Reframing entrepreneurship for early-career researchers

We use two interrelated framing interventions.
1) email content manipulation, where participants receive an invitation to be informed about a training program.
2) landing page that presents information about the program, with alternative framing and a registration button to receive further information.

2023-09-18

2023-11-24

We want to understand the effect size of a broader, collaborative - impact-focused - framing of entrepreneurship by capturing their preference for this condition instead of the current individual and narrower representation.

Rising awareness of entrepreneurship as a career option for those currently in a scientific career.

1) email content manipulation, with stratified randomization - by department/institute. Individuals receive information that describes the training program as the beginning of a journey towards commercialization of science (business as usual), and the other subjects receive information that portrays the program as a a program to make an impact with their research (treatment), it has a broad understanding of entrepreneurship with a focus on impact. We will be distributing the email to the sample, tracking their response (opt-in), controlling the message they received. We will also send a questionnaire to identify their entrepreneurial identity (Sieger et al. 2016 JBV), their growth mindset (Schmitt 2022), and impulsivity (Barratt 1994) and essential descriptive data of the individual.
2) Correspondance intervention, we will be using different texts in a landing page, with more information about the program. Presenting entrepreneurship as a) an individual behavior (business as usual) suggesting a match with what makes also science and research work successful; or as b) a collaborative behavior (treatment), where tasks and activities have to be shared with a group of people, suggesting that this is also the case in succesful scientific projects.

In both cases, we are running a stratified randomization (50%/50% for every condition) inside each institute/department.

Not available

Randomization done by computer, balanced weights, 50%.

Randomization (stratified) planned by institute (group-level cluster).

Yes

150 institutes

2300 early-career researchers (PhD students and Post-docs)

We expect an equal distribution - 50% of the planned number of individual participants (max. 1000) in each arm for the interventions.

In the email manipulation and landing page, we will be using the "more information" or "keep me updated" response as the main outcome. Based on similar types of treatments (see Guzmann, Oh & Sen 2020 - MS), and the first version of this experiment run in 2022, we expect to see a 25%-30% difference between the economic and social/impact framing of the program. Also for the individual vs. collective framing. This is because we have increased the text distinctiveness (calculating the cosine similarity), and believe that our treatment is now stronger that in the version of 2022. As in both interventions, it is only an "opt-in" to get more information or stay updated, we anticipate an incidence of 15% for the business-as-usual conditions and a 25% for the treatment conditions. With a Power of 0.8 and an Alpha of 0.05, we should reach at least 500 individuals (250 for each condition). Using the estimation tool developed by Rosner B. Fundamentals of Biostatistics. 7th ed. Boston, MA: Brooks/Cole; 2011.