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Early evidence of digital labor in accounting: Innovation with Robotic Process Automation
Institution:1. Michael Smurfit Graduate Business School, University College Dublin, Ireland;2. The University of Queensland Business School, Australia;3. The University of Queensland Business School and TC Beirne School of Law, Australia;1. Aston University, Aston Triangle, Birmingham B4 7ET, UK;2. Naval Postgraduate School, 1 University Circle, Monterey, CA 93943, USA;3. Aalto University, Ekonominaukio 1, Espoo, 02150, Finland;4. University of Jyväskylä, Seminaarinkatu 15, Jyväskylä, 40014, Finland;1. Reykjavik University, School of Business, Menntavegur 1, 101 Reykjavik, Reykjavik, Iceland;2. Queensland University of Technology, School of Accountancy, Level 3, B Block, Gardens Point, 2 George St., Brisbane, QLD 4000, Australia
Abstract:Robotic Process Automation (RPA) is an emerging technology that enables the automation of rules-based business processes and tasks through the use of software bots. Drawing upon the theory of Task-Technology Fit (TTF) and Technology-to-Performance Chain (TPC) (Goodhue and Thompson 1995) and research on expert systems (Messier and Hansen 1987; Sutton 1990), this study explores emerging themes surrounding bot implementation for accounting and finance tasks. We collect and analyze interview data from adopters of RPA and document task suitability, task-technology fit, implementation issues, and resulting performance outcomes. We find that securing technical capability is only a part of RPA implementation process. Organizations engage in standardization and optimization of processes, develop scorecard-like tools to rank tasks, adjust governance structures to include digital employees, and redefine internal controls. Organizations benefit from automating only certain processes, those that are structured, repeated, rules-based, and with digital inputs. Along with cost savings, organizations experience improved process documentation, lower error rates, more accurate measurement of process performance, and better report quality.
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