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• W128793577 abstract "INTRODUCTION The ability to attract customer orders has long been recognized as one of the key success factors for process-focused production or job shops. Scant attention however has been devoted in the literature to the customer acceptance decision. That is, the decision as to whether a customer should in fact be accepted once it is received. This decision is part of the firm's demand management function. Guerrero and Kern (1988) point out the importance of the customer acceptance decision: Under any circumstances, accepting orders without considering their possibly costly impact on capacity can lead to paying for the privilege of accepting an order (p. 59). The need for acceptance decision rules is also addressed by Matsui (1982, 1985) and others. Guerrero and Kern (1988) suggest a framework for demand management. From a day-today perspective, a simple demand management system, as shown in Figure 1, includes entry, accumulation, establishment of priority, precapacity allocation, and acceptance decision. A well developed demand management system offers at least two advantages for the firm. First, shop capacity can be more effectively planned and controlled. Second, realistic customer due date commitments can be made. Traditionally, managers have a tendency toward accepting all incoming orders. However, some customer orders may in fact not be a good match with current shop capacity. Two specific questions arise: (a) What is the relationship between system performance and the customer acceptance decision process? (b) What types of decision rules might be adopted to assist managers in accepting customer orders in a process-focused production system? Despite the importance of control and acceptance in practice, researchers have published very little on the development of effective answers to these questions. There are several important factors that impact customer acceptance decisions. These factors include the decision period (the period of time over which orders may be collected before acceptance decisions must be made), size of the order, due date requirements, current capacity constraints, and preference (e.g. profit margin, customer credit, etc.). The production system considered in this research is a make-to-order, non-MRP, process-focused production shop. Process-focused production systems are commonly referred to as job shops or intermittent production because products move from department to department in jobs that are normally determined by customer orders. An acceptance decision is considered on a micro level for each individual order. Fixed capacity is assumed in the shop and due dates are the function of estimated processing time and set-up time. The primary purpose of this research is to test an acceptance algorithm, the JOA model, for the customer acceptance decision in a process-focused production system. REVIEW OF LITERATURE Little attention and effort has been directly devoted to demand management in the literature. Prior research has addressed demand management primarily in broad terms, for example, as demand forecasting, entry, due date promising, customer service, and other customer contact-related terms (Vollmann, Berry, & Whybark, 1988). Most research efforts related to demand management have been directed toward aggregate level decisions in an MRP environment, such as demand forecasting and the interaction between demand management and master production scheduling (MPS). McClelland (1988), for example, provides guidelines for the selection of an appropriate master scheduling method for a make-to-order firm to improve promising. Although job shop scheduling has an interactive relationship with demand management, including the individual acceptance policy, job shop studies do not normally consider demand management decisions. …" @default.
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• W128793577 title "Customer Order Acceptance Decision Models for a Process-Focused Production System" @default.
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