DocumentCode
744462
Title
Linking Business Analytics to Decision Making Effectiveness: A Path Model Analysis
Author
Guangming Cao ; Yanqing Duan ; Gendao Li
Author_Institution
Univ. of Bedfordshire, Luton, UK
Volume
62
Issue
3
fYear
2015
Firstpage
384
Lastpage
395
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 managers´ knowledge and understanding by demonstrating how business analytics should be implemented to improve DME.
Keywords
decision making; modal analysis; organisational aspects; service industries; statistical analysis; U.K. businesses; business analytics applications; contingency theory; data-driven insights; decision making effectiveness; information processing capability; information processing view; large-medium companies; organizational DME; path model analysis; professional service industries; statistical differences; structural equation modeling; Analytical models; Companies; Decision making; Industries; Information processing; Business analytics (BA); contingency theory; data-driven environment (DDE); decision-making effectiveness (DME); information processing capability (IPC); information processing view;
fLanguage
English
Journal_Title
Engineering Management, IEEE Transactions on
Publisher
ieee
ISSN
0018-9391
Type
jour
DOI
10.1109/TEM.2015.2441875
Filename
7132744
Link To Document