Managerial or entrepreneurial capital? Untangling constraints of innovative entrepreneurs

Last registered on July 07, 2024
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Pre-Trial

Trial Information

General Information

Title
Managerial or entrepreneurial capital? Untangling constraints of innovative entrepreneurs
RCT ID
AEARCTR-0008641
Initial registration date
December 27, 2021

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
December 28, 2021, 2:04 PM EST

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

Last updated
July 07, 2024, 9:53 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name
Michael Leatherbee
Affiliation
Pontificia Universidad Católica de Chile
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Other Primary Investigator(s)

PI Name
Juanita Gonzalez-Uribe
PI Affiliation
London School of Economics
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PI Name
Santiago Reyes
PI Affiliation
World Bank
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Additional Trial Information

Status
On going
Start date
2021-09-17
End date
2024-09-09
Keywords
Firms & Productivity
Additional Keywords
Entrepreneurial capital, startups, business accelerators
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Entrepreneurial support programs have been implemented over the last decades to foster innovative entrepreneurs in developed and developing countries. Usually, these programs are carried by local business accelerators that provides cash and support services in terms of training, mentorship, access to contacts, among others. While there is some evidence that this type of interventions can foster innovative entrepreneurs , it is still unknown what are the mechanisms that drive the ventures’ growth.

Gonzalez-Uribe and Reyes (2020) explores whether providing support services (training, mentorships, etc.) and no cash have an impact on ventures’ success. This paper finds that innovative entrepreneurs face different constraints besides financial ones. Entrepreneurs that received non-monetary support increased their annual sales by 66% during the three following years after the intervention. However, it is still not clear how those interventions affect the entrepreneurs. Is it because it provides them with managerial capital (a la Bloom and Van Reenen, 2010; Bruhn, Karlan, and Schoar, 2010) so they can run their businesses more efficiently? Or is it because it provides them with entrepreneurial capital (a la Gonzalez-Uribe and Leatherbee, 2018) so they can discover and capture valuable opportunities more effectively?

As well-known practitioners such as Steve Blank have declared, “new ventures are not small versions of large companies.” Implicit in this statement is the idea that the knowledge required to manage a large company is different to the knowledge required to build a new venture. In fact, it implicitly highlights the hypothesis that applying the knowledge that is effective for managing a large company to a new venture can, in fact, be detrimental. Understanding the validity of this hypotheses is paramount for all initiatives that aim at fostering the creation and development of new ventures. If providing entrepreneurs managerial capital is as –or more– effective than providing them with entrepreneurial capital, then many programs that are currently doing so should stick to the status quo. However, if providing managerial capital to entrepreneurs is detrimental and, in contrast, providing them with entrepreneurial capital improves value creation and socioeconomic development, then many entrepreneurship-promotion initiatives may, in fact, require an urgent pivot in their provision of this type of capital.

The answer to this question will have large implications on how to run entrepreneurship support programs. In order to disentangle the effects of managerial versus entrepreneurial capital, we will provide equivalent groups of entrepreneurs unique treatments which aim to endow them with one or the other type of capital. Subsequently, we will compare how each group fares in terms of performance, growth and job creation.
External Link(s)

Registration Citation

Citation
Gonzalez-Uribe, Juanita, Michael Leatherbee and Santiago Reyes. 2024. "Managerial or entrepreneurial capital? Untangling constraints of innovative entrepreneurs." AEA RCT Registry. July 07. https://doi.org/10.1257/rct.8641-2.0
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Experimental Details

Interventions

Intervention(s)
A managerial capital intervention will focus in how to run the current company as efficiently as possible, while an entrepreneurial capital intervention will focus on exploring, validating and capturing market needs and business opportunities. On one hand, if entrepreneurs lack managerial capital, the intervention should help entrepreneurs to implement organizational changes such as the establishment of concrete routines, the creation of specific incentives for employees, or improving inventory management. In contrast, an intervention based on entrepreneurial capital should help founders discover and capture higher value opportunities for their products and services, much like the lean startup method induces founders to come up with new business ideas and converge faster on the viability of their ideas (Leatherbee & Katila, 2020). This can be done by providing entrepreneurs with mentors who have an entrepreneurial mindset (e.g., Sarasvathy, 2001; Busenitz and Barney, 1997) and consulting services oriented towards the exploratory stages (as opposed to the exploitative stages) of business creation.

This experiment aims to answer these questions by implementing a Randomized Control Trial (RCT) in Colombia, in collaboration with the Cali Chamber of Commerce (CCC), the same Institution who executed the program where Gonzalez-Uribe and Reyes (2020) find an impact of entrepreneurial schooling under a no-cash design for young businesses. This RCT will provide entrepreneurs with differential treatments: one aimed at improving management practices and making the established opportunity more efficient (i.e., exploitation), while the other one will be aimed at discovery, validation, capture and scaling of novel opportunities (i.e., exploration).

The main objective of this experiment is to identify what type of non-financial capital has the larger impact on start-up performance (i.e., sales, growth, profits and jobs)? And whether that type differs by innovative level of the business idea, characteristics of the entrepreneur, or stage of development of the firm.
Intervention Start Date
2021-12-01
Intervention End Date
2022-06-10

Primary Outcomes

Primary Outcomes (end points)
Short-term outcomes (after the program closure):
• Demo-day score: the pitch score as evaluated by judges in the demo-day (see above for more details on demo-day scores)
• Change in business practices index as measured by surveys
• Change in innovation and openness to new information index as measured by surveys

Primary long-term outcomes (within 1 and 2 years of application):
• Sales as measured by administrative data and surveys
• Business survival as measured by administrative data
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary long-term outcomes (within 1 and 2 years of application):
• Profits as measured by surveys
• Number of employees as measured by surveys and administrative data
• Wages as measured by surveys and administrative data
• Change in business practices index as measured by surveys
• Time dedicated to administrative, exploration and exploitation tasks
• Execution of exploration and exploitation activities
• Delegation of organizational tasks
• Change in innovation and openness to new information index as measured by surveys
• Online activity as measured by Alexa
• Number of followers on Linkedin, Twitter and/or Facebook (if it applies to the firm)



Score of the project (used for selection), and program classification of too entrepreneurs

Quality of the business model (innovativeness and scalability)

Characteristics of the entrepreneur and its team (education, sex, labor experience, experience as entrepreneur, and skill)

Initial stage of the firm (measured in terms of sales)

Initial stage of the entrepreneur’s focus (measured in terms if exploration and exploitation focus and activities)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The program will be divided into two stages. It is expected to have at least 154 beneficiary companies, these companies will be randomly divided between the two treatment arms.

1. In the first stage, each startup will receive a basic training program (same for the two treatment arms), weekly follow-ups (different focus depending on treatment arm) and 3 hours of support services (different focus depending on treatment arm). The first stage lasts 5 months.
2. After the first stage is completed, a demo day will be held in front of an evaluation panel that will include high-level executives, investors, and ecosystem leaders, among others.
The highest scoring 77 entrepreneurs of each treatment arm will be selected to go to the second phase of the program, for a total of 154 beneficiaries. This second stage will provide the entrepreneurs with 5 consultancy sessions. The focus of the session and who provides the session will be based on the treatment arm of the entrepreneur. The second stage will last 6 months.

Note: if at the time of program implementation there is a larger budget for more beneficiaries, the same rule of dividing the beneficiaries equally between the two treatment arms would apply.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
Unit of randomization: firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
6 regions of Colombia
Sample size: planned number of observations
At least 154 firms in total
Sample size (or number of clusters) by treatment arms
The planned number of firms and clusters is 360 (180 per treatment arm).

After the completion of the first stage, the second stage will include the top scoring 75 firms of each treatment arm (according to the application scores) for a total of 150 firms and clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect is $32M COP (with a power of 0.8, and using ANCOVA). The parameters and assumptions we used to produce this estimate are: 1. The revenue within one year of participation for previous cohorts of participants in the program is $107M COP, with a standard deviation of $133M COP (on a baseline revenue of $96M COP). The previous cohorts of participants have been offered services most similar to our managerial capital treatment arm, so we use these numbers as an estimate of the effect in the managerial capital arm of our experiment. 2. The sample size we use is the 360 firms that participate in both the first and the second stage of the experiment. 3. We assume one follow-up and a correlation of 0.6. 4. To replicate the MDE of $32M COP, use the following routine in stata: sampsi 107 139, n1(180) n2(180) sd1(133) pre(1) post(1) r01(0.6). This MDE corresponds to 0.3 standard deviations.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
The london school of economics and political science
IRB Approval Date
2021-11-11
IRB Approval Number
46635
Analysis Plan

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