團隊

港大經管學院助理教授黨矗（Ivy Dang）早前針對網戀平台的偏好差異進行研究，發現執着於「夢中情人」的理想條件，可能讓用戶錯失真正合適的伴侶。她亦指出，過多的個人訊息並不一定有助於配對成功，反而可能導致用戶過早篩選潛在對象，降低配對機會。

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.

理科出身的我，非常欣賞同學們的商業觸覺。作為他們的師長，在教導他們使用數理工具作出科學判斷的同時，我亦希望能夠鼓勵他們愛上學習，保持對未知事物的好奇心，應用課堂所學到的知識為社會做出貢獻。

黨博士在大學主修應用物理學，畢業後以博士生的身份在香港研究量子物理學。因緣際會下，她發現自己真正的興趣所在—計量市場學。 2020年2月，黨博士以市場學助理教授的身份加入香港大學經管學院。理科出身的她希望將自然科學中的數理模型和歸納推理方法應用到教學和研究中，為商學教育和發展做出自己的貢獻。