自动化偏差与审计中的“金发姑娘效应”[j]

IF 1.6 Q3 BUSINESS, FINANCE
Cory A. Campbell, S. Ramamoorti, Thomas G. Calderon
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引用次数: 0

摘要

区块链技术似乎具有独特的特征,例如固有的信任、不变性、透明度和更严格的安全性,这些可能有助于审计过程。通过对AICPA成员的调查,我们研究了对区块链支持环境中与管理断言相关的审计证据评估的回应。我们假设在支持区块链的环境中依赖审计证据可能产生三种影响:(1)金发效应(没有自动化偏见),或者审计师表现出“恰到好处”的专业怀疑态度和应有的谨慎态度,从而达到最佳审计水平的理想情况;(2)光环效应或积极的自动化偏差,可能导致过度依赖证据,从而导致审计不足;(3)炒作效应或负面的自动化偏差,这可能导致对证据的依赖不足,进而导致过度审计。我们的结果表明,我们调查的受访者主要受到光环效应的影响,表明在管理断言中倾向于积极的自动化偏见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automation Bias and the “Goldilocks Effect” in Auditing Blockchain
Blockchain technology appears to have unique characteristics such as inherent trust, immutability, transparency, and tighter security that might facilitate the audit process. Using a survey of AICPA members, we examine responses to the evaluation of audit evidence related to management assertions in a blockchain-enabled environment. We posit three possible effects pertaining to reliance on audit evidence in blockchain-enabled environments: (1) Goldilocks Effect (no automation bias) or the ideal scenario where auditors exhibit “just right” levels of professional skepticism and due care resulting in an optimal level of auditing; (2) Halo Effect or positive automation bias, which potentially results in over-reliance on evidence and, in turn, underauditing and; (3) Hype Effect or negative automation bias, which potentially results in under-reliance on evidence and, in turn, overauditing. Our results suggest that respondents to our survey are predominantly influenced by the Halo Effect, indicating a propensity for positive automation bias across management assertions.
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来源期刊
CiteScore
4.30
自引率
27.80%
发文量
14
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