Business analytics

Abstract: Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.

Abstract: In business-to-business settings, dyadic relationships between firms are of paramount interest. Recent developments in business practice strongly suggest that to understand these business relationships, greater attention must be directed to the embedded context within which dyadic business relationships take place. The authors provide a means for understanding the connectedness of these relationships. They then conduct a substantive validity assessment to furnish some empirical support that the constructs they propose are sufficiently well delineated and to generate some suggested measures for them. They conclude with a prospectus for research on business relationships within business networks.

Abstract: Managers increasingly must make decisions based on almost unlimited information. How can they navigate and organize this vast amount of data? Essentials of Business Research Methods provides research techniques for people who aren't data analysts. The authors offer a straightforward, hands-on approach to the vital managerial process of gathering and using data to make clear business decisions. They include such critical topics as the increasing role of online research, ethical issues, data mining, customer relationship management, and how to conduct information-gathering activities more effectively in a rapidly changing business environment. This is the only such book that includes a chapter on qualitative data analysis, and the coverage of quantitative data analysis is more extensive and much easier to understand than in other works. The book features a realistic continuing case throughout the text that enables students to see how business research information is used in the real world. It includes applied research examples in all chapters, as well as Ethical Dilemma mini - cases, and interactive Internet applications and exercises.

Abstract: You have more information at hand about your business environment than ever before. But are you using it to "out-think" your rivals? If not, you may be missing out on a potent competitive tool. In "Competing on Analytics: The New Science of Winning" , Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon: Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples - from organizations as diverse as Amazon, Barclay's, Capital One, Harrah's, Procter & Gamble, Wachovia, and the Boston Red Sox - illuminate how to leverage the power of analytics.