Performance Measure Aggregation in Multi‐Task Agencies
研究了多任务环境下绩效信息汇总效率与定制化/标准化程度的关系，发现汇总无信息损失需至少与有效任务数相同的指标，而汇总无经济损失可用单一指标但需定制化，并预测复杂多任务工作需高度定制化绩效评估。
ABSTRACT In multi‐task environments, the efficiency of aggregating managerial performance information and the degree of customization/standardization are closely related. Aggregation without information loss (i.e., statistically sufficient) requires at least as many measures as there are effective tasks (which arise through a task aggregation process analogous to that applied to homogeneous activities in activity‐based costing) and can be used uniformly for evaluation across similar jobs. Aggregation without economic loss (i.e., economically sufficient) can be achieved with a single performance measure but requires customization even across similar jobs. The main implication is that job complexity, the number of aggregate performance measures, and the degree of customization in performance measurement are interrelated. In particular, at the same level of performance measure aggregation, we predict highly customized performance evaluation in complex multi‐task jobs and standardized (uniform) performance evaluation only in simpler jobs with fewer tasks. We discuss additional empirical implications in the conclusion.