The utilization of crowdsourcing to acquire distant knowledge is increasing. In the new product development process, sustainable crowdsourcing is an effective way to exploit both external and internal resources to boost enterprise innovation quality and the efficiency of the competitive edge of macro tasks in a relatively long cycle. The challenge of sustainable crowdsourcing is how to design a proper incentive mechanism to achieve the maximum initiator profit and, at the same time, satisfy the solver’s motivation so that they can continuously participate in the innovation process. In two situations, including a single motivation and multiple motivations of the solver, this paper analyzed the impact of a few factors on the initiator’s profit and the incentive coefficient for the solver based on the Principal–Agent Model. From the model and simulation results, the solver’s incentive coefficient is positively correlated to the solver’s work quality and negatively correlated to the uncertainty of the enterprise operation, the solver’s Effort Cost, the solver’s degree of risk aversion, etc. If the initiator is more sensitive to the benefits of the solver’s intrinsic motivation, the monetary incentive will be higher. The research results provide a theoretical basis to quantify the initiator’s expected profit and design a proper incentive plan for the solver. Finally, the conclusions offer practical guidance for enterprise to execute incentive plans for sustainable crowdsourcing from the perspective of the solver’s motivation.

Collaborative innovation, with universities as the main body, is an important foundation for deepening the cooperation between industry, universities, and research institutes. Taking the collaborative innovation of five universities in Japan Shikoku area as an example, this paper summarizes the content of collaborative innovation in colleges and universities. The Shikoku SICO, which is established by government, is set to integrate the resource of university, enterprises, industry, and government, expand and broaden the knowledge chain, and promote knowledge flow and value realization through knowledge gathering and diffusion, knowledge dissemination and sharing, and knowledge transfer and application. Based on SICO's collaborative innovation mode of the Japan Shikoku area, five universities have established a virtuous circle of knowledge, capital, and talents, forming a collaborative innovation ecosystem characterized by symbiosis. From an ecology perspective, this paper establishes a regional collaborative innovation symbiotic system, which is characterized by knowledge, with the components of producer, consumer, decomposer, and catalyzer. Finally, from the perspective of constructing symbiosis system, this paper puts forward the experience of colleges and universities in Japan in terms of knowledge dissemination, knowledge transfer, and knowledge gathering.

Scientific crowdsourcing, which can effectively obtain wisdom from solvers, has become a new type of open innovation to address worldwide scientific and research problems. In the crowdsourcing process, the initiator should satisfy his own research needs by selecting a proper solver from the crowd, and the solver must have multiple competitions in order to obtain scientific research tasks from the initiator. The participants in the scientific crowdsourcing are based on the knowledge flow to realize the value added of knowledge. This paper discusses a few factors, including knowledge utility, knowledge transfer cost, knowledge distance, and knowledge trading cost, which all affect the solvers to achieve game equilibrium and win tasks in scientific crowdsourcing. By referring to the concept of Hotelling model, this paper constructs a game model with the solvers as the participants, and analyses solvers’ behaviours in scientific crowdsourcing and their profit impacts by each of the key elements. The results show that from a crowdsourcing solver’s point of view, increasing knowledge utility, controlling knowledge transfer cost, shortening knowledge distance to the initiator, and leveraging with a knowledge trading cost are four effective approaches to wining the competition of a scientific crowdsourcing task. The research conclusions provide a theoretical basis and practice guidance for crowdsourcing solvers to participate in scientific crowdsourcing from the perspective of the knowledge flow process.

Scientific crowdsourcing based on knowledge transfer between enterprises has drawn wide attention. This paper constructs the Stackelberg master–slave game model and the benefit sharing model. Through the model comparison and numerical simulation, the knowledge transfer behavior and the revenue distribution mechanism of crowdsourcing initiator and solver in the context of scientific crowdsourcing are studied. The research shows that the knowledge transfer quality and the crowdsourcing total revenue under the benefit sharing state are better than the Stackelberg master–slave game under the leadership of the crowdsourcing initiator and when the revenue distribution coefficient between the crowdsourcing initiator and solver is within a certain range. The final revenue for each party in the benefit sharing state is higher than the one in the Stackelberg master–slave game state. In addition, the research finds that the knowledge coupling degree between the initiator and the solver has a positive impact on knowledge transfer and crowdsourcing benefits. The conclusions of this paper provide a theoretical basis for enterprises, especially for large-scale high-tech business to business enterprises, to transfer knowledge and distribute revenue and eventually improve their scientific crowdsourcing quality.