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- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely...
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Keywords:
Peer-to-peer Markets;
Marketplace Matching;
AI and Machine Learning;
Demand and Consumers;
Digital Platforms;
Marketing
Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
- 2023
- Working Paper
State Employment as a Strategy of Autocratic Control in China
By: Jaya Y. Wen
This paper presents evidence that autocrats use state-owned firms to strategically pacify social unrest via employment provision, a role that may contribute to their favorable treatment and persistence across settings. I use variation in a regional conflict between...
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Wen, Jaya Y. "State Employment as a Strategy of Autocratic Control in China." Working Paper, January 2023.
- 2022
- Working Paper
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with...
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Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Working Paper, March 2022.
- August 2021
- Article
Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders
By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British...
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Keywords:
Mixed Methods;
Insider-outsiders;
Myth Of Informed Objectivity;
Hybrid Research;
Oral Narratives;
Research;
Analysis;
India
Khanna, Tarun, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam, and Meena Hewett. "Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders." Academy of Management Perspectives 35, no. 3 (August 2021): 384–399.
- Article
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
By: Wanqian Yang, Lars Lorch, Moritz Graule, Himabindu Lakkaraju and Finale Doshi-Velez
Domains where supervised models are deployed often come with task-specific constraints, such as prior expert knowledge on the ground-truth function, or desiderata like safety and fairness. We introduce a novel probabilistic framework for reasoning with such constraints...
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Yang, Wanqian, Lars Lorch, Moritz Graule, Himabindu Lakkaraju, and Finale Doshi-Velez. "Incorporating Interpretable Output Constraints in Bayesian Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- October 2020
- Case
PraDigi Open Learning: Transforming Rural India
By: John J-H Kim and Malini Sen
Pratham is a non-governmental organization, focusing on high-quality, low-cost and replicable interventions to address gaps in the Indian education system. Co-founder Madhav Chavan is interested in using technology for education but differed in the way it is used in...
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Keywords:
Decision Choices and Conditions;
Social Entrepreneurship;
Education;
Information Technology;
Learning;
Growth and Development Strategy;
Non-Governmental Organizations;
Social Issues;
Education Industry;
India;
Asia
Kim, John J-H, and Malini Sen. "PraDigi Open Learning: Transforming Rural India." Harvard Business School Case 321-022, October 2020.
- 2017
- Working Paper
Digital Labor Markets and Global Talent Flows
By: John Horton, William R. Kerr and Christopher Stanton
Digital labor markets are rapidly expanding and connecting companies and contractors on a global basis. We review the environment in which these markets take root, the micro- and macro-level studies of their operations, their ongoing evolution and recent trends, and...
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Horton, John, William R. Kerr, and Christopher Stanton. "Digital Labor Markets and Global Talent Flows." Harvard Business School Working Paper, No. 17-096, May 2017.
- 2014
- Chapter
Firms and Global Capitalism
By: Geoffrey Jones
This chapter forms part of the two-volume Cambridge History of Capitalism, a definitive new reference work that traces the history of capitalism from its origins to the present day. The chapter focuses on the role of business enterprises as powerful actors in...
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Keywords:
Political Economy;
American History;
Economic History;
Business History;
Labor History;
Slavery;
Numeracy And Quantification;
Science And Technology Studies;
History Of The Book;
International Investment;
International Business;
International Marketing;
Globalization;
History
Jones, Geoffrey. "Firms and Global Capitalism." Chap. 6 in The Cambridge History of Capitalism: Volume 2. The Spread of Capitalism: From 1848 to the Present, edited by Larry Neal and Jeffrey G. Williamson, 169–200. Cambridge: Cambridge University Press, 2014.
- August 2007
- Article
Remedying Education: Evidence from Two Randomized Experiments in India
By: A. Banerjee, Shawn A. Cole, E. Duflo and L. Linden
This paper presents the results of two randomized experiments conducted in schools in urban India. A remedial education program hired young women to teach students lagging behind in basic literacy and numeracy skills. It increased average test scores of all children in...
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Banerjee, A., Shawn A. Cole, E. Duflo, and L. Linden. "Remedying Education: Evidence from Two Randomized Experiments in India." Quarterly Journal of Economics 122, no. 3 (August 2007): 1235–1264.
- Forthcoming
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with...
View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics (forthcoming). (Pre-published online July 8, 2024.)