This track is dedicated to research that applies and/or develops novel data science and analytics theories, algorithms, methods, and frameworks to address challenging and practical problems that benefit business and society at large. Domains may include small businesses, healthcare, judicial systems, social media and energy, and applications such as fraud detection, social network services, human resource analytics, privacy, recommendation systems, etc. Contributions may be motivated by the shortcomings of state-of-the art approaches in addressing practical challenges, or may apply novel data science tools to existing problems. This track is open to all types of research, including conceptual, theoretical, analytical, and/or empirical.

Track Co-Chairs
Gene Moo Lee, Ph.D., University of British Columbia
Ali Sunyaev, Ph.D., Karlsruhe Institute of Technology
Jing Wang, Ph.D., Hong Kong University of Science and Technology

Schedule
2022
Monday, December 12th
12:00 AM

AI Explainability: Embedding Conceptual Models

Wolfgang Maass, Saarland University
Arturo Castellanos, William & Mary
Monica Tremblay, The College of William and Mary
Roman Lukyanenko, HEC Montreal
Veda C. Storey, Georgia State University

12:00 AM

Big Data and Data Analytics for Enhanced Decision-Making in the Public Sector

Olga Vasilyeva, Australian National University
Alex Richardson, The Australian National University

12:00 AM

Career Path Clustering via Sequential Job Embedding and Mixture Markov Models

Hao Zhong, ESCP Business School
Chuanren Liu, University of Tennessee

12:00 AM

Data Analytics for Effective Decision-Making in Crises - Identifying Relevant Data Analytics Competencies for Automotive Procurement Departments

Sven Klee, Universität Kassel
Andreas Janson, Institute of Information Management

12:00 AM

Data Analytics for Uncovering Fraudulent Behaviour in Elite Sports

Maxx Richard Rahman, Saarland University
Thomas Piper, German Sport University Cologne (DSHS)
Hans Geyer, German Sport University Cologne (DSHS)
Tristan Equey, World Anti-Doping Agency (WADA)
Norbert Baume, World Anti-Doping Agency (WADA)
Reid Aikin, World Anti-Doping Agency (WADA)
Wolfgang Maass, Saarland University

12:00 AM

Driving Big Data – Integration and Synchronization of Data Sources for Artificial Intelligence Applications with the Example of Truck Driver Work Stress and Strain Analysis

Matthias Klumpp, University of Göttingen
Benedikt Severin, University of Duisburg-Essen
Henrik Lechte, University of Goettingen
Jannes Heinrich Diedrich Menck, University of Goettingen
Maria Keil, University Goettingen
Sarah M. Straub, University of Hohenheim
Caroline Ruiner, University of Hohenheim
Viola Milke, University of Bremen
Vera Hagemann, University of Bremen
Marc Hesenius, University of Duisburg-Essen

12:00 AM

Enhancing Recommendation Interpretability with Tags: A Neural Variational Model

Shen Liu, Tsinghua University
Shangkun Che, Tsinghua University
Hongyan Liu, Tsinghua University

12:00 AM

Firm Profiling and Competition Assessment via Heterogeneous Occupation Network

Hao Zhong, ESCP Business School
Chuanren Liu, University of Tennessee

12:00 AM

Insights from Niche Markets: Explainable and Predictive Values of Consumption Tendency on Credit Risks

Wenwen Li, Fudan University
Yue Wu, Fudan University
Yingjie Zhang, Peking University
Tian Lu, Arizona State University
Yiheng Sun, Tencent Weixin Group
Xuehao Zheng, Tencent Weixin Group

12:00 AM

Real-Time Purchase Prediction Using Retail Video Analytics

Anindya Ghose, New York University
Beibei Li, Carnegie Mellon University
Rubing Li, New York University
Kaiquan Xu, Nanjing University

12:00 AM

Revival of the Cover Letter? Experimental Evidence on the Performance of AI-driven Personality Assessments

Christoph Kecht, Technical University of Munich
Michael Kurschilgen, Technical University of Munich
Magnus Strobel, Technical University of Munich

12:00 AM

The Best of Two Worlds – Using Recent Advances from Uplift Modeling and Heterogeneous Treatment Effects to Optimize Targeting Policies

Jannik Rößler, University of Cologne
Richard Guse, Karlsruhe Institute of Technology
Detlef Schoder, University of Cologne

12:00 AM

To Reduce Bias, You Must Identify It First! Towards Automated Gender Bias Detection

Lorena Göritz, German Research Center for Artificial Intelligence
Daniel Stattkus, German Research Center for Artificial Intelligence
Jan Heinrich Beinke, German Research Center for Artificial Intelligence
Oliver Thomas, German Research Center for Artificial Intelligence

12:00 AM

Unleashing the Potential of Argument Mining for IS Research: A Systematic Review and Research Agenda

Pablo Weingart, Universität Kassel
Thiemo Wambsganss, EPFL
Matthias Söllner, Universität Kassel

12:00 AM

Visual Communication and Fashion Popularity Contagion in Social Networks

Xiang Li, City University of Hong Kong
Yunhui Wang, City University of Hong Kong
Liu Junming, City University of Hong Kong
Hui Xiong, Rutgers University

12:00 AM