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Offline Assortment Optimization in the Presence of an Online Channel

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  • Daria Dzyabura

    (Stern School of Business, New York University, New York, New York 10012)

  • Srikanth Jagabathula

    (Stern School of Business, New York University, New York, New York 10012)

Abstract

Firms are increasingly selling through both offline and online channels, allowing customers to experience the touch and feel of product attributes before purchasing those products. Consequently, the selection of products offered offline affects the demand in both channels. We address how firms should select an optimal offline assortment to maximize profits across both channels; we call this the showcase decision problem. We incorporate the impact of physical evaluation on preferences into the consumer demand model. Under this model, we show that the decision problem is NP-hard. Analytically, we derive optimal results for special cases and near-optimal approximations for general cases. Empirically, we use conjoint analysis to identify changes in consumer preferences resulting from physically evaluating products. For this application, we demonstrate gains in expected revenue of up to 40% due to accounting for the impact of offline assortment on the online sales.

Suggested Citation

  • Daria Dzyabura & Srikanth Jagabathula, 2018. "Offline Assortment Optimization in the Presence of an Online Channel," Management Science, INFORMS, vol. 64(6), pages 2767-2786, June.
    • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:6:p:2767-2786
    DOI: 10.287/mnsc.2016.2708
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    References listed on IDEAS

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    Cited by:

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    2. Zhisong Chen & Shong-Iee Ivan Su, 2021. "Consignment supply chain cooperation for complementary products under online to offline business mode," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 136-182, March.
    3. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    4. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    5. Hense, Jonas & Hübner, Alexander, 2022. "Assortment optimization in omni-channel retailing," European Journal of Operational Research, Elsevier, vol. 301(1), pages 124-140.
    6. Jin, Delong & Caliskan-Demirag, Ozgun & Chen, Frank (Youhua) & Huang, Min, 2020. "Omnichannel retailers’ return policy strategies in the presence of competition," International Journal of Production Economics, Elsevier, vol. 225(C).
    7. Schäfer, Fabian & Hense, Jonas & Hübner, Alexander, 2023. "An analytical assessment of demand effects in omni-channel assortment planning," Omega, Elsevier, vol. 115(C).
    8. Daria Dzyabura & John R. Hauser, 2019. "Recommending Products When Consumers Learn Their Preference Weights," Marketing Science, INFORMS, vol. 38(3), pages 417-441, May.
    9. Daria Dzyabura & Srikanth Jagabathula & Eitan Muller, 2019. "Accounting for Discrepancies Between Online and Offline Product Evaluations," Marketing Science, INFORMS, vol. 38(1), pages 88-106, January.
    10. Gupta, Vishal Kumar & Ting, Q.U. & Tiwari, Manoj Kumar, 2019. "Multi-period price optimization problem for omnichannel retailers accounting for customer heterogeneity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 155-167.
    11. Vasilyev, Andrey & Maier, Sebastian & Seifert, Ralf W., 2023. "Assortment optimization using an attraction model in an omnichannel environment," European Journal of Operational Research, Elsevier, vol. 306(1), pages 207-226.

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