Sample and Descriptive Statistics
Our data collection process starts by identifying all German universities that have the right to grant doctorates and have a business administration and/or economics faculty. After having identified these universities, we browse the web pages of the universities at the end of 2018 and collect the names of all business administration professors (n = 1116) at the respective business administration (or economics) faculties. Next, we gather CV information for each professor. For this purpose, we browse the CVs of the professors that are available online on the webpages of the universities or the personal webpages of the professors. We collect information (year and institution) regarding each career step (graduation, doctorate, habilitation, first tenured professorship) as well as demographic information (year of birth and gender) for each professor. For 70 professors we are not able to derive any information online, which restricts our sample to 1046 individuals.
To examine publication behavior in different fields of business administration, we merge data regarding the publications of the professors in our sample with our initial CV dataset. The online research-monitoring portal Forschungsmonitoring provides us with this publication data. This publication data is of high quality, as Forschungsmonitoring not only retrieves information from publication databases but also asks researchers to correct and complement their publication records.Footnote 13 The publication data contains information about the title, year, journal, and coauthors of all publications for each researcher. While merging our hand-collected CV data with the publication data, we drop eight professors, as they are not included in the publication dataset. Furthermore, we restrict the Forschungsmonitoring data to publications classified as “research articles” as we only focus on journal publications and further exclude conference presentations and conference proceedings. Also, we omit professors without any publications which are classified as research articles. Thus, our final dataset consists of 28,992 publications written by 1016 professors.
To assign each professor a field of business administration, we follow Eisend and Schuchert-Güler (2015), who use the fields in the journal Business Research, now Schmalenbach Journal of Business Research, as a classification scheme. According to the denomination of the respective professorship, we assign each professor to one of the following fields: accounting (n = 191), business information systems (n = 74), finance (n = 169), management (n = 265), marketing (n = 124), and operations (n = 137). We add a seventh category called other (n = 56) for those professors who do not fit in one of the above-listed categories.Footnote 14 Please note that we include financial accounting, managerial accounting and taxation professors in the accounting group. The operations group contains, according to the Business Research classification—besides operations professors—professors in the fields of entrepreneurship and innovation management, and thus is quite heterogeneous. The group of other professors largely consists of business education professors.Footnote 15
Table 1 reports summary statistics on the variables derived from the professor’s CVs that we use later in our regression analyses. E.g., the average time to tenure, i.e., the difference in years between the PhD and the first tenured professorship, is approximately seven years. The average age at which the professors in our data obtained their first tenured professorship is 37 years. On average, a professor in our sample has been tenured for roughly 12 years in 2018. Our sample includes 188 women, which equals approximately 19% of our sample.Footnote 16
Publication Behavior Variables
To explore the publication behavior in different fields of business administration, we build on all publications of each professor as of the end of 2018 as provided by Forschungsmonitoring. Based on this data, we create a set of new variables. These variables help us to improve our understanding of differences in publication behavior of professors in several business administration fields.Footnote 17 In order to provide a better overview over our results, we cluster these variables into four dimensions according to our research questions.
First, we investigate the national focus of the German business administration professors. Therefore, we calculate the share of publications with a German title. To do so, we apply Google’s Compact Language Detector 2 (Ooms 2018) on the titles of every publication. After having identified all publications with German titles, we compute for each professor in our data the fraction of publications with a German title. Next, we calculate for each field the mean of publications with a German title over all professors in the respective field. Second, we measure the share of publications in DACH region journals. To derive this variable, we process all journals included in our dataset by hand and tag those that originate from one of the three DACH countries.Footnote 18Footnote 19 Table 1 shows that the professors in our data set publish on average about 40% of their publications with German titles and almost every second (49%) publication in a DACH region journal.
Second, we analyze the focus on practitioner journals. In order to do so, we follow Fülbier and Weller (2011) and make use of the journal rating JQL3. More precisely, we classify D journals according to the JQL3 as well as journals where more than 50% of the respondents in the JQL3 survey stated that the journal is not primarily a scientific journal as practitioner journals. After having identified all practitioner journals, we compute the fraction of publications in practitioner journals for each professor individually. Next, we calculate the mean over all professors in the respective field to derive the average share of publications in practitioner journals for each field. Professors in our sample publish on average 18% of their papers in practitioner journals according to Table 1.
Third, we focus on three categories of publications in particularly prestigious journals. First, we focus on publications in journals included in the FT50 list (Vidgen et al. 2019; Zhang 2021; Fassin 2021). In particular, we calculate the number of publications in such journals for each professor before calculating the averages for each field. On average, professors in our sample have 1.73 FT50 publications. Second, we focus on publications in highly rated journals according to the JQL3 (Eisend 2011; Schrader and Henning-Thurau 2009). This rating essentially assigns any journal one of six categories: A+, A, B, C, D, and “not ranked”, with A+ being assigned to the journals with the highest attributed quality, i.e., the most prestigious journals. We focus on particularly highly rated journals and count the number of publications—not adjusted for the number of coauthors—in journals that are classified as A and A+, as well as the number of publications in journals that are classified A+.Footnote 20 Professors in our sample have 3.77 publications in journals classified at least as A and 0.67 publications in A+ journals on average.
Finally, we conduct a holistic evaluation of the professors’ publication output. We again focus on the JQL3, as it is often applied in evaluation practice, as well as in research (see, e.g., Clermont (2016)). Forschungsmonitoring transforms the classification scheme of the JQL3 (A+, A, B, C, D, not ranked) into respective points: 1.0, 0.5, 0.25, 0.1, 0.05, and 0.025. Based on these points, we calculate our variable as the sum of the weighted JQL3 points of a professor from the beginning of her publishing career until the end of 2018:
The score for each professor i is calculated from k = 1, i.e., the first publication at the beginning of the respective (publishing) career until k = K, the last publication until the year 2018. Pointsk are the JQL3 points of the journal in which publication k is published. We divide the JQL3 points by Nk, the number of coauthors of publication k. We supplement this analysis by replacing the JQL3 with two international journals ratings based on citations rather than expert judgements, the SJR (González-Pereira et al. 2010) and the SNIP (Moed 2010). More precisely, we replace the JQL3 points by points assigned to the respective journal according to these two international measures, which can range between 0.025 and 1.0.Footnote 21 On average, a business administration professor has a JQL3 Score of 2.37, which, e.g., translates into two single-authored publications in an A+ journal (e.g., Journal of Finance or Academy of Management Journal) and one A+ publication, which the professor has written with two coauthors.
In order to answer our research questions, we estimate a series of OLS regression models with the publication behavior variables being our dependent variables twice. In the first models, our independent variable of interest is a dummy variable that equals 1, if a professor is classified as an accounting professor. Consequently, we compare accounting professors with the aggregate of the remaining fields. In the second models, we include dummy variables for all fields except accounting. In this setting, we compare accounting professors with professors in each of the other fields separately.
In all regression models, we include a set of control variables that have been found to impact publication output in previous literature. First, we apply the time to tenure, i.e., the difference in years between obtaining the PhD and obtaining the first tenured professorship. Second, we include the age at which the professors obtained their first tenured professorship. Third, we control for the years since the professors in our data obtained their first professorship. The three variables account for changing publication output during the academic life cycle of individual researchers (see, e.g., Rauber and Ursprung (2008)) as well as for changing publication output over time in general (see, e.g., Ayaita et al. (2019)). The fourth control variable is the gender of the professors as previous literature documents gender differences with regard to publication output (see, e.g., Hilber et al. (2021), Jokinen and Pehkonen (2017), Madison and Fahlman (2020)). Fifth, we control for the total number of publications, as a proxy for the overall publication activity of the professors. Lastly, we control for the number of different coauthors a professor has collaborated with as prior literature shows a relationship between academic networks and research output (see, e.g., Ductor (2015), Li et al. (2013)).