In May 2015, the Washington Post published an article titled: “Uncle Sam Had Better Start Treating His Employees Right.” The article’s title captures the essence of the status of human capital in the federal government. Currently, the federal bureaucracy is faced with the potential threat of losing talented workforce due to budget constraints (Wynen & Op de Beeck, 2014), work environments ( Choi, 2009; S.H. Kim, 2005; S.Y. Lee & Whitford, 2008; Lee & Jimenez, 2011), and human resource management practices ( S.H. Kim, 2005; Moyihan & Landuyt, 2008; Shaw, Delery, Jenkins, & Gupta, 1998; Lee & Jimenez, 2011). The potential exit of human capital poses a severe threat to recruiting and retaining the best and the brightest workers. Also, to make the federal government labor force situation worse, many federal workers are now eligible for retirement. Ertas (2015) refers to a report published in 2010 that states that the Office of Personnel Management (OPM) reported by 2015 that 48% of the federal workforce will be eligible for retirement (Partnership for Public Service & Booz Allen Hamilton, 2010, p. 5). With the aforementioned factors, federal agencies cannot afford to have employees exit. The departure of workers adversely impacts expertise in the organization and productivity, and costs agencies a substantial amount of money (Grissom, Nicolson-Crotty, & Keiser, 2012; Kellough & Osuna, 1995; Lambert & Hogan, 2009; Monnihan & Landuyt, 2008; Wynen & Op de Beeck, 2014). This study utilizes the personal viewpoint of current employees from the large federal agencies to develop a model that will assist federal agencies to identify factors that will encourage employees’ intent to stay with their organization and have long, lasting careers in the federal service. This study employs the Federal Employee Viewpoint Survey.
Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-5641 |
Date | 12 August 2016 |
Creators | Settles, Allison Mckenzie |
Publisher | Scholars Junction |
Source Sets | Mississippi State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
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