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The rise of two-sided matching platforms such as Uber, Airbnb, Upwork, and Tinder has changed the way we commute, travel, work, and even date. The success of these platforms depends on the role of information: What information and how much information should be provided? In this study, we focus on a defining characteristic of two-sided matching markets—that is, a match depends on the possibly different preferences of the two sides—and argue that the optimal amount of information released depends on the extent to which the preferences of the two sides are mismatched. Specifically, in an empirical context of online dating, we find that when there exists preference mismatch between the two sides, having less match-relevant information about the other side leads to a better matching outcome. Our study provides insights into how the amount of information available to each side affects matching outcomes on two-sided platforms and offers guidance on information design strategies. Additionally, our findings are not confined to dating websites and can be extended to other matching platforms, such as Airbnb and Upwork, where misaligned preferences can exist between the two sides. This paper examines the role of information in two-sided matching markets where preference mismatch is present. Two-sided markets are characterized by different preferences of the parties involved, and a match occurs when both sides show a preference for each other. In practice, however, there is often a preference mismatch. In this study, we use a large data set from an online dating website to provide empirical evidence for preference mismatch in the field. We also develop empirical models to investigate the impact of information under preference mismatch by analyzing variations in the amount of available information. Specifically, we compare partial and complete information contained in the users' short and long profiles, respectively. We find that more information about the other side does not necessarily improve the likelihood of a match. In fact, the side making the proposal has a better chance of matching if the decision is based on the information contained in the short profile rather than the long profile. This suggests that users are better off seeing partial rather than complete information about the candidates, a phenomenon we refer to as the "less information is more" effect. Our empirical analysis shows that this effect is driven by the mismatched preferences of the two sides. These results imply that there is an optimal amount of information that one side should possess about the other before making a proposal. Our study highlights the importance of optimal information design strategies to determine the appropriate amount of information that should be provided to each side. Our findings also offer managerial implications regarding information provision strategies for online platforms in general. History: Pei-Yu Chen, Senior Editor; Xitong Li, Associate Editor. Funding: This work was supported by the University of Macau [Grant SRG2023-00023-FBA] and the Research Grants Council of Hong Kong, University Grants Committee [Grants ECS 27504221, GRF 14500521, GRF 14501320, GRF 14503818, GRF 165052947, PDFS 2021-4H04, TRS:T31-604/18-N]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.0233. [ABSTRACT FROM AUTHOR]

We develop a technology based on competitive adsorption between drug molecules and water, specifically designed to address the critical issue of poor drug solubility. By specially engineering silica nanosurfaces with ultrahigh densities of silanol, we significantly enhance their affinity for both drug molecules and water, with a notably greater increase in water affinity. Such surfaces can effectively adsorb a variety of drug molecules under dry conditions. Upon exposure to water, these surfaces preferentially bind to water molecules, initiating a competitive adsorption process with the drug molecules. This competitive process turns water molecules from obstacles into catalysts for drug dissolution by actively displacing drug molecules from the surface, causing their rapid desorption and potentially enhancing their solubility by two to three orders of magnitude. The method is general, applicable to a wide array of drugs, stable for long-time storage, cost-effective, and scalable for mass production. Consequently, it has the potential to emerge as a next-generation platform for drug formulation and delivery., Competing Interests: Competing interests statement:Z. X., D. W. and L. X. are co-founders of the startup company PharmaEase Tech Limited and own some equity., Yes, the authors have patent filings to disclose, Z. X. is the author of a filed China patent no. 202411494974.X and a filed PCT no. PCT/CN2024/128187, which describe the methods used herein.