Comparing Different Approaches to Entrepreneurial Learning: A Field Experiment in Pakistan

Last registered on September 20, 2023


Trial Information

General Information

Comparing Different Approaches to Entrepreneurial Learning: A Field Experiment in Pakistan
Initial registration date
September 17, 2023

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 20, 2023, 10:56 AM EDT

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


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Primary Investigator


Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Failure is widely acknowledged as a critical component of the organizational learning and innovation processs. Learning from failure, in particular, seems extremely relevant in the context of entrepreneurship, where failure often emerges as the predominant outcome. Remarkably, most entrepreneurship training programs predominantly emphasize success stories of entrepreneurs, without leveraging the learning potential that come from stories of failure. Consequently, we investigate how entrepreneurs assimilate lessons from the failure of others differently compared to the success of others and, subsequently, how these distinct learning approaches impact the decisions entrepreneurs make about their businesses.

To investigate this research question, we conduct a randomized controlled trial (RCT) aimed at providing robust empirical evidence and assessing the effects of adopting a "learning from failure" approach vis-à-vis the conventional "learning from success" approach.
In this study, about 300 entrepreneurs participate to a training program focused on market validation with the same structure: we utilize robust frameworks and tools commonly employed in entrepreneurial education, we provide practical examples from other founders, we facilitate discussions on essential thematic elements, and provide opportunities for participants to reflect on the content. However, frameworks, examples, discussions, and self-reflections focus on learning from the failure of others for one group (half of the participants), and on learning from the success of others for the other group (half of the participants). Our expectation is that both types of training will benefit entrepreneurs but in different ways. We will measure outcomes related to both entrepreneurial intentions, actions, and decision-making processes to gain deeper insights into how distinct learning methodologies influence the development of new businesses.
External Link(s)

Registration Citation

Apostoloski, Nenad and Chiara Spina. 2023. "Comparing Different Approaches to Entrepreneurial Learning: A Field Experiment in Pakistan." AEA RCT Registry. September 20.
Sponsors & Partners

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Experimental Details


Participants will receive 7 sessions of in-person training. These sessions will include interactive lectures and coaching by qualified mentors/instructors each working with a subset of the sample to ensure small interactive sessions. Treated and control startups will receive the same amount of training on market validation (on topics like business model canvas, customers' interviews, minimum viable products/services, etc.). One group will be taught using key themes, insights, robust frameworks and examples of entrepreneurial success. Another group of treated startups will be taught using key themes, insights, robust frameworks and examples of entrepreneurial failure.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
We are interested in the performance of the new businesses as a primary outcome. Having in mind the complexity of measuring the performance of new businesses we are basing our outcomes on key steps of the entrepreneurial development process. This includes intentions (i.e., intention to close business, to pivot, to make revenue, etc.) as an important precursor to action and the actual actions taken (closing the business, pivoting, making revenue) of the entrepreneurs.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We are also interested in understanding whether the exposure to different training affects other outcomes related to psychological constructs:
- Entrepreneurial Persistence,
- Entrepreneurial Self-Efficacy, and
- Entrepreneurial Passion
- Optimism
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The RCT focuses on early-stage entrepreneurs without restrictions in terms of industries. We advertise the program through digital channels as a general course overseeing all the important aspects of market validation. The course is free of charge in order to ensure the participation of those with limited financial resources. Entrepreneurs receive training in-person. The same amount of training is offered to the two groups in order to ensure comparability. Multiple instructors/coaches will be trained to deliver the training using standard materials, purposely designed. Each instructor/coach teaches two classes (one subgroup of startups treated with the learning from failure approach, and one subgroup of startups treated with the learning from success approach). The research team designs, coordinates and oversees all the activities, ensuring that the learning modules and coaching activities are appropriately carried out by the instructors/coaches.
Experimental Design Details
Not available
Randomization Method
Pure parallel randomization, done by a computer using STATA. After being randomly assigned into one of the two groups (control or treatment), multiple subgroups of startups (of about 25 startups) will be created and randomly matched with the instructors/coaches so that each instructor/coach teaches two subgroups - of approximately 25 startups. Randomization checks: mean values comparison and t-tests across groups.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Not clustered
Sample size: planned number of observations
300 businesses X 12 observations = 3600 observations
Sample size (or number of clusters) by treatment arms
300 startups (150 in the treatment group, 150 in the control group)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number