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Linking business analytics to decision making effectiveness: a path model analysis

Research Output: Contribution to journal Article Peer-review

Open access

Abstract

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 DME

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 384-385

Journal (Volume, Issue Number)

IEEE Transactions on Engineering Management (Volume 62, Issue 3)

Publication milestones

  • Published - 24/06/2015

Publication status

Published - 24/06/2015

ISSN

0018-9391

External Publication IDs

  • handle.net: 10547/560379
  • Scopus: 85027926999

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