The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.

An order batching and processing heuristic to address aisle congestion in a manual order picking warehouse with order due dates

A heuristic for batching orders in a manual order-picking warehouse has been developed. It prioritizes orders based on due time to prevent mixing of orders of different priority levels. The order density of aisles criterion is used to form batches. It also determines the number of pickers required and assigns batches to pickers such that there is a uniform workload per unit of time. The effectiveness of the heuristic was studied by observing computational time and aisle congestion for various numbers of total orders and number of orders that form a batch. An initial heuristic performed well for small number of orders, but for larger number of orders, a partitioning technique is computationally more efficient, needing only minutes to solve for thousands of orders, while preserving 90% of the batch quality obtained with the original heuristic. Comparative studies between the heuristic and other published heuristics are needed. ^

The impact of bandwidth in structured interviewing and criterion stability in predicting and assessing manager performance across transition and maintenance stages

The current study examined the role of three important components in the use of structured employment interviewing in performance prediction: construct bandwidth, observed communication skill, and the stability/dynamicity of performance criteria over time. A matched sample of 242 hospitality managers was derived from a field data set provided by a large hospitality management organization. Interview data and two years of performance appraisal data were provided. Bandwidth analysis demonstrated only minimal differences in prediction between matched predictor-criterion pairs compared with predictor to overall aggregate ratings (unmatched). The communication skill analysis revealed that this interviewer rated observation significantly predicted a number of the individual performance dimensions as well as overall performance over time. Of the five interview items, the strongest overall predictor of performance was interviewer rated communication skill. The stability/dynamicity analyses demonstrated the performance criteria to be generally stable over the two year period examined, which provides support for the long held notion that performance criteria is stabile over time. However, there were two exceptions. The interview dimension customer service orientation had shifting relationships over time with four of the criteria over the two year period. The performance criteria employee development also demonstrated some instability in its relationships with predictors. Thus, some evidence of dynamicity in performance criteria was revealed. Interestingly, both of the most noteworthy findings in the study involved items that were rated differently than the others in the study. The rated interview item communication skill and the rated performance criteria client satisfaction were ratings that involved a more direct level of observation. Additional analyses also revealed evidence of a general factor of performance. These two themes are more fully covered in the discussion.

Hybrid approaches to estimating freeway travel times using point traffic detector data

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

Gender Benders: Shakespeare's Rosalind and Woolf's Orlando

English Renaissance playwright, William Shakespeare and twentieth century modernist author, Virginia Woolf’s works, “As You Like It” (1599) and “Orlando” (1928), respectively posit a vision of gender that transcends the physical sex of the body. The play’s heroine, Rosalind, and the novel’s protagonist, Orlando, each challenge the stability of the binary categories of male and female, demonstrating how gender is not absolute but rather a constantly adapting and evolving construct. This thesis traces the development of Rosalind and Orlando by analyzing and comparing both protagonists’ journeys towards concordia discors, considering how gender transformation plays a pivotal role in helping both figures transcend prescribed gender roles and restraints placed upon them by family and society. Both Rosalind and Orlando mount challenges to prescribed gender norms during periods when conservative gender roles were strictly enforced. By doing so, each character positions themselves as pivotal and progressive representations of gender performance for their time.