Capacity Management in Agricultural Commodity Processing and Application in the Palm Industry

Abstract

This paper examines the capacity investment decisions of a processor that uses a commodity input to produce both a commodity output and a by-product in the context of agricultural industries. We employ a multiperiod model to study the optimal one-time processing and (output) storage capacity investment decisions—in addition to the periodic processing and inventory decisions—when both input and output spot prices as well as production yield are uncertain. We characterize the optimal decisions and perform sensitivity analysis to investigate how spot price uncertainty affects the processor’s optimal capacity and profitability. Using a calibration based on the palm industry, we study (both numerically and analytically) the performance of a variety of heuristic capacity investment policies that can be used in practice. We find that if the yield uncertainty is ignored in capacity planning, then basing those plans on the average yield is preferable to basing them (as often occurs in practice) on the maximum yield. However, planning based on the average yield performs well only when the relative (processing-to-storage) capacity investment cost is high; otherwise, it leads to a significant loss of profit. We also find that ignoring spot price uncertainty in capacity planning results in a relatively small profit loss. In contrast, ignoring by-product revenue—which constitutes a small portion of total revenues—during capacity planning substantially reduces the processor’s profit. The online appendix is available at https://doi.org/10.1287/msom.2017.0624 .

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