Research for Personnel

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May 1, 1983
This paper uses a rating-specific model that incorporates both cost and productivity data to find the most efficient balance of accession and retention.
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May 1, 1983
Addresses the concerns of personnel managers about the accuracy of the ASVAB score scale. The report attempts to determine the causes of the error in the scale and to verify that the corrections to the scale did in fact restore the traditional meaning of the ASVAB scores.
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February 1, 1983
This paper addresses concerns about manning the active force with volunteers. These concerns include supply, quality and cost of manpower.
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February 1, 1983
This paper presents a research design to measure the hidden costs imposed on the Navy by policies that require Navy families to relocate about every two years. Supersedes 05-821784.10
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January 1, 1983
This paper examines the labor market behavior of the combined military services by developing linkage between military and civilian wages.
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January 1, 1983
This paper examines the effects of veteran status on civilian earnings and personnel hiring rates.
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November 1, 1982
This paper estimates the differential impact of lump-sum and installment bonuses and derives the implied discount rate from these estimates.
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October 1, 1982
Determination of trade-offs between personnel with different characteristics is vital to attaining a high ratio of personnel productivity to costs. Personnel trade-offs are evaluated using unit performance, individual performance, and survey data as measures of productivity. For each approach, previous work is briefly reviewed, then models for improving productivity measurement are presented. Broad-based proposals are made for advancing personnel productivity measurement in the Navy.
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October 1, 1982
This paper determines whether manpower requirements can be developed that will lead to increases in the Navy's level of readiness.
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April 1, 1982
Survival curves for NPS female recruits were estimated through eight years of service using the FY 1979 cross-sectional data base. Separate analyses were performed for Class A school attendees and non-A school attendees, holding constant the effects of age, educational level, and mental group. Mean survival times (the areas under the survival curves) were then calculated for each recruit profile. We found that no further screening based on expected months of service is feasible. This is largely due to the fact that the NPS female population is already highly screened. As expected, educational level has the greatest impact on survival. Women with a high school diploma survive an average of 3-4 months longer than those with a GED certificate. The effect of mental group on survival is quite different for A school and non-A school attendees. Survival across mental groups is essentially constant for A school attendees but displays a downward trend as mental group declines for non-A school attendees. For A school attendees, there appears to be a generally increasing trend in survival as age increases. Purely from the standpoint of survival, ages 22 and older are the optimal recruiting ages for these recruits. On the other hand, non-A school attendees exhibit the opposite pattern of survival with respect to age, but to a lesser degree. These recruits have an optimal recruiting age of 17-22.
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