1 | TITLE | Status | Authors | Short Description | |
---|---|---|---|---|---|
2 | 1 | Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation | Management Science (2014) | Kartik Hosanagar, Daniel Fleder, Dokyun Lee, and Andreas Buja | Hybrid recommenders do not seem to cause filter bubble. Users' commonality increases while consuming more diverse set of products caused by volume (buy more) and product mix (buy similar products) effects. |
3 | 2 | Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook | Management Science (2018) | Dokyun Lee, Kartik Hosanagar, and Harikesh Nair | Informative content is good for clickthroughs and shares while brand personality content (persuasive) content is good for engagement. Mixing two is good for both path-to-purchase and engagement |
4 | 3 | How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation Via Randomized Field Experiment | Information Systems Research (2019) | Dokyun Lee and Kartik Hosanagar | Collaborative filtering recommenders increase individual view and purchase diversity but decrease aggregate diversity as consumers are pushed to the same products. While niche item's absolute sales increase, market share decreases. |
5 | 4 | Large Scale Cross Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning | Journal of Marketing Research (2019) | Xiao Liu, Dokyun Lee, Kannan Srinivasan | Content in user-generated product reviews that cause purchase in e-commerce is identified and their impact quantified |
6 | 5 | How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages | Management Science (2020) SSRN | Dokyun Lee and Kartik Hosanagar | How recommender systems interact with different product attributes in different purchase stages are quantified via experiments. |
7 | 6 | Soul and Machine (Learning) | Marketing Letters (2020) SSRN | Many authors | The role of machine learning in Marketing |
8 | 7 | Focused Concept Miner (FCM): Interpretable Deep Learning for Text Exploration | ISR (3rd) Web, SSRN | Dokyun Lee, Emaad Ahmed Manzoor, Zhaoqi Cheng | Interpretable text exploration deep learning model customized to extract out coherent concepts related to business variable of importance |
9 | 8 | What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features | Management Science (2021) SSRN | Shunyuan Zhang, Dokyun Lee, Param Vir Singh, Kannan Srinivasan | Good photos are associated with additional $2500 dollars per year revenue in airbnb. While 60% that can be accounted for by photo quality, we also breakdown 12 interpretable image qualities that are correlated to increased demand |
10 | 9 | Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft | Journal of Marketing Research (2021) SSRN | Shunyuan Zhang, Dokyun Lee, Param Vir Singh, Tridas Mukhpadhyay | Airbnb and ridesharing apps are complementary |
11 | 10 | How Do Peer Awards Motivate Creative Content? Experimental Evidence From Reddit | Management Science (2021) | Gordon Burtch, Qinglai He, Yili Hong, Dokyun Lee | Peer awards induced recipients to make longer, more frequent posts, and that these effects were particularly pronounced among newer community members. Impact at the platform level is also discussed |
12 | 11 | The Effects of Outcome Valence and Explanations for Algorithmic Decisions on Consumer Understanding | Under Revision | Joy Tong Lu, Dokyun Lee, Taewan Kim, David Danks | Framework of what dimensions to consider when devising algorithmic explanation |
13 | 12 | Fast Fashion May Actually Increase The Demand for Premium Brand | Journal of Marketing Research (2022 Accepted) | June Shi, Dokyun Lee, Xiao Liu, Kannan Srinivasan | In fashion social media, fast fashion can be used to compliment premium brand and actually increase demand. |
14 | 13 | Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online | Management Science (2022) arxiv | Emaad Manzoor, George Chen, Dokyun Lee, Mike Smith | Individual's reputation significantly impacts their persuasion rate above and beyond the validity, strength and presentation of their arguments. |
15 | 14 | Text, Deep Learning, and Patent Valuation | Under Revision | Po-Hsuan Hsu, Dokyun Lee, Prasanna Tambe, David H. Hsu | We utilize text in patent to predict the value of patent |
16 | 15 | Nudging Private Ryan: Mobile Micro-Giving under Economic Incentives and Audience Effect | MISQ (2022) SSRN | Dongwon Lee, Anandasivam Gopal, Dokyun Lee, Dongwook Shin | On private mobile settings, economic incentives (rebate, match) to encourage donation work differently. |
17 | 16 | InnoVAE: Generative AI for Understanding Patents and Innovation | Management Science (2nd Round) SSRN | Zhaoqi Cheng, Dokyun Lee, Prasanna Tambe | Using Beta-VAE, we situate patents incorporating both structured and unstructured data in a vector space spanned by interpretable axis that comprise factors of innovation |
18 | 17 | Interpretable Machine Learning for Theory Building | Work in Progress | Dokyun Lee, Eric Zhou, Chengfeng Mao, Gerald Kane | Conceptual framework of how Interpretable Machine Learning can be used to find theory-worthy patterns in unstructured data |
19 | 18 | Modeling Lengthy Behavioral Log Data for Customer Churn Management | Under Review | Daehwan Ahn, Dokyun Lee, Kartik Hosanagar | Details coming soon |