An asymmetric option game in a duopolistic real estate market

Makoto Goto, Tomoaki Tabata, Takahiro Ono

Research output: Contribution to journalArticlepeer-review


This article deals with investment decision-making under uncertainty and competition. The traditional net present value (NPV) method doesn't consider the flexibility of decision-making, so project values tend to be underestimated. A. real options approach that can make up for the weak point of NPV has recently been the focus, but it considers only one agent, similar to the money market. However, in actual case, a competitor's decision-making is sure to influence the project value of the agent. Therefore, the influence of a competitor's decision-making must be estimated. Game theory is effective to optimize one's own actions subject to a competitor's decision-making (strategy). Therefore, the reduction in project value due to competition is formulated by applying game theory to a real options approach. The model should be solved so that the conditional expected value is maximized. We considered a duopolistic real estate market by referring Grenadier [1] in previous studies. While the previous study formulated two symmetric agents, we try to extend the model to two asymmetric agents. Asymmetry results in an asymmetric equilibrium exercise strategy. With this result, we are able to explain the economic phenomenon that previous studies couldn't explain. That is, a firm with superior development technology has an advantage over the firm with inferior technology. Furthermore, we indicate the change in decision-making caused by uncertainty and construction costs from comparative statistics.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalJournal of Japan Industrial Management Association
Issue number1
Publication statusPublished - 2005


  • Competition
  • Game theory
  • Investment decision
  • Real options
  • Uncertainty

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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