Latest Research Publications

Manufacturers often preannounce reference prices for products that have not yet been produced or even developed. These prices are rarely binding, meaning that the manufacturers can make price adjustments in the future, possibly at a cost. In this paper, we argue that price preannouncements can serve as a weak price commitment that, we find, helps the manufacturers secure better deals from their suppliers, thereby lowering their procurement costs and improving their profit. Surprisingly, even an extremely weak price commitment can substantially improve a manufacturer’s profit. On the other hand, when the price commitment is credible enough, the manufacturer forgoes the price preannouncement. Collectively, these results underscore the strategic effects that price preannouncements can have on firms’ marketing decisions.

How does the balance between text and pictorial content in marketer-generated social media posts affect user engagement? The authors address this question by using computer vision and natural language processing tools to extract the visual and textual features of 34,610 organic brand posts from Facebook and Instagram. Using a Confounding-and-Cluster-Robust Causal Forests model, they test how the balance of text and picture affects social media engagement across content and visual contexts. Results show that posts with greater emphasis on overlay text over pictorial content tend to have fewer likes and comments. However, the performance of text-oriented posts improves if text is more centered, informative, emotionally positive, and congruent with the pictorial content, and if the picture contains fewer prominent objects or less information such as social cues. They quantify how incremental changes in such content composition affect social media engagement. These findings set forth evidence-based principles for optimizing text and picture balance in marketer-generated content (MGC) and provide actionable guidelines on whether, where, when, and how to present text on an image. This research highlights the potential for transforming content and media creation from an imprecise art form into an empirical science nested within a data-driven visual optimization framework.

What influences consumers to make product decisions alone versus with household partners? This research examines how consumers’ preference for solo or joint decision-making with household partners varies between product acquisition and disposal stages. Ten pre-registered studies demonstrate that for many household products, consumers are more likely to choose joint (vs. solo) decision-making with household partners for disposal than for acquisition. This asymmetry occurs because disposal (vs. acquisition) increases perceptions of the potential for infringement on a household partner’s rights, which increases the desire for clarity about a partner’s product valuation and thus the choice of joint (vs. solo) decision-making with one’s partner. The authors identify three process-consistent boundary conditions, wherein this acquisition-disposal asymmetry is mitigated: (1) when the product cannot be used by one’s partner, (2) when considering decisions with non-household members (e.g., non-cohabitating close friends) instead of one’s household partner, and (3) when the product’s price exceeds the household’s typical budget. Moreover, the authors discuss implications of this acquisition-disposal asymmetry for consumer well-being and marketing strategies, including its potential to cause delays in disposal decisions relative to acquisition decisions. This research contributes to understanding household decision dynamics and identifies a novel contributor to overaccumulation of household products.

This paper identifies a new channel through which employment protection laws can harm workers: they enable employers to exploit naïve present-biased employees. The theoretical mechanism through which firing costs enable exploitation is built upon a widespread career structure. Employers frequently offer career trajectories with an unattractive entry phase (e.g., with low pay or high effort), an even less attractive mid-career stage, and high rewards promised in a final career phase. Naïve employees accept such contracts, expecting to complete the high-reward track. They, however, eventually drop out or sort into alternative paths mid-career when costs loom large and rewards remain distant. As a result, employers avoid paying the promised rewards while capturing surplus from early-career phases. Firing costs give employers more leeway to exploit workers with such contracts: they reduce the employees’ expected risk of dismissal and make long-term rewards appear more credible. Employers can then exploit employees even more—for example, by lowering early-career wages—knowing that employees will still accept such steeper contracts despite not following through. Our model aligns with career patterns in fields such as healthcare, academia, or accounting. It also yields testable predictions on wage structures, attrition, and how firing costs and labor market conditions shape contract design.

We propose a new approach to modeling bond risk and risk premia, inspired by the equity risk-return literature, which does not impose the tight restrictions found in models that generate closed-form bond prices. We estimate the joint dynamics of the volatility and Sharpe ratio of principal-component bond-factor portfolios for the US and China. Predictors include yield curve variables and, for the US, VIX. We document complex time-varying relations between the price and quantity of interest rate risk inconsistent with the frameworks in existing studies. Interesting differences between the US and China further highlight the need for our more flexible approach.

This paper studies the performance of the spectral method in the estimation and uncertainty quantification of the unobserved preference scores of compared entities in a general and more realistic setup. Specifically, the comparison graph consists of hyper-edges of possible heterogeneous sizes, and the number of comparisons can be as low as one for a given hyper-edge. Such a setting is pervasive in real applications, circumventing the need to specify the graph randomness and the restrictive homogeneous sampling assumption imposed in the commonly used Bradley-Terry-Luce (BTL) or Plackett-Luce (PL) models. Furthermore, in scenarios where the BTL or PL models are appropriate, we unravel the relationship between the spectral estimator and the maximum likelihood estimator (MLE). We discover that a two-step spectral method, where we apply the optimal weighting estimated from the equal weighting vanilla spectral method, can achieve the same asymptotic efficiency as the MLE. Given the asymptotic distributions of the estimated preference scores, we also introduce a comprehensive framework to carry out both one-sample and two-sample ranking inferences, applicable to both fixed and random graph settings. It is noteworthy that this is the first time effective two-sample rank testing methods have been proposed. Finally, we substantiate our findings via comprehensive numerical simulations and subsequently apply our developed methodologies to perform statistical inferences for statistical journals and movie rankings.

Problem definition: As digitization transforms the service sector and empowers service platforms, questions arise about utilizing and disseminating customer information captured by digitization to enhance platform operations. We contribute by investigating how providing customer-related information at the start of a service encounter impacts both service supply and demand in the context of entertainment service platforms. Methodology/results: We conducted a field experiment on a live-streaming platform that connects hundreds of millions of viewers with individual broadcasters. For broadcasters randomly assigned to the treatment condition (but not for broadcasters in the control condition), when a viewer entered their shows, information about the viewer appeared on the screen. Our analyses, involving a random sample of 49,998 broadcasters, demonstrate that relative to control broadcasters, treatment broadcasters expanded service supply by 12.62% by increasing both show frequency (3.31%) and show length (7.10%), thus earning 10.44% more income, based on our conservative estimate. Moreover, our intervention increased service demand (measured by viewer watch time) by 4.51%. Additional analyses and surveys in our field setting and online experiments (n = 3,115) shed light on the potential mechanisms. Viewer-related information enables broadcasters to offer personalized service and vividly perceive viewers. On the demand side, viewers appreciate personalized service and interact with broadcasters more, which collectively boost demand. On the supply side, broadcasters not only enjoy the increased interaction with viewers but also feel a stronger sense of appreciation due to the more vivid mental image of viewers, which collectively lifts service supply. Managerial implications: This research suggests that providing customer-related information at the beginning of a service encounter can increase both service demand and supply. This low-cost, information-based intervention has important implications for digital service platforms that have little control over service providers’ work schedules and service quality.

Psychological empowerment plays a crucial role in motivating individuals to pursue their goals. This research explores a unique method to empower consumers in their goal pursuit: anthropomorphizing goals as dependent persons in need of care. Through three studies, including an incentive-compatible study and a field study conducted at a hypermarket, we demonstrate that viewing personal goals as dependent persons who require care and nurturance (e.g., presenting a goal as a dependent person in a health app) can significantly enhance goal pursuit (e.g., choosing healthy snacks) by boosting psychological empowerment. We find that this motivational boost does not occur when a goal is simply anthropomorphized as any person (Study 1), when it is depicted as a dependent object (Study 1), or when it is anthropomorphized as an independent person (Study 2). This research contributes to a deeper understanding of motivation in goal pursuit and offers practical implications for marketers. Specifically, by using marketing communications to frame goals as entities that require care, marketers can help individuals foster a more engaging and empowering relationship with their aspirations.

Although everyone must make decisions about where to live, we know little about how consumers perceive social interactions with neighbors and incorporate information about neighbors into their residence decisions. This article explores the impact of consumers' self-construal on the importance they attribute to neighbor information when choosing a residence. Across seven preregistered studies, including lab experiments and online surveys, the findings consistently show that independent consumers, compared with interdependent ones, place greater importance on information about potential neighbors. This tendency stems from independent consumers' stronger desire for social closeness with neighbors, prompting them to place more weight on information that will help them find neighbors with whom they could become friends.