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Water Scarcity and Specificity of Saving Tips
Last registered on July 31, 2017


Trial Information
General Information
Water Scarcity and Specificity of Saving Tips
Initial registration date
July 28, 2017
Last updated
July 31, 2017 9:16 AM EDT
Primary Investigator
University of Cologne
Other Primary Investigator(s)
Additional Trial Information
In development
Start date
End date
Secondary IDs
Water scarcity is becoming a global phenomenon. Examples can be found in California, Spain, India and also Namibia, where limited rainfall has caused the worst droughts in decades. As a cheap and fast way to reduce water demand, water utilities typically rely on mass communication to foster water conservation efforts among consumers. However, there seemingly exists no experimental evidence on how specific saving tips shoud be. This research project classifies saving tips by their specificity to provides first empirical evidence. Specific and less specific tips face a trade-off between simplicity and involving the recipient in the idea-generating process.
External Link(s)
Registration Citation
Tonke, Sebastian. 2017. "Water Scarcity and Specificity of Saving Tips." AEA RCT Registry. July 31. https://doi.org/10.1257/rct.2280-1.0.
Former Citation
Tonke, Sebastian. 2017. "Water Scarcity and Specificity of Saving Tips." AEA RCT Registry. July 31. http://www.socialscienceregistry.org/trials/2280/history/19965.
Experimental Details
This interventions aims to increase water conservation efforts in Namibia. Three text mesage treatments via mobile phone ask customers to use less water. The treatments however vary the degree of their specificity. The treated customers will receive one treatment in English and one in Oshiwambo (local language).

1. Untreated comparison group

2. Specific tips treatment group:
Customers receive three specific savings tips as for example “Shorten the time you spend in the shower by a minute or two”.

3. Semi-specific ("Betty Crocker’s Eggs") treatment group:
Customers receive three semi-specific saving tips as for example “How can you re-use water in your household (for example from the kitchen)?”.

4. Unspecific treatment group:
Customers are asked to come up with three own ideas on how to reduce water consumption.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Water consumption behavior and payment behavior.
Primary Outcomes (explanation)
I use administartive data on water consumption and payment behavior from the Namibian Water Corporation. The main outcome variables (water consumption and payments) show very high variance, which reduces power. Data transformations (logs and winsorizing) to deal with outliers are necessary to reduce variance as well as looking at subsamples with lower variance.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Customers will be randomly assigned to one of three treatment conditions or the baseline. They will receive a short text messages in both English and Oshiwambo (Local language) to encourage water conservation efforts as described in the intervention. Behavioral predictions are contradicting.

Hypothesis 1: Effectiveness increases with specificity of tips
Complexity and limited cognitive resources reduce the ability and motivation to act on pro-environmentally behavior (Steg, 2016). The specification of saving tips reduces the cognitive effort to find ways to act on pro-environmental behavior. Further, people are more likely to engage in a certain behavior if the task is perceived as easy (Ajzen, 1991). Literature on implementation intentions shows that specifying a concrete action plan increases the likelihood of acting on that behavior (Gollwitzer & Sheeran, 2006). Once a plan is established, people execute their plans without having to invest cognitive effort, making their behavior swift and efficient (Gollwitzer, 1999). From a practical perspective, reducing complexity and simplifying difficult choices has been shown to be among the most effective “nudges” (Thaler & Sunstein, 2008). Hence, this body of research suggests that a specific saving should be most effective.

Hypothesis 2: Effectiveness decreases with specificity of tips
Previous research has shown that people have a tendency to overvalue their own ideas over the ideas of others. Hooshangi and Loewenstein (2016) for example show that subjects in the laboratory are investing more in their own entrepreneurial ideas than in others holding the quality of the entrepreneurial ideas constant. Norton, Mocho and Ariely (2012) show that subjects increase their valuation of self-made products, the so called “Ikea-effect”. While unspecific saving tips as for example “Please find a way to safe water” could benefit from the active involvement in the idea-generating process yet they require recipients to invest own cognitive efforts.
Additionally, less specific tips avoid that recipients receive tips that already in use (for example if a car is never washed with water anyways) or if the savings tip not applicable (for example if the recipient does not own a car). Lastly, involving participants to express their opinions is an important factor to improve the acceptability of pro-environmental strategies (Dietz & Stern, 2008; Steg, 2016).

Experimental Design Details
Randomization Method
Randomization done in office by a computer to balance pre-treatment payment and consumption behavior. Treatments are stratified geographically by pipeline location.
Randomization Unit
Randomization is done at the individual level (customer)
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Total amount of customers that are assigned to receive a text message: 15231.
Due to outdated phone numbers and technological restrictions (e.g., network erros), not all customers will receive a text message.
Sample size: planned number of observations
Total amount of customers that are assigned to receive a text message: 15231. Due to outdated phone numbers and technological restrictions (e.g., network erros), not all customers will receive a text message.
Sample size (or number of clusters) by treatment arms
1. Untreated comparison group: 3788
2. Specific tips treatment: 3811
3. Semi-specific tips treatment: 3803
4. Unspecific tips treatment: 3829
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Data Publication
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Program Files
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Reports, Papers & Other Materials
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