Robustness of open source community multi-project knowledge collaboration network based on structural hole theory.

Nodes in the structural hole position play a key role in the multi-project network of the open source community (OSC). This paper studies the robustness of this network based on structural hole theory. First, a semantic-based multi-project KCN is constructed, and four node types are identified: knowledge contribution nodes, knowledge dissemination nodes, structural hole nodes (SHNs) and opinion leader nodes. Second, a robustness analysis model of the edge failures of these four key nodes is constructed. Third, a simulation test is conducted on the proposed model using empirical data from the Local Motors multi-project OSC. The results show that the KCN has the lowest robustness when facing the edge failure of opinion leader nodes, followed by knowledge dissemination nodes, knowledge contribution nodes, SHNs and random nodes. The edge failure of opinion leader nodes causes the lowest network robustness because of the propagation effect of these nodes. Additionally, SHN failure has only a small initial impact on connectivity, whereas knowledge collaboration efficiency decreases rapidly (i.e., the edge failure of SHNs causes the network to enter a state of high connectivity and low efficiency). The proposed model can be used to provide comprehensive and targeted management guidance for OSC development.

Robustness of Multi-Project Knowledge Collaboration Network in Open Source Community.

Multi-project parallelism is an important feature of open source communities (OSCs), and multi-project collaboration among users is a favorable condition for an OSC's development. This paper studies the robustness of this type of community. Based on the characteristics of knowledge collaboration behavior and the large amount of semantic content generated from user collaboration in open source projects, we construct a directed, weighted, semantic-based multi-project knowledge collaboration network. Using analysis of the KCN's structure and user attributes, nodes are divided into knowledge collaboration nodes and knowledge dissemination nodes that participate in either multi- or single-project collaboration. From the perspectives of user churn and behavior degradation, two types of failure modes are constructed: node failure and edge failure. Based on empirical data from the Local Motors open source vehicle design community, we then carry out a dynamic robustness analysis experiment. Our results show that the robustness of our constructed network varies for different failure modes and different node types: the network has (1) a high robustness to random failure and a low robustness to deliberate failure, (2) a high robustness to edge failure and a low robustness to node failure, and (3) a high robustness to the failure of single-project nodes (or their edges) and a low robustness to the failure of multi-project nodes (or their edges). These findings can be used to provide a more comprehensive and targeted management reference, promoting the efficient development of OSCs.

Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification.

A large amount of semantic content is generated during designer collaboration in open-source projects (OSPs). Based on the characteristics of knowledge collaboration behavior in OSPs, we constructed a directed, weighted, semantic-based knowledge collaborative network. Four social network analysis indexes were created to identify the key opinion leader nodes in the network using the entropy weight and TOPSIS method. Further, three degradation modes were designed for (1) the collaborative behavior of opinion leaders, (2) main knowledge dissemination behavior, and (3) main knowledge contribution behavior. Regarding the degradation model of the collaborative behavior of opinion leaders, we considered the propagation characteristics of opinion leaders to other nodes, and we created a susceptible-infected-removed (SIR) propagation model of the influence of opinion leaders' behaviors. Finally, based on empirical data from the Local Motors open-source vehicle design community, a dynamic robustness analysis experiment was carried out. The results showed that the robustness of our constructed network varied for different degradation modes: the degradation of the opinion leaders' collaborative behavior had the lowest robustness; this was followed by the main knowledge dissemination behavior and the main knowledge contribution behavior; the degradation of random behavior had the highest robustness. Our method revealed the influence of the degradation of collaborative behavior of different types of nodes on the robustness of the network. This could be used to formulate the management strategy of the open-source design community, thus promoting the stable development of OSPs.

Dynamic Robustness of Semantic-Based Collaborative Knowledge Network of Open Source Project.

Robustness of the collaborative knowledge network (CKN) is critical to the success of open source projects. To study this robustness more comprehensively and accurately, we constructed a weighted CKN based on the semantic analysis of collaborative behavior, where (a) open source designers were the network nodes, (b) collaborative behavior among designers was the edges, and (c) collaborative text content intensity and collaborative frequency intensity were the edge weights. To study the robustness from a dynamic viewpoint, we constructed three CKNs from different stages of the project life cycle: the start-up, growth and maturation stages. The connectivity and collaboration efficiency of the weighted network were then used as robustness evaluation indexes. Further, we designed four edge failure modes based on the behavioral characteristics of open source designers. Finally, we carried out dynamic robustness analysis experiments based on the empirical data of a Local Motors open source car design project. Our results showed that the CKN performed differently at different stages of the project life cycle, and our specific findings could help community managers of open source projects to formulate different network protection strategies at different stages of their projects.

Research on flexibility of production system based on hybrid modeling and simulation.

In order to analyze the influence of the personnel flexibility on the flexibility of the production system and optimize the organization and configuration of the production system, this paper puts forward a flexible simulation study of production system personnel based on mixed modeling. Firstly, the flexible evaluation index of production system is constructed from four dimensions: machine utilization ratio, personnel utilization ratio, production and personnel production efficiency. The concrete calculation method is given accordingly. Secondly, the simulation model of discrete event-multibody mixed modeling in production system is established, and the construction principle of the model is given. Thirdly, based on the flexible evaluation index and mixed modeling method, the flexible personnel skills of a motorcycle engine key parts production system are simulated and analyzed, and the comparative analysis of multiple schemes is realized. The simulation results show that multi-energy and personnel cooperation have an important influence on the flexibility of production system. In the medium and large fluctuation production environment, compared with the professional production team, the flexibility of the four dimensions of machine utilization, personnel utilization, production and personnel production efficiency of the multi-energy production team has been significantly improved. The case study also shows that the hybrid modeling simulation model can realize the dynamic configuration and operation evaluation of the flexible personnel elements, and provide a dynamic and quantitative research method for the organizational optimization of the production system.