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The implications of big data for developing and transitional economies: Extending the Triple Helix?

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  • Marko M. Skoric

    (City University of Hong Kong)

Abstract

This study examines the implications of the predicted big data revolution in social sciences for the research using the Triple Helix (TH) model of innovation and knowledge creation in the context of developing and transitional economies. While big data research promises to transform the nature of social inquiry and improve the world economy by increasing the productivity and competitiveness of companies and enhancing the functioning of the public sector, it may also potentially lead to a growing divide in research capabilities between developed and developing economies. More specifically, given the uneven access to digital data and scarcity of computational resources and talent, developing countries are at disadvantage when it comes to employing data-driven, computational methods for studying the TH relations between universities, industries and governments. Scientometric analysis of the TH literature conducted in this study reveals a growing disparity between developed and developing countries in their use of innovative computational research methods. As a potential remedy, the extension of the TH model is proposed to include non-market actors as subjects of study as well as potential providers of computational resources, education and training.

Suggested Citation

  • Marko M. Skoric, 2014. "The implications of big data for developing and transitional economies: Extending the Triple Helix?," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 175-186, April.
    • Handle: RePEc:spr:scient:v:99:y:2014:i:1:d:10.1007_s11192-013-1106-5
    DOI: 10.1007/s11192-013-1106-5
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    References listed on IDEAS

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    1. Gohar Feroz Khan & Han Woo Park, 2012. "Editorial: Triple Helix and innovation in Asia using scientometrics, webometrics, and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 1-7, January.
    2. Gohar Feroz Khan & Junghoon Moon & Han Woo Park & Bobby Swar & Jae Jeung Rho, 2011. "A socio-technical perspective on e-government issues in developing countries: a scientometrics approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 267-286, May.
    3. Sujin Choi & Ji-young Park & Han Woo Park, 2012. "Using social media data to explore communication processes within South Korean online innovation communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 43-56, January.
    4. Loet Leydesdorff, 2012. "The Triple Helix, Quadruple Helix, …, and an N-Tuple of Helices: Explanatory Models for Analyzing the Knowledge-Based Economy?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 3(1), pages 25-35, March.
    5. Park, Han Woo & Leydesdorff, Loet, 2013. "Decomposing social and semantic networks in emerging “big data” research," Journal of Informetrics, Elsevier, vol. 7(3), pages 756-765.
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    Cited by:

    1. Jungwon Yoon & Joshua SungWoo Yang & Han Woo Park, 2017. "Quintuple helix structure of Sino-Korean research collaboration in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 61-81, October.
    2. Miguel A. Ortiz Acuña & Adiel T. Almeida Filho & Francisco S. Ramos, 2024. "Modelling the triple helix system innovation of the main economies from Latin America: a coalitional game theory approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3245-3270, June.

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