BEHAVIORAL WAREHOUSE LOGISTICS: HUMAN FACTORS AND NUDGE TOOLS FOR REDUCING ORDER-PICKING ERRORS

The paper addresses the growing cost of order-picking errors in trade and distribution warehouses where many operations remain human-driven despite the adoption of a warehouse management system (WMS). Under volatile demand, peak loads, staff shortages and, for Ukraine, wartime disruptions (interruptions, power outages, air-raid alerts), small lapses in attention may lead to rework, returns, service failures and safety incidents. The article conceptualizes behavioral warehouse logistics as an approach that complements process engineering and automation with behavioral economics and human factors. It discusses the main behavioral drivers of picking inaccuracies and performance variability: cognitive load, limited attention, fatigue accumulation, time pressure created by tight norms, incentive misalignment that rewards speed over quality, and team norms that shape compliance with standard operating procedures. To connect these drivers with managerial levers, the paper outlines an «environment– behavior–result» logic, emphasizing how work organization, information design (labels, wayfinding cues, radiofrequency (RF) prompts, confirmation steps) and performance management jointly shape operator choices during picking, replenishment, packing and internal moves. The paper also considers low-cost, scalable interventions: standardization of labeling and navigation, choice-architecture nudges embedded in task interfaces, error-proofing for high-risk steps, micro-breaks and task rotation, composite KPIs (Key Performance Indicators) that balance speed and accuracy, and real-time feedback supported by a learning loop based on error taxonomy and root-cause routines. The concluding section outlines directions for future research, including controlled pilots and quasi-experiments (e.g., A/B testing of labels and prompts) across warehouses and third-party logistics providers (3PL), as well as modeling the speed–quality–safety trade-off and integrating behavioral analytics into WMS.