This on-road field investigation employed, for the first time, a completely automated, trigger-based data collection system capable of evaluating driver performance in an extended duration real-world commercial motor vehicle environment. The complexities associated with the development of the system, both technological and logistical and the necessary modifications to the plan of research are presented herein This study, performed in conjunction with an on-going three year contract with the Federal Highway Administration, examined the use of self-rating of alertness and temporal separation (minimum time-to-collision, minimum headway, and mean headway) as indicators of driver fatigue. Without exception, the regression analyses for both the self-rating of alertness and temporal separation yielded models low in predictive ability; neither metric was found to be a valid indicator of driver fatigue. Various reasons for the failure of self-rating of fatigue as a valid measure are discussed. Dispersion in the data, likely due to extraneous (non-fatigue related) factors (e.g., other drivers) are credited with reducing the sensitivity of the temporal separation indicators. Overall fatigue levels for all temporal separation incidents (those with a time-to-collision equal to or less than four seconds) were found to be significantly higher than for those randomly triggered incidents. On this basis, it is surmised that temporal separation may be a sensitive indicator for time-to-collision values greater than the 4-second criterion employed in this study. Two unexpected relationships in the data are also discussed. A "wall" effect was found to exist for minimum time-to-collision values at 1.9 seconds. That is, none of the participants who participated in this research effort exhibited following behaviors with less than a 1.9-second time-to-collision criterion. In addition, based upon the data collected for this research, anecdotal evidence suggests that commercial motor vehicle operators do not appear to follow the standard progression of events associated with the onset of fatigue. / Ph. D.

The field of entrepreneurship is rapidly advancing and matures as a discipline that receives substantial amount of attention. One popular area of research in the discipline of entrepreneurship is to investigate one’s intent to start a business, which is entrepreneurial intention. This is an important construct that warrants ongoing research because entrepreneurial intention is not only a great predictor of entrepreneurial behavior but also an important step in the process of becoming an entrepreneur. The present study, based on a sample of 321 subjects along with 264 observers, makes five contributions to the entrepreneurship literature. First, I examined the psychometric property of entrepreneurial take-over intention and found that it is a construct different from entrepreneurial start-up intention. Second, the results demonstrated that risk propensity and proactive personality are positive predictors of entrepreneurial start-up and take-over intentions, whereas cognitive ability is a negative predictor of entrepreneurial start-up and take-over intentions. Rebelliousness is a positive predictor of entrepreneurial take-over intention and also has an inverted U-shaped relationship with entrepreneurial take-over intention. Third, entrepreneurial self-efficacy mediates the relationship between three individual traits (i.e., emotional intelligence, risk propensity, and proactive personality) and entrepreneurial start-up and take-over intentions. Need for cognition mediates the relationship between two individual traits (i.e., cognitive ability and proactive personality) and entrepreneurial start-up intention. Fourth, 2D:4D ratio (a proxy measure for prenatal testosterone exposure level) negatively predicts risk propensity. There also exist two two-step mediations from 2D:4D ratio to both entrepreneurial start-up and take-over intentions through risk propensity and entrepreneurial self-efficacy. Fifth, the results suggest that observer ratings of individual traits only contribute modest incremental validity above and beyond self-reported ratings of them in predicting entrepreneurial start-up and take-over intentions. I discuss implications, limitations, and future directions informed by the present study.