Business-related decision making seems more difficulty than ever before. Diffusion signals from different market make it difficult for policy makers to adopt clear strategy, and the lack of clear coping strategies will hinder stakeholders in the market from making strong investment decisions as early as possible. To cope with this problem, we propose an innovative model that can analyze production decisions and technology adoption of enterprises been faced with two coupled markets. With the help of this quantitative method, we answer the basic question of the investment path and technology adoption time in a class of enterprises, and further analyze which factors in the related markets have a more obvious impact on the decision. A novel feature of this work is that we characterize the connection mechanism of the two markets so that we can investigate the interaction between enterprises’ decisions and the markets’ signals. Our stochastic model allows for quite general dependence on energy fuel price and investment choice. Turning to the special Monte-Carlo based method, we can determine the optimal time to invest as well as the switching time. We applied this framework to an empirical case of heating technology on a highway, and found that both consumer preferences and energy prices have a significant impact on enterprise's investment strategy, but consumer preferences have a greater impact on the transition time for cleaner technologies. Also, the results have potentially important policy implications and can provide a rationale for supporting cleaner technologies.

与业务相关的决策似乎比以往任何时候都更加困难。来自不同市场的扩散信号使决策者难以采用清晰的策略，缺乏清晰的应对策略将阻碍市场中的利益相关者尽早做出强有力的投资决策。为了解决这个问题，我们提出了一种创新模型，可以分析面临两个耦合市场的企业的生产决策和技术采用情况。借助这种定量方法，我们回答了一类企业的投资路径和技术采用时间的基本问题，并进一步分析了相关市场中哪些因素对决策有更明显的影响。这项工作的一个新颖之处在于，我们描述了两个市场之间的联系机制，从而可以研究企业决策与市场信号之间的相互作用。我们的随机模型允许对能源价格和投资选择的普遍依赖。转到基于蒙特卡洛的特殊方法，我们可以确定最佳投资时间以及转换时间。我们将此框架应用于高速公路供暖技术的经验案例，发现消费者的偏好和能源价格对企业的投资策略都有重大影响，但是消费者的偏好对清洁技术的过渡时间影响更大。而且，结果可能具有重要的政策含义，并可以为支持更清洁的技术提供依据。