Identifying the configurations leading to the central position in the inter-country research collaboration network: Evidence from tracking configurations over time with fsQCA

During the last two decades, less than 10% of countries have had the necessary capacities for high participation in international research activities. These countries have occupied central positions in the inter-country research collaboration network. This study, using the theoretical framework of the social system, tried to understand which subsystems were involved in achieving the central position. Based on the theoretical model of the research, an empirical study was conducted using fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify the political, economic, social, and cultural factors that simultaneously led to the central position in the inter-country research collaboration network from 2002 to 2017. Data was analyzed through two novel methodological strategies: fuzzy-set ideal type analysis and strategy of multiple periods, single fsQCA. The results indicated the existence of twenty types of central countries and four causal configurations leading to the central position. This study concludes that in liberal democratic states, at least two political and economic subsystems exist. In non-liberal democratic states, at least three political, economic, and social subsystems must intervene to achieve the central position. By identifying causal configurations leading to the central position through the social system framework and strategies of tracking configurations over time with fsQCA, this study contributes to the literature on international research collaboration. It also offered suggestions to improve the semi-peripheral countries' position

Exploring a Modelling Method with Semantic Link Network and Resource Space Model

To model the complex reality, it is necessary to develop a powerful semantic model. A rational approach is to integrate a relational view and a multi-dimensional view of reality. The Semantic Link Network (SLN) is a semantic model based on a relational view and the Resource Space Model (RSM) is a multi-dimensional view for managing, sharing and specifying versatile resources with a universal resource observation. The motivation of this research consists of four aspects: (1) verify the roles of Semantic Link Network and the Resource Space Model in effectively managing various types of resources, (2) demonstrate the advantages of the Resource Space Model and Semantic Link Network, (3) uncover the rules through applications, and (4) generalize a methodology for modelling complex reality and managing various resources. The main contribution of this work consists of the following aspects: 1. A new text summarization method is proposed by segmenting a document into clauses based on semantic discourse relations and ranking and extracting the informative clauses according to their relations and roles. The Resource Space Model benefits from using semantic link network, ranking techniques and language characteristics. Compared with other summarization approaches, the proposed approach based on semantic relations achieves a higher recall score. Three implications are obtained from this research. 2. An SLN-based model for recommending research collaboration is proposed by extracting a semantic link network of different types of semantic nodes and different types of semantic links from scientific publications. Experiments on three data sets of scientific publications show that the model achieves a good performance in predicting future collaborators. This research further unveils that different semantic links play different roles in representing texts. 3. A multi-dimensional method for managing software engineering processes is developed. Software engineering processes are mapped into multiple dimensions for supporting analysis, development and maintenance of software systems. It can be used to uniformly classify and manage software methods and models through multiple dimensions so that software systems can be developed with appropriate methods. Interfaces for visualizing Resource Space Model are developed to support the proposed method by keeping the consistency among interface, the structure of model and faceted navigation