Product selection and pricing policy of assemble-to-order manufacturer based on heterogeneous demands

被引:0
|
作者
Li Y. [1 ]
Huang B. [2 ]
Huang H. [3 ]
机构
[1] School of Economics and Management, Chongqing Normal University, Chongqing
[2] School of Economics and Business Administration, Chongqing University, Chongqing
[3] School of Business, Hunan Agricultural University, Changsha
关键词
assemble-to-order; heterogeneous consumers; multi-markets; pricing; product selection;
D O I
10.13196/j.cims.2022.07.030
中图分类号
学科分类号
摘要
Considering the situation that an Assemble-to-Order (ATO) manufacturer provided multiple products from a same product family to multi-markets, where the utilities of a same product to different consumers were different, and decreased with the increase of its time for sale on markets, a product selection and pricing model of ATO manufacturers was proposed based on heterogeneous consumers' demands in multi-markets, and the product selection and pricing policy of the manufacturer and corresponding replenishment policy of its specific and common parts were studied according to the heterogeneous consumers' preference and choice behavior. A genetic simulated annealing hybrid algorithm was designed to solve the model. Finally, an experimental study and a case study of the product selection and pricing policy of Apple's iPhone were used to illustrate the proposed model. It was found that the manufacturer should provide different product sets with a same flagship product for different markets at different prices, and timely adjust the product sets and selling prices for maximizing its profit. © 2022 CIMS. All rights reserved.
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页码:2263 / 2272
页数:9
相关论文
共 26 条
  • [1] LEE H, EUN Y., Discovering heterogeneous consumer groups from sales transaction data, European Journal of Operational Research, 280, 1, pp. 338-350, (2020)
  • [2] LI Yuyu, HUANG Bo, Replenishment policy of ATO supply chain under mixed replenishment mode based on supplier alliance [J], Journal of Industrial Engineering and Engineering Management, 30, 2, pp. 124-132, (2016)
  • [3] BENDERBAL H H, BENYOUCEF L., Machine layout design problem under product family evolution in reconfigurable manufacturing environment: A two-phase-based AMOSA approach, The International Journal of Advanced Manufacturing Technology, 104, 1, pp. 375-389, (2019)
  • [4] AHMADI T, ATAN Z, DE KOK T, Et al., Optimal control policies for assemble-to-order systems with commitment lead time, USE Transactions, 51, 12, pp. 1365-1382, (2019)
  • [5] GALIZIA F G, ELMARAGHY H, BORTOLINI M, Et al., Product platforms design, selection and customisation in high-variety manufacturing, International Journal of Production Research, 58, 3, pp. 893-911, (2020)
  • [6] TANG C S, YIN R., The implications of costs, capacity, and competition on product line selection, European Journal of Operational Research, 200, 2, pp. 439-450, (2010)
  • [7] JALALI H, CARMEN R, VAN NIEUWENHUYSE I, Et al., Quality and pricing decisions in production/inventory systems, European Journal of Operational Research, 272, 1, pp. 195-206, (2019)
  • [8] AKQAY Y, NATARAJAN H P, XU S H., Joint dynamic pricing of multiple perishable products under consumer choice, Management Science, 56, 8, pp. 1345-1361, (2010)
  • [9] GALLEGO G, WANG R X., Multiproduct price optimization and competition under the nested logit model with product-differentiated price sensitivities, Operations Research, 62, 2, pp. 450-461, (2014)
  • [10] HEREON A., Dynamic pricing vs. acquiring information on consumers' heterogeneous sensitivity to product freshness [J], International Journal of Production Research, 52, 3, pp. 918-933, (2014)