2019 Conference on Artificial Intelligence, Machine Learning, and Business Analytics
DECEMBER 12-13, 2019
1801 Liacouras Walk
Alter Hall 7th Floor, MBA Commons
Fox School of Business
Temple University
Philadelphia, Pennsylvania
Co-organized by
Stern School of Business, New York University
Heinz College, Carnegie Mellon University
Fox School of Business, Temple University
Over five billion people worldwide actively engage with AI, bots, machine-to-machine connected solutions, wearables, Internet-of-Things, 5G, AR/VR technologies, Fintech, Mooc, and blockchain. This conference will explore how digital, social, and mobile technologies affect business models, customer behavior, public policy, and social changes at large. Exemplar topics include:
AI automation/ Robotics AI adoption and user behavior/AI chatbot voice-mining for promo and recommendations/ Bot trading and AI advisor in financial markets/AI for ad creatives and publishers/ AI applications in worker training, hiring, and supervising/ ML applications in fintech, pharma, and e-commerce/ Privacy and new technologies/ Data breach and security/ Blockchain applications/ Future of work and unemployment/ Big data IoT, 5G, AR, and VR applications/ Public policy and regulation of AI technologies/ AI algorithm bias, interpretable ML/ Machine learning for causal inference/ ML and deep learning for statistics methods/ Machine learning for empirical IO/ Deep reinforcement learning for microeconomics theory / Healthcare applications of ML/ Multi-armed bandits for online advertising and pricing/ Contextual MAB for personalized dynamic recommendations/ MOOC education online with ML and AI NLP with social media text data for targeting/ ML for images, voice, and video data B2B markets with ML and AI
Confirmed Keynote Speakers: Ravi Bapna (Minnesota), Ryan Dew (Wharton), Anindya Ghose (NYU), Szu-Chi Huang (Stanford), Nan Jia (USC), Dokyun Lee (CMU), Beibei Li (CMU), Xiao Liu (NYU), Michael Luca (Harvard), Xueming Luo (Temple), Puneet Manchanda (Michigan), Harikesh Nair (Stanford), Oded Netzer (Columbia), Param Singh (CMU), Michael Smith (CMU), K. Sudhir (Yale), Roland Rust (Maryland), Prasanna Tambe (Wharton), Gerry Tellis (USC), Artem Timoshenko (Kellogg)
Submission logistics: Submit either a 3-page abstract, full paper, or 10 PPT slides to vAIML2019Conf@gmail.com and cc the conference co-chairs: Xueming.Luo@temple.edu, BeibeiLi@andrew.cmu.edu, AGhose@stern.nyu.edu.
Submission deadline: October 7, 2019. Acceptance notification date: October 20, 2019 (Acceptance of submission requires one co-author to register and present at the conference)
This annual conference was hosted at Chicago Booth in 2014, NYU Stern in 2015 and 2017, Stanford GSB in 2016, and CMU Tepper in 2018. It has attracted a vibrant group of professors, industry people, and PhD students (each year max 150 people) working on cutting-edge ML AI models and data in inter-disciplinary fields. This conference serves as an intellectual bridge between computer science, economics, statistics, marketing, management, finance, strategy, IS, healthcare, education, public policy, and others.
Conference Schedule
Alter Hall 7th Floor, MBA Commons
8:00 AM – 8:50 AM: Registration and Breakfast
8:50 AM – 9:00 AM: Welcome by Dean Anderson and Conference Chairs
9:00 AM – 10:30 AM: Plenary Session 1, Chair: Sudipta Basu (Temple University)
- Anindya Ghose (NYU): Using AI and Blockchain to Monetize the Mobile Economy
- Roland Rust (Maryland): The Feeling Economy: Managing in the Next Generation of AI
- Mike Smith (CMU): AI, Machine Learning, and the Fight Against Online Sex Trafficking
- Puneet Manchanda (Michigan): Finding the Sweet Spot: Ad Scheduling on Streaming Media
10:30 AM – 11:00 AM: Coffee Break
1:00 AM – 12:30 PM: Concurrent Sessions 1
| Session | 1A | 1B | 1C |
|---|---|---|---|
| Theme | Deep Learning and AI Bots | AI, Privacy and Society | AI, B2B and Machine Learning |
| Location | Room 745 | Room 746 | Room 603 |
| Moderator | Wen Wang (Carnegie Mellon University) | Manav Raj (New York University) | Najlae Zhani (International University of Rabat) |
| Papers | A Deep Learning Approach to Industry Classification
Xiao Fang (University of Delaware), Xiaohang Zhao (University of Delaware), Jing He (University of Delaware), Olivia Sheng (The University of Utah) |
Privacy & market concentration: Intended & unintended consequences of the GDPR Garrett A. Johnson (Boston University), Scott K. Shriver (University of Colorado Boulder) |
Truth & Justice: Extending Traditional Research Evaluation to an AI World
Rich Timpone (Ipsos Global Science Org), Nicole M. Alexander (Ipsos Innovation) |
| Early Predictions for Medical Crowdfunding: A Deep Learning Approach Using Diverse Inputs
Tong Wang (University of Iowa), Fujie Jin (Indiana University), Yuan Cheng (Tsinghua University), Yu Jeffrey Hu (Georgia Institute of Technology) |
AI Coach for Salesforce Agents
Marco Qin (Temple University), Z. Fang (Sichuan University) |
From Darknets to Light
Prasad Vana (Dartmouth College), Pradeep Pachigolla (Dartmouth College) |
|
| Relational AI Bots in Healthcare
Wenyu Jiao (Temple University), Y. Huang (Zhongshan University), H. Wang (Zhongshan University) |
How Social Networks Constrain Consumer Mobility Behavior
Jayson S. Jia (The University of Hong Kong), Yiwei Li (Lingnan University), Yijian Ning (Southwest Jiaotong University), Xianchi Dai (The Chinese University of Hong Kong), Nicholas A. Christakis (Yale University), Jianmin Jia (The Chinese University of Hong Kong) |
Emoji as a New Targeting Language: A Multimodal Emoji Mining Approach
Xinying Hao (University of Arizona), Vijay Mahjan (University of Texas-Austin) |
|
| Artificial Intelligence (AI) Agents for Personalized Promotions
Wen Wang (Carnegie Mellon University), Beibei Li (Carnegie Mellon University), Xueming Luo (Temple University) |
Artificial Intelligence: Labor, Skills, and Polarization
Edward Felten (Princeton University), Manav Raj (New York University), Robert Seamans (New York University) |
Decision-making using artificial intelligence and machine learning in B2B markets
Najlae Zhani (International University of Rabat) |
12:30 PM – 1:30 PM: Lunch
1:30 PM – 3:00 PM: Plenary Session 2, Chair: Yang Wang (Temple University)
- K: Sudhir (Yale University): Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Attribute Self-Selection
- Ravi Bapna (Minnesota): Next-Gen Referral Marketing: Experimental Evidence from the Field
- Harikesh Nair (Stanford): Experimentation and Causality in Modern Digital Advertising
- Xueming Luo (Temple): AI and the Future of Work
3:00 PM – 3:30 PM: Coffee Break
3:30 PM – 5:10 PM: Concurrent Sessions 2
| Session | 2A | 2B | 2C |
|---|---|---|---|
| Theme | Images, Search and NLP | Text Mining, Demand Forecasting | AI-Human Hybrids, Sales Performance |
| Location | Room 745 | Room 746 | Room 603 |
| Moderator | Siham El Kihal (Frankfurt School of Finance & Management) | Dong Soo Kim (Ohio State University) | Tarun Kushwaha (University of North Carolina at Chapel Hill) |
| Papers | Emotional Empathy and Engagement in Live Streaming
Yan Lin (Shenzhen University), Dai Yao (National University of Singapore), Xingyu Chen (Shenzhen University) |
Predicting Taxi and Uber Demand in Cities: Approaching the Limit of Predictability
Kai Zhao (Georgia State University), Denis Khryashchev (Graduate Center, City University of New York), Huy Vo (City College of New York) |
AI for Sales Call Automation
Jack Tong (Temple University), Z. Qu (Fudan University), and Z. Fang (Sichuan University) |
| Effects of Platform Free Promotions on Non-Redeemers
Lin Boldt (UCF), X. Wang (Zhejiang University) |
Disclosure of Pricing Information in Earnings Calls: A Text Mining Approach
Alexander Edeling (University of Cologne), Alexander Himme (Kühne Logistics University), Shuba Srinivasan (Boston University) |
All that Automation is not Perceived Gold: Exploring Consumer Responses to AI-designed Luxury Products
Lidan Xu (Oklahoma State University), Ravi Mehta (University of Illinois at Urbana Champaign) |
|
| The Value of Plant Images in Digital Property Profiles
Yuqian Chang (Temple University), Ning Ye (Stockton University), Maureen Morrin (Rutgers University-Camden), Rong Huang (Saint Anselm College), and Nathan Fong (Rutgers University-Camden) |
L1-Norm Subspace Estimation for Customer Contact Center Scheduling with Demand Spikes
J. Paul Brooks (Virginia Commonwealth University), José H. Dulá (University of Alabama) |
Effects of AI-Human Supervisor Assemblages on Worker Productivity
Narayan Ramasubbu (University of Pittsburgh), He Peng (Fudan University) |
|
| Impact of Free Shipping Threshold on PC and Mobile Channels: Evidence from an Online Retailer
Fujie Jin (Indiana University), Fei Gao (Indiana University), Jianbin Li (Huazhong University of Science and Technology) |
Telling a Story about the Story: How Trailer Design Elements Predicts Box Office Performance
Alex Chaudhry (Texas Tech University), Yang Wang (Temple University) |
The Impact of a Mobile Payment App: A Natural Experiment
Steven Lu (The University of Sydney) |
|
| A Natural Language Processing Approach to Predicting the Persuasiveness of Marketing Communications
A. Selin Atalay (Frankfurt School of Finance & Management), Siham El Kihal (Frankfurt School of Finance & Management), Florian Ellsaesser (Frankfurt School of Finance & Management) |
A Flexible Method for Demand Forecasting with Structural Decomposition
Dong Soo Kim (Ohio State University), Chul Kim (Baruch College, CUNY), Mingyu (Max) Joo (University of California Riverside) |
Humans vs. Machines: Value of Private Information in Assortment Automation
Tarun Kushwaha (University of North Carolina at Chapel Hill), Saravanan Kesavan (University of North Carolina at Chapel Hill) |
5.30 PM – 8.30 PM: Conference Dinner with drinks: Alter Hall 7th floor, MBA Commons (Room 702)
6.30 PM – 7.30 PM: Rising Stars in AI/ML Research Special Panel: Alter Hall 7th floor, MBA Commons (Room 702)
- Chair: Beibei Li (Carnegie Mellon University)
- Artem Timoshenko (Kellogg): Cross-Category Product Choice: A Scalable Deep- Learning Model
- Ryan Dew (Wharton): Letting Logos Speak: Leveraging Multiview Representation Learning for Data-Driven Logo Design
- Xiao Liu (NYU): Sequential Coupon Targeting in LiveStream Shopping with Deep Reinforcement Learning
- Tianshu Sun (USC): The Value of Personal Data in Internet Commerce: A High-stake Field Experiment on Data Regulation Policy
Alter Hall 7th Floor, MBA Commons
8:00 AM – 9:00 AM: Breakfast
9:00 AM – 10:30 AM: Plenary Session 3, Chair: Ed Rosenthal (Temple University)
- Oded Netzer (Columbia): The Power of Brand Selfies
- Szu-chi Huang (Stanford): Living among Robots: Consumer Health, Prosocial Contribution and Dating
- Dokyun Lee (CMU): Interpretable Machine Learning: The Problem, Progress and Potential for Marketing Research
- Nan Jia (USC)” Management by AI-Bot: A Field Experiment of Algorithm Coaching on Employee Performance
10:30 AM – 11:00 AM: Coffee Break
11:00 AM – 12:40 PM: Concurrent Sessions 3
| Session | 3A | 3B | 3C |
|---|---|---|---|
| Theme | AI Bot and Voice AI Field Experiments | Sharing Economy, Online Reviews and Social Media | Optimization, Algorithm Disclosure |
| Location | Room 745 | Room 746 | Room 603 |
| Moderator | Nan Jia (University of Southern California) | Siddhartha Sharma (Carnegie Mellon University) | Liu Liu (University of Colorado Boulder) |
| Papers | The Effect of Voice AI on Consumer Purchase and Search Behavior
Chenshuo Sun (New York University), Zijun Shi (HKUST), Xiao Liu (New York University), Anindya Ghose (New York University) |
How Incumbents Beat Disruptors? Evidence from Hotels’ Responses to Home-sharing Rivals Leveraging Causal Inference and Machine Learning
Wei Chen (University of Arizona), Karen Xie (University of Denver), Jianwei Liu (Harbin Institute of Technology), Yong Liu (University of Arizona) |
Optimality-based Clustering: An Inverse Optimization Approach
Zahed Shahmoradi (University of Houston), Taewoo Lee (University of Houston) |
| Adoption of Artificial Intelligence in the Presence of Human Intelligence: A Field Study
Xue (Jane) Tan (Indiana University), Mochen Yang (University of Minnesota), Gang Wang (ApplySquare Inc.) |
The Financial Consequences of Customer Satisfaction: Evidence from Yelp Ratings and SBA Loans
Ruidi Huang (Southern Methodist University) |
What Can We Learn from Online Movie Reviews? Capturing Viewers’ Movie Experience through Machine Learning
Steven Lu (The University of Sydney), Madhumita Nanda (The University of Sydney), Junbin Gao (The University of Sydney), Ting Guo (The University of Sydney) |
|
| Estimating the Economic Impact of ‘Humanizing’ Customer Service Chatbots
Scott Schanke (University of Minnesota), Gordon Burtch (University of Minnesota), Gautam Ray (University of Minnesota) |
Do Review Manipulations Harm or Benefit Online Platforms? An Economining Approach
Sang-Pil Han (Arizona State University), Sanghak Lee (Arizona State University), Donghyuk Shin (Arizona State University), Seok Kee Lee (Hansung University) |
Algorithm-Human Assemblage Recommendation Disclosures
Han Chen (Temple University), H Xue (USTC), Y Li (USTC) |
|
| An Interpretable Approach to Predicting Consumer Activity with Omnichannel Data
Chenshuo Sun (New York University), Anindya Ghose (New York University), Xueming Luo (Temple University) |
Augmenting Human Perceptual and Reasoning Capability with Big Data Analytics: From Health Care to Education
Lujie Chen (Carnegie Mellon University) |
Capturing Behavior Dynamics of Video Game Players: A Recurrent Marked Point Process Approach
Zisu Wang (University of Arizona), Junming Yin (University of Arizona), Tianyu Gu (University of Arizona), Yong Liu (University of Arizona) |
|
| Can Artificial Intelligence Technologies Complement or Substitute Human Managers?
Nan Jia (University of Southern California), Z. Fang (Sichuan University), Bo Xu (Fudan University) |
I Hear You: Does Quality Improve with Customer Voice?
Uttara Ananthakrishnan (University of Washington), Davide Proserpio (University of Southern California), Siddhartha Sharma (Carnegie Mellon University) |
Capturing Heterogeneity among Consumers with Multi-taste Preference
Liu Liu (University of Colorado Boulder), Daria Dzyabura (New Economics School) |
12:40 PM – 1:40 PM: Lunch
1:40 PM – 3:10 PM: Plenary Session 4, Chair: Marco Qin (Temple University)
- Param Singh (CMU): AI Algorithms and the Rising Concerns of Racial Bias
- Prasanna Tambe (Wharton): IT, AI, and Intangible Capital
- Gerry Tellis (USC): Is Creativity Purely Random: Alternative AI Algorithms for Predicting Success in Crowdsourcing Contents
- Mike Luca (Harvard): Discrimination in Online Markets
3:10 PM: Closing Remarks
Conference adjourns