Abstract
The economic and social need to spread knowledge between universities and industry has become increasingly evident in recent years. This paper presents a ranking based partly on research and knowledge transfer indicators from U-multirank data but using data-driven weights. The choice of specific weights and the comparison between ranks remain a sensitive topic. A restricted version of the benefit of the doubt method is implemented to build a new university ranking that includes an endogenous weighting scheme. Furthermore, a novel procedure is presented to compare the principal method with U-multirank. At the best of my knowledge, the U-multirank data set has been unapplied to achieve alternative rankings that include research and knowledge transfers dimensions. A significant result arises from the benefit of the doubt: the highest importance weight is assigned to the co-publications with industrial partners and interdisciplinary publication indicators. This paper fills a bit of the existing gap on the role of co-publications with industrial partners in the university efficiency around the world.
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Source: Author. U-Multirank (2018)
Author. U-Multirank (2018)
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Notes
https://www.umultirank.org. Performance groups with numbers: A = 1, B = 2, C = 3, D = 4, and E = 5.
The logical function is =MATCH($A2;$C$2:$C$819;0). The MATCH function searches for a specified item in a range of cells, and then returns the relative position of that item in the range.For instance, if the range A1:A3 contains the values 5, 25, and 38, then the formula =MATCH(25,A1:A3,0) returns the number 2, because 25 is the second item in the range.
As an example for the BODR \(=IF\)(Y($\(C3>0\);$\(C3<=3\));”1”;IF(Y($\(C3>3\);$\(C3<=42\)); ”2”;IF(Y($\(C3>42\);$\(C3<=53\));”3”; IF(Y($\(C3>53\);$\(C3<=54\));”4”; IF(Y($\(C3>54\);$\(C3<=84\));”5”;IF(Y($\(C3>84\);$\(C3<=110\)); “6”;IF(Y($\(C3>110\);$\(C3<=112\)); “7”)))))))
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Acknowledgements
Thanks to U-multirank consortium for generously providing the official database for this academic paper. I want to thank the anonymous referees for their valuable comments which helped to improve the manuscript.
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Appendices
Appendix 1: Figures
See Figs. 3, 4, 5, 6, 7, 8, 9, 10 and 11.
Author. U-Multirank (2018)
Universities in Europe.
Universities in USA
Universities in Asia
Author. U-Multirank (2018)
The Silhouette method. See Gupta and Panda (2019).
Author. U-Multirank (2018)
CLARA: Kendall’s correlation coefficient, density and Scatter plot.
Author. U-Multirank (2018)
Importance weights mean. Whole sample. BODR.
Author.U-Mutirank 2018
U-Multirank. Construction.
Author.U-Mutirank 2018
BODR. BODRC. Construction.
Author.U-Mutirank 2018.
Spearman’s orden rank correlation. BODR with different \(\alpha \) values. All significant at 1% (p < 0:01)
Appendix 2: Tables
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Dip, J.A. What does U-multirank tell us about knowledge transfer and research?. Scientometrics 126, 3011–3039 (2021). https://doi.org/10.1007/s11192-020-03838-2
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DOI: https://doi.org/10.1007/s11192-020-03838-2