Tiantian Yang

Current Courses (Spring 2026)

• MGMT2930 - People Analytics

  This course examines the use of data to understand and improve how people are managed in organizations. People really are organizations' most important asset, providing the critical link in converting strategy and capital into value. Yet throughout most of our history, most organizations have relied on long-standing traditions, hear-say, political expedience, prejudice and gut instinct to make decisions about how those people should be managed. Recent years have seen a growing movement to bring more science to how we manage people. In some cases, that means ensuring that whatever practices and approaches we adopt are backed up by solid evidence as to their effectiveness. Often, organizations will seek to go further, analyzing their own data to identify problems and learn what is working and what is not in their own context. This course applies the insights of the people analytics movement to help students become better managers and more critical analysts within their organizations. The course aims to develop students in three specific ways. First, it will provide students with an up-to-the-minute grounding in current evidence about managing people, providing a knowledge base that can ensure that their future management is guided by best practices. Second, we will develop the skills and understanding necessary to be thoughtful, critical consumers of evidence on people management, allowing them to make the most of the analysis available to them as they make people decisions. Third, we will provide guidance and practice in conducting people analytics, preparing students to gather data of their own, and making them more skilled analysts. We will pursue these goals through a mixture of lecture, case discussion, and hands on exploration of a variety of data sets.

  MGMT2930401 ( Syllabus )

  MGMT2930402 ( Syllabus )

• MGMT9180 - Personnel Economics A

  This is a half-semester PhD course in the Management Department that is also open to any current PhD students at Wharton. The canonical model in economics views an agent as a fully rational, atomistic individual making optimal choices under scarcity. This approach has been very powerful theoretically and empirically to explain and to predict behavior in the workplace. This model has also been enriched to accommodate other phenomena arguably affecting behavior in the workplace like the social context (e.g. peer effects, altruism, or social comparison), non-standard time preferences, loss aversion, and cognitive costs. Incorporating these ideas into the standard model can be accomplished in various ways but the real stress test for these theories is whether they predict behavior more generally (i.e. we don't just use theory to explain one choice but choices more generally) and to generate empirical predictions that can be tested using experiments. In this mini-course we start-off with a tour de force of the fundamental principal-agent model and the various behavioral extensions. The core of the course is, however, not theoretical but a practical course on how to design field experiments to test these ideas.

  MGMT9180002 ( Syllabus )

• OIDD2930 - People Analytics

  This course examines the use of data to understand and improve how people are managed in organizations. People really are organizations' most important asset, providing the critical link in converting strategy and capital into value. Yet throughout most of our history, most organizations have relied on long-standing traditions, hear-say, political expedience, prejudice and gut instinct to make decisions about how those people should be managed. Recent years have seen a growing movement to bring more science to how we manage people. In some cases, that means ensuring that whatever practices and approaches we adopt are backed up by solid evidence as to their effectiveness. Often, organizations will seek to go further, analyzing their own data to identify problems and learn what is working and what is not in their own context. This course applies the insights of the people analytics movement to help students become better managers and more critical analysts within their organizations. The course aims to develop students in three specific ways. First, it will provide students with an up-to-the-minute grounding in current evidence about managing people, providing a knowledge base that can ensure that their future management is guided by best practices. Second, we will develop the skills and understanding necessary to be thoughtful, critical consumers of evidence on people management, allowing them to make the most of the analysis available to them as they make people decisions. Third, we will provide guidance and practice in conducting people analytics, preparing students to gather data of their own, and making them more skilled analysts. We will pursue these goals through a mixture of lecture, case discussion, and hands on exploration of a variety of data sets.

  OIDD2930401 ( Syllabus )

  OIDD2930402 ( Syllabus )

All Courses

• MGMT2930 - People Analytics

  This course examines the use of data to understand and improve how people are managed in organizations. People really are organizations' most important asset, providing the critical link in converting strategy and capital into value. Yet throughout most of our history, most organizations have relied on long-standing traditions, hear-say, political expedience, prejudice and gut instinct to make decisions about how those people should be managed. Recent years have seen a growing movement to bring more science to how we manage people. In some cases, that means ensuring that whatever practices and approaches we adopt are backed up by solid evidence as to their effectiveness. Often, organizations will seek to go further, analyzing their own data to identify problems and learn what is working and what is not in their own context. This course applies the insights of the people analytics movement to help students become better managers and more critical analysts within their organizations. The course aims to develop students in three specific ways. First, it will provide students with an up-to-the-minute grounding in current evidence about managing people, providing a knowledge base that can ensure that their future management is guided by best practices. Second, we will develop the skills and understanding necessary to be thoughtful, critical consumers of evidence on people management, allowing them to make the most of the analysis available to them as they make people decisions. Third, we will provide guidance and practice in conducting people analytics, preparing students to gather data of their own, and making them more skilled analysts. We will pursue these goals through a mixture of lecture, case discussion, and hands on exploration of a variety of data sets.

• MGMT9180 - Personnel Economics A

  This is a half-semester PhD course in the Management Department that is also open to any current PhD students at Wharton. The canonical model in economics views an agent as a fully rational, atomistic individual making optimal choices under scarcity. This approach has been very powerful theoretically and empirically to explain and to predict behavior in the workplace. This model has also been enriched to accommodate other phenomena arguably affecting behavior in the workplace like the social context (e.g. peer effects, altruism, or social comparison), non-standard time preferences, loss aversion, and cognitive costs. Incorporating these ideas into the standard model can be accomplished in various ways but the real stress test for these theories is whether they predict behavior more generally (i.e. we don't just use theory to explain one choice but choices more generally) and to generate empirical predictions that can be tested using experiments. In this mini-course we start-off with a tour de force of the fundamental principal-agent model and the various behavioral extensions. The core of the course is, however, not theoretical but a practical course on how to design field experiments to test these ideas.

• OIDD2930 - People Analytics

  This course examines the use of data to understand and improve how people are managed in organizations. People really are organizations' most important asset, providing the critical link in converting strategy and capital into value. Yet throughout most of our history, most organizations have relied on long-standing traditions, hear-say, political expedience, prejudice and gut instinct to make decisions about how those people should be managed. Recent years have seen a growing movement to bring more science to how we manage people. In some cases, that means ensuring that whatever practices and approaches we adopt are backed up by solid evidence as to their effectiveness. Often, organizations will seek to go further, analyzing their own data to identify problems and learn what is working and what is not in their own context. This course applies the insights of the people analytics movement to help students become better managers and more critical analysts within their organizations. The course aims to develop students in three specific ways. First, it will provide students with an up-to-the-minute grounding in current evidence about managing people, providing a knowledge base that can ensure that their future management is guided by best practices. Second, we will develop the skills and understanding necessary to be thoughtful, critical consumers of evidence on people management, allowing them to make the most of the analysis available to them as they make people decisions. Third, we will provide guidance and practice in conducting people analytics, preparing students to gather data of their own, and making them more skilled analysts. We will pursue these goals through a mixture of lecture, case discussion, and hands on exploration of a variety of data sets.

• Top 50 Best Undergraduate Business School Professors, Poets & Quants, 2025
• Wharton Teaching Excellence Award, 2025
• Wharton Teaching Excellence Award, 2024
• Wharton Teaching Excellence Award, 2022
• Penn Undergraduate Research Mentorship (PURM) Award, 2021
• Stanford Center for Advanced Study in the Behavioral Sciences Summer Institute, 2019
• Frank H. Kenan Institute of Private Enterprise Research Grant, 2019
• Kauffman Junior Faculty Fellowship, 2017
• Arts & Sciences Council Committee Faculty Research Grant, Duke University, 2017
• Arts & Sciences Council Committee Faculty Research Grant, Duke University, 2015
• Royster Society of Fellows Dissertation Completion Fellowship Award, 2013
• Howard W. Odum Award for Excellence, University of North Carolina- Chapel Hill, Department of Sociology, 2013
• Ewing Marion Kauffman Dissertation Fellowship, 2012

• Top 50 Best Undergraduate Business School Professors, Poets & Quants - 12/01/2025
• Female-led start-ups embrace Plan B — then C, D, E . . . , Financial Times - 03/07/2022

Knowledge at Wharton

• Why Women’s Networks Are Stronger During Crisis | Tiantian Yang, Knowledge at Wharton - 3/3/2026
• How AI Is Fueling the Gender Pay Gap in Tech, Knowledge at Wharton - 12/2/2025
• Why Women Are Leaving Male-dominated STEM, Knowledge at Wharton - 7/1/2025
• Can Intrapreneurship Help Close the Racial Wealth Gap?, Knowledge at Wharton - 4/22/2024
• Can Intrapreneurship Help Close the Racial Wealth Gap?, Knowledge at Wharton - 4/12/2024
• Understanding the Value of Networks for Mothers Reentering the Workforce, Knowledge at Wharton - 4/11/2024
• For Working Moms, Entrepreneurship Beats the ‘Motherhood Penalty’, Knowledge at Wharton - 5/8/2023

Wharton Stories

• At Wharton, Three Students of Asian Heritage Found An Abundance of Community, Wharton Stories - 05/08/2023
• Get to Know the 20 New Faculty Members Joining Wharton This Year, Wharton Stories - 08/17/2020