Can diversification reduce small business vulnerability?

Last registered on July 05, 2020

Pre-Trial

Trial Information

General Information

Title
Can diversification reduce small business vulnerability?
RCT ID
AEARCTR-0005181
Initial registration date
December 15, 2019
Last updated
July 05, 2020, 9:33 AM EDT

Locations

Region

Primary Investigator

Affiliation
Insper Institute of Education and Research

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2019-10-28
End date
2021-03-01
Secondary IDs
Abstract
This study investigates whether and how diversification in small businesses reduces the vulnerabilities to which poor entrepreneurs are exposed. We indirectly (and randomly) change the level of diversification of a group of small businesses in Brazil by increasing entrepreneurs' ability to sell through a platform. Treatment thus consists of online training sessions aimed at increasing entrepreneurs' platform-related sales and marketing capabilities. Main analyses focus on how treatment impacts platform sales and core-business sales (to grasp potential diversification effects). Other analyses consider how treatment impacts the diffusion of platform sellers within geographic regions.
External Link(s)

Registration Citation

Citation
Nardi, Leandro. 2020. "Can diversification reduce small business vulnerability?." AEA RCT Registry. July 05. https://doi.org/10.1257/rct.5181-2.0
Experimental Details

Interventions

Intervention(s)
All businesses in the sample are, to some extent, diversified since they sell both core business products/services and platform services, such as bill payment, phone recharges. Businesses randomly assigned to treatment receive platform-related sales and marketing training to increase the proportion of platform sales (i.e., revenues from the diversified source) vis-a-vis total business revenues.
Intervention Start Date
2019-10-28
Intervention End Date
2020-02-29

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes of interest are platform sales (diversified source), total business sales (including non-diversified source) and the ratio between these variables. Business average profits are also examined, as well as the number of platform sellers within ZIP codes.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
About half of businesses were assigned to treatment. Treatment was stratified in two levels: industry/sector and preexisting platform sales experience (i.e., a group with higher number of platform transactions in the nine months preceding the beginning of the trial versus a group with lower number of platform transactions in the same period). To avoid contamination, most of the businesses in the study are located in separated geographic areas. This design also allows for a ZIP-code-level analysis of treatment effects on platform diffusion.
Experimental Design Details
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Individual business.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
315 businesses
Sample size: planned number of observations
306 businesses
Sample size (or number of clusters) by treatment arms
151 businesses treatment and 155 businesses control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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