Publications

August 2019
Article

When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation

By: Yicheng Song, Nachiketa Sahoo and Elie Ofek

Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,... View Details

Keywords: Recommender Systems; Personalization; Recommendation Diversity; Variety Seeking; Collaborative Filtering; Consumer Utility Models; Digital Media; Clickstream Analysis; Learning-to-rank; Consumer Behavior; Media; Customization and Personalization; Strategy; Mathematical Methods

Find at Harvard

2018
Working Paper

Semi-Parametric Estimation of Dynamic Discrete Choice Models

By: David Hao Zhang

I develop a new method for estimating counterfactuals in dynamic discrete choice models, a widely used set of models in economics, without requiring a distributional assumption on utility shocks. Applying my method to the canonical Rust (1987) setting, I find that the... View Details

Keywords: Semiparametrics; Dynamic Discrete Choice; Consumer Choice; Mathematical Methods

February 2010
Supplement

Real Property Negotiation Game (CW): Excel Model

By: Arthur I. Segel, John Vogel and Justin Seth Ginsburgh

This Excel model is used to analyze the deals made in The Real Property Negotiation Game, which simulates the experience negotiating the sale, purchase, or financing of a property. View Details

Keywords: Property; Negotiation Deal; Sales; Financing and Loans; Mathematical Methods; Real Estate Industry

2012
Article

Demand and Capacity Management in Air Transportation

This paper summarizes research trends and opportunities in the area of managing air transportation demand and capacity. Capacity constraints and resulting congestion and low schedule reliability currently impose large costs on airlines and their passengers. Significant... View Details

Keywords: Demand Management; Capacity Management; Mathematical Modeling; Congestion And Delays; Trends And Opportunities; Demand and Consumers; Air Transportation; Mathematical Methods; Performance Capacity; Air Transportation Industry

January 2002
Background Note

Note on Business Model Analysis for the Entrepreneur

By: Richard G. Hamermesh, Paul W. Marshall and Taslim Pirmohamed

Describes the primary elements and defining characteristics of a company's business model from the perspective of an entrepreneur. Introduces several analytic techniques and provides illustrative examples of business models to support the analytic framework presented. View Details

Keywords: Business Model; Entrepreneurship; Framework; Mathematical Methods; Opportunities; Perspective

Educators

January 2003 (Revised February 2011)
Tool

Business Analysis and Valuation Model (Version 5)

By: Paul M. Healy, Krishna G. Palepu and Jonathan Barnett

Once you enter company financial statements, this software enables you to standardize them to a common format, make any needed adjustments to the company's accounting, and make assumptions about the company's future performance. The model then provides financial ratios... View Details

Keywords: Financial Statements; Standards; Mathematical Methods; Valuation

1979
Dissertation

Inference in Partially Identified Models

By: Dutch Leonard

Keywords: Mathematical Methods

spring 1973
Article

A Stochastic Model for Auditing

By: Robert S. Kaplan

Keywords: Mathematical Methods; Accounting Audits

Find at Harvard

2008
Working Paper

Minimally Altruistic Wages and Unemployment in a Matching Model

By: Julio J. Rotemberg

This paper presents a model in which firms recruit both unemployed and employed workers by posting vacancies. Firms act monopsonistically and set wages to retain their existing workers as well as to attract new ones. The model differs from Burdett and Mortensen (1998)... View Details

Keywords: Retention; Selection and Staffing; Employment; Wages; Mathematical Methods

2024
Working Paper

Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference

By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov

Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details

Keywords: Mathematical Methods; Analytics and Data Science

2023
Article

Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju

One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details

Keywords: AI and Machine Learning; Mathematical Methods

1977
Chapter

A Diagnostic Model for Organizational Behavior

By: D. Nadler and M. Tushman

Keywords: Mathematical Methods; Organizational Design; Organizational Structure; Behavior

2009
Article

Modeling Expert Opinions on Food Healthfulness: A Nutrition Metric

By: Jolie M. Martin, John Beshears, Katherine L. Milkman, Max H. Bazerman and Lisa Sutherland

Research over the last several decades indicates the failure of existing nutritional labels to substantially improve the healthiness of consumers' food and beverage choices. The difficulty for policy-makers is to encapsulate a wide body of scientific knowledge in a... View Details

Keywords: Judgments; Food; Nutrition; Labels; Knowledge Use and Leverage; Demand and Consumers; Measurement and Metrics; Mathematical Methods

Find at Harvard

1 Dec 1998
Conference Presentation

An Introduction to Mixed Models in SAS

By: William B. Simpson

Keywords: Applications and Software; Mathematical Methods

August 2020 (Revised September 2020)
Technical Note

Assessing Prediction Accuracy of Machine Learning Models

By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne

The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details

Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods

Educators

2008
Chapter

Corporate Honesty and Business Education: A Behavioral Model

By: Rakesh Khurana and Herbert Gintis

Since the mid-1970s neoclassical economic theory has dominated business school thinking and teaching in dealing with the nature of human motivation. However valuable in understanding competitive product and financial markets, neoclassical economic theory employs an... View Details

Keywords: Business Education; Ethics; Managerial Roles; Corporate Social Responsibility and Impact; Organizational Culture; Business and Shareholder Relations; Mathematical Methods; Behavior