Analytics and Data Science

Chapter 1. Exploring the Analytics Frontiers through Research and PedagogyAmit V. Deokar, Ashish Gupta, Lakshmi Iyer, and Mary C. Jones Chapter 2. Introduction: Research and Research-in-ProgressAnna Sidorova, Babita Gupta, and Barbara Dinter Chapter 3. Business Intelligence CapabilitiesThiagarajan Ramakrishnan, Jiban Khuntia, Terence Saldanha, and Abhishek Kathuria Chapter 4.Big Data Capabilities: An Organizational Information Processing PerspectiveÖyküIsik Chapter 5. Business Analytics Capabilities and Use: A Value Chain PerspectiveRudolph T. Bedeley, TorupallabGhoshal, Lakshmi S. Iyer, and JoyenduBhadury Chapter 6.Critical Value Factors in Business Intelligence Systems ImplementationsPaul P. Dooley, Yair Levy, Raymond A. Hackney, and James L. Parrish Chapter 7. Business Intelligence Systems Use in Chinese OrganizationsYutong Song, David Arnott, and ShijiaGao Chapter 8. The Impact of Customer Reviews on Product Innovation: Empirical Evidence in Mobile AppsZhilei Qiao, G. Alan Wang, Mi Zhou, and Weiguo Fan Chapter 9. Whispering on Social MediaJuheng Zhang Chapter 10. Does Social Media Reflect Metropolitan Attractiveness? Behavioral Information from Twitter Activity in Urban AreasJohannes Bendler, Tobias Brandt, and Dirk Neumann Chapter 11. The Competitive Landscape of Mobile Communications Industry in Canada - Predictive Analytic Modeling with Google Trends and TwitterMichal Szczech and OzgurTuretken Chapter 12. Scale Development Using Twitter Data: Applying Contemporary Natural Language Processing Methods in IS ResearchDavid 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 GuptaChapter 14. Online Information Processing of Scent-Related Words and Implications for Decision MakingMeng-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 DataSimon Alfano Chapter 16. Introduction: Pedagogy in Analytics and Data ScienceNicholas Evangelopoulos, Joseph W. Clark, and Sule Balkan Chapter 17. Tools for Academic Business Intelligence & Analytics Teaching - Results of an EvaluationChristoph Kollwitz, Barbara Dinter, and Robert Krawatzeck Chapter 18. Neural Net TutorialBrian R. Huguenard, and Deborah J. Ballou Chapter 19. An Examination of ERP Learning Outcomes: A Text Mining ApproachMary M. Dunaway Chapter 20. Data Science for All: A University-Wide Course in Data Literacy David Schuff