Organizing warehouse management
Purpose: The purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by task complexity (TC) and market dynamics (MD). Design/methodology/approach: A multi-variable conceptual model is developed based on the literature and tested among 215 warehouses using a survey. Findings: The results suggest that TC and MD are the main drivers of warehouse management, measured by planning extensiveness (PE), decision rules complexity, and control sophistication. Differences between production and distribution warehouses are found with respect to the relationship between assortment changes and PE. Furthermore, TC appears to be a main driver of the specificity of the warehouse management (information) system (WMS). Research limitations/implications: This paper is based on 215 warehouses in The Netherlands and Flanders (Belgium); future research may test the model on a different sample. More research should be conducted to further validate the measures of the core dimensions of warehouse management. Practical implications: Different levels of TC and MD characterize warehouses. Such a characterization is a first step in determining generic warehouse functionalities and helping managers to decide on the best software for their warehouse operations. Originality/value: The paper defines the core dimensions of warehouse management, makes them measurable, tests them and assesses how these drivers impact specificity of WMS. The paper shows that PE in production warehouses is driven by different variables than in distribution centers.
|Keywords||Conceptual framework, Empirical, Information management, Logistics, Operations planning, Survey|
|Persistent URL||dx.doi.org/10.1108/IJOPM-12-2011-0471, hdl.handle.net/1765/76574|
|Journal||International Journal of Operations and Production Management|
Faber, N, de Koster, M.B.M, & Smidts, A. (2013). Organizing warehouse management. International Journal of Operations and Production Management, 33(9), 1230–1256. doi:10.1108/IJOPM-12-2011-0471