We study a continuous-time reputation game in which an informed player bene ts from persistent private information while an uninformed player suffers from it. Observing noisy signals of the informed player's actions, the uninformed player chooses when to reveal the informed player's private...

Cyber-insecurity is a serious threat in the digital world. In the present paper, we argue that a suboptimal cybersecurity environment is partly due to organizations’ underinvestment and a lack of suitable policies. The motivation for this paper stems from a related policy question: how to...

Recently, mobile applications have offered users the option to share their location information with friends. Using data from a major location-based social networking application in China, we estimate an empirical model of restaurant discovery and observational learning. The unique feature of...

This paper investigates predictions of structural credit risk models for interest rate sensitivities of corporate bond returns. Recent evidence has shown that the existing models fail to capture this sensitivity (a stylized fact referred to as the interest rate sensitivity puzzle). We propose...

We analyze the spillover effects of the online reviews of other co-visited products on the purchases of a focal product using clickstream data from a large retailer. Drawing upon signaling theory, as online reviews serve as signals, the proposed spillover effects are moderated by: (a) whether...

We propose a model of price competition in which firms select prices conditional on privately-observed production costs and a subset of consumers can choose to search sequentially given price dispersion. In the model, we investigate how competition affects the consumers’ choice of whether to...

Slandering of a firm’s products by competing firms poses significant threats to the victim firm. The resulting damage can be as large as the one from a product-harm crisis. Unlike a true product-harm crisis, the disparagement is based on a false claim, thus we call it a pseudo-product-harm...

We demonstrate the value of machine learning in accounting through a detailed examination of litigation risk, an important and frequently used estimate in the literature. We evaluate a comprehensive set of twelve machine learning techniques and benchmark their performance against the logistic...