The impact of forecasting model selection on the value of information sharing in a supply chain

Zhao, Xiande; Xie, Jinxing; Leung, Janny

doi:10.1016/s0377-2217(01)00300-9

Cited by 184 publications

(100 citation statements)

References 10 publications

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“…The overall SC performance has been proved higher with high quality information from SC partners (Forsuland & Jonsson, 2007;Zhao et al, 2002). But, obtaining the high quality information in (2007) POS & market data Improve responsiveness to demand fluctuations Ketzenberg (2009) Demand, recovery yield, capacity utilisation Capacity utilisation showed more value than any other information in a capacitated closed loop SC.…”

Section: Literature On Supply Chain Information and Research Approachmentioning

confidence: 99%

How Smart Operations Help Better Planning and Replenishment?

Ramanathan

2017

Supply Chain Management in the Big Data Era

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This chapter discusses various roles of smart information in Supply Chains (SC) of digital age and tries to answer an important question - What types of collaborative arrangements facilitate smart operations to improve planning, production and timely replenishment? We have conducted longitudinal case studies with firms practicing SC collaborations and also using smart information for operations. Based on the case analysis, the companies are further classified as ‘smart planning' and ‘traditional planning'. Research findings show the importance of aligning SC partnerships based on smart information requirements. These findings are based on case studies of Indian firms with global SC collaboration. We also discuss the role of Big Data for the companies using smart planning.

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Section: Literature On Supply Chain Information and Research Approachmentioning

confidence: 99%

How Smart Operations Help Better Planning and Replenishment?

Ramanathan

2017

Supply Chain Management in the Big Data Era

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“…Planning and decision making processes in supply chains heavily rely on forecasts. Accordingly, forecasting accuracy is a core factor that influences the performance of a supply chain (Zhao, Xie & Leung, 2002). Bullwhip effect is a prime example of how predictive inaccuracy can easily intensify through the supply chain (Chang & Lin, 2010), crippling the affected partners.…”

Section: Forecasting and Supply Chain Flexibilitymentioning

confidence: 99%

Supply Chain Flexibility: Managerial Implications

Önkal¹,

Aktaş²

2011

Supply Chain Management - Pathways for Research and Practice

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“…More information and shorter lead times lead to lower variance. More recent papers consider a variety of mathematical models of collaborative planning and forecasting arrangements: sharing inventory and demand information (Aviv, 2002), vendor managed inventories (Yu et al, 2002), and, by using simulation approach, an examination of the effects of forecasting model selection (Zhao et al, 2002).…”

Section: Demand Uncertainty In the Supply Chain: Collaborative Forecamentioning

confidence: 99%

“…The notion of sharing information is theoretically attractive, as the research has shown, but the question of how valuable it is to share has not been adequately addressed. Lee et al (2000), Aviv (2001) and Zhao et al (2002) all report substantial savings (20% +) from information sharing. But the benefits reported depend upon the often implausible assumptions made regarding the supply chain structure, and lack any empirical foundation.…”

Section: Demand Uncertainty In the Supply Chain: Collaborative Forecamentioning

confidence: 99%

Forecasting and operational research: a review

Fildes

Νικολόπουλος

Crone

et al. 2008

Journal of the Operational Research Society

227

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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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The impact of forecasting model selection on the value of information sharing in a supply chain

Cited by 184 publications

References 10 publications

How Smart Operations Help Better Planning and Replenishment?

How Smart Operations Help Better Planning and Replenishment?

Supply Chain Flexibility: Managerial Implications

Forecasting and operational research: a review

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