Determinants of Voluntary Turnover and Layoffs in an Environment of Repeated Downsizing Following a Merger: An Event History Analysis

2000 ◽  
Vol 26 (5) ◽  
pp. 977-1003 ◽  
Author(s):  
Roderick D. Iverson ◽  
Jacqueline A. Pullman

In this study we formulate and test models of voluntary turnover and downsizing in a hospital undergoing workforce reduction following a merger. Targeted separation packages were primarily employed by the hospital in selecting departments and units as having surplus staff, as well as identifying individual employees. Determinants for the models were derived from the disparate disciplines of economics, sociology, and psychology, as well as demographic and reactions to change variables. Applying event history analysis to data from a sample of 415 hospital employees over a five year period, the results indicate that older, full-time employees, who were less absent, and had an acceptable workload, yet experienced lower co-worker support and responded negatively to the amalgamation of the hospital were more likely to be downsized. Conversely, employees who were younger, white-collar, intended to leave, and predisposed to the amalgamation were more likely to resign. In addition, the differential effects (based on discriminant function analysis) of the five categories of variables found that age, blue-collar, co-worker support, full-time, amalgamation, and work overload discriminated between the two forms of turnover. The theoretical and practical implications of the findings are discussed.

1996 ◽  
Vol 81 (6) ◽  
pp. 705-716 ◽  
Author(s):  
David N. Dickter ◽  
Mary Roznowski ◽  
David A. Harrison

1995 ◽  
Vol 49 (2) ◽  
pp. 355-357
Author(s):  
Johannes Huinink

1998 ◽  
Vol 10 (1-3) ◽  
pp. 1-9
Author(s):  
Onno Boonstra ◽  
Maarten Panhuysen

Population registers are recognised to be a very important source for demographic research, because it enables us to study the lifecourse of individuals as well as households. A very good technique for lifecourse analysis is event history analysis. Unfortunately, there are marked differences in the way the data are available in population registers and the way event history analysis expects them to be. The source-oriented approach of computing historical data calls for a ‘five-file structure’, whereas event history analysis only can handle fiat files. In this article, we suggest a series of twelve steps with which population register data can be transposed from a five-file structured database into a ‘flat file’ event history analysis dataset.


Author(s):  
Yujin Kim

In the context of South Korea, characterized by increasing population aging and a changing family structure, this study examined differences in the risk of cognitive impairment by marital status and investigated whether this association differs by gender. The data were derived from the 2006–2018 Korean Longitudinal Study of Aging. The sample comprised 7,568 respondents aged 45 years or older, who contributed 30,414 person-year observations. Event history analysis was used to predict the odds of cognitive impairment by marital status and gender. Relative to their married counterparts, never-married and divorced people were the most disadvantaged in terms of cognitive health. In addition, the association between marital status and cognitive impairment was much stronger for men than for women. Further, gender-stratified analyses showed that, compared with married men, never-married men had a higher risk of cognitive impairment, but there were no significant effects of marital status for women.


1998 ◽  
Vol 43 (S6) ◽  
pp. 33-55 ◽  
Author(s):  
Holly J. McCammon

Historians and social scientists often investigate the conditions that influence the occurrence of particular events. For instance, a researcher might be concerned with the causes of revolutionary action in some countries or the forces that unleash racial rioting in major cities. Or perhaps the researcher wishes to examine why industrial workers decide to strike or what prompts policy-makers to pass new legislation. In each of these examples, a qualitative shift occurs, from a circumstance without racial rioting in a particular city, for instance, to one with racial rioting. Event history analysis can aid researchers in uncovering the conditions that lead to such a shift.


2004 ◽  
Vol 95 (2) ◽  
pp. 589-592 ◽  
Author(s):  
Anne E. Lincoln

Research has indicated significant age differences between male and female Academy Award nominees and winners. However, this discrepancy may be associated with sex differences in actors' ages when they first begin their acting careers. The present research uses event history analysis to investigate the duration of Academy Award nominees' careers from career start (first film) to first three Academy Award nominations. Analysis suggested controlling for an actor's age at first film explains the sex-age disparity between Academy Award nominees and winners.


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