Impact of JIT‐selling strategy on organizational structure

Abstract

Purpose

This study aims to assess the impact of a JIT‐selling strategy on organizational structure by generally replicating the previous work of Germain et al.

Design/methodology/approach

In contrast to the sample population of logistics managers surveyed by Germain et al. this research draws on data from manufacturing executives with marketing responsibilities. More importantly, a major limitation of the earlier research, use of a single‐item scale measurement of the JIT‐selling construct, is overcome. A structural equation modeling approach was used to assess the impact of JIT‐selling on the organizational structure dimensions of integration, performance control, specialization, and decentralization.

Findings

Germain et al. found that JIT‐selling impacts performance control, specialization, and scheduling decentralization but not integration. While the results of this study support earlier findings that JIT‐selling impacts performance control and specialization, the results alternately find support for a relationship between JIT‐selling and integration and refute the previous finding that JIT‐selling is related to decentralization.

Research limitations/implications

The findings generally support the proposition that adoption of a JIT‐selling strategy will result in changes in organizational structure.

Practical implications

Manufacturing managers working to strengthen relationships with customers through a JIT‐selling approach should prepare for organizational change in terms of increased integration, performance control, and specialization.

Originality/value

JIT strategies are being used to strengthen the operations/marketing interface within the manufacturing sector. Specifically, this study assesses the impact of the JIT‐selling strategy on organizational structure in an effort to verify the work of Germain et al.

Citation

Green, K.W., Inman, R.A. and Birou, L.M. (2011), "Impact of JIT‐selling strategy on organizational structure", Industrial Management & Data Systems, Vol. 111 No. 1, pp. 63-83. https://doi.org/10.1108/02635571111099730