Proof over promise: towards a more inclusive ranking of Dutch academics in Economics & Business

The Dutch Economics top-40, based on publications in ISI listed journals, is - to the best of our knowledge - the oldest ranking of individual academics in Economics and is well accepted in the Dutch academic community. However, this ranking is based on publication volume, rather than on the actual impact of the publications in question. This paper therefore uses two relatively new metrics, the citations per author per year (CAY) metric and the individual annual h-index (hIa) to provide two alternative, citation-based, rankings of Dutch academics in Economics & Business. As a data source, we use Google Scholar instead of ISI to provide a more comprehensive measure of impact, including citations to and from publications in non-ISI listed journals, books, working and conference papers. The resulting rankings are shown to be substantially different from the original ranking based on publications. Just like other research metrics, the CAY or hIa-index should never be used as the sole criterion to evaluate academics. However, we do argue that the hIa-index and the related citations per author per year metric provide an important additional perspective over and above a ranking based on publications in high impact journals alone. Citation-based rankings are also shown to inject a higher level of diversity in terms of age, gender, discipline and academic affiliation and thus appear to be more inclusive of a wider range of scholarship

Do we need to distance ourselves from the distance concept? Why home and host country context might matter more than (cultural) distance

We scrutinize the explanatory power of one of the key concepts in International Business: the concept of (cultural) distance. Here we focus on its effect on entry mode choice, one of the most researched fields in international business strategy. Our findings might, however, be equally be relevant for the field of International Business as a whole. Our analysis is based on a review of 92 prior studies on entry mode choice, as well as an empirical investigation in over 800 subsidiaries of MNCs, covering nine host and fifteen home countries across the world. We conclude that the explanatory power of distance is highly limited once home and host country context are accounted for, and that any significant effects of cultural distance on entry mode choice might simply be caused by inadequate sampling. Entry mode studies in particular, and International Business research in general, would do well to reconsider its fascination with distance measures, and instead, focus first and foremost on differences in home and host country context. We argue that serious engagement with deep contextualization is necessary in International Business research to pose new and relevant questions and develop new and innovative theories that explain empirical phenomena

Why and how does shared language affect subsidiary knowledge inflows? A social identity perspective

We draw on social identity theory to conceptualize a moderated mediation model that examines the relationship between shared language among subsidiary and HQ managers, and subsidiaries’ knowledge inflows from HQ. Specifically, we study (1) whether this relationship is mediated by the extent to which subsidiary managers share HQ goals and vision, and the extent to which HR decisions are centralized; and (2) whether subsidiary type moderates these mediated relationships. Building on a sample of 817 subsidiaries in nine countries/regions, we find support for our model. Implications for research on HQ-subsidiary knowledge flows, social identity theory and international HRM are discussed

Using Google Scholar Institutional Level Data to Evaluate the Quality of University Research

In recent years, the extent of formal research evaluation, at all levels from the individual to the multiversity has increased dramatically. At the institutional level, there are world university rankings based on an ad hoc combination of different indicators. There are also national exercises, such as those in the UK and Australia that evaluate research outputs and environment through peer review panels. These are extremely costly and time consuming. This paper evaluates the possibility of using Google Scholar (GS) institutional level data to evaluate university research in a relatively automatic way. Several citation-based metrics are collected from GS for all 130 UK universities. These are used to evaluate performance and produce university rankings which are then compared with various rankings based on the 2014 UK Research Excellence Framework (REF). The rankings are shown to be credible and to avoid some of the obvious problems of the REF ranking, as well as being highly efficient and cost effective. We also investigate the possibility of normalizing the results for the university subject mix since science subjects generally produce significantly more citations than social science or humanities

Google Scholar Metrics evolution: an analysis according to languages

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-013-1164-8In November 2012 the Google Scholar Metrics (GSM) journal rankings were updated, making it possible to compare bibliometric indicators in the ten languages indexed—and their stability—with the April 2012 version. The h-index and h-5 median of 1,000 journals were analysed, comparing their averages, maximum and minimum values and the correlation coefficient within rankings. The bibliometric figures grew significantly. In just seven and a half months the h-index of the journals increased by 15 % and the median h-index by 17 %. This growth was observed for all the bibliometric indicators analysed and for practically every journal. However, we found significant differences in growth rates depending on the language in which the journal is published. 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COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts

© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance