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- 1969
- Other Unpublished Work
An Empirical Investigation of the Samuelson Rational Warrant Pricing Theory
By: Robert C. Merton
- April 1966
- Article
A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression
By: D. B. Crane and James R. Crotty
Keywords: Mathematical Methods
Crane, D. B., and James R. Crotty. "A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression." Management Science 13, no. 8 (April 1966).
- Other Unpublished Work
A Technique to Estimate Retail Demand and Lost Sales
By: A. Raman and Giulio Zotteri
- 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
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.)
- Research Summary
Competitive Strategy
Porter is engaged in a major new body of work on the theoretical foundations of competitive positioning and the underpinnings of sustainable competitive advantage. This research highlights the distinction between positioning and operational effectiveness; the... View Details
- Research Summary
Overview
By: Ethan C. Rouen
Relying on empirical archival methodologies—as well as techniques in data science—to develop and structure new sources of data by which to approach questions of looming disclosure changes, Professor Rouen has focused on one of the Securities and Exchange Commission’s... View Details
- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
- Forthcoming
- Article
Preference Externality Estimators: A Comparison of Border Approaches and IVs
By: Xi Ling, Wesley R. Hartmann and Tomomichi Amano
This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003). We highlight two dimensions in... View Details
Ling, Xi, Wesley R. Hartmann, and Tomomichi Amano. "Preference Externality Estimators: A Comparison of Border Approaches and IVs." Management Science (forthcoming). (Pre-published online January 23, 2024.)
- Forthcoming
- Article
Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers
By: Mengjie Cheng and Shunyuan Zhang
The growth of the influencer marketing industry warrants an empirical examination of the effect of posting sponsored videos on influencers' reputations. We collected a novel dataset of user-generated YouTube videos created by prominent English-speaking influencers in... View Details
- Forthcoming
- Article
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Organization Science (forthcoming). (Pre-published online May 31, 2023.)
- 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.)
- Other Unpublished Work
The Role of Inventory in Empowered Work Settings: Model and Empirical Analysis
By: S. Datar, M. Alles and R. Sarkar
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