Publications

2015
Working Paper

Match Your Own Price? Self-Matching as a Retailer's Multichannel Pricing Strategy

By: Pavel Kireyev, Vineet Kumar and Elie Ofek

Multichannel retailing has created several new strategic choices for firms. With respect to pricing, an important decision is whether to offer a "self-matching policy." Self-matching allows a multichannel retailer to offer the lowest of its online and in-store prices... View Details

Keywords: Price Self-matching; Multichannel Retailing; Pricing Strategy; Marketing Strategy; Price; Distribution Channels; Supply and Industry; Retail Industry

April 2011
Article

Institutional Tax Clienteles and Payout Policy

By: Mihir Desai and Li Jin

This paper employs heterogeneity in institutional shareholder tax characteristics to identify the relation between firm payout policy and tax incentives. Analysis of a panel of firms matched with the tax characteristics of the clients of their institutional... View Details

Keywords: Institutional Investors; Clienteles; Payout Policy; Private Equity; Investment; Taxation; Ownership Stake; Business and Shareholder Relations

2023
Working Paper

Money, Time, and Grant Design

By: Kyle Myers and Wei Yang Tham

The design of research grants has been hypothesized to be a useful tool for influencing researchers and their science. We test this by conducting two thought experiments in a nationally representative survey of academic researchers. First, we offer participants a... View Details

Keywords: Research; Power and Influence; Money

2020
Working Paper

Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus

By: David Hao Zhang and Paul Willen

We use a new methodology to assess mortgage pricing discrimination by race. We make four main contributions. First, we show that existing estimates of mortgage pricing differences by race can be confounded by a "menu problem," which is the problem associated with... View Details

Keywords: Mortgages; Financing and Loans; Prejudice and Bias; Race; Measurement and Metrics; Banking Industry; United States

2013
Working Paper

Competing by Restricting Choice: The Case of Search Platforms

By: Hanna Halaburda and Mikolaj Jan Piskorski

Seminal papers recommend that platforms in two-sided markets increase the number of complements available. We show that a two-sided platform can successfully compete by limiting the choice of potential matches it offers to its customers while charging higher prices... View Details

Keywords: Matching Platform; Indirect Network Effects; Limits To Network Effects; Decision Choices and Conditions; Network Effects; Two-Sided Platforms; Marketplace Matching; Competitive Strategy

SSRN

2013
Working Paper

Managing Firms in an Emerging Economy: Evidence from the Time Use of Indian CEOs

By: Raffaella Sadun

The success or failure of a company is often ascribed to the behavior of its CEO. Yet little is known about what top managers actually do, whether this matters for firm performance, and why it differs across firms. We provide some answers by developing a new survey... View Details

Keywords: Management Style; Performance; Outcome or Result; Management Teams; Manufacturing Industry; India

14 Aug 2018
First Look

First Look at New Research and Ideas, August 14, 2018

Psychology Preferences for Experienced Versus Remembered Happiness By: Mogilner, Cassie, and Michael I. Norton Abstract—Consider two types of happiness: one experienced on a moment-to-moment basis, the other a reflective evaluation where... View Details

Keywords: by Sean Silverthorne

March 2022
Article

Learning to Rank an Assortment of Products

By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar

We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue... View Details

Keywords: Online Learning; Product Ranking; Assortment Optimization; Learning; Internet and the Web; Product Marketing; Consumer Behavior; E-commerce

April 2021
Article

A Model of Multi-Pass Search: Price Search Across Stores and Time

By: Navid Mojir and K. Sudhir

In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across... View Details

Keywords: Consumer Search; Multi-pass Search; Price Search; Store Search; Spatial Search; Temporal Search; Spatiotemporal Search; Dynamic Structural Models; MPEC; Price Promotions; Store Loyalty; Consumer Behavior; Price; Spending; Marketing; Mathematical Methods

SSRN

March 2019
Article

A Structural Analysis of the Role of Superstars in Crowdsourcing Contests

By: Shunyuan Zhang, Param Singh and Anindya Ghose

We investigate the long-term impact of competing against superstars in crowdsourcing contests. Using a unique 50-month longitudinal panel data set on 1677 software design crowdsourcing contests, we illustrate a learning effect where participants are able to improve... View Details

Keywords: Crowdsourcing Contests; Superstar Effect; Bayesian Learning; Utility; Economics Of Information System; Dynamic Structural Model; Dynamic Programming; Markov Chain; Monte Carlo; Learning; Competition; Performance Improvement

October 2021
Article

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

By: Nicolas Padilla and 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; Programs; Consumer Behavior; Analysis

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