1st AIM (Artificial Intelligence in Management) Workshop and Conference

1st AIM Conference (Artificial Intelligence in Management):

Workshop Date: Friday March 13th 7:30 AM to 12 NN.
Conference Dates: Friday March 13th 12 NN to 7 PM and Saturday March 14th 7:30 AM to 7 PM.
Location: JKP (Popovich Hall) USC Marshall School of Business
Hotel: USC Hotel on Figueroa Street
Airports: LAX, SNA, ONT, BUR

Registration

Download a copy of the schedule

Workshop March 13

Day Time Presenter Title Affiliation of Sub Author
Friday 7:30 to 8:30 Breakfast    
  8:30 to 9:30 Seshadri Tirunilla Comparison of AI Methods: Past, Present, and Future  
  9:30 to 9:45 Break    
  9:45 to 10:45 Dinesh Puranam Sentiment and Attribute from Text  
  10:45 to 11:00 Break    
  11:00 to 12:00 Lan Luo Deep Learning of Images  

Conference March 13

Day Time Authors Title Affiliation of Sub Author
Friday 12:00 to 1:00 Lunch & Registration    
      Review of AI Tech Applications  
  1:00 to 1:40 Parris, Bowers, Wang Technology and Digital Revolutions in Marketing: Review and A Foundation for Future Research Oklahama
    Chen Artificial intelligence in Marketing: A comprehensive literature network review Texas A&M Kingsville
  1:40 to 1:55 Break    
    AI Discrimination & Adoption    
  1:55 to 3:20 Liu, Yildirim, Zhang AI Resistance and Price Discrimination Wharton
    Ukanwa, Rust AI Discrimination in Service USC
    Luo, Qin, Fang, Qu Impact of Artificial Intelligence Coach on Sales Agent Performance: A Field Experiment Temple
    Sood, Kumar, Gupta Fostering Adoption of AI Service Technologies Across Countries GSU, MICA
  3:20 to 3:35 Break    
      AI in Selection & Prediction  
  3:35 to 5:00 Vossler, Chi, Lv FLINK: Feature Selection in Causal Inference with Knockoffs USC
    Lu, Fan, Lv, Noble DeepPINK: Reproducible Feature Selection in Deep Neural Networks USC
    Lee, Johnson, Tellis Can AI OutPredict Surveys: Micro-Geo Predictions of US Presidential Election Miami
    Miller AI for Capital Project Management USC
  5:00 to 7:00 Reception    

Conference March 14

Saturday 7:30 to 8:30 Breakfast & Registration    
      Deep Learning Applications  
  8:30 to 9:45 Johnson, Ogihara, Ren, Lee A Deep Neural Network System for the Analysis and Prediction of Ad Effectiveness Miami
    Kim, Kim, Joo, Che A Hybrid Approach to Counterfactual Demand Predictions Using Deep Learning UC Riverside
    Rubera, Grossetti, Cillo A better picture: how computer vision can help market segmentation Bocconi
    Rubera, Grossetti, Cillo A better picture: how computer vision can help market segmentation Bocconi
    Zhang, Luo Can User-Posted Photos Serve as a Leading Indicator of Restaurant Survival? Evidence from Yelp USC
  9:45 to 10:00 Break    
      AI Applications  
  10:00 to 11:40 Munoko, Cho, Brown-Liburd Reading between the lines: An ensemble machine learning approach to fraud detection Rutgers
    Bowers, Parris Delivering on the Promises of AI Driven Personalization Oklahama
    Park, Puranam Valence and certainty on perceived helpfulness: Interpretable deep learning on consumer reviews USC
    Alantari, Deng, Currim, Singh Comparison of Models for Automated Text-based Sentiment Analysis of Online Consumer Reviews UC Ivine
    Bellet, Borah, Dubois When Veblen Meets Big Data: A Search-Based Index of Brand Conspicuous Value Insead
  11:40 to 12:00 Break    
      AI in Innovation  
  12:00 to 1:15 Miric, Jia, Huang Comparing Machine Learning and Keyword Methods for Classification in Management Research: Patents USC
    Chen, Liu, Proserpio, Troncoso Product2Vec: Understanding Product-Level Competition Using Representation Learning USC
    Novak, Hoffman Reifying Space of Personal Automation Practices: An Empirical Approach Grounded in Assemblage Theory George Washington
    Teodoridis, Lu, Furman Measuring Changes in the Direction of Innovation: A Machine Learning Approach USC
  1:15 to 2:15 Lunch    
      AI in Creativity  
  2:15 to 3:30 Hong, Wei, Tellis Does the Similarity Pattern among Crowdfunding Projects Help Design a Winning Project USC
    Bell, Pescher, Tellis, Füller Can AI Do Ideation? Testing Alternate Algorithms for Idea Screening in Crowdsourcing Contests Oxford
    Chaudhry, Wang How trailer design elements predict box office performance Temple
    Burnap, Hauser Identifying “Design Gaps” in Market: Demand Models over Data-Driven Feasible Design Spaces MIT
  3:30 to 3:45 Break    
      AI Adoption  
  3:45 to 4:45 Jia, Luo, Fang, Xu Can AI Substitute or Complement Managers? Outcomes for Transformational and Transactional Managers USC
    Clegg, Hofstetter, de Bellis, Schmitt Perceptions of AI: How Disclosing Algorithm Type Can Shape Users’ Adoption of New Technologies Lucerne
    Blanas Distinct Effects of Information and Communication Technologies on the Age-Skill Composition of Labour Bank of Belgium
  4:45 to 7:00 Reception