Latest Research Publications

We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, that is, unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short-term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short-sales constraints. We identify the information driving return predictability through content-based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information. Supporting Information

Problem definition: Content promotion policies are crucial for online content platforms to improve content consumption and user engagement. However, traditional promotion policies generally neglect the diffusion effect within a crowd of users. In this paper, we study the candidate generation and promotion optimization (CGPO) problem for an online content platform, emphasizing the incorporation of the diffusion effect. Methodology/results: We propose a diffusion model that incorporates platform promotion decisions to characterize the adoption process of online content. Based on this diffusion model, we formulate the CGPO problem as a mixed-integer program with nonconvex and nonlinear constraints, which is proved to be NP-hard. Additionally, we investigate methods for estimating the diffusion model parameters using available online platform data and introduce novel double ordinary least squares (D-OLS) estimators. We prove the submodularity of the objective function for the CGPO problem, which enables us to find an efficient (1−1/𝑒) -approximation greedy solution. Furthermore, we demonstrate that the D-OLS estimators are consistent and have smaller asymptotic variances than traditional ordinary least squares estimators. By utilizing real data from a large-scale video-sharing platform, we show that our diffusion model effectively characterizes the adoption process of online content. Compared with the policy implemented on the platform, our proposed promotion policy increases total adoptions by 49.90%. Managerial implications: Our research highlights the essential role of diffusion in online content and provides actionable insights for online content platforms to optimize their content promotion policies by leveraging our diffusion model.

This paper examines how the worship of ancient wisdom affects economic progress in historical China, where the learned class embraced classical wisdom for millennia but encountered the shock of Western industrial influence in the mid-nineteenth century. Using the number of sage temples to measure the strength of classical worship in 269 prefectures, I find that classical worship discouraged intellectuals from appreciating modern learning and thus inhibited industrialization between 1858 and 1927. By contrast, industrialization grew faster in regions less constrained by classicism. This finding implies the importance of cultural entrepreneurship, or the lack thereof, in shaping modern economic growth. “The humor of blaming the present, and admiring the past, is strongly rooted in human nature, and has an influence even on persons endued with the profoundest judgment and most extensive learning.” —David Hume (1754, p. 464).

Using firm-level earnings forecasts and managerial guidance data, we construct guidance surprises for analysts, i.e., differences between managerial guidance and analysts' initial forecasts. We document new evidence on expectation formation: (i) analysts overreact to managerial guidance and the overreaction is state-dependent, i.e., it is stronger for negative guidance surprises but weaker for surprises that are larger in size; and (ii) forecast revisions are neither symmetric in guidance surprises nor monotonic. We organize these facts with a model where analysts are uncertain about the quality of managerial guidance. We show that a reasonable degree of ambiguity aversion is necessary to account for the documented heterogeneous overreaction pattern.

Many consumers are caregivers and, as part of caregiving, frequently make food choices for their dependents. This research examines how food choices made for children influence the healthiness of parents’ subsequent self-choices. Whereas prior work focuses on choices for the self (others) as based on self-needs (other-needs), the authors theorize when and why self-choices involve consideration of other-needs. Five studies, including a nursery school field study, test the effect of choosing healthy food for a child on the healthiness of parents’ self-choices, focusing on the role of anticipating potentially sharing self-choices with one's child. Potential sharing increased parents’ likelihood of making an unhealthy subsequent self-choice if they first made a healthy choice for their child. This effect was driven by parents’ present-focused parenting concerns about whether one's child would eat and enjoy healthy options chosen for them. This effect was mitigated when parents instead had future-focused parenting concerns. Additionally, this effect was mitigated after making an initial choice for the child that was (1) unhealthy or (2) healthy but relatively liked by the child. This research contributes to understanding how choices for others shape choices for the self and offers important marketing and policy implications.

Media platforms generate revenue by bringing consumers and advertisers together. Although advertisers like to promote their services and products to consumers, consumers dislike advertisements to varying levels. Given heterogeneity in consumers’ dislike for ads, platforms could adopt either a uniform pricing strategy or a tiered pricing strategy for consumers. In this paper, we examine competing media platforms’ equilibrium pricing strategies in the presence of cross-side externalities between consumers and advertisers and their endogenous homing decisions. We find that symmetric platforms may adopt asymmetric pricing strategies in an attempt to focus on different sides of the market and soften interplatform competition if the incremental value that consumers derive from multihoming is large. However, they pursue only symmetric pricing strategies if this value is small. Counter to the intuition based on one-sided markets, our analysis shows that tiered pricing strategies need not improve the profits of platforms competing in a media market. In fact, when the incremental value that consumers derive from multihoming is large, competing platforms may earn lower profits from tiered pricing and yet pursue it (Prisoner’s dilemma). In contrast to standard results on tiered prices, we find that high-type consumers may not pay as much as their full willingness-to-pay for ad avoidance, implying that the incentive-compatibility constraint of high-type consumers may not be binding. Finally, we extend the model to allow for heterogeneous advertisers, vary the decision sequence, permit platforms to compete on ad capacity (rather than ad price), entertain an alternative formulation of transportation cost, and consider correlated advertising reach.

This work provides performance guarantees for solving data-driven contextual newsvendor problems when the contextual data contains intertemporal dependence and non-stationarities. While machine learning tools have observed increasing use in data-driven inventory management problems, most of the existing work assumes that the contextual data are independent and identically distributed (often referred to as i.i.d.). However, such assumptions are often violated in real operational environments where the contextual data are sequentially generated with intertemporal correlations and possible non-stationarities. By accommodating these naturally arising operational environments, our work adopts comparatively more realistic assumptions and develops out-of-sample performance bounds for learning data-driven contextual newsvendor problems.

This paper studies a dynamic principal–agent setting in which the principal needs to dynamically schedule an agent to work or be suspended. When the agent is directed to work and exert effort, the arrival rate of a Poisson process is increased, which increases the principal’s payoff. Suspension, on the other hand, serves as a threat to the agent by delaying future payments. A key feature of our setting is a switching cost whenever the suspension stops and the work starts again. We formulate the problem as an optimal control model with switching and fully characterize the optimal control policies/contract structures under different parameter settings. Our analysis shows that, when the switching cost is not too high, the optimal contract demonstrates a generalized control-band structure. The length of each suspension episode, on the other hand, is fixed. Overall, the optimal contract is easy to describe, compute, and implement.

The current research examines the relationship between crowding and consumers’ responsiveness to sales promotions. Six studies show that the experience and feeling of crowdedness reduce the impact of sales promotions, demonstrating that consumers’ product/service purchase intention changes to a lesser extent in response to such promotions. This effect is found to be driven by consumers shifting their attention from the external environment to their internal feelings and thoughts when experiencing crowdedness. As a result, consumers rely more on their internal feelings and thoughts than on external cues in judgment, and consequently their purchase intention becomes less susceptible to external sales promotion information. In addition, this effect is found to be attenuated in situations where product attitudes are detached from consumers’ own preferences, such as in the context of gift choices, and when the experience of crowding is not aversive (e.g., watching an exciting football game in a bar).