Robotic Process Automation (RPA) has proven to be an efficiency-boosting automation technology in corporate practice that makes many of the work steps performed by employees obsolete and, as a result, greatly changes the way they work. A critical success factor for the sustainable introduction and establishment of the efficiency potential of RPA is the acceptance of the employees involved. Studies also show that management decisions are made on the basis of subjective criteria in almost half of all cases, despite the availability of automated knowledge.
Two types of influencing factors are responsible for this: the conscious disregard of the knowledge gained due to a lack of acceptance of this and the associated unconscious prejudices and cognitive distortions, so-called biases. Examples of biases include an excessive preference for the status quo over change (status quo bias) and an inability to adapt one's thinking to new evidence and information quickly enough (conservatism bias). To overcome these hurdles, a holistic approach to using RPA in organizations while ensuring employee buy-in must be developed.
In addition to technological and systems adaptation, this approach also calls for a necessary transformation of corporate organization and culture. For SMEs, this is particularly challenging due to limited human and financial resources. The aim of the "RPAcceptance" research project is therefore to develop an acceptance model that encompasses the key influencing factors with regard to the acceptance of RPA. These influencing factors will be empirically tested by a questionnaire study, a behavioral laboratory experiment and an online study in order to develop a sustainable approach for the systematic use of RPA by ensuring employee acceptance.

Cooperation partner: Research Association FIR e. V. at RWTH Aachen University

Sponsor: The IGF project 21512 N of the Research Association FIR e. V. at RWTH Aachen University is funded by the German Federal Ministry for Economic Affairs and Energy (BMWi) via the AiF as part of the program for the promotion of joint industrial research (IGF) based on a resolution of the German Bundestag.

Project period: November 2020 - October 2022