TY - JOUR
T1 - Academic success is in the eye of the beholder
T2 - understanding scholars’ implicit appointment preferences through adaptive choice-based conjoint analysis
AU - Graf, Laura
AU - Rimbeck, Marlen
AU - Stumpf-Wollersheim, Jutta
AU - Welpe, Isabell M.
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023
Y1 - 2023
N2 - Because scholarly performance is multidimensional, many different criteria may influence appointment decisions. Previous studies on appointment preferences do not reveal the underlying process on how appointment committee members consider and weigh up different criteria when they evaluate candidates. To identify scholars’ implicit appointment preferences, we used adaptive choice-based conjoint analysis (ACBC), which is able to capture the non-compensatory process of complex decisions like personnel selection. Junior and senior scholars (N = 681) from different countries and types of higher education institutions took part in a hypothetical appointment procedure. A two-step segmentation analysis based on unsupervised and supervised learning revealed three distinct patterns of appointment preferences. More specifically, scholars differ in the appointment criteria they prefer to use, that is, they make different trade-offs when they evaluate candidates who fulfill some but not all of their expectations. The most important variable for predicting scholars’ preferences is the country in which he or she is currently living. Other important predictors of appointment preferences were, for example, scholars’ self-reported research performance and whether they work at a doctorate-granting or not-doctorate-granting higher education institution. A comparison of scholars’ implicit and explicit preferences yielded considerable discrepancies. Through the lens of cognitive bias theory, we contribute to the extension of the literature on professorial appointments by an implicit process perspective and provide insights for scholars and higher education institutions.
AB - Because scholarly performance is multidimensional, many different criteria may influence appointment decisions. Previous studies on appointment preferences do not reveal the underlying process on how appointment committee members consider and weigh up different criteria when they evaluate candidates. To identify scholars’ implicit appointment preferences, we used adaptive choice-based conjoint analysis (ACBC), which is able to capture the non-compensatory process of complex decisions like personnel selection. Junior and senior scholars (N = 681) from different countries and types of higher education institutions took part in a hypothetical appointment procedure. A two-step segmentation analysis based on unsupervised and supervised learning revealed three distinct patterns of appointment preferences. More specifically, scholars differ in the appointment criteria they prefer to use, that is, they make different trade-offs when they evaluate candidates who fulfill some but not all of their expectations. The most important variable for predicting scholars’ preferences is the country in which he or she is currently living. Other important predictors of appointment preferences were, for example, scholars’ self-reported research performance and whether they work at a doctorate-granting or not-doctorate-granting higher education institution. A comparison of scholars’ implicit and explicit preferences yielded considerable discrepancies. Through the lens of cognitive bias theory, we contribute to the extension of the literature on professorial appointments by an implicit process perspective and provide insights for scholars and higher education institutions.
KW - Adaptive choice-based conjoint analysis
KW - Appointment preferences
KW - Decision-making
KW - Higher education
KW - Implicit preferences
KW - Personnel selection
UR - http://www.scopus.com/inward/record.url?scp=85180225905&partnerID=8YFLogxK
U2 - 10.1007/s11573-023-01184-2
DO - 10.1007/s11573-023-01184-2
M3 - Article
AN - SCOPUS:85180225905
SN - 0044-2372
JO - Journal of Business Economics
JF - Journal of Business Economics
ER -