IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i2d10.1007_s11192-019-03314-6.html
   My bibliography  Save this article

The impact of a paper’s new combinations and new components on its citation

Author

Listed:
  • Yan Yan

    (Renmin University of China)

  • Shanwu Tian

    (Renmin University of China)

  • Jingjing Zhang

    (University of Chinese Academy of Sciences)

Abstract

A paper’s novelty enhances its impact and citation. In this paper, we examine two dimensions of a paper’s novelty: new combinations and new components. We define new combinations as new pairs of knowledge elements in a related research area, and new components as new knowledge elements that have never appeared in a related research area previously. The importance of both dimensions is stressed, and we analyze the mechanisms that affect the frequency of a paper’s citation; we believe that a paper’s new combinations and new components both have an inverted U-shaped effect on its citation count. Utilizing a text-mining approach, we develop a novel method for constructing new combinations and new components using a paper’s keywords. Using keywords from papers published in the wind energy field between 2002 and 2015 as our sample, we conduct an empirical analysis on the above-mentioned relationships. To do so, we use the negative binomial regression method and several robustness tests. The results provide support for our hypotheses that propose a paper’s new combinations and new components significantly affect its impact. Specifically, new combinations and new components lead to more citation counts up to a specific threshold. When the number of new combinations and new components exceed the threshold, the paper is likely to be cited less frequently. Finally, we discuss the theoretical contributions, methodological contributions, and practical implications of these findings.

Suggested Citation

  • Yan Yan & Shanwu Tian & Jingjing Zhang, 2020. "The impact of a paper’s new combinations and new components on its citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 895-913, February.
    • Handle: RePEc:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03314-6
    DOI: 10.1007/s11192-019-03314-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03314-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-019-03314-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    2. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
    3. Glenn D. Walters, 2006. "Predicting subsequent citations to articles published in twelve crime-psychology journals: Author impact versus journal impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(3), pages 499-510, December.
    4. Loet Leydesdorff & Lutz Bornmann & Caroline S. Wagner, 2019. "The Relative Influences of Government Funding and International Collaboration on Citation Impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(2), pages 198-201, February.
    5. Jue Wang & Philip Shapira, 2011. "Funding acknowledgement analysis: an enhanced tool to investigate research sponsorship impacts: the case of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 563-586, June.
    6. Wang, Jian & Veugelers, Reinhilde & Stephan, Paula, 2017. "Bias against novelty in science: A cautionary tale for users of bibliometric indicators," Research Policy, Elsevier, vol. 46(8), pages 1416-1436.
    7. Sarah Kaplan & Keyvan Vakili, 2015. "The double-edged sword of recombination in breakthrough innovation," Strategic Management Journal, Wiley Blackwell, vol. 36(10), pages 1435-1457, October.
    8. Pablo D. Batista & Mônica G. Campiteli & Osame Kinouchi, 2006. "Is it possible to compare researchers with different scientific interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 179-189, July.
    9. Strumsky, Deborah & Lobo, José, 2015. "Identifying the sources of technological novelty in the process of invention," Research Policy, Elsevier, vol. 44(8), pages 1445-1461.
    10. Richard F. J. Haans & Constant Pieters & Zi-Lin He, 2016. "Thinking about U: Theorizing and testing U- and inverted U-shaped relationships in strategy research," Strategic Management Journal, Wiley Blackwell, vol. 37(7), pages 1177-1195, July.
    11. Elias Sanz-Casado & J. Carlos Garcia-Zorita & Antonio Eleazar Serrano-López & Birger Larsen & Peter Ingwersen, 2013. "Renewable energy research 1995–2009: a case study of wind power research in EU, Spain, Germany and Denmark," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 197-224, April.
    12. Danielle H. Lee & Peter Brusilovsky, 2019. "The first impression of conference papers: Does it matter in predicting future citations?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(1), pages 83-95, January.
    13. Nicolas Carayol, 2016. "The Right Job and the Job Right: Novelty, Impact and Journal Stratification in Science," Post-Print hal-02274661, HAL.
    14. Massimiliano Agovino & Luigi Aldieri & Antonio Garofalo & Concetto Paolo Vinci, 2017. "Quality and quantity in the innovation process of firms: a statistical approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1579-1591, July.
    15. Jiancheng Guan & Yan Yan & Jingjing Zhang, 2015. "How do collaborative features affect scientific output? Evidences from wind power field," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 333-355, January.
    16. Guan, Jiancheng & Zhang, Jingjing & Yan, Yan, 2015. "The impact of multilevel networks on innovation," Research Policy, Elsevier, vol. 44(3), pages 545-559.
    17. Gautam Ahuja & Curba Morris Lampert, 2001. "Entrepreneurship in the large corporation: a longitudinal study of how established firms create breakthrough inventions," Strategic Management Journal, Wiley Blackwell, vol. 22(6‐7), pages 521-543, June.
    18. Tahamtan, Iman & Bornmann, Lutz, 2018. "Creativity in science and the link to cited references: Is the creative potential of papers reflected in their cited references?," Journal of Informetrics, Elsevier, vol. 12(3), pages 906-930.
    19. Tahamtan, Iman & Bornmann, Lutz, 2018. "Core elements in the process of citing publications: Conceptual overview of the literature," Journal of Informetrics, Elsevier, vol. 12(1), pages 203-216.
    20. Stephen J. Bensman, 2008. "Distributional differences of the impact factor in the sciences versus the social sciences: An analysis of the probabilistic structure of the 2005 journal citation reports," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(9), pages 1366-1382, July.
    21. Gallouj, Faiz & Weinstein, Olivier, 1997. "Innovation in services," Research Policy, Elsevier, vol. 26(4-5), pages 537-556, December.
    22. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
    23. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    24. Paul F. Skilton, 2006. "A comparative study of communal practice: Assessing the effects of taken-for-granted-ness on citation practice in scientific communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 73-96, July.
    25. Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
    26. Guan, Jian Cheng & Yan, Yan, 2016. "Technological proximity and recombinative innovation in the alternative energy field," Research Policy, Elsevier, vol. 45(7), pages 1460-1473.
    27. Hamid R. Jamali & Mahsa Nikzad, 2011. "Article title type and its relation with the number of downloads and citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 653-661, August.
    28. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    29. Abbasi, Alireza & Jaafari, Ali, 2013. "Research impact and scholars’ geographical diversity," Journal of Informetrics, Elsevier, vol. 7(3), pages 683-692.
    30. Zhang, JingJing & Yan, Yan & Guan, JianCheng, 2019. "Recombinant distance, network governance and recombinant innovation," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 260-272.
    31. Kevin W. Boyack & Katy Börner, 2003. "Indicator‐assisted evaluation and funding of research: Visualizing the influence of grants on the number and citation counts of research papers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 447-461, March.
    32. Bernard J. Jansen & Udo Pooch, 2001. "A review of Web searching studies and a framework for future research," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(3), pages 235-246.
    33. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    34. Lee, You-Na & Walsh, John P. & Wang, Jian, 2015. "Creativity in scientific teams: Unpacking novelty and impact," Research Policy, Elsevier, vol. 44(3), pages 684-697.
    35. Katherine W. McCain, 1989. "Descriptor and citation retrieval in the Medical Behavioral Sciences literature: Retrieval overlaps and novelty distribution," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(2), pages 110-114, March.
    36. Lutz Bornmann & Hans-Dieter Daniel, 2006. "Selecting scientific excellence through committee peer review - A citation analysis of publications previously published to approval or rejection of post-doctoral research fellowship applicants," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 427-440, September.
    37. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    38. Saviotti, P. P. & Metcalfe, J. S., 1984. "A theoretical approach to the construction of technological output indicators," Research Policy, Elsevier, vol. 13(3), pages 141-151, June.
    39. Jingjing Zhang & Yan Yan & Jiancheng Guan, 2015. "Scientific relatedness in solar energy: a comparative study between the USA and China," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1595-1613, February.
    40. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    41. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luo, Zhuoran & Lu, Wei & He, Jiangen & Wang, Yuqi, 2022. "Combination of research questions and methods: A new measurement of scientific novelty," Journal of Informetrics, Elsevier, vol. 16(2).
    2. Shuo Xu & Mengjia An & Xin An, 2021. "Do scientific publications by editorial board members have shorter publication delays and then higher influence?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6697-6713, August.
    3. Sotaro Shibayama & Deyun Yin & Kuniko Matsumoto, 2021. "Measuring novelty in science with word embedding," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-16, July.
    4. Chen, Wei & Yan, Yan, 2023. "New components and combinations: The perspective of the internal collaboration networks of scientific teams," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Hou, Jianhua & Wang, Dongyi & Li, Jing, 2022. "A new method for measuring the originality of academic articles based on knowledge units in semantic networks," Journal of Informetrics, Elsevier, vol. 16(3).
    6. Zhang, Xinyuan & Xie, Qing & Song, Min, 2021. "Measuring the impact of novelty, bibliometric, and academic-network factors on citation count using a neural network," Journal of Informetrics, Elsevier, vol. 15(2).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
    2. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    3. Luo, Zhuoran & Lu, Wei & He, Jiangen & Wang, Yuqi, 2022. "Combination of research questions and methods: A new measurement of scientific novelty," Journal of Informetrics, Elsevier, vol. 16(2).
    4. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    5. Chen, Wei & Yan, Yan, 2023. "New components and combinations: The perspective of the internal collaboration networks of scientific teams," Journal of Informetrics, Elsevier, vol. 17(2).
    6. Guan, JianCheng & Zhang, JingJing, 2018. "The dynamics of partner and knowledge portfolios in alternative energy field," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2869-2879.
    7. Ron Boschma & Ernest Miguelez & Rosina Moreno & Diego B. Ocampo-Corrales, 2021. "Technological breakthroughs in European regions: the role of related and unrelated combinations," Papers in Evolutionary Economic Geography (PEEG) 2118, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2021.
    8. Sandro Montresor & Gianluca Orsatti & Francesco Quatraro, 2023. "Technological novelty and key enabling technologies: evidence from European regions," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(6), pages 851-872, August.
    9. Zhang, JingJing & Yan, Yan & Guan, JianCheng, 2019. "Recombinant distance, network governance and recombinant innovation," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 260-272.
    10. Bornmann, Lutz & Tekles, Alexander & Zhang, Helena H. & Ye, Fred Y., 2019. "Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data," Journal of Informetrics, Elsevier, vol. 13(4).
    11. Yan Yan & Jiancheng Guan, 2018. "How multiple networks help in creating knowledge: evidence from alternative energy patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 51-77, April.
    12. JingJing Zhang & Jiancheng Guan, 2017. "Scientific relatedness and intellectual base: a citation analysis of un-cited and highly-cited papers in the solar energy field," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 141-162, January.
    13. Kuniko Matsumoto & Sotaro Shibayama & Byeongwoo Kang & Masatsura Igami, 2021. "Introducing a novelty indicator for scientific research: validating the knowledge-based combinatorial approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6891-6915, August.
    14. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    15. Fontana, Magda & Iori, Martina & Montobbio, Fabio & Sinatra, Roberta, 2020. "New and atypical combinations: An assessment of novelty and interdisciplinarity," Research Policy, Elsevier, vol. 49(7).
    16. Yan, Hong-Bin & Li, Ming, 2022. "Consumer demand based recombinant search for idea generation," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    17. Ugo Rizzo & Nicolò Barbieri & Laura Ramaciotti & Demian Iannantuono, 2020. "The division of labour between academia and industry for the generation of radical inventions," The Journal of Technology Transfer, Springer, vol. 45(2), pages 393-413, April.
    18. Martorell Cunil, Onofre & Otero González, Luis & Durán Santomil, Pablo & Mulet Forteza, Carlos, 2023. "How to accomplish a highly cited paper in the tourism, leisure and hospitality field," Journal of Business Research, Elsevier, vol. 157(C).
    19. Cammarano, Antonello & Michelino, Francesca & Lamberti, Emilia & Caputo, Mauro, 2017. "Accumulated stock of knowledge and current search practices: The impact on patent quality," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 204-222.
    20. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03314-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.