On the product line selection problem under attraction choice models of consumer behavior

被引:41
作者
Schoen, Cornelia [1 ]
机构
[1] Leibniz Univ Hannover, GISMA Business Sch, D-30167 Hannover, Germany
关键词
Pricing; Product line design; CONJOINT-ANALYSIS; ALGORITHM; DESIGN;
D O I
10.1016/j.ejor.2010.01.012
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Product line design (PLD) involves important decisions at the interface of operations and marketing that are very costly to implement and change, and, simultaneously, determinant for market success. To evaluate the financial performance of a product line, a number of mathematical programming approaches have been proposed. Problem formulations are typically mixed or pure integer non-linear optimization models that are intractable for exact solution - in particular when empirically supported consumer choice models are incorporated. In this note, we present an exact approach for determining a profit-maximizing product line with continuous prices when consumers choose among available products according to a general and widely applied attraction choice model including the MNL, the BTL, the MCI, and approximately the first choice model. In particular, we show how to efficiently exploit the structural properties resulting from attraction models when consumer behavior is (a) modelled at the aggregate level or (b) disaggregated into customer segments in such a way that each segment can be offered a customized price - a strategy that firms more and more engage in, recognizing it to be not only very profitable but also implementable in the era of e-business. Under these assumptions, we can transform the standard MINLP formulation of the PLD problem into a more convenient convex MIP that can be solved globally with current solvers even for large instances with ten-thousands of products in reasonable time. Therefore our work contributes by accommodating a new trend increasingly encountered in practice and by providing an efficient exact approach to profit-driven PLD for real-world applications. (C) 2010 Published by Elsevier B.V.
引用
收藏
页码:260 / 264
页数:5
相关论文
共 36 条
[1]  
[Anonymous], 2007, Conjoint measurement, DOI [10.1007/978-3-540-71404-0_17, DOI 10.1007/978-3-540-71404-0_17]
[2]  
[Anonymous], 2002, Discrete choice methods with simulation
[3]   Putting one-to-one marketing to work: Personalization, customization, and choice [J].
Arora, Neeraj ;
Dreze, Xavier ;
Ghose, Anindya ;
Hess, James D. ;
Iyengar, Raghuram ;
Jing, Bing ;
Joshi, Yogesh ;
Kumar, V. ;
Lurie, Nicholas ;
Neslin, Scott ;
Sajeesh, S. ;
Su, Meng ;
Syam, Niladri ;
Thomas, Jacquelyn ;
Zhang, Z. John .
MARKETING LETTERS, 2008, 19 (3-4) :305-321
[4]   MARKET SHARE THEOREM [J].
BELL, DE ;
KEENEY, RL ;
LITTLE, JDC .
JOURNAL OF MARKETING RESEARCH, 1975, 12 (02) :136-141
[5]   Optimizing product line designs: Efficient methods and comparisons [J].
Belloni, Alexandre ;
Freund, Robert ;
Selove, Matthew ;
Simester, Duncan .
MANAGEMENT SCIENCE, 2008, 54 (09) :1544-1552
[6]  
Bitran G., 2003, Manufacturing & Service Operations Management, V5, P203, DOI 10.1287/msom.5.3.203.16031
[7]   Conjoint optimization: An exact branch-and-bound algorithm for the share-of-choice problem [J].
Camm, JD ;
Cochran, JJ ;
Curry, DJ ;
Kaman, S .
MANAGEMENT SCIENCE, 2006, 52 (03) :435-447
[8]   Technical note: Mathematical properties of the optimal product line selection problem using choice-based conjoint analysis [J].
Chen, KD ;
Hausman, WH .
MANAGEMENT SCIENCE, 2000, 46 (02) :327-332
[9]   Personalized pricing and quality differentiation [J].
Choudhary, V ;
Ghose, A ;
Mukhopadhyay, T ;
Rajan, U .
MANAGEMENT SCIENCE, 2005, 51 (07) :1120-1130
[10]  
Cooper L.G., 1988, MARKET SHARE ANAL