The impact of advanced analytics and data accuracy on operational performance: a contingent resource based theory (RBT) perspective

K-REx Repository

Show simple item record

dc.contributor.author Chae, Bongsug
dc.contributor.author Yang, Chenlung
dc.contributor.author Olson, David
dc.contributor.author Sheu, Chwen
dc.date.accessioned 2014-06-12T19:55:22Z
dc.date.available 2014-06-12T19:55:22Z
dc.date.issued 2014-06-12
dc.identifier.uri http://hdl.handle.net/2097/17843
dc.description.abstract This study is interested in the impact of two specific business analytic (BA) resources—accurate manufacturing data and advanced analytics—on a firms’ operational performance. The use of advanced analytics, such as mathematical optimization techniques, and the importance of manufacturing data accuracy have long been recognized as potential organizational resources or assets for improving the quality of manufacturing planning and control and of a firms’ overall operational performance. This research adopted a contingent resource based theory (RBT), suggesting that the moderating and mediating role of fact-based SCM initiatives as complementary resources. This research proposition was tested using Global Manufacturing Research Group (GMRG) survey data and was analyzed using partial least squares/structured equation modeling. The research findings shed light on the critical role of fact-based SCM initiatives as complementary resources, which moderate the impact of data accuracy on manufacturing planning quality and mediate the impact of advanced analytics on operational performance. The implication is that the impact of business analytics for manufacturing is contingent on contexts, specifically, the use of fact-based SCM initiatives such as TQM, JIT, and statistical process control. Moreover, in order for manufacturers to take advantage of the use of data and analytics for better operational performance, complementary resources such as fact-based SCM initiatives must be combined with BA initiatives focusing on data quality and advanced analytics. en_US
dc.language.iso en_US en_US
dc.relation.uri http://www.sciencedirect.com/science/article/pii/S0167923613002595 en_US
dc.subject Supply chain analytics en_US
dc.subject Data accuracy en_US
dc.subject SCM initiatives en_US
dc.subject Moderating effect en_US
dc.subject Mediating effect en_US
dc.title The impact of advanced analytics and data accuracy on operational performance: a contingent resource based theory (RBT) perspective en_US
dc.type Article (author version) en_US
dc.date.published 2014 en_US
dc.citation.doi doi:10.1016/j.dss.2013.10.012 en_US
dc.citation.epage 126 en_US
dc.citation.jtitle Decision Support Systems en_US
dc.citation.spage 119 en_US
dc.citation.volume 59 en_US
dc.contributor.authoreid bchae en_US
dc.contributor.authoreid csheu en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search K-REx


Advanced Search

Browse

My Account

Statistics








Center for the

Advancement of Digital

Scholarship

118 Hale Library

Manhattan KS 66506


(785) 532-7444

cads@k-state.edu