2017
DOI: 10.1016/j.ijpe.2017.05.016
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Investigating the added value of integrating human judgement into statistical demand forecasting systems

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Cited by 36 publications
(32 citation statements)
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“…This study also evaluates the impacts of combining forecast methods in terms of inventory performance, especially in reducing inventory costs. The benefit of combining forecasting methods also reported by Baecke et al [28] and Feng et al [29].…”
Section: E Combined Methodssupporting
confidence: 61%
“…This study also evaluates the impacts of combining forecast methods in terms of inventory performance, especially in reducing inventory costs. The benefit of combining forecasting methods also reported by Baecke et al [28] and Feng et al [29].…”
Section: E Combined Methodssupporting
confidence: 61%
“…Political articles focused on predicting presidential outcomes, a categorical target (Graefe, 2015, 2018; Graefe, Armstrong, Jones Jr, & Cuzán, 2014a, 2014b; Hurley & Lior, 2002; Morgan, 2014). Risk‐related targets were continuous and categorical: the probability of structural damage, nuclear fallout, occupational hazards, and balancing power load (Adams et al, 2009; Baecke et al, 2017; Brito et al, 2012; Brito & Griffiths, 2016; Cabello et al, 2012; Craig et al, 2001; Hathout et al, 2016; Jana et al, 2019; Kläs et al, 2010; Mu & Xianming, 1999; Neves & Frangopol, 2008; Ren‐jun & Xian‐zhong, 2002; Wang et al, 2008; Zio, 1996; Zio & Apostolakis, 1997). Public health papers predicted continuous targets over time, like forecasting carcinogenic risk (Evans et al, 1994) and US mortality rates (Alho, 1992).…”
Section: Resultsmentioning
confidence: 99%
“…Experts are able to make predictions without structured data, and instead, rely on their experience and contextual knowledge of the prediction task. Expert forecasts are most readily found in finance, business, and marketing (Alvarado‐Valencia, Barrero, Önkal, & Dennerlein, 2017; Baecke, De Baets, & Vanderheyden, 2017; Franses, 2011; Kabak & Ülengin, 2008; Petrovic, Xie, & Burnham, 2006; Seifert & Hadida, 2013; Shin et al, 2013; Song, Gao, & Lin, 2013). These fields focus on decision makers and their ability to make predictions from data that cannot easily be collected and fed to a statistical model.…”
Section: Introductionmentioning
confidence: 99%
“…Goodwin et al (2018) provide different behaviours of how individuals can game the forecasting process, such as enforcing, filtering, hedging and second guessing. The intangibility and perishability of service creates more uncertainties in the service supply chain and forecast bias has attracted the attention of numerous scholars (Baecke et al, 2017;Meeran et al, 2017). In the related research of forecast bias in the service supply chain, overconfidence receives most concern, which can be subdivided into over-placement, overestimation and over-precision.…”
Section: Strategic Behaviourmentioning
confidence: 99%