Abstract Online platforms typically store multiple products in their warehouses, which often run out of space. Hence we are motivated to study how platforms can effectively allocate their limited warehouse capacity among different products. We establish a game-theoretic model to investigate the optimal warehouse capacity allocation strategy of a platform that serves the dual role of a marketplace and a reseller. Our research reveals that, in the single-product case, a platform’s profit increases – first convexly and then concavely – with warehouse capacity. Second, we study the optimal warehouse capacity allocation strategy of a platform in the case of multiple products with different characteristics. We establish that the capacity allocated to a product increases with the commission rate and with the platform’s unit procurement cost, and also as the retailer’s unit procurement cost decreases. However, the capacity allocation for products characterized by high fixed warehouse operating costs or high unit product volumes depends to a large extent on the platform’s total warehouse capacity. The numerical study verifies our theoretical results and generates more management insights. We complete our study with two extensions. The first shows that platforms without warehouses cannot use the same warehouse operation strategy as those that do have warehouses unless (a) the warehouse investment cost coefficient is relatively low and (b) the platform intends to manage all products in its newly built warehouse. Our second extension demonstrates that a platform is generally more willing to store and sell high-quality (than low-quality) products.

    Highlights An online platform serves dual roles of a marketplace and a reseller. Consumers have heterogeneous preferences for the platform/retailer. The platform stores multiple products in its warehouse, which has a capacity constraint. We investigate the platform’s warehouse capacity allocation scheme for multiple products.


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    Titel :

    Online platforms’ warehouse capacity allocation strategies for multiple products


    Beteiligte:
    Hu, Shu (Autor:in) / Yu, Dennis Z. (Autor:in) / Fu, Ke (Autor:in)


    Erscheinungsdatum :

    2023-05-16




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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