A Design Science Framework for the Adoption and Implementation of Augmented Reality in Warehouse Logistics

Abstract

Augmented reality (AR) has been studied extensively as a means of supporting warehouse order picking, particularly through wearable displays, visual guidance, and pilot applications. Less attention has been given to how these elements are brought together when an AR solution is introduced into an operating warehouse. This study develops a six-phase Design Science framework for the systematic adoption and implementation of AR in warehouse logistics. The framework integrates strategic and organizational readiness, data preparation, business process redesign, multi-criteria hardware selection, three-tier system architecture, human-centric interface design, and phased implementation with continuous improvement. The framework was instantiated through an industrial Vision Picking pilot in the central distribution center of a telecommunications provider. The pilot included ARIS-based process redesign, AHP-supported selection of a head-mounted display, integration with the existing warehouse information systems, and development of a context-aware wearable interface for location and product-identifier verification. A comparative operational evaluation showed that productivity increased from 106.3 to 112.0 lines per hour per picker, corresponding to a 5.36% improvement, while the error rate decreased from 36.2 to 11.1 errors per 10,000 order lines, corresponding to a 69.34% reduction. Because the evaluation relies on aggregated operational indicators from a single industrial implementation, the findings serve as case-based evidence of the proposed framework’s practical applicability rather than as generalizable evidence of AR technology effectiveness. The study contributes an integrated decision-support artifact that connects organizational, process, technological, and human-centric implementation decisions within a coherent AR adoption pathway for warehouse logistics.