Method limitations

  1. Statistical analysis approaches are suitable for identifying correlations between factors,  but not causation
  2. 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)
  3. 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
  4. Currently  time-consuming process to find evidence for literature classifications of  technologies
  5. 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
  6. Risk  that clustering techniques may struggle with small number of technologies  considered
  7. Technologies  have been selected based on where evidence is obtainable to indicate the mode  of adoption followed
  8. 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
  9. 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

  1. 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
  2. Web  of Science:    TBD
  3. International  Energy Agency:    TBD
  4. World Bank:    TBD
  5. ICCT:    TBD
  6. Eurostat:    TBD
  7. International  Data Corporation:    TBD
  8. BIS  Strategic Decisions:    TBD
  9. IT Candor:    TBD
  10. Ascend  Fleets:    TBD
  11. GAMA:    TBD
  12. ITU:    TBD

Building a technology classification model from Technology Life Cycle features

Technology adoption data collection and aggregation

TBD