Different departments, different drivers: Asymmetry in antecedents and outcomes of voluntary knowledge exchange between sales and production functions

Date

2017

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Publisher

Emerald

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Article

ISSN

0144-3577

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Citation

Bendoly E, Guo L, Hu Y, Tobias J. (2017) Different departments, different drivers: asymmetry in antecedents and outcomes of voluntary knowledge exchange between sales and production functions. International Journal of Operations and Production Management, Volume 37, Issue 8, 2017, pp. 1031-1053

Abstract

In this study, we examine the antecedents and performance consequences of voluntary information exchange between the Production and Sales functions. Building on the Motivation-Opportunity-Ability (MOA) framework, we first posit a general model for bilateral information exchange across functional levels. The innovation presented in this model consists in allowing both sides of such an exchange (e.g., Production-to-Sales and Sales-to-Production) to differ in the perceived adequacy of information they receive.The two sides can also differ in terms of how their motivation and ability impact that adequacy. To test the model, we make use of survey responses and objective data from Sales, Production and executive managers of 182 Chinese manufacturers. Analysis of our sample shows the Sales-to-Production exchange has a smaller estimated performance effect than the Production-to-Sales exchange. Although shared opportunity is important in predicting both sides of the exchange, our measure of motivation appears to only significantly impact the Sales-to-Production exchange. In contrast, our measure of ability only appears to significantly affect the Production-to-Sales exchange. Although limited to a regional context, differences in information-sharing drivers on the two sides of Production-Sales dyads pose strong implications that may be generalizable. Specifically, these findings suggest alternative approaches and foci for resource investment that higher level managers can leverage in developing more effective cross-functional work settings.

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Github

Keywords

Empirical, Operational performance, Information exchange, Cross-functional

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Attribution-NonCommercial 4.0 International

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