Publications/Accepted Papers

1. AI-Human Hybrids for Marketing Research: Leveraging LLMs as Collaborators, Journal of Marketing (2024)

with Neeraj Arora and Yohei Nishimura  (https://journals.sagepub.com/doi/abs/10.1177/00222429241276529)

2. Can AI and AI-Hybrids detect persuasion skills? Salesforce hiring with conversational video interviews, Marketing Science (2024) with Khai Chiong, Howard Dover and K. Sudhir  ( https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4137872 )

3. Attribute sentiment scoring with online text reviews: Accounting for language structure and attribute self-selection, Journal of Marketing Research (2022)  with  Minkyung Kim and K. Sudhir  (https://journals.sagepub.com/doi/pdf/10.1177/00222437211052500 )

Winner, Donald R. Lehmann Award, 2023  for best dissertation-based article in Journal of Marketing/Journal of Marketing Research

4. Artificial Intelligence Applications to Customer Feedback Research: A Review, Review of Marketing Research (2022)

with Shrabastee Banerjee and Peter Lee  (https://www.emerald.com/insight/content/doi/10.1108/S1548643520230000020010/full/html)

Selected Working Papers

1. Neither a Picasso Nor a Da Vinci: A Multi-modal Model for Pricing of Novice Artwork , with  Sharmistha Sikdar and Nika Dogonadze 

2. The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks, with Isamar Troncoso, Minkyung Kim and Soohyun Kim

3. What’s in a Response? Uncovering Management Response Strategies and Their Impact on Future Ratings and Sales, Hulya Karaman and Shrabastee Banerjee 

4. FEWD: A Fused Explainable Model using Wide and Deep Networks for Synthesizing Multi-Modal Content with John Lalor and Vamsi Kanuri

Patents

https://patents.justia.com/patent/11574266

Patent number: 11574266
Abstract: A human interaction replacement evaluation system analyzes actions taken by a user with an application on a client device that provides features to replace human interaction services with computer-based services. The results of the action provide an indication of the success of a particular action supported by the application (e.g., whether the action has a positive or negative effect on a key performance indicator) or an indication of how likely the user is to be ready to adopt a particular computer-based service. Recommendations are then provided to the user of the application or a manager of the application indicating actions to use, actions that have negative or positive effects on a key performance indicator, and so forth.
Type: Grant
Filed: August 6, 2020
Date of Patent: February 7, 2023
Assignee: Adobe Inc.
Inventors: Atanu R. Sinha, Ishita Sunity Kumar Chakraborty