Judgemental adjustment of initial forecasts
Its effectiveness and biases
Bibliographic Data
| ID | 12166308 |
|---|---|
| Authors | Joa Sang Lim (UNSW Sydney, corresponding author), Marcus O’Connor (0000-0001-6312-7867, UNSW Sydney) |
| Year | 1995 |
| Volume | 8 |
| Issue | 3 |
| Pages | 149-168 |
| Publication date | 1995-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Behavioral Decision Making (JOURNAL) |
| Journal identifiers | ISSN: 0894-3257 • E-ISSN: 1099-0771 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/bdm.3960080302 |
| OpenAlex | W2109141422 |
| Language | EN |
| Citations received | 26 |
| References cited | 66 |
Managers are often required to integrate their own forecasts with statistical forecasts. The studies reported in this paper examine the efficacy of allowing people to adjust their own forecasts in the light of statistical forecasts that are provided to them. Three experimental studies varied the reliability of the statistical forecasts and examined the performance of people over time. Issues of the form of the feedback and the use of decision support were also examined. The results unequivocally suggest that the effectiveness of judgemental adjustment depended on the statistical model's reliability and seasonally of time series. However, people had considerable difficulty placing less weight on their own forecasts (compared to the statistical forecasts) and this behaviour became more pronounced over time. Even provision of decision support did not improve performance at the task
Consensus forecast · Econometrics · Economics · Machine learning · Reliability (semiconductor · Statistical analysis · Statistical model · Statistics · Task (project management · Computer Science · Decision-Making and Behavioral Economics · Forecasting Techniques and Applications · Mathematics · Psychology
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Advice Taking in Decision Making
Social Projection to Ingroups and Outgroups
Receiving other people’s advice
Judgmental forecasts of time series affected by special events
Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts
Investigating lay evaluations of models
Risk prediction algorithms and clinical judgment
Social Influence Under Uncertainty in Interaction with Peers, Robots and Computers
The influence of explicit self-esteem, implicit self-esteem and the discrepancies between them on advice taking
Majority views and confidence information promote informed decisions
Searching for certainty in an uncertain world
Improving judgmental forecasts with judgmental bootstrapping and task feedback support
Individual and group advice taking in judgmental forecasting
Effects of task difficulty on use of advice
The relative influence of advice from human experts and statistical methods on forecast adjustments
Mixed‐effects regression weights for advice taking and related phenomena of information sampling and utilization
Accuracy and bias of experts’ adjusted forecasts
The best option illusion in self and social assessment
Improving Forecasting Accuracy by Combining Statistical and Judgmental Forecasts in Tourism
Effects of Experience and Advice on Process and Performance in Negotiations
The Role of Anticipated Regret in Advice Taking
Advisors want their advice to be used – but not too much
Naïve realism and capturing the “wisdom of dyads”
Psychological factors underlying attitudes toward AI tools
Clinical versus statistical prediction
Combining forecasts
Simple models or simple processes? Some research on clinical judgments.
Comparison of Bayesian and regression approaches to the study of information processing in judgment
Consequences of individual feedback on behavior in organizations.
Clinical Versus Actuarial Judgment
Judgment under Uncertainty
Social Judgment Theory
Conservatism in human information processing
The need for contextual and technical knowledge in judgmental forecasting
The illusion of control
Why we still use our heads instead of formulas
Linear models in decision making
Manova method for analyzing repeated measures designs
| Unique citing works | 26 |
|---|---|
| Citations per year | 0,96 |
| Citation span | 1999 - 2026 (28) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 26 |