Interorganizational system characteristics and supply chain integration: An empirical assessment*
Saeed, Khawaja A. Malhotra, Manoj K. Grover, Varun
Saeed, Khawaja A.
Malhotra, Manoj K.
Grover, Varun
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2011-02-23
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Article
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Keywords
Cluster Analysis,Electronic Integration,Interorganizational Systems,Supply Chain,Survey
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Citation
Saeed, K.A., Malhotra, M.K. and Grover, V. (2011), Interorganizational System Characteristics and Supply Chain Integration: An Empirical Assessment*. Decision Sciences, 42: 7-42. https://doi.org/10.1111/j.1540-5915.2010.00300.x
Abstract
Some firms have gained significant benefits by effectively deploying interorganizational systems (IOS) to tightly couple operations with their supply chain partners. In contrast, other firms with IOS deployments have struggled to achieve this level of success. So it is not clear how such systems can be configured to promote idiosyncratic interorganizational processes that integrate the supply chains and facilitate successful outcomes. To shed further light on this issue, we draw from multiple theoretical perspectives to develop a comprehensive and unique conceptualization of IOS characteristics that goes beyond the limited treatment it has received in extant literature. Furthermore, we empirically examine the IOS configuration choices made by firms with different supply chain integration (SCI) profiles. Our results support the notion that successful firms sequence the configuration of IOS characteristics toward effectively developing and supporting their supply chain process capabilities. In particular, we found that firms at the lower end of SCI configure IOS features to support supplier evaluation and automatic alerts. As organizations move to the upper end of the SCI spectrum, greater attention is paid to features associated with systems integration, planning, and forecasting. Recommendations to managers and academics stemming from our study are provided, along with avenues for future research. © 2011 The Authors Decision Sciences Journal © 2011 Decision Sciences Institute.
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This is an open access article under the CC by license
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John Wiley & Sons
Journal
Decision Sciences
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15405915