Demand Fulfillment in Multi-Stage Customer Hierarchies

Vogel, Sebastian

doi:10.1007/978-3-658-02864-0

Cited by 5 publications

(4 citation statements)

References 0 publications

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Order By: Relevance

“…its first derivative with respect to θ k is strictly negative. A formal proof can be found in Vogel (2013).…”

Section: The Ada Scheme For Decentral Plannersmentioning

confidence: 98%

“…We present the ADA scheme under which overall profit comes very close to the first best OCA benchmark with a central planner. To the knowledge of the authors, this allocation problem in multi-stage customer hierarchies was first characterized by Vogel (2013); our paper carves out the key insights developed there. We make the following contributions:…”

Section: Problem Statementmentioning

confidence: 99%

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Decentral allocation planning in multi-stage customer hierarchies

Vogel

Meyr

2015

European Journal of Operational Research

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“…its first derivative with respect to θ k is strictly negative. A formal proof can be found in Vogel (2013).…”

Section: The Ada Scheme For Decentral Plannersmentioning

confidence: 98%

Section: Problem Statementmentioning

confidence: 99%

Decentral allocation planning in multi-stage customer hierarchies

Vogel

Meyr

2015

European Journal of Operational Research

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“…Then, these steps are applied to the alternate with the second highest priority and so on. The reader who is interested in scientific research on optimization-based allocation planning and order promising is, for example, referred to Meyr (2009) and Quante (2009) for single-level andVogel (2014) for multi-level customer hierarchies.…”

Section: Atp Consumption By Examplementioning

confidence: 99%

Demand Fulfilment and ATP

Kilger¹,

Meyr

2014

Springer Texts in Business and Economics

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The planning process that determines how the actual customer demand is fulfilled is called demand fulfillment. The demand fulfillment process calculates the first promise date for customer orders and-thus-strongly influences the order leadtime and the on time delivery.1 In today's competitive markets it is important to generate fast and reliable order promises in order to retain customers and increase market share. This holds particularly true in an e-business environment: Orders are entered on-line in the e-business front end, and the customer expects to receive a reliable due date within a short time period.Further, e-business solutions have to support on-line inquiries where the customer requests a reliable due date without committing the order. The fast generation of reliable order promises gets more complex as • The number of products increases • Products are configured during the ordering process • The average product life cycles get shorter • The number of customers increases • Flexible pricing policies are being introduced • Demand variations increase and get less predictable. 1 In the following, we use the terms order promising and order quoting synonymously, as well as the terms promise and quote.

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“…Many scholars present linear programming-based approaches in which the aim is to maximise overall profits by integrating AP with production planning in assemble-to-order or make-to-order environments (Ball et al, 2004;Ervolina et al, 2009;Chen and Dong, 2014;Chiang and Hsu, 2014) or in make-to-stock environments (Lebreton, 2015;Meyr, 2009;Cano-Belm� an and Meyr, 2019). Vogel (2014) proposes a method for multi-stage customer hierarchies. He shows that the approach can lead to higher profits compared with profits achieved by an optimal central allocation approach, if demand forecast accuracy is very low.…”

Section: Literature Reviewmentioning

confidence: 99%