International Collaboration in Open Access Publications: How Income Shapes International Collaboration

Publications

Taylor Rockwell¹  Michael Cary² 

[1] Department of English, West Virginia University, Morgantown, WV 26506, USA;Division of Resource Economics and Management, West Virginia University, Morgantown, WV 26506, USA;

关键词: international collaboration;    collaboration;    open access;    open science;    publication;    data set;   

DOI  :  10.3390/publications8010013

来源: DOAJ

【 摘 要 】

Does the rise of open access journals change the way researchers collaborate? Specifically, since publishing in open access journals requires a publication fee, does income affect how researchers form international collaborations? To answer this question, we create a new data set by scraping bibliographic data from Multidisciplinary Digital Publishing Institute (MDPI) journals. Using the four income group classifications from the World Bank Analytical Classifications, we find that researchers from low-income nations are more likely to form international collaborations than researchers from wealthier nations. This result is verified to be significant using a series of pairwise Kolmogorov−Smirnov tests. We then study which nations most frequently form international collaborations with other nations and find that the USA, China, Germany, and France are the most preferred nations for forming international collaborations. While most nations prefer to form international collaborations with high-income nations, some exceptions exist, where a nation most often forms international collaborations with a nearby nation that is either an upper-middle-income or lower-middle-income nation. We further this analysis by showing that these results are apparent across the six different research categories established in the Frascati Manual. Finally, trends in publications in MDPI journals mirror trends seen in all journals, such as the continued increase in the percentage of published papers involving international collaboration.

【 授权许可】

Unknown