Analysis of Collaborative Innovation Behavior of Megaproject Participants Under the Reward and Punishment Mechanism

Abstract

Megaprojects are characterized by significant environmental uncertainty and technical complexity, which bring great challenges to engineering construction. Cross-organizational collaborative innovation is an important way to solve these problems. As the main body that understands the difficulties of the construction site and uses innovative products, the participation of megaproject participants is not only conducive to increasing innovation efficiency but also conducive to the application and promotion of innovative achievements. The collaborative innovation behavior of the participants in megaprojects under the reward and punishment incentive mechanism was studied. A game model between different participants was built by combining evolutionary game theory with prospect theory. Then, the dynamic evolution process of the collaborative innovation strategy of participants was analyzed, and the main factors affecting the evolutionary stability strategy of collaborative innovation through numerical simulation were examined. The research results indicate that reward and punishment incentives of collaborative innovation can encourage participants to choose the evolutionary stability strategy of participating in collaborative innovation from both objective and subjective aspects. Factors, such as the cost of participating, the synergy coefficient, the proportion of collaborative revenue distribution, and risk preference, can influence participants’ willingness to engage in collaborative innovation to different degrees.

Incentive Mechanisms of an Experimental Resource-Sharing Platform Considering Reputation Effects for Megaprojects

“…In 2022, the Chengdu R&D base of the NTIC invested an additional 148.802 million RMB in the construction of the platform. The investment cost of the digital laboratory was 42.05 million RMB, that of the intelligent construction laboratory was 11 million RMB, that of the disaster warning and prevention and control laboratories was 27.611 million RMB, that of the geography and geology laboratories was 61.501 million RMB, and that of the other laboratories was 6.64 million To better assess the changes and influence of various parameters and to better understand the incentive models used in this paper, it combined the actual situation of this project and related literature (Wang et al, 2020b;Zhou & Liu, 2021;Li et al, 2022a;Liu & Zhou, 2022) through numerical simulation of different scenarios to analyze the impact of the degree of sharing (d) and the reputation impact coefficient (k) on the laboratories' optimal effort level (e * ), fixed funding (α), benefits (W) and the platform's benefits (V). To validate the previous related conclusions, the random perturbations caused by external factors are assumed to obey the N(0, 1) standard normal distribution.…”

Evolutionary mechanism of green technology innovation behavior in the operation period of construction and demolition waste recycling public–private partnership projects

“…Influenced by the complexity and uncertainty of innovation activities, some enterprises try to integrate innovation resources by establishing collaborative relationships (Brown et al, 2020). However, some factors, such as the level of collaboration, absorptive capacity, and risk preference, may affect enterprises' choice of collaborative innovation (Liu & Zhou, 2022). In addition, China has issued Green Credit Guidelines to promote the development of green credit, so as to support green innovation activities.…”