1. Antecedents and Consequences of Unsolicited vs
Antecedents and Consequences of Unsolicited vs. Explicitly Solicited Advice
Alyssa Mitchell Gibbons
Janet A. Sniezek
University of Illinois at Urbana-Champaign
Reeshad S. Dalal
Purdue University
SJDM 2003

2. In memory of Janet A. Sniezek

3. Background
Judge Advisor System (JAS) – decision making group with role differentiation (Sniezek & Buckley, 1995)
Judge – responsible for making the final decision
Advisor(s) – provides information to Judge (information, recommendations, explanations, expressions of confidence, etc.)
Previous JAS research focused mostly on the Judge:
How Judges reconcile external and internal information and conflicting advice (Sniezek & Buckley, 1995)
Judges’ motivations for using advice (Harvey & Fischer, 1997)
How well Judges assess advice vs. how well they use it (Harvey, Harries, & Fischer, 2000)

4. Advice is usually provided on every decision. (e. g
Advice is usually provided on every decision. (e.g., Birnbaum & Stegner, 1979; Harvey & Fischer, 1997; Harvey, Harries, & Fischer, 2000; Koestner et al., 1999)
In the “real world,” however, advice is neither automatically sought nor automatically provided for every decision.
Research has not (yet) focused on the factors that facilitate advice
…when it is explicitly solicited by the Judge
…when it is provided unsolicited by the Advisor

5. Design
Participants randomly paired and assigned to be either Judge or Advisor.
Advisor in Control (AC): 101 dyads
Judge in Control (JC): 40 dyads
Answered 20 moderately difficult 2-choice items about social psychology.
Worked at networked computers in separate rooms – advice was given by means of a videoconferencing link.
Dyads had opportunity to win cash reward based on the Judge’s final answers.
Items thought to be difficult, but not impossible, for introductory psychology students – they would not have expertise in this domain, but they should have some familiarity with the terms, etc. on which they could base their reasoning.

6. Judge in Control (advice is solicited)
On each decision…
Advising interaction occurs
Yes
Judge and Advisor provide initial opinions and confidence estimates
Judge and Advisor provide final opinions and confidence estimates No
Does Judge solicit advice?

7. Advisor in Control (unsolicited advice)
On each decision…
Advising interaction occurs
Yes
Judge and Advisor provide initial opinions and confidence estimates
Judge and Advisor provide final opinions and confidence estimates No
Does Advisor volunteer advice?
Advisor becomes aware of Judge’s initial opinion and confidence estimate

8. Variables of Interest Outcomes Variables
Offering unsolicited advice or seeking advice
Response to advice once given
Answer change
Agreement with advisor
Final decision accuracy (judge)
Variables
Accuracy – choosing the correct answer
Confidence – self-report of confidence in own choice, from .50 to 1.00
Conflict – difference in Judge and Advisor initial choices
# of items answered not necessarily the same for all participants – time was limited but didn’t rush them
Initial and final measures of confidence and accuracy

9. Results: Initial ComparisonsAC JC
Judge Initial Mean Accuracy
.59
.60
Judge Initial Mean Confidence
.66
.69
Advisor Initial Mean Accuracy
.58
.61
Advisor Initial Mean Confidence
.67
Within each condition, Judges and Advisors were not significantly different from each other in their initial answers.
Participants in the two conditions were not initially significantly different from each other.
Calibration – correlation between accuracy and confidence – was poor: highest correlation in any group = .095.

10. Results: Advice and ConsequencesAC JC
Proportion of Advice Sought or Given
.22
.52
Judge Final Mean Accuracy
.60
.64
Judge Final Mean Confidence
.67
.71
Advisor Final Mean Accuracy
.61
.62
Advisor Final Mean Confidence
.66
Based significance test on arcsin transformed data , but reported interpretable proportion
Judges appear to want more advice than advisors want to give
Judges appear to have better outcomes when the advice is on their terms
However, we don’t know from these data that the advice enhances outcomes – it could be that simply having control makes Judges more comfortable, which allows them to make more accurate decisions, etc…
Need to look at the item level to determine the antecedents and consequences of advice.
Judges asked for significantly more advice than Advisors offered unsolicited.
Judges who were in control of advice were significantly more accurate and confident.

11. Predicting Advice Giving and Seeking

12. Predicting Advice: Regression Models
Judge in Control (solicited advice) :
Model R2 = .149
Advisor in Control (unsolicited advice) :
Model R2 = .279
All beta values reported were significant, p<.05
Variable
Beta (std)
Judge Initial Confidence
-.379
Variable
Beta (std)
Advisor Initial Confidence
.300
Judge Initial Confidence
-.164
Conflict
1.037
Conflict x Advisor Initial Confidence
1.019
Conflict x Judge Initial Confidence
-.433
Interpretation: As expected, only judge confidence predicts explicit advice seeking.

13. Confidence and Unsolicited Advice
No difference between high & low confidence with no conflict for either
When conflict exists, advice is more likely in general, plus high advisor conf -> more advice, but higher judge conf -> less advice

14. Advice Response

15. Advice Response: Regression Models
Judge in Control (solicited advice) :
Model R2 = .149
Advisor in Control (unsolicited advice) :
Model R2 = .279
Variable
Beta (std)
Conflict x Advisor Initial Confidence
.597
Conflict x Judge Initial Confidence
-.933
Interpretation: As expected, only judge confidence predicts explicit advice seeking.
Variable
Beta (std)
Conflict x Advisor Initial Confidence
.544
Conflict x Judge Initial Confidence
-.541

16. Answer Change After Advice
High & Low Conf are NS different for both studies, regardless of whether or not conflict was present.
However, the studies are sig diff, and conflict is always higher than no conflict.

17. Answer Change After Advice
Under No Conflict, Low/High cells are NS different from each other.
All corresponding cells are sig different across studies.
Conflict is different from no conflict in both studies.
When conflict, low conf is sig diff from high conf in both studies.

18. Conclusions
Advisors weighed more factors in deciding to give unsolicited advice than Judges in deciding to seek advice.
Conflict
Confidence – Advisor high or Judge low
Somewhat intuitive – Advisors had more information than Judges – but they did make use of this information.

19. Conclusions
Answer change was more likely when Judge sought advice than when advice was unsolicited.
Confidence an important determinant of answer change.
Limitations –
Novice advisors
No performance feedback

20. Questions?

21. Final Accuracy

22. Final Decision Accuracy (Advisor in Control)
Model R2 = .659
Variable
Beta (std)
Judge Initial Accuracy
.678
Advisor Initial Accuracy
.196
Advice
-.131
Advice x Advisor Initial Accuracy
.242
Advice x Judge Initial Accuracy
-.451
Interpretation:

23. Final Decision Accuracy (Judge in Control)
Model R2 = .619
Variable
Beta (std)
Judge Initial Accuracy
.563
Advice x Advisor Initial Accuracy
.390
Advice x Judge Initial Accuracy
-.430
Advisor Initial Accuracy X Judge Initial Confidence
-.445
Advisor Initial Confidence X
-.498
Judge Initial Accuracy X
Judge Initial Confidence
.647
Interpretation:

24. Results Summary: Both Studies
 indicates positive effect on Judge Final Accuracy
 indicates negative effect on Judge Final Accuracy
= indicates no effect
General results:
Effect of:
Is:
When:
Judge Correct 
(all cases)
Advice
Judge Incorrect 
Advisor Incorrect
Advisor Correct

25. Results Summary JUDGE IN CONTROL Effect of: Is: When: Advisor Correct
Judge Confidence = Low =
Judge Confidence = High
Advisor Confidence
Judge Incorrect
Judge Correct
Judge Confidence 
ADVISOR IN CONTROL
Effect of:
Is:
When:
Advisor Correct 
(all cases)
Advice 

26. Data Considerations - Dependency
Item level data are doubly dependent:
Within-persons
Within-items
Not interested in item or person factors as such, but in the situational factors that induce advice giving or taking over and above these general tendencies.
Strategy: Double-mean-center data to eliminate effects of person & item:
Advice = (person mean) + (item mean) + (situation effects)
Advice - person mean - item mean = situation effects