The Scientometric Measurement of Interdisciplinarity and Diversity in Research Portfolios of Chinese Universities

Abstract

Purpose: “Interdisciplinarity” is a hot topic in science- and technology-policy. However, the concept of “Interdisciplinarity” is both abstract and complex, and therefore difficult to measure using a single indicator. A variety of measures for diversity and interdisciplinarity have been proposed in the literature. Can one rank institutions in terms of their (inter )disciplinary diversity? Design/methodology/approach: We developed a routine (interd_vb.exe ) which outputs for any data matrix the values of the advanced diversity diversity indicators Rao-Stirling (RS) diversity and DIV*, as well as standard measures of diversity such as the Gini coefficient, the Shannon entropy, and the Simpson Index. As an empirical example, we compare the research portfolios of 42 “Double First-Class” Chinese universities in terms of Web-of-Science Subject Categories (WCs). Findings: The empirical results suggest that DIV* provides results which are in line with intuitive impressions more than RS, particularly when the results are based on sample-dependent disparity measures. Diversity values based on a global disparity matrix are more consistent than the results based on a local map. Research limitations: “Interdisciplinarity” can be operationalized as bibliographic coupling among (sets of) documents with references to disciplines. Diversity at the institutional level, however, may also indicate comprehensiveness. Different from impact (e.g., citation), diversity and interdisciplinarity are context-specific and thus provide a different (that is, second) dimension to the evaluation. Policy or practical implications: Operationalization and quantification force the analyst to make one’s choices and options clear. Although the equations of diversity indicators are often mathematically transparent, the specification in terms of computer code helps the analyst to further precision in decisions. Furthermore, our empirical results indicate that universities do not tend to isomorphism in this second dimension. Although diversity is not necessarily a goal of universities, a high value of diversity may support potential policies of interdisciplinarity at the university level. Originality/value: We introduce a non-commercial application in the public domain enabling researchers and policy analysts to measure “diversity” and “interdisciplinarity” using the various indicators as encompassing as possible for any document set or network structure (e.g., a network of co-authors). Insofar as we know, such a professional computing tool to evaluate data sets using diversity indicators has not yet been made available online.