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We formulate and analyze a stylized dynamic model of a price-taking firm that manages production and capacity, uses only internal financing, and faces stochastic market environments. The firm has two operationally independent production facilities, each of which makes two products, and a cash reserve that finances all operations and dividend issuance. Each period the firm chooses the amount of dividend to issue, and at each facility it chooses production quantities and amounts of capacity to augment or divest. Relevant market data are exogenous and evolve stochastically. We completely characterize the optimal policy and the endogenous values of the capacities and cash reserve, and show that they invite a real-option interpretation. We find that internal financing creates a spillover between the endogenous values of the two operationally independent facilities, and we specify how this leads to interdependence of their optimal policies. We show that an "invest/stay put/divest" (ISD) policy remains optimal for partially irreversible investments, but internal financing changes the ISD thresholds. If the exogenous data are intertemporally independent, an internally financed firm is less likely to issue dividends or to expand capacity than if it were in a perfect capital market. As the market becomes more volatile, the endogenous values of capacities and cash increase, and the firmbecomes more reluctant to issue dividends. [ABSTRACT FROM AUTHOR]

Manufacturers manage interrelated flows of material and cash. Material needs capital, and sales contribute cash. Therefore, it may be beneficial to coordinate operational and financial decisions. We study a dynamic model of coordination in an equity-financed firm in which inventory and financial decisions interact in the presence of demand uncertainty, financial constraints, and a risk of default. The criterion is to maximize the expected present value of dividends net of capital subscriptions. The optimal target inventory level and financial decision variables are non-decreasing functions of the levels of inventory and retained earnings. Some important attributes of an optimal policy remain the same regardless of whether default precipitates Chapter 7 of Chapter 11 bankruptcy. The optimal policy is myopic, and if pertinent cost functions are piecewise linear, it is characterized with simple formulas. We show that the methods of inventory theory are useful in analyzing models of operational and financial coordination. [ABSTRACT FROM AUTHOR]

We study lot-size policies in a serial, multistage manufacturing/inventory system with two key generalizations, namely (1) random yields at each production stage and (2) an autoregressive demand process. Previous research shows that the optimal policies in models with random yields (even in models with a single installation) lack the familiar order-up-to structure and are not myopic. Thus, dynamic programming algorithms are needed to compute optimal policies, and one encounters the "curse of dimensionality"; this is exacerbated here by the need to expand the size and dimension of the state space to accommodate the autoregressive demand feature. Nevertheless, although our model is more complex, we prove that there is an optimal policy with the order-up-to feature and, more importantly, that the optimal policy is myopic. This avoids the computational burden of dynamic programming. Our results depend on two assumptions concerning the stochastic yield, namely that the expected yield at a work station is proportional to the lot size, and the distribution of the deviation of the yield from its mean does not depend on the lot size. We introduce the concept of echelon-like variables, a generalization of Clark and Scarf's classical concept of echelon variables, to derive the structure of optimal policies. Furthermore, we show that the same kind of policy is optimal for several criteria: infinite-horizon discounted cost, infinite-horizon long-run average cost, and finite-horizon discounted cost (with the appropriate choice of the salvage value function). [ABSTRACT FROM AUTHOR]

In a factory with a given employment level, there are often opportunities to make adjustments to that level via overtime, the use of subcontractors, a curtailed work week, etc. These temporary adjustments are unlike those m production smoothing models where any change in the employment level during one period is earned over to the beginning of the next one For a single product having stochastic demand, we characterize optimal production policies when the temporary adjustments have proportional costs Other production costs in the model are proportional to the quantity produced and expected inventory holding and penalty costs are convex. The cases treated include nonstationary finite horizon stationary finite horizon, discounted cost, average cost, and excess demand being either backlogged or lost. The infinite-horizon problems have optimal policies that depend on two parameters that can be computed with relatively small linear programming problems. The computations exploit the structure of the streamlined separable version of our Markovian decision problem. [ABSTRACT FROM AUTHOR]