journal article Sep 02, 2015

Leveraging Supply Chain Integration through Planning Comprehensiveness: An Organizational Information Processing Theory Perspective

Decision Sciences Vol. 46 No. 5 pp. 823-861 · Wiley
View at Publisher Save 10.1111/deci.12166
Abstract
ABSTRACTThis study extends prior research on supply chain planning and integration by examining the underlying capabilities by which firms exploit the information they gain from integration activities. We use organizational information processing theory (OIPT) to develop hypotheses that identify the comprehensiveness of an organization's supply chain planning capabilities as an important mediator in the relationship between its supply chain integration activities and its operational performance. Further, our interpretation of OIPT suggests that an organization's usage of technology‐enabled supply chain management systems (SCMS) moderates these effects. Using survey data from 445 global firms, we estimate the corresponding moderated‐mediation structural model. The results indicate that usage of SCMS enables organizations to better utilize the information they gain from external integration efforts (relationships with customers and suppliers), thus improving the comprehensiveness of their supply chain planning capabilities. In contrast, the use of SCMS appears to be a partial substitute for internal integration as a driver of planning comprehensiveness. Most importantly, the results suggest that planning comprehensiveness is a significant generative means by which integration and technology investments produce superior operational performance. These findings provide a richer and more theoretically grounded explanation of relationships between supply chain integration, supply chain planning, and operational performance.
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Published
Sep 02, 2015
Vol/Issue
46(5)
Pages
823-861
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Cite This Article
Ravi Srinivasan, Morgan Swink (2015). Leveraging Supply Chain Integration through Planning Comprehensiveness: An Organizational Information Processing Theory Perspective. Decision Sciences, 46(5), 823-861. https://doi.org/10.1111/deci.12166
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