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- All HBS Web (327)
- Faculty Publications (110)
Show Results For
- All HBS Web (327)
- Faculty Publications (110)
- March 2004
- Article
Inflation, Inflation Variability, and Corruption
By: Miguel Braun and Rafael Di Tella
We present a model where agents can inflate the cost of goods needed to start an investment project and inflation variability increases monitoring costs. We show that inflation variability can lead to higher corruption and lower investment. We document a positive... View Details
Braun, Miguel, and Rafael Di Tella. "Inflation, Inflation Variability, and Corruption." Economics & Politics 16, no. 1 (March 2004).
- 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
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.)
Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans
We estimate a dynamic structural model of sales force response to a bonus based compensation plan. Substantively, the paper sheds insights on how different elements of the compensation plan enhance productivity. We find evidence that: (1) bonuses enhance productivity... View Details
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,... View Details
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- March–April 2014
- Article
Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans
By: Doug J. Chung, Thomas Steenburgh and K. Sudhir
We estimate a dynamic structural model of sales force response to a bonus based compensation plan. Substantively, the paper sheds insights on how different elements of the compensation plan enhance productivity. We find evidence that: (1) bonuses enhance productivity... View Details
Chung, Doug J., Thomas Steenburgh, and K. Sudhir. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans." Marketing Science 33, no. 2 (March–April 2014): 165–187. (Lead article. Featured in HBS Working Knowledge.)
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
- January 22, 2015
- Other Article
Are Capital Controls Effective? Firm-level Evidence from Brazil
By: Laura Alfaro, Anusha Chari and Fabio Kanczuk
Capital controls are back in fashion. This column discusses new firm-level evidence from Brazil showing that capital controls segment international financial markets, reduce external financing, and lower firm-level investment. They disproportionately affect small,... View Details
Alfaro, Laura, Anusha Chari, and Fabio Kanczuk. "Are Capital Controls Effective? Firm-level Evidence from Brazil." Vox, CEPR Policy Portal (January 22, 2015).
- 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
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.
- winter 2003
- Article
Massively Categorical Variables: Revealing the Information in Zip Codes
We introduce the idea of a massively categorical variable, a variable such as zip code that takes on too many values to be treated in the standard manner, and show how to use it directly as explanatory variables in an econometric model. In an application of this... View Details
Steenburgh, Thomas J., Andrew Ainslie, and Peder Hans Engebretson. "Massively Categorical Variables: Revealing the Information in Zip Codes." Marketing Science 22, no. 1 (winter 2003): 40–57.
- October 1, 2021
- Article
An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance.
By: B.M. Balk, M.R. De Koster, Christian Kaps and J.L. Zofio
Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a... View Details
Keywords: Efficiency Analysis; Performance Benchmarking; Warehousing; Analytics and Data Science; Performance Evaluation; Measurement and Metrics; Mathematical Methods
Balk, B.M., M.R. De Koster, Christian Kaps, and J.L. Zofio. "An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance." Art. 126261. Applied Mathematics and Computation 406 (October 1, 2021).
- February 2018 (Revised December 2020)
- Case
People Analytics at Teach For America (A)
By: Jeffrey T. Polzer and Julia Kelley
As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (A)." Harvard Business School Case 418-013, February 2018. (Revised December 2020.)
- February 2005 (Revised November 2016)
- Background Note
Forecasting the Adoption of a New Product
By: Elie Ofek
Provides tools and methodologies that allow forecasting demand for innovative new products. Highlights the Bass model—the theory behind it and ways to determine its parameters. Provides a detailed example of how to use the Bass model to forecast demand for satellite... View Details
Keywords: Forecasting and Prediction; Innovation and Invention; Marketing; Demand and Consumers; Mathematical Methods; Competition
Ofek, Elie. "Forecasting the Adoption of a New Product." Harvard Business School Background Note 505-062, February 2005. (Revised November 2016.)
- 2001
- Working Paper
Strategies to Fight Ad-sponsored Rivals
By: Ramon Casadesus-Masanell and Feng Zhu
We analyze the optimal strategy of a high-quality incumbent that faces a low-quality ad-sponsored competitor. In addition to competing through adjustments of tactical variables such as price or the number of ads a product carries, we allow the incumbent to consider... View Details
Casadesus-Masanell, Ramon, and Feng Zhu. "Strategies to Fight Ad-sponsored Rivals." Harvard Business School Working Paper, No. 10-026, September 2009. (Revised March 2010.)
- January 2020
- Article
Using Time-Driven Activity-Based Costing to Demonstrate Value in Perioperative Care: Recommendations and Review from the Society for Perioperative Assessment and Quality Improvement
By: O. Allin, R. D. Urman, A. F. Edwards, J. D. Blitz, K. J. Pfeifer, T. W. Feeley and A. M. Bader
A shift in health care payment models from volume toward value-based incentives will require deliberate input into systems development from both perioperative clinicians and administrators to ensure appropriate recognition of the value of all services... View Details
Keywords: Value-based Health Care; Outcomes; Time-Driven Activity-Based Costing; Health Care and Treatment; Cost Management; Value; Activity Based Costing and Management
Allin, O., R. D. Urman, A. F. Edwards, J. D. Blitz, K. J. Pfeifer, T. W. Feeley, and A. M. Bader. "Using Time-Driven Activity-Based Costing to Demonstrate Value in Perioperative Care: Recommendations and Review from the Society for Perioperative Assessment and Quality Improvement." Journal of Medical Systems 44, no. 1 (January 2020).
- 28 Nov 2011
- Research & Ideas
Rethinking the Fairness of Organ Transplants
simulations, the model suggests that life-year expectancies for the program can be increased by up to 8 percent, depending on variables plugged into the process. As with the "Moneyball" metrics... View Details
- September 2018
- Article
Assembling the Sales Team
Data and analytical tasks have lengthened productivity ramp-up times in many sales contexts, making each hire a bigger sunk cost for a longer time. Most companies adopt two common practices: They hire on the basis of “experience” and/or look at their best reps and try... View Details
Strategies to Fight Ad-sponsored Rivals
We analyze the optimal strategy of a high-quality incumbent that faces a low-quality ad-sponsored competitor. In addition to competing through adjustments of tactical variables such as price or the number of ads a product carries, we allow the incumbent to... View Details
- December 2010
- Article
Altruistic Dynamic Pricing with Customer Regret
By: Julio J. Rotemberg
A model is considered where firms internalize the regret costs that consumers experience when they see an unexpected price change. Regret costs are assumed to be increasing in the size of price changes and this can explain why the size of price increases is less... View Details
Keywords: Cost; Price; Change; Inflation and Deflation; Cost Management; Customers; Practice; Announcements; Forecasting and Prediction
Rotemberg, Julio J. "Altruistic Dynamic Pricing with Customer Regret." Scandinavian Journal of Economics 112, no. 4 (December 2010).
- 2009
- Working Paper
Altruistic Dynamic Pricing with Customer Regret
By: Julio J. Rotemberg
A model is considered where firms internalize the regret costs that consumers experience when they see an unexpected price change. Regret costs are assumed to be increasing in the size of price changes and this can explain why the size of price increases is less... View Details