No abstract

No abstract

Network-based incubation has undergone rapid developments and the incubation mechanism has begun to change recently. To incentive the start-ups on the basis of ensuring its own interests, the incubator need to design a feasible contract. According to network theory, a single network cannot adequately describe the heterogeneous alliances of incubated start-ups in the business incubator. Therefore, by constructing super-network structure of incubated start-ups, this paper designs two types of linear incentive contracts and uses numerical simulation to further discuss the model. The results indicate that the business incubator should design the contract according to the different capability levels and risk preference degree of start-ups: linear screening contract (LSC) is more effective to motivate the incubated start-ups to improve the capability, while the incentive effect will be weakened by the increasing proportion of high-capability start-ups; for high risk-preference start-ups, linear pooling contract (LPC) is superior than LSC. The results can serve as a theoretical direction for the business incubator to effectively distinguish different capability levels of start-ups and make better decision on contract design to motivate start-ups on the basis of ensuring the maximization of its own utility.

With more and more end-of-life products in daily life, many companies are engaging in remanufacturing, including backward production capacity (BPC) enterprises. Meanwhile, take-back regulation always asks the manufacturer to take back end-of-life products to reduce pollution. However, the effect of take-back regulation on remanufacturers remains unclear. In this paper, we first analyzed the take-back regulation threshold with the elimination effect. We then discussed the impact on stakeholders, such as the manufacturer, the remanufacturer, consumers, and the government. A two-stage dynamic market model is proposed, which considers the market with/without BPC remanufacturer. Take-back regulation’s elimination effect is studied, and the results show that when the collection target reaches the elimination threshold, the manufacturer’s profit declines, the BPC remanufacturer is eliminated, consumer surplus decreases, and social welfare is improved. Besides, to cope with a high take-back regulation target, the manufacturer will reduce new product output, which leads to BPC remanufacturer’s benefits decline. A numerical study is given with a different collecting strategy of the BPC remanufacturer, the incentive interval, the inhibition interval, and the elimination interval of the take-back regulation for stakeholders which are described. At last, some managerial insights are given to help the regulator implement take-back regulation.

No abstract