IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i7d10.1007_s11192-022-04443-1.html
   My bibliography  Save this article

Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage

Author

Listed:
  • Dejian Yu

    (Nanjing Audit University)

  • Zhaoping Yan

    (Nanjing Audit University)

Abstract

With the development of the era of big data, research data are accumulating, and various research directions emerge endlessly. It is difficult for researchers to grasp the hotspots and development trends of the discipline. Therefore, exploring methods to quickly and accurately identify research fronts is of great significance to scientific and technological innovation. This paper proposes a research front identification method integrating machine learning and main path analysis in conjunction with papers and patents based on the existing research. The innovation of this method is the combination of citation analysis and semantic analysis to identify research front from the perspective of science-technology linkage. This article takes the Internet of Things in supply chain as an example to verify the feasibility and effectiveness of the method. It is of great significance to identify important scientific and technological research fronts in a specific domain by intuitively revealing knowledge diffusion and text mining. The proposed method enriches the application of MPA and helps scholars grasp the latest information, mainstreams and future directions.

Suggested Citation

  • Dejian Yu & Zhaoping Yan, 2022. "Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4251-4274, July.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:7:d:10.1007_s11192-022-04443-1
    DOI: 10.1007/s11192-022-04443-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04443-1
    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/s11192-022-04443-1?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. Zhang, Li-Hao & Li, Tian & Fan, Ti-Jun, 2018. "Radio-frequency identification (RFID) adoption with inventory misplacement under retail competition," European Journal of Operational Research, Elsevier, vol. 270(3), pages 1028-1043.
    2. Hwang, Seonho & Shin, Juneseuk, 2019. "Extending technological trajectories to latest technological changes by overcoming time lags," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 142-153.
    3. Jiaojiao Ji & George A. Barnett & Jianxun Chu, 2019. "Global networks of genetically modified crops technology: a patent citation network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 737-762, March.
    4. Shuo Xu & Dongsheng Zhai & Feifei Wang & Xin An & Hongshen Pang & Yirong Sun, 2019. "A novel method for topic linkages between scientific publications and patents," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(9), pages 1026-1042, September.
    5. Yang, Huixiao & Chen, Wenbo, 2020. "Game modes and investment cost locations in radio-frequency identification (RFID) adoption," European Journal of Operational Research, Elsevier, vol. 286(3), pages 883-896.
    6. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    7. Vincent C. Ma & John S. Liu, 2016. "Exploring the research fronts and main paths of literature: a case study of shareholder activism research," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 33-52, October.
    8. Olle Persson, 1994. "The intellectual base and research fronts of JASIS 1986–1990," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(1), pages 31-38, January.
    9. Carpenter, Mark P. & Narin, Francis, 1983. "Validation study: Patent citations as indicators of science and foreign dependence," World Patent Information, Elsevier, vol. 5(3), pages 180-185.
    10. John S. Liu & Louis Y. Y. Lu & Wen-Min Lu, 2016. "Research Fronts and Prevailing Applications in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 543-574, Springer.
    11. Wang, Jianxin & Lim, Ming K. & Zhan, Yuanzhu & Wang, XiaoFeng, 2020. "An intelligent logistics service system for enhancing dispatching operations in an IoT environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    12. Jiang, Xiaorui & Zhuge, Hai, 2019. "Forward search path count as an alternative indirect citation impact indicator," Journal of Informetrics, Elsevier, vol. 13(4).
    13. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    14. Fan, Tijun & Tao, Feng & Deng, Sheng & Li, Shuxia, 2015. "Impact of RFID technology on supply chain decisions with inventory inaccuracies," International Journal of Production Economics, Elsevier, vol. 159(C), pages 117-125.
    15. Junmo Kim & Juneseuk Shin, 2018. "Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1439-1459, September.
    16. Mauricio Marrone, 2020. "Application of entity linking to identify research fronts and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 357-379, January.
    17. Wolfgang Glänzel & Martin Meyer, 2003. "Patents cited in the scientific literature: An exploratory study of 'reverse' citation relations," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(2), pages 415-428, October.
    18. Yi-Ching Liaw & Te-Yi Chan & Chin-Yuan Fan & Cheng-Hsin Chiang, 2014. "Can the technological impact of academic journals be evaluated? The practice of non-patent reference (NPR) analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 17-37, October.
    19. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    20. Li, Ling, 2013. "Technology designed to combat fakes in the global supply chain," Business Horizons, Elsevier, vol. 56(2), pages 167-177.
    21. Noyons, E. C. M. & van Raan, A. F. J. & Grupp, H. & Schmoch, U., 1994. "Exploring the science and technology interface: inventor-author relations in laser medicine research," Research Policy, Elsevier, vol. 23(4), pages 443-457, July.
    22. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    23. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    24. Cannella, Salvatore & Dominguez, Roberto & Framinan, Jose M., 2017. "Inventory record inaccuracy – The impact of structural complexity and lead time variability," Omega, Elsevier, vol. 68(C), pages 123-138.
    25. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
    26. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    27. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Romero-Castro, Noelia María & Pérez-Pico, Ada María, 2020. "Innovation, entrepreneurship and knowledge in the business scientific field: Mapping the research front," Journal of Business Research, Elsevier, vol. 115(C), pages 475-485.
    28. Huang, Mu-Hsuan & Yang, Hsiao-Wen & Chen, Dar-Zen, 2015. "Increasing science and technology linkage in fuel cells: A cross citation analysis of papers and patents," Journal of Informetrics, Elsevier, vol. 9(2), pages 237-249.
    29. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    30. Martin Meyer, 2002. "Tracing knowledge flows in innovation systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 193-212, June.
    31. Li-Hao Zhang & Huixiao Yang, 2019. "Incentives for RFID adoption with imperfect read rates: Wholesale price premium versus cost sharing," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(9), pages 1440-1456, September.
    32. Ba, Zhichao & Liang, Zhentao, 2021. "A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling," Journal of Informetrics, Elsevier, vol. 15(3).
    33. Balconi, Margherita & Breschi, Stefano & Lissoni, Francesco, 2004. "Networks of inventors and the role of academia: an exploration of Italian patent data," Research Policy, Elsevier, vol. 33(1), pages 127-145, January.
    34. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    35. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    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. Houqiang Yu & Yian Liang & Yinghua Xie, 2024. "Predicting Scientific Breakthroughs Based on Structural Dynamic of Citation Cascades," Mathematics, MDPI, vol. 12(11), pages 1-18, June.
    2. Qiang Gao & Man Jiang, 2024. "Exploring technology fusion by combining latent Dirichlet allocation with Doc2vec: a case of digital medicine and machine learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4043-4070, July.

    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. Shuo Xu & Ling Li & Xin An, 2023. "Do academic inventors have diverse interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1023-1053, February.
    2. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
    3. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    4. Martin Eling & Omid Ghavibazoo, 2019. "Research on long-term care insurance: status quo and directions for future research," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(2), pages 303-356, April.
    5. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    6. Kuan, Chung-Huei & Lin, Jia-Tian & Chen, Dar-Zen, 2021. "Characterizing Patent Assignees by Their Structural Positions Relative to a Field’s Evolutionary Trajectory," Journal of Informetrics, Elsevier, vol. 15(4).
    7. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    8. Boyack, Kevin W. & Klavans, Richard, 2008. "Measuring science–technology interaction using rare inventor–author names," Journal of Informetrics, Elsevier, vol. 2(3), pages 173-182.
    9. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
    10. Li-Hao Zhang & Shan-Shan Wang, 2022. "Strategic analysis of RFID adoption sequences in a supply chain with Cournot competition: effects of ordering-timing strategies," Annals of Operations Research, Springer, vol. 315(2), pages 2169-2208, August.
    11. Yu, Dejian & Yan, Zhaoping, 2023. "Main path analysis considering citation structure and content: Case studies in different domains," Journal of Informetrics, Elsevier, vol. 17(1).
    12. Ba, Zhichao & Liang, Zhentao, 2021. "A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling," Journal of Informetrics, Elsevier, vol. 15(3).
    13. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Xu, Haiyun & Yang, Guancan, 2022. "A semantic main path analysis method to identify multiple developmental trajectories," Journal of Informetrics, Elsevier, vol. 16(2).
    14. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    15. Meyer, Martin, 2006. "Are patenting scientists the better scholars?: An exploratory comparison of inventor-authors with their non-inventing peers in nano-science and technology," Research Policy, Elsevier, vol. 35(10), pages 1646-1662, December.
    16. Zhou, Yong & Yang, Qijin & Lu, Shuo, 2023. "Research on the identification and formation mechanism of the main path of digital technology diffusion: Empirical evidence from China," Technology in Society, Elsevier, vol. 75(C).
    17. Hwang, Seonho & Shin, Juneseuk, 2019. "Extending technological trajectories to latest technological changes by overcoming time lags," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 142-153.
    18. Ba, Zhichao & Meng, Kai & Ma, Yaxue & Xia, Yikun, 2024. "Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    19. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    20. Wang, Xiaoli & Liang, Wenting & Ye, Xuanting & Chen, Lingdi & Liu, Yun, 2024. "Disruptive development path measurement for emerging technologies based on the patent citation network," Journal of Informetrics, Elsevier, vol. 18(1).

    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:127:y:2022:i:7:d:10.1007_s11192-022-04443-1. 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.