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Strategic price bundling for online retail platforms considering consumer behavior of valuation discount

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  • Ting Chen
  • Xiaolong Guo
  • Feng Yang
  • Lin Tian

Abstract

Bundling has become an important operational tool for online retail platforms to attract consumers. Nevertheless, published empirical results on consumer behavior show that a bundle discount negatively influences the consumers’ perceived value of individual component products. We investigate how valuation discounts like these influence the online retail platforms’ decision optimization in bundling. Optimization models for mixed-joint and mixed-leader bundling are developed to analyze this effect. Based on the benchmark model of no-bundling, insightful implications are provided by comparing these three models. It is found that, in specified conditions, mixed-leader bundling outperforms mixed-joint bundling due to the negative effects of valuation discounts. Moreover, when the potential consumer pools of individual components are both large, mixed-joint bundling, which common knowledge considers the most profitable strategy, performs worse than the no-bundling strategy when valuation discounts are taken into account.

Suggested Citation

  • Ting Chen & Xiaolong Guo & Feng Yang & Lin Tian, 2023. "Strategic price bundling for online retail platforms considering consumer behavior of valuation discount," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(12), pages 2648-2664, December.
    • Handle: RePEc:taf:tjorxx:v:74:y:2023:i:12:p:2648-2664
    DOI: 10.1080/01605682.2023.2174051
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