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.
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Acknowledgments
This work was supported by the cluster funding scheme from the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore. I would like to thank Zhu Qinfeng for her help with the database search and analysis.
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Skoric, M.M. The implications of big data for developing and transitional economies: Extending the Triple Helix?. Scientometrics 99, 175–186 (2014). https://doi.org/10.1007/s11192-013-1106-5
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DOI: https://doi.org/10.1007/s11192-013-1106-5