A revenue management approach to demand management and order booking in assemble‐to‐order manufacturing

Abstract

Revenue management is an order acceptance and refusal process that employs differential pricing strategies and stop sales tactics to reallocate capacity, enhance delivery reliability and speed, and realize revenue from change order responsiveness in order to maximize the revenue from pre-existing capacity. While previously considered primarily as a tool of service operations, revenue management has considerable potential for assemble to order (ATO) manufacturing environments. Increasing demand for customer responsiveness has created service-oriented manufacturing environments suitable for the application of revenue management methods. This paper applies revenue management concepts and techniques to ATO manufacturing environments and presents models for optimal pricing and capacity decisions.* Corresponding author. the airline, railway, cruise ship (Belobaba, 1989;Smith et al., 1992), hotel and resort (Kimes, 1989;Hanks et al., 1992), health care (Chapman and Cannel, 1992), electric utility, car rental, broadcasting advertising, entertainment, printing and publishing, and telecommunications industries. While previously considered primarily as a tool of service operations, revenue management has considerable potential for manufacturing operations. Increased demand for shorter and more reliable delivery times and for change order responsiveness in manufacturing create the need for, and profit potential from, revenue management methods. This paper synthesizes revenue management theory, concepts and techniques, and demonstrates their applicability for assemble-toorder (ATO) manufacturing.Revenue management helps firms reallocate undifferentiated units of capacity to alternative market 0272-6963/95/$09.50 © 1995 Elsevier Science B.V. All fights reserved SSDI 0272-6963(95)00029-1

Revenue management for manufacturing companies

“…Low (1974) studies a semi-Markov decision process for determining optimal pricing policies for a M/M/c queue. Harris and Pinder (1995) consider an assemble-to-order manufacturing company and determine optimal pricing and capacity reallocation policies for a static revenue management problem with an arbitrary number of customer classes. Gallego and van Ryzin (1997) consider pricing a given set of inventories of components that go into finished products over a finite time horizon.…”

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

“…For this purpose, some works consider various classes of customers in the order acceptance procedure and dierent priority rules are presented to meet the expectations of dierent customer segments. Harris and Pinder (1995) consider an assemble-to-order manufacturing company and determine optimal pricing and capacity reallocation policies for a revenue management problem with an arbitrary number of customer classes. Keskinocak et al (2001) Another part of the literature emphasizes that proper negotiations with customers on the order terms is a promising avenue to mange order acceptance problems (Calosso et al, 2004;Cakravastia and Nakamura, 2002).…”

“…Harris and Pinder (1995) considered a make-to-order manufacturing company and determined optimal pricing and capacity reallocation policies for a revenue maximizing problem with an arbitrary number of customer classes. Keskinocak et al (2001) studied several online and oine algorithms for quoting various lead times to dierent customer classes where revenues obtained from the customers are sensitive to the lead time.…”

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

“…Examples of the practical application of planning models are provided by Tang and Liu (2007) and Tang, Liu, Rong, and Yang (2000). Starting in the mid-90's, initial works of Balakrishnan, Sridharan, and Patterson (1996), Harris and Pinder (1995) and Patterson, Balakrishnan, and Sridharan (1997) investigate the application of RM methods to manufacturing environments in general. Models of capacity control in m-t-o environments, specifically, are later presented by Barut and Sridharan (2005), Defregger and Kuhn (2007), Gallien, Le Tallec, and Schoenmeyr (2004), Gupta and Wang (2004) and Jalora (2006), all considering the sequential order acceptance for multiple offered products with exogenous delivery dates with respect to expected demand.…”

“…At ThyssenKrupp VDM the capacity of the majority of production units can only be expanded with substantial capital infusion, time lag, and downtime. Therefore, adapting available capacity to short-term fluctuations of demand is not practical (Harris and Pinder 1995). Further, Barut and Sridharan (2005) observe that quickly adding capacity could lead to a glut and seriously jeopardize the health of a company in the long term.…”