, Volume 114, Issue 3, pp 883–904 | Cite as

Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research



Funded research has been linked to academic production and performance. While the presence of funding acknowledgements may serve as an indicator of quality to some extent, we still lack tools to evaluate whether funding agencies allocate resources to novel and innovative research rather than mature fields. We address this issue in the present study by using bibliometrics. In particular, we exploit the citation network properties of academic articles to classify specific research fields into four categories: change maker, breakthrough, incremental, and matured. We then use funding acknowledgement information to identify the sponsors involved in each research type to characterize funding agencies. We focus our analysis on the robotics field in order to reveal international trends of financial acknowledgements. We find that the incremental and matured research areas show the highest counts of funding acknowledgements. Moreover, although research funded by some agencies is mostly recognized as incremental-type research, those in other categories may perform better in terms of the number of citations. Additionally, we analyze the interest of selected funding agencies in granular subject categories. The characterization of funding agencies in this study may help policymakers and funding organizations assess or adjust their strategies, benchmark with other key players, and obtain an overview of local and global acknowledgement trends.


Acknowledgement analysis Funding analysis Citation network Emerging technology Robotics 

Mathematics Subject Classification

62H25 91B82 

JEL Classification

C38 C81 D02 O32 



The authors thank Tiecheng Jin for collaborating in the name disambiguation task. Part of this research was supported by a scholarship from the Ministry of Education, Culture, Sports, Science and Technology of Japan.


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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2017

Authors and Affiliations

  1. 1.Department of Innovation, Graduate School of Innovation ManagementTokyo Institute of TechnologyTokyoJapan

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