interdependencies, and competitive intelligence to produce a viable forecast. We illustrate by assessing prospects for ceramic engine technologies.

No abstract

-Exploiting information resources, particularly diverse research & development databases, presents opportunities to enhance technology management. Many such databases [e.g., Science Citation Index, Business Index] offer useful index fields to help you access documents. However, these indexes sometimes fail to address your requirements effectively. We present an approach that allows you to extract and categorize desired information from particular datasets that lack effective indexing for your purposes. We illustrate for a U.S. Patents dataset on lightweight automotive materials.