Applying decision science methods to identify
non-economic factors to energy efficiency
investments in the commercial sector
Nichole Hanus
E n g i ne e r i ng a n d Pu b l i c Po l i c y, C a r n e g i e M e l l o n U n i ve rs i t y
A d vi s e d by : Ga b r i e l l e Wo ng- Pa ro di , C M U
A l ex D avi s , C M U
I n e s A zeve d o, C M U
B EC C 1 0 / 19/ 2016
Low EE adoption rates among commercial buildings
• Commercial buildings
account for ~20% of US
energy consumption
(CBECS, 2012)
• Annual energy reduction
of 3% per year is
achievable (DOE, 2014)
(Emerging Scholars, 2012)
• Policy initiatives – Better Buildings Initiative 20% reduction by 2020
• 3.5 billion square feet of commercial building space committed out
of 85 billion square feet (DOE, 2015)
Despite efforts and potential, adoption rates low
2
Decision model from the literature
Behavioral
Decision
Profile
Social Psychology (e.g.
political ideologies,
corporate social
responsibility)
Organizational &
Social Influences
Internal
Influences
(e.g. tenants)
Building Systems
Options
Investment
Decision
External
Influences (e.g.
government)
3
Equipment
Selection
Alternative
Investments
Reserves
Economics
Behavioral
Economics (e.g.
bounded rationality,
time discounting)
Financing
Models
Investment
Economics
Existing
Equipment
Status
New
Technology
Options
Interview Protocol
EE climate in
Pittsburgh
Q: Can you describe
what, if any, areas of the
market have had less
penetration in regard to
EE?
A: “Medium sized
manufacturers. They
probably represent the
biggest sector in
Pittsburgh’s economy.
They operate on such a
margin. They are worried
about making payroll and
getting product out the
door.”
4
Motivations/
barriers in EE
Social
Influences
Q: What do you believe
motivates building
owners to pursue EE?
Q: Can you list any
buildings and/or
companies that you
perceive as energy
efficient?
A: “It’s probably broken
up into 3 categories:
mission-oriented, best
practice, and saving
money.”
A: “A building like 11
Stanwix with Chris
Pinelli is an example of
a building that is really
operating well.”
Ranking
Exercises
Methods of analysis
Open-ended responses
• Transcription Coding
• Open-coding procedure (Strauss, 1987)
• Inter-rater reliability by pairwise
agreement – to be completed
(Neuendorf, 2002)
• Frequency of mention & code
pairings
Ranking data
• Exploratory data analysis
• Comparative frequency plots
• Comparative ranking plots
• Fisher’s Exact Test
• Experts vs. Owners/Managers
• Motivations & Barriers
Listed Not Listed
Expert
A
B
A+B
Owner/Manager
C
D
C+D
A+C
B+D
=
5
=
+
(1 −
)
Investment Decision Process – Organizational & Social Influences
“My guys are really good. They like learning about this stuff [energy efficiency],
so they went to school for it. I’m confident in their abilities” – Owner/Manager
140
No. of Mention
120
(10)
Owner/Manager
Expert
(10)
100
(#) No. of Participants
80
(9)
60
(7)
(10)
(10)
40
20
(4)
(9)
(7)
(8) (9)
(8)
(4)
0
Mentioned Discussion of Motivations Investment
Social
Building Staff
Consultant
Influences
6
Goals &
strategy
Organization
Barriers
Comparison of barriers between experts and owners/managers
Experts (n = 10)
Owners and Managers (n = 10)
Capital
Staff support
low priority
* EE
Lack incentive
Uncertainty
Lack
information
*
Investment horizon
Immature tech.
Lack financing
Time discounting
Fear of Change
Tech. knowledge
Lack policy
Generalized
benefits
Tech. support
Tenants
Future tech. costs
Low energy costs
Building codes
Building engineers
(n = 20)
7
10
Economic
Barriers
* Significantly more
listings by Experts (p<0.05)
5
0
Frequency (non-NA)
5
10
Comparison of motives between experts and owners/managers
Experts (n = 10) Owners and Managers (n = 10)
Reduce energy costs
Retain tenants
Reduce labor costs
Reputation
Imminent investment
Real estate
Premium tenants
Fresh air
Occupant
productivity
Ample subsidies
Occupant comfort
Occupant health
Social responsibility
Industry leaders
Regulation/policy
Reliability/security
Healthy building
(n = 17)
Corporate Social
Responsibility
(CSR)
10
5
0
5
Frequency (non-NA)
8
10
Key findings from Phase 1 interviews
• Heterogeneity among interviewed experts and
owners/managers regarding value of CSR
• Interviewed owners/managers listed more CSR motivations than
experts
• Interviewed owner/managers listed tenants, employees, and
building engineers as influential to their EE investment decisions
• Information is a barrier recognized by interviewed experts
and owners/managers; interviewed owners/managers
value input from sources unaffiliated with products
• Potential emerging concepts identified in interviews
suggest psychological and social influences are promising
areas of research in EE investment decision making
9
References
1.
2.
3.
4.
5.
6.
Better Buildings Challenge Progress Update, U.S. Department of Energy. [Online.]
Available :http://energy.gov/sites/prod/files/2014/05/f15/progress-updatemay2014_0.pdf
Better Buildings U.S. Department of Energy (2015). Progress Report 2015.
Retrieved from:
http://betterbuildingssolutioncenter.energy.gov/sites/default/files/news/attach
ments/DOE%20BB%202015%20Progress%20Report%20052015_0.pdf
Commercial Buildings Energy Consumption Survey. [Online.] Available:
http://www.eia.gov/consumption/commercial/reports/2012/preliminary/index.c
fm?src=‹
Emerging Scholars (2012). Image retrieved from:
http://blog.emergingscholars.org/wp-content/uploads/2012/09/mg_0175-fbglam-1024x512.jpg
Neuendorf, K. (2002). The Content Analysis Guidebook. Thousand Oaks, CA: Sage
Publications.
Strauss, A. (1987). Qualitative Analysis for Social Scientists. Press Syndicate of the
University of Cambridge, New York, NY.
10