Resale is an effective tool for reward-based crowdfunding creators to make more profit after crowdfunding successfully. On the one hand, funds raised during the crowdfunding affect the resale pricing as a capital constraint; on the other hand, backers’ strategic purchasing behavior in the resale stage can also disturb the creator’s financing target decision-making through affecting resale pricing. In view of this, this paper builds a two-stage crowdfunding model to examine the interaction between the financing target and resale pricing in the presence of strategic backers. The results show that a lower financing amount leads to higher prices in the resale stage due to the rationing effect, and suppresses price volatility due to strategic purchasing behavior. In contrast, a higher financing amount enables the creator to build a large capacity, which does not restrict the resale prices and profit. Besides, in the context of high unit production cost or high backer patience level, there is no need for the creator to set a high financing target at the risk of crowdfunding failure.
Risk analysis of emergency is vital to effective emergency management. However, conventional analysis is challenged by the emerging problems as risk of emergency appearing increasingly complicated. The risk attributes of emergency originate in complicated sources, and their information is always incomplete. To ensure the efficiency and stability of emergency risk analysis, we proposed an elaborative approach composed of structural description framework and fuzzy evidential reasoning. Firstly, the risk attributes are identified by structural description framework. The information as evidence is obtained and normalized for further analysis. Secondly, risk analysis model with fuzzy evidential reasoning is constructed, and risk grade is evaluated. Finally, a certain railway project accident is taken as an example to test the model and some managerial insights are demonstrated. An approach combining structural description framework and fuzzy evidential reasoning model is feasible and effective; furthermore, it provides stable support for emergency risk analysis.