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Performance Measure Aggregation in Multi‐Task Agencies

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  • Florin Şabac
  • Junwook Yoo

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. Dans les environnements polyvalents (multitâches), l'efficience du regroupement des informations relatives au rendement des dirigeants et le degré de personnalisation ou de standardisation sont en étroite relation. Le regroupement sans perte d'informations (regroupement statistiquement suffisant) exige au moins autant de mesures qu'il y a de tâches différentes (ce que l'on obtient au moyen d'un processus de regroupement des tâches analogue à celui qui s'applique aux activités homogènes en comptabilité par activités) et peut être utilisé uniformément dans l'évaluation d'un ensemble de postes similaires. Le regroupement sans perte économique (c'est‐à‐dire économiquement suffisant) peut être réalisé à l'aide d'une simple mesure du rendement mais exige la personnalisation, même pour un ensemble de postes similaires. Il s'ensuit principalement que la complexité du poste, le nombre de mesures du rendement regroupées et le degré de personnalisation dans l'évaluation du rendement sont interreliés. Pour un même niveau de regroupement des mesures du rendement, les auteurs prévoient en particulier une évaluation du rendement très personnalisée dans le cas des postes complexes nécessitant une grande polyvalence et une évaluation du rendement standardisée (uniforme) uniquement dans le cas des postes moins exigeants, faisant intervenir un moins grand nombre de tâches. Les auteurs concluent en traitant des répercussions empiriques de ces observations.

Suggested Citation

  • Florin Şabac & Junwook Yoo, 2018. "Performance Measure Aggregation in Multi‐Task Agencies," Contemporary Accounting Research, John Wiley & Sons, vol. 35(2), pages 716-733, June.
  • Handle: RePEc:wly:coacre:v:35:y:2018:i:2:p:716-733
    DOI: 10.1111/1911-3846.12418
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    Cited by:

    1. Junwook Yoo & Igor Semenenko, 2021. "Performance measure aggregation – two action levels," Economics Bulletin, AccessEcon, vol. 41(2), pages 564-572.
    2. Peter O. Christensen & Hans Frimor & Florin Şabac, 2020. "Real Incentive Effects of Soft Information," Contemporary Accounting Research, John Wiley & Sons, vol. 37(1), pages 514-541, March.

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