This study proposes that self-reported work stress among U.S. managers is differentially related (positively and negatively) to work outcomes depending on the stressors that are being evaluated. Specific hypotheses were derived from this general proposition and tested using a sample of 1,886 U.S. managers and longitudinal data. Regression results indicate that challenge-related self-reported stress is positively related to job satisfaction and negatively related to job search. In contrast, hindrance-related self-reported stress is negatively related to job satisfaction and positively related to job search and turnover. Future research directions are discussed.

The present study examined the degree to which demographic, human capital,motivational, organizational, and industry/region variables predicted executive career success. Career success was assumed to comprise objective (pay, ascendancy) and subjective (job satisfaction, career satisfaction) elements. Results obtained from a sample of 1,388 U.S.executives suggested that demographic, human capital, motivational, and organizational variables explained significant variance in objective career success and in career satisfaction. Particularly interesting were findings that educational level, quality, prestige, and degree type all predicted financial success. In contrast, only the motivational and organizational variables explained significant amounts of variance in job satisfaction. These findings suggest that the variables that lead to objective career success often are quite different from those that lead to subjectively defined success. This research was funded by CAHRSThis paper has not undergone formal review or approval of the faculty of the ILR School. It is intended to make results of research, conferences, and projects available to others interested in human resource management in preliminary form to encourage discussion and suggestions. Running Head: EXECUTIVE CAREER SUCCESS Executive Career Success WP 94-08Page 2 AbstractThe present study examined the degree to which demographic, human capital, motivational, organizational, and industry/region variables predicted executive career success.

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The relationship between job performance and voluntary employee turnover was investigated for 5,143 exempt employees in a single firm. As hypothesized, support was found for E. F. Jackofsky's (1984) curvilinear hypothesis, as turnover was higher for low and high performers than it was for average performers. Two potential moderators of the curvilinearity were examined in an attempt to explain conflicting results in the performance-turnover literature. As predicted, low salary growth and high promotions each produced a more pronounced curvilinear performance-turnover relationship. Most notably, salary growth effects on turnover were greatest for high performers, with high salary growth predicting rather low turnover for these employees, whereas low salary growth predicted extremely high turnover. Additionally, once salary growth was controlled, promotions positively predicted turnover, with poor performer turnover most strongly affected.The cost of voluntary employee turnover depends on many factors, including the relative supply and cost of replacements in either the internal or external labor market, the amount of training invested in the employee, and the performance level of the employee (Boudreau & Berger, 1985: Cascio, 1994Dalton, Todor, & Krackhardt, 1982: Hollenbeck & Williams, 1986. Where replacement costs are low and average performance of replacements is expected to be high, organizations can benefit from turnover of poor performers. In contrast, turnover of high performers is more likely to be dysfunctional for the organization (e.g., Hollenbeck & Williams, 1986;Park, Ofori-Dankworth, & Bishop, 1994;Schwab, 1991). Thus, it is important to identify the conditions under which employees of different performance levels are most likely to voluntarily leave the organization. This is especially true at the organization's higher job levels, where, for several reasons, high performer turnover is more costly than at lower job levels. For instance, because the standard deviation of performance tends to be

Recent research suggests that the turnover process is not fully captured by the traditional sequential model relating job dissatisfaction to subsequent turnover. The present study contributes to this research by modeling within-individual job satisfaction as a function of job change patterns to determine if individual work attitudes change systematically with the temporal turnover process. Specifically, the authors hypothesized that low satisfaction would precede a voluntary job change, with an increase in job satisfaction immediately following a job change (the honeymoon effect), followed by a decline in job satisfaction (the hangover effect). Though this pattern is suggested in the literature, no prior research has integrated and tested this complete temporal model within individuals. Findings based on a sample of managers supported the proposed honeymoon-hangover effect.

O perations management (OM) and human resources management (HRM) historically have been very separate fields. In practice, operations managers and human resource managers interact primarily on administrative issues regarding payroll and other matters. In academia, the two subjects are studied by separate communities of scholars publishing in disjoint sets of journals, drawing on mostly separate disciplinary foundations. Yet, operations and human resources are intimately related at a fundamental level. Operations are the context that often explains or moderates the effects of human resource activities such as pay, training, communications, and staffing. Human responses to OM systems often explain variations or anomalies that would otherwise be treated as randomness or error variance in traditional operations research models. In this paper, we probe the interface between operations and human resources by examining how human considerations affect classical OM results and how operational considerations affect classical HRM results. We then propose a unifying framework for identifying new research opportunities at the intersection of the two fields.