Learning vs. Costly Information Processing in Technology Adoption: Evidence from a Cluster Randomized Controlled Trial in India

Last registered on December 06, 2023

Pre-Trial

Trial Information

General Information

Title
Learning vs. Costly Information Processing in Technology Adoption: Evidence from a Cluster Randomized Controlled Trial in India
RCT ID
AEARCTR-0012160
Initial registration date
November 24, 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
December 06, 2023, 7:52 AM EST

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

Locations

Region

Primary Investigator

Affiliation
University of Goettingen

Other Primary Investigator(s)

PI Affiliation
University of Goettingen

Additional Trial Information

Status
In development
Start date
2024-03-01
End date
2025-05-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Recent studies highlight information constraints as an important barrier to technology adoption, but there is very little evidence that allows to distinguish the roles of different information frictions for adoption decisions of different types of technology. We design a cluster randomized controlled trial among 1,200 farmers in Haryana, India, to promote adoption of early sown wheat varieties and zero tillage technology—two agricultural innovations that can help farmers adapt to climate change by increasing resilience to heat and water stress. Guided by a novel theoretical framework that captures the distinct roles of two information frictions, learning and costly information processing, the experiment is designed to test whether different types of technology require different types of information provision to facilitate adoption. The insights derived from this study have strong policy implications and help in understanding the role of information frictions for adoption decisions beyond the specific technologies considered here.
External Link(s)

Registration Citation

Citation
Naeher, Dominik and Sebastian Vollmer. 2023. "Learning vs. Costly Information Processing in Technology Adoption: Evidence from a Cluster Randomized Controlled Trial in India." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.12160-1.0
Experimental Details

Interventions

Intervention(s)
Intervention 1 comprises a one-day training workshop focused on increasing farmers’ knowledge about the general features and benefits of using Early Sown Wheat Varieties (ESW) and Zero-Tillage Equipment (ZT), with the goal of facilitating uptake and usage of these two technologies.

Intervention 2 consists in providing handholding support to participants designed to assist individual famers in staying attentive to changes in environmental conditions and react in appropriate ways to any challenges arising on their wheat plots, thereby reducing uncertainty about optimal usage practices and timing of agricultural tasks related to ESW and ZT.
Intervention Start Date
2024-05-01
Intervention End Date
2025-04-30

Primary Outcomes

Primary Outcomes (end points)
- Farmers’ adoption decisions of ESW
- Farmers’ adoption decisions of ZT
- Farmers’ perceptions towards ESW and ZT, including: (a) farmers’ general awareness of ESW and ZT, (b) farmers’ beliefs about whether ESW and ZT offer advantages over conventional wheat varieties and methods of soil preparation, and (c) farmers’ stated intention to use ESW or ZT in the future.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1) Wheat yields and occurrence of crop failure
2) Agricultural income from wheat cultivation (gross and net of input costs)
3) Use of agricultural inputs (manure, chemical fertilizers, herbicide, pesticide) on wheat plots
4) Irrigation practices and amount of water used on wheat plots
5) Labor input and management decisions for different tasks in wheat cultivation (including land preparation, sowing, weeding, irrigating, applying fertilizer and other inputs, harvesting, threshing, grain cleaning)
6) Agriculture waste disposal practices (incl. instance of crop residue burning)
7) Farmers’ perceptions towards the practice of residue burning and air pollution
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will conduct a cluster RCT with multiple treatment arms designed to test several hypotheses motivated by our theoretical framework. Randomization of the participating farmers into treatment arms will be conducted both between clusters (i.e., villages) and within clusters. Specifically, there will be three types of villages: Control villages, Treatment(1) villages, and Treatment(2) villages. The Control villages constitute a pure control group in which the participating farmers will be asked to respond to our baseline and endline surveys, but will not benefit from any intervention. The participants within each Treatment(1) village will be randomly assigned to one of two groups. The first group (T1) will receive Intervention 1, whereas the second group (C1) will receive no information treatment regarding ESW or ZT (to facilitate implementation and compliance, the farmers assigned to C1 will receive a placebo information treatment). Similarly, the participants within each Treatment(2) village will be randomly assigned to either the T2 or the C2 group. Participants in T2 will receive both Intervention 1 and Intervention 2, whereas the participants in C2 will only receive Intervention 1.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Step 1: randomly select 60 clusters (villages) from the village sampling frame.
Step 2: randomly assign 20 villages to Control, 20 villages to Treatment(1), and 20 villages to Treatment(2) groups, respectively.
Step 3: Within each Treatment(1) village, randomly assign half of the participants to T1 group and half to C1 group. Within each Treatment(2) village, randomly assign half of the participants to T2 group and half to C2 group.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
60 villages
Sample size: planned number of observations
1200 farm households
Sample size (or number of clusters) by treatment arms
20 villages Control, 20 villages Treatment(1), 20 villages Treatment(2)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For β=0.7 (statistical power) and K=0.1 (coefficient of variation of true proportions between clusters within each group), we will be able to detect a relative increase in the adoption rate of ESW of 6.6%-points (e.g., from a baseline of 14.4% to 21.3%) under Intervention 1, and an increase in the adoption rate of ZT of 8.2%-points (e.g., from a baseline of 24.5% to 32.7%), both at a statistical significance level of 5%. For β=0.8 and K=0.2, we will still be able to detect an increase of 8.1%-points for ESW and an increase of 9.8%-points for ZT, at a statistical significance level of 5%.
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee of the University of Göttingen
IRB Approval Date
2023-08-01
IRB Approval Number
N/A
Analysis Plan

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