How to use aggregation and combined forecasting to improve seasonal demand forecasts

Dekker, Magda M. J.; Donselaar, KH Karel van; Ouwehand, Pim

doi:10.1016/j.ijpe.2004.02.004

Cited by 84 publications

(51 citation statements)

References 12 publications

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“…Ouwehand et al (2005) commented on the few publications dealing with aggregation approaches to forecasting (some of the most important are those by Dalhart, 1974;Withycombe, 1989;Vassilopoulos, 1993, 1999;and Dekker et al, 2004). In this paper, we begin by reviewing work on group seasonal indices, and find that there are many issues still to be resolved.…”

Section: Introductionmentioning

confidence: 89%

See 1 more Smart Citation

Formation of seasonal groups and application of seasonal indices

Boylan

Chen

Mohammadipour

et al. 2014

Journal of the Operational Research Society

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Section: Introductionmentioning

confidence: 89%

“…An alternative approach, based on exponential smoothing, was presented by Dekker et al (2004). They proposed that the Holt-Winters method should be adapted, allowing seasonal estimates at the group level while the level and trend estimates remain at the individual level.…”

Section: Whatever Causes the Seasonal Fluctuation In Demand Operates mentioning

confidence: 99%

Formation of seasonal groups and application of seasonal indices

Boylan

Chen

Mohammadipour

et al. 2014

Journal of the Operational Research Society

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“…In the situation where there are many data series sharing similar seasonal components, better estimates of seasonality can be obtained by shrinking the estimates towards the mean. Examples can be found in Bunn and Vassilopoulos (1999), Dekker et al (2004) and Miller and Williams (2004). Recently, Chen and Boylan (2007) derived guidelines for when such shrinking should prove helpful.…”

Section: Extrapolative Methodsmentioning

confidence: 99%

Forecasting and operational research: a review

Fildes

Νικολόπουλος

Crone

et al. 2008

Journal of the Operational Research Society

226

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From its foundation, operational research (OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scope of OR's interest in forecasting, research from an OR perspective remains vigorous. OR has been more receptive than other disciplines to the specialist research published in the forecasting journals, capitalizing on some of their key findings. In this paper, we identify the particular topics of OR interest over the past 25 years. After a brief summary of the current research in forecasting methods, we examine those topic areas that have grabbed the attention of OR researchers: computationally intensive methods and applications in operations and marketing. Applications in operations have proved particularly important, including the management of inventories and the effects of sharing forecast information across the supply chain. The second area of application is marketing, including customer relationship management using data mining and computer-intensive methods. The paper concludes by arguing that the unique contribution that OR can continue to make to forecasting is through developing models that link the effectiveness of new forecasting methods to the organizational context in which the models will be applied. The benefits of examining the system rather than its separate components are likely to be substantial.

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“…Published works about forecast demand have analyzed various products, such as beer (Calôba, Calôba, and Saliby, 2002); fresh milk (Doganis, Alexandridis, Patrinos, and Sarimveis, 2006); other perishable products (Higuchi, 2006); food retail (Zotteri;Kalchschmidt, and Caniato, 2005); wireless subscribers (Venkatesan and Kumar, 2002); supermarket sales (Taylor, 2007), number of births (Souto, Baldeon, and Russo, 2006); plastic products (Pellegrini and Fogliatto, 2000); price forecast ( Australia (Calôba et al, 2002); Holland (Dekker, van Donselaar, and Ouwehand, 2004); China (Kuo, 2001); the UK (Taylor, 2007); the US (Zeng, 2000), Greece (Doganis et al, 2006); and Italy (Zotteri et al, 2005). The Brazilian market for food products has been a subject of research only in recent years (Queiroz and Cavalheiro, 2006;Higuchi, 2006;Medeiros et al, 2006).…”

Section: Formula Applicationmentioning

confidence: 99%

A Acuracidade Dos Modelos De Previsão De Demanda Como Fator Crítico Para O Desempenho Financeiro Na Indústria De Alimentos

Rita¹,

Veiga²,

Duclós

2010

FSRJ

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Every organization needs to balance their production capacities with demand. The role of demand forecasting is to assist in the organization's strategic planning; this process allows administrators to anticipate the future and plot an appropriate course of action. On its own, however, a system of demand forecasting is not enough. It is the quality of information obtained by this system which enables the organization to achieve better operational planning. In this context, this paper presents case study P R O F U T U R O : F U T U R E S T U D I E S P R O G R A MScientific editor: James Terence Coulter Wright Evaluation: Doublé Blind Review by SEER

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How to use aggregation and combined forecasting to improve seasonal demand forecasts

Cited by 84 publications

References 12 publications

Formation of seasonal groups and application of seasonal indices

Formation of seasonal groups and application of seasonal indices

Forecasting and operational research: a review

A Acuracidade Dos Modelos De Previsão De Demanda Como Fator Crítico Para O Desempenho Financeiro Na Indústria De Alimentos

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