Behavioural interventions for
energy efficiency adoption: an
example in China
MASSIMO TAVONI (WITH YU GAO, GIOVANNA D’ADDA)
POLITECNICO DI MILANO
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Behavioural programs for EE
Mckerracher and Torriti, 2013
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Purchasing decisions
Electric appliances and equipment are long lasting
E.E. purchasing ensure persistent savings
Behavioural reasons for not choosing efficient products:
◦ Present bias and inconsistent time preferences
◦ Information gap about energy consumption
◦ Salience of purchasing price
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Incandescent light bulbs
Compact Fluorescent lamps
(CFLs)
Light-emitting diode lamps
(LEDs)
Background on light bulbs
60w
14w
7w/8w
Cost $7 per year
Cost $2 per year
Cost $1 per year
Price: $1
Lifespan: 1 year
Price: $4
Lifespan: 8 years
Price: $6
Lifespan: 10 years
Allcott & Taubinski (2015, AER)
Our research
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Why don’t people buy better light bulbs?
• Other self-harming behaviors:
Not saving enough, eating unhealthily,
smoking, etc.
Present bias
Lack of knowledge about direct
and indirect costs
Delay payment
Provide info about consumption
and environmental impact
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Experimental Design: two dimensions
Get Now
Pay Now
Get Now
Pay Later
Get Later
Pay Later
Baseline
Cost
Information
Environmental
Information
Baseline
Cost
Information
Environmental
Information
Cost
Information
Environmental
Information
Baseline
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Experimental Design:
information dimension
o Shopping budget of CNY30 (USD4.5)
o Incentive compatible: One pairwise choice is randomly chosen
Cost
Information
Baseline
￥20
￥16
￥8
Environmental
Information
1. In China, electricity is mainly
generated from coal.
2. Burning coal is directly related to
greenhouse gas emission and air
pollutant emissions.
3. Inhaling air pollutant leads to health
problems.
4. Your choices of light bulbs affect air
pollution. LEDs produce 50% less
pollutants compared to CFLs.
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Experimental Design:
time dimension
Now
Get Now
Pay Now
• Light bulb
• Remaining budget
Get Now
Pay Later
• Light bulb
Get Later
Pay Later
After 1 month
• Remaining budget
• Light bulb
• Remaining budget
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Subjects
• Chinese on-line panel: Sojump
• N=813 (409 female)
• Payment: Show-up fee CNY3 + shopping budget CNY30
• Mean response time: 18 min
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Results
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Consumers heterogeneity
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Results:
Tobit regression on panel data
Main effects : DV (WTP for LEDs)
Coefficients
SE
Coefficients
SE
(Intercept)
29.13**
11.74
Kids
1.13
1.02
Tr. NOW
4.24***
1.34
Age
-0.3
0.92
Tr. GNPL
2.23*
1.31
CC_nonbeliever -1.32
2.68
Cost
Information
7.41****
0.73
CC_Anxious
5.89***
1.89
Environmental
Information
5.14****
0.85
Delivery
2.20**
1.11
Log(Income)
1.09
0.84
Female
-0.87
1.09
<0.1 *
<0.05 **
<0.01 ***
<0.001 ****
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Conclusions
• Energy purchasing decisions are key for promoting efficiency, and
are often sub-optimal
• Utilities (marketplace) and retailers can use behavioural science
insights on how to promote efficient purchasing
•Ongoing research to test which mechanisms work better on which
decisions and which type of consumers
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• [email protected]
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