- 著者
-
土橋 力也
- 出版者
- 日本経営学会
- 雑誌
- 日本経営学会誌 (ISSN:18820271)
- 巻号頁・発行日
- vol.43, pp.3-14, 2019 (Released:2020-11-01)
- 参考文献数
- 38
Scholars in the fields of management and economics note the importance of gaining users and achieving network effects in online C2C platforms (OCP). Although the extant literature stresses the importance of network effects and the “quantity” of users, another important factor in OCP—the “quality” of users—is often ignored. Poor quality users harm the platform's reputation; their presence makes potential users hesitant to join it. Thus, we thus build a framework for managing users' quality in OCP, and, then, analyze how managing users' quality affects trust in C2C platforms and the transaction intention of users. We build a framework for analyzing users' quality with two pairs of influential factors: ex-ante and ex-post, and top and bottom users. These two pairs lead to four quadrants. Quadrant 1 has ex-ante and bottom users; it signifies platform firms' behavior to restrict bad users from joining by ex-ante screening (entrance fees or some qualifications). Quadrant 2, which is ex-ante and top, signifies how platform firms attract superstars. Quadrant 3 is ex-post and top and signifies how platform firms educate and finally convert normal users to loyal ones. Quadrant 4—ex-post and bottom users—signifies how platform firms find users that satisfy their criteria; this helps to exclude the bad users already present on the platform. To analyze this framework, the present study analyzes data obtained from OCP users of Mercari and Airbnb by distributing 461 questionnaires (Mercari n=242, Airbnb n=219) through a research company. We find that: (1) controlling bottom users (limited participation) increases trust in C2C platforms, and (2) controlling top users (favorable treatment for high quality users) increases the transaction intention of users. This paper highlights the issue of users' quality in OCP by building a framework for managing it—something prior research neglected by focusing on network effects.