Linking business analytics to decision making effectiveness: a path model analysis
Affiliation
University of BedfordshireIssue Date
2015-06-24Subjects
business analyticsinformation processing capability
decision-making effectiveness
information processing view
contingency theory
data-driven environment
N210 Management Techniques
decision making
information processing
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Show full item recordAbstract
While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to manager's knowledge and understanding by demonstrating how business analytics should be implemented to improve DMECitation
Cao G, Duan Y, Li G (2015) 'Linking business analytics to decision making effectiveness: a path model analysis', IEEE Transactions on Engineering Management, 62 (3), pp.384-385.Publisher
IEEEType
ArticleLanguage
enISSN
0018-9391ae974a485f413a2113503eed53cd6c53
10.1109/TEM.2015.2441875
Scopus Count
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