When does entrepreneurship broaden scientists’ careers beyond economic impact?

Last registered on September 19, 2022


Trial Information

General Information

When does entrepreneurship broaden scientists’ careers beyond economic impact?
Initial registration date
September 14, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 19, 2022, 4:16 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.


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Primary Investigator

University of Stuttgart

Other Primary Investigator(s)

PI Affiliation
University of Stuttgart
PI Affiliation
University of Stuttgart

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Early-stage researchers (ESRs - PhDs and Post-docs) are repeatedly touted as an untapped source of high-potential entrepreneurship. However, most entrepreneurship initiatives have either focused on undergraduate students or on consolidated scientists (PIs and professors). We argue that attempts to translate these initiatives to engage early-stage researchers (ESRs) are missing the positive impact of entrepreneurship beyond the direct commercialization of scientific outputs.

In this experiment we aim to achieve two objectives: 1) establish and measure the effect size of a narrow view of entrepreneurship as a linear – patent-centric – science commercialization path for ESRs, and 2) identify to what extent framing the alignment between ESRs’ social identity and the framing of an entrepreneurship training intervention can increase the likelihood of a) engaging in entrepreneurial training activities, b) the adherence to such activities.
External Link(s)

Registration Citation

Giones, Ferran, Kathrin Lichius and Andreas Wahl. 2022. "When does entrepreneurship broaden scientists’ careers beyond economic impact?." AEA RCT Registry. September 19. https://doi.org/10.1257/rct.10039-1.0
Sponsors & Partners

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Experimental Details


We use two interrelated framing interventions.
1) email content manipulation, where participants receive an invitation to be informed about either a narrow or broad entrepreneurship training program.
2) matching intervention, an invitation (also via email) to take part in an entrepreneurship training offer that matches (or not) the entrepreneurial identity of the subject.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Uptake in an entrepreneurship training program aimed at early-stage researchers. We want to understand the effect size of an alternative framing for the intention to participate or interest, and then also understand the uptake to the program depending on a matching or non-matching offer.
Primary Outcomes (explanation)
Intention to participate,
Uptake in the program,

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
1) email content manipulation, part of the subjects (stratified randomization - by department/institute) receive information that describes the entrepreneurship training program information as the beginning of a journey towards commercialization of science (business as usual), and the other subjects receive information that describes the program as a career enabler (treatment), with a broad understanding of entrepreneurship including societal and economic impact. We will be distributing the email to the sample, tracking their response (opt-in), considering if they received a broad or narrow message. For those participants that opt-in, we will send a questionnaire to identify their entrepreneurial identity (Sieger et al. 2016 JBV), their views on entrepreneurship orientation (adapting Lam 2011 RP), and essential descriptive data of the individual. This will be used in the second experiment.
2) matching intervention, part of the subjects will receive a training offer with framing and content that matches their entrepreneurial identity (narrow - economic focus / broad - career and societal impact), and part of the subjects will receive a non-matching offer. For this we will be using the survey data to characterize the subjects as aligned with a narrow - economic impact - view of entrepreneurship in science, or those with a broader entrepreneurial identity. We will be randomizing the matching non-matching to ensure that about 70% get a matching offer and 30% get a non-matching offer. We will then follow the actual enrollment in the program (yes / no), and their adherence: complete more than 60% of the suggested workshops or activities (4-5 activities in each of the offers) in the following 6 months.
Experimental Design Details
Not available
Randomization Method
Initial randomization by computer, 50%. Matching randomization 70/30% also by computer.
Randomization Unit
Randomization (stratified) planned by institute (group-level cluster) in the first sub-experiment. Randomized at individual (cluster by identity profile) level for the second sub-experiment, matching or non-matching offer.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
150 institutes
Sample size: planned number of observations
1800 early-stage researchers, including phds and postdocs.
Sample size (or number of clusters) by treatment arms
Balanced 50% of the planned number of participants (max. 900) in each arm for the email intervention. Unbalanced (70%/30%) for the matching (max. 1260) vs non-matching (max. 540) randomization training offer.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
In our first experiment, we will be using the opt-in response as the main outcome. Based on similar types of treatments (see Guzmann, Oh and Sen 2020 - MS) we expect to see a 25%-30% difference between the narrow and broad framing of the program. As the first intervention is only to opt-in to get more information we anticipate an incidence of 15% for the narrow group and a 25% for the broad group. With a Power of 0.8 and an Alpha of 0.05, we should reach at least 500 individuals (250 for each group). Using the estimation tool developed by Rosner B. Fundamentals of Biostatistics. 7th ed. Boston, MA: Brooks/Cole; 2011. For the second experiment, we expect a higher individual incidence rate (matching - 45%, non-matching 25%). For this effect size, we would then have to make sure to recruit over 180 subjects. We used the same estimation tool for the sample size to be able to detect the expected treatment effect (Rosner B. Fundamentals of Biostatistics. 7th ed. Boston, MA: Brooks/Cole; 2011).

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number