Abstract
Using questionnaire data from the 2010 Survey of Academic Chairs, the study focuses on decision autonomy, a component of the power wielded by science, technology, engineering and mathematics (STEM) department chairs in U.S. research extensive universities. A “power index” is developed to measure chairs’ decision autonomy, specifically their control of resources employed in negotiations with faculty job candidates. The study asks: What determines the degree of decision autonomy power possessed by department heads; and, what are the strategic implications of department heads’ degree of this particular aspect of power? Results of an ordered logistic regression model show that having more power is associated with being hired from outside the current university, being male, and with department size. The power index is employed to predict departmental strategic priorities. Results show that the power index is positively associated with a strategic priority for research. The results show a negative relationship between degree of chair decision autonomy and a priority to increase faculty lines. A student-focused strategy is not predicted by the power index but is related to the size, with larger departments placing less emphasis on numbers or quality of students.
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Notes
For convenience, much of the discussion below uses the term “power” rather than “decision-making autonomy dimension of power,” but it is important to keep in mind that we are focusing a single aspect of power.
All analyses are conducted using disciplinary—not departmental—indicators; sensitivity analyses indicated that collapsing departments into disciplines in this manner does not affect substantive conclusions. The departments included in the physical science discipline include physics, mathematics, chemistry, statistics, computer science, and earth and atmospheric science. Departments included in the social science discipline are sociology and economics; each is a quantitatively oriented social science discipline and included in the NSF definition of science. Life science disciplines are departments of biology, agriculture and ecology. Public health disciplines include departments of biostatistics, epidemiology, environmental health science, behavioral science, and health policy and management. The engineering discipline encompasses any engineering department present at a focal institution.
The authors thank the anonymous reviewer that suggested testing for the parallel regression assumption.
In a procedure not reported in this paper, we developed a power index based simply on the summation of these dummies. The results were very close to the ones reported in this paper. However, we use the more complicated measure because it is closer to the concept of power employed. Tables for the simple additive measure are available from the authors.
The approach is also supported by a simple heuristic analysis we performed. We took the highest loading (in terms of factor loadings on the respective factor dimension) variable for each of the strategy dimensions and regressed the power index and control variables in a simply OLS model. The results were quite close to the OLS regression using the factor scores as dependent variables. In every case, if the dimensional variable was significant the single variable representation of that dimension was significant and with the same valence. Results are available from the authors.
Since 69 % of the nonwhite chairs are Asian, it would not be misleading to interpret the variable as a proxy for having an Asian chair.
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The authors gratefully acknowledge the support of the National Science Foundation under Grant No. 0701836 (Monica Gaughan, Principal Investigator).
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Bozeman, B., Fay, D. & Gaughan, M. Power to Do…What? Department Heads’ Decision Autonomy and Strategic Priorities. Res High Educ 54, 303–328 (2013). https://doi.org/10.1007/s11162-012-9270-7
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DOI: https://doi.org/10.1007/s11162-012-9270-7