A Study of Methods to Identify Industry-University-Research Institution Cooperation Partners based on Innovation Chain Theory

Purpose： This study aims at identifying potential industry-university-research collaboration（IURC） partners effectively and analyzes the conditions and dynamics in the IURC process based on innovation chain theory.Design/methodology/approach： The method utilizes multisource data, combining bibliometric and econometrics analyses to capture the core network of the existing collaboration networks and institution competitiveness in the innovation chain. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors.Findings： Empirical analysis of the genetic engineering vaccine field shows that through the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify the more complementary capacities among organizations.Research limitations： In this study, the overall approach is shaped by the theoretical concept of an innovation chain, a linear innovation model with specific types or stages of innovation activities in each phase of the chain, and may, thus, overlook important feedback mechanisms in the innovation process.Practical implications： Industry-university-research institution collaborations are extremely important in promoting the dissemination of innovative knowledge, enhancing the quality of innovation products, and facilitating the transformation of scientific achievements.Originality/value： Compared to previous studies, this study emulates the real conditions of IURC. Thus, the rule of technological innovation can be better revealed, the potential partners of IURC can be identified more readily, and the conclusion has more value.

Identification and Prediction of Interdisciplinary Research Topics: A Study Based on the Concept Lattice Theory

Purpose: Formal concept analysis(FCA) and concept lattice theory(CLT) are introduced for constructing a network of IDR topics and for evaluating their effectiveness for knowledge structure exploration.Design/methodology/approach: We introduced the theory and applications of FCA and CLT, and then proposed a method for interdisciplinary knowledge discovery based on CLT. As an example of empirical analysis, interdisciplinary research(IDR) topics in Information & Library Science(LIS) and Medical Informatics, and in LIS and Geography-Physical, were utilized as empirical fields. Subsequently, we carried out a comparative analysis with two other IDR topic recognition methods.Findings: The CLT approach is suitable for IDR topic identification and predictions.Research limitations: IDR topic recognition based on the CLT is not sensitive to the interdisciplinarity of topic terms, since the data can only reflect whether there is a relationship between the discipline and the topic terms. Moreover, the CLT cannot clearly represent a large amounts of concepts.Practical implications: A deeper understanding of the IDR topics was obtained as the structural and hierarchical relationships between them were identified, which can help to get more precise identification and prediction to IDR topics.Originality/value: IDR topics identification based on CLT have performed well and this theory has several advantages for identifying and predicting IDR topics. First, in a concept lattice, there is a partial order relation between interconnected nodes, and consequently, a complete concept lattice can present hierarchical properties. Second, clustering analysis of IDR topics based on concept lattices can yield clusters that highlight the essential knowledge features and help display the semantic relationship between different IDR topics. Furthermore, the Hasse diagram automatically displays all the IDR topics associated with the different disciplines, thus forming clusters of specific concepts and visually retaining and presenting the associations of IDR topics through multiple inheritance relationships between the concepts.

Empirical research of advantage disciplines of C9 League

Purpose:Based on the case of the top nine elite universities in China(i.e.C9 League),we evaluate the university discipline advantages in terms of outputs and influence of scientific articles.Combining with the discipline collaboration analysis,we provide suggestions on discipline development and future collaboration for C9 League members.Design/methodology/approach:First,we carry out a correlation analysis.Then,we obtain the new combination evaluation indicators through factor analysis on seven primary indicators from InCite platform.Afterwards,we assign the weighted values to different indicators in order to get the evaluation scores and the ranking for each C9 League member.Then,we obtain the bibliographic data of the C9 League members for extracting the category classifications from the Web and transforming them into Degree-Granting and Personal Trainning Courses Catalogue(DPTCC).According to the original collaboration frequencies among C9 League members,we carry out the analysis on two-mode collaboration networks.Finally,we propose some suggestions on the future collaboration and development.Findings:There is correlation relationship between the outputs of scientific papers and influence indicators,so it is necessary to use the various indicators to acquire the more scientific evaluation.Meanwhile,league members are different in the discipline development level,and have inadequate collaboration with each other,which indicates that there exists the great potential for further collaborations.Research limitations:Despite the relative high quality SCI papers,preference for different disciplines of SCI and different discipline features for C9 members probably exert negative influence on evaluation results.Practical implications:We provide a research thought and an operational approach to the disciplines evaluation,which would promote more methods for scientific discipline evaluation and reasonable management for universities.Originality/value:There are more and more articles on the universities evaluation indexes,but rarely on the relationship among the indicators.Therefore,our approach would be helpful for the evaluation of university disciplines.