Thesis (Ph. D.)--University of California, San Diego, 1999. / Vita. Includes bibliographical references.

The purposes of this study were twofold. The first was to construct a modified model of the voluntary turnover process that clarifies the antecedents of turnover intentions and turnover behavior. The second was to investigate empirically the proposed model's validity by assessing the influences of nine variables of job satisfaction, organizational commitment, job search, intention to stay in the organization, and six demographic variables as potential predictors of employee voluntary turnover.

It is estimated that by 2018, workers age 55 or older will compose nearly a quarter of the labor force (Tossi, 2009). The aging workforce is dramatically affecting the nursing workforce. Indeed, the nursing workforce is expected to face staffing shortages of epidemic proportions because of the impending retirement of nurses who are Baby Boomers (Buerhaus, et al., 2006). Moreover, the nursing shortage is exacerbated by younger nurses' greater willingness to turn over (Aiken et al., 2001). Consequently, investigating how the workplace context affects retention of nurses is important. The present study sought to address the nursing shortage concern through examining how the workplace climate associated with age-related worker treatment and individual characteristics affect nurse retention. In this study, I developed and validated new ageism climate measures, which include younger worker, older worker, and general ageism climates. I examined how ageism climates affect people's job withdrawal intentions, organizational commitment, and work engagement. Additionally, I investigated whether Core Self-Evaluation (CSE; Judge, Locke, Durham, 1998) moderates the ageism climates relationships with the outcome variables. During the scale development and validation process, I found that assessments of younger and older worker ageism climates depend on the age of the respondent, whereas general ageism climate did not have this dependency. Because younger and older ageism climates displayed measurement non-equivalence across age groups, I tested each of my hypotheses using three sample variations (under 40, 40 and older, and combined sample). In the under 40 sample, CSE buffered the negative effects of negative older and younger worker ageism climates, and CSE enhanced the positive effects of a positive general age climate on turnover intentions and organizational commitment. In the 40 and older sample, I found that less ageist younger and older worker climates were associated with decreased turnover intentions and increased affective commitment. Finally, in the combined sample, I observed that a less ageist general ageism climate was associated with lower turnover intentions and greater affective commitment. The results contribute to our understanding of how perceptions of age-related treatment affect important workplace outcomes. The findings also support ageism climates as separate measures. However, additional measure development and validation is needed because this was the initial study to investigate ageism climate. This study has implications for the relational demography paradigm (Tsui & O'Reilly, 1989) in that people's age group identification may affect their ageism climate perceptions. This potentially explains the differential relationships among the ageism climates on the outcomes between the under 40 and 40 and older age groups. From a practical perspective, improving ageism climates in the workplace could positively affect nurse retention, which could alleviate some of the nursing shortage concerns.

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