12.1.3 Examples of bibliometric research on authors

Many academics have used Publish or Perish to do an impact analysis of authors and create rankings of scholars in their specific field. Below, I discuss a very small selection of these efforts to give you an idea how you can use PoP to do bibliometric analysis for authors. A more detailed example of how to use Publish or Perish for bibliometric research on authors across disciplines can be found in Chapter 16 (Author citation analysis across disciplines).

Most of these examples are in the broad field of Economics & Business. This is probably partly caused by the fact that I am working in this field myself and hence academics are more likely to send me papers in this area. However, it also reflects the fact that Google Scholar and Publish and Perish provide a more comprehensive assessment of research impact in this field (for more details see Chapter 16). However, the basic topics and methods described in these papers are equally applicable in other disciplines.

Ranking Israel's economists

Ben-David (2010) examined Israel's academic economists and economics departments, ranking them according to the number of citations on their work in Google Scholar. He finds that although in general there is link between the academic rank of a researcher and the number of citations received, there are a large number of individuals at lower ranks who have considerably more citations than those at professorial ranks.

Ben-David argues that promotion rigidities and discrepancies have been a major factor in the unparalleled brain drain of junior academics, especially in Economics. He also indicates that the rise of the Internet, freely available citation data in Google Scholar software such as Publish and Perish software, “makes it possible to shine many a bright spotlight into areas that were, until now, very difficult and expensive to observe.” (Ben-David, 2010: 361). This is exactly the kind of transparency and level of empowerment for individual academics that Publish or Perish was designed for!

German scholars in Business administration

Breuer (2009) used Google scholar for a citation-based ranking of more than 100 German scholars in business administration. He found their ranking to be only weakly correlated with existing rankings, which were either based on publications in German language journals only or on publications in top ISI listed journals. Breuer prefers the Google Scholar ranking as it does not create an ex-ante discrimination across different kinds of publication outlets.

He sees the fact that Google Scholar leads to more attention for non-journal publications as a strong positive as books have traditionally been important publication outlets in Germany. He also argues that Google Scholar based ranking may help to reduce the US-American dominance in business administration. Finally, he sees Google Scholar as more in tune with current times where the internet allows the fast dissemination of new knowledge in the form of working papers.

Research impact of fellows of professional associations in management

Mingers (2009) applies the Google Scholar h-index and related measures to rank a random sample of 30 members of three groups of management scholars: BAM (British Academy of Management) fellows, members of COPIOR (Committee of Professors in Operations Research) and INFORMS (Institute for Operations Research and the Management Sciences) fellows. Whilst the first two groups mainly consist of British academics, the last group consists mainly of US academics.

Mingers finds that there is a large variance within this group of highly distinguished academics, with h-indices ranging from 4 to 38. This leads Mingers to conclude that Fellowships by learned societies are not always awarded on the basis of research output, but presumably also because of contribution in other areas. On average, the first and last group have h-indices of 18, whilst the average for COPIOR members is lower at around 15.

This article is one of the few papers that includes Hirsch's m (called h-rate by Mingers). Using the h-rate instead of the h-index drastically changes the rankings of academics as it improves the scores of those with shorter careers over those with longer career. Mingers concludes that an h-rate of 1 could be seen as reflective of a top scholar. I read a similar conclusion in the analysis conducted in Chapter 16, where I compare citation metrics across disciplines.

Cumulative and career-stage citation impact in Social Pyschology

Nosek (2010) and his co-authors analyzed citation data for more than 600 academics in the field of social psychology in the US and Canada, using Google scholar and Publish or Perish to gather their data. Data were analyzed both at the individual level and at the departmental level. As the number of citations and the h-index are strongly linked to the academics seniority, they created new indicators unrelated to the number of years since PhD.

As a result they were able to provide benchmarks for evaluating impact across the career span in psychology, and other disciplines with similar citation patterns. The authors indicate that career-stage indicators can provide a very different perspective on the research impact of individuals and programs than cumulative impact. They can therefore be very useful to predict emerging scientists and programs.

The authors data management and search procedures are exemplary. Anyone wanting to conduct bibliometric research on authors would be well advised to read their paper. The paper also has an excellent supplementary page with career-stage impact calculators, additional analyses and search tips (http://projectimplicit.net/nosek/papers/citations/)