The sharing economy has entered the phase of deep integration, giving rise to the “sharing +” mode, which carries two layers of meaning: one is the “sharing platform + non-platform enterprises”, that is, platform enterprises, while focusing on their core businesses, continuously explore innovation and integration of related services; the other is the “sharing platform + sharing platform”, that is, super platforms collaborate with other service platforms. The essence of “sharing +” mode lies in the collaborative creation and sharing of value among multiple service entities linked by the platform. This process is driven by platform enterprises and other stakeholders, which, through competitive cooperation, interaction, and resource integration, work together to create value. In this context, the platform acts as the value creator, while other service entities (such as manufacturers, technical support providers, and other platforms etc.) act as co-creators of value. In the process, the platform needs to invest significant resources and costs to expand its user base and leverage accumulated consumption data; meanwhile, other service entities need to improve their product quality and services to enhance customer satisfaction. In essence, both creators and co-creators need to strive to enhance their value production.Based on the aforementioned observation, few literature uses mathematical models to explore how the platform, as the primary value creator, collaborates with multiple co-creators to jointly create and share value, and theoretically analyzes the time-varying nature of equilibrium solutions. In this paper, a dynamic model is established for this new business model of value co-creation and shared consumption, and discusses platform collaboration strategies and influencing factors. First, we consider the scenario where the platform creates value independently. Next, we delve into the differential game (Nash game) between the platform, acting as the primary value creator and multiple co-authors. Finally, we expand the analysis to a scenario where the platform subsidizes co-creators based on their efforts to incentivize greater contribution (Stackelberg leader-follower game). This paper analyzes these three scenarios, exploring the optimal time path of equilibrium solutions and conducts theoretical and simulation analyses on parameter elasticity. The goal is to provide relevant collaboration recommendations to both the platform and co-creators, aiming at enhancing the platform ecosystem.The main research findings are as follows: 1) From the perspective of value output, optimal effort levels and optimal returns, the strategy of providing incentives to co-creators is superior to that without incentives, which, in turn, is superior to that the platform solely creates values; 2) The platform′s effort gradually decreases over time, while the co-creators′ effort remains constant, leading to an increase in value output and optimal returns; 3) The impact of co-creators′ monetization capability and value output rate on optimal value is logically consistent. Stronger monetization capability or higher output efficiency leads to greater value output and higher mutual returns. However, the co-creators′ marginal costs have the opposite effect on the optimal value. Higher costs result in lower value output and lower mutual returns. 4) The natural loss rate of value and discount factor influence the optimal value as follows: a higher loss rate or discount rate leads to a lower value returns and overall returns. The management insights are as follows: 1) When enhancing the ecosystem, the platform should actively collaborate with other service entities. By providing subsidies, the platform can encourage vigorous co-creators to put in more efforts, thereby attracting more co-creators to join the platform ecosystem; 2) Both the platform and the co-creators aim to enhance the monetization capability of co-creators; To this end, the platform can offer complementary measures such as increased visibility, priority recommendations, and advertising promotion etc. to help co-creators improve exposure and monetization potential; 3) When selecting co-creators, the platform can prioritize those with lower marginal costs; 4) Both the platform and co-creators should strive to leverage technological tools to improve their value creation efficiency.