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Incentive effects of enterprise systems on the magnitude and detectability of reporting manipulations

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  • Stratopoulos, Theophanis C.
  • Vance, Tom W.
  • Zou, Xiorong

Abstract

We consider how the information environment effects of enterprise system (ES) forecasting tools affect a given manager's decision to manipulate reported performance. As ES forecasting accuracy increases, the manager is better able to determine whether anticipated performance is going to exceed the desired level of performance, and we propose that this may affect how the manager chooses to use the ES. To investigate this setting, we construct a model of manipulation behavior as a function of desired performance, uncertainty in forecasted performance and internal control strength. The implications of the model suggest that as a manager's forecast of an impending shortfall in expected performance becomes more certain, the economically optimal decision is increasingly to manipulate reported performance and to use smaller magnitude adjustments. This result holds unless a significant countervailing investment in internal control strength accompanies the ES, which evidence suggests is not the norm in practice. This study furthers our understanding of the effects of ES adoption on managerial behavior and contributes to the burgeoning literature investigating the dual control and empowerment roles of technology. Opportunities for future research are discussed.

Suggested Citation

  • Stratopoulos, Theophanis C. & Vance, Tom W. & Zou, Xiorong, 2013. "Incentive effects of enterprise systems on the magnitude and detectability of reporting manipulations," International Journal of Accounting Information Systems, Elsevier, vol. 14(1), pages 39-57.
    • Handle: RePEc:eee:ijoais:v:14:y:2013:i:1:p:39-57
    DOI: 10.1016/j.accinf.2012.08.001
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    Cited by:

    1. Shaio Yan Huang & Chi-Chen Lin & An-An Chiu & David C. Yen, 2017. "Fraud detection using fraud triangle risk factors," Information Systems Frontiers, Springer, vol. 19(6), pages 1343-1356, December.
    2. Shaio Yan Huang & Chi-Chen Lin & An-An Chiu & David C. Yen, 0. "Fraud detection using fraud triangle risk factors," Information Systems Frontiers, Springer, vol. 0, pages 1-14.

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