Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing.

1. Diffusion of Feedback
Perceptions and Adoption of Devices
Beth Karlin
School of Social Ecology
University of California, Irvine

2. Underlying Assumptions
1. Technology & new media are changing how people
interact with our natural, built, and social worlds.
Karlin 2012

3. Underlying Assumptions
1. Technology & new media are changing how people
interact with our natural, built, and social worlds.
2. There are potential opportunities to leverage these
changes for pro-social / pro-environmental benefit.
Karlin 2012

4. Underlying Assumptions
1. Technology & new media are changing how people
interact with our natural, built, and social worlds.
2. There are potential opportunities to leverage these
changes for pro-social / pro-environmental benefit.
3. Psychology provides a rich history and theoretical base
with which to understand this potential.
Karlin 2012

5. Transformational Media Lab
Mission:
Our lab studies how media is (and can be) used to
transform individuals, communities, and systems.
Karlin 2012
Narrative
Strategies
Social Action
Campaigns
Energy
Feedback

6. What is Feedback?
“Information about the result of a process
or action that can be used in modification
or control of a process or system”
Oxford English Dictionary
Karlin 2012

7. What is Feedback?
“Information about the result of a process
or action that can be used in modification
or control of a process or system”
Oxford English Dictionary

8. Kempton & Layne, 1984

9. How much energy does your washer use?
Karlin 2012

10. How about your whole house?

11. The “Behavioral Wedge”
— “Unlocking Energy Efficiency in the US Economy”
— $1 trillion
— 20 gigatons of greenhouse gas
“…but only if the nation can craft a comprehensive and innovative
approach to unlock it.” (McKinsey & Company, 2009)
— “Household actions can provide a behavioral wedge to rapidly
reduce carbon emissions”
— 5-12% reduction in 5 years
— 9-22% reduction in 10 years
“…without waiting for new technologies or regulations or changing
household lifestyle.” (Dietz, Gardner, Gilligan, Stern, & Vandenbergh, 2009)
Karlin 2012

12. Our Window of Opportunity
RIP
Traditional Meter
Circa 1880 –2020
Automatic transmission to utilities
Feedback to consumers
Karlin 2012

13. 200+ products in the market
Karlin 2012

14. Looking at past research
— 100+ studies conducted since 1976
— Effect sizes ranged from -.0830 to .4803
— Mean r-effect size = .1174 (p < .001)
— Moderating variables:
— duration (longer = more effective)
— Frequency (more frequent = more effective)
— Medium (computer/device > paper)
Karlin 2012

15. Limitations of Studies
— Not naturalistic
— Participants recruited to participate
— May be different from “active adopters”
— Not comparative
— Most studies tests one type of feedback (vs. control)
— Very few commercial products in studies
— Not testing mediation
— DV is energy use, but studies rarely test possible
mediators to explain effectiveness
Karlin 2012

16. Present research
1. Identify ‘naturalistic’ users of feedback
— Who is really using these products?
— Purposive sampling
2. Ask about the user experience
— Enables comparisons between devices
— Gain insights into usability, adoption, etc.
3. Explore perceptions and barriers
— Understand market beyond the “early adopters”
— Identify potential barrier and leverage points
Karlin 2012

17. But first…
A
(very)
brief
introduction
to
Diffusion
of
Innovation
Theory
Karlin 2012

18. Diffusion of Innovation
Theory of technology adoption which explains:
1. Social process by which an innovation spreads throughout a population
2. Personal process by which individuals decide to adopt an innovation
(Rogers, 1962) Karlin 2012

19. Diffusion of Innovation
Theory of technology adoption which explains:
1. Social process by which an innovation spreads throughout a population
2. Personal process by which individuals decide to adopt an innovation
(Rogers, 1962) Karlin 2012

20. Diffusion of Innovation
Theory of technology adoption which explains:
1. Social process by which an innovation spreads throughout a population
2. Personal process by which individuals decide to adopt an innovation
(Rogers, 1962) Karlin, 2012

21. Our Study
Antecedent characteristics:
1. Demographic
2. Psychographic
Knowledge Persuasion Decision Confirmation
Knowledge factors:
1. Awareness
2. Impression
Perceived Barriers
1. Cost
2. Requirements
Sample: 836 adults who use energy in the home
Method: 15-minute online survey on energy conservation and feedback devices
Variables: Demographic & psychographic variables; awareness, impressions and use of
feedback devices, willingness to pay, barriers to adoption.
Confirmation factors:
1. Usability
2. Outcome
Karlin 2012
Did they adopt?
Social System
1. Adoption

22. Our Study
Antecedent characteristics:
1. Demographic
2. Psychographic
Knowledge Persuasion Decision Confirmation
Karlin 2012
Did they adopt?

23. Are feedback users different?
Demographic Psychological
Gender Environmental Motivation
Age Environmental Concern
Race Financial Motivation
Marital Status Price Consciousness
Political Affiliation Social Motivation
Education Social Norms
Income
Home Type
Homeownership
Karlin 2012

24. Demographic
Variable Feedback users Non-feedback users
Gender*** 46% female
54% male
70% female
30% male
Age** 45.5 years 39.9 years
Race 81.7% Caucasian
1.2% Hispanic
6.1% Asian
1.2% African-American
9.7% Other/Decline
81.8% Caucasian
6.7% Hispanic
6.1% Asian
1.6% African-American
3.8% Other/Decline
Marital Status* 62% married
38% not married
52% married
48% not married
Political Affiliation*
(1 = liberal, 5 = conservative)
2.04 2.33
Education 17.9 years 17.4 years
Income** $104,000 $88,000
Home Type ** 74% detached house
26% apartment/condo/other
53% detached house
47% apartment/condo/other
Homeowner*** 82% own
18% rent
57% own
43% rent
* p < .05, ** p < .01, p < .001

25. Psychographic
Variable Feedback users
Non-feedback users
Environmental
- Environmental Concern*** 4.40 4.18
- Environmental Motivation** 3.18 2.80
Financial
- Price Conciousness* 0.70 0.59
- Financial Motivation** 2.67 3.07
Social
- Social Norms 3.04 2.92
- Social Motivation 1.95 1.83
* p < .05, ** p < .01, p < .001
Karlin 2012

26. What variables best explain variance?
Karlin 2012

27. Our Study
Knowledge Persuasion Decision Confirmation
Karlin 2012
Did they adopt?
Social System
1. Adoption

28. Adoption
Questions
— What device/system did you use?
— How did you find out about it?
— Where did you get it?
Findings
— Social Diffusion (family/friends/colleagues)
— 20% learned about product through friend/family
— 14% received product from friend/family
— Utility acquisition (21%)
— Borrowing (13%)
Karlin 2012

29. Our Study
Knowledge Persuasion Decision Confirmation
Karlin 2012
Knowledge factors:
1. Awareness
2. Impression

30. Awareness
Karlin 2012
27%
37% Aware of devices
35%
Aware, but not specific
Not aware of feedback
38%
62%
Adopted
Not adopted
Had no idea that these exist. The idea of it I find very appealing.
I have never heard about this kind of mechanism
as I have not been proactive in learning about it.

31. General Impression
Karlin 2012
10%
48%
42%
Negative
Ambivalent
Positive
No because I don't feel its your business to tell me
what I can use or to monitor my opinions on the matter
Assume they make sense since the
utility companies are promoting them.
A wonderful idea!

32. Our Study
Knowledge Persuasion Decision Confirmation
Karlin 2012
Perceived Barriers
1. Cost
2. Requirements

33. Persuasion
Reason For Not Using Feedback %
Did not know that they existed 44%
Do not know where to buy them 27%
Do not know how to install/set up 18%
Already conserving energy 16%
Never got around to it 15%
Too expensive 11%
No time to install/set up 9%
Do not see any benefit in using such a device 5%
Conserving energy is not a priority in my life 2%
they might not be
available in my area
I’m too busy to worry about
my energy consumption
I already keep track of many things in my life
and do not want to add another burden

34. Willingness to Pay
30%
25%
20%
15%
10%
5%
0%
$0 (Not
willing to
pay)
$1 - $20 $21 - $50 $51 - $100 $101 - $200 $200 +
17%
27% 26%
7%
2% 1%
“I often recommend it, but have a hard time convincing
others that it is worth the [money]”
Karlin 2012
“To induce behavior these devices have to
be free or very low cost.”

35. Our Study
Knowledge Persuasion Decision Confirmation
Karlin 2012
Did they adopt?
Confirmation factors:
1. Usability
2. Outcome

36. Confirmation
Usability
— What do you like / dislike about the product?
— What was your most surprising experience?
Outcomes
— Did knowledge, behavior, and/or energy use change?
— Do you still use this product?
Karlin 2012

37. Confirmation – positive
Usability
— Ease of use
— Effective energy information
Outcomes
— Correct inaccurate assumptions about energy use
— Both general and specific behavior change reported
We installed power strips to easily power off all
high energy items
Karlin, 2012
I had no idea how much energy computers used

38. Confirmation - negative
“Rebound Effect”
— 15% were surprised that they used less energy than they thought
Diminishing utility
“…I’ve actually wound up using more energy on some devices
when I see how little energy they use (my laptop, for one).”
— 48% said they do not still use the product
— No longer in possession/borrowed
— Do not see a need to continue using
“it’s served it’s purpose”
“I checked almost every device I have, so continued usage isn't
very informative unless I start tracking usage in a spreadsheet -
way too much work.”
Karlin, 2012

39. Implications
1. Further research into active feedback adopters could yield
positive results for segmentation.
2. Research into leveraging social networks to promote the use
of feedback devices is promising.
3. There is promise for utility-based and lending/borrowing
programs for distribution.
4. Integrating injunctive social norms (e.g. social comparison)
could address rebound effect.
5. Further research is needed into actual and perceived barriers
of potential users.
Karlin 2012

40. Closing Thoughts
“Energy efficiency is not just low-hanging fruit; it is fruit
that is lying on the ground.”
Steven Chu, US Energy Secretary
Acknowledgements
uci@home research team
David Kirkby, Physics Daniel Stokols, Psychology
Nora Davis, Social Ecology Kristen Gamble, Psychology
Haly Hererra, Engineering Angela Sanguinetti, Planning
Contact: bkarlin@uci.edu