Hongye Sun

Research Interests

Natural Experiments via Econometric Methods, Lab and Field Experiments, Natural Language Processing, Deep Learning Applications in Marketing, Potential of Large Language Models

Papers Prepared for Submission

• From Algorithms to Sales: A Field Study on the Performance of AI-Generated Product Descriptions
  with Tianyu Gu and Paul Hu
  Cooperation with Utah IS department and GMW e-commerce Company in USA. Presented at INFORMS Marketing Science Conference. Considering submission to Journal of Marketing.
• Optimizing LLMs as Customer Service Co-Pilots: Effects of Centralized versus Non-Centralized and Distributed versus Non-Distributed Strategies
  with Tianyu Gu and Paul Hu
  Cooperation with Utah IS department and a top car manufacturer in South China. Preparing for submission to Marketing Science.
• Generative AI in Sales Training: A Large Language Model Approach to Personalized Learning Optimization
  with Yu Zhu
  Cooperation with U of Delaware IS department. Methodology innovation paper. Preparing for submission to Management Science.
• Structural Equation Modeling of Salesforce Resilience: Incentives, Information Asymmetry, and Organizational Design
  with Yulin Hao, Mitchell Lovett
  Cooperation with U of Rochester MKT department. Structural modeling paper. Planning submission to Marketing Science.
• The Performance-Strategy Nexus: Appraisal Innovation and its Impact on Salesforce Effectiveness
  with Liangding Jia
  Cooperation with NJU and a company with over 500 salespeople. Considering Academy of Management Journal (AMJ) or Strategic Management Journal (SMJ).

Working Papers

• Optimizing AIGC for FMCG Package Design: Field Studies to Balance Algorithmic Creativity and Brand Constraints
  with Tianyu Gu and Paul Hu
  Cooperation with Utah IS department and a Beijing-based Creative Ideas Firm. Serving as project lead. Considering Journal of Marketing Research.
• Consumer Behavior and Visual Analytics: Mapping Time-Dependent Compliance and Perception in Retail Environments
  with Arul Mishra and Himanshu Mishra
  Cooperation with JLU MKT department, ASU IS department, and a large chain supermarket. Considering Journal of Consumer Research and Marketing Science.
• Real-Time Video Analysis: Unveiling New Frontiers in Consumer Cognition Research
  with Yu Zhu and Yu Qin
  Cooperation with U of Delaware IS department and ASU IS department. Considering Management Science or ISR.
• Econometric Modeling of Price Optimization in Hyper-Diverse Product Ecosystems
  with Yufeng Huang, Yulin Hao
  Cooperation with U of Rochester MKT department. Structural modeling paper. Considering Marketing Science.
• Balancing Efficiency and Reputation in Healthcare: An Empirical Analysis of Chain Hospital Management
  with Xiangming Zhan
  Cooperation with ASU public health and a chain hospital in North China. Considering health care section of Management Science.

Conference and Competition Projects

• Unraveling the Secrets of Global Movie Success: How Policy and Cultural Barriers Shape Box Office Performance
  with Tianyu Gu
  Presented at INFORMS Marketing Science Conference.
• Unlocking the Black Box of Language Models: Bridging Consumer and Machine Cognition for Enhanced Performance
  with Olivia Sheng and Yu Qin
  Methodology innovation project.
• LLM-Enhanced Career Path Optimization: An Algorithmic Framework to Tackle STEM Youth Unemployment in China
  with Xiao Fang and Yu Zhu
  Cooperation with U of Delaware IS department and a leading provincial STEM training center.
• Optimizing Market Access Strategies for Novel HIV Therapeutics
  with Shannuo Li and Xiangming Zhan
  Cooperation with Utah Pharmaceutics and ASU public health.

Research Experience

• Master Thesis: The Effect of Word-of-Mouth on Box Office: a Emotional Resonance Perspective (June 2020)
  Leveraged online review data and interviews to examine the impact of expert vs. customer reviews on movie performance.
• Research Assistant for Ann Veeck (Western Michigan) and Hongli Zhang (Jilin U) (Jul.2015 - Dec.2016)
  Participated in field research on youth consumption trends, including questionnaire design, data collection, and analysis.