TY - JOUR
T1 - Factors of data infrastructure and resource support influencing the integration of business intelligence into enterprise resource planning systems
AU - Shen, Chien Wen
N1 - Publisher Copyright:
© 2015 Inderscience Enterprises Ltd.
PY - 2015
Y1 - 2015
N2 - This study aims to investigate whether data infrastructure and resource support affect the integration of business intelligence (BI) into enterprise resource planning (ERP) systems. A Bayesian network model includes the variables of data warehouse, OLAP, data mining, ERP vendor, online period of ERP, return on assets, return on sales, return on investment, sales over employees and BI implementation was developed to investigate the issues of this research. Empirical findings from ERP-implemented manufacturers suggest that BI implementation may not have positive impacts on financial performances. In contrast, BI-implemented companies generally have more complicated data infrastructure than the companies without BI systems. In addition, results of Bayesian inferences suggest that ERP vendor, data warehouse, OLAP and data mining may have significant impacts on the implementation of BI systems. Hence, companies should choose their ERP solutions carefully or start planning their data infrastructure if they expect to adopt BI solutions in the future.
AB - This study aims to investigate whether data infrastructure and resource support affect the integration of business intelligence (BI) into enterprise resource planning (ERP) systems. A Bayesian network model includes the variables of data warehouse, OLAP, data mining, ERP vendor, online period of ERP, return on assets, return on sales, return on investment, sales over employees and BI implementation was developed to investigate the issues of this research. Empirical findings from ERP-implemented manufacturers suggest that BI implementation may not have positive impacts on financial performances. In contrast, BI-implemented companies generally have more complicated data infrastructure than the companies without BI systems. In addition, results of Bayesian inferences suggest that ERP vendor, data warehouse, OLAP and data mining may have significant impacts on the implementation of BI systems. Hence, companies should choose their ERP solutions carefully or start planning their data infrastructure if they expect to adopt BI solutions in the future.
KW - Bayesian networks
KW - Business intelligence
KW - Data mining
KW - Data warehouse
KW - ERP
KW - OLAP
KW - enterprise resource planning
UR - http://www.scopus.com/inward/record.url?scp=84938798067&partnerID=8YFLogxK
U2 - 10.1504/IJIIDS.2015.070822
DO - 10.1504/IJIIDS.2015.070822
M3 - 期刊論文
AN - SCOPUS:84938798067
SN - 1751-5858
VL - 9
SP - 1
EP - 14
JO - International Journal of Intelligent Information and Database Systems
JF - International Journal of Intelligent Information and Database Systems
IS - 1
ER -