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Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives

Author

Listed:
  • Jiang, Yuanchun
  • Liu, Yezheng
  • Shang, Jennifer
  • Yildirim, Pinar
  • Zhang, Qingfu

Abstract

Online promotion helps enhance brand awareness and boost sales. Although it attracts customer traffic, an ill-conceived price promotion has serious repercussions because it disproportionately draws bargain hunters, results in profit erosion and causes operational chaos due to erratic demands. This research proposes a long-term optimization model to help dual channel (click-and-mortar) retailers understand the conditions necessary to promote products online across all markets. When partial markets are recommended, we investigate how to price and select the market portfolio for promotion in each time period. We develop a multi-objective evolutionary algorithm to efficiently solve complex and large-scale problems. Both theoretical analysis and numerical study show that the proposed model outperforms the conventional strategy of promoting online across the board.

Suggested Citation

  • Jiang, Yuanchun & Liu, Yezheng & Shang, Jennifer & Yildirim, Pinar & Zhang, Qingfu, 2018. "Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives," European Journal of Operational Research, Elsevier, vol. 267(2), pages 612-627.
  • Handle: RePEc:eee:ejores:v:267:y:2018:i:2:p:612-627
    DOI: 10.1016/j.ejor.2017.11.059
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