IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v81y2009i3d10.1007_s11192-009-2058-7.html
   My bibliography  Save this article

Structural equation model with PLS path modeling for an integrated system of publicly funded basic research

Author

Listed:
  • Jiancheng Guan

    (Fudan University)

  • Nan Ma

    (Beijing University of Aeronautics and Astronautics)

Abstract

This study develops and tests an integrated conceptual model of basic research evaluation from a varying perspective. The main objective is to obtain a more complete understanding of the external factors affecting the publicly fund basic research in a country. Structural Equation Modeling (SEM) with Partial Least Squares (PLS) is used to test the conceptual model with empirical data collected from WCY (World Competitiveness Yearbook) and ESI (Essential Science Indicators) database. Interrelationships among the research output and outcome, together with three external factors (resource, impetus, accumulative advantage) have been successfully explored and the conceptual model of journal evaluation has been examined.

Suggested Citation

  • Jiancheng Guan & Nan Ma, 2009. "Structural equation model with PLS path modeling for an integrated system of publicly funded basic research," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 683-698, December.
  • Handle: RePEc:spr:scient:v:81:y:2009:i:3:d:10.1007_s11192-009-2058-7
    DOI: 10.1007/s11192-009-2058-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-009-2058-7
    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/s11192-009-2058-7?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. Cozzens, Susan E., 1997. "The knowledge pool: Measurement challenges in evaluating fundamental research programs," Evaluation and Program Planning, Elsevier, vol. 20(1), pages 77-89, February.
    2. Mansfield, Edwin, 1991. "Academic research and industrial innovation," Research Policy, Elsevier, vol. 20(1), pages 1-12, February.
    3. Chaves, Catari Vilela & Moro, Sueli, 2007. "Investigating the interaction and mutual dependence between science and technology," Research Policy, Elsevier, vol. 36(8), pages 1204-1220, October.
    4. Anthony F J van Raan, 1993. "Advanced bibliometric methods to assess research performance and scientific development: basic principles and recent practical applications," Research Evaluation, Oxford University Press, vol. 3(3), pages 151-166, December.
    5. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    6. Sohn, S.Y. & Gyu Joo, Yong & Kyu Han, Hong, 2007. "Structural equation model for the evaluation of national funding on R&D project of SMEs in consideration with MBNQA criteria," Evaluation and Program Planning, Elsevier, vol. 30(1), pages 10-20, February.
    7. Dominique Guellec & Bruno Van Pottelsberghe de la Potterie, 2004. "From R&D to Productivity Growth: Do the Institutional Settings and the Source of Funds of R&D Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 353-378, July.
    8. Adams, James D, 1990. "Fundamental Stocks of Knowledge and Productivity Growth," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 673-702, August.
    9. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    10. Mansfield, Edwin, 1980. "Basic Research and Productivity Increase in Manufacturing," American Economic Review, American Economic Association, vol. 70(5), pages 863-873, December.
    11. Mansfield, Edwin, 1992. "Academic research and industrial innovation: A further note," Research Policy, Elsevier, vol. 21(3), pages 295-296, June.
    12. Phillimore, A. J., 1989. "University research performance indicators in practice: The University Grants Committee's evaluation of British universities, 1985-86," Research Policy, Elsevier, vol. 18(5), pages 255-271, October.
    13. Francis Narin & Dominic Olivastro & Kimberly A. Stevens, 1994. "Bibliometrics/Theory, Practice and Problems," Evaluation Review, , vol. 18(1), pages 65-76, February.
    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. 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.
    2. Giulio Giacomo Cantone, 2024. "How to measure interdisciplinary research? A systemic design for the model of measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4937-4982, August.
    3. Tang Yao & Yigang Wei & Jianhong Zhang & Yani Wang & Yunjiang Yu & Wenyang Huang, 2022. "What influences the urban sewage discharge in China? The effect of diversified factors on the urban sewage discharge in different regions of China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6099-6135, May.
    4. Cui Huang & Jun Su & Xiang Xie & Jiang Li, 2014. "Basic research is overshadowed by applied research in China: a policy perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 689-694, June.
    5. Xinhua Zhu & Yigang Wei & Yani Lai & Yan Li & Sujuan Zhong & Chun Dai, 2019. "Empirical Analysis of the Driving Factors of China’s ‘Land Finance’ Mechanism Using Soft Budget Constraint Theory and the PLS-SEM Model," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
    6. Chen, Kaihua & Guan, Jiancheng, 2011. "Mapping the functionality of China's regional innovation systems: A structural approach," China Economic Review, Elsevier, vol. 22(1), pages 11-27, March.

    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. Kokko, Ari & Tingvall, Patrik Gustavsson & Videnord, Josefin, 2015. "The growth effects of R&D spending in the EU: A meta-analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-26.
    2. Gersbach, Hans & Sorger, Gerhard & Amon, Christian, 2018. "Hierarchical growth: Basic and applied research," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 434-459.
    3. Gersbach, Hans & Schetter, Ulrich & Schmassmann, Samuel, 2023. "From local to global: A theory of public basic research in a globalized world," European Economic Review, Elsevier, vol. 160(C).
    4. Roel van Elk & Bas ter Weel & Karen van der Wiel & Bram Wouterse, 2019. "Estimating the Returns to Public R&D Investments: Evidence from Production Function Models," De Economist, Springer, vol. 167(1), pages 45-87, March.
    5. Jürgen Janger & Matthias Firgo & Kathrin Hofmann & Agnes Kügler & Anna Strauss-Kollin & Gerhard Streicher & Hans Pechar, 2017. "Wirtschaftliche und gesellschaftliche Effekte von Universitäten," WIFO Studies, WIFO, number 60794, August.
    6. Andrea Bonaccorsi & Cinzia Daraio, 2013. "Knowledge spillover effects at the sub-regional level. Theory and estimation," DIAG Technical Reports 2013-13, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    7. Leyden, Dennis & Link, Albert N., 2012. "Knowledge Spillovers, Collective Entrepreneurship, & Economic Growth: The Role of Universities," UNCG Economics Working Papers 12-8, University of North Carolina at Greensboro, Department of Economics.
    8. Dennis Leyden & Albert Link, 2013. "Knowledge spillovers, collective entrepreneurship, and economic growth: the role of universities," Small Business Economics, Springer, vol. 41(4), pages 797-817, December.
    9. Bronwyn H. Hall & Albert N. Link & John T. Scott, 2003. "Universities as Research Partners," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 485-491, May.
    10. G Cameron, 1996. "Innovation and Economic Growth," CEP Discussion Papers dp0277, Centre for Economic Performance, LSE.
    11. Richard Florida & Ruben Gaetani, 2020. "The university's Janus face: The innovation–inequality nexus," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 1097-1112, September.
    12. Carillo, Maria Rosaria & Papagni, Erasmo, 2014. "“Little Science” and “Big Science”: The institution of “Open Science” as a cause of scientific and economic inequalities among countries," Economic Modelling, Elsevier, vol. 43(C), pages 42-56.
    13. Hans Gersbach & Maik Schneider & Olivier Schneller, 2013. "Basic research, openness, and convergence," Journal of Economic Growth, Springer, vol. 18(1), pages 33-68, March.
    14. Maria Rosaria Carillo & Erasmo Papagni, 2004. "Academic Research, Social Interactions And Economic Growth," Working Papers 10_2004, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    15. Lawrence J. White, 1999. "University-Industry Research and Development Relationships: The University Perspective," Working Papers 99-12, New York University, Leonard N. Stern School of Business, Department of Economics.
    16. Cameron, Gavin & Proudman, James & Redding, Stephen, 2005. "Technological convergence, R&D, trade and productivity growth," European Economic Review, Elsevier, vol. 49(3), pages 775-807, April.
    17. Banerjee, Rajabrata & Gupta, Kartick, 2021. "Do country or firm-specific factors matter more to R&D spending in firms?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 75-95.
    18. Diamond, Arthur Jr., 2003. "Edwin Mansfield's contributions to the economics of technology," Research Policy, Elsevier, vol. 32(9), pages 1607-1617, October.
    19. Young Eun Kim & Norman V. Loayza, 2019. "Productivity Growth: Patterns and Determinants across the World," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(84), pages 36-93.
    20. Mosahid Khan & Kul B. Luintel & Konstantinos Theodoris, 2010. "How Robust is the R&D – Productivity relationship? Evidence from OECD Countries," WIPO Economic Research Working Papers 01, World Intellectual Property Organization - Economics and Statistics Division, revised Dec 2010.

    More about this item

    Statistics

    Access and download statistics

    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:81:y:2009:i:3:d:10.1007_s11192-009-2058-7. 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.