The Impact of Business Intelligence and Analytics Adoption on Decision Making Effectiveness and Managerial Work Performance Cover Image

The Impact of Business Intelligence and Analytics Adoption on Decision Making Effectiveness and Managerial Work Performance
The Impact of Business Intelligence and Analytics Adoption on Decision Making Effectiveness and Managerial Work Performance

Author(s): Luminita Hurbean, Florin Militaru, Mihaela Muntean, Doina Dănăiaţă
Subject(s): Business Economy / Management, Methodology and research technology, Management and complex organizations, ICT Information and Communications Technologies
Published by: Editura Universităţii »Alexandru Ioan Cuza« din Iaşi
Keywords: Business Intelligence and Analytics; data-driven culture; decision-making effectiveness; individual work performance;

Summary/Abstract: Business Intelligence and Analytics systems have the capability to enable organizations to better comprehend their business and to increase the quality of managerial decisions, and consequently improve their performance. Recently, organizations have embraced the idea that data becomes a core asset, and this belief also changes the culture of the organization; data and analytics now determine a data-driven culture, which makes way for more effective data-driven decisions. To the best of our knowledge, there are few studies that investigate the effects of BI&A adoption on individual decision-making effectiveness and managerial work performance. This paper aims to contribute to bridging this gap by providing a research model that examines the relationship between BI&A adoption and manager’s decision-making effectiveness and then his individual work performance. The research model also theorizes that a data-driven culture promotes the BI&A adoption in the organization. Using specific control variables, we also expect to observe differences between different departments and managerial positions, which will provide practical implications for companies that work on BI&A adoption.

  • Issue Year: 70/2023
  • Issue No: Special
  • Page Range: 43-54
  • Page Count: 12
  • Language: English