Using Behavioral Games to Understand Water-Saving Technology Adoption in Uzbekistan.

Last registered on December 20, 2024

Pre-Trial

Trial Information

General Information

Title
Using Behavioral Games to Understand Water-Saving Technology Adoption in Uzbekistan.
RCT ID
AEARCTR-0015008
Initial registration date
December 11, 2024

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 20, 2024, 12:31 PM EST

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

Locations

Region

Primary Investigator

Affiliation
UW-Madison

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2024-12-10
End date
2024-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This research examines water management challenges in Uzbekistan's agricultural sector, where upstream and downstream farmers face significantly different water access conditions within the same irrigation networks. In a country where agriculture consumes 90% of water resources, downstream farmers often struggle with water scarcity due to overconsumption by upstream users. While government subsidies for drip irrigation systems can reduce water usage by 30% and increase yields by 20%, adoption rates vary dramatically by location, from zero to wide adoption, suggesting that financial incentives alone may be insufficient to promote widespread adoption of water-saving technologies.

The study implements a structured experimental design using modified Irrigation games, an established methodology for studying water resource management, to test whether participatory interventions can enhance the effectiveness of subsidy programs and promote cooperation between upstream and downstream farmers. Our experiment spans four regions in Uzbekistan, with 32 Irrigation games conducted across 16 districts (two games per district), involving 160 farmers total. We modify the traditional Irrigation game framework to incorporate investment decisions for water-saving technologies while maintaining the fundamental upstream-downstream dynamics. Our mathematical model suggests that adoption decisions are influenced not only by water availability but also by social dynamics and community cooperation.

This research aims to: (1) examine whether Irrigation games can increase technology adoption rates beyond what subsidies alone achieve, (2) analyze differences in adoption patterns between upstream and downstream farmers, and (3) investigate how the adoption of water-saving technologies by upstream farmers impacts water availability and subsequent adoption decisions by downstream users. The findings will contribute to understanding behavioral barriers to technology adoption and inform policy interventions for sustainable water management in agricultural systems.

We hypothesize that: (1) Irrigation games could increase the adoption rate of water-saving technologies compared to subsidies alone by improving farmers' understanding of collective benefits; (2a) in cases of high water distribution disparities, midstream farmers will show the highest adoption rates within the games; (2b) in cases of low water distribution disparities, upstream farmers will lead in adoption due to their greater control over water resources and higher social benefits from installation; and (3) the adoption of water-saving technologies will have differential effects depending on overall water availability - under abundant water conditions, adoption will improve water availability for other farmers, while under severe shortages, adopters will use their improved efficiency to maintain their own production rather than share saved water.
External Link(s)

Registration Citation

Citation
Liutin, Anton. 2024. "Using Behavioral Games to Understand Water-Saving Technology Adoption in Uzbekistan.." AEA RCT Registry. December 20. https://doi.org/10.1257/rct.15008-1.0
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Experimental Details

Interventions

Intervention(s)
Our research intervention builds upon an ongoing International Food Policy Research Institute (IFPRI) survey of farmers in Uzbekistan. Rather than implementing a new random selection process, we recruit participants from the existing pool of IFPRI survey respondents at the district level. This approach allows us to leverage comprehensive baseline data about participating farmers while ensuring our sample represents active agricultural practitioners familiar with local water management challenges.

The core of our intervention consists of modified Irrigation games, conducted with farmers across four regions in Uzbekistan. Within each region, we work across four districts, conducting two games per district, resulting in 32 total games involving 160 farmers. Each game brings together five farmers and progresses through three distinct phases: an initial learning phase of 3-5 rounds where participants familiarize themselves with the basic mechanics, followed by 5-7 rounds incorporating water-saving technology options, and concluding with 7-12 rounds featuring water allocation shocks. This structure allows participants to first master the fundamental dynamics before engaging with more complex decisions about technology adoption and resource management under uncertainty.

The game mechanics simulate real-world irrigation challenges and decisions. Players begin each round with 20 tokens and must make sequential decisions about investing in public water infrastructure and potentially adopting water-saving technologies. The technology adoption option, representing drip irrigation systems, requires an investment of 15 tokens for 3 turns in a rounds but provides lasting benefits through a 50% reduction in water consumption for all subsequent rounds. Players extract water in sequential order from upstream to downstream, mirroring the actual dynamics of surface irrigation systems in Uzbekistan.

Following each game session, we conduct structured discussions with the participating farmers to explore their insights about water management challenges, technology adoption processes, and lessons learned from the gaming experience. These discussions provide valuable qualitative data to complement the quantitative metrics collected during gameplay.

Our data collection synthesizes multiple sources: baseline information from the IFPRI survey, detailed game performance metrics, discussion outcomes, and follow-up data on actual technology adoption and water use patterns. This comprehensive approach allows us to examine how farmers' behavior in the games correlates with their real-world decisions about water-saving technology adoption and whether participation in the games influences their subsequent technology adoption choices.

This intervention design specifically targets understanding how participatory learning through gaming might enhance the effectiveness of existing government subsidy programs for drip irrigation, while also providing insights into the social and behavioral factors that influence water resource management decisions.
Intervention (Hidden)
Intervention Start Date
2024-12-10
Intervention End Date
2024-12-31

Primary Outcomes

Primary Outcomes (end points)
**Primary Outcome Variables:**

1. In-Game Outcomes:
- Adoption of water-saving technology (binary: 0/1)
- Investment in water infrastructure (tokens)
- Water extraction (units of water)
- Total earnings (tokens)
- Round of adoption (number)

2. Real-World Technology Adoption:
- Installation of drip irrigation (binary: 0/1)
- Timing of installation (months since game participation)
- Area under drip irrigation (hectares)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our research implements modified Irrigation games across four regions in Uzbekistan to study water-saving technology adoption behavior. The study builds upon an ongoing International Food Policy Research Institute (IFPRI) NEXUS-Gains survey, with participants recruited from the existing survey respondent pool.

Study Structure:
- 4 regions in Uzbekistan
- 4 districts per region (16 total districts)
- 2 games per district (32 total games)
- 5 farmers per game (160 total participants)

Game Implementation:
Each game consists of three phases:
1. Learning phase (3-5 rounds)
2. Technology adoption phase (5-7 rounds)
3. Water supply shock phase (7-12 rounds)

Game Design:
- Players start each round with 20 tokens
- Sequential decision-making in fixed upstream to downstream order
- Players can:
* Invest in shared water infrastructure
* Adopt water-saving technology (costs 15 tokens)
* Extract water for agricultural production
- Water-saving technology reduces water consumption by 50%

Data Collection:
- Baseline data from IFPRI NEXUS-Gains survey in Uzbekistan
- Game performance metrics
- Post-game technology adoption tracking
- Real-world water use patterns

This design allows us to examine how participatory learning through games influences water-saving technology adoption decisions and water resource management practices.
Experimental Design Details
Randomization Method
The selection of participants follows a two-stage process, building upon the existing IFPRI survey sampling:

**Stage 1: Initial Survey Randomization**
The baseline pool of farmers was established through IFPRI's randomized selection process prior to our study. This selection was conducted using a computerized random sampling of all registered farmers in Uzbekistan, stratified by:
- Farm size
- Village

**Stage 2: Game Participant Selection**
From this pre-established survey pool, we recruit game participants through the following process:
1. Contact farmers from the IFPRI survey list within each district
2. Once 5 farmers from a district agree to participate, we proceed with organizing first game session
3. Next when another 5 farmers from a district agree to participate, we proceed with organizing second game session

This approach maintains the random selection benefits of the original IFPRI sampling while accommodating the practical constraints of organizing game sessions. The sequential recruitment process (continuing until 10 farmers agree) helps ensure consistent game group sizes while preserving the randomization from the initial survey selection.
Randomization Unit
From each region, four districts were selected based on their IFPRI survey completion rates. Districts were chosen where survey completion was near full coverage (4 out of 5 districts had reached this threshold). The games were conducted during the ongoing survey period, with participating farmers recruited from the pool of already-surveyed respondents in these districts. There was no additional randomization beyond working with these surveyed farmers.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Not applicable - this study does not utilize cluster randomization. The study involves 32 individual game sessions (two sessions in each of 16 districts), but these do not function as randomized clusters.
Sample size: planned number of observations
160 farmers (5 farmers per game × 2 games per district × 4 districts per region × 4 regions) These 160 farmers are selected from a total pool of 900 farmers who participated in the IFPRI survey. The remaining 740 surveyed farmers, including those in districts where no games were conducted, serve as the control group. This ensures clean separation between treated and non-treated populations.
Sample size (or number of clusters) by treatment arms
160 farmers (5 farmers per game × 2 games per district × 4 districts per region × 4 regions)

These 160 farmers are selected from a total pool of 900 farmers who participated in the IFPRI survey. The remaining 740 surveyed farmers, including those in districts where no games were conducted, serve as the control group. This ensures clean separation between treated and non-treated populations.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
The Institutional Review Boards Office of University of Wisconsin-Madison
IRB Approval Date
2024-12-10
IRB Approval Number
2024-1307

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