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Aiding Consumer Decisions on the Web Gary McClelland University of Colorado @ Boulder with assistance from Barbara Faso

Aiding Consumer Decisions on the Web Gary McClelland University of Colorado @ Boulder with assistance from Barbara Fasolo & Katharine Lange Presented at The Wharton School University of Pennsylvania 26 February 2001. Today’s Tour. Consumer-Aiding Websites

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Aiding Consumer Decisions on the Web Gary McClelland University of Colorado @ Boulder with assistance from Barbara Faso

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  1. Aiding Consumer Decisions on the Web Gary McClelland University of Colorado @ Boulder with assistance from Barbara Fasolo & Katharine Lange Presented at The Wharton School University of Pennsylvania 26 February 2001

  2. Today’s Tour • Consumer-Aiding Websites • Winnowing via EBA, LEX, MCD, WADD, MAUT, etc. • Why Attribute Correlations Matter • Typical Attribute Correlations • Effects of Attribute Correlations

  3. Decision Guides

  4. Decision Guides

  5. MouseLab IDB (ca. 1990)

  6. Consumer Reports

  7. Consumer Reports Online Paid Subscriptions: 532,000 in Feb 2001

  8. IDB—Options x Attributes www.decide.com

  9. IDB—Attributes x Options www.point.com

  10. IDB—46 x 5 www.activebuyersguide.com

  11. IDB—Continued www.activebuyersguide.com

  12. IDB—Still More www.activebuyersguide.com

  13. IDB—More Yet! www.activebuyersguide.com

  14. IDB—The End www.activebuyersguide.com

  15. Many, Many Options www.personalogic.com www.point.com

  16. Aiding the Consumer • Winnowing • Comparing • Evaluating • Recommending • Choosing

  17. Company Sites:Not Much Help www.panasonic.com

  18. Compared to What? www.panasonic.com

  19. Additional Info www.panasonic.com

  20. Compared to Other Phone? www.panasonic.com

  21. Automobile Sites:This is Decision Help?

  22. IDBs Designed for Decision Making Sort by Attribute, Eliminate Options, Choose www.cdw.com

  23. Decision Sites in Transition

  24. Retail Sales 2000:4Q • Online: Up 36% to $8.7 billion • Online: > 1.1 % of total retail • Total: Up 5.4% Source:Reuters, 16 Feb 2001

  25. Today’s Tour • Consumer-Aiding Websites • Winnowing via EBA, LEX, MCD, WADD, MAUT, etc. • Why Attribute Correlations Matter • Typical Attribute Correlations • Effects of Attribute Correlations

  26. Winnowing Options • Setting Attribute Cutoffs (EBA) • Sorting along Attributes (LEX,TB) • Weighting Attributes (WADD) • Measuring Tradeoffs (MAUT)

  27. Winnowing:Lexicographic

  28. Winnowing:Elimination by Aspects

  29. Winnowing:Satisficing

  30. Winnowing: Most Confirming Dimensions

  31. Winnowing:Adding (Equal Wts)

  32. Winnowing:Implications

  33. Attribute Processing EBA or LEX or TakeBest

  34. Elimination-by-Aspects www.point.com

  35. Elimination-by-Aspects www.point.com

  36. EBA—Are You Sure? www.activebuyersguide.com

  37. EBA & LEX www.decide.com

  38. Option Processing WADD or MAUT Score

  39. WADD—Getting the Wts www.personalogic.com

  40. WADD—Weights & Values mro.frictionless.com

  41. Weight Profiles mro.frictionless.com

  42. WADD—Option Score mro.frictionless.com

  43. MAUT—Tradeoffs www.activebuyersguide.com

  44. MAUT—Global www.activebuyersguide.com

  45. Collaborative Filtering • www.amazon.com • movielens.umn.edu • www.imdb.com

  46. Today’s Tour • Consumer-Aiding Websites • Winnowing via EBA, LEX, MCD, WADD, MAUT, etc. • Why Attribute Correlations Matter • Typical Attribute Correlations • Effects of Attribute Correlations

  47. Positive Correlation = “Friendly Decision” r = .21

  48. Weight Insensitivity X1 + 3 X2 3 X1 + X2 r= .21

  49. X1X2 B B A G G F C C E D F E D A Attribute Agreement r = .21 = .24

  50. Equal Weights History • Wilks (1938) • Gulliksen (1950) • Dawes & Corrigan (1974) • Einhorn & Hogarth (1975) • Wainer (1976) • Meehl (1999)

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