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Prioritization of Customer Order Selection Factors by Utilizing Conjoint Analysis: A Case Study for a Structural Steel Firm

Authors: Burcu Akyildiz, Cigdem Kadaifci, Y. Ilker Topcu, Burc Ulengin

Abstract:

In today’s business environment, companies should  make strategic decisions to gain sustainable competitive advantage.  Order selection is a crucial issue among these decisions especially for  steel production industry. When the companies allocate a high  proportion of their design and production capacities to their ongoing  projects, determining which customer order should be chosen among  the potential orders without exceeding the remaining capacity is the  major critical problem. In this study, it is aimed to identify and  prioritize the evaluation factors for the customer order selection  problem. Conjoint Analysis is used to examine the importance level  of each factor which is determined as the potential profit rate per unit  of time, the compatibility of potential order with available capacity,  the level of potential future order with higher profit, customer credit  of future business opportunity, and the negotiability level of  production schedule for the order.

 

Keywords: Conjoint analysis, Profit Management, order prioritization, structural steel firm

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1090880

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References:


[1] H. H. Guerreroand G. M. Kern, "How to more effectively accept and refuse orders,” Production and Inventory Management Journal,vol. 29, no. 4, 1988, pp. 59-63.
[2] D. C. Whybark and J. Wijngaard, "Editorial: manufacturing-sales coordination,” International Journal of Production Economies, vol. 37, no. 1, 1994, pp. 1-4.
[3] F. H. Harris and J. P. Pinder, "A revenue management approach to demand management and order booking in assemble-to-order manufacturing,” Journal of Operations Management, vol. 13, no. 4, 1995, pp. 299-309.
[4] V. Sridharan, "Managing capacity in tightly constrained systems,” International Journal of Production Economics, vol. 56-57, no. 1, 1998, pp. 601-610.
[5] P.E. Green and V. Srinivasan, "Conjoint Analysis in Consumer Research: Issues and Outlook,” Journal of Consumer Research, vol. 5, no. 2, 1978, pp. 103–212.
[6] J. Wang, J. Q. Yang, and H. Lee, "Multicriteria Order Acceptance Decision Support in Over-Demand Job Shops: A Neural Network Approach,” Mathematical Computer Modeling, vol. 19, no. 5, 1994, pp. 1-19.
[7] Y. F. Hung and T. Y. Lee, "Capacity rationing decision procedures with order profit as a continuous random variable,” International Journal of Production Economies, vol. 125, 2010, pp. 125-136.
[8] F. Arredondo and E. Martinez, "Learning and adaptation of a policy for dynamic order acceptance in make-to-order manufacturing,” Computers & Industrial Engineering, vol. 58, 2010, pp. 70-83.
[9] S. Mestry, P. Damodaran, and C-S Chen, "A branch and price solution approach for order acceptance and capacity planning in make-to-order operations,” European Journal of Operational Research, vol. 211, 2011, pp. 480–495.
[10] S. Nahmias and W. S. Demmy, "Operating characteristics of an inventory system with rationing,” Management Science, vol. 27, no. 11, 1981, pp. 1236-1245.
[11] H. C. Haynsworth and B. A. Price, "A model for use in the rationing of inventory during lead-time,” Naval Research Logistics, vol. 36, no. 4, 1989, pp. 491-506.
[12] D. B. Rinks, "Rationing safety stock in the USAF’s multi-echelon inventory system,” Engineering Costs and Production Economics, vol. 17, no. 1-4, 1989, pp. 99-109.
[13] A. Y. Ha, "Inventory rationing in a make-to-stock production system with several demand classes and lost sales,” Management Science, vol. 3, no. 8, 1997, pp. 1093-1103.
[14] N. Balakrishnan, V. Sridharan, and J. W. Patterson, "Rationing capacity between two product classes,” Decision Sciences, vol. 27, no. 2, 1996, pp. 185-214.
[15] J. W. Patterson, N. Balakrishnan, and V. Sridharan, "An experimental comparison of capacity rationing models,” International Journal of Production Research, vol. 35, no. 6, 1997, pp. 1639-1649.
[16] M. Barut and V. Sridharan, "Revenue management in order-driven production systems,” Decision Sciences, vol. 36, no. 2, 2005, pp. 287- 316.
[17] C. Oğuz, F. S. Salman, and Z. Bilgintürk Yalçın, "Order acceptance and scheduling decisions in make-to-order systems,” International Journal of Production Economics, vol. 125, 2010, pp. 200–211.
[18] K. P. Yoon and C-L. Hwang, Multi Attribute Decision Making: An Introduction. Sage Univ. Papers Series, Quantitative Applications in the Social Sciences, No 07-104, London: Sage Pub., 1995.
[19] B. K. Orme, Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research, Research Publishers, 2005.
[20] D. Raghavarao, J. B. Wiley, and P. Chitturi, Choice-Based Conjoint Analysis: Models and Designs, Chapman and Hall, 2010.
[21] V.R. Rao,Applied Conjoint Analysis, Springer, 2013.
[22] URL-1 ,accessed at 15.10.2013 (Sawtooth software).