Characterization of strategic emerging technologies: the case of big data
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DOI: 10.1007/s10100-018-0597-9
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- Min Song & Su Yeon Kim, 2013. "Detecting the knowledge structure of bioinformatics by mining full-text collections," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 183-201, July.
- Hyndman, Rob J. & Khandakar, Yeasmin, 2008.
"Automatic Time Series Forecasting: The forecast Package for R,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
- Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
- Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
- Bildosola, Iñaki & Río-Bélver, Rosa María & Garechana, Gaizka & Cilleruelo, Ernesto, 2017. "TeknoRoadmap, an approach for depicting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 25-37.
- Xin Ying An & Qing Qiang Wu, 2011. "Co-word analysis of the trends in stem cells field based on subject heading weighting," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 133-144, July.
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- Josefa Mula & Marija Bogataj, 2021. "OR in the industrial engineering of Industry 4.0: experiences from the Iberian Peninsula mirrored in CJOR," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(4), pages 1163-1184, December.
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Keywords
Strategic emerging technologies; Bibliometrics; Time series analysis; Technology forecasting; Big data;All these keywords.
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