Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 777

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Expert Opinions in Forecasting: The Role of the Delphi Technique

Rowe, Gene, Wright, George·2001·International Series in Operations Research & Management Science

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/978-0-306-47630-3_7

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Research works printed but not linked: 55

  1. Arkes, H. (2001), “Overconfidence in judgmental forecasting,” in J..S. Armstrong (ed.), Principles of Forecasting. Norwell, MA.: Kluwer Academic Publishers.
  2. Bardecki, M.J. (1984), “Participants’ response to the Delphi method: An attitudinal perspective,” Technological Forecasting and Social Change, 25, 281–292. · DOI
  3. Beach, L. R. and L. D. Phillips (1967), “Subjective probabilities inferred from estimates and bets,” Journal of Experimental Psychology, 75, 354–259. · doi:10.1037/h0025061
  4. Best, R. J. (1974), “An experiment in Delphi estimation in marketing decision making,” Journal of Marketing Research, 11, 448–452. · DOI
  5. Boje, D. M. and J. K. Murnighan (1982), “Group confidence pressures in iterative decisions,” Management Science, 28, 1187–1196. · DOI
  6. Brockhoff, K. (1975), “The performance of forecasting groups in computer dialogue and face to face discussions,” in H. Linstone and M. Turoff (eds.), The Delphi Method: Techniques and Applications. London: Addison-Wesley.
  7. Cooper, A., C. Woo and W. Dunkelberger (1988), “Entrepreneurs perceived chances of success,” Journal of Business Venturing, 3, 97–108. · DOI · Paper page
  8. Dalkey, N.C., B. Brown and S. W. Cochran (1970), “The Delphi Method III: Use of self- ratings to improve group estimates,” Technological Forecasting, 1, 283–291. · DOI
  9. Dietz, T. (1987), “Methods for analyzing data from Delphi panels: Some evidence from a forecasting study,” Technological Forecasting and Social Change, 31, 79–85. · DOI
  10. Erffineyer, R. C., E. S. Erffineyer and I. M. Lane (1986), “The Delphi technique: An empirical evaluation of the optimal number of rounds,” Group and Organization Studies, 11, 120–128. · DOI
  11. Erffineyer, R. C. and I.M. Lane (1984), “Quality and acceptance of an evaluative task: The effects of four group decision-making formats,” Group and Organization Studies, 9, 509–529. · DOI
  12. Fischer, G. W. (1981), “When oracles fail-a comparison of four procedures for aggregating subjective probability forecasts,” Organizational Behavior and Human Performance, 28, 96–110. · DOI
  13. Gigerenzer, G. (1994), “Why the distinction between single event probabilities and frequencies is important for psychology (and vice-versa),” in G. Wright and P. Ayton (eds.), Subjective Probability. Chichester, U.K.: Wiley.
  14. Goodwin, P. and G. Wright (1998), Decision Analysis for Management Judgment, 2nd ed. Chichester, U.K.: Wiley.
  15. Gustafson, D. H., R. K. Shukla, A. Delbecq and G. W. Walster (1973), “A comparison study of differences in subjective likelihood estimates made by individuals, interacting groups, Delphi groups and nominal groups,” Organizational Behavior and Human Performance, 9, 280–291. · DOI · Paper page
  16. Hauser, P.M. (1975), Social Statistics in Use. New York: Russell Sage.
  17. Hill, G. W. (1982), “Group versus individual performance: Are N+1 heads better than one?” Psychological Bulletin, 91, 517–539. · doi:10.1037/0033-2909.91.3.517 · Paper page
  18. Hill, K. Q. and J. Fowles (1975), “The methodological worth of the Delphi forecasting technique,” Technological Forecasting and Social Change, 7, 179–192. · DOI · Paper page
  19. Hogarth, R. M. (1978), “A note on aggregating opinions,” Organizational Behavior and Human Performance, 21, 40–46. · DOI · Paper page
  20. Jolson, M. A. and G. Rossow (1971), “The Delphi process in marketing decision making,” Journal of Marketing Research, 8, 443–448. · doi:10.2307/3150234
  21. Kahneman, D. and D. Lovallo (1993), “Timid choices and bold forecasts: A cognitive perspective on risk taking,” Management Science, 39, 17–31. · DOI · Paper page
  22. Larreché, J. C. and R. Moinpour (1983), “Managerial judgment in marketing: The concept of expertise,” Journal of Marketing Research, 20, 110–121. · doi:10.2307/3151678
  23. Linstone, H. A. (1975), “Eight basic pitfalls: A checklist,” in H. Linstone and M. Turoff (eds.), The Delphi Method: Techniques and Applications. London: Addision-Wesley.
  24. Linstone, H. A. and M. Turoff (1975), The Delphi Method: Techniques and Applications. London: Addision-Wesley.
  25. Lock, A. (1987), “Integrating group judgments in subjective forecasts,” in G. Wright and P. Ayton (eds.), Judgmental Forecasting. Chichester, U.K.: Wiley.
  26. MacGregor, D. G. (2001), “Decomposition for judgmental forecasting and estimation,” in J. S. Armstrong (ed.), Principles of Forecasting. Norwell, MA.: Kluwer Academic Publishers.
  27. Martino, J. (1983), Technological Forecasting for Decision Making, ( 2nd ed. ). New York: American Elsevier.
  28. McClelland, A. G. R. and F. Bolger (1994), “The calibration of subjective probabilities: Theories and models 1980–1994,” in G. Wright and P. Ayton (eds.), Subjective Probability. Chichester, U.K.: Wiley.
  29. Meehl, P. E. (1954), Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence. Minneapolis: University of Minnesota Press. · DOI · Paper page
  30. Miner, F. C. (1979), “A comparative analysis of three diverse group decision making approaches,” Academy of Management Journal, 22, 81–93. · DOI
  31. Noelle-Neuman, E. (1970), “Wanted: Rules for wording structured questionnaires,” Public Opinion Quarterly, 34, 190–201.
  32. Parenté, F.J., J. K. Anderson, P. Myers and T. O’Brien (1984), “An examination of factors contributing to Delphi accuracy,” Journal of Forecasting, 3, 173–182. · DOI
  33. Parenté, F. J. and J. K. Anderson-Parenté (1987), “Delphi inquiry systems,” in G. Wright and P. Ayton (eds.), Judgmental Forecasting. Chichester, U.K.: Wiley.
  34. Payne, S.L. (1951), The Art of Asking Questions. Princeton, NJ: Princeton University Press.
  35. Riggs, W. E. (1983), “The Delphi method: An experimental evaluation,” Technological Forecasting and Social Change, 23, 89–94. · DOI
  36. Rohrbaugh, J. (1979), “Improving the quality of group judgment: Social judgment analysis and the Delphi technique,” Organizational Behavior and Human Performance, 24, 73–92. · DOI · Paper page
  37. Rowe, G. and G. Wright (1996), “The impact of task characteristics on the performance of structured group forecasting techniques,” International Journal of Forecasting, 12, 73–89. · DOI
  38. Rowe, G. and G. Wright (1999), “The Delphi technique as a forecasting tool: Issues and analysis,” International Journal of Forecasting, 15, 353–375. (Commentary follows on pp. 377–381.)
  39. Rowe, G., G. Wright and F. Bolger (1991), “The Delphi technique: A reevaluation of research and theory,” Technological Forecasting and Social Change, 39, 235–251. · DOI · Paper page
  40. Sackman, H. (1975), Delphi Critique. Lexington, MA: Lexington Books.
  41. Salancik, J. R., W. Wenger and E. Helfer (1971), “The construction of Delphi event statements,” Technological Forecasting and Social Change, 3, 65–73. · DOI
  42. Scheibe, M., M. Skutsch and J. Schofer (1975), “Experiments in Delphi methodology,” in H. Linstone and M. Turoff (eds.), The Delphi Method: Techniques and Applications. London: Addison-Wesley.
  43. Sniezek, J. A. (1989), “An examination of group process in judgmental forecasting,” International Journal of Forecasting, 5, 171–178. · DOI
  44. Sniezek, J. A. (1990), “A comparison of techniques for judgmental forecasting by groups with common information,” Group and Organization Studies, 15, 5–19. · DOI
  45. Sniezek, J. A. and T. Buckley (1991), “Confidence depends on level of aggregation,” Journal of Behavioral Decision Making, 4, 263–272. · DOI
  46. Stewart, T.R. (1987), “The Delphi technique and judgmental forecasting,” Climatic Change, 11, 97–113. · DOI
  47. Stewart, T.R. (2001), “Improving reliability in judgmental forecasts,” in J. S. Armstrong (ed.), Principles of Forecasting. Norwell, MA.: Kluwer Academic Publishers.
  48. Sudman, S. and N. Bradburn (1982), Asking Questions. San Francisco: Josey-Bass.
  49. Van de Ven, A. H. and A. L. Delbecq (1971), “Nominal versus interacting group processes for committee decision making effectiveness,” Academic Management Journal, 14, 203–213. · DOI · Paper page
  50. Van de Ven, A. H. and A. L. Delbecq (1974), “The effectiveness of nominal, Delphi, and interacting group decision making processes,” Academy of Management Journal, 17, 605–621. · DOI · Paper page
  51. Welty, G. (1974), “The necessity, sufficiency and desirability of experts as value forecasters,” in W. Leinfellner and E. Kohler (eds.), Developments in the Methodology ofSocial Science. Boston: Reidel.
  52. Wright, G. and P. Ayton (1994), Subjective Probability. Chichester, U.K.: Wiley.
  53. Wright, G., G. Rowe, F. Bolger and J. Gammack (1994), “Coherence, calibration and expertise in judgmental probability forecasting,” Organizational Behavior and Human Decision Processes, 57, 1–25. · DOI
  54. Wright, G., C. Saunders and P. Ayton (1988), “The consistency, coherence and calibration of holistic, decomposed and recomposed judgmental probability forecasts,” Journal of Forecasting, 7, 185–199. · DOI
  55. Wright, G. and P. Whalley (1983), “The supra-additivity of subjective probability,” in B. Stigum and F. Wenstop (eds.), Foundations of Risk and Utility Theory with Applications. Dordrecht: Reidel.

Cited by

See all 777

Metadata

Authors
Rowe, G., & Wright, G.
Venue
International Series in Operations Research & Management Science
Publisher
Springer US
Published
2001
Pages
125-144
ISSN
0884-8289 (ISSN-L)
OpenAlex
W35220292
Cited by
777
References
3
FWCI
10.51
Type
book chapter
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Expert Opinions in Forecasting: The Role of the Delphi Technique. https://app.cochat.ai/papers/10.1007/978-0-306-47630-3_7
The paper
Rowe, G., & Wright, G. (2001). Expert Opinions in Forecasting: The Role of the Delphi Technique. International Series in Operations Research & Management Science. https://doi.org/10.1007/978-0-306-47630-3_7

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.