Bundle pricing in a two-stage supply chain with customer heterogeneity

This is the latest version of this item.

Official URL: http://dx.doi.org/10.1093/imaman/dpag022

This paper investigates the effectiveness of mixed bundling as a profit-enhancing strategy in a two-stage supply chain consisting of a supplier and a retailer. The retailer offers two products both individually and as a discounted bundle to a heterogeneous market, where customers have relatively high or relatively low valuations for each of the products. The supplier provides wholesale price incentives to support bundling. We examine both decentralized and centralized supply chain structures to assess the value of coordination and the robustness of bundling as a pricing lever. Through numerical analysis, we identify the conditions under which mixed bundling is most effective. Our results reveal that the degree of complementarity/substitutability of the bundled products plays a central role in shaping the demand and profitability effects of bundling in both decentralized and centralized supply chains. Furthermore, on average, bundling generates the largest supply chain gains when most customers have a relatively high valuation for one of the bundled products and a relatively low valuation for the other. In decentralized supply chains, we find that retailers, on average, offer slightly lower bundle discounts than suppliers, but generally absorb a higher share of the discount cost. Moreover, mixed bundling contributes more to profitability under decentralization than centralization, as it partially mitigates inefficiencies arising from double marginalization. Our results also highlight that although centralization enhances overall profitability, bundling can partially offset the inefficiencies of decentralized decision-making under certain conditions. Overall, the framework developed in this study provides managers with guidance on when bundling is likely to be effective and how to implement it in alignment with product and market characteristics, and supply chain constraints.