Lin Li

In engineering R&D organizations, resource contention among autonomous projects creates complex scheduling challenges in distributed multi-project environments. Traditional coordination mechanisms often prioritize global efficiency while overlooking inter-project fairness, which can lead to stakeholder resistance and execution delays. This study proposes a transparent decision support approach for the Distributed Resource-Constrained Multi-Project Scheduling Problem (DRCMPSP). We develop a two-stage scheduling mechanism that integrates Multi-Criteria Decision-Making (MCDM) into the global coordination process. First, an enhanced Chaotic Genetic Algorithm (CGA) with elitism generates local schedules. Second, global resource conflicts are resolved using MCDM methods. Inter-project fairness is implemented by limiting each project’s relative objective deterioration and by evaluating the dispersion of the resulting project-level burdens. Validation through an Unmanned Aerial Vehicle R&D case study and extensive experiments shows that the TOPSIS-based mechanism achieves a significantly lower standard deviation than the auction-based mechanism under high resource contention. The approach supports transparent and fairness-aware conflict resolution by making trade-offs among project-level outcomes explicit to managers.

Innovation consortiums, as a new collaborative innovation model within the open innovation ecosystem, play a significant role in breakthroughs in key core technologies in China and in improving enterprises' technological innovation levels. However, identifying key resource‐matching partners is the primary challenge that innovation consortiums face in achieving sustainable innovation. This paper employs resource dependence theory and field theory to propose a method for identifying and dynamically selecting innovative partners: potential partners of leading enterprises are identified through association rules, evaluated and ranked using the R‐TOPSIS model, and finally selected by constructing a collaborative innovation field. Through the case study of the data of China Zhaotai Medical Company (Company Z), the applicability and effectiveness of this method were further verified. This research study makes a dual contribution. Theoretically, it enriches the literature on open innovation ecosystems and collaborative innovation by integrating resource dependence and field theories within the context of Chinese practices. Methodologically, it offers a novel, dynamic framework for partner selection in an innovation consortium. By facilitating the effective integration of key resources over time, this approach directly supports the sustainable development of such a consortium, enabling them to tackle complex technological challenges aligned with broader socio‐economic goals persistently.

Faced with the intensification of international competition, the innovation consortium, as an important open innovation paradigm to promote the deep integration of industrial chain and innovation chain, has become a key path for the breakthrough of industrial core technology. However, there are some practical challenges in forming an innovation consortium, such as prominent sharing barriers of key resources and insufficient collaborative efficiency, which make it challenging to meet the needs of sustainable innovation. Based on this, this paper breaks through the traditional linear collaboration analysis framework. It constructs a game model of “leading enterprise‐cooperative organization‐government” to describe the interaction mechanism of multiagent key resource sharing decision‐making in an information asymmetric environment from the perspective of multiagent collaboration and multihelix. Vensim‐PLE simulation software is used to simulate and analyze the influencing factors of multihelix of key resource sharing. The results show that the degree of participation of various agents in sharing key resources is closely related to the sharing ability, cost, benefit, and coordination mechanism. In addition, improving the effectiveness of sharing key resources, enhancing the willingness and scope of sharing, and optimizing resource potential differentials can significantly promote the effect of multihelix of key resources. Therefore, this paper puts forward relevant management suggestions on improving innovation consortium's incentive and constraint mechanism, dynamic selection of partners, and construction of pricing and compensation mechanisms to enhance the innovation consortium's sustainable innovation. To sum up, this study not only expands the research paradigm of open innovation and enriches the connotation dimension of collaborative innovation theory but also provides new ideas for innovation consortiums under competitive environment to solve the dilemma of “resource island” and achieve sustainable collaborative innovation, which has significant practical value for guiding the breakthrough of industrial core technologies.

The most important subsystem of regional low-carbon innovation capability is low-carbon technology innovation system. It is necessary to objectively evaluate the balance of interest among low-carbon technology innovation subjects. This paper constructs the theoretical framework model of benefit balance evaluation of low-carbon collaborative innovation (LCCI). It also explores the main content and index system of evaluation and makes a specific evaluation with TOPSIS method. Our study shows the follow conclusions: ① The interest balance of the subjects of LCCI includes not only the interest balance among subjects, but also the balance of interests within the subject. ② Subjects have different motivations for cooperation. ③ The benefit distribution of LCCI includes the distribution of all tangible and intangible benefits. ④ The equilibrium state is dynamic. When it is unbalanced, it can be adjusted according to the evaluation results to achieve equilibrium. Finally, according to the research conclusions, three suggestions are put forward for LCCI management practice.

The rational allocation and utilization of key corporate resources is the key to the success of collaborative innovation projects. Finding an optimal strategy for the allocation and utilization of key resources is of great significance for promoting the smooth progress of cooperative both innovation parties and increasing project returns. Therefore, from the perspective of the repeated games of the project participants, this article studies the optimal allocation and utilization of key resources of the enterprise in collaborative innovation projects. In this study, nine scenarios and eighteen strategic combinations of resources allocation and utilization by collaborative innovation partners are explored. Explicit expressions for the components of sixteen equilibrium points in terms of parameters are derived. Among these equilibrium points, four stable solutions are determined. These stable solutions correspond to the optimal strategies for enterprises allocating key resources and A&R parties to use these resources in different scenarios, and these strategies enable partners to maximize their interests. On this basis, some suggestions are put forward to promote cooperation and improve project performance.

The government’s supervision of new residential building projects’ (NRBPs) energy-saving can promote carbon neutrality policies within its jurisdiction. A scientific and systematic evaluation of NRBPs energy-saving reflects a government’s management performance. However, achieving accurate and reasonable results with unitary evaluation standards without considering regional characteristics is not easy. This study proposes an evaluation method of intelligently evaluating the effectiveness of government energy-saving supervision with regional characteristics weighted in. Consequently, these evaluation indicators can reveal the key issues in carrying out local energy-saving policies and provide concrete guidance for local governments to manage the energy-saving of NRBPs better. The method was tested with ten projects and found to be effective.

This study conducted a comprehensive and systematic investigation of the influencing factors for collaborative innovation project (CIP) performance. First, a theoretical framework model was constructed, and then a structural equation model (SEM) was used for an empirical analysis of 199 CIPs. Furthermore, we divided the factors into tangible and intangible categories and considered the impact mechanism of nine typical factors on project performance. The results are as follows: (1) All nine factors had a significant positive impact on the performance of collaborative innovation projects, among which benefit distribution and collaborative innovation capability were the most important. (2) Benefit distribution, resource dependence, organizational climate, and collaborative innovation affected project performance, both directly and indirectly. (3) Effective communication, leadership support, knowledge sharing, and collaborative innovation ability only had a direct influence, while the incentive mechanism played only an indirect role. Finally, three suggestions were put forward on the idea of high-quality, sustainable development.

With the development of the urbanization process, the demand for water resources has increased significantly, but the pollution of water resources has caused serious problems. These changes pose a potential threat to water resource carrying capacity in many regions. However, how to determine the areas of highest risk in water resource carrying capacity is an urgent problem which remains to be solved. Resounding to these circumstances, this study establishes a TODIM-PROMETHEE Ⅱ (An acronym in Portuguese for interactive and multiple attribute decision making- preference ranking organization method for enrichment evaluation Ⅱ) based decision support framework to address this issue for the regions of intensive governance, thereby providing support. In this framework, a novel theoretical concept, namely probabilistic linguistic Z-numbers, is proposed to describe group decision information. The related knowledge of probabilistic linguistic Z-numbers is developed, including a comparison method, distance, and operational rules. Subsequently, a case study involving the evaluation of water resource carrying capacity is conducted to demonstrate the feasibility of the decision support model, followed by sensitivity analysis, comparison analysis, and discussion. The findings demonstrate that the constructed framework demonstrates great performance to address this issue.