Framing of Seeker-Generated Information and New Solver Participation in Open Innovation Contests: An Empirical Analysis of the Temporal Effects

Open innovation contests are dynamic, allowing new solvers to enter at any point before the deadline, and their participation can be influenced by seeker-generated information (SGI), which is publicly accessible to all solvers. Whereas prior literature has primarily examined solver participation among existing participants in a contest, we shift our focus to potential solvers who have not yet joined. Building on evaluation latitude theory, we identify two dimensions of SGI framing when seekers specify their expectations: the extent of preference disclosure and the latitude of rejection (i.e., defining boundaries for design elements deemed unacceptable). Drawing on construal level theory (CLT), this study investigates how these two dimensions of SGI framing influence new solver entry and how these effects vary with the number of remaining days in the contest. Using a comprehensive data set from an open innovation contest platform, this research employs various text-mining techniques to construct measures and conducts contest-day-level analyses with multiple estimation strategies. Our findings indicate that extensive preference disclosure increases the daily influx of new solvers, and this effect becomes stronger as the number of remaining days decreases. Additionally, a wide latitude of rejection initially deters but later encourages solver participation as the deadline nears. These results offer actionable insights into how seekers can strategically frame SGI at different contest stages to enhance solver participation in open innovation contests.

History: Xiaoquan (Michael) Zhang, Senior Editor; De Liu, Associate Editor.

Funding: N. Zhang acknowledges support from the National Natural Science Foundation of China [Grants 72302053 and 72271058].

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2017.0320.