Skip to main content
View expanded cover

Research and Technology Management in the Electricity Industry pp 67–112Cite as

Technology Forecasting Methods

Part of the Green Energy and Technology book series (GREEN)

Abstract

This study analyzes the origins and historical evolution and revolution of technology forecasting methods, a discipline that identifies the concept, assumptions and evaluates technology forecasting techniques with significant relationship between them. A variety of technology forecasting approaches, initiated in the 1950s, with the pioneering researches carried out by US department of Defense, and some researchers of The RAND Corporation. For over 1960 years, numerous technology forecasting methods have been developed and recently become a distinct field of investigation of future world. Mostly revolutionary techniques would have been to combine different methods characterized by the several disciplines, such as exploratory, normative and intuitive approaches. This paper proposes the gap of the main techniques of technology forecasting, developed over the course of time, identifying their methodological origin. Some concluding remarks and lessons learned complete the research.

Keywords

  • Data Envelopment Analysis
  • Analytical Hierarchy Process
  • Technological Change
  • Delphi Method
  • Analytical Hierarchy Process Method

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4471-5097-8_4
  • Chapter length: 46 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   119.00
Price excludes VAT (USA)
  • ISBN: 978-1-4471-5097-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   159.99
Price excludes VAT (USA)
Hardcover Book
USD   179.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3

Notes

  1. 1.

    ‘Strategic research’ is defined as “basic research carried out with the expectation that it will produce a broad base of knowledge likely to form the background to the solution of recognized current or future practical problems” [108], p. 4.

  2. 2.

    ‘generic technology’ is defined as “a technology the exploitation of which will yield benefits for a wide range of sectors of the economy and/or society” [148], p. 51.

  3. 3.

    It measures the age of the closest prior art in technical and scientific papers or in patents.

  4. 4.

    It represent the number of patents in a given period to find an increasing or decreasing number of firms and inventors coming into a specific area.

  5. 5.

    It looks how the patents in an area are connected together by citations with a network analysis.

  6. 6.

    DYSMAP was developed by the System Dynamics Group at Bradford Management Center.

  7. 7.

    STELLA was introduced by isee systems (formerly High Performance Systems) in the late 1980s.

  8. 8.

    isee systems (formerly High Performance Systems Inc.) in USA developed iThink for business simulation in 1990.

  9. 9.

    Ventana Systems, Inc. created Vensim language and released Vensim in 1988.

  10. 10.

    Powersim studio was developed Powersim Software AS, based in Bergen Norway.

References

  1. Albright RE, Kappel TA (2003) Technology roadmapping: roadmapping the corporation. Research technology management, p 31

    Google Scholar 

  2. Anderson P, Tushman ML (1990) Technological discontinuities and dominant designs: a cyclical model of technological change. Adm Sci Q 35(4):604

    CrossRef  Google Scholar 

  3. Anderson P, Tushman ML (1990) Technological discontinuities and dominant designs: a cyclical model of technological change. Adm Sci Q 35(4):604–633

    CrossRef  Google Scholar 

  4. Anderson TR, Hollingsworth K, Inman OL (2001) Assessing the rate of change in the enterprise database system market over time using DEA. PICMET’01. Portland international conference on management of engineering and technology. Proceedings vol 1: book of summaries (IEEE Cat. No.01CH37199), pp 384–390

    Google Scholar 

  5. Anderson T, Daim T, Kim J (2008) Technology forecasting for wireless communication. Technovation 28(9):602–614

    CrossRef  Google Scholar 

  6. Applebaum AL (1920) A monthly application curve. J Pat Office Soc II:433

    Google Scholar 

  7. Ascher W (1979) Forecasting: an appraisal for policy-makers and planners. The Johns Hopkins University Press, p 256

    Google Scholar 

  8. Ayres RU (1969) Technological forecasting and long-range planning. McGraw-Hill, Inc., New York

    Google Scholar 

  9. Baldi L (1996) Industry roadmaps: the challenge of complexity. Microelectron Eng 34(1):9–26

    CrossRef  Google Scholar 

  10. Barker D, Smith DJH (1995) Technology foresight using roadmaps. Long Range Plan 28(2):21–28

    CrossRef  Google Scholar 

  11. Bass FM (1969) A new product growth for model consumer durables. Manage Sci 15(5):215–227

    MATH  CrossRef  Google Scholar 

  12. Bengisu M, Nekhili R (2006) Forecasting emerging technologies with the aid of science and technology databases. Technol Forecast Soc Chang 73(7):835–844

    CrossRef  Google Scholar 

  13. Blackman AW (1972) A mathematical model for trend forecasts. Technol Forecast Soc Chang 3:441–452

    CrossRef  Google Scholar 

  14. Blind K, Cuhls K, Grupp H (1999) Current foresight activities in. Technol Forecast Soc Chang 60(1):15–35

    CrossRef  Google Scholar 

  15. Blind K, Cuhls K, Grupp H (1999) Current foresight activities in Central Europe. Technol Forecast Soc Chang 60:15–35

    CrossRef  Google Scholar 

  16. Borjeson L, Hojer M, Dreborg K-H, Ekvall T, Finnveden G (2006) Scenario types and techniques: towards a user’s guide. Futures 38:723–739

    CrossRef  Google Scholar 

  17. Bower JL, Christensen CM (1995) Disruptive technologies: Catching the wave, Harvard business review

    Google Scholar 

  18. Bradfield R, Wright G, Burt G, Cairns G, Van Der Heijden K (2005) The origins and evolution of scenario techniques in long range business planning. Futures 37(8):795–812

    CrossRef  Google Scholar 

  19. Bradford SC (1934) Sources of information on specific subjects. Engineering 137(85)

    Google Scholar 

  20. Bray OH, Garcia ML (1997) Technology roadmapping: the integration of strategic and technology planning for competitiveness. Innovation in technology management. The key to global leadership. PICMET’97. IEEE, pp 25–28

    Google Scholar 

  21. Brenner MS (1996) Technology intelligence and technology scouting. Compet Intell Rev 7(3):20–27

    CrossRef  Google Scholar 

  22. Bright JR (1968) Technological forecasting for industry and government: methods and applications. Prentice-Hall Inc., Englewood Cliffs, p 484

    Google Scholar 

  23. Bright JR (1970) Evaluating signals of technological change. Harv Bus Rev 48:62

    Google Scholar 

  24. Brookes BC (1985) Sources of information on specific subjects by S.C. Bradford. J Inf Sci 10(4):173–175

    CrossRef  Google Scholar 

  25. Bruseberg A, Mcdonagh-Philp D (2001) New product development by eliciting user experience and aspirations. Int J Hum Comput Stud 55:435–452

    MATH  CrossRef  Google Scholar 

  26. Bunn DW, Salo AA (1993) Forecasting with scenarios. Eur J Oper Res 68(3):291–303

    CrossRef  Google Scholar 

  27. Callon M (1986) Pinpointing industrial invention: an exploration of quantitative methods for the analysis of patents: in mapping the dynamics of science and technology. Macmillan Press Ltd., London

    Google Scholar 

  28. Callon M, Courtial J-P, Turner W (1979) PROXAN: A visual display technique for scientific and technical problem networks. Second Workshop on the Measurement of R&D Output, Paris, France

    Google Scholar 

  29. Callon M, Courtial J-P, Turner WA, Bauin S (1983) From translations to problematic networks: an introduction to co-word analysis. Soc Sci Inf 22(2):191–235

    CrossRef  Google Scholar 

  30. Callon M, Courtial J-P, Laville F (1991) Co-word analysis as a tool for describing the network of interactions between basic and technological research: the case of Polymer Chemistry. Scientometrics 22(1):155–205

    CrossRef  Google Scholar 

  31. Campbell RS (1983) Patent trends as a technological forecasting tool. World Patent Inf 5(3):137–143

    CrossRef  Google Scholar 

  32. Carr LJ (1932) The patenting performance of 1,000 inventors during Ten years. Am J Sociol 37(4):569–580

    CrossRef  Google Scholar 

  33. Cattell JM (1903) Statistics of American Psychologists. Am J Psychol 14(3):310–328

    CrossRef  Google Scholar 

  34. Cetron MJ (1969) Technological forecasting: a practical approach. Gordon and Breach, Science, New York, London, Paris

    Google Scholar 

  35. Chaffin WW, Talley WK (1980) Individual stability in Delphi studies. Technol Forecast Soc Chang 16(1):67–73

    CrossRef  Google Scholar 

  36. Christensen CM, Overdorf M (2000) Meeting the challenge of disruptive change. Harvard business review, no. Mar–Apr

    Google Scholar 

  37. Churchman CW, Ackoff RL, Arnoff EL (1957) Introduction to operations research. Wiley, Oxford, England

    MATH  Google Scholar 

  38. Claxton JD, Ritchie JRB, Zaichkowsky J (1980) The nominal group technique: Its potential for consumer research. J Consumer Res 7(3):308–313

    CrossRef  Google Scholar 

  39. Coates FJ (1985) Foresight in Federal government policy making. Futures Res Quart 1(2)

    Google Scholar 

  40. Coates FJ, Mahaffie JB, Hines A (1994) Technological forecasting: 1970–1993. Technol Forecast Soc Chang 47:23–33

    CrossRef  Google Scholar 

  41. Coates V, Farooque M, Klavans R, Lapid K, Linstone HA, Pistorius C, Porter AL (2001) On the future of technological forecasting. Technol Forecast Soc Chang 67(1):1–17

    CrossRef  Google Scholar 

  42. Cuhls K (2003) From forecasting to foresight processes—new participative foresight activities in Germany. J Forecast 22(2–3):93–111

    CrossRef  Google Scholar 

  43. Cunningham SW, Porter AL, Newman NC (2006) Special issue on tech mining. Technol Forecast Soc Chang 73(8):915–922

    CrossRef  Google Scholar 

  44. Cunningham SW, Porter AL, Newman NC (2006) Special issue on tech mining. Technol Forecast Soc Chang 73(8):915–922

    CrossRef  Google Scholar 

  45. Daim T, Rueda G, Martin H, Gerdsri P (2006) Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technol Forecast Soc Chang 73(8):981–1012

    CrossRef  Google Scholar 

  46. Dalkey NC (1969) The Delphi method_an experimental study of group opinion

    Google Scholar 

  47. Dalkey N (1969) An experimental study of group opinion: the Delphi Method. Futures 1(5):408–426

    CrossRef  Google Scholar 

  48. de Price DJS (1965) Networks of scientific papers. Science 149(3683):510–515

    Google Scholar 

  49. Delbecq AL, Ven AHVD (1971) A group process model for problem identification and program planning. J Appl Behav Sci 7(4):466

    CrossRef  Google Scholar 

  50. Delbecq AL, Van de Ven AH, Gustafson DH (1975) Group techniques for program planning: a guide to nominal group and Delphi processes. Foresman and Company, Glenview, Scott

    Google Scholar 

  51. Donegan HA, Dodd FJ, McMaster TBM (1992) A new approach to AHP decision-making. Statistician 41(3):295–302

    CrossRef  Google Scholar 

  52. Dosi G (1982) Technological paradigms and technological trajectories. Res Policy 11(3):147–162

    CrossRef  Google Scholar 

  53. Easingwood C, Mahajan V, Muller E (1981) A nonsymmetric responding logistic model for forecasting technological substitution. Technol Forecast Soc Chang 20(3):199–213

    CrossRef  Google Scholar 

  54. Eerola A, Jørgensen BH (2002) Technology foresight in the Nordic Countries

    Google Scholar 

  55. Ellis P, Hepburn G, Oppenheim C (1978) Studies on patent citation networks. J Documentation 34(1):12–20

    CrossRef  Google Scholar 

  56. Enzer S (1970) A case study using forecasting as a decision-making aid. Futures 2(4):341–362

    CrossRef  Google Scholar 

  57. Enzer S (1971) Delphi and cross-impact techniques: an effective combination for systematic futures analysis. Futures, pp 48–61

    Google Scholar 

  58. Enzer S (1980) Interax—an interactive model for studying future business environments: Part I. Technol Forecast Soc Chang 17(2):141–159

    CrossRef  Google Scholar 

  59. Ernst H (2003) Patent information for strategic technology management. World Patent Inf 25(3):233–242

    MathSciNet  CrossRef  Google Scholar 

  60. Fayyad U, Piatetsky-shapiro G, Smyth P (1996) From data mining to knowledge discovery in databases. AI Magazine 17(3):37–54

    Google Scholar 

  61. Fayyad U, Piatetsky-Shapiro G, Smyth P (1996) The KDD process for extracting useful knowledge from volumes of data. Commun ACM 39(11):27–34

    CrossRef  Google Scholar 

  62. Feldman R, Dagan I (1995) KDT—knowledge discovery in texts. In: The first international conference on knowledge discovery from databases

    Google Scholar 

  63. Feldman R, Dagan I, Hirsh H (1998) Mining text using keyword distributions. J Intell Inf Syst 10:281–300

    CrossRef  Google Scholar 

  64. Fisher JC, Pry RH (1971) A simple substitution model of technological change. Technol Forecast Soc Chang 88(3):75–88

    CrossRef  Google Scholar 

  65. Fontana R, Nuvolari A, Verspagen B (2008) Mapping technological trajectories as patent citation networks: an application to data communication standards. 44(166):0–57

    Google Scholar 

  66. Foray D (1997) The dynamic implications of increasing returns: technological change and path dependent inefficiency. Int J Ind Organ 15(6):733–752

    CrossRef  Google Scholar 

  67. Forrester JW (1961) Industrial dynamics. Wright-Allen Press, Cambridge

    Google Scholar 

  68. Forrester JW (1968) Industrial dynamics-after the first decade. Manage Sci 14(7):398–415

    CrossRef  Google Scholar 

  69. Forrester JW (1969) Urban dynamics. MIT Press, Cambridge, p 285

    Google Scholar 

  70. Forrester JW (1980) Information sources for modeling the national economy. J Am Stat Assoc 75(371):555–566

    CrossRef  Google Scholar 

  71. Forrester JW (1991) System dynamics and the lessons of 35 years

    Google Scholar 

  72. Forrester JW (1992) System dynamics, systems thinking, and soft OR. Syst Dyn Rev 10(2):1–14

    Google Scholar 

  73. Foster MJ (1993) Scenario planning for small businesses. Long Range Plan 26(1):123–129

    CrossRef  Google Scholar 

  74. Frawley WJ, Piatetsky-shapiro G, Matheus CJ (1991) Knowledge discovery in databases: an overview. In: Knowledge discovery in databases. MIT Press, Cambridge, pp 1–27

    Google Scholar 

  75. Friedman L, Sinuany-stern Z (1997) Scaling units via the canonical correlation analysis in the DEA context. Eur J Oper Res 100:629–637

    MATH  CrossRef  Google Scholar 

  76. Galvin R (1998) Science roadmap. Science 280(5365):803

    CrossRef  Google Scholar 

  77. Garcia ML (1997) Introduction to technology roadmapping: the semiconductor industry association’ s technology roadmapping process. Sandia National Laboratories

    Google Scholar 

  78. Garfield E (1966) Patent citation indexing and the Notions of Novelty, Similarity, and Relevance. J Chem Documentation 6:63

    CrossRef  Google Scholar 

  79. Gerdsri N, Kocaoglu DF (2007) Applying the analytic hierarchy process (AHP) to build a strategic framework for technology roadmapping. Math Comp Model 46(7–8):1071–1080

    CrossRef  Google Scholar 

  80. Geurs K, Wee BV (2004) Backcasting as a tool for sustainable transport policy making: the environmentally sustainable transport study in the Netherlands. EJTIR 1:47–69

    Google Scholar 

  81. Gilfillan SC (1935) Sociology of invention. Follett Publishing Co, Chicago, pp 113–119

    Google Scholar 

  82. Gilfillan SC (1952) The prediction of technical change. Rev Econ Stat 34(4):368–385

    CrossRef  Google Scholar 

  83. Glas FD (1986) Fiction and bibliometrics: analyzing a Publishing House’s Stocklist. Libri 36(1):40–64

    Google Scholar 

  84. Gordon TJ (1969) Cross-impact matrices: an illustration of their use for policy analysis. Futures 1(6):527–531

    CrossRef  Google Scholar 

  85. Gordon TJ (1994) Trend impact aanalysis. Futures research methodology

    Google Scholar 

  86. Gordon TJ, Hayward H (1968) Initial experiments with the cross impact matrix method of forecasting. Futures 1(2):100–116

    CrossRef  Google Scholar 

  87. Gordon TJ, Stover J (1976) Using perceptions and data about the future to improve the simulation of complex systems. Technol Forecast Soc Chang 9(1–2):191–211

    CrossRef  Google Scholar 

  88. Gordon TJ, Becker HS, Gerjuoy H (1974) Trend impact analysis: a new forecasting tool. Futures Group, Glastonbury, Conn

    Google Scholar 

  89. Gorn MH (1988) Harnessing the genie: science and technology forecasting for Air Force 1944–1986. U.S. Government Printing Office, Washington

    Google Scholar 

  90. Griliches Z (1957) Hybrid corn: an exploration in the economics of technological change. Econometrica 25(4):501–522

    CrossRef  Google Scholar 

  91. Griliches Z (1990) Patent statistics as economic indicators: a survey. J Econ Lit 28(4):1661–1707

    Google Scholar 

  92. Groenveld P (1997) Roadmapping integrates business and technology. Res Technol Manage 40(5):48–55

    Google Scholar 

  93. Gross PLK, Gross EM (1927) College libraries and chemical education. Science 66(1713):385–389

    CrossRef  Google Scholar 

  94. Grupp H, Linstone HA (1999) National technology foresight activities around the globe: resurrection and new paradigms. Technol Forecast Soc Chang 60:85–94

    CrossRef  Google Scholar 

  95. Harrell S, Seidel T, Fay B (1996) The national technology roadmap for semiconductors and SEMATECH future directions. Microelectron Eng 30

    Google Scholar 

  96. Harvey AC (1984) Time series forecasting based on the logistic curve. Oper Res Soc 35(7):641–646

    MATH  Google Scholar 

  97. Healey P, Rothman H, Hoch PK (1986) An experiment in science mapping for research planning. Res Policy 15(5):233–251

    CrossRef  Google Scholar 

  98. Helmer O, Rescher N (1959) On the epistemology of the inexact sciences, vol. 6, no. 1, pp 25–52

    Google Scholar 

  99. Henrich TR, Greene TJ (1991) Using the nominal group technique to elicit roadblocks to an MRP II implementation. Comput Ind Eng 21(1–4):335–338

    CrossRef  Google Scholar 

  100. Heraud J, Cuhls K (1999) Current foresight activities in France, Spain, and Italy. Technol Forecast Soc Chang 60:55–70

    CrossRef  Google Scholar 

  101. Hojer M, Mattsson L-G (2000) Determinism and backcasting in future studies. Futures 32:613–634

    CrossRef  Google Scholar 

  102. Hood WW, Wilson CS (2001) The literature of bibliometrics, scientometrics, and informetrics. Scientometrics 52(2):291–314

    CrossRef  Google Scholar 

  103. Huang IB, Keisler J, Linkov I (2011) Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Sci Total Environ 409(19):3578–3594

    CrossRef  Google Scholar 

  104. Huss WR (1988) A move toward scenario analysis. Int J Forecast 4:377–388

    CrossRef  Google Scholar 

  105. Huss WR, Honton EJ (1987) Scenario planning- what style should you use? Long Range Plan 20(4):21–29

    CrossRef  Google Scholar 

  106. Inman OL (2004) Technology forecasting using data envelopment analysis. Portland State University

    Google Scholar 

  107. Inman O, Anderson T, Harmon R (2006) Predicting U.S. Jet Fighter Aircraft introductions from 1944 to 1982: a dogfight between regression and TFDEA☆. Technol Forecast Soc Chang 73(9):1178–1187

    CrossRef  Google Scholar 

  108. Irvine J, Martin BR (1984) Foresight in science: picking the winners. Frances Pinter, London and Dover

    Google Scholar 

  109. Jager-Waldau A (2004) R&D roadmap for PV. Thin Solid Films 451–452:448–454

    CrossRef  Google Scholar 

  110. Jansen L (2003) The challenge of sustainable development. J Clean Prod 11(3):231–245

    CrossRef  Google Scholar 

  111. Jantsch E (1967) Technological forecasting in perspective: a framework for technological forecasting, its techniques and organization

    Google Scholar 

  112. Jefferson M (1929) The geographic distribution of inventiveness. Geogr Rev 19(4):649–661

    CrossRef  Google Scholar 

  113. Johnson EH (1970) Some computational aspects of cross impact matrix forecasting. Futures, pp 123–131

    Google Scholar 

  114. Kahn H, Mann I (1957) Techniques of systems analysis

    Google Scholar 

  115. Kahn H, Wiener AJ (1967) The year 2000: a framework for speculation on the next thirty- three years. Macmillan, New York

    Google Scholar 

  116. Kajikawa Y, Abe K, Noda S (2006) Filling the gap between researchers studying different materials and different methods: a proposal for structured keywords. J Inf Sci 32(6):511–524

    CrossRef  Google Scholar 

  117. Kajikawa Y, Yoshikawa J, Takeda Y, Matsushima K (2008) Tracking emerging technologies in energy research: Toward a roadmap for sustainable energy. Technol Forecast Soc Chang 75(6):771–782

    CrossRef  Google Scholar 

  118. Kappel TA (2001) Perspectives on roadmaps: how organizations talk about the future. J. Prod. Innov. Manage. 18(1):39–50

    CrossRef  Google Scholar 

  119. Karki MMS, Krishnan KS (1997) Patent citation analysis: a policy analysis tool. World Patent Inf 19(4):269–272

    CrossRef  Google Scholar 

  120. Kessler MM (1963) Bibliographic coupling extended in time: ten case histories. Inf Storage Retr 1:169–187

    CrossRef  Google Scholar 

  121. Kessler MM (1963) An experimental study of bibliographic coupling between technical papers. IEEE Trans Inf Theory 9(1):49

    CrossRef  Google Scholar 

  122. Kim S-B, Whang K-S (1993) Forecasting the capabilities of the Korean Civil Aircraft Industry. Omega 21(1):91–98

    CrossRef  Google Scholar 

  123. Könnölä T, Brummer V, Salo A (2007) Diversity in foresight: insights from the fostering of innovation ideas. Technol Forecast Soc Chang 74(5):608–626

    CrossRef  Google Scholar 

  124. Kostoff RN (1991) Database tomography: multidisciplinary research thrusts from co-word analysis. In: Portland international conference on management of engineering and technology, pp 27–31

    Google Scholar 

  125. Kostoff RN (1994) Database tomography: Origins and duplications. Compet Intell Rev (5)

    Google Scholar 

  126. Kostoff R (2004) Disruptive technology roadmaps. Technol Forecast Soc Chang 71(1–2):141–159

    CrossRef  Google Scholar 

  127. Kostoff RN, Schaller RR (2001) Science and technology roadmaps. IEEE Trans Eng Manage 48(2):132–143

    CrossRef  Google Scholar 

  128. Kostoff RN, Eberhart HJ, Toothman DR (1997) Database tomography for information retrieval. J Inf Sci 23(4):301–311

    CrossRef  Google Scholar 

  129. Kostoff RN, Eberhart HJ, Toothman DR (1998) Database tomography for technical intelligence: a roadmap of the near-earth space science and technology literature. Inf Process Manage 34(1):69–85

    CrossRef  Google Scholar 

  130. Kostoff RN, Toothman DR, Eberhart HJ, Humenik JA (2001) Text mining using database tomography and bibliometrics: a review. Technol Forecast Soc Chang 68:223–253

    CrossRef  Google Scholar 

  131. Kuhn TS (1970) The structure of scientific revolutions, 2nd edn, vol. II, no. 2. The University of Chicago, USA

    Google Scholar 

  132. Kuwahara T (1999) Technology forecasting activities in Japan. Technol Forecast Soc Chang 60(1):5–14

    CrossRef  Google Scholar 

  133. Lenz RC Jr (1962) Technological forecasting, US Air Force, Cameron station, Alexandria, Virginia

    Google Scholar 

  134. Leufkens H, Haaijer-Ruskamp F, Bakker A, Dukes G (1994) Scenario analysis of the future of medicines. BMJ (Clin Res ed) 309(29):1137–1140

    CrossRef  Google Scholar 

  135. Levary RR, Han D (1995) Choosing a technological forecasting method. Ind Manage 1(37)

    Google Scholar 

  136. Levenbach H, Reuter BE (1976) Forecasting trending time series with relative growth rate models. Technometrics 18(3):261–272

    MATH  CrossRef  Google Scholar 

  137. Linstone HA (1999) TFSC : 1969–1999. Technol Forecast Soc Chang 62:1–8

    CrossRef  Google Scholar 

  138. Linstone HA, Turoff M (2002) The Delphi method: techniques and applications

    Google Scholar 

  139. Linton J (2004) Determining demand, supply, and pricing for emerging markets based on disruptive process technologies. Technol Forecast Soc Chang 71(1–2):105–120

    MathSciNet  CrossRef  Google Scholar 

  140. Losiewicz P, Oard DW, Kostoff RN (2000) Textual data mining to support science and technology management. J Intell Inf Syst 15:99–119

    CrossRef  Google Scholar 

  141. Lotka AJ (1926) The frequency distribution of scientific productivity. J Wash Acad Sci 16:317–323

    Google Scholar 

  142. Lovell MC (1983) Data mining. Rev Econ Stat 65(1):1–12

    CrossRef  Google Scholar 

  143. Luna-Reyes LF, Andersen DL (2003) Collecting and analyzing qualitative data for system dynamics: methods and models. Syst Dyn Rev 19(4):271–296

    CrossRef  Google Scholar 

  144. Mansfield E (1961) Technical change and the rate of imitation. Econometrica 29(4):741–766

    MATH  CrossRef  Google Scholar 

  145. Martin BR (1995) Foresight in science and technology. Technol Anal Strategic Manage 7(2)

    Google Scholar 

  146. Martin BR (2001) Technology foresight in a rapidly globalizing economy, no. April. UNIDO, Vienna, Austria

    Google Scholar 

  147. Martin BR (2010) The origins of the concept of ‘foresight’ in science and technology: an insider’s perspective. Technol Forecast Soc Chang 77(9):1438–1447

    CrossRef  Google Scholar 

  148. Martin BR, Irvine J (1993) Research foresight and the exploitation of the science base. Science Policy Research Unit, London: Brighton

    Google Scholar 

  149. Martin BR, Johnston R (1999) Technology foresight for wiring up the national innovation system experiences in Britain, Australia, and New Zealand. Technol Forecast Soc Chang 60:37–54

    CrossRef  Google Scholar 

  150. Martin WT, Sharp JM (1973) Reverse factor analysis: a modification of relevance tree techniques. Technol Forecast Soc Chang 4:355–373

    CrossRef  Google Scholar 

  151. Martino JP (1969) Forecasting the progress of technology. Air University Review

    Google Scholar 

  152. Martino JP (1980) Technological forecasting-an overview. Manage Sci 26(1):28–33

    CrossRef  Google Scholar 

  153. Martino JP (1993) Techology forecasting for decision making, vol. 3, 3rd edn, McGraw-Hill, Inc.

    Google Scholar 

  154. Martino JP (2003) A review of selected recent advances in technological forecasting. Technol Forecast Soc Chang 70(8):719–733

    CrossRef  Google Scholar 

  155. Meade N, Islam T (1998) Technological forecasting model stability, and model selection, models combining. Manage Sci 44(8):1115–1130

    MATH  CrossRef  Google Scholar 

  156. Mietzner D, Reger G (2005) Advantages and disadvantages of scenario approaches for strategic foresight. Int J Technol Intell Plann 1(2):220

    CrossRef  Google Scholar 

  157. Miles I (2010) The development of technology foresight: a review. Technol Forecast Soc Chang 77(9):1448–1456

    CrossRef  Google Scholar 

  158. Miller D, Shewchuk R, Elliot TR, Richards S (2000) Nominal group technique: a process for identifying diabetes self-care issues among patients and caregivers. Diabetes Educator 26(2):305–314

    CrossRef  Google Scholar 

  159. Millett SM (1988) How scenarios trigger strategic thinking. Long Range Plan 21(5):61–68

    CrossRef  Google Scholar 

  160. Millett SM, Honton EJ (1991) A manager’s guide to technology forecasting and strategy analysis methods. Battelle Press, Columbus, Ohio

    Google Scholar 

  161. Mishra S, Deshmukh SG, Vrat P (2002) Matching of technological forecasting technique to a technology. Technol Forecast Soc Chang 69(1):1–27

    CrossRef  Google Scholar 

  162. Mishra S, Deshmukh SG, Vrat P (2002) Matching of technological forecasting technique to a technology. Technol Forecast Soc Chang 69:1–27

    CrossRef  Google Scholar 

  163. Moed HF, Glanzel W, Schmoch U (eds) (2005) Handbook of quantitative science and technology research: the use of publication and patent statistics in studies of S&T systems. Kluwer Academic Publishers, New York, Boston, Dordrecht, London, Moscow, p 785

    Google Scholar 

  164. Molas-Gallart J, Barre R, Zappacosta M, Gavigan J (2002) A trans-national analysis of results and implications of industrially-oriented technology foresight studies, no. Feb. European Commission, p 59

    Google Scholar 

  165. Morris S, DeYong C, Wu Z, Salman S, Yemenu D (2002) DIVA: a visualization system for exploring document databases for technology forecasting. Comput Ind Eng 43(4):841–862

    CrossRef  Google Scholar 

  166. Narin F (1994) Patent bibliometrics. Scientometrics 30(1):147–155

    CrossRef  Google Scholar 

  167. Narin F, Olivastro D, Stevens KA (1994) Bibliometrics/theory, practice and problems. Eval Rev 18(1):65–76

    CrossRef  Google Scholar 

  168. National Resources Committee. (1937) Technological trends and national policy, including the social implications of new inventions, Washington

    Google Scholar 

  169. Novaky E, Lorant K (1978) A method for the analysis of interrelationships between mutually connected events : a cross-impact method. Technol Forecast Soc Chang 12:201–212

    CrossRef  Google Scholar 

  170. O’Connor TJ (1971) A methodology for analogies. Technol Forecast Soc Chang 2:289–309

    CrossRef  Google Scholar 

  171. Pavitt K (1985) Patent statistics as indicators of innovative activities: possibilities and problems. Scientometrics 7(1–2):77–99

    CrossRef  Google Scholar 

  172. Pavitt K (1988) Uses and abuses of patent statistics, Handbook of Quantitative Studies of Science and Technology. North Holland: Elsevier Publishers, Amsterdam

    Google Scholar 

  173. Peters HPF, Hartmann D, Raan AFJV (1987) Monitoring advances in chemical engineering: a multi-database approach. Research report to the Netherlands Technological Research Council, Report SSU-87-01, Leiden

    Google Scholar 

  174. Phaal R, Muller G (2009) An architectural framework for roadmapping: towards visual strategy. Technol Forecast Soc Chang 76(1):39–49

    CrossRef  Google Scholar 

  175. Phaal R, Farrukh C, Probert D (2001) Technology roadmapping: linking technology resources to business objectives. University of Cambridge, pp 1–18

    Google Scholar 

  176. Phaal R, Farrukh CJP, Probert DR (2004) Technology roadmapping—a planning framework for evolution and revolution. Technol Forecast Soc Chang 71(1–2):5–26

    CrossRef  Google Scholar 

  177. Phaal R, Farrukh C, Probert D (2004) Customizing roadmapping. Res Technol Manage 47(2):26

    Google Scholar 

  178. Porter AL (1999) Technology forecasting: an empirical perspective. Technol Forecast Soc Chang 28:19–28

    CrossRef  Google Scholar 

  179. Porter AL (2005) Tech mining. Compet Intell Mag 8(1):30–37

    Google Scholar 

  180. Porter AL (2009) Tech mining for future-oriented technology analysis

    Google Scholar 

  181. Porter AL, Detampel MJ (1995) Technology opportunities analysis. Technol Forecast Soc Change 49:237–255

    Google Scholar 

  182. Porter AL, Roper AT, Mason TW, Rossini FA, Banks J, Wiederholt BJ (1991) Forecasting and management of technology. Wiley, New York, Chichester, Brisbane, Toronto, Singapore, p 448

    Google Scholar 

  183. Pritchard A (1969) Statistical bibliography or bibliometrics? J Documentation 25:348–349

    Google Scholar 

  184. Probert D, Radnor M (2003) Frontier experiences from industry-academia consortia: corporate roadmappers create value with product and technology roadmaps. Res Technol Manage 46(2):27

    Google Scholar 

  185. Quinn JB (1967) Technological forecasting, Harvard business review

    Google Scholar 

  186. Quist J, Vergragt PJ (2003) Backcasting for industrial transformations and system innovations towards sustainability: is it useful for Governance? In: The 2003 Berlin conference on the Human dimensions of global environmental change, no. pp 1–26

    Google Scholar 

  187. Quist J, Vergragt PJ (2006) Past and future of backcasting: the shift to stakeholder participation and a proposal for a methodological framework. Futures 38(9):1027–1045

    CrossRef  Google Scholar 

  188. Raan AFJ, Peters HPF (1989) Dynamics of a scientific field analysed by co-subfield structures. Scientometrics 15(5–6):607–620

    CrossRef  Google Scholar 

  189. Reekie WD (1973) Patent data as a guide to industrial activity. Res Policy 2(3):246–264

    CrossRef  Google Scholar 

  190. Richardson GP (1996) Problems for the future of system dynamics. Syst Dyn Rev 12(2):141–157

    CrossRef  Google Scholar 

  191. Rip A, Courtial J-P (1984) Co-word maps of biotechnology: an example of cognitive scientometrics. Scientometrics 6(6):381–400

    CrossRef  Google Scholar 

  192. Ritchey T (1998) Fritz zwicky, Morphologie and policy analysis

    Google Scholar 

  193. Ritchey T (1998) Fritz zwicky, Morphologie and Policy Analysis. In: 16th Euro conference on operational analysis

    Google Scholar 

  194. Ritchey T (2006) Problem structuring using computer-aided morphological analysis. J Oper Res Soc 57(7):792–801

    MATH  CrossRef  Google Scholar 

  195. Ritchey T (2011) Wicked problems—social messes: decision support modelling with morphological analysis, p 106

    Google Scholar 

  196. Roberts EB (1969) Exploratory and normative technological forecasting: a critical appraisal. Technol Forecast 1(2):113

    CrossRef  Google Scholar 

  197. Robertson TB (1923) The chemical basis of growth and senescenc. J. B. Lippincott Company, Philadelphia and London

    Google Scholar 

  198. Robinson JB (1982) Backing into the future: on the methodological and institutional biases embedded in energy supply and demand forecasting. Technol Forecast Soc Chang 21(3):229–240

    CrossRef  Google Scholar 

  199. Robinson JB (1982) Energy backcasting: a proposed method of policy analysis. Energy Policy 10:337–344

    CrossRef  Google Scholar 

  200. Robinson JB (1990) Futures under glass: a recipe for people who hate to predict. Futures

    Google Scholar 

  201. Rohrbaugh J (1981) Improving the quality of group judgment: social judgment analysis and the nominal group technique. Organ Behav Hum Perform 28(2):272–288

    CrossRef  Google Scholar 

  202. Roorda N (2001) Backcasting the future. Int J Sustain High Educ 2(1):63–69

    CrossRef  Google Scholar 

  203. Rubin G, De Wit N, Meineche-Schmidt V, Seifert B, Hall N, Hungin P (2006) The diagnosis of IBS in primary care: consensus development using nominal group technique. Fam Pract 23(6):687–692

    CrossRef  Google Scholar 

  204. Saaty TL (1977) A scaling method for priorities in Hierarchical Structures. J Math Psychol 15:234–281

    MathSciNet  MATH  CrossRef  Google Scholar 

  205. Salo A, Gustafsson T, Ramanathan R (2003) Multicriteria methods for technology foresight. J Forecast 22:235–255

    CrossRef  Google Scholar 

  206. Saritas O, Oner MA (2004) Systemic analysis of UK foresight results Joint application of integrated management model and roadmapping. Technol Forecast Soc Chang 71(1–2):27–65

    CrossRef  Google Scholar 

  207. Scherer FM (1965) Firm size, market structure, opportunity, and the output of patented inventions. Am Econ Rev 55(5):1097–1125

    Google Scholar 

  208. Schiffel D, Kitti C (1978) Rates of invention: international patent comparisons. Res Policy 7:324–340

    CrossRef  Google Scholar 

  209. Schmookler J (1954) The level of inventive activity. Rev Econ Stat 36(2):183–190

    CrossRef  Google Scholar 

  210. Schnaars SP (1984) Situational factors affecting forecast accuracy. J Mark Res 21(3):290–297

    CrossRef  Google Scholar 

  211. Schnaars SP (1987) How to develop and use scenarios. Long Range Plan 20(1):105–114

    CrossRef  Google Scholar 

  212. Schnaars SP (1989) Megamistakes: forecasting and the myth of rapid technological change. Free Press, New York, London, p 202

    Google Scholar 

  213. Schoemaker PJH (1993) Multiple scenario development: its conceptual and behavioral foundation. Strateg Manag J 14(3):193–213

    CrossRef  Google Scholar 

  214. Schoemaker PJH (1995) Scenario planning: a tool for strategic thinking. Sloan management review, Winter

    Google Scholar 

  215. Schon Donald A (1967) Forecasting and technological forecasting. Daedalus 96(3):759–770

    Google Scholar 

  216. Schwartz P (1991) The art of the long view: planning for the future in an Uncertain World. Doubleday, a division of Random House, Inc., New York, p 272

    Google Scholar 

  217. Seidel AH (1949) Commentaria citation system for patent office. J Pat Office Soc 31

    Google Scholar 

  218. Sharif MN, Islam MN (1980) The Weibull distribution as a general model for forecasting technological change. Technol Forecast Soc Chang 18(3):247–256

    CrossRef  Google Scholar 

  219. Shin T, Hong S, Grupp H (1999) Technology foresight activities in Korea and. Technol Forecast Soc Chang 60:71–84

    CrossRef  Google Scholar 

  220. Silberglitt R, Hove A, Shulman P (2003) Analysis of US energy scenarios: meta-scenarios, pathways, and policy implications. Technol Forecast Soc Chang 70(4):297–315

    CrossRef  Google Scholar 

  221. Sink DS (1983) Using the nominal group technique effectively. Natl Prod Rev 2(2):173

    CrossRef  Google Scholar 

  222. Small H (1973) Co-citation in the scientific literature: a new measure of the relationship between two document. J Am Soc Inf Sci

    Google Scholar 

  223. Small H, Griffith BC (1974) The structure of scientific literatures i: identifying and graphing specialties. Sci Stud 4(1):17–40

    CrossRef  Google Scholar 

  224. Stafford AB (1952) Is the rate of invention declining? Chic J 57(6):539–545

    Google Scholar 

  225. Stover J (1975) The use of probabilistic system dynamics an analysis of national development policies: a study of the economic growth and income distribution in Uruguay. In: Proceedings of the 1975 summer computer simulation conferences

    Google Scholar 

  226. Strauss JD, Radnor M (2004) Roadmapping for dynamic and uncertain environments. Research technology management, pp 51–58

    Google Scholar 

  227. Stuart TE, Podolny JM (1996) Local search and the evolution of technological capabilities. Strateg Manag J 17:21–38

    CrossRef  Google Scholar 

  228. Swager WL (1972) Strategic planning I: The roles of technological forecasting. Technol Forecast Soc Chang 4:85–99

    CrossRef  Google Scholar 

  229. Swedish Morphological Society (2004) MA/Carma: advanced computer support for general morphological analysis. [Online]. Available. www.swemorph.com/pdf/macasper1.pdf

  230. T. L. Saaty, The Analytic Hierarchy Process. McGraw-Hill, Inc., 1980

    Google Scholar 

  231. Tague-sutcliffe J (1992) An introduction to informetrics among information scientists in Western Europe and North America, the term informetrics has become common only in the past five years, as a general field of study which includes the earlier fields of bibliometrics and. Inf Proc Manage 28(I):1–3

    Google Scholar 

  232. TFAMW Group (2004) Technology futures analysis: toward integration of the field and new methods. Technol Forecast Soc Change 71(3):287–303

    Google Scholar 

  233. The Bartlett School of Planning and Halcrow Group Ltd (2006) Visioning and backcasting for UK transport policy (VIBAT)

    Google Scholar 

  234. Tijssen JWR (1992) A quantitative assessment of interdisciplinary structures in science and technology: co-classification analysis of energy research. Res Policy 21:27–44

    CrossRef  Google Scholar 

  235. Tijssen JWR (1992) A quantitative assessment of interdisciplinary structures in science and technology : Co-classification analysis of energy research *. Res Policy 21:27–44

    CrossRef  Google Scholar 

  236. Trajtenberg M (1990) A penny for your quotes: patent citations and the value of innovations. Rand J Econ 21(1):172–187

    CrossRef  Google Scholar 

  237. Twiss BC (1992) Managing technological innovation, 4th edn. Longman, London, New York, p 309

    Google Scholar 

  238. Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29

    MathSciNet  MATH  CrossRef  Google Scholar 

  239. van der Heijden K (1996) Scenarios: the art of strategic conversation. Wiley, Chichester, New York, Brisbane, Toronto, Singapore

    Google Scholar 

  240. van der Meulen B (1999) The impact of foresight on environmental science and technology policy in the Netherlands. Futures 31(1):7–23

    CrossRef  Google Scholar 

  241. van Notten PWF, Rotmans J, van Asselt MBA, Rothman DS (2003) An updated scenario typology. Futures 35(5):423–443

    CrossRef  Google Scholar 

  242. Vanston JH (1996) Technology forecasting: A practical tool for rationalizing the R & D process, New telecom quarterly, pp 57–62

    Google Scholar 

  243. Ven AHVD, Delbecq AL (1972) The nominal group as a research instrument for exploratory health studies. Am J Public Health 62(3):337–342

    CrossRef  Google Scholar 

  244. Von Goethe JW (1988) Scientific studies. Suhrkamp Publishers, New York

    Google Scholar 

  245. Wack P (1985) Scenarios: uncharted waters ahead. Harvard business review

    Google Scholar 

  246. Wack P (1985) Scenarios: shooting the rapids. Harvard business review, pp 139–151

    Google Scholar 

  247. Wells R, Phaal R, Farrukh C, Probert D (2004) Technology roadmapping for a service organization. Research technology management

    Google Scholar 

  248. Willyard CH, McClees CW (1987) Motorola’s technology roadmap process. Research Management, pp 13–19

    Google Scholar 

  249. Winsor CP (1932) The Gompertz curve as a growth curve. Natl Acad Sci 18(2)

    Google Scholar 

  250. Wissema GJ (1976) Morphological analysis: its application to a company TF investigation. Futures, pp 146–153

    Google Scholar 

  251. Wolstenholme EF (1982) System dynamics in perspective. J Oper Res Soc 33(6):547–556

    MathSciNet  Google Scholar 

  252. Wolstenholme EF (1990) System enquiry: a system dynamics approach. Wiley, UK

    Google Scholar 

  253. Yoon B, Phaal R, Probert D (2008) Morphology analysis for technology roadmapping: application of text mining. R&D Management 38(1):51–68

    CrossRef  Google Scholar 

  254. Zipf G (1932) Selective studies and the principle of relative frequency in language. Mass, Cambridge

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Portland State University, Portland, USA

    Yonghee Cho & Tugrul Daim

Authors
  1. Yonghee Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tugrul Daim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tugrul Daim .

Editor information

Editors and Affiliations

  1. , Engineering and Technology Management, Portland State University, SW Fourth, Portland, 97201, USA

    Tugrul Daim

  2. Bonneville Power Administration, NE 11th Ave 905, Portland, 97207, Oregon, USA

    Terry Oliver

  3. Bonneville Power Administration, NE 11th Ave 905, Portland, 97232, Oregon, USA

    Jisun Kim

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Cho, Y., Daim, T. (2013). Technology Forecasting Methods. In: Daim, T., Oliver, T., Kim, J. (eds) Research and Technology Management in the Electricity Industry. Green Energy and Technology. Springer, London. https://doi.org/10.1007/978-1-4471-5097-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5097-8_4

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5096-1

  • Online ISBN: 978-1-4471-5097-8

  • eBook Packages: EnergyEnergy (R0)