The ability to develop bots to automate tasks and processes using robotic process automation (RPA) is receiving significant attention in accounting. Auditors often struggle to know what tasks to automate and how to prioritize bot development. Drawing upon socio-technical systems (STS) theory and using a design science methodology, we develop and validate a three-step evaluation framework to assist auditors as they decide what activities to automate. We validate this framework using interviews, surveys of experienced internal and external auditors, and two case studies. By developing and validating our framework through the lens of STS theory, we also provide several insights that help explain the mixed findings in prior research regarding the effectiveness and adoption of emerging technologies in audit. The implications of our study yield many opportunities for future research in the areas of RPA and emerging technologies in audit.

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We investigate whether the type of performance feedback (individual versus relative) firms provide employees on one task alters employees' willingness to help other employees on a subsequent, unrelated task. Consistent with prior research, results from our experiment show that employees perform better on a production task when they receive relative performance feedback as opposed to individual performance feedback about the task. However, we document that the valence of RPI feedback appears to moderate the effect of RPI on subsequent helping behavior. Specifically, those who receive RPI feedback indicating that they performed (better) worse than another participant exhibit (lower) higher levels of helping behavior relative to those who receive only individual feedback. Our results highlight the complex tradeoffs confronting managers and management accountants when designing performance feedback systems and the need for them to consider employees' tasks holistically rather than in isolation when deciding what type of performance feedback to provide. JEL Classifications: C71; M41; J31. Data Availability: Available upon request.

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