Analytics and Data Science

Chapter 1. Exploring the Analytics Frontiers through Research and Pedagogy

Amit V. Deokar, Ashish Gupta, Lakshmi Iyer, and Mary C. Jones 

Chapter 2. Introduction: Research and Research-in-Progress

Anna Sidorova, Babita Gupta, and Barbara Dinter 

Chapter 3. Business Intelligence Capabilities

Thiagarajan Ramakrishnan, Jiban Khuntia, Terence Saldanha, and Abhishek Kathuria 

Chapter 4.Big Data Capabilities: An Organizational Information Processing Perspective

ÖyküIsik 
Chapter 5. Business Analytics Capabilities and Use: A Value Chain Perspective
Rudolph T. Bedeley, TorupallabGhoshal, Lakshmi S. Iyer, and JoyenduBhadury 

Chapter 6.Critical Value Factors in Business Intelligence Systems Implementations

Paul P. Dooley, Yair Levy, Raymond A. Hackney, and James L. Parrish 

Chapter 7. Business Intelligence Systems Use in Chinese Organizations

Yutong Song, David Arnott, and ShijiaGao 

Chapter 8. The Impact of Customer Reviews on Product Innovation: Empirical Evidence in Mobile Apps

Zhilei Qiao, G. Alan Wang, Mi Zhou, and Weiguo Fan 
Chapter 9. Whispering on Social Media
Juheng Zhang 

Chapter 10. Does Social Media Reflect Metropolitan Attractiveness? Behavioral Information from Twitter Activity in Urban Areas

Johannes Bendler, Tobias Brandt, and Dirk Neumann 

Chapter 11. The Competitive Landscape of Mobile Communications Industry in Canada – Predictive Analytic Modeling with Google Trends and Twitter

Michal Szczech and OzgurTuretken 

Chapter 12. Scale Development Using Twitter Data: Applying Contemporary Natural Language Processing Methods in IS Research

David Agogo and Traci J. Hess 

Chapter 13. Information Privacy on Online Social Networks: Illusion-in-Progress in the Age of Big Data?

Shwadhin Sharma and Babita Gupta

Chapter 14. Online Information Processing of Scent-Related Words and Implications for Decision Making

Meng-Hsien (Jenny) Lin, Samantha N.N. Cross, William J. Jones, and Terry L. Childers 

Chapter 15. Say It Right: IS Prototype to Enable Evidence-Based Communication Using Big Data

Simon Alfano 

Chapter 16. Introduction: Pedagogy in Analytics and Data Science

Nicholas Evangelopoulos, Joseph W. Clark, and Sule Balkan 

Chapter 17. Tools for Academic Business Intelligence & Analytics Teaching – Results of an Evaluation

Christoph Kollwitz, Barbara Dinter, and Robert Krawatzeck 

Chapter 18. Neural Net Tutorial

Brian R. Huguenard, and Deborah J. Ballou 

Chapter 19. An Examination of ERP Learning Outcomes: A Text Mining Approach

Mary M. Dunaway 

Chapter 20. Data Science for All: A University-Wide Course in Data Literacy

David Schuff