This paper, using mixed methods, studies the long-run memories of the aftermath of forced displacement resulting from the 1947 Partition of British India and helps us understand why several categories of institutions pertaining to the management of human capital, particularly in northern India and Pakistan, emerged as they did, in response to this massive ‘shock’ to the preceding structures of British India. The data, in the form of oral narratives of survivors, were collected via a modified form of respondent-driven sampling more than seventy years after the event. Prior analyses of the Partition have been qualitative and largely the purview of historians. In contrast, this paper is an example of how quantifying and employing mixed methods to a largely qualitative dataset related to an historical event and its continuing impact can be helpful to identify trends, gain unique insights, and confirm anecdotal wisdom, about the institutional underpinnings of society in light of epochal events that shape its economic and social structures. For example, finding that migrants into Pakistan express continuing support for the Partition, despite their economic losses and negative experiences, and subsequent political and economic upheaval of the country, shows the importance of narrative and the politics of identity.
Tarun Khanna is the Jorge Paulo Lemann Professor at the Harvard Business School. For over two decades, he has studied entrepreneurship as a means to social and economic development in emerging markets. At HBS since 1993, after obtaining degrees from Princeton and Harvard, he has taught courses on strategy, corporate governance and international business to MBA and Ph.D. students and senior executives.
Karim R. Lakhani is a Professor of Business Administration at the Harvard Business School and one of the Principal Investigators of the Laboratory for Innovation Science at Harvard (LISH). He specializes in the management of technological innovation in firms and communities. His research is on distributed innovation systems and the movement of innovative activity to the edges of organizations and into communities. He has extensively studied the emergence of open source software communities and their unique innovation and product development strategies. He has also investigated how critical knowledge from outside of the organization can be accessed through innovation contests. Currently, Professor Lakhani is investigating incentives and behavior in contests and the mechanisms behind scientific team formation through field experiments on the Topcoder platform and the Harvard Medical School.
Ruihan Wang is a data scientist at Laboratory for Innovation Science (LISH). He received his master’s degree in Information Science from University of Michigan and a bachelor’s degree in E-Commerce Engineering from Beijing University of Posts and Telecommunications. He focuses on using innovative data-driven methods to explore real-world problems. His interests include various data science techniques, such as data manipulation, machine learning and natural language processing.
Michael works as a research scientist at the Crowd Innovation Lab. His present projects use field experiments and historical data to investigate individual behavior in tournament environments. He received his Ph.D. in economics from the University of Pittsburgh in 2011 under his advisor Prof. Lise Vesterlund. Michael’s dissertation work focuses on the private provision of public goods by non-profit organizations. He examines contribution behavior using theory and laboratory experiments.
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