Track 03: Business Analytics and Data Science

ARFIMA for Feature-Based Time Series Classification

Rauzan Sumara, Warsaw University of Technology
Wladyslaw Homenda, Warsaw University of Technology
Witold Pedrycz, University of Alberta

Assigning the Optimal Treatment for Your Customers: A Counterfactual-based Uplift Modeling Approach

Baoqiang Zhan, The Hong Kong Polytechnic University
Eric W. T. Ngai, Hong Kong Polytechnic University
Chong Wu, Harbin Institute of Technology

Developing Data Analytics Capabilities Through Organizational Learning

Prashanth Madhala, Tampere University
Hongxiu Li, Tampere University
Nina Helander, Tampere University

Evaluating the Impact of Open Innovation Strategies on Organizational Financial Performance through Patent Mining

Deng-Neng Chen, National Pingtung University of Science and Technology
Tsai-Ju Yang, National Pingtung University of Science and Technology

Gauging Novelty in Crowdfunding Projects: A Theory-Driven Text Analysis Approach

Yan Lin, University of Macau
Waifong Boh, Nanyang Technological University

Predicting Brand Personality with User-generated Content: Deep Learning Methods

Chih-Ping Wei, National Taiwan University
Ren-Han Yang, National Taiwan University
Lei-Yao Hung, National Taiwan University

Research on the Construction of Product Quality Evaluation System Based on Online Text Mining and Fine-Grained Sentiment Analysis

Feng Wang, Kunming University of Science and Technology
Yuetong Chen, Kunming University of Science and Technology
Tiedan Wang, Kunming University of Science and Technology
Jiale Wang, Kunming University of Science and Technology
Yitong Liu, Kunming University of Science and Technology

Who Let the Dogs Out? How Ignoring Certain Customer Types is Improving Treatment Assignment Policies

Patrick Seidel, University of Cologne
Henri Beyer, University of Cologne
Jannik Rößler, University of Cologne
Detlef Schoder, University of Cologne