International Journal of Forecasting最新文献

Acknowledgement to reviewers

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-02-17 DOI: 10.1016/j.ijforecast.2025.02.003

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Introduction to the Special Issue on Judgment in Forecasting

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-02-07 DOI: 10.1016/j.ijforecast.2025.01.004

Robert Fildes, Fergus Bolger, Paul Goodwin, Nigel Harvey, Matthias Seifert

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How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-01-22 DOI: 10.1016/j.ijforecast.2024.12.001

Vahid Karimi Motahhar , Thomas S. Gruca

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Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament 存在风险的主观概率预测：混合劝说-预测比赛的初步结果

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-01-17 DOI: 10.1016/j.ijforecast.2024.11.008

Ezra Karger , Josh Rosenberg , Zachary Jacobs , Molly Hickman , Phillip E. Tetlock

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Forecast value added in demand planning

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-12-26 DOI: 10.1016/j.ijforecast.2024.07.006

Robert Fildes , Paul Goodwin , Shari De Baets

{"title":"Forecast value added in demand planning","authors":"Robert Fildes , Paul Goodwin , Shari De Baets","doi":"10.1016/j.ijforecast.2024.07.006","DOIUrl":"10.1016/j.ijforecast.2024.07.006","url":null,"abstract":"<div><div>Forecast value added (FVA) analysis is commonly used to measure the improved accuracy and bias achieved by judgmentally modifying system forecasts. Assessing the factors that prompt such adjustments, and their effect on forecast performance, is important in demand forecasting and planning. To address these issues, we collected the publicly available data on around 147,000 forecasts from six studies and analysed them using a common framework. Adjustments typically led to improvements in bias and accuracy for only just over half of stock keeping units (SKUs), though there was variation across datasets. Positive adjustments were confirmed as more likely to worsen performance. Negative adjustments typically led to improvements, particularly when they were large. The evidence that forecasters made effective use of relevant information not available to the algorithm was weak. Instead, they appeared to respond to irrelevant cues, or those of less diagnostic value. The key question is how organizations can improve on their current forecasting processes to achieve greater forecast value added. For example, a debiasing procedure applied to adjusted forecasts proved effective at improving forecast performance.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 649-669"},"PeriodicalIF":6.9,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-12-10 DOI: 10.1016/j.ijforecast.2024.11.005

David A. Comerford , Jack B. Soll

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An overview of the effects of algorithm use on judgmental biases affecting forecasting

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-11-21 DOI: 10.1016/j.ijforecast.2024.09.007

Alvaro Chacon , Esther Kaufmann

{"title":"An overview of the effects of algorithm use on judgmental biases affecting forecasting","authors":"Alvaro Chacon , Esther Kaufmann","doi":"10.1016/j.ijforecast.2024.09.007","DOIUrl":"10.1016/j.ijforecast.2024.09.007","url":null,"abstract":"<div><div>In the realm of forecasting, judgmental biases often hinder efficiency and accuracy. Algorithms present a promising avenue for decision makers to enhance their forecasting performance. In this overview, we scrutinized the occurrence of the most relevant judgmental biases affecting forecasting across 162 papers, drawing from four recent reviews and papers published in forecasting journals, specifically focusing on the use of algorithms. Thirty-three of the 162 papers (20.4%) at least briefly mentioned one of twelve judgmental biases affecting forecasting. Our comprehensive analysis suggests that algorithms can potentially mitigate the adverse impacts of biases inherent in human judgment related to forecasting. Furthermore, these algorithms can leverage biases as an advantage, enhancing forecast accuracy. Intriguing revelations have surfaced, focusing mainly on four biases. By providing timely, relevant, well-performing, and consistent algorithmic advice, people can be effectively influenced to improve their forecasts, considering anchoring, availability, inconsistency, and confirmation bias. The findings highlight the gaps in the current research landscape and provide recommendations for practitioners. They also lay the groundwork for future studies on utilizing algorithms (e.g., large language models) and overcoming judgmental biases to improve forecasting performance.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 424-439"},"PeriodicalIF":6.9,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Service-level anchoring in demand forecasting: The moderating impact of retail promotions and product perishability

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-11-18 DOI: 10.1016/j.ijforecast.2024.07.007

Ben Fahimnia , Tarkan Tan , Nail Tahirov

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Robust recalibration of aggregate probability forecasts using meta-beliefs

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-10-30 DOI: 10.1016/j.ijforecast.2024.09.005

Cem Peker , Tom Wilkening

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An extended logarithmic visualization improves forecasting accuracy for exponentially growing numbers, but residual difficulties remain

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-10-24 DOI: 10.1016/j.ijforecast.2024.09.006

Ben H. Engler, Florian Hutzler, Stefan Hawelka

{"title":"An extended logarithmic visualization improves forecasting accuracy for exponentially growing numbers, but residual difficulties remain","authors":"Ben H. Engler, Florian Hutzler, Stefan Hawelka","doi":"10.1016/j.ijforecast.2024.09.006","DOIUrl":"10.1016/j.ijforecast.2024.09.006","url":null,"abstract":"<div><div>Humans find it notoriously difficult to predict the future development of numbers in scenarios where the data exhibits exponential growth. This study explored how employing logarithmically scaled graphs can improve forecasting accuracy in such scenarios. Experiment 1 shows that a modified visualization improves forecasting, mitigating the inaccuracies encountered with linear and ordinary logarithmic depictions. The modification consists of putting the y-axis on the right side of a logarithmically scaled graph and extending the x-axis to the range of the forecast period. This effect was independent of general graph literacy, and participants were more confident in their estimates. To uncover the role of tick marks in estimation accuracy, we conducted a second experiment manipulating the presence of minor tick marks and varying target values systematically with respect to their proximity to the next major tick mark. Participants performed worse for target values midway between two major tick marks and no accuracy benefits related to the presence of tick marks. Analysis of eye movements during the same task suggests that the poor utilization of minor tick marks is not simply due to a lack of attention but to difficulties in converting the location into the corresponding numerical value.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 466-474"},"PeriodicalIF":6.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0