Supply Chain Information Flow Strategies: an Empirical Taxonomy

E. Vanpoucke, K. Boyer, A. Vereecke

Research output: Contribution to journalArticleAcademicpeer-review

37 Citations (Scopus)

Abstract

Purpose – the purpose of this paper is to identify different information flow strategies to enhance integration in strategic alliances and studies these strategies with respect to contextual factors and the impact on performance.design/methodology/approach – the paper examines empirical data gathered from 56 manufacturing companies, describing 112 supply chain relationships. An empirical taxonomy is created based on cluster analysis.findings – based on a parsimonious description of inter-firm information flows in the literature and this paper's empirical findings, three types of alliances are identified: silent; communicative; and it intensive. While silent alliances have the poorest overall performance, substantial similarities are found between communicative and it intensive alliances. In particular, the analysis suggests that it intensive alliances, albeit performing better on operational capabilities, are not performing better on relationship satisfaction compared to communicative alliances. Additional analyses indicate that partners of an it intensive alliance are substantially more interdependent and larger in size.research limitations/implications – this research presents a taxonomy of information flow strategies in a supply chain context. This research is not describing causality, since the data are not longitudinal in nature.practical implications – managers need to selectively invest in it according to an overall supply chain integration strategy, which also takes softer, less technological forms of integration into consideration.originality/value – this research provides insight into inter-firm information flows from a contingency perspective, recognizing heterogeneity of firms and supply chain practices.
Original languageEnglish
Pages (from-to)1213-1241
Number of pages28
JournalInternational Journal of Operations & Production Management
Volume29
Issue number12
DOIs
Publication statusPublished - 1 Jan 2009

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