Building a Better World through Information Systems

Decision Analytics, Big Data, and Visualisation

Advances in modern technology have allowed businesses, governments and researchers to collect and store huge amounts of data. Big Data repositories, characterized by high magnitudes of data volume, velocity and variety, present many critical challenges for analysis. These include methods that can scale (volume), results that can be delivered in real-time (velocity), and insights that can be derived by combining different data sources and types such as structured and unstructured data (variety).

For this track, we invite paper submissions that address novel data analysis methods, concepts or implementations that rely on principles and techniques in data mining, statistics, econometrics, psychometrics, computer science, and other computational or quantitative fields, which tackle one or more of the above challenges. We welcome new exploratory methods and visualization approaches for discovering patterns in large and dynamic data sources. We also welcome causal-explanatory modeling approaches that can lead to meaningful theory development and rigorous causal derivations in light of big data challenges and opportunities. New predictive and prescriptive (optimization-based) analytic models, methods or approaches are also highly relevant for this track. Applications or implementations of the aforementioned data analytic methods or approaches could be demonstrated in various contexts such as web intelligence and
analytics, healthcare analytics, new performance metrics specific to Big Data era, social media analytics, etc. We are less interested in existing methods applied to existing problems but with large data sets, conceptual papers on the role of big data, or anecdotes of how big data alone provided managerial insights. Above all, we encourage new research that spans boundaries across disciplines, data sources and methods to address important topics in information systems and directly relate to decision
making at the individual, group or organizational level.

Topics of interest include, but are not limited to:

·        Capturing and sharing knowledge in social networks

·        Data, text, and web mining for business intelligence

·        Web intelligence and web analytics

·        Data integration from multiple sources

·        Visualization and human-computer interface research for business
intelligence

·        Real-time data analysis for decision making

·        Interactive visualization and decision making

·        Statistical and econometric methods that scale to Big Data

·        Recommender systems

·        Large-sample experiments

·        Contextual advertising and data-driven marketing

·        Dynamic pricing and revenue optimization

·        Geospatial data analytics for location-based services

Track Chairs

Associate Editors