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Mei Li

University of Oklahoma - Michael F. Price College of Business

307 West Brooks

Norman, OK 73019-4004

United States

SCHOLARLY PAPERS

4

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TOTAL CITATIONS

0

Scholarly Papers (4)

1.

Is In-Game Purchase a Guilty Pleasure? Negative Beliefs and Treatment

Posted: 22 Jun 2023
University of Oklahoma - Michael F. Price College of Business, Arizona State University (ASU) - W.P. Carey School of Business, Independent and University of Minnesota - Twin Cities - Department of Operations and Management Science

Abstract:

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In-Game Purchases, Microtransactions, Negative Beliefs, Attitude, Behavioral Experiments

2.

Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making

Posted: 07 Dec 2022
Arizona State University (ASU) - Department of Information Systems, Xi'an Jiaotong University, School of Management, Xi'an Jiaotong University (XJTU) - School of Management, University of Oklahoma - Michael F. Price College of Business and University of Washington - Michael G. Foster School of Business

Abstract:

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Fairness, Machine Learning, Scoring System, Mixed Integer Programming

3.

Examining Network Entry Decisions in Healthcare: Competition, Collaboration, and Organizational Characteristics

Posted: 10 Jun 2021
Michigan State University, University of Oklahoma - Michael F. Price College of Business, Miami University of Ohio and Independent

Abstract:

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Accountable Care Organizations (ACOs); Healthcare; Network Entry Decisions; Competition Network; Collaboration Network; Theory of Networks

4.

People Do Not Know What They Want Until You Show it to Them. But When?

Posted: 06 Mar 2021
University of Oklahoma - Michael F. Price College of Business, JD.com American Technologies Corporation, Xi'an Jiaotong University (XJTU) - School of Management, Michigan State University - The Eli Broad College of Business and The Eli Broad Graduate School of Management and Temple University - Department of Statistics, Operations, and Data Science

Abstract:

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Online recommendation, Recommendation system design, Repurchase cycle, Recommendation timing, Demand-driven recommendation system, Large-scale online experiment