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The increased reliance on interorganizational collaborations (ICs) has created new challenges for leaders. They must attempt to apply leadership theories and behaviors developed primarily for leading within one organization or group to leading collaborations of multiple organizations and stakeholders. To provide insight into this issue, this study examines leadership behavior in an IC developing a strategic plan to promote changes to address public health and safety concerns related to substance abuse. Combining observations and interviews, we followed a statewide interagency taskforce in a southwestern state of the United States from its inception through completion of its strategic plan within a 10-month deadline. Findings show different leadership behaviors were integrated and evolved over time to strike a balance between decision-making effectiveness and efficiency. In particular, the findings support recent research on examining leadership behavior holistically to develop a 'fuller full-range' leadership perspective (Antonakis and House, 2014), especially in terms of how collectivistic and instrumental leadership should complement transformational leadership, and by demonstrating that the combinations of leadership change over time and occur at multiple levels. These findings provide guidance for future practice and research on ICs promoting change.

Objective: The aim of this laboratory experiment was to demonstrate how taking a longitudinal, multilevel approach can be used to examine the dynamic relationship between subjective workload and performance over a given period of activity involving shifts in task demand. Background: Subjective workload and conditions of the performance environment are oftentimes examined via cross-sectional designs without distinguishing within- from between-person effects. Given the dynamic nature of performance phenomena, multilevel designs coupled with manipulations of task demand shifts are needed to better model the dynamic relationships between state and trait components of subjective workload and performance. Method: With a sample of 75 college students and a computer game representing a complex decision-making environment, increases and decreases in task demand were counterbalanced and subjective workload and performance were measured concurrently in regular intervals within performance episodes. Data were analyzed using hierarchical linear modeling. Results: Both between- and especially within-person effects were dynamic. Nevertheless, at both levels of analysis, higher subjective workload reflected performance problems, especially more downstream from increases in task demand. Conclusion: As a function of cognitive-energetic processes, shifts in task demand are associated with changes in how subjective workload is related to performance over a given period of activity. Multilevel, longitudinal approaches are useful for distinguishing and examining the dynamic relationships between state and trait components of subjective workload and performance. Application: The findings of this research help to improve the understanding of how a sequence of demands can exceed a performer's capability to respond to further demands.

Objective: This study examined the effectiveness of collaborative training for individuals with low pretraining self-efficacy versus individuals with high pretraining selfefficacy regarding the acquisition of a complex skill that involved strong cognitive and psychomotor demands. Background: Despite support for collaborative learning from the educational literature and the similarities between collaborative learning and interventions designed to remediate low self-efficacy, no research has addressed how selfefficacy and collaborative learning interact in contexts concerning complex skills and human-machine interactions. Method: One hundred fifty-five young male adults trained either individually or collaboratively with a more experienced partner on a complex computer task that simulated the demands of a dynamic aviation environment. Participants also completed a task-specific measure of self-efficacy before, during, and after training. Results: Collaborative training enhanced skill acquisition significantly more for individuals with low pretraining self-efficacy than for individuals with high pretraining self-efficacy. However, collaborative training did not bring the skill acquisition levels of those persons with low pretraining self-efficacy to the levels found for persons with high pretraining self-efficacy. Moreover, tests of mediation suggested that collaborative training may have enhanced appropriate skill development strategies without actually raising self-efficacy. Conclusion: Although collaborative training can facilitate the skill acquisition process for trainees with low self-efficacy, future research is needed that examines how the negative effects of low pretraining self-efficacy on complex skill acquisition can be more fully remediated. Application: The differential effects of collaborative training as a function of self-efficacy highlight the importance of person analysis and tailoring training to meet differing trainee needs.

This study constructively extends Arthur et al. (2001) by assessing the convergence of self-report and archival motor vehicle crash involvement and moving violations data in a 2-year longitudinal follow-up. The relationships among these criteria, conscientiousness, and driving speed were also assessed using both predictive and postdictive criterion-related validation designs. Data were collected from a 2-year follow-up sample of 334 participants. Results suggested a lack of convergence between self-report and archival data at both Time 1 and Time 2. In addition, the predictor/criterion relationships varied across research design and data source. An actual application of our findings is that the interpretation of relationships between specified predictors and crash involvement and moving violations must be made within the context of the criterion-related validation design and criterion data source. Specifically, predictive designs may produce results different from those of postdictive designs (which are more commonly used). Furthermore, self-report data appear to include a broader range of incidents (more crashes and tickets), and thus researchers should consider using self-report data when they are interested in including lower threshold crashes and tickets that may not be reported on state records (e.g., because of the completion of a defensive driving course)

In the crash involvement literature, it is generally assumed that archival and other "objective" criterion data are superior to self-reports of crash involvement. Using 394 participants (mean age = 36.23 years), the present study assessed the convergence of archival and self-report measures of motor vehicle crash involvement and moving violations. We also sought to determine whether predictor/criterion relationships would vary as a function of criterion type (i.e., archival vs. self-report), and if a combination of both criteria would result in better prediction than would either by itself. The degree of agreement between the two criterion sources was low, with participants self-reporting more crashes and tickets than were found in their state records. Different predictor/criterion relationships were also found for the two criterion types; stronger effects were obtained for self-report data. Combining the two criteria did not result in relationships stronger than those obtained for self-reports alone. Our findings suggest that self-report data are not inherently inferior to archival data and, furthermore, that the two sources of data cannot be used interchangeably. Actual or potential applications include choosing the appropriate criterion to use, which, as the finding of this study reveals, may depend on the purpose of the investigation.