Robotic process automation in logistics: Implementation model and factors of success

Purpose: Robotic process automation (RPA) refers to software robots (bots) that automate repetitive, rule-based tasks in a business process. In this study, the research questions regarding logistics applications are as follows: (1) What are suitable use cases for RPA in logistics? (2) Which criteria support the selection of appropriate processes? (3) How should a procedure model for implementation be designed to systematically support the introduction while considering critical success factors? Methodology: This study follows the design science research process by Peffers et al. (2006). The research gap was identified through an extensive literature analysis, reflecting the state of research. Insights gained were compared with empirical data from the use of RPA at a case company. Findings: A procedure model was designed to systematically consider success factors for an implementation, comprising (1) initiation; (2) piloting; (3) deployment; and (4) ongoing governance, maintenance, and continuous improvement. Originality: RPA can contribute to solving challenges such as increased service demands from customers, combined with cost pressures and a shortage of skilled labor. The procedure model closes a research gap, both from a scientific perspective and from the practitioners’ viewpoint, supporting an efficient and effective implementation. The consideration of knowledge from both theory and practice ensures practical relevance and significantly expands the state of research.