Competing on Time: An Integrated Framework to Optimize Dynamic Time-to-Market and Production Decisions
Published in Production and Operations Management, 22(3) pp. 473-488, 2013
36 Pages Posted: 3 Apr 2012 Last revised: 14 Oct 2017
Date Written: January 3, 2012
Abstract
This paper develops a comprehensive framework to optimize new product introduction timing and subsequent production decisions faced by a component supplier. Prior to market entry, the supplier performs process design activities, which improve manufacturing yield and the chances of getting qualified for the customer's product. However, a long delay in market entry allows competitors to enter the market and pass the customer's qualification process before the supplier, reducing the supplier's share of the customer's business. After entering the market and if qualified, the supplier also needs to decide how much to produce for a finite planning horizon by considering several factors such as manufacturing yield and stochastic demand, both of which depend on the earlier time-to-market decision. To capture this dependency, we develop a sequential, nested, two-stage decision framework to optimize the time-to-market and production decisions in relation to each other. We show that the supplier's optimal market entry and qualification timing decision need to be revised in real time based on the number of qualified competitors at the time of market entry decision. We establish the optimality of a threshold policy. Following this policy, at the beginning of each decision epoch, the supplier should optimally stop preparing for qualification and decide whether to enter the market if her order among qualified competitors exceeds a predetermined threshold. We also prove that the supplier's optimal production policy is a state-dependent, base-stock policy, which depends on the time-to-market and qualification decisions. The proposed framework also enables a firm to quantify how market conditions (such as, price and competitor entry behavior) and operating conditions (such as, the rate of learning and inventory/production related costs) affect time-to-market strategy and post-entry production decisions.
Keywords: time-to-market, qualification timing, stochastic production systems, learning by doing, learning before doing, optimal stopping, state-dependent policy
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