article

Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study

Authors:

Gustavo Cattelan Nobre,

Elaine TavaresAuthors Info & Claims

Scientometrics, Volume 111, Issue 1

Pages 463 - 492

https://doi.org/10.1007/s11192-017-2281-6

Published: 01 April 2017 Publication History

Abstract

Circular economy (CE) is a term that exists since the 1970s and has acquired greater importance in the past few years, partly due to the scarcity of natural resources available in the environment and changes in consumer behavior. Cutting-edge technologies such as big data and internet of things (IoT) have the potential to leverage the adoption of CE concepts by organizations and society, becoming more present in our daily lives. Therefore, it is fundamentally important for researchers interested in this subject to understand the status quo of studies being undertaken worldwide and to have the overall picture of it. We conducted a bibliometric literature review from the Scopus Database over the period of 2006---2015 focusing on the application of big data/IoT on the context of CE. This produced the combination of 30,557 CE documents with 32,550 unique big data/IoT studies resulting in 70 matching publications that went through content and social network analysis with the use of `R' statistical tool. We then compared it to some current industry initiatives. Bibliometrics findings indicate China and USA are the most interested countries in the area and reveal a context with significant opportunities for research. In addition, large producers of greenhouse gas emissions, such as Brazil and Russia, still lack studies in the area. Also, a disconnection between important industry initiatives and scientific research seems to exist. The results can be useful for institutions and researchers worldwide to understand potential research gaps and to focus future investments/studies in the field.

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cover image Scientometrics

Scientometrics Volume 111, Issue 1

April 2017

540 pages

ISSN:0138-9130

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Copyright © Copyright © 2017 Akadémiai Kiadó, Budapest, Hungary.

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Springer-Verlag

Berlin, Heidelberg

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Published: 01 April 2017

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