PREDICTORS OF FACULTY EARLY RETIREMENT DECISION-MAKING IN ARIZONA.
AuthorMONAHAN, DEBORAH JUNE.
KeywordsRetirement age -- Arizona -- Tucson.
College teachers -- Arizona -- Tucson -- Retirement.
University of Arizona. Faculty.
Committee ChairLeslie, Larry
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractChanges in retirement policy in the United States have affected management policies and practices in higher education. As a result of the 1978 amendments to the Age Discrimination in Employment Act, mandatory retirement prior to age seventy is prohibited. The significance of this policy change has stimulated the development of innovative personnel and retirement policies in an effort to increase the number of "elective" early retirements. The purpose of this study was to assess whether particular departmental and individual characteristics had predictive power with respect to faculty decisions to retire early. Data sources were existing university administrative data files, combined with interviews from a random sample of seventy-two early retirees and eligible nonretirees. Results of the study are summarized below: (1) In general, demographic characteristics studied (age, sex, marital and health status, etc.) were not strong predictors of early retirement decisions among the respondents. (2) Faculty salary was not a strong predictor of early retirement behavior. (3) Self reported faculty productivity was a strong predictor of early retirement decision-making. (4) Job satisfaction variables were moderate predictors of early retirement decisions. (5) Departmental characteristics (governance, fit in the department, recognition and rewards, etc.) were strong predictors of faculty early retirement decisions. In the present study, multiple discriminant analysis identified thirteen variables that strongly discriminated between the early retiree and non-retiree groups. Analysis of the prediction function assisted in assessing the relative importance of these variables in distinguishing between the two groups, and may serve as a useful management tool in understanding motives for early retirement as well as identifying faculty who may be most (or least) likely to choose an early retirement option. The present study, by examining the joint influences of a wide variety of variables on the propensity to elect early retirement, helped reveal the complexity of the relationships, while seeking to parsimoniously characterize the key factors influencing these decisions.
Degree ProgramHigher Education