Tiantian Yang

Tiantian Yang
  • Assistant Professor of Management

Contact Information

  • office Address:

    2025 SH-DH
    3620 Locust Walk
    Philadelphia, PA 19104

Research Interests: Entrepreneurship, Careers, Job Mobility, Organizational Theory, Economic Sociology, Gender and Race

Links: CV, Google Scholar, MGMT/OIDD 293 People Analytics Course Preview

Overview

Tiantian Yang  is an Assistant Professor of Management at the Wharton School, University of Pennsylvania. She received her PhD from the University of North Carolina-Chapel Hill in 2014. Prior to joining Wharton, she was an Assistant Professor in the Department of Sociology at Duke University. She has published many articles, including several in top management and sociology journals, such as the American Sociological Review, Organization Science and Journal of Management. She has received two highly prestigious awards based on nominations and recommendations: the Kauffman Dissertation Fellowship in 2012 (15 awarded nationwide) and the Kauffman Junior Faculty Fellowship in 2017 (7 awarded nationwide).

Tiantian’s research makes three principal contributions to the study of entrepreneurship, career mobility, and social inequality. First, she examines the entrepreneurial process to understand the mechanisms by which entrepreneurs can successfully create new organizations. Second, she draws on organizational theory and perspectives of career mobility to understand the career antecedents and consequences of entrepreneurial mobility. Third, she examines how inequalities in career attainment are (re)produced along gender and race lines in understudied social settings.

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Research

  • Tiantian Yang, Jiayi Bao, Howard E. Aldrich (2020), The Paradox of Resource Provision in Entrepreneurial Teams: Between Self-interest and the Collective Enterprise, Organization Science, 31 (6), pp. 1336-1358.

    Abstract: Viewing entrepreneurship as a form of collective action, this paper investigates the tension between an entrepreneurial team’s reliance on collective efforts for achieving success and individual members’ tendencies to withhold their personal resources. We argue that the precarious nature of the early founding stage and the difficulty of redeploying some resources for other uses amplify the risk of early-stage resource contributions and may lead to team members withholding resources or even free riding. Two conditions may help overcome such collective action problems: adopting a formal contract to specify rewards and sanctions and encouraging reciprocal exchange among team members through the lead entrepreneur’s voluntary contributions. Analyzing a nationally representative multiwave panel study of entrepreneurial teams in the United States, we show that early-stage team members are reluctant to provide resources tailored to the business, even though such resources are critical to venture survival. We find that presigned formal contracts and founding entrepreneurs’ initial contributions make members’ contributions of such resources much more likely. Lead entrepreneurs’ voluntary contributions to their businesses, signified by their provision of resources that impose high risks on themselves but increase the viability of the business, help mitigate collective action problems within entrepreneurial teams.

  • Tiantian Yang, Aleksandra Kacperczyk, Lucia Naldi (Under Revision), Career Antecedents of Female Entrepreneurship.

    Description: Revise and Resubmit at Organization Science

  • Tiantian Yang and Aleksandra Kacperczyk (Under Revision), Minority Entrepreneurship and Alternative Opportunities Inside Established Organizations.

    Description: Revise and Resubmit at Strategic Management Journal

  • Tiantian Yang (Under Revision), When Do Women Seek Reemployment? Motherhood Challenges and Constrained Preference.

    Description: Revise and Resubmit at Management Science

  • Tiantian Yang, Ming D. Leung, Jiayi Bao (Under Review), Approaching or Avoiding: Gender Asymmetry in Reactions to Prior Job Search Experience.

    Abstract: This paper presents a novel investigation into how supply-side job seeking interacts with demand-side hiring decisions to reproduce occupational gender segregation. The authors theorize that because female job seekers are less confident of their ability in male-typed jobs than their male counterparts, they will be more responsive to cues from employers. Specifically, job application success will encourage female job seekers to approach similar work in the future; employers’ rejections, on the other hand, will be particularly discouraging, leading women to avoid similar work in the future. Analyses of a longitudinal dataset of three million applications for IT and programming jobs from an online freelancing platform support the theory. Past job-seeking experience, either positive or negative, exerted a stronger effect on how women, compared to men, approached or avoided applying to IT and programming. Because failure is the more prevalent outcome, female freelancers stop applying to male-typed jobs quicker than males. In contrast, analyses in the female-typed writing and translation field did not reveal similar gender patterns. Gender asymmetries in response to employers’ hiring decisions reproduce occupational gender segregation by reducing women’s representation in male-typed but not female-typed fields. Implications for research on gender segregation, careers and hiring are discussed.

    Description: Under Review at ILR Review

  • Prasanna Tambe and Tiantian Yang (Under Review), Gender, Tech Bubbles, and the IT Earnings Gap.

    Description: Under Review at MIS Quarterly

  • Tiantian Yang and Maria del Carmen Triana (2019), Set up to Fail: Explaining When Women-Led Businesses Are More Likely to Fail, Journal of Management, 45 (3), pp. 926-954.

    Abstract: Drawing on role congruity theory, we examine whether and when women-led ventures are more likely to fail than men-led ventures. We investigate the relationship between the gender of the leading entrepreneur and business failure and three important moderators of this relationship: whether the leadership assignment is consistent with merit, whether the venture operates in a female-dominated industry, and whether the venture is operated by a spousal team. Drawing on a unique, nationally representative data set of entrepreneurial firms sampled from the U.S. population in 2005 and followed yearly until 2011, we demonstrate that female entrepreneurs’ businesses are more likely to fail than those of their male counterparts. Regarding the moderating effects, our results show that female entrepreneurs’ businesses are more likely to fail when their merit-based competence is inferior to that of their cofounders. However, in the same scenario, male entrepreneurs are still able to lead their businesses successfully. We also find that women entrepreneurs’ disadvantages in leading new businesses are amplified in contexts that many have expected to be supportive of women, including in industries dominated by women and within spousal teams. Together, our results suggest that women’s disadvantages in leading their businesses may be perpetuated by gender beliefs that discount women’s leadership. Based on our findings, we discuss our contributions to theory and practice, and we offer implications for future research.

  • Rebecca Zarutskie and Tiantian Yang, “Measuring Entrepreneurial Businesses: Current Knowledge and Challenges”. In National Bureau of Economic Research Volume, edited by John Haltiwanger, Erik Hurst, Javier Miranda, and Antoinette Schoar. (University of Chicago Press, 2017)

  • Tiantian Yang and Howard E. Aldrich (2017), “The Liability of Newness” Revisited: Theoretical Restatement and Empirical Testing in Emergent Organizations, Social Science Research, 63, pp. 36-53.

    Abstract: The mismatch between Stinchcombe's original propositions regarding “the liability of newness” and subsequent attempts to test those propositions suggests to us that the form and causes of the liability remain open to further investigation. Taking organizational emergence as a process comprising entrepreneurs engaging in actions that produce outcomes, we propose hypotheses about the social mechanisms of organizational construction involved in investing resources, developing routines, and maintaining boundaries. Distinguishing between initial founding conditions versus subsequent activities, our results not only confirm the liability of newness hypothesis, but also reveal a much higher risk of failure in organizations' early lifetime than rates found in previous research. Moreover, our results highlight the importance of entrepreneurs' continuing effort after their initial organizing attempts. Whereas only a few initial founding conditions lower the risk of failure, subsequent entrepreneurial activities play a major role in keeping the venture alive. Entrepreneurs contribute to whether a venture survives through raising more resources, enacting routines, and gaining increased public recognition of organizational boundaries. After controlling for financial performance, our results still hold. Based on our analysis, we offer suggestions for theory and research on organizations and entrepreneurship.

  • Tiantian Yang and Howard E. Aldrich (2014), Who’s the Boss? Explaining Gender Inequality in Entrepreneurial Teams, American Sociological Review, 79 (2), pp. 303-327.

    Abstract: Sociologists have examined gender inequalities across a wide array of social contexts. Yet, questions remain regarding how inequalities arise among autonomous groups pursuing economic goals. In this article, we investigate mixed-sex entrepreneurial teams to unpack the mechanisms by which gender inequality in leadership emerges, despite strong pressures toward merit-based organizing principles. We theorize the potentially competing relationships between merit and gender and explore the contingencies moderating their effects. Drawing on a unique, nationally representative dataset of entrepreneurial teams sampled from the U.S. population in 2005, we use conditional logistic regression to test our hypotheses. We demonstrate that merit’s effect becomes much larger when multiple merit-based criteria provide consistent predictions for which team member is superior to others, and when entrepreneurial founders adopt bureaucratic templates to construct new ventures. However, gender stereotypes of leaders pervasively constrain women’s access to power positions, and gender’s effect intensifies when spousal relationships are involved. Women have reduced chances to be in charge if they co-found new businesses with their husbands, and some family conditions further modify women’s chances, such as husbands’ employment and the presence of children.

Teaching

Current Courses (Spring 2023)

  • 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

    MGMT2930402

  • 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

    OIDD2930402

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.

  • MGMT2940 - Understanding Careers

    The class will examine a variety of aspects of careers. The first few sessions explore the basic building blocks of the career, outlining our knowledge on the different orientations that individuals take to their careers, how approaches to the career change as people get older, and how different kinds of job moves within and across firms advance careers. We will complement academic research by also hearing from an experienced executive who can talk about the issues that she dealt with as her career unfolded, and how she approached major decisions. The second part of the course explores in more detail the social resources that affect careers. Much research has examined how the structure of social networks affect success in the workplace and access to job. We will review this evidence with an eye to understanding how effective relationships can be developed. We will also examine some of the most critical relationships for shaping careers - those involving mentors and sponsors. The third section of the course then examines a number of the most important and difficult issues affecting modern careers. We explore one of the most difficult transitions that forms part of many careers, moving into management from an individual contributor role. We will also explore important social psychological conditions and strategies that allow individuals to persist and succeed in their career pursuit, especially in the face of obstacles, such as career setbacks and employer rejections. We then turn to issues of gender and careers. There is much evidence on the particular challenges that have faced women managers and executives in moving up the corporate ladder. We examine that evidence and discuss possible responses by managers and by organizations. We also discuss how individuals and organizations can manage the challenges of balancing work and personal life throughout the career.

  • 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.

Awards and Honors

  • Wharton Teaching Excellence Award, 2022
  • 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
  • Howard W. Odum Award for Excellence, University of North Carolina- Chapel Hill, Department of Sociology, 2013
  • Royster Society of Fellows Dissertation Completion Fellowship Award, 2013
  • Ewing Marion Kauffman Dissertation Fellowship, 2012

In the News

Activity

Latest Research

Tiantian Yang, Jiayi Bao, Howard E. Aldrich (2020), The Paradox of Resource Provision in Entrepreneurial Teams: Between Self-interest and the Collective Enterprise, Organization Science, 31 (6), pp. 1336-1358.
All Research

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