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Whether to invest in process development that can reduce the unit cost and thereby raise future profits or to conserve cash and reduce the likelihood of bankruptcy is a key trade‐off faced by many startup firms that have taken on debt. We explore this trade‐off by examining the production quantity and cost reducing R&D investment decisions in a two period model wherein a startup firm must make a minimum level of profit at the end of the first period to survive and operate in the second period. We specify a probabilistic survival measure as a function of production and investment decisions to track and manage the risk exposure of the startup depending on three key market factors: technology, demand, and competitor's cost. We develop managerial insights by characterizing how to create operational hedges against the bankruptcy risk: if a startup makes a “conservative” investment decision, then it also selects an optimal quantity that is less than the monopoly level and hence sacrifices some of first period expected profits to increase its survival chances. If it decides to invest “aggressively,” then it produces more than the monopoly level to cover the higher bankruptcy risk. We also illustrate that debt constraint shrinks the decision space, wherein such process investments are viable.

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W e consider a firm that procures an input commodity to produce an output commodity to sell to the end retailer. The retailer's demand for the output commodity is negatively correlated with the price of the output commodity. The firm can sell the output commodity to the retailer through a spot, forward or an index-based contract. Input and output commodity prices are also correlated and follow a joint stochastic price process. The firm maximizes shareholder value by jointly determining optimal procurement and hedging policies. We show that partial hedging dominates both perfect hedging and no-hedging when input price, output price, and demand are correlated. We characterize the optimal financial hedging and procurement policies as a function of the term structure of the commodity prices, the correlation between the input and output prices, and the firm's operating characteristics. In addition, our analysis illustrates that hedging is most beneficial when output price volatility is high and input price volatility is low. Our model is tested on futures price data for corn and ethanol from the Chicago Mercantile Exchange.

We study a supply chain where a retailer buys from a supplier who faces financial constraints. Informational problems about the supplier's demand prospects and production capabilities restrict her access to capital. By committing to a minimum purchase quantity, the retailer can mitigate these informational problems and expand the supplier's feasible production set. We assume a newsvendor model of operations and analyze the strategic interaction of the two parties as a sequential game. Key parameters in our model are the supplier's ex ante credit limit, her informational transparency-which conditions the amount of additional capital released by the commitment-and the demand characteristics of the final market. We show that in equilibrium the supplier can benefit from a lower ex ante credit limit or lower informational transparency. The retailer always benefits from an increase in these parameters. We also indicate limits to the commitment approach: under certain conditions, the retailer may prefer to relax the supplier's financial constraint by adjusting the wholesale price, or a combination of wholesale price and commitment. Our study provides a novel perspective on capital market frictions in supply chains.