Direct Trade Sourcing Strategies for Specialty Coffee

Problem definition : Leading specialty coffee roasters rely on direct trade to source premium coffee beans. We examine a roaster who sells two basic types of roasts: (1) a single-origin roast sourced from a specific locale and (2) a blend roast that uses a mix of beans from sources that vary over the course of a year. The prices of blend roasts are lower than those of single-origin roasts and appeal to a larger market. We study how characteristics of the operating and market environment affect the optimal sourcing strategy for single-origin beans. Methodology/results : We develop a two-stage stochastic program with recourse that reflects these characteristics. A roaster has the option to allocate some of the single-origin beans for sale under a blend label, known as downward substitution. We identify three distinct optimal sourcing strategies—specialized (no downward substitution), diversified (consistent downward substitution), and mixed (between these extremes)—and show that they are robust under different definitions of yield and demand. Managerial implications : We identify four main insights: (1) Two factors determine which strategy is optimal: the mean price of the inferior product (blend label) and the marginal cost of the superior product (single-origin label). (2) When compared with the newsvendor model, we find distinct structural differences across strategies. For example, whereas the effects of increasing uncertainty on optimal quantity align with the newsvendor model under a mixed strategy, the effects are distinctly different under specialized and diversified strategies (e.g., monotonic decreasing behavior for specialized, no change in quantity under diversified). (3) The weighted average price of an agricultural product is decreasing in negative yield–price correlation. We coin this as the “farmer’s curse,” which carries lessons for direct trade sourcing (e.g., advocating against paying the grower at postharvest market prices). (4) We find evidence of a virtuous feedback loop wherein the grower–roaster relationship becomes stronger over time. Our findings also point to a simple signal that policymakers may use to identify coffee growing locales where targeted interventions can improve grower welfare.