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This study examines the relative efficacy of groups in both virtual and traditional face-to-face courses, as well as differences in group dynamics between the two delivery methods. We surveyed students in online and traditional classroom sections of the same intermediate-level cost accounting course about their perceptions of group processes, general satisfaction with group work, learning outcomes, and group communications. Traditional classroom students were more positive about their group processes and learning outcomes than were online students. They also were more likely to agree that the learning benefits of group work outweighed the costs, (e.g., uneven and inefficient work distribution.) Our findings suggest that instructors who use groups in online courses should specifically consider the potentially negative effects of such factors as workload imbalances when designing group learning activities so that learning objectives are not adversely affected.

Prior experimental budgeting research has focused primarily on individuals’ budget setting and little experimental research has examined budgeting in a group setting. Using a controlled experiment, this study extends prior participative budgeting research by examining the effects of aggregation levels of performance feedback and task interdependence on budgetary slack and the effects of different levels of feedback on group performance in a group participative budget setting.

The results suggest that aggregation levels of performance feedback differentially impact budgetary slack and group performance. Providing both group and individual performance feedback increases group performance and reduces budgetary slack compared to providing group performance feedback only. Providing information about other subordinates’ performance further increases group performance and reduces budgetary slack beyond the effects of providing individual workers information only about their own performance. The results indicate that task interdependence also affects the level of budgetary slack. Specifically, high task interdependence groups created more budgetary slack than did low task interdependence groups.

Examines the effects of the outcome of an over‐budget audit on supervisors' perceptions of the auditor's performance.

Uses a cognitive model developed by Lipe. In a computer‐based experiment and an external audit context, professional auditors assumed the role of a supervisor evaluating a subordinate. Participants assessed the excess audit time in terms of perceived benefits to the firm and subsequently evaluated the job performance of the auditor.

The results provide partial support for Lipe's model, but differ in some respects. Interestingly, the effect of audit findings on the perceived benefit to the firm was not significant after considering experience in public accounting, but experience was not related to the actual performance evaluation. Instead, the audit outcome significantly affects the evaluation.

The level of benefit perceived from the audit was also associated with framing the audit time in terms of a “cost” or “loss”. Finally, as subjects tended toward framing the excess time as a “cost”, they evaluated the auditor more favorably.

For non‐normal Pearsonian processes, Clements proposed a method for calculating estimators of the two basic process capability indices C_p and C_pk. Pearn and Kotz applied Clements’ method to obtain estimators for the other two more advanced process capability indices C_pm and C_pmk. Their considerations on those indices, however, are restricted to processes with symmetric tolerances. Recently, Pearn and Chen proposed a generalization of the index C_pk to handle cases with asymmetric tolerances. The generalization takes into account the asymmetry of the manufacturing specifications, which is shown to be superior to the other existing methods. In this paper, we apply this approach and consider a generalization of Clements’ method for non‐normal Pearsonian processes where the manufacturing tolerances are asymmetric. Comparisons between the original Clements’ method and the proposed generalization are provided. The results indicate that the generalization is more accurate than the original Clements’ method in measuring process capability.

Financial analysts' forecasts serve as a proxy for market earnings expectations, and research provides mixed evidence of the relation between financial analysts' expertise and forecast accuracy. The judgment and decision-making (J/DM) literature suggests that those with more expertise will not perform better when tasks exhibit either extremely high or extremely low complexity. Expertise is expected to contribute to superior performance for tasks between these two extremes. Using archival data, this research examines the effect of analysts' expertise on forecasting performance by taking into consideration the forecasting task's complexity. Results indicate that expertise is not an explanatory factor for forecast accuracy when the forecasting task's complexity is extremely high or low. However, when task complexity falls between these two extremes, expertise is a significant explanatory variable of forecast accuracy. Both results are consistent with our expectations.