Understanding employees' unused vacation days: A social cognitive approach.

Despite the benefits of vacations for health and well-being, many employees do not use all of their paid vacation days. In this article, we seek to understand why this occurs. Using a social cognitive perspective, we propose that employees use fewer vacation days when they do not believe they can successfully detach from work while on vacation (i.e., have low detachment self-efficacy), do not expect positive outcomes (e.g., feeling relaxed, connecting with loved ones) from their vacations, and expect negative outcomes (e.g., feeling stressed, facing negative financial consequences) from their vacations. We test this explanation across four studies in which we develop and validate measures for our social cognitive constructs (Studies 1-3) and test whether these constructs predict employees' unused vacation days (Study 4). Results revealed that employees had more unused vacation days if they lacked detachment self-efficacy, did not expect to feel relaxed on vacation, and expected negative financial consequences of vacations. Overall, our results highlight the usefulness of social cognitive theory for understanding employees' unused vacation days. We discuss implications for theory, future research, and practice. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

"Worse than I anticipated" or "This isn't so bad"?: The impact of affective forecasting accuracy on self-reported task performance.

Various motivational theories emphasize that desired emotional outcomes guide behavioral choices. Although motivational theory and research has emphasized that behavior is affected by desired emotional outcomes, little research has focused on the impact of anticipated feelings about engaging in behavior. The current research seeks to partly fill that void. Specifically, we borrow from affective forecasting research in suggesting that forecasts about engaging in performance-relevant behaviors can be more or less accurate. Furthermore, we suggest that the degree of accuracy has implications for self-reported task performance. To examine these ideas, we conducted two studies in which individuals made affective predictions about engaging in tasks and then later reported how they actually felt during task engagement. We also assessed their self-reported task performance. In Study 1, 214 workers provided affective forecasts about upcoming work tasks, and in Study 2, 185 students made forecasts about studying for an exam. Results based on polynomial regression were largely consistent across the studies. The accuracy of the forecasts did not conform to the pattern of affective forecasting accuracy typically found outside the performance domain. Furthermore, anticipated and experienced affect jointly predicted self-reported task performance in a consistent manner. Collectively, these findings suggest that taking into account anticipated affect, and its relationship with later experienced affect, provides a more comprehensive account of affect's role in task performance.