The impact of supply chain analytics on operational performance: a resource-based view

dc.citation.doidoi:10.1080/00207543.2013.861616en_US
dc.citation.epage4710en_US
dc.citation.issue16en_US
dc.citation.jtitleInternational Journal of Production Researchen_US
dc.citation.spage4695en_US
dc.citation.volume52en_US
dc.contributor.authorChae, Bongsug K.
dc.contributor.authorOlson, David
dc.contributor.authorSheu, Chwen
dc.contributor.authoreidbchaeen_US
dc.contributor.authoreidcsheuen_US
dc.date.accessioned2014-11-06T15:23:54Z
dc.date.available2014-11-06T15:23:54Z
dc.date.issued2014-11-06
dc.date.published2014en_US
dc.description.abstractThis study seeks to better understand the role of supply chain analytics (SCA) on supply chain planning satisfaction and operational performance. We define the architecture of SCA as the integration of three sets of resources, data management resources (DMR), IT-enabled planning resources and performance management resources (PMR), from the perspective of a resource-based view. Based on the data collected from 537 manufacturing plants, we test hypotheses exploring the relationships among these resources, supply chain planning satisfaction, and operational performance. Our analysis supports that DMR should be considered a key building block of manufacturers’ business analytics initiatives for supply chains. The value of data is transmitted to outcome values through increasing supply chain planning and performance capabilities. Additionally, the deployment of advanced IT-enabled planning resources occurs after acquisition of DMR. Manufacturers with sophisticated planning technologies are likely to take advantage of data-driven processes and quality control practices. DMR are found to be a stronger predictor of PMR than IT planning resources. All three sets of resources are related to supply chain planning satisfaction and operational performance. The paper concludes by reviewing research limitations and suggesting further SCA research issues.en_US
dc.identifier.urihttp://hdl.handle.net/2097/18644
dc.language.isoen_USen_US
dc.relation.urihttp://www.tandfonline.com/doi/full/10.1080/00207543.2013.861616#.VFFPecVdVQxen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research, 2014, available online at: http://www.tandfonline.com/doi/full/10.1080/00207543.2013.861616#.VFFPecVdVQxen_US
dc.subjectManufacturing managementen_US
dc.subjectData miningen_US
dc.subjectSupply chain managementen_US
dc.titleThe impact of supply chain analytics on operational performance: a resource-based viewen_US
dc.typeArticle (author version)en_US

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