CONFERENCE PROGRAM Conference Co-Chairs: USC Marshall
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2nd Annual AIM (Artificial Intelligence in Management)
Virtual Workshop and Conference
May 19-20, 2022
https://www.marshall.usc.edu/artificial-intelligence-management
CONFERENCE PROGRAM
Conference Co-Chairs:
Milan Miric, Florenta Teodoridis, Gerard J. Tellis
Marshall School of Business, University of Southern California
Los Angeles, CA
Sponsored By:
USC Marshall Center for Global Innovation (CGI)
USC Marshall Institute for Outlier Research in Business (iORB)
USC Marshall Institute for Digital Competition
Informs Society of Marketing Science (ISMS)
Marketing Science Institute (MSI)
CONFERENCE REGISTRATION
Register here: https://www.eventbrite.com/e/ai-marshall-2022-online-conference-registration-tickets-319043877827
Please note that we are charging a nominal registration fee for the conference:
• Academic Presenter: $50
• Academic Non -Presenter: $50
• Non-Academic (Non-Presenter): $100
• PhD Students: $25
We would like to ensure that presenters register for the conference before May 1, 2022.
If you have a scheduling conflict, please reach out to us at AIM@marshall.usc.edu and we will
accommodate you.PROGRAM OVERVIEW
All times in PST (Pacific Standard Time) zone
Thursday, May 19, 2022
AIM CONFERENCE – DAY 1 [Plenary 2:00pm to 5:10pm]
⇒ 2:00 to 2:10pm –Welcome Remarks from Gerrard Tellis (Conference Co-Chair)
⇒ 2:10 to 3:00pm – Fireside Chat
o Moderator: Sue Siegel (CEO/Board Director/VC, Tech., Healthcare & Business)
o Keynote Speaker: Yu-Ting Kuo (Tsing Hua University / MIT)
TRACK #T.1 TRACK #T.2
⇒ 3:00 to 4.00pm – T.1.A. AI & Consumer Behavior ⇒ 3:00 to 4.00pm - T.2.A. Recommender Systems
⇒ 4:10 to 5:10pm – T.1.B. ML Methods ⇒ 4:10 to 5:10pm - T.2.B. AI & Social Media
Friday, May 20, 2022
TRACK #F.1 TRACK #F.2
⇒ 9:00 to 10.00am - F.1.A. AI & Communities ⇒ 9:00 to 10.00am - F.2.A. AI & Decision Making
⇒ 10:10 to 11.10am - F.1.B. Health & Human Mind ⇒ 10:10 to 11.10am – F.2.B. AI & Retail
⇒ 11:20 to 12.20pm - F.1.C. Text Analytics ⇒ 11:20 to 12.20pm - F.2.C AI & E-Commerce
⇒ 12:30 to 1:30pm – F.1.D. Image Analytics ⇒ 12:30 to 1:30pm - F.2.D. AI & Human CapitalDETAILED PROGRAM –Thursday – TRACK 1
Track Chair: Florenta Teodoridis
SESSION T.1.A AI & CONSUMER BEHAVIOR (3:00 to 4:00PM)
1. Artificial Intelligence: Information Collection and Behavior-Based Pricing under Privacy Concerns. Krista
Li, Changying Li, Jianhu Zhang
2. Targeted Advertising as an Implicit Recommendation and Personal Data Opt-Out. Z. Eddie Ning,
Jiwoong Shin, Jungju Yu
3. Frugality versus Thrifty: The Gender Difference in Saving Behavior. Ying Bao, Alex Yao
4. Measuring Preferences for Hedonic Consumption. Anirban Mukherjee, Hannah Chang
SESSION T.1.B. MACHINE LEARNING METHODS (3:10 to 4:10PM)
1. Dynamic Marketing Policies: Constructing Markov States for Reinforcement Learning. Yuting Zhu,
Duncan Simester, Jonathan Parker, Antoinette Schoar
2. An Affine-Subspace Shrinkage Approach to Choice-Based Conjoint Estimation. Yupeng Chen, Qi
Yu, Raghuram Iyengar
3. Comparative Study of Structural Causal Model and Bayesian Network in Causal Inference on P2P
Lending Business. Wenwen, Ding
4. AI For Crowdsourcing? Integrated Theoretical Model for Idea Screening. Christian Pescher, Jason
Bell, Gerard J. Tellis, Johann FüllerDETAILED PROGRAM – Thursday – TRACK 2
Track Chair: Milan Miric
SESSION T.2.A Recommender Systems (3:00 to 4:00PM)
1. User Control and Acceptance of Recommender Systems. Emil Mirzayev, Zakaria Babutsidze.
2. Does Machine Learning Amplify Pricing Errors in Housing Market?: Economics of ML Feedback Loops.
Nikhil Malik.
3. Modeling the Role of Ranking Algorithms in Crowdfunding. Prasad Vana, Anja Lambrecht.
4. Finding the Sweet Spot: Ad Targeting on Streaming Media. Prashant Rajaram, Puneet Manchanda,
Eric Schwartz
SESSION T.2.B AI & Social Media (4:10 to 5:10PM)
1. The Impact of Interacting with Malicious Automated Twitter Bots on User Behavior and Generated
Content. Zakaria Babutsidze, Dorian Vincileoni.
2. Optimizing Selection of Key Opinion Leaders (KOLs) via Large-scale Network Analytics. Xiao Han,
Natasha Zhang Foutz, Ruiqing Ding, Weiguo Fan.
3. Winning the Attention Race: Analyzing Content Popularity and Topic Evolution on TikTok. Zijun
Tian, Ryan Dew, Raghuram Iyengar.DETAILED PROGRAM –Friday – TRACK 1
Track Chair: Milan Miric
SESSION F.1.A. AI IN UNDERREPRESENTED COMMUNITIES (9:00 to 10:00AM)
1. Development of AI Through Communities: Deep Learning Indaba, Masakhane and Khipu.ai. Milan
Miric, Leid Zejnilovic, Ulrich Paquet, Vukosi Marivate.
SESSION F.1.B HEALTH & HUMAN MIND (10:10 to 11:10AM)
1. The Impact of Loosening Firearm Usage Restrictions on Firearm Sales and Public Health. Jessica
Jumee Kim.
2. How Introduction of Video Technology Amplifies Inequalities in Accessing Healthcare Resources. Jiang
Qian, Jian Ni, Meng Zhu.
3. Voice Assistants in Different Usage Applications: Which Factors Matter in Simple and Complex
Applications? John Vara Prasad Ravi, Ramon Palau Saumell, Jan-Hinrich Meyer, Felix
Friedreich Thomas.
4. The Impact of Artificial Intelligence on Human Creativity: A Mixed-Method Approach Driven Conceptual
Framing. Margherita Pagani.
SESSION F.1.C. TEXT ANALYTICS (11:20 to 12:20PM)
1. Mapping Complex Technologies via Science-Technology Linkages; The Case of Neuroscience. Daniel
Hain, Roman Jurowetzki, Mariagrazia Squicciarini.
2. Politicizing Policy Response? Ramifications and Remedies. Chengyue Huang, Min Zhang, Natasha
Z. Foutz.
3. Toward a More Data-driven Product Design: An Integrated Machine Learning Approach. Zijing Hu,
Venkatesh Shankar.
SESSION F.1.D. IMAGE ANALYTICS (12:30 to 1:30PM)
1. The Effects of Underlying Product Features on Sales: A Machine Learning Approach to Analyze Images
and Reviews. Chi Zhang, Venkatesh Shankar.
2. Comparing Automated Image Classification Methods. Keno Tetzlaff, Jochen Hartmann, Mark
Heitmann.
3. Automatically Discovering Unknown Product Attributes Impacting Consumer Preferences. Ankit
Sisodia, Alex Burnap, Vineet Kumar.
4. Emoji as New Targeting language: A Multimodal Emoji Mining Approach. Xinying Hao, Vijay
Mahajan.DETAILED PROGRAM – Friday – TRACK 2
Track Chair: Florenta Teodoridis
SESSION F.2.A. AI & DECISION MAKING (9:00 to 10:00AM)
1. Consumers’ Responses to Algorithmic Biases: A Conceptual Framework, Propositions, and Implications
Raji Srinivasan
2. Bias and Noise in Hiring: Role of Evaluator Diversity, Interviewer Effects and Structured Evaluations
Ishita Chakraborty
3. Affectively Mistaken? How Human Augmentation and Information Transparency Offset Algorithmic
Failures in Emotion. Lauren Rhue
4. Algorithmic Fairness and Service Failures: Why Firms Should Want Algorithmic Accountability
Kalinda Ukanwa
SESSION F.2.B. AI & RETAIL (10:10 to 11:10AM)
1. The Impact of E-Scooters on Retail Visits: Empirical Analysis using Graph Neural Networks. Ruichun
Liu, Unnati, Narang
2. The Impact of Consumer Mobility and Store Flux on Consumer Response to Geo-fenced Promotional Ads.
A Deep Learning Approach. Sanjana Surange, Venky Shankar
3. The Effects of Store Closure on Omnichannel Shopping and Mobile App Usage. Taotao Ye, Venky,
Shankar
4. Buying and Payment Habits: Using Grocery Data to Predict Credit Card Payments. Jung Youn Lee,
Joonhyuk Yang, Eric Anderson
SESSION F.2.C. AI & E-COMMERCE (11:20 to 12:20PM)
1. Deep learning for simulation-based Bayesian inference of hidden parameters in online reputation systems.
Shrabastee Banerjee, Narendra Mukherjee, Amin Rahimian
2. Detecting Fake Review Buyers Using Network Structure: Direct Evidence from Amazon. Sherry He,
Brett Hollenbeck, Gijs Overgoor, Davide Proserpio, Ali Tosyani
3. Measurement and Mitigation of Disintermediation in Online Two-sided Platforms: Evidence from Airbnb
and Location Big Data. Jinan Lin, Tingting Nian, Natasha Zhang Foutz
4. How Retail Practices Co-evolve: Managerial Perspectives on AI Induced Practice Disruptions Francesca
Bonetti, Matteo Montecchi, Kirk Plangger, Hope Jensen SchauSESSION F.2.D. AI & HUMAN CAPITAL (12:30 to 1:30PM)
1. Falling Asleep at the Wheel: Human/AI Collaboration in a Field Experiment on HR Recruiters.
Fabrizio Dell'Acqua
2. AI-Driven Platform Ecosystems: How Emotions Affect Strategic Adoption Decisions. Alex Mari, Pinar
Ozcan
3. How to Make Artificial Intelligence Technologies a “Useful Servant” for Managers? Evidence from Mixed
Methods. Nan Jia, Xueming Luo, Zheng Fang, Bo Xu
4. Explainability’s Gain is Rationality’s Loss? - An Empirical Study. Charles Wan, Rodrigo Belo,
Leid ZejnilovićPLENARY SPEAKERS Sue Siegel CEO/Board Director/VC, Tech., Healthcare & Business Sue Siegel has been a CEO, VC, and a Board member for big and small, private and public, and non-profit organizations. Her current Board portfolio includes Illumina, Align, Nevro, the Bakar BioEnginuity Hub at UC Berkeley and KaiserFamily Foundation. She is Chairman of Board of MIT’s The Engine. Previously, Sue served as GE’s Chief Innovation Officer, CEO of GE Ventures& Licensing, and CEO of Healthymagination. Before GE, she was a VC General Partner at Mohr Davidow Ventures, leading investments in Life Sciences & Health. Sue has been recognized as Fortune’s “34 Leaders Who Are Changing Health Care,” as one of “The 100 Most Influential Women in Silicon Valley” and was awarded the “Lifetime Achievement Award” by Global Corporate Venture in 2020.
Yu-Ting Kuo (he/him/his), Adjunct Professor of Computer Science, National Tsing Hua University Executive Board Member, MIT Sloan School of Management Yu-Ting Kuo is currently an adjunct professor of computer science at National Tsing Hua University where he teaches artificial intelligence and machine learning. Kuo also lectures MBA students on mergers & acquisitions, corporate entrepreneurship, and leadership at the University of Oxford and MIT. He is a mentor and resident expert for the MIT delta v and Oxford OXFO Elevate accelerator programs. Kuo serves on the Alumni and Executive Boards of the MIT Sloan School of Management and has endowed a graduate fellowship at MIT to support underrepresented minority students in STEM management careers. He is on the advisory board of AI startups Aifi and KindWorks.ai. Kuo is also an independent director on the boards of Skymizer and the National Tsing Hua University North America Foundation. Kuo is a former Corporate Vice President at Microsoft, retiring in 2021 after more than 25 years. While at Microsoft, Kuo founded and managed Microsoft’s computer vision and cloud AI services product teams. He also led cross- company technical and strategic initiatives in the areas of context-optimized, deployment-aware machine learning and AI at scale. In 2021, Kuo was named by Business Insider as one of “the 11 power players leading artificial intelligence at Microsoft, helping guide CEO Satya Nadella’s grand pivot to AI.” He is also the recipient of the Inaugural Chinese Institute of Engineers/USA-SEA Asian American Luminary Award in Science and Engineering Innovation in 2018 for his pioneering work in cloud AI services. Kuo holds 11 US and international patents on Internet search and AI technologies. In 2018, Kuo established Microsoft’s Computer Vision Group, where he managed a global engineering and science organization that developed state-of- the-art technologies in the areas of computer vision and the metaverse. He helped found Microsoft’s AI R&D Centers in Belgrade, Cambridge (UK), Taipei, and Zürich where the company works on advanced computer vision and mixed reality capabilities. In 2016, Kuo led Microsoft's acquisition of London-based SwiftKey, the top AI-powered mobile keyboard, and served as its post-acquisition general manager. In 2015, Kuo founded and launched Microsoft’s Azure Cognitive Services, the first publicly available suite of AI services for developers, helping democratize AI technology for the industry and reaching millions of developer customers. In 2014, Kuo served as Technical Advisor to the Executive Vice President of Microsoft’s AI and Research Group, where he led technical strategy, planning, incubation, and strategic prototyping. Kuo started his career as a strategy consultant at McKinsey & Company. He joined Microsoft as a technical evangelist in 1996. Kuo attended National Tsing Hua University, Stanford University, MIT and the University of Oxford. He was named a distinguished alum of the College of Science at National Tsing Hua University in 2020. In 2021, Kuo was inducted into the Tsing Hua Entrepreneur Network as an overseas member. Kuo and his family live in the Seattle area and enjoy exploring unique corners of the world together.
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