Optimal timing and proportion in two stages learning investment

Abstract

This article introduces a two-stage real option approach with a learning effect to examine the optimal timing and proportion of investment for a firm entering a new market. Numerical findings illustrate that firms with different learning speeds exhibit distinct investment strategies: those with slower learning speeds tend to invest large proportion in the early time of first stage and invest the rest of small proportion in the later time of second stage, whereas firms with faster learning speeds invest small proportion in the early time of first stage and invest the rest of large proportion in the later time of second stage, compared to traditional one-stage investments. Leveraging the flexibility provided by two-stage learning investment, firms can effectively utilize timing and scale options, as emphasized in previous research. Furthermore, the proposed model addresses instances of learning investments with losses that cannot be accounted for by one-stage approaches.