Revenue management optimization for make-to-order and engineering-to-order manufacturing context

The order promising process for Make-To-Order (MTO) and Engineering-To-Order (ETO) companies usually implies not only verifying delivery quantity and due date feasibility but also negotiating prices with clients derived from product customization. The existence of variable operation costs due to process selection and volatile raw material prices, emphasizes the need for precise supplier choice and cost estimation for pricing. These decisions fall within the scope of Revenue Management (RM), which is addressed in this paper through a novel optimization model for companies with hybrid MTO/ETO manufacturing strategy and even extendable to Make-To-Stock (MTS) one. A Conceptual Framework is proposed to characterize the RM problem, systematically review existing literature, and justify the novelties of this research. The model is tested on a metal-mechanic company with characteristics not previously modelled, and evaluated under different scenarios, demonstrating its effectiveness providing a price acceptable for the customer as well as profitable for the company. • Revenue Management (RM) is crucial for ensuring profitability in Engineering-To-Order and Make-To-Order Environments. • A conceptual framework (CF) and a novel RM-model are developed to characterize and optimize the RM problem. • The CF is used to perform a literature review identifying gaps and the paper contribution. • The novel RM-model is validated in a real metal mechanic company.

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Publication Details

Journal
International Journal of Production Economics
Published
2025-06-24
DOI
https://doi.org/10.1016/j.ijpe.2025.109715
Citations
1
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
1.24
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article

Revenue management optimization for make-to-order and engineering-to-order manufacturing context

Alfredo Jiménez, M. M. E. Alemany, Ana Esteso, José María Cavero
1 citations
International Journal of Production Economics
Manufacturing Process and Optimization
1.24
article

Revenue management optimization for make-to-order and engineering-to-order manufacturing context

Alfredo Jiménez, M. M. E. Alemany, Ana Esteso, José María Cavero
article en
1 citations

Abstract

The order promising process for Make-To-Order (MTO) and Engineering-To-Order (ETO) companies usually implies not only verifying delivery quantity and due date feasibility but also negotiating prices with clients derived from product customization. The existence of variable operation costs due to process selection and volatile raw material prices, emphasizes the need for precise supplier choice and cost estimation for pricing. These decisions fall within the scope of Revenue Management (RM), which is addressed in this paper through a novel optimization model for companies with hybrid MTO/ETO manufacturing strategy and even extendable to Make-To-Stock (MTS) one. A Conceptual Framework is proposed to characterize the RM problem, systematically review existing literature, and justify the novelties of this research. The model is tested on a metal-mechanic company with characteristics not previously modelled, and evaluated under different scenarios, demonstrating its effectiveness providing a price acceptable for the customer as well as profitable for the company. • Revenue Management (RM) is crucial for ensuring profitability in Engineering-To-Order and Make-To-Order Environments. • A conceptual framework (CF) and a novel RM-model are developed to characterize and optimize the RM problem. • The CF is used to perform a literature review identifying gaps and the paper contribution. • The novel RM-model is validated in a real metal mechanic company.

International Journal of Production EconomicsVol. 288
Universitat Politècnica de València (ES)
Openalex Percentile: Top 18%
Manufacturing Process and Optimization
1.24
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Revenue management optimization for make-to-order and engineering-to-order manufacturing context — Alfredo Jiménez, M. M. E. Alemany, et al. · International Journal of Production Economics (2025) | TGRS Research Map | TGRS