Fertigation Technology

Last registered on August 20, 2026
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Pre-Trial

Trial Information

General Information

Title
Fertigation Technology
RCT ID
AEARCTR-0019362
Initial registration date
August 12, 2026

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 20, 2026, 8:42 AM EDT

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

Locations

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Primary Investigator

Name
Yi Cui
Affiliation
Beijing Technology and Business University
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Other Primary Investigator(s)

PI Name
Huang Chen
PI Affiliation
Xiamen University
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PI Name
Jinxia Wang
PI Affiliation
Hohai University
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Additional Trial Information

Status
In development
Start date
2026-08-14
End date
2027-08-31
Keywords
Agriculture
Additional Keywords
Willingness to Pay, Fertigation Technology, Randomized Controlled Trial, Information Intervention
JEL code(s)
Q16, Q25, D83
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Fertigation (integrated water and fertilizer integration) technology precisely integrates irrigation and fertilization management by delivering water and nutrients directly to crop root zones in a targeted and timed manner. Compared with traditional flood irrigation and manual fertilization methods, this technology effectively reduces water and fertilizer waste, improves crop nutrient absorption efficiency and yield performance, and mitigates agricultural non-point source pollution caused by nutrient leaching, thereby achieving more efficient and environmentally friendly agricultural production.

Although fertigation technology has been widely promoted and applied in agricultural sectors of many countries including the United States, Canada, and Israel, its popularization and adoption among Chinese farmers remain insufficient. To explore the key informational barriers restricting the diffusion of fertigation technology, this study conducts a randomized controlled trial (RCT) covering a total of approximately 1,600 farming households across nine provincial regions in China, including Beijing, Jilin, Hebei, Ningxia, Sichuan, Zhejiang, Jiangsu, Anhui, and Yunnan. This study adopts two diversified information intervention methods: organizing farmers to watch targeted promotional videos and guiding farmers to utilize artificial intelligence large models to independently acquire relevant agricultural information. Centering on four core information dimensions including technical characteristics, cost-benefit performance, subsidy policies, and ecological environmental effects, this paper systematically analyzes the differential impacts of different information types and intervention approaches on farmers’ willingness to pay (WTP) for fertigation technology adoption.

The core research hypotheses to be verified in this study are proposed as follows:

Hypothesis 1: Information interventions concerning technical characteristics, cost-benefit performance, subsidy policies, and ecological environmental effects can significantly improve farmers’ willingness to pay for fertigation technology, with cost-benefit information exerting a stronger promotional effect on farmers’ adoption willingness than the other three types of information.

Hypothesis 2: Large-scale farmers exhibit a higher willingness to pay for fertigation technology compared with small-scale farmers.

Hypothesis 3: Farmers facing higher fertilizer price levels show a stronger willingness to pay to adopt fertigation technology.
External Link(s)

Registration Citation

Citation
Chen, Huang, Yi Cui and Jinxia Wang. 2026. "Fertigation Technology." AEA RCT Registry. August 20. https://doi.org/10.1257/rct.19362-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-08-14
Intervention End Date
2026-08-31

Primary Outcomes

Primary Outcomes (end points)
The core research hypotheses to be verified in this study are proposed as follows:
Hypothesis 1: Information interventions concerning technical characteristics, cost-benefit performance, subsidy policies, and ecological environmental effects can significantly improve farmers’ willingness to pay for fertigation technology, with cost-benefit information exerting a stronger promotional effect on farmers’ adoption willingness than the other three types of information.
Hypothesis 2: Large-scale farmers exhibit a higher willingness to pay for fertigation technology compared with small-scale farmers.
Hypothesis 3: Farmers facing higher fertilizer price levels show a stronger willingness to pay to adopt fertigation technology.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The field operation will be supported by governments at different administrative levels to guarantee the randomization of the sample selection and treatment assignment. At the grassroots level, village leaders will be informed by their corresponding township leaders about the general plan of the survey. Farmers will be randomly selected from the name list at the village leader's office 2 or 3 days prior to the survey event. Village leaders will cooperate with the research team to contact each of the sampled farmers and make an appointment with them to participate in our survey and RCT experiment at the village leader's office building.

All surveyed farmers will be informed by the survey investigators before the survey starts about the purpose of the survey (i.e., for purely scientific research purposes), the general survey structure (including an RCT experiment), the anticipated length of the survey, and other necessary information (such as self-introduction and payment information for participating in the survey) to obtain their agreement to participate in the survey.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Village randomization for some treatments, and individual randomization for some treatments.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
162 villages.
Sample size: planned number of observations
1620 households
Sample size (or number of clusters) by treatment arms
420 households control, 1200 households treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
80%.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Institutional Review Board of Finance and Economics Experimental Laboratory The Wang Yanan Institute for Studies in Economics, Xiamen University
IRB Approval Date
2026-07-30
IRB Approval Number
FEEL260701
Analysis Plan