Demand forecasting for supply processes in consideration of pricing and market information

Reiner, Gerald; Fichtinger, Johannes

doi:10.1016/j.ijpe.2008.08.009

Cited by 23 publications

(14 citation statements)

References 19 publications

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“…Gavirneri, 2006;Reiner and Fichtinger, 2009). For price-elastic products, when the price of an item changes, the customer demand will also change.…”

Section: Factors Influencing the Bullwhip Effectmentioning

confidence: 99%

Judgement and Supply Chain Dynamics

Syntetos¹,

Boylan²,

Dangerfield³

2017

System Dynamics

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Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and 'laboratory' studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper.

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“…Gavirneri, 2006;Reiner and Fichtinger, 2009). For price-elastic products, when the price of an item changes, the customer demand will also change.…”

Section: Factors Influencing the Bullwhip Effectmentioning

confidence: 99%

Judgement and Supply Chain Dynamics

Syntetos¹,

Boylan²,

Dangerfield³

2017

System Dynamics

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show abstract

“…However, Reiner and Fichtinger (2009) model the effect of different forecast model by including price effect. It is shown from the case study of a two stage supply chain with weekly empirical sales and pricing data that different forecast model might have different accuracy of predicting the future demand.…”

Section: Scm Simulationmentioning

confidence: 99%

Steel supply chain management by simulation modelling

Sandhu

Helo

Kristianto

2013

Benchmarking: An International Journal

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The aim of this paper is to propose a simulation study of the "steel supply chain" to demonstrate the effect of inventory management and demand variety on the bullwhip effect mitigation. Design/methodology/approach -The relevant literature is reviewed, and then the simulation model proposed.Findings -This study identifies reasons for sharing information under varying levels of demand and some variants, and demonstrates the benefits of mitigating the bullwhip effect by applying a design of experiment. It is shown that the information sharing is able to mitigate the bullwhip effect in the steel supply chain by extending the order interval and minimising the order batch size. Research limitations/implications -This study explores the factors associated with the bullwhip effect. This research is focused on built-to-order simulation, so the results are only oriented on the basis of orders; hence a simultaneous order-and forecast-based steel supply chain should be carried out in the future. Practical implications -This framework is expected to provide a convenient way to measure the optimum inventory level against a limited level of demand uncertainty, and thus enterprises can promote the supply chain coordination. Originality/value -An innovative simulation model of the "steel supply chain" is proposed, which includes information sharing in the simulation model. Furthermore, dynamic scheduling is shown by applying a continuous ordering and order prioritization rule to replace traditional scheduling methods.

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“…From the literature, a gap emerges in linking demand segments to supply according to its feature and characteristics. So far, limited work has been carried out to match demand and supply and, within tourism and the service industries in general, the main focus is still on either forecasting (Fei, Lu, & Lju, ; Reiner & Fichtinger, ), demand fluctuations and seasonality (Kandampully, ), or the service encounter (Brown & Kirmani, ; Mattila & Enz, ; Matttila, Grandey, & Fisk, ; Sharma, Mathur, & Abhinav, ). The present paper broadens the existing knowledge and provides an integrated conceptual framework to jointly analyze demand and supply for small hospitality firms, and specifically agritourism firms.…”

Section: Discussionmentioning

confidence: 99%

An integrated demand and supply conceptual framework: Investigating agritourism services

Brandano

Osti

Pulina

2018

Journal of Tourism Research

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The present paper offers an integrated conceptual framework to jointly analyze demand and supply of agritourism firms and aims to identify motivations along with perceptions of externalities that influence the choice of a firm over another. On the supply side, a cluster analysis identifies homogenous groups of agritourism firms. On the demand side, a factor analysis is run on a set of motivations and environmental externalities and a probabilistic model estimates the determinants that influence the likelihood to choose 1 type of firm over the other. The results show that traditional and genuine food, culture, and authenticity are elements that determine the choice of 1 firm over another. A further contribution of this paper is the identification of environmental externalities as determinants of the attractiveness of a firm. From a marketing perspective, linking demand to supply is essential to determine product development strategies capable of satisfying actual and potential customers. Several strategies are proposed to different types of agritourism firms to attract and retain customers.

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Demand forecasting for supply processes in consideration of pricing and market information

Cited by 23 publications

References 19 publications

Judgement and Supply Chain Dynamics

Judgement and Supply Chain Dynamics

Steel supply chain management by simulation modelling

An integrated demand and supply conceptual framework: Investigating agritourism services

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