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Paper Number
1366
Paper Type
Complete
Description
Advanced technologies are introduced in warehouse operations, rendering the interplay between human worker behavior and information systems (IS) a critical issue. We investigate how IS supports manual order picking by studying how visual color-coding information on picking locations provided through personal digital assistants accelerates search and picking tasks. Considering real-world data on a storage system where 20 dissimilar items are stored together at one picking location, we apply a log-logistic accelerated failure time model with N=112,672 picks performed by N=190 workers and find that color-coding accelerates the picking process by up to 17.28%. To increase the internal validity of our field-based examination, we conduct one VR experiment (N=29 participants) providing evidence for an acceleration of 23.74%, and one online experiment (N=178 participants) indicating an acceleration of 24.29%. Based on an innovative method of triangulation, we demonstrate how IS can influence picker behavior and discuss how to better design IT artifacts.
Recommended Citation
Loske, Dominic; Menck, Jannes Heinrich Diedrich; Lechte, Henrik; Lembcke, Tim-Benjamin; Modica, Tiziana; and Klumpp, Matthias, "The Colors of Performance – Assessing the Impact of Color-Coding on Worker Behavior in Retail Order Picking" (2022). ICIS 2022 Proceedings. 1.
https://aisel.aisnet.org/icis2022/user_behaivor/user_behaivor/1
The Colors of Performance – Assessing the Impact of Color-Coding on Worker Behavior in Retail Order Picking
Advanced technologies are introduced in warehouse operations, rendering the interplay between human worker behavior and information systems (IS) a critical issue. We investigate how IS supports manual order picking by studying how visual color-coding information on picking locations provided through personal digital assistants accelerates search and picking tasks. Considering real-world data on a storage system where 20 dissimilar items are stored together at one picking location, we apply a log-logistic accelerated failure time model with N=112,672 picks performed by N=190 workers and find that color-coding accelerates the picking process by up to 17.28%. To increase the internal validity of our field-based examination, we conduct one VR experiment (N=29 participants) providing evidence for an acceleration of 23.74%, and one online experiment (N=178 participants) indicating an acceleration of 24.29%. Based on an innovative method of triangulation, we demonstrate how IS can influence picker behavior and discuss how to better design IT artifacts.
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