How long will it take? Power biases time predictions

People tend to underestimate the time it takes to accomplish tasks. This bias known as the planning fallacy derives from the tendency to focus attention too narrowly on the envisaged goal and to ignore additional information that could make predictions more accurate and less biased. Drawing on recent research showing that power induces attentional focus, four studies tested the hypothesis that power strengthens the tendency to underestimate future task completion time. Across a range of task domains, and using multiple operationalizations of power, including actual control over outcomes (Study 1), priming (Studies 2 and 3), and individual differences (Study 4), power consistently led to more optimistic and less accurate time predictions. Support was found for the role of attentional focus as an underlying mechanism for those effects. Differences in optimism, self-efficacy, and mood did not contribute to the greater bias in powerful individuals’ forecasts. We discuss the implications of these findings for institutional decision processes and occupational health.     

Judgment in a dynamic task: Microburst forecasting

The major goals of this research are to (a) study professionals engaging in dynamic, representative task conditions, (b) apply lens model theory to these conditions, (c) learn how judgments are changed in response to changing conditions, and (d) utilize a hierarchical judgment model to investigate the judgment process from perception of data to final judgment. The results indicate that (a) agreement regarding inferred cue values is modest, not because of differences in perception of proximal, directly observed cue values but because of differences in inferences drawn from them, (b) agreement in probability judgments is higher when inferred cue values are specified, (c) little change in judgments occurred over time, and (d) confidence increased over time. The results regarding agreement and accuracy over time were ambiguous.     

The stability of mastery motivation and its relationship with home environment in infants and toddlers

Mastery motivation (intrinsic drives to explore and master one's environment) is a key developmental element. The aims of this study were to investigate (1) the stability of mastery motivation between 2 and 3 years of age for two genders; and (2) the associations between early home environment and toddlers’ mastery motivation in children with typical development.

Methods

Data of 102 children developing typically from a birth cohort study at Northern Taiwan were analyzed in two parts: (1) stability part: mastery motivation of children were measured at 2 and 3 years of age; (2) environment part: child-parent dyads were assessed from birth, 4 months, 6 months, and 2-3 years of age. Outcomes variables were measured at ages 2 and 3 years by the Dimension of Mastery Questionnaire-17th version. Main predictive variables were measured by Home Observation for Measuring Environment Inventory (HOME) to collect data of the qualities of home environment at 6 months and 2 years; by the Revised Infant Temperament Questionnaire to obtain 4-month activity levels; and by the Comprehensive Developmental Inventory for Infants and Toddlers to obtain 2-year developmental quotient (DQ).

Results

There was moderate stability of mastery motivation from 2 to 3 years, and girls’ stability was higher than boys’. 6-Month HOME rather than 2-year HOME measures were positively and significantly correlated with instrumental mastery motivation even when controlling for gender, activity level, and DQ.

Conclusion

Mastery motivation had moderate stability during the toddler period. The quality of home environment in infancy appeared to have a significant impact on toddler's mastery motivation. To promote mastery motivation, caregivers should provide better quality of home environment for infants/toddlers during the very early years.     

The need for contextual and technical knowledge in judgmental forecasting

The purpose of this research is to assess the extent to which judgmental forecasts are improved by having more contextual and technical knowledge. Contextual information is knowledge gained by practitioners through experience on the job, consisting of general forecasting experience in the industry as well as specific product knowledge. Technical knowledge is knowledge about data analysis and formal forecasting procedures, including information on how to analyze data judgmentally. We directly compared judgmental forecasts of business practitioners with those generated by students, using 22 real-world time series. The practitioners had considerable contextual but no technical knowledge. The students had no contextual but two different levels of technical knowledge. We also generated forecasts with statistical methods to benchmark performance. Results show that contextual knowledge is particularly important in making good judgmental forecasts, while technical knowledge has little value. Practitioner forecasts are better than student forecasts in almost all comparisons. A decisive factor affecting forecast performance appears to be data variability, measured by the coefficient of variation of the time-series data. As the variability of a time series increases, the performance of all forecasts deteriorates, but judgmental forecasts by practitioners become more preferable. Statistical methods have difficulty achieving reasonable forecasts when the data are more variable, whereas judgemental forecasts reinforced by contextual information do relatively well. Data variability is one explanation for the mixed findings of past studies, relative to how well statistical techniques compare with judgment as a forecasting method.     

Planning, personality, and prediction: The role of future focus in optimistic time predictions

The present studies examined cognitive processes underlying the tendency to underestimate project completion times. Two experiments tested the hypothesis that people generate overly optimistic predictions, in part, because they focus narrowly on their future plans for the target task and thus neglect other useful sources of information. Consistent with the hypothesis, instructing participants to adopt a “future focus”—in which they generated concrete, specific plans for the task at hand—led them to make more optimistic predictions about when they would complete their intended Christmas shopping (Study 1) and major school assignments (Study 2). The future focus manipulation did not have a corresponding effect on actual completion times, and thus increased the degree of optimistic bias in prediction. The studies also demonstrated that the optimistic prediction bias generalized across different task domains, relevant individual differences (i.e., trait optimism and procrastination), and other contextual variations.