Author
Listed:
- Hongchuan Shen
(Faculty of Business Administration, University of Macau, Macau, China)
- Chu (Ivy) Dang
(Faculty of Business and Economics, The University of Hong Kong, Hong Kong)
- Xiaoquan (Michael) Zhang
(Department of Decision Sciences and Managerial Economics, Business School, Chinese University of Hong Kong, Hong Kong; Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing 100084, China)
Abstract
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.
Suggested Citation
Hongchuan Shen & Chu (Ivy) Dang & Xiaoquan (Michael) Zhang, 2024.
"Mr. Right or Mr. Best: The Role of Information Under Preference Mismatch in Online Dating,"
Information Systems Research, INFORMS, vol. 35(4), pages 2013-2029, December.
Handle:
RePEc:inm:orisre:v:35:y:2024:i:4:p:2013-2029
DOI: 10.1287/isre.2022.0233
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:35:y:2024:i:4:p:2013-2029. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.