Revenue management for make-to-order manufacturing systems with a real-life application


BAYKASOĞLU A., SUBULAN K., Gucdemir H., DUDAKLI N., EREN AKYOL D.

ENGINEERING ECONOMIST, cilt.65, sa.1, ss.27-65, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65 Sayı: 1
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1080/0013791x.2019.1571145
  • Dergi Adı: ENGINEERING ECONOMIST
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, EconLit, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.27-65
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Due to successful applications of revenue management in the airline industry, in recent years, there has been a growing interest to adopt revenue management in make-to-order (MTO) manufacturing systems. Several interrelated decision problems such as order acceptance/rejection, short-term capacity planning, due date assignment, and order scheduling need to be studied simultaneously in order to manage revenues effectively in MTO manufacturing systems. Both the producer's and customer's requirements need to be taken into account through some negotiation mechanisms that are sensitive to the service-level reputation of the manufacturing companies. In this article, we propose a new dynamic bid price-based revenue management model that considers all of the aforementioned decision problems simultaneously. A simulation optimization approach is utilized in order to determine the best possible values of control parameters for bid price, due date assignment, and price increment/reduction mechanisms. The performance of the proposed integrated revenue management model is tested on both a hypothetical example and a real problem of a bridal gown company. The computational results show that the proposed model provides significant improvements in total revenue compared to other static and dynamic bid price policies.