In the following, we first consider cognitive biases as theoretical foundation. Second, we present previous research on professorial appointments decisions. Third, with regard to previous studies, we discuss differences in appointment preferences through the lens of cognitive biases.
2.1 Cognitive bias theory
Both behavioral and psychological research show that cognitive biases in decision-making especially occur in situations of high uncertainty and complexity (Pitz and Sachs
1984). “Cognitive biases are an ever-present ingredient of strategic decision-making” (Das and Teng
1999, p. 757) and, thus, they are also very likely to occur in professorial appointment decisions. In the context of professorial appointment decisions, cognitive biases arise from, among other things, the choice of useful shortcuts that appear promising for successful decision-making (i.e., heuristics). Heuristics, however, result from information-processing or evolutionary mechanisms, meaning that the criteria for strategic decision-making function adequately in principle, but may exhibit systematic errors (Haselton et al.
2005). Regarding professorial appointment decisions, previous research reveals that, despite changing environmental demands (e.g., the need to adopt innovative teaching concepts to counteract declining student numbers), the appointment criteria seem more or less unchanging over a long period of time. Heuristics might emerge due to limited time and information processing abilities and due to the fact that especially employees in positions of power invoke established rules to allocate attentional resources and cognitive effort otherwise (Haselton et al.
2005; Keltner et al.
2003). This explanation can be transferred to professorial appointment decisions, given that professors usually allocate their cognitive resources across a multifaceted range of tasks and, accordingly, may prioritize established appointment criteria, such as publication performance, in their decision-making. In this context, Morewedge and Kahneman (
2010) describe dual-system models that explain how automated decisions emerge under errors of judgement. Here, three features are central to the decision-making process: associative coherence, attribute substitution, and processing fluency. These features may also be transferred to the context of professorial appointment decisions, as the fulfillment of specific appointment criteria elicit self-reinforcing responses in associative memory of the appointment committee (i.e., associative coherence); the evaluation of the appointment criteria is accompanied by an unconscious assessment of other dimensions (e.g., a high number of publications suggests high professional aptitude) (i.e., attribute substitution); and the cognitive effort to engage a professor is eased by the adoption of the appointment criteria (i.e., processing speed). Accordingly, cognitive biases, especially heuristics, and concretely dual-system models, serve as an appropriate theoretical basis for explaining the emergence of the underlying process on how appointment committee members weigh up a large number of different criteria when they evaluate the performance of candidates.
2.2 Influences on professorial appointment decisions
Researchers have used various methods to answer the question of what influences appointment decisions. First, several studies on professorial appointments analyzed documents, in which universities describe the criteria they will use to select candidates, for example, job advertisements (e.g., Finch et al.
2016; Gould et al.
2011; Klawitter
2017; Meizlish and Kaplan
2008; Pikciunas et al.
2016; Winter
1997) and policy documents (e.g., Crothall et al.
1997; Parker
2008; Subbaye
2018). The procedures and resulting contributions are manifold. For instance, Finch et al. (
2016) analyzed job advertisements for tenure-track positions and found that business schools in the U.S. attach equal importance to research qualifications (i.e., at least one publication) and teaching qualifications (i.e., teaching experience). However, a major drawback of this approach is that the criteria written down in job advertisements, policy documents and official university documents may not always be the same criteria as those that appointment committees actually use (Finch et al.
2016; Subbaye
2018; van den Brink et al.
2010) and do not give insight into the individual preferences of the committee members who were involved in the decision-making process. Through the lens of cognitive biases, reports of appointment committees are potentially prone to several self-report biases, including introspective bias (e.g., Nisbett and Wilson
1977; Uhlmann et al.
2012) and social desirability (e.g., Arnold and Feldman
1981).
Second, analyzing career trajectories of scholars is one of the most common approaches to determine the criteria underlying the decisions of appointment committees. Based on datasets from scholars (e.g., performance, individual characteristics, appointment decision), researchers identify which variables are the best predictors for being successful in becoming a professor (e.g., Cruz-Castro and Sanz-Menendez
2010; Lutter and Schröder
2016; Pezzoni et al.
2012; Schulze et al.
2008; van Dijk et al.
2014; Youtie et al.
2013). Considering the results, career trajectory studies showed that different aspects of publication performance are related to scholars’ success in appointment procedures. For example, Sanz-Menéndez et al. (
2013) found that the more researchers at Spanish universities publish before earning their doctoral degree, the sooner they get promoted to the level of professor. However, in collecting data on scholars’ characteristics, authors focus on information that is publicly available, thus neglecting many potentially relevant appointment criteria. Considering cognitive biases, career trajectory studies suffer from the so-called survivor bias (Jungbauer-Gans and Gross
2013; Lutter and Schröder
2016), which is problematic, as samples do not include the unsuccessful scholars who competed against the successful ones in appointment procedures.
Third, self-reports in the form of surveys and interviews are another common approach in the literature on appointment preferences. Some confirmed that appointment committees consider publication performance an important criterion, but they show that other criteria play a role as well, for example, acquiring grants, teaching performance, and the candidate’s fit to the hiring department (e.g., Macfarlane
2011, pp. 59–60; Sheehan et al.
1998). Studies highlight that appointment preferences are not homogeneous but that there are different appointment preferences depending on various factors. For instance, Landrum and Clump (
2004) showed that candidates’ teaching performance is more important to private than to public institutions, whereas public institutions emphasize the number of publications and the acquisition of research grants. However, survey participants are typically asked to consider each appointment criterion independently and to state its importance on a ranking or rating scale. This approach has been criticized because participants tend to rate all items as similarly important (e.g., Orme
2014). Further, scholars’ answers may be biased because they are influenced by the public opinion as to which criteria should be important (i.e., social desirability bias; e.g., Arnold and Feldman
1981).
Up until now, a few studies on appointment preferences employed experimental designs (e.g., Kasten
1984; Steinpreis et al.
1999; Williams and Ceci
2015). During these experiments, narrative summaries or full CVs served as the basis for assessing appointment criteria. The shortcoming of such statistical approaches lies in not adapting to the participants’ responses, thus neglecting the underlying process on how scholars consider and weigh up many different appointment criteria when they evaluate candidates for a professorship. So far, Fiedler and Welpe (
2008) are the only ones who applied conjoint analysis to research on professorial appointments. In contrast to narrative summaries, conjoint analysis uses hypothetical candidate profiles that consist of succinct descriptions of candidate characteristics, which reduces the complexity for participants. Thus, conjoint analysis enables the inclusion of more appointment criteria and the systematic variation of all criteria in a within-subject design. More specifically, the authors conducted an adaptive conjoint analysis, which allowed them to include many different appointment criteria, dynamically adapt those criteria to the respondents’ preferences and, in consequence, to study how scholars compare the performance of candidates. Fiedler and Welpe (
2008) observe that, on average, prestigious journal publications are most important to management professors, followed by social competency, and person–subject fit. However, this type of conjoint analysis has also several drawbacks, because it does not mimic the decision-making process of appointment procedures. In contrast, adaptive choice-based conjoint (ACBC) analysis allows creating a more realistic and engaging simulation of a complex decision-making process with a variety of appointment criteria. Moreover, the procedure of ACBC analysis (e.g., using non-compensatory heuristics) facilitates focusing on the most important stimuli and providing precise estimations. Overall, the ACBC design allows for detailed insights about the ideal set of appointment criteria. Accordingly, the ACBC analysis validates and synthesizes previous research findings and extends them by providing a holistic, implicit process perspective on appointment preferences. More precisely, the differences between our study and that of Fielder and Welpe (
2008) are threefold: first, in our study, we expanded and modified the appointment criteria based on recent literature and new preliminary studies. Second, in the Fiedler and Welpe (
2008) study, participants selected their appointment criteria in advance, and only those appointment criteria were considered in the later stages of the survey, probably causing bias. Third, participants in the Fiedler and Welpe (
2008) study rated their average candidates on percentages. In relation to actual personnel selection procedures, our design appears more realistic. In the following, we briefly review past findings on factors that contribute to differences in scholars’ appointment preferences, to consider which further aspects should be addressed as part of the ACBC analysis.
2.3 Differences in appointment preferences
Most previous studies that examined differences with regard to appointment criteria focused on differences among countries and among scientific fields. However, they either compared scientific fields in one specific country (e.g., Sanz-Menéndez et al.
2013; Williams and Ceci
2015) or compared countries with regard to one specific scientific field (e.g., Fiedler and Welpe
2008; Pezzoni et al.
2012). Past research also suggests that there are differences in appointment preferences between higher education institutions, which are related to specific organizational characteristics (e.g., Fiedler and Welpe
2008; Finch et al.
2016; Iyer and Clark
1998). This finding indicates that the current needs of departments (e.g., to improve their reputation) may influence how much importance appointment committees attach to specific criteria. Similarly, interviews with university presidents and deans indicate that the strategic objectives of the higher education institution and of the department are most important for defining the profile of an advertised professorship (Kleimann and Klawitter
2016). Although it can be assumed that individual appointment committee members differ in their opinion as to what aspects of scholarly performance are most important, little is known about whether there are systematic differences in appointment preferences depending on individual characteristics. Fiedler and Welpe (
2008) provide initial evidence that homophily effects are important in explaining individual differences in appointment preferences between scholars. For example, professors had a stronger preference for candidates with international experience when they had international experience themselves. The homophily effect is accompanied by cognitive biases and may be explained with the dual-system perspective according to Morewedge and Kahneman (
2010). In the example given, the presence of international experience may lead to other preferable qualities (e.g., superior language proficiency) being attributed to the candidate at the same time or the coherent and easy evaluation of international experience may result in increased process fluidity. In this context, a more systematic understanding of cognitive biases (e.g., homophily effects, heuristics) on appointment decisions is still lacking. In particular, it is unclear how scholars’ own performance in other areas, such as research, is related to differences in appointment preferences. Furthermore, it is unknown whether there are differences in appointment preferences depending on academic rank. Considering that appointment committees often comprise not only professors, it is crucial to also examine the appointment preferences of scholars who hold positions below the level of professor (e.g., post-doctoral fellows).
Past research reveals a multitude of factors that exert an influence on scholars’ appointment preferences, including country, scientific field, organizational characteristics, and individual characteristics. However, previous studies included only some of these factors while excluding others. Considering that all of the factors described above exert an influence on appointment preferences, it is crucial to identify distinct patterns of implicit appointment preferences (i.e., groups of scholars with similar preferences) and predict scholars´ patterns of implicit appointment preferences based on country, scientific field, as well as individual and organizational characteristics.