Secondary Outcomes (explanation)
Students will be encouraged to form partnerships via a “speed dating” exercise where the students sequentially meet potential partners to discuss possible collaboration. For each meeting, students will evaluate potential partners’ quality on a Likert scale of very low, low, medium, high, very high:
Shared vision for business
Partner’s Ability to execute
Fit between your skills/resources and your partner’s
Equity split Arrangement Game/Exercises and Matching Outcomes
The treatments will be short video lectures presenting one of two perspectives on equity splits in startups. The equal-splits treatment will feature a video advocating the “1/N rule”—that each founder should receive an equal stake in the company and its profits. Students will be provided with the arguments frequently cited for this division rule: that equity is an incentive so small stakes should be avoided, that uncertainty about future roles and productivity make it hard to predict appropriate shares, and that unequal splits go against basic notions of fairness and can sour your relationship with your cofounder from the beginning.
The unequal-splits treatment will feature a video advocating a formal pie slicing approach—that the founders should give a numerical score to their value added along several dimensions—initial idea, business plan development, domain expertise, commitment & risk, and day-to-day responsibilities—assign weights to each dimension, and use the averaged scores as a starting point to discuss an equity split. Students will be provided with the arguments frequently cited for this division rule: that effort and value added will rarely be equal, so equal splits can create friction as asymmetries become clear; that founders often bring capital to the table or work without pay while the other founder keeps their day job, rationalizing a greater share.
The unequal-splits treatment video will illustrate an excel implementation of the pie slicing activity, which the students in this treatment will perform with their partner later in the program.
Finally, we will estimates heterogeneous effects based on race, work-related dimensions and personality (using the big five taxonomy).