![Sample our Information Science journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5940/TOC-Subject-Sample-2021-Communication-Studies.jpg"})
Abstract
Despite numerous testimonials of first movers, the underlying mechanisms of organizations’ big data analytics (BDA) usage deserves close investigation. Our study addresses two essential research questions: (1) How does organizational BDA usage affect value creation? and (2) What are key antecedents of organizational-level BDA usage? We draw on dynamic capabilities theory to conceptualize BDA use as a unique information processing capability that brings competitive advantage to organizations. Furthermore, we employ the technology–organization–environment (TOE) framework to identify and theorize paths via which factors influence the actual usage of BDA. Survey data collected from 161 U.S.-based companies show that: organizational-level BDA usage affects organizational value creation; the degree to which BDA usage influences such creation is moderated by environmental dynamism; technological factors directly influence organizational BDA usage; and organizational and environmental factors indirectly influence organizational BDA usage through top management support. Collectively, these findings provide a theory-based understanding of the impacts and antecedents of organizational BDA usage, while also providing guidance regarding what managers should expect from usage of this rapidly emerging technology.
Notes
1. For more details, see www.pwc.com/us/bigdata.
2. One exabyte is 1 billion gigabytes.
3. For example, whereas traditional business intelligence (BI) tools are database management systems (or DBMS)-based (i.e., to process structured data collected through legacy systems); BDA tools are web and mobile based (i.e., to process unstructured data collected from various sources). Furthermore, using traditional BI tools, data are moved into the software, whereas using BDA tools, data software is being moved to the data. As such, BDA creates new demand for workers, and education for new skills.
4. We have observed that, although a wide range of business analytics tools exist in the marketplace, the features of these BDA technologies can be categorized as data management (e.g., massively parallel-processing databases), open-source programming (e.g., Hadoop, MapReduce), statistical analysis (e.g., sentiment analysis, time-series analysis), visualization tools that help structure and connect data to uncover hidden patterns, anomalies, unknown correlations, and other actionable insights, and in-memory computing (IMC) (e.g., SAP’s HANA).
5. These practitioners include executives and editors at CSCMP, SCMR, a couple of other supply chain practice journals, and CSC partners in global regions.
Additional information
Notes on contributors
Daniel Q. Chen
Daniel Q. Chen (corresponding author; [email protected]) is an associate professor in the Department of Information Systems and Supply Chain Management in the Neeley School of Business at Texas Christian University. He received his Ph.D. in MIS from the University of Georgia and also holds an M.B.A. degree from Washington University in St. Louis. His research interests lie across the areas of strategic management, supply chain management, and technology management. His work has appeared or is forthcoming in Journal of Management Information Systems, MIS Quarterly, Decision Sciences, Decision Support Systems, Journal of Operations Management, Journal of Strategic Information Systems, MIS Quarterly Executive, and others.
David S. Preston
David S. Preston is an associate professor in the Department of Information Systems and Supply Chain Management in the Neeley School of Business at Texas Christian University. He received his Ph.D. in MIS from the University of Georgia and also holds an M.B.A. from the University of Georgia. His research interests include information systems (IS) in supply chain management, IS leadership, and IS strategic alignment. His work has been published or is forthcoming in a variety of journals, including Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Decision Sciences, Journal of Operations Management, IEEE Transactions on Engineering Management, Journal of Strategic Information Systems, MIS Quarterly Executive, and others.
Morgan Swink
Morgan Swink is the Eunice and James L. West Chaired Professor of Supply Chain Management in the Neeley School of Business at Texas Christian University. He also serves as the executive director of the Supply and Value Chain Center in the Neeley School. He is the former coeditor in chief of the Journal of Operations Management. He has coauthored two textbooks on supply chain operations, one managerial book on supply chain excellence, and more than 50 articles in academic and managerial journals.