Ranking Economists on the Basis of Many Indicators: An Alternative Approach Using RePEc Data

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different indicators for more than 30,000 economists. Based on this bibliographic information RePEc calculates well-known rankings for authors and academic institutions. We provide some cautionary remarks concerning the interpretation of some provided bibliometric measures in RePEc. Moreover, we show how individual and aggregated rankings can be biased due to the employed ranking methodology. In order to select key in-dicators describing and assessing research performance of scientist, we propose to apply principal component analysis in this data-rich environment. This approach allows us to assign weights to each indicator prior to aggregation. We illustrate the approach by providing a new overall ranking of economists based on RePEc data.RePEc, ranking aggregation, principal components analysis, economics profession

Which World Bank reports are widely read?

Knowledge is central to development. The World Bank invests about one-quarter of its budget for country services in knowledge products. Still, there is little research about the demand for these knowledge products and how internal knowledge flows affect their demand. About 49 percent of the World Bank’s policy reports, which are published Economic and Sector Work or Technical Assistance reports, have the stated objective of informing the public debate or influencing the development community. This study uses information on downloads and citations to assesses whether policy reports meet this objective. About 13 percent of policy reports were downloaded at least 250 times while more than 31 percent of policy reports are never downloaded. Almost 87 percent of policy reports were never cited. More expensive, complex, multi-sector, core diagnostics reports on middle-income countries with larger populations tend to be downloaded more frequently. Multi-sector reports also tend to be cited more frequently. Internal knowledge sharing matters as cross support provided by the World Bank’s Research Department consistently increases downloads and citations

Positional Effects on Citation and Readership in arXiv

arXiv.org mediates contact with the literature for entire scholarly communities, both through provision of archival access and through daily email and web announcements of new materials, potentially many screenlengths long. We confirm and extend a surprising correlation between article position in these initial announcements, ordered by submission time, and later citation impact, due primarily to intentional "self-promotion" on the part of authors. A pure "visibility" effect was also present: the subset of articles accidentally in early positions fared measurably better in the long-term citation record than those lower down. Astrophysics articles announced in position 1, for example, overall received a median number of citations 83\% higher, while those there accidentally had a 44\% visibility boost. For two large subcommunities of theoretical high energy physics, hep-th and hep-ph articles announced in position 1 had median numbers of citations 50\% and 100\% larger than for positions 5--15, and the subsets there accidentally had visibility boosts of 38\% and 71\%. We also consider the positional effects on early readership. The median numbers of early full text downloads for astro-ph, hep-th, and hep-ph articles announced in position 1 were 82\%, 61\%, and 58\% higher than for lower positions, respectively, and those there accidentally had medians visibility-boosted by 53\%, 44\%, and 46\%. Finally, we correlate a variety of readership features with long-term citations, using machine learning methods, thereby extending previous results on the predictive power of early readership in a broader context. We conclude with some observations on impact metrics and dangers of recommender mechanisms.Comment: 28 pages, to appear in JASIS

Downloads vs. Citations: Relationships, Contributing Factors and Beyond

Citations to 200 top downloaded papers at RePEc, a digital library in economics, were obtained from SSCI and Google Scholar respectively to address questions relating to downloads and their corresponding citations. This study finds that top downloaded documents are used in various degrees when citation is regarded as an indicator of usage. Results also show that a single downloaded paper selected for this study on average receives twice as many citations from Google Scholar as that from SSCI although the latter has been established much earlier in time. According to the coefficients computed, downloads appear having a moderate relationship with citations. However, other measures such as the download vs citation ratio indicate a stronger connection between the two. While author’s reputation positively affect both download and citation frequencies, other factors (e.g., targeted readers and subject content) seem in play differently for the documents that are repeatedly downloaded or cited. In a nutshell, an infrastructure that encourages downloading at digital libraries would eventually lead to higher usage of their resources

Usage Bibliometrics

Scholarly usage data provides unique opportunities to address the known shortcomings of citation analysis. However, the collection, processing and analysis of usage data remains an area of active research. This article provides a review of the state-of-the-art in usage-based informetric, i.e. the use of usage data to study the scholarly process.Comment: Publisher's PDF (by permission). Publisher web site: books.infotoday.com/asist/arist44.shtm