Achieving efficient resilience through human adjustments of algorithm prescriptions–a retail management application

As the frequency of significant market disruptions rises, retailers are forced to respond through resilience activities which often comes at the cost of sacrificing operational efficiency. To alleviate this resilience-efficiency trade-off, retailers increasingly rely on digital technologies, particularly artificial intelligence (AI). Specifically, they are employing AI-based algorithm prescriptions to guide humans in operational decision-making, aiming to improve resilience while maintaining high efficiency. In our field study involving 341 stores of a large European retailer, we examine the effects of human-AI collaboration on this resilience-efficiency trade-off. Our results indicate that human adjustments of algorithm prescriptions regarding supply strategy factors (i.e., delivery frequency and delivery pattern) can intensify the trade-off. However, if organizational experience and product differentiation are high, adjusting algorithm prescriptions helps to reduce the conflict between resilience and efficiency. For practice, we offer important implications on how firms can leverage the potential of AI-based tools in retail stores to become both resilient and efficient.