Humans and Algorithms in Organizational Decision Making: Evidence from a Field Experiment

Sebastian Maximillian Krakowski, Darek Haftor, Johannes Luger, Natallia Pashkevich, Sebastian Raisch

Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsResearchpeer-review


This paper reports the results of a controlled field experiment designed to investigate the interaction effects between humans and algorithms in organizational decision-making. We study the performance consequences of providing groups of managers making unstructured sales calls with alternative versions of an algorithm-based sales support system. Surprisingly, we find that standardized algorithms - which are clearly superior in terms of functionality and information processing when compared to the control group's basic information system - showed a negative overall treatment effect on managers' sales performance. In comparison, an algorithm adapted to sales managers' cognitive styles, showed a positive treatment effect. We further explore the role of human experience and find additional evidence for a human-algorithm interaction effect. Collectively, our results suggest intriguing complementarities in human and machines' information processing when dealing with complex organizational decision-making.
Original languageEnglish
Title of host publicationAcademy of Management Proceedings 2019
EditorsGuclu Atinc
Number of pages1
Place of PublicationBriarcliff, NY
PublisherAcademy of Management
Publication date2019
Publication statusPublished - 2019
SeriesAcademy of Management Proceedings

Cite this