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We model a firm's decisions about product innovation; focusing on the extent to which features should be improved or changed in the succession of models that comprise a life cycle. We show that the structure of the internal and external environment in which a firm operates suggests when to innovate to the technology frontier. The criterion is maximization of the expected present value of profits during the life cycle. Computational studies complement the theoretical results and lead to insights about when to bundle innovations across features. The formalization was influenced by extensive interviews with managers in a high-technology firm that dominates its industry. (Product Development; Innovation; Technology Management), 1. Introduction 1.1. Background The accelerating pace of technological advancement magnifies the competitive importance of the management of product and process innovation for manufacturing firms. Their profitability and viability depend [...]

Traditional multireservoir river basin models carry dimensionality problems in stochastic optimization. These problems are addressed in the analysis of a discrete-time model of a reservoir hydroelectric system. A structure defining optimal policy for the model is used to evaluate a Markov decision process function. The value function illustrates the applicability of piecewise linear approximation because sample errors were less than 1%.

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]

Delivery guarantees are an important element in a customer satisfaction program. When setting delivery guarantees, a firm must consider customer expectations as well as operational constraints. We develop a profit-maximization model in which a firm's sales organization, with incomplete information on operations'status, solicits orders and quotes delivery dates. If obtained, orders are processed in a make-to-order facility, after which revenue is received, minus tardiness penalty if the delivery was later than quoted. We specify conditions for an optimal log-linear decision rule and provide exact expressions for its effect on arrival rate, mean processing time, and mean cycle time. [ABSTRACT FROM AUTHOR]

Recent years have seen a marked increase in the rate of investment in facilities for water quality control and a concurrent recognition of the need to program water resource use on a regional basis. This paper outlines the nature of regional water quality systems and presents programming models for several water quality improvement problems. A linear programming formulation of a static improvement in quality is contrasted with a traditional policy for programming improvements; the traditional policy results in a mixed integer problem. The maximization of the ratio of benefits to costs of an improvement program is transformed to a linear programming problem. A stochastic natural environment leads to other programming models. A discussion of the application of least-cost models terminates the paper. [ABSTRACT FROM AUTHOR]