Fintech Adoption by Retail Firms in an Emerging Market: Experimental Evidence of Tech, Marketing, and Financial Interventions

Last registered on March 13, 2024

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0009984

Initial registration date

August 26, 2022

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

August 29, 2022, 2:02 PM EDT

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

Last updated

March 13, 2024, 6:41 PM EDT

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

Locations

Country

Mexico

Region

Jalisco

Primary Investigator

Name

Shreya Kankanhalli

Affiliation

Cornell University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Stephen Anderson

PI Affiliation

UT Austin

Contact Investigator

PI Name

Sridhar Narayanan

PI Affiliation

Stanford University

Contact Investigator

PI Name

Leonardo Iacovone

PI Affiliation

World Bank

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Additional Trial Information

Status

Completed

Start date

2019-04-19

End date

2023-08-31

Keywords

Finance & Microfinance, Firms & Productivity

Additional Keywords

Fintech, Financial Inclusion, Marketing

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Across developing economies, cash is the conduit for retail transactions. Policymakers, multinational product manufacturers and marketers of electronic payment systems are interested in understanding how to stimulate the growth of electronic payments in emerging markets. In this paper, we investigate what hinders the adoption of e-payment technology by traditional retailers, in particular, whether barriers to adoption are technological, informational or financial in nature. We do this through a rigorous field experiment, where we randomize 900 small retailers in Guadalajara, Mexico into four experimental groups: i) N = 225 firms receive an e-payment technology kit; ii) N = 225 firms receive the e-payment technology kit and informational materials to market e-payments to customers; iii) N = 225 firms receive the e-payment technology kit, informational materials, and a 4-month transaction fee waiver; and iv) N = 225 firms constitute a control group who receive no intervention. By comparing the adoption rates of the different treatment groups, we are able to cleanly analyze which barriers are critical to technology adoption. We additionally aim to study the impact of these interventions on e-payment adoption by neighboring retailers, and business performance.

External Link(s)

Registration Citation

Citation

Kankanhalli, Shreya et al. 2024. "Fintech Adoption by Retail Firms in an Emerging Market: Experimental Evidence of Tech, Marketing, and Financial Interventions." AEA RCT Registry. March 13. https://doi.org/10.1257/rct.9984-2.1

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Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2019-06-03

Intervention End Date

2022-09-16

Primary Outcomes

Primary Outcomes (end points)

Sales, profits, technology adoption, technology usage

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

900 small-scale retailers in Guadalajara, Mexico are randomized into four equal-sized groups:
• Control (N=225 firms): No intervention offered to participants.
• Technology (N=225 firms): Retailers in this treatment group are given a smartphone that is enabled with: (i) technology for electronic payments, including an attachable dongle to read credit/debit cards and the software to process payments, and (ii) a six-month data plan. In addition, retailers receive 4 hours (two visits) of IT support from a technical consultant. The hours are focused on installing
the technology, ensuring the entire system is functioning correctly and on helping the focal retailer effectively process
electronic payment transactions.
• Technology + Marketing (N=225 firms): In addition to receiving everything from the first treatment, retailers in this group also receive assistance with understanding and marketing the benefits of e-payment technology to customers. This is delivered through “E-payment Agents” (i.e. top university students majoring in business, economics or related disciplines) who visit treated retailers eight times, for two-hour long sessions. They help the business owner develop a strategy to: (i) reach out to new customer segments who would find the payment
option attractive; (ii) install the provided marketing materials such as posters, stickers, outdoor pop-up stands; and (iii) to communicate the existence and benefits of paying by card at the business.
• Technology + Marketing + Commissions (N=225 firms): In addition to receiving the intervention components from the previous two treatments, these retailers receive a four-month waiver for the commission normally paid on each e-payment transaction.
This experiment is underway, with the intervention completed for N = 805 firms.

Experimental Design Details

To measure the impact of our interventions, we plan to collect detailed information on e-payment adoption and usage in the 6-month post-intervention survey of the full study sample. By comparing the adoption and usage rates of the different treatment groups, we will be able to cleanly analyze which barriers are critical to adoption and usage. We will also collect firm performance measures (sales, costs, and profits) in this survey round to answer how e-payment adoption by small-scale retailers impacts performance. Additionally, we complement this survey data with corresponding data from the e-payment service provider, so that for every treated business we can objectively measure how much they sold through the technology. The e-payment application records each transaction made through the dongle, allowing us to calculate total monthly sales through e-payments. Using this type of data for measuring firm sales would solve the problem of accurately measuring activities of firms in developing economies, something most researchers struggle with. We have also secured funding to survey retail businesses neighboring our sample to measure the spillover effects of the intervention on e-payment adoption.

Randomization Method

Randomization done in office by a computer

Randomization Unit

Firm

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

N/A

Sample size: planned number of observations

900 firms

Sample size (or number of clusters) by treatment arms

225 firms: Control
225 firms: Technology intervention only
225 firms: Technology and marketing intervention
225 firms: Technology, marketing, and financial waiver intervention

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

Supporting Documents and Materials

IRB