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Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?

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Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour? / Petropoulos, Fotios; Fildes, Robert Alan; Goodwin, Paul.

In: European Journal of Operational Research, Vol. 249, No. 3, 16.03.2016, p. 842-852.

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Petropoulos, Fotios ; Fildes, Robert Alan ; Goodwin, Paul. / Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?. In: European Journal of Operational Research. 2016 ; Vol. 249, No. 3. pp. 842-852.

Bibtex

@article{ced8d34e3ed1438a9579e0d970cf04c4,
title = "Do {\textquoteleft}big losses{\textquoteright} in judgmental adjustments to statistical forecasts affect experts{\textquoteright} behaviour?",
abstract = "The behaviour of poker players and sports gamblers has been shown to change after winning or losing a significant amount of money on a single hand. In this paper, we explore whether there are changes in experts{\textquoteright} behaviour when performing judgmental adjustments to statistical forecasts and, in particular, examine the impact of {\textquoteleft}big losses{\textquoteright}. We define a big loss as a judgmental adjustment that significantly decreases the forecasting accuracy compared to the baseline statistical forecast. In essence, big losses are directly linked with wrong direction or highly overshooting judgmental overrides. Using relevant behavioural theories, we empirically examine the effect of such big losses on subsequent judgmental adjustments exploiting a large multinational data set containing statistical forecasts of demand for pharmaceutical products, expert adjustments and actual sales. We then discuss the implications of our findings for the effective design of forecasting support systems, focusing on the aspects of guidance and restrictiveness.",
keywords = "Forecasting, Judgment, Behavioural analytics, Decision support systems",
author = "Fotios Petropoulos and Fildes, {Robert Alan} and Paul Goodwin",
year = "2016",
month = mar,
day = "16",
doi = "10.1016/j.ejor.2015.06.002",
language = "English",
volume = "249",
pages = "842--852",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "3",

}

RIS

TY - JOUR

T1 - Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?

AU - Petropoulos, Fotios

AU - Fildes, Robert Alan

AU - Goodwin, Paul

PY - 2016/3/16

Y1 - 2016/3/16

N2 - The behaviour of poker players and sports gamblers has been shown to change after winning or losing a significant amount of money on a single hand. In this paper, we explore whether there are changes in experts’ behaviour when performing judgmental adjustments to statistical forecasts and, in particular, examine the impact of ‘big losses’. We define a big loss as a judgmental adjustment that significantly decreases the forecasting accuracy compared to the baseline statistical forecast. In essence, big losses are directly linked with wrong direction or highly overshooting judgmental overrides. Using relevant behavioural theories, we empirically examine the effect of such big losses on subsequent judgmental adjustments exploiting a large multinational data set containing statistical forecasts of demand for pharmaceutical products, expert adjustments and actual sales. We then discuss the implications of our findings for the effective design of forecasting support systems, focusing on the aspects of guidance and restrictiveness.

AB - The behaviour of poker players and sports gamblers has been shown to change after winning or losing a significant amount of money on a single hand. In this paper, we explore whether there are changes in experts’ behaviour when performing judgmental adjustments to statistical forecasts and, in particular, examine the impact of ‘big losses’. We define a big loss as a judgmental adjustment that significantly decreases the forecasting accuracy compared to the baseline statistical forecast. In essence, big losses are directly linked with wrong direction or highly overshooting judgmental overrides. Using relevant behavioural theories, we empirically examine the effect of such big losses on subsequent judgmental adjustments exploiting a large multinational data set containing statistical forecasts of demand for pharmaceutical products, expert adjustments and actual sales. We then discuss the implications of our findings for the effective design of forecasting support systems, focusing on the aspects of guidance and restrictiveness.

KW - Forecasting

KW - Judgment

KW - Behavioural analytics

KW - Decision support systems

U2 - 10.1016/j.ejor.2015.06.002

DO - 10.1016/j.ejor.2015.06.002

M3 - Journal article

VL - 249

SP - 842

EP - 852

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -