Deokar A.V., Gupta A., Iyer L.S., Jones M.C. (eds.) Analytics and Data Science: Advances in Research and Pedagogy

Springer, 2018. — 299 p. — (Annals of Information Systems 21). — ISBN: 9783319580968, 9783319580975.Amit V. Deokar, Ashish Gupta, Lakshmi S. Iyer, Mary C. Jones (eds.)This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015.
Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.Amit V. Deokar, Ashish Gupta, Lakshmi S. Iyer, and Mary C. Jones
Exploring the Analytics Frontiers Through Research and Pedagogy
Anna Sidorova, Babita Gupta, and Barbara Dinter
Introduction: Research and Research-in-Progress
Thiagarajan Ramakrishnan, Jiban Khuntia, Abhishek Kathuria, and Terence J.V. Saldanha
Business Intelligence Capabilities
Öykü Isik
Big Data Capabilities: An Organizational Information Processing Perspective
Torupallab Ghoshal, Rudolph T. Bedeley, Lakshmi S. Iyer, and Joyendu Bhadury
Business Analytics Capabilities and Use: A Value Chain Perspective
Paul P. Dooley, Yair Levy, Raymond A. Hackney, and James L. Parrish
Critical Value Factors in Business Intelligence Systems Implementations
Yutong Song, David Arnott, and Shijia Gao
Business Intelligence System Use in Chinese Organizations
Zhilei Qiao, G. Alan Wang, Mi Zhou, and Weiguo Fan
The Impact of Customer Reviews on Product Innovation: Empirical Evidence in Mobile Apps
Juheng Zhang
Whispering on Social Media
Johannes Bendler, Tobias Brandt, and Dirk Neumann
Does Social Media Reflect Metropolitan Attractiveness? Behavioral Information from Twitter Activity in Urban Areas
Michal Szczech and Ozgur Turetken
The Competitive Landscape of Mobile Communications Industry in Canada: Predictive Analytic Modeling with Google Trends and Twitter
David Agogo and Traci J. Hess
Scale Development Using Twitter Data: Applying Contemporary Natural Language Processing Methods in IS Research
Shwadhin Sharma and Babita Gupta
Information Privacy on Online Social Networks: Illusion-in-Progress in the Age of Big Data?
Meng-Hsien (Jenny) Lin, Samantha N.N. Cross, William Jones, and Terry L. Childers
Online Information Processing of Scent-Related Words and Implications for Decision Making
Simon Alfano, Nicolas Pröllochs, Stefan Feuerriegel, and Dirk Neumann
Say It Right: IS Prototype to Enable Evidence-Based Communication Using Big Data
Nicholas Evangelopoulos, Joseph W. Clark, and Sule Balkan
Introduction: Pedagogy in Analytics and Data Science
Christoph Kollwitz, Barbara Dinter, and Robert Krawatzeck
Tools for Academic Business Intelligence and Analytics Teaching: Results of an Evaluation
Brian R. Huguenard and Deborah J. Ballou
Neural Net Tutorial
Mary M. Dunaway
An Examination of ERP Learning Outcomes: A Text Mining Approach
David Schuff
Data Science for All: A University-Wide Course in Data Literacy