In this paper, we consider two kinds of technologies distinguished by their level of productivity and associated costs, such that one technology increases the quantity of output more than the alternative technology. The firm must then decide in which technology to invest and when to invest in the chosen R&D project so as to maximize profit. To solve this problem, we formulate it as an optimal stopping problem for the firm. Using this analysis, we endogenously obtain the firm’s expenditure on R&D investment and numerically locate the R&D investment thresholds for the firm’s projects.

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In this paper, we formulate the investment of a firm in a production facility with maximum capacity and outsourcing strategy. Previous research on capacity selection has resulted in explosive capacity and long delay in investment. The possibility that a firm will install a facility with an explosive capacity is slight, and firms can generally outsource production when the demand exceeds the capacity of a facility. The outsourcing strategy is expected to inhibit capacity, accelerate investment, and increase value. In this paper, we simultaneously investigate the optimal investment timing, the size of a facility, and the outsourcing strategy.

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The authors model the development of plug-in electric vehicle (PEV) markets hand-in-hand with the charging infrastructure for PEV users and include the market fluctuation of fuel costs. One of the driving factors for PEV buyers is the prospect of fuel cost-savings relative to the price of the PEV. Another key factor is charging station availability in the community. The decision regarding whether to purchase a PEV thus involves an investment decision under fuel economy uncertainty in the future. Policies to support the proliferation of PEVs are also affected by the economic trend of fossil fuels. This paper estimates the possible ranges of gasoline price fluctuation over the next 10 years and quantitatively analyzes these fluctuations’ influence on the market growth of electric vehicles. We then aim to evaluate various public subsidy initiatives to PEV buyers and charging infrastructure enterprises.

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We consider the risk management problem in the Japanese public pension system using government data and programs. Specially, we formulate a simple model of pension sustainability for the long term and then model the budgetary balance as a stochastic process using the growth rate of wages and the rate of fund return. Our objects are to assess the effects of economic scenarios when forecasting reserve values and to evaluate the risk of a failure to pay benefits in the target year. We measure risk in our scenarios by backward calculating the option pricing for a binomial tree. We assess the sustainability of pensions in three economic scenarios with deflation, middle inflation, and high-inflation economies.

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