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Thematic less explored in the internet of things

Thematic less explored in the internet of things

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The bibliometric technics allow us to illustrate aspects of interpretation of data obtained through data bases that are focus in science spreading, which offers an aggregated value to researchers. In this article, we explore the importance of such obtained information from articles’ query; in this particular case study the Internet of Things (IoT)....

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... and Google Scholar databases. These results were obtained on January 30th 2015 and they are shown in Table 2. ...

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The main objective of this study is to investigate and analyze global research productivity in knowledge management (KM) research published from 1960 to 2017 and indexed in Scopus database. It is the first scientometric study investigating and analyzing 56 years of KM literature indexed in Scopus. The study used scientometric approach to identify and analyze bibliographic information of 63474 documents retrieved, in August 2018, from Scopus database. KM research productivity has grown from a single digit in 1960 to four digits in 2003. The results of the study indicate that, for the past 20 years (1997-2017), KM research recorded 63141 documents compared to 333 documents in 36 years (1960-1996), and the year 2009 emerged as the most productive year. China appeared leading the world in respect to the institutional productivity and took the second position, after the USA, as the most productive country in KM research. Findings of the study showed conference proceedings leading the types of publications followed by the journals, and book series. The “Journal of Knowledge Management” leads the top 10 journals in the number of publications, while the journal of “Expert Systems with Applications” top the list in the number of citations. A total of 4134 unique contributors produced an average of 15.35 papers from 1960-2017; and the top three authors are from Australia, USA, and Norway. Findings of the study could be a useful report for knowledge workers, academic institutions, and government agencies who are interested in improving KM projects and scientific research.