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.

Topic Detection Based on Weak Tie Analysis： A Case Study of LIS Research

Purpose: Based on the weak tie theory, this paper proposes a series of connection indicators Acof weak tie subnets and weak tie nodes to detect research topics, recognize their connections, and understand their evolution.Design/methodology/approach: First, keywords are extracted from article titles and preprocessed. Second, high-frequency keywords are selected to generate weak tie co-occurrence networks. By removing the internal lines of clustered sub-topic networks, we focus on the analysis of weak tie subnets’ composition and functions and the weak tie nodes’ roles.Findings: The research topics’ clusters and themes changed yearly; the subnets clustered with technique-related and methodology-related topics have been the core, important subnets for years; while close subnets are highly independent, research topics are generally concentrated and most topics are application-related; the roles and functions of nodes and weak ties are diversified.Research limitations: The parameter values are somewhat inconsistent; the weak tie subnets and nodes are classified based on empirical observations, and the conclusions are not verified or compared to other methods.Practical implications: The research is valuable for detecting important research topics as well as their roles, interrelations, and evolution trends. Originality/value: To contribute to the strength of weak tie theory, the research translates weak and strong ties concepts to co-occurrence strength, and analyzes weak ties’ functions. Also, the research proposes a quantitative method to classify and measure the topics’ clusters and nodes.

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.

Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis

Purpose： This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach： The analysis framework includes the following steps： l） co-classification analysis based on the International Patent Classification （IPC） codes and Derwent Manual Codes （DMC） to detect sub-tech fields, 2） keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3） social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings： The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations： In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not considered.Practical implications： The analysis framework provides valuable information for decision- makers of large institutions which have many patents with broad application prospects. Originality/value： Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperation among different patent assignees.

Arbuscular mycorrhizal fungi enhance the growth of the exotic species Ambrosia artemisiifolia

Arbuscular mycorrhizal fungi(AMF)can increase host plant nutrient uptake via their mycelium,thus promoting plant growth.AMF have always been associated with successful invasion of most exotic plant species.However,knowledge regarding how AMF affect the success of plant invasion remains limited.Exotic Ambrosia artemisiifolia is an invasive and mycorrhizal plant species.A long-term field experiment was conducted to examine the differences in AMF diversity and composition in the roots of A.artemisiifolia and Setaria viridis subjected to interspecific competition during growth.A greenhouse experiment was also performed to test the effect of Funneliformis mosseae on the growth of these two species.Ambrosia artemisiifolia invasion caused AMF diversity to change in native S.viridis roots.Meanwhile,the relative abundance of F.mosseae was significantly higher in the roots of A.artemisiifolia than in those of S.viridis.The higher AMF colonization rate in the exotic species(A.artemisiifolia)than in the native species(S.viridis)was found in both the field and greenhouse experiments.The greenhouse experiment possibly provided that AMF advantaged to the growth of A.artemisiifolia,by influencing its photosynthetic capacity as well as its phosphorus and potassium absorption.These observations highlight the important relationship of AMF with the successful invasion of A.artemisiifolia.

Locomotor activity and anxiety status, but not spatial working memory,are affected in mice after brief exposure to cuprizone

Chronic long-term exposure to cuprizone causes severe brain demyelination in mice,which leads to changes in locomotion,working memory and anxiety.These findings suggest the importance of intact myelin for these behaviors.This study aimed to investigate the possible behavioral changes in mice with mild oligodendrocyte/myelin damage that parallels the white matter changes seen in the brains of patients with psychiatric disporders.We used the cuprizonetreated mouse model to test both tissue changes and behavioral functions（locomotor activity,anxiety status,and spatial working memory）.The results showed that mice given cuprizone in their diet for 7 days had no significant myelin breakdown as evaluated by immunohistochemical staining for myelin basic protein,while the number of mature oligodendrocytes was reduced.The number and length of Caspr protein clusters,a structural marker of the node of Ranvier,did not change.The locomotor activity of the cuprizonetreated mice increased whereas their anxiety levels were lower than in normal controls;spatial working memory,however,did not change.These results,for the first time,link emotion-related behavior with mild white matter damage in cuprizone-treated mice.