Thought Leadership

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.