Who Search for Research Grant for What and When?

Yusuke Yamamoto

Abstract


We analyze access logs of the research grant search engines in our univerisity to under- stand researchers’ needs for funding opportunities. Through an analysis of university grant search engine access logs, we present (1) the features of popular grants for researchers, (2) the reasons for grant needs, and (3) the timing of grant seeking. Our analysis of the data suggests that larger number of researchers look for small-scale funding opportunities and the researchers often want budgets for indirect-research purposes such as human develop- ment, publication, and holding of conferences. The results show that researchers’ needs for funding opportunities can be comprehensively and cost-effectively investigated using access logs to design and improve university research administration/promotion services without direct communication with the researchers. 


Full Text:

PDF

References


T. Brown, “Design Thinking”, Harvard Business Review, June, 2008, pp. 84-92.

M. Stickdorn and J. Schneider. This Is Service tesign thinking: Basics, tools, cases, BIS Publishers, 2011.

Y.Kanda,andT.Kuwahara,“ShrinkingResearchTimeforUniversityFacultyMembers Comparison of 2002 and 2008 in the Survey on Full-Time Equivalents at Universities”, NISTEP Discussion Paper, No.80, 2011 (in Japanese).

National Institute of Science and Technology Policy, “Analytical Report for 2013 NISTEP Expert Survey on Japanese S&T and Innovation System”, 2013; http://www.nistep.go.jp/en/?p=3449.

I. Weber and C. Castillo, “The Demographics of Web Search”, Proceedings of the 33rd international ACM SIGIR conference on Research and development in information re- trieval (SIGIR 2010), 2010, pp. 523–530.

I. Weber and A. Jaimes, “Who Uses Web Search for What: and How”, Proceedings of the fourth ACM international conference on Web search and data mining (WSDM 11), 2011, pp. 15–24.

Andrei Broder, “A taxonomy of web search”, ACM SIGIR Forum, vol. 36 no. 2, pp. 3-10, 2002.

J.R. Herskovic, L.Y. Tanaka, W. Hersh, and E.V. Bernstam, “A day in the life of PubMed: Analysis of a typical day’s query log”, Journal of the American Medical Informatics Association, vol. 14, no. 2, 2007, pp. 212-220.

P. Resnick, and H. Varian, “Recommender systems”, Communications of the ACM, vol. 40 no. 3, 1997, pp. 56-58.

Y. Koren, R. Bell, and C. Volinsky, “Matrix factorization techniques for recommender systems”, IEEE Computer, vol. 42, no. 8, 2009, pp. 30–37.


Refbacks

  • There are currently no refbacks.