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Training Entrepreneurs to Act like Scientists: A Field Experiment with Start-ups in Turin
Last registered on October 13, 2020

Pre-Trial

Trial Information
General Information
Title
Training Entrepreneurs to Act like Scientists: A Field Experiment with Start-ups in Turin
RCT ID
AEARCTR-0006579
Initial registration date
October 11, 2020
Last updated
October 13, 2020 9:14 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
INSEAD
Other Primary Investigator(s)
PI Affiliation
Politecnico di Torino
PI Affiliation
Politecnico di Torino
PI Affiliation
Politecnico di Torino
PI Affiliation
Politecnico di Torino
PI Affiliation
Bocconi University
PI Affiliation
Bocconi University
Additional Trial Information
Status
Completed
Start date
2018-07-01
End date
2019-02-28
Secondary IDs
Abstract
This project studies how a scientific approach to entrepreneurial decision-making impacts start-up performance of entrepreneurs with a background in science. We argue that entrepreneurs with a background in science apply more effectively the scientific approach in a business context, since they can exploit their prior knowledge of the scientific method that they learnt in the context of natural sciences. More specifically, we expect that entrepreneurs with a background in science who learn about the scientific approach: (i) exit more, (ii) pivot more and (iii) earn more revenue than other entrepreneurs. To test our predictions, we embed a field experiment into a pre-accelerator program and use this setting to randomly assign entrepreneurial teams to either learn about a scientific approach or not.
External Link(s)
Registration Citation
Citation
Battaglia, Daniele et al. 2020. "Training Entrepreneurs to Act like Scientists: A Field Experiment with Start-ups in Turin." AEA RCT Registry. October 13. https://doi.org/10.1257/rct.6579-1.0.
Experimental Details
Interventions
Intervention(s)
In order to replicate previous work exploring the relationships between the scientific approach to decision-making and entrepreneurial performance, we replicate the experimental settings presented in Camuffo et al. (2019) and Camuffo et al. (2020). Accordingly, we embed a field experiment in a pre-accelerator program by randomly assigning entrepreneurs to either a treatment (being taught how to use a scientific approach when developing a business idea) or a control group (being taught how to develop a business idea).
This pre-accelerator program provides training to early-stage entrepreneurs for a short period of time (three months). Consistently with previous studies, we targeted early-stage entrepreneurs. After a call for application, that resulted in a total of 149 applications, we selected 142 start-ups. Through STATA, each start-up was randomly assigned to either a treatment or a control group through simple randomization. We checked that treatment (71 start-ups) and control groups (71 start-ups) were balanced on several key covariates that might affect the absorption of the treatment and subsequent outcomes. Differences between treatment and control are small in magnitude, and there are no significant differences between the two groups.
Treated and control teams have been trained during eight sessions from October 2018 to February 2019 (24 hours of training for each group). Consistently with the training supplied by Camuffo et al. (2019), our pre-accelerator program focused on market validation, a series of activities aimed at testing the desirability of a product or service concept against a potential target market. The content and length of each session was the same for both groups, but start-ups in the treatment group were taught how to make entrepreneurial decisions according to the scientific approach. In each class of the treatment group, start-ups were taught to elaborate a theory behind their choices, articulate hypotheses and test them rigorously. The control group, instead, did not learn about the scientific approach, but followed the traditional approach to decision-making used by entrepreneurs, that relies on trial-and-error techniques. We avoid contamination and other threats to internal validity following the same approach used by Camuffo et al. (2019).
Intervention Start Date
2018-10-13
Intervention End Date
2019-01-19
Primary Outcomes
Primary Outcomes (end points)
Dependent Variables
Exit This is a binary variable equal to 0 until entrepreneurs exit (they abandon the program and cease their start-up), 1 when entrepreneurs decide to exit.
Pivot: This is the cumulative number of times in which a start-up changed one of the key elements of their business model canvas.
Revenue: Amount of revenue earned by the start-up.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
EXPERIMENTAL DESIGN
In order to replicate previous work exploring the relationships between the scientific approach to decision-making and entrepreneurial performance, we replicate the experimental settings presented in Camuffo et al. (2019) and Camuffo et al. (2020). Accordingly, we embed a field experiment in a pre-accelerator program by randomly assigning entrepreneurs to either a treatment (being taught how to use a scientific approach when developing a business idea) or a control group (being taught how to develop a business idea).
This pre-accelerator program provides training to early-stage entrepreneurs for a short period of time (three months). Consistently with previous studies, we targeted early-stage entrepreneurs. After a call for application, that resulted in a total of 149 applications, we selected 142 start-ups. Through STATA, each start-up was randomly assigned to either a treatment or a control group through simple randomization. We checked that treatment (71 start-ups) and control groups (71 start-ups) were balanced on several key covariates that might affect the absorption of the treatment and subsequent outcomes. Differences between treatment and control are small in magnitude, and there are no significant differences between the two groups.
Treated and control teams have been trained during eight sessions from October 2018 to February 2019 (24 hours of training for each group). Consistently with the training supplied by Camuffo et al. (2019), our pre-accelerator program focused on market validation, a series of activities aimed at testing the desirability of a product or service concept against a potential target market. The content and length of each session was the same for both groups, but start-ups in the treatment group were taught how to make entrepreneurial decisions according to the scientific approach. In each class of the treatment group, start-ups were taught to elaborate a theory behind their choices, articulate hypotheses and test them rigorously. The control group, instead, did not learn about the scientific approach, but followed the traditional approach to decision-making used by entrepreneurs, that relies on trial-and-error techniques. We avoid contamination and other threats to internal validity following the same approach used by Camuffo et al. (2019).
Data Collection procedure
Consistently with previous studies, we collected detailed information on all the entrepreneurs using telephone interviews. Consistently with Camuffo et al. (2019), we conducted regular telephone interviews with each start-up. Each Telephone interview usually lasted for about 30 minutes and included questions on changes in the entrepreneurial team, about the activities conducted and on performance. Through these calls, we are able to measure if entrepreneurs abandon their business idea or if they pivot to a different one. We conducted telephone interviews from the end of the training up to February 2020 (17 data collection points, one more data collection point is scheduled for March 2020) on all the 132 start-ups that completed the pre-accelerator program.
Experimental Design Details
Randomization Method
Simple randomization implemented with STATA
Randomization Unit
Firm
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
NA
Sample size: planned number of observations
132 X 18 = 2376
Sample size (or number of clusters) by treatment arms
66 firms in the treatment group, 66 firms in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Bocconi University IRB
IRB Approval Date
2018-09-30
IRB Approval Number
N/A
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS