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Joint optimization of inventory control and product placement on e-commerce websites using genetic algorithms

Author

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  • Yan-Kwang Chen

    (National Taichung University of Science and Technology)

  • Fei-Rung Chiu

    (Overseas Chinese University)

  • Hung-Chang Liao

    (Chung-Shan Medical University)

  • Chien-Hua Yeh

    (National Taichung University of Science and Technology)

Abstract

Prior research had shown that the design of product listing pages has significant influence on the sales volume on an e-commerce website. This study focused on product placement in designing product listing pages; that is, how venders of online stores place their products over the product listing pages for maximization of profit. When trying to increase the sales volume through a better website design, it is imperative to keep a close watch on inventory replenishment so as to reduce business cost. Therefore, this study proposed a visual-attention-dependent demand inventory model for determining the optimal product placement and inventory replenishment decisions that jointly maximize the total profit under the arrangement constraints. This model assumes that visual stimuli such as image size and location have a significant effect on product demand. The substitution effect between products on demand was also examined. Then a genetic algorithms-based search method was employed to solve the model. Finally, the validity of the proposed model was illustrated with example problems.

Suggested Citation

  • Yan-Kwang Chen & Fei-Rung Chiu & Hung-Chang Liao & Chien-Hua Yeh, 2016. "Joint optimization of inventory control and product placement on e-commerce websites using genetic algorithms," Electronic Commerce Research, Springer, vol. 16(4), pages 479-502, December.
    • Handle: RePEc:spr:elcore:v:16:y:2016:i:4:d:10.1007_s10660-016-9216-9
    DOI: 10.1007/s10660-016-9216-9
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    References listed on IDEAS

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