Method limitations
- Statistical analysis approaches are suitable for identifying correlations between factors, but not causation
- Quantitative methods are unlikely to provide real depth of knowledge behind patent trends - for this they will have to be supported by causal exploration (case study descriptions and system dynamics analysis)
- Limited number of technologies considered in this study due to time taken to compile relevant data sets, including evidence of mode of adoption – further technologies should be included to increase confidence
- Currently time-consuming process to find evidence for literature classifications of technologies
- Technologies do not come from a truly representative cross-section of all industries, so possible that they are better representations of those industries included rather than a generalised result
- Risk that clustering techniques may struggle with small number of technologies considered
- Technologies have been selected based on where evidence is obtainable to indicate the mode of adoption followed
- Patent search results and records can vary to a large degree based on the database and search engines used, however overall trends once normalised should remain consistent with other studies
- Functional linear regression requires that all technology case studies have the same number of time samples – linear interpolation could introduce some errors where resampling has been used
Selected data sources
- Questel-Orbit: The Keywords search box searches terms in the title, abstract and key content of FamPat records. Searching the title and abstract applies to the entire FamPat collection. Searches in key content applies only to US, EP and PCT (English language publications only). The key content contains the independent claim, advantages and drawbacks and the patent object. The search is run on the data of all family members, subject to the limitations expressed above
- Web of Science: TBD
- International Energy Agency: TBD
- World Bank: TBD
- ICCT: TBD
- Eurostat: TBD
- International Data Corporation: TBD
- BIS Strategic Decisions: TBD
- IT Candor: TBD
- Ascend Fleets: TBD
- GAMA: TBD
- ITU: TBD
Building a technology classification model from Technology Life Cycle features
Technology adoption data collection and aggregation
TBD