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Aiding Consumer Decisions on the Web Gary McClelland University of Boulder with assistance from Barbara Fasolo & Katharine Lange Presented at.

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Presentation on theme: "Aiding Consumer Decisions on the Web Gary McClelland University of Boulder with assistance from Barbara Fasolo & Katharine Lange Presented at."— Presentation transcript:

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

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.comwww.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 O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 LEX

28 Winnowing: Elimination by Aspects O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 EBA

29 Winnowing: Satisficing O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 SAT

30 Winnowing: Most Confirming Dimensions O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 MCD

31 Winnowing: Adding (Equal Wts) O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 ADD

32 Winnowing: Implications O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 LEXSATEBAMCDADD

33 Attribute Processing Opt 1Opt 2Opt 3 Att AV A1 V A2 V A3 Att BV B1 V B2 V B3 Att CV C1 V C2 V C3 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 Opt 1Opt 2Opt 3 Att AV A1 V A2 V A3 Att BV B1 V B2 V B3 Att CV C1 V C2 V C3 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 3 X1 + X2X1 + 3 X2 r=.21

49 Attribute Agreement X1 X2 B A G G F C E D F E D A r =.21  =.24

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

51 Equal Wts Correlations

52 Markets -> Nondominated Options r = -.87

53 Weight Sensitivity! 3 X1 + X2X1 + 3 X2 r= -.87

54 Nondominated Shapes

55 Equal Wts Value Loss

56 X1 X2 A E B D C D B E A Attribute Disagreement r = -.87  = -1.0

57 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

58 Real Choice Sets What are their attribute correlations? Are they approximately nondominated sets? Consumer Reports

59

60 Example CR Choice Set Mtn Bikes r = -.82

61 -P/Q Correlations from CR -.17 Air Conditioners -.27 Bike Helmets +.16 Dishwashers -.82 Mtn Bikes -.74 Printers -.49 Pro Ranges -.28 Fridge -.59 27” TVs -.16 Vacuums -.56 Wall Oven

62 -P/Q Correlations

63 Attribute Correlations from CR +.35 Air Conditioners +.07 Bike Helmets -.03 Dishwashers +.37 Mtn Bikes +.18 Printers +.47 Pro Ranges -.06 Fridge +.05 27” TVs +.12 Vacuums +.04 Wall Oven

64 Average r = –.05 O1O2O3O4O5 A1 +++++0 A2 –0+–++ A3 –++++ A4 –0––+++ A5 –00+0 LEXSATEBAMCDADD

65 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

66 WebIDB

67 Sample Data Streams Att Opt Time 0 1 276 0 0 1595 1 0 851 0 0 859 0 1 836 0 0 535 0 1 975 0 2 652 0 3 652 0 4 543 Att Opt Time 1 4 557 1 3 166 0 2 234 1 2 472 1 1 765 2 1 2111 2 2 2519 2 3 1031 2 4 448 Attribute Focus

68 WebIDB cf. MouseLab WebIDB replicated MouseLab results –Attribute Focus is the default strategy –Increasing Attributes -> Attribute Focus –Increasing Options -> Less info, more var. Different result –Somewhat more information viewed in WebIDB –Somewhat greater attribute focus in WebIDB

69 Prior Research on Correlation Effects Johnson, Meyer & Ghose (1989) Theory: Negative – > Attribute-based Results: Null Bettman, Johnson, Luce & Payne (1993) Theory: Negative –> Option-based Results: Negative –> Option-based

70 Experiments Study 1 –8 att x 5 opts –Attribute Correlation: Pos (.5) vs. Neg (-.14) –8 Matrices –Between Subjects Study 2 –Within Subjects: Switch after 4 Matrices

71 Proportion of Cells Visited

72 Attribute Visit S.D. Equal Attention Selective Attention

73 Payne Index = (Opt-Att)/(Opt+Att) Attribute Focus Option Focus

74 Self-Ratings

75 Switch Attribute Correlation

76 Results Summary Default Strategy is Attribute Processing Negative Correlation —> Option Processing Immediate Sensitivity to Correlation Quickly Switch to Option Processing Amount of Information Constant

77 Research Questions What winnowing strategies do consumers use? Attribute-based unless forced towards Option-based by negative attribute correlations

78 Research Questions What winnowing strategies might consumers be willing to use if aided? And how do attribute correlations affect the use of such aids?

79 Correlations and EBA

80 Correlations and WADD

81 End of Tour Consumer-Aiding Websites Winnowing via EBA, LEX, MCD, WADD, MAUT, etc. Why Attribute Correlations Matter Typical Attribute Correlations Effects of Attribute Correlations


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