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Publications

Publications

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  • All HBS Web  (302)
    • News  (22)
    • Research  (250)
    • Events  (4)
  • Faculty Publications  (230)

Show Results For

  • All HBS Web  (302)
    • News  (22)
    • Research  (250)
    • Events  (4)
  • Faculty Publications  (230)
← Page 9 of 302 Results →
  • 2020
  • Working Paper

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry
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Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
  • May 2020
  • Article

Identifying Sources of Inefficiency in Health Care

By: Amitabh Chandra and Douglas O. Staiger
In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted and push standardization of care as a way of reducing allocative inefficiency. However, an... View Details
Keywords: Health Care and Treatment; Performance Efficiency; Performance Productivity; Mathematical Methods
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Chandra, Amitabh, and Douglas O. Staiger. "Identifying Sources of Inefficiency in Health Care." Quarterly Journal of Economics 135, no. 2 (May 2020): 785–843.
  • 2022
  • Article

Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations

By: Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach and Himabindu Lakkaraju
As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting explanations is consistently high across all subgroups of a population. For instance, it... View Details
Keywords: Prejudice and Bias; Mathematical Methods; Research; Analytics and Data Science
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Dai, Jessica, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach, and Himabindu Lakkaraju. "Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 203–214.
  • 2017
  • Working Paper

Identifying Sources of Inefficiency in Health Care

By: Amitabh Chandra and Douglas O. Staiger
In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted and push standardization of care as a way of reducing allocative inefficiency. However, an... View Details
Keywords: Health Care and Treatment; Performance Efficiency; Performance Productivity; Mathematical Methods
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Chandra, Amitabh, and Douglas O. Staiger. "Identifying Sources of Inefficiency in Health Care." NBER Working Paper Series, No. 24035, November 2017.
  • Forthcoming
  • Article

Branch-and-Price for Prescriptive Contagion Analytics

By: Alexandre Jacquillat, Michael Lingzhi Li, Martin Ramé and Kai Wang
Contagion models are ubiquitous in epidemiology, social sciences, engineering, and management. This paper formulates a prescriptive contagion analytics model where a decision maker allocates shared resources across multiple segments of a population, each governed by... View Details
Keywords: COVID-19; Mathematical Methods
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Jacquillat, Alexandre, Michael Lingzhi Li, Martin Ramé, and Kai Wang. "Branch-and-Price for Prescriptive Contagion Analytics." Operations Research (forthcoming). (Pre-published online March 13, 2024.)
  • 2007
  • Working Paper

Optimal Reserve Management and Sovereign Debt

By: Laura Alfaro and Fabio Kanczuk
Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign's willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming... View Details
Keywords: Sovereign Finance; Borrowing and Debt; Financial Liquidity; International Finance; Emerging Markets; Mathematical Methods
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Alfaro, Laura, and Fabio Kanczuk. "Optimal Reserve Management and Sovereign Debt." NBER Working Paper Series, No. 13216, July 2007.
  • 2011
  • Chapter

An Exploration of the Japanese Slowdown during the 1990s

By: Diego A. Comin
Why was the 1990s a lost decade for Japan? How is it possible that the Japanese economy stagnated for a decade if none of the shocks that arguably hit the economy seemed to have persisted for much more than three years or so? In this paper I show that the endogenous... View Details
Keywords: Economic Slowdown and Stagnation; Performance Productivity; Mathematical Methods; Research and Development; Technology Adoption; Japan
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Comin, Diego A. "An Exploration of the Japanese Slowdown during the 1990s." In Japan's Bubble, Deflation, and Long-term Stagnation, edited by Koichi Hamada, Anil Kashyap, and David Weinstein. MIT Press, 2011.
  • March 2022
  • Article

Where to Locate COVID-19 Mass Vaccination Facilities?

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
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Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
  • 2010
  • Working Paper

Substitution Patterns of the Random Coefficients Logit

By: Thomas J. Steenburgh and Andrew Ainslie
Previous research suggests that the random coefficients logit is a highly flexible model that overcomes the problems of the homogeneous logit by allowing for differences in tastes across individuals. The purpose of this paper is to show that this is not true. We prove... View Details
Keywords: Decision Choices and Conditions; Mathematical Methods; Behavior; Prejudice and Bias
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Steenburgh, Thomas J., and Andrew Ainslie. "Substitution Patterns of the Random Coefficients Logit." Harvard Business School Working Paper, No. 10-053, January 2010.
  • 2016
  • Working Paper

Algorithmic Foundations for Business Strategy

By: Mihnea Moldoveanu
I introduce algorithmic and meta-algorithmic models for the study of strategic problem solving, aimed at illuminating the processes and procedures by which strategic managers and firms deal with complex problems. These models allow us to explore the relationship... View Details
Keywords: Mathematical Methods; Business Strategy
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Moldoveanu, Mihnea. "Algorithmic Foundations for Business Strategy." Harvard Business School Working Paper, No. 17-036, October 2016.
  • Article

Matching in Networks with Bilateral Contracts: Corrigendum

By: John William Hatfield, Ravi Jagadeesan and Scott Duke Kominers
Hatfield and Kominers (2012) introduced a model of matching in networks with bilateral contracts and showed that stable outcomes exist in supply chains when firms' preferences over contracts are fully substitutable. Hatfield and Kominers (2012) also asserted that in... View Details
Keywords: Matching With Contracts; Substitutability; Mathematical Methods
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Hatfield, John William, Ravi Jagadeesan, and Scott Duke Kominers. "Matching in Networks with Bilateral Contracts: Corrigendum." American Economic Journal: Microeconomics 12, no. 3 (August 2020): 277–285.
  • 26 Apr 2023
  • In Practice

Is AI Coming for Your Job?

users may have additional knowledge or context that the AI doesn’t (e.g. that the AI hasn’t been trained on, propriety knowledge, a better understanding of the specific task at hand, etc.). Another risk with these generative AI models is... View Details
Keywords: by Kristen Senz; Technology
  • 2010
  • Working Paper

The Unbundling of Advertising Agency Services: An Economic Analysis

By: Mohammad Arzaghi, Ernst R. Berndt, James C. Davis and Alvin J. Silk
We address a longstanding puzzle surrounding the unbundling of services occurring over several decades in the U.S. advertising agency industry: What accounts for the shift from bundling to unbundling of services and the slow pace of change? Using Evans and Salinger's... View Details
Keywords: Advertising; Change; Forecasting and Prediction; Cost; Price; Analytics and Data Science; Surveys; Marketing Strategy; Media; Service Operations; Agency Theory; Mathematical Methods; Advertising Industry; United States
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Arzaghi, Mohammad, Ernst R. Berndt, James C. Davis, and Alvin J. Silk. "The Unbundling of Advertising Agency Services: An Economic Analysis." Harvard Business School Working Paper, No. 11-039, September 2010.
  • May–June 2018
  • Article

Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations

By: Joel Goh, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh and David Moore
Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When Markov chains are used as a modeling framework for such studies, this data inadequacy can manifest itself as imprecision in the elements of the transition matrix. In this paper,... View Details
Keywords: Markov Chains; Cost Effectiveness; Medical Innovations; Colorectal Cancer; Health Care and Treatment; Cost vs Benefits; Innovation and Invention; Mathematical Methods; Health Industry
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Goh, Joel, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh, and David Moore. "Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations." Operations Research 66, no. 3 (May–June 2018): 697–715. (Winner, 2014 INFORMS Health Applications Society Pierskalla Award & Finalist, 2014 INFORMS George E. Nicholson student paper competition.)
  • 2010
  • Working Paper

Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

By: Doug J. Chung, Thomas J. Steenburgh and K. Sudhir
We estimate a dynamic structural model of sales force response to a bonus based compensation plan. The paper has two main methodological innovations: First, we implement empirically the method proposed by Arcidiacono and Miller (2010) to accommodate unobserved latent... View Details
Keywords: Compensation and Benefits; Performance Productivity; Mathematical Methods; Salesforce Management; Motivation and Incentives
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Chung, Doug J., Thomas J. Steenburgh, and K. Sudhir. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans." Harvard Business School Working Paper, No. 11-041, October 2010.
  • June 2008
  • Article

Minimally Acceptable Altruism and the Ultimatum Game

By: Julio J. Rotemberg
I suppose that people react with anger when others show themselves not to be minimally altruistic. With heterogeneous agents, this can account for the experimental results of ultimatum and dictator games. Moreover, it can account for the surprisingly large fraction of... View Details
Keywords: Philanthropy and Charitable Giving; Game Theory; Mathematical Methods
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Rotemberg, Julio J. "Minimally Acceptable Altruism and the Ultimatum Game." Journal of Economic Behavior & Organization 66, nos. 3-4 (June 2008).
  • 2022
  • Working Paper

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods
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Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
  • Article

Moment-to-moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing

By: Thales S. Teixeira, Michel Wedel and Rik Pieters
We develop a conceptual framework for understanding the impact that branding activity (the audio-visual representation of brands) and consumers' dispersion of attention have on their moment-to-moment avoidance decisions during television advertising. It formalizes this... View Details
Keywords: Advertising; Decision Choices and Conditions; Television Entertainment; Brands and Branding; Consumer Behavior; Mathematical Methods
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Teixeira, Thales S., Michel Wedel, and Rik Pieters. "Moment-to-moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing." Marketing Science 29, no. 5 (September–October 2010): 783–804. (Lead Article.)
  • May 2020
  • Article

Scalable Holistic Linear Regression

By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
Keywords: Mathematical Methods; Analytics and Data Science
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Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
  • 2011
  • Working Paper

Free to Punish? The American Dream and the Harsh Treatment of Criminals

By: Rafael Di Tella and Juan Dubra
We describe the evolution of selective aspects of punishment in the U.S. over the period 1980-2004. We note that imprisonment increased around 1980, a period that coincides with the "Reagan revolution" in economic matters. We build an economic model where beliefs about... View Details
Keywords: Crime and Corruption; Economy; Moral Sensibility; Mathematical Methods; Opportunities; Behavior; United States
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Di Tella, Rafael, and Juan Dubra. "Free to Punish? The American Dream and the Harsh Treatment of Criminals." NBER Working Paper Series, No. 17309, August 2011.
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