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Time series citation data: the Nobel Prize in economics

Author

Listed:
  • Samuel Bjork

    (University of Oxford)

  • Avner Offer

    (University of Oxford)

  • Gabriel Söderberg

    (Uppsala University)

Abstract

Citation time series are not easy to compile from the most popular databases. The Data for Research service of the JSTOR journal database is a large and high-quality sample of citations, weighted towards humanities and social sciences. It provides time series citation data over many decades, back to the origins of the constituent journals. The citation trajectories of Nobel Prize winners in economics are analyzed here from 1930 to 2005. They are described mathematically by means of the Bass model of the diffusion of innovations. A bell-shaped curve provides a good fit with most prize winner citation trajectories, and suggests that economic knowledge follows the typical innovation cycle of adoption, peak, and decline within scholarly careers and shortly afterwards. Several variant trajectories are described.

Suggested Citation

  • Samuel Bjork & Avner Offer & Gabriel Söderberg, 2014. "Time series citation data: the Nobel Prize in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 185-196, January.
    • Handle: RePEc:spr:scient:v:98:y:2014:i:1:d:10.1007_s11192-013-0989-5
    DOI: 10.1007/s11192-013-0989-5
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    2. Victoria Anauati & Sebastian Galiani & Ramiro H. Gálvez, 2016. "Quantifying The Life Cycle Of Scholarly Articles Across Fields Of Economic Research," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 1339-1355, April.
    3. Josef Bajzik & Jan Janku & Simona Malovana & Klara Moravcova & Ngoc Anh Ngo, 2023. "Monetary Policy Has a Long-Lasting Impact on Credit: Evidence from 91 VAR Studies," Working Papers 2023/19, Czech National Bank.
    4. Julián D. Cortés & Daniel A. Andrade, 2022. "Winners and runners-up alike?—a comparison between awardees and special mention recipients of the most reputable science award in Colombia via a composite citation indicator," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    5. Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
    6. Zehra Taşkın, 2021. "Forecasting the future of library and information science and its sub-fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1527-1551, February.
    7. Yue Guiling & Siti Aisyah Panatik & Mohammad Saipol Mohd Sukor & Noraini Rusbadrol & Li Cunlin, 2022. "Bibliometric Analysis of Global Research on Organizational Citizenship Behavior From 2000 to 2019," SAGE Open, , vol. 12(1), pages 21582440221, February.
    8. Gema Albort-Morant & Jörg Henseler & Antonio Leal-Millán & Gabriel Cepeda-Carrión, 2017. "Mapping the Field: A Bibliometric Analysis of Green Innovation," Sustainability, MDPI, vol. 9(6), pages 1-15, June.
    9. Jelnov, Pavel & Weiss, Yoram, 2022. "Influence in economics and aging," Labour Economics, Elsevier, vol. 77(C).
    10. Mikel Alayo & Txomin Iturralde & Amaia Maseda & Gloria Aparicio, 2021. "Mapping family firm internationalization research: bibliometric and literature review," Review of Managerial Science, Springer, vol. 15(6), pages 1517-1560, August.
    11. Gloria Aparicio & Txomin Iturralde & Ana Vilma Rodríguez, 2023. "Developments in the knowledge-based economy research field: a bibliometric literature review," Management Review Quarterly, Springer, vol. 73(1), pages 317-352, February.
    12. Xiaoyu Li & Jiahong Yuan & Yan Shi & Tianteng Wang & Xiangpei Hu & Felix Tung Sun Chan & Junhu Ruan, 2020. "An extended Bass Model on consumer quantity of B2C commerce platforms," Electronic Commerce Research, Springer, vol. 20(3), pages 609-628, September.
    13. Hugo Baier-Fuentes & José M. Merigó & José Ernesto Amorós & Magaly Gaviria-Marín, 2019. "International entrepreneurship: a bibliometric overview," International Entrepreneurship and Management Journal, Springer, vol. 15(2), pages 385-429, June.
    14. Ho Fai Chan & Malka Guillot & Lionel Page & Benno Torgler, 2015. "The inner quality of an article: Will time tell?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 19-41, July.
    15. Claudio A. Bonilla & José M. Merigó & Carolina Torres-Abad, 2015. "Economics in Latin America: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1239-1252, November.
    16. Grzegorz Mentel & Anna Lewandowska & Justyna Berniak-Woźny & Waldemar Tarczyński, 2023. "Green and Renewable Energy Innovations: A Comprehensive Bibliometric Analysis," Energies, MDPI, vol. 16(3), pages 1-21, February.
    17. Alexander Krauss, 2024. "Science’s greatest discoverers: a shift towards greater interdisciplinarity, top universities and older age," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    18. Eusebio Scornavacca & Francesco Paolone & Stefano Za & Laura Martiniello, 2020. "Investigating the entrepreneurial perspective in smart city studies," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1197-1223, December.
    19. Bilal Barış Alkan & Leyla Karakuş & Bekir Direkci, 2023. "Knowledge discovery from the texts of Nobel Prize winners in literature: sentiment analysis and Latent Dirichlet Allocation," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5311-5334, September.

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