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Maya Balakrishnan

Maya Balakrishnan

Doctoral Student

Doctoral Student

Maya Balakrishnan is a fifth year doctoral candidate at Harvard Business School in the Technology and Operations Management program. Her research uses a wide range of methods including lab experiments, econometrics, text analysis, modeling, and machine learning. She studies how organizations can design their operations in order to inspire trust. This includes understanding how companies can structure their workforces and communicate information around the diversity of their workforces to improve public perceptions, how companies can better take stances on sociopolitical issues to be well received by consumers, and how organizations can design algorithms and present their predictions to properly calibrate trust from end-users. Maya will be on the 2023-2024 job market. For the most up to date information, please visit her personal website. 

Maya previously earned a BS in Computer Science specializing in Human-Computer Interaction and a minor in Philosophy from Stanford University. Before entering graduate school, Maya previously worked at Microsoft and Goldman Sachs, and founded and ran a VC funded company which created software for packaged food manufacturers to digitize their operations, get detailed analytics around process optimization opportunities, and comply with food safety regulations. 

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Maya Balakrishnan is a fifth year doctoral candidate at Harvard Business School in the Technology and Operations Management program. Her research uses a wide range of methods including lab experiments, econometrics, text analysis, modeling, and machine learning. She studies how organizations can design their operations in order to inspire trust. This includes understanding how companies can structure their workforces and communicate information around the diversity of their workforces to improve public perceptions, how companies can better take stances on sociopolitical issues to be well received by consumers, and how organizations can design algorithms and present their predictions to properly calibrate trust from end-users. Maya will be on the 2023-2024 job market. For the most up to date information, please visit her personal website. 

Maya previously earned a BS in Computer Science specializing in Human-Computer Interaction and a minor in Philosophy from Stanford University. Before entering graduate school, Maya previously worked at Microsoft and Goldman Sachs, and founded and ran a VC funded company which created software for packaged food manufacturers to digitize their operations, get detailed analytics around process optimization opportunities, and comply with food safety regulations. 

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Maya Balakrishnan
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Publications Research Summary Awards & Honors

Journal Articles
Journal Articles

  • Balakrishnan, Maya, Jimin Nam, and Ryan W. Buell. "Differentiating on Diversity: How Disclosing Workforce Diversity Influences Consumer Choice." Production and Operations Management (forthcoming). View Details
  • Nam, Jimin, Maya Balakrishnan, Julian De Freitas, and Alison Wood Brooks. "Speedy Activists: Firm Response Time to Sociopolitical Events Influences Consumer Behavior." Special Issue on Consumer Insights from Text Analysis edited by Grant Packard, Sarah G. Moore, and Jonah Berger. Journal of Consumer Psychology 33, no. 4 (October 2023): 632–644. View Details

Working Papers
Working Papers

  • Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021. View Details
  • Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, December 2022. View Details
All Publications

Maya Balakrishnan is a fifth year doctoral candidate at Harvard Business School in the Technology and Operations Management program. Her research uses a wide range of methods including lab experiments, econometrics, text analysis, modeling, and machine learning. She studies how organizations can design their operations in order to inspire trust. This includes understanding how companies can structure their workforces and communicate information around the diversity of their workforces to improve public perceptions, how companies can better take stances on sociopolitical issues to be well received by consumers, and how organizations can design algorithms and present their predictions to properly calibrate trust from end-users. Maya will be on the 2023-2024 job market. For the most up to date information, please visit her personal website. 

Maya previously earned a BS in Computer Science specializing in Human-Computer Interaction and a minor in Philosophy from Stanford University. Before entering graduate school, Maya previously worked at Microsoft and Goldman Sachs, and founded and ran a VC funded company which created software for packaged food manufacturers to digitize their operations, get detailed analytics around process optimization opportunities, and comply with food safety regulations. 

Journal Articles
  • Balakrishnan, Maya, Jimin Nam, and Ryan W. Buell. "Differentiating on Diversity: How Disclosing Workforce Diversity Influences Consumer Choice." Production and Operations Management (forthcoming). View Details
  • Nam, Jimin, Maya Balakrishnan, Julian De Freitas, and Alison Wood Brooks. "Speedy Activists: Firm Response Time to Sociopolitical Events Influences Consumer Behavior." Special Issue on Consumer Insights from Text Analysis edited by Grant Packard, Sarah G. Moore, and Jonah Berger. Journal of Consumer Psychology 33, no. 4 (October 2023): 632–644. View Details
Working Papers
  • Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021. View Details
  • Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, December 2022. View Details
Research Summary
Overview
My research uses a combination of lab experiments and empirical methods to understand how organizations can design their operations in order to inspire trust.
Keywords: Behavioral Operations; Human-in-the-loop; Algorithm Transparency; Corporate Social Responsibility; Operations Management
Awards & Honors
Awarded the 2023 Prize in the POMS Junior Scholar Paper Competition from the College of Behavioral Operations at the Production and Operations Management Society for “Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence.”
Winner of the 2022 INFORMS Advances in Decision Analysis Conference Best PhD Blitz Presentation for "Unlocking Algorithm Potential: Overcoming Naïve Advice Weighting with Feature Transparency."
Additional Information
  • Maya Balakrishnan CV
  • Personal Website
Area of Study
  • Technology and Operations Management
Additional Information
Maya Balakrishnan CV
Personal Website

Area of Study

Technology and Operations Management
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