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Marital Status, Number of Dependents...

Talis, Jonathan J.

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Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army./
Author:	Talis, Jonathan J.
Description:	123 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-06(E), Section: A.
Contained By:	Dissertation Abstracts International77-06A(E).
Subject:	Management. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3743592
ISBN:	9781339363325

Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army.
Talis, Jonathan J.

Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army. - 123 p.

Source: Dissertation Abstracts International, Volume: 77-06(E), Section: A.

Thesis (Ph.D.)--Northcentral University, 2015.

Many junior officers are leaving the Army to pursue other opportunities. Upon completing their initial active duty obligation, 40 to 50% of Army captains choose to leave active duty. The problem addressed in this study was the limited understanding of the causes for the high voluntary turnover rates of junior officers in the U.S. Army. Without an understanding of why junior officers depart at such high rates, Army representatives cannot craft successful retention policies to curb turnover. Factors that have been proposed to be related to turnover rates include family separation, months of deployment and months away from duty station. However, previous research was conducted in 1999 and did not include data from recent deployments to Iraq and Afghanistan. Therefore, there is a need for more current research. The purpose of this quantitative correlational study that used archival data was to examine the predictive value of marital status, number of dependents, number of months deployed and number of months away from duty station on junior officers' turnover intention ratings. The participants in this study consisted of 485 junior officers who were in the process of deciding whether or not to remain on active duty beyond their initial service obligation. A Spearman correlation, Mann-Whitney U test, and ordinal logistic regression were used to determine whether there was a significant relationship between the predictors and turnover intention. Of the predictors, only number of dependents (p = .001) and number of months deployed (p = .004) had statistically significant relationships with turnover intentions. Number of dependents had a negative relationship with turnover (r = -.14), whereas number of months deployed had a positive relationship with turnover intentions ( r = 0.13). Marital status (z = -0.08, p = .939) and number of months away from duty station (p = .208) were not statistically significant. These findings contribute to the military turnover and COR literature. Future research should examine the deployment variable in greater detail to determine the exact number of months deployed required to affect turnover intentions, as well as the greatest resources lost or threatened to be lost during deployment.

ISBN: 9781339363325Subjects--Topical Terms:

516664
Management.

Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army.
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245 1 0 $a Marital Status, Number of Dependents, Months Deployed and Months Away as Predictors of Turnover Intentions of Junior Officers in the U.S. Army.
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500 $a Source: Dissertation Abstracts International, Volume: 77-06(E), Section: A.
500 $a Adviser: Kelley Chappell.
502 $a Thesis (Ph.D.)--Northcentral University, 2015.
520 $a Many junior officers are leaving the Army to pursue other opportunities. Upon completing their initial active duty obligation, 40 to 50% of Army captains choose to leave active duty. The problem addressed in this study was the limited understanding of the causes for the high voluntary turnover rates of junior officers in the U.S. Army. Without an understanding of why junior officers depart at such high rates, Army representatives cannot craft successful retention policies to curb turnover. Factors that have been proposed to be related to turnover rates include family separation, months of deployment and months away from duty station. However, previous research was conducted in 1999 and did not include data from recent deployments to Iraq and Afghanistan. Therefore, there is a need for more current research. The purpose of this quantitative correlational study that used archival data was to examine the predictive value of marital status, number of dependents, number of months deployed and number of months away from duty station on junior officers' turnover intention ratings. The participants in this study consisted of 485 junior officers who were in the process of deciding whether or not to remain on active duty beyond their initial service obligation. A Spearman correlation, Mann-Whitney U test, and ordinal logistic regression were used to determine whether there was a significant relationship between the predictors and turnover intention. Of the predictors, only number of dependents (p = .001) and number of months deployed (p = .004) had statistically significant relationships with turnover intentions. Number of dependents had a negative relationship with turnover (r = -.14), whereas number of months deployed had a positive relationship with turnover intentions ( r = 0.13). Marital status (z = -0.08, p = .939) and number of months away from duty station (p = .208) were not statistically significant. These findings contribute to the military turnover and COR literature. Future research should examine the deployment variable in greater detail to determine the exact number of months deployed required to affect turnover intentions, as well as the greatest resources lost or threatened to be lost during deployment.
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