Purpose:In studies of the research process,the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked.This study aims to address this gap.Design/met...Purpose:In studies of the research process,the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked.This study aims to address this gap.Design/methodology/approach:This study analyzes this relationship using a dataset of more than 8,500 researchers across all scientific fields and the globe.It studies the associations between the dimensions of two inventories:the Conceptions of Research Inventory(CoRI)and the Multi-Dimensional Research Agenda Inventory—Revised(MDRAI-R).Findings:The findings show a relatively strong association between researchers’conceptions of research and their research agendas.While all conceptions of research are positively related to scientific ambition,the findings are mixed regarding how the dimensions of the two inventories relate to one another,which is significant for those seeking to understand the knowledge production process better.Research limitations:The study relies on self-reported data,which always carries a risk of response bias.Practical implications:The findings provide a greater understanding of the inner workings of knowledge processes and indicate that the two inventories,whether used individually or in combination,may provide complementary analytical perspectives to research performance indicators.They may thus offer important insights for managers of research environments regarding how to assess the research culture,beliefs,and conceptualizations of individual researchers and research teams when designing strategies to promote specific institutional research focuses and strategies.Originality/value:To the best of the authors’knowledge,this is the first study to associate research agendas and conceptions of research.It is based on a large sample of researchers working worldwide and in all fields of knowledge,which ensures that the findings have a reasonable degree of generalizability to the global population of researchers.展开更多
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/methodolo...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.展开更多
基金supported by doctoral grant PD/BD/113999/2015 from the Fundacao para a Ciência e Tecnologia and by the European Social Fund and the Portuguese Ministry of Science and Educationfunded by the Research Grants Council (Hong Kong SAR, China)project entitled “Characterizing researchers’ research agenda-setting: an international perspective across fields of knowledge” (project number: 27608516)。
文摘Purpose:In studies of the research process,the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked.This study aims to address this gap.Design/methodology/approach:This study analyzes this relationship using a dataset of more than 8,500 researchers across all scientific fields and the globe.It studies the associations between the dimensions of two inventories:the Conceptions of Research Inventory(CoRI)and the Multi-Dimensional Research Agenda Inventory—Revised(MDRAI-R).Findings:The findings show a relatively strong association between researchers’conceptions of research and their research agendas.While all conceptions of research are positively related to scientific ambition,the findings are mixed regarding how the dimensions of the two inventories relate to one another,which is significant for those seeking to understand the knowledge production process better.Research limitations:The study relies on self-reported data,which always carries a risk of response bias.Practical implications:The findings provide a greater understanding of the inner workings of knowledge processes and indicate that the two inventories,whether used individually or in combination,may provide complementary analytical perspectives to research performance indicators.They may thus offer important insights for managers of research environments regarding how to assess the research culture,beliefs,and conceptualizations of individual researchers and research teams when designing strategies to promote specific institutional research focuses and strategies.Originality/value:To the best of the authors’knowledge,this is the first study to associate research agendas and conceptions of research.It is based on a large sample of researchers working worldwide and in all fields of knowledge,which ensures that the findings have a reasonable degree of generalizability to the global population of researchers.
基金an outcome of the project "Study on the Recognition Method of Innovative Evolving Trajectory based on Topic Correlation Analysis of Science and Technology" (No. 71704170) supported by National Natural Science Foundation of Chinathe project "Study on Regularity and Dynamics of Knowledge Diffusion among Scientific Disciplines" (No. 71704063) supported by National Natura Science Foundation of Chinathe Youth Innovation Promotion Association, CAS (Grant No. 2016159)
文摘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.
