A scientific and sustainable approach to business decision making

Last registered on January 02, 2025

Pre-Trial

Trial Information

General Information

Title
A scientific and sustainable approach to business decision making
RCT ID
AEARCTR-0015080
Initial registration date
January 01, 2025

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
January 02, 2025, 7:57 AM EST

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

Locations

Region

Primary Investigator

Affiliation
Universidad ORT Uruguay

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-09-01
End date
2026-09-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Existing evidence suggests that entrepreneurs do not frequently employ robust methods to make decisions under uncertainty. Entrepreneurs tend to rely more on intuition than structured decision-making processes to discover the value of their business ideas. However, these methods have the potential to provide high-quality information for entrepreneurs’ strategic decision-making in their business ventures. Therefore, it is important to study how applying structured methods helps entrepreneurs improve the quality of their strategic decisions and enhance their ventures’ performance. This becomes even more relevant in a context where new elements of uncertainty arise, going beyond purely commercial aspects, such as the environmental and social sustainability of ventures.

This project investigates one of these methods. Specifically, it examines the causal relationship between the so-called “scientific method” and the performance of entrepreneurs in Uruguay. By formulating theories, hypotheses, and experiments to validate business models, the scientific method potentially improves the quality of strategic decisions and, in turn, business performance. Specifically, through this RCT, we will study the impact of applying the scientific method on project abandonment, modifications (pivots) to business models, and entrepreneurs’ revenues.

To this end, two controlled experiments are designed: one replicating a previous study, and another based on the former but focused on sustainable businesses, thereby providing novel findings. Upon completion of the experiment, it will be possible to (a) evaluate whether this method leads to better performance for those who employ it in a higher-uncertainty economy compared to the original study done in Italy and the UK (b) understand how this method enhances the effectiveness and efficiency of sustainable businesses, and (c) translate the findings into concrete products aimed at fostering entrepreneurship and sustainable enterprises in Uruguay.
External Link(s)

Registration Citation

Citation
Segantini, Marcos. 2025. "A scientific and sustainable approach to business decision making." AEA RCT Registry. January 02. https://doi.org/10.1257/rct.15080-1.0
Sponsors & Partners

Sponsors

Experimental Details

Interventions

Intervention(s)
Following Camuffo et al (2024), this replication project focuses on teaching entrepreneurs, in this case in Uruguay, how to use a structured, scientific approach to make business decisions. Instead of relying on intuition, the program designs an intervention to train entrepreneurs to analyze their ideas systematically. Participants are taught to break down their business models into key components, identify the assumptions behind their strategies, derive hypotheses, design experiments to test these hypotheses, and make decisions based on the results of their testing procedures. This method, modeled after the scientific method, helps entrepreneurs gather real-world customer feedback, test minimum viable products, and make data-driven decisions about whether to proceed, pivot, or abandon their business ideas. Entrepreneurs are divided into two groups: one receives traditional training, and the other learns to apply scientific techniques. The project measures and compares the outcomes of these two groups, particularly in terms of business performance, strategy changes (business model pivots), and whether participants decide to continue or end their ventures. By applying this structured approach, the intervention aims to improve entrepreneurs’ ability to adapt to uncertainty, focus on viable opportunities, and make empirical-based decisions, ultimately enhancing the success of their businesses in a challenging economic environment.

Camuffo, A., Gambardella, A., Messinese, D., Novelli, E., Paolucci, E., & Spina, C. (2024). A scientific approach to entrepreneurial decision-making: Large-scale replication and extension. Strategic Management Journal, 2024(1), 1–29
Intervention Start Date
2025-09-01
Intervention End Date
2025-11-17

Primary Outcomes

Primary Outcomes (end points)
Total Revenue Accumulated
Time to Revenue
-Time to First Client
-Termination
-Time to Termination
-Total Pivots
Primary Outcomes (explanation)
1) The first set of outcomes aims to measure business performance:

-Total Revenue Accumulated: The total revenue generated by a participant’s venture during the observation period, measured in Uruguayan pesos.
-Time to Revenue: The time (in months) it takes for a participant’s venture to begin generating revenue.
-Time to First Client: The time (in months) it takes for a participant’s venture to acquire its first client.

2) The second set of outcomes aims to measure strategic entrepreneurial decisions

-Termination: Whether a participant decides to terminate their venture project (dichotomous variable: 1 = terminated, 0 = not terminated).
-Time to Termination: The time (in months) it takes for a participant to decide to terminate their venture project.
-Total Pivots: The total number of strategic pivots (e.g., changes in business model components) made by a participant’s venture during the observation period.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experimental design of this project involves two randomized controlled trials (RCTs), each tailored to address distinct entrepreneurial contexts: one focusing on traditional business ventures and the other on sustainable business models. Both experiments aim to evaluate the impact of teaching entrepreneurs a scientific approach to decision-making, emphasizing evidence-based methods for testing business hypotheses and refining strategies. The experiments are designed to ensure robust comparisons between a treatment group, which receives the scientific training, and a control group, which receives conventional entrepreneurial training.
In both experiments, participants are recruited through a comprehensive outreach campaign targeting aspiring entrepreneurs. The selection process involves screening applications to ensure participants have early-stage ventures suitable for the intervention. Once selected, participants are randomly assigned to treatment and control groups to minimize bias and ensure balance across key variables, such as industry, development stage, and geographic location. This randomization allows for a causal analysis of the impact of the intervention on various outcome variables, such as revenue generation, project termination, and strategic pivots.
The training intervention for the treatment group in the first experiment emphasizes using the scientific method to enhance decision-making in traditional entrepreneurial ventures. Participants are taught to identify assumptions in their business models, formulate testable hypotheses, and design experiments to validate these hypotheses. The training includes techniques like customer interviews, A/B testing, and minimum viable product (MVP) development. Control group participants receive conventional training covering similar topics but without the structured scientific framework for decision-making. Outcomes such as revenue growth, time to first client, and the frequency of strategic pivots are monitored over time.
The second experiment, focusing on sustainable business models, incorporates additional elements to address social and environmental dimensions. Participants in the treatment group use an adaptation of the traditional canvas aimed to integrate environmental and social factors into their business strategies. The training emphasizes engaging diverse stakeholders, such as regulators, community members, and environmental experts, to validate sustainability-related hypotheses. Control group participants in this experiment receive training that includes sustainability topics but lacks the hypothesis-driven scientific approach. Outcome variables for this experiment are the same as the first, including traditional metrics like revenue, client acquisition, project termination, and strategic pivots. By combining these designs, the project aims to generate actionable insights into the effectiveness of structured decision-making approaches across diverse entrepreneurial contexts.
Experimental Design Details
Not available
Randomization Method
Participants will be randomly assigned to balanced groups based on the same variables used in the original experiments. These variables will be collected through an application form that aspiring participants must complete during the selection process. Additionally, applicants will be asked whether they know other entrepreneurs applying to the training course. After acceptance, they will be asked again if they know any other accepted participants. To address potential biases, if any participants know one another, they will be assigned to the same stratum to ensure that such cases are consistently placed in either the treatment or control group to avoid contamination between groups.
The randomization process will utilize a computer-generated algorithm in R, a widely used and reliable method for RCTs. This approach ensures assignments are random and unbiased, giving each participant an equal chance of being placed in either the treatment or control group, except for cases involving prior knowledge among them. To maintain balance across key variables, such as industry, development stage, and geographic location, statistical tests will be conducted post-randomization to confirm the balance between groups. These tests will align with the protocols followed in the original studies conducted in Italy and the UK.
The randomization process will be thoroughly documented to ensure transparency and adherence to protocol. This includes maintaining and making the codes of the randomization output traceable and recording all decisions made during the process.
Randomization Unit
Nascent entrepreneurs; except those that know each other. If we have participants who knew each other previously, they will be assigned to strata to ensure they belong to either treatment or control groups. However, it is worth mentioning that the described situation has not been relevant in previous versions of this experiment.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
116 nascent entrepreneurs
Sample size: planned number of observations
If no entrepreneur abandons their project during the observation period, the experiment will yield a total of 1,392 observations. However, this scenario is highly unlikely. For participants who declare project abandonment, their data will be recorded up to the point of their declaration. Consequently, while the maximum number of observations per experiment is 1,392, the actual total may vary depending on the number of project abandonments.
Sample size (or number of clusters) by treatment arms
Each experiment requires a minimum of 116 nascent entrepreneurs, with 58 participants allocated to the treatment group and 58 to the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee - Universidad ORT Uruguay
IRB Approval Date
2024-12-20
IRB Approval Number
N/A