The ‘bioeconomics vs bioeconomy’ debate: Beyond criticism, advancing research fronts

2022 ◽  
Vol 42 ◽  
pp. 58-73
Author(s):  
Sandrine Allain ◽  
Jean-François Ruault ◽  
Marc Moraine ◽  
Sophie Madelrieux
Keyword(s):  
2020 ◽  
Vol 9 (3) ◽  
pp. 55-62
Author(s):  
Alistair Duffy ◽  
Gang Zhang

Omega ◽  
2016 ◽  
Vol 58 ◽  
pp. 33-45 ◽  
Author(s):  
John S. Liu ◽  
Louis Y.Y. Lu ◽  
Wen-Min Lu

2017 ◽  
Vol 2 (1) ◽  
pp. 89-104 ◽  
Author(s):  
Guoqiang Liang ◽  
Haiyan Hou ◽  
Zhigang Hu ◽  
Fu Huang ◽  
Yajie Wang ◽  
...  

Abstract Purpose Research fronts build on recent work, but using times cited as a traditional indicator to detect research fronts will inevitably result in a certain time lag. This study attempts to explore the effects of usage count as a new indicator to detect research fronts in shortening the time lag of classic indicators in research fronts detection. Design/methodology/approach An exploratory study was conducted where the new indicator “usage count” was compared to the traditional citation count, “times cited,” in detecting research fronts of the regenerative medicine domain. An initial topic search of the term “regenerative medicine” returned 10,553 records published between 2000 and 2015 in the Web of Science (WoS). We first ranked these records with usage count and times cited, respectively, and selected the top 2,000 records for each. We then performed a co-citation analysis in order to obtain the citing papers of the co-citation clusters as the research fronts. Finally, we compared the average publication year of the citing papers as well as the mean cited year of the co-citation clusters. Findings The citing articles detected by usage count tend to be published more recently compared with times cited within the same research front. Moreover, research fronts detected by usage count tend to be within the last two years, which presents a higher immediacy and real-time feature compared to times cited. There is approximately a three-year time span among the mean cited years (known as “intellectual base”) of all clusters generated by usage count and this figure is about four years in the network of times cited. In comparison to times cited, usage count is a dynamic and instant indicator. Research limitations We are trying to find the cutting-edge research fronts, but those generated based on co-citations may refer to the hot research fronts. The usage count of older highly cited papers was not taken into consideration, because the usage count indicator released by WoS only reflects usage logs after February 2013. Practical implications The article provides a new perspective on using usage count as a new indicator to detect research fronts. Originality/value Usage count can greatly shorten the time lag in research fronts detection, which would be a promising complementary indicator in detection of the latest research fronts.


2007 ◽  
Vol 74 (3) ◽  
pp. 331-344 ◽  
Author(s):  
Sandra Miguel ◽  
Félix Moya-Anegón ◽  
Víctor Herrero-Solana

2020 ◽  
Vol 218 ◽  
pp. 02010
Author(s):  
Jing Chang

Sustainability issues make the transformation to a more sustainable business model increasingly desirable. This study aims to analyze the literatures on SBM to provide a systematic review of the current status of the SBM literatures. This paper uses visual bibliometrics and comparative research methods to carry out collaboration, co-citation, and co-occurrence analyses of the literatures from the Web of Science by CiteSpace. Compared with the existing literature reviews of SBM, this paper makes a set of knowledge maps and analyzes visual results based on BMI-3 category framework to show the features of literatures, the future trend and the potential approaches contributing to SBM. It is the first study to present the major clusters to reveal their associated intellectual bases and research fronts in SBM.


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