The Decision to Go Green: Individual vs. Group Influences on Our Likelihood to Build Sustainably

2009 BECC Conference Presentation

The Decision to Go Green: Individual vs. Group Influences on Our Likelihood to Build Sustainably

Marcel Harmon, PhD, PE, LEED-AP

Introduction (SLIDE 1)

Introductory remarks. (SLIDE 2) Depending on the source you site, buildings in the United States

account for anywhere from 40 to 50 percent of all carbon dioxide emissions compared to transportation

and industry. (SLIDE 3) Globally, studies place that value anywhere from 30 percent to 50 percent. I

think everyone in this room would agree that the built environment in general consumes a significant

portion of our world’s resources and its collective carbon footprint will have to be reduced to effectively

bring down greenhouse gas emissions to levels proposed by the IPCC and other organizations.

(SLIDE 4) If we use LEED registration and certification as a proxy for sustainability, we can see

that there has been a rapid increase in reducing the building sector’s carbon footprint over the last five

years, and that trend is expected to continue. But will it happen fast enough? (SLIDE 5) Out of the eight

“wedges” of global actions for reducing GHG emissions, one is devoted to building energy efficiency,

represented by the maroon wedge here. Effectively applying each wedge before 2050 would allow

emissions and CO2 levels to stabilize. According to the recently released 2009 Green Building Market

and Impact Report, the current projected penetration rate of LEED certification has the potential to

account for half of this building wedge 2050 target. Unfortunately the slope of the LEED carbon

reduction line shown here is too shallow through 2030 – only accounting for roughly 10% of the wedge

by this date. The rate of LEED adoption (as well as other green certification systems and sustainable

design/construction practices) must be increased in the near term to maximize GHG reductions from

building energy efficiency in order to match or exceed the slope of the building wedge line.

But anyone who’s worked in the building construction industry knows that it’s often a struggle

to convince an owner to incorporate a truly effective sustainable design, construction, and O&M process

into their various projects. Premiums associated with sustainable design/construction (small though

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they may be), paybacks longer than 3 years, narrow views of the benefits that exclude the occupant, and

fears associated with having personnel (and occupants) capable of operating and maintaining a green

facility, are often enough to kill “green”, or greatly reduce its scope. I’ve touted occupant benefits ‘till

I’m blue in the face with some owners to no avail. Benefits that include performance/productivity

enhancements resulting from daylighting, (SLIDE 6) from indoor air quality improvements, (SLIDE 7) and

from increased local environmental control.

(SLIDE 8) Such occupant factors comprise a large portion of business operating expenses.

Studies have shown that over the span of about 20 years, the ratio of building construction cost to

building operations costs is about 1 to 1.5, but the ratio of construction costs to business operations is

on the order of 1 to 15. So the occupant-related financial benefits of successful green building far

outweigh the energy- and operations-related benefits. But even a life cycle cost analysis taking all of

these factors into account often isn’t enough. Why?

Background/Hypothesis

(SLIDE 9) Human interaction is a complicated, messy process with multiple competing interests

and benefits that occur at the various levels of individual and group interaction involved in any given

situation. This, along with the hierarchy of variables involved in our consumption, conservation, and self-

preservation habits can elevate short-term considerations above long-term considerations.

(SLIDE 10) Enter the studies by researchers affiliated with the Center for Research on

Environmental Decisions (CRED) – their research has demonstrated that the long term benefits that

result from green, sustainable design are given more weight by groups as opposed to individuals.

Cognitive psychologists generally divide our decision making systems, with respect to risk, into analytical

vs. emotional reactions. The former carefully considers costs versus benefits, while the latter interprets

risks emotionally; as a “primitive and urgent reaction to danger” intended to rapidly size up a given

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situation and remove us from that danger. Neither system is particularly suited for rationally considering

long-term benefits thanks to our evolutionary past as hunter/gatherers.

(SLIDE 11) This is not meant as an insult, but you all have Stone Age brains. Our “stone-age”

brains and cognitive abilities evolved in the vastly different and more limited context of our ancestors;

the people dealt with on a daily basis were fewer, the geographic area and environmental variability

smaller (their world was “smaller”), and the “future” limited to the annual cycles of weather, migration,

etc. Most of our evolutionary history was spent in this type of environment (timeline around the room

explanation). As a result our analytical analyses and emotional responses tend to over emphasize those

events, threats, etc., that have immediate impact in our daily lives – i.e., job loss, daily deadlines, etc. vs.

rising sea levels or GHG emissions.

In addition, these studies have demonstrated that the degree of our reactions, responses,

urgencies, and calls to action end up being relative to our perception of the impact on ourselves and

those we call our own. Current and projected crises in other countries or regions, or that affect

different social/cultural groups and are not perceived as providing us with risk, may not result in a

response or change in our behavior.

However, this picture begins to change when decision making shifts from the individual and very

small group level to larger groups. If cooperation and group unity is achieved, decision making is often

made with respect to the common good. Delayed, long-term benefits are given more weight by groups

(households, companies, community boards, etc.) than by individuals. For example, the development,

modification, and acceptance of building codes is a group endeavor; one that generally increases initial

cost while at the same time providing for a safer environment over the life-spans of our buildings, which

may be multi-generational.

(SLIDE 12) This fits well within a branch of evolutionary theory known as multi-level selection, or

MLS. MLS provides a framework in which natural selection and other evolutionary forces operate at all

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levels simultaneously – genes, cells, organisms/individuals, and groups of organisms/individuals.

Sometimes environmental and social/cultural conditions are right for the evolutionary forces to be

stronger at the level of the individual; sometimes these forces are stronger at the group level, resulting

in highly cohesive groups. Uniformity among group members, high levels of cooperation, and functional

integration become the hallmarks of successful groups.

(SLIDE 13) Within MLS the two sides of human behavior known as selfishness and pro-social

behavior each become advantageous at different levels of interaction. While “selfish acts”, such as a city

official accepting a bribe to ignore aspects of the building code for a particular project, or a CEO deciding

to avoid the extra cost of installing an intelligent lighting control system, will benefit individuals or small

groups competing within larger groups, pro-social behaviors, such as the pursuit of LEED Platinum or

dying for one’s country, will benefit larger groups encompassing these individuals and smaller groups.

Selfish behaviors tend to be locally advantageous and more relevant in the short term, while pro-social

behaviors tend to be globally advantageous and more relevant in the long term. Prosocial behaviors

also tend to enhance cooperation among group members. And our social/cultural norms act as a kind of

“glue”, binding together unrelated individuals within larger groups and providing a measure of

uniformity in their behavior.

(SLIDE 14) The selective advantage that cooperation and prosocial behavior offered our

hunter/gatherer ancestors fostered the development of a species of very social creatures who in general

love to congregate. Other CRED studies have demonstrated how easy it is to get even random

individuals to work together. In one test subjects were given a blue star and told they were on the “blue-

star team”; this alone increased group participation from 35 percent to 50 percent. Just seating them

together at a table increased participation rates to 75 percent. This ability to function easily and well

within groups is a core component of what it is to be human, and may offer some insights in promoting

sustainable behaviors.

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So going back to the building construction industry, it would seem that short term, local,

benefits often outweigh long-term benefits when making decisions on how green to be. Following the

above line of reasoning, this suggests that in those cases where short term, local benefits have won out,

individuals or small groups whose common good did not necessarily coincide with green’s delayed

benefits were the primary decision makers involved. And it would also suggest that these decision

makers had less influence from other people within their own organization, as well as outside their

organization. So this essentially became the hypothesis to test:

(SLIDE 15) Hypothesis: The more people who have a say in the decisions involved in a

construction project (particularly earlier in the design process), the more likely it will be designed and

built sustainably (LEED or otherwise), all else being equal.

Methodology/Study Structure

To test this, I decided to compare a dataset of certified, non-certified but green, and

conventionally designed facilities with respect to the decision makers – the number of decision makers

involved, who they were, their demographic make-up, their core values, and the degree of outside

influence that impacted their decisions. By certified, I’m referring to any recognized formal means of

sustainable design & construction verification. LEED is typically what comes to mind here, but there are

others, such as Energy Star, Green Globes, Green Star, etc. Data collection has been primarily through

surveys to members of project design teams as well as building owners, with subsequent follow up for

clarification where respondents indicate a willingness to be contacted. In addition, further background

research on a project-by-project basis will occur as a means of randomly “checking” the answers

submitted, as well as to further clarify project contextual information related to the decision makers.

• Funding sources for the project

• The number of people involved or influencing the final decision process.

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• The demographic background of the individuals and/or group(s) involved in making the final

decision

• The reasons that the final decision was based on

• How to gauge the success of the project in terms of sustainability.

• The nature of the local social/cultural rules of interactions, the social/cultural concepts of

sustainability (business, ethnicity, etc.) that facilitated the interactions involved in the final

decision making process.

(SLIDE 16) I have divided the research into two phases. Phase 1, which I am currently finishing,

has consisted of 1) developing the survey tool, 2) distributing it internally and externally via a few email

lists (Space-and-Place listserv, Anthrodesign, Epic-Global-Impact, and the BigGreen listserv) for review as

well as to actually collect preliminary data (primarily M.E. Group projects), and 3) analyzing the review

comments and data with the goal of evaluating/fine-tuning the survey tool and the research process in

general. Phase 2 will consist of a much wider distribution of the survey tool to M.E. Group clients,

partners, and contacts, multiple email lists, and social networking sites. I am considering using the

preliminary Phase 1 findings for funding requests, perhaps partnering with a university and/or other

private partner to assist with the follow-ups, random checks, and data analyses.

(SLIDE 17) The survey itself currently consists of 30 questions, subdivided into 3 sections.

Section 1 provides the “book-keeping” information on the project itself, such as project name, facility

type, funding sources, etc. Section 2 provides the information on the sustainable nature of the project –

the types of sustainable elements that were incorporated into the project regardless of whether

certification was pursued. It also provides the information on the type and version of certification

system used (i.e., LEED NC, version 2.2) and the level of certification achieved (i.e., certified, silver, gold,

platinum). Section 3 seeks to understand the quantity of people involved in the final decision and the

number of people inside and outside the organization influencing this decision. In addition, it seeks to

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determine the respondents understanding of why sustainable elements and/or certification was or was

not pursued. For those that are interested in viewing the survey, it is at the following address; and I

would welcome additional comments before implementing phase 2.

Initial Results/Discussion

(SLIDE 18) Currently I have 26 projects entered into the database via this survey tool – not

enough to reach definitive conclusions, but their analysis is nevertheless interesting and has provided

some insights into the remaining process. I’ve initially looked at the correlation between the number of

people involved in the decision process (directly and via influence) and both a) the number of

sustainable elements incorporated and b) the level of certification sought. Specifically I ran a Kendall’s

Tau-B correlation test and the table here shows the resulting rank correlation coefficients for each

comparison. The coefficient can range from -1 to 1, with -1 indicating perfect disagreement or negative

correlation between the two variables, 1 indicating perfect agreement and 0 indicating complete

independence between the two variables (no correlation).

To quickly clarify the variables involved, the sustainability indicator is simply the sum of the

number of sustainable elements incorporated into each project and the certification indicator

represents the survey responses weighted by the certification level achieved. In the survey, the people

involved were subdivided into 1) the number directly involved in the decision, 2) the number within the

organization who influenced the decision makers (such as employees), and 3) the number outside the

organization who influenced the decision makers (such as tenants, customers, etc.). The other two

columns represent combining the number estimates for a) all those within the organization and b) all of

the people involved.

Several things are worth noting. All coefficients are positive, indicating at least some agreement

in all of the variable comparisons. So as the number of people involved per project increases within this

dataset, so does the degree of sustainability and certification. In addition, notice that the agreements

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are stronger for the certification indicator than for the sustainability indicator. This is not surprising as

achieving certification is a prosocial formal process that typically requires some additional resources for

the certification paperwork, commissioning, and generally incorporating a broader suite of sustainable

elements. In contrast, the sustainability indicator simply tells us whether or not individual sustainable

elements were incorporated into design and construction, not necessarily as part of a focused prosocial

sustainable effort. Even in an environment where short term, local considerations rule, individual

sustainable elements will make into a design here and there because of the short term benefits they

may also offer.

And finally note that the coefficients indicate increasing agreement going from the individual

decision makers, to those within the organization influencing the decision makers, to those influencing

externally. Now this may partially be an artifact of the number ranges that I’m using in the survey to

choose from for the number of people questions - organizational decision making bodies typically

consist of smaller numbers of people, and therefore the ranges that I’m using in the survey may not be

fine enough to detect the increases in the decision makers that may be occurring. Regardless, though,

we’re still talking about small numbers of people even if there is an increase, so I think most of the

answer lies in the previous MLS and CRED decision making discussions.

Now all else being equal, individuals and small numbers of people are more likely to make

cost/benefit decisions within a short term, local framework. Hence the lower agreement values for this

column. But when we move to the level of the organization, there is an increase in the level of

agreement, though its still below 0.5, likely reflecting a highly contextual mix of short term, local and

long term, global considerations at play. But the biggest jump in agreement occurs going from within the

organization to outside the organization. Here we approach both numbers of people and geographic

areas that potentially move us substantially beyond short term, localized costs/benefits. (SLIDE 19)

Assuming that the Phase 2 efforts confirm these results, this would suggest that by somehow creating

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an environment where building owners actively reach out to their employees, as well as their clients,

tenants, surrounding neighbors, etc., and directly solicit their opinions regarding any new construction

or existing renovations, it will increase the likelihood that these projects will be sustainable and

certified.

Conclusion

(SLIDE 20) Now obviously with such a small dataset this analysis has been more of an intellectual

exercise to help lay the groundwork for the Phase 2 portion of the research. Research that will continue

to illuminate the nature of group vs. individual influences on sustainable decision making in the building

construction industry, as well as how contextual social/cultural norms impact the nature of these group

vs. individual influences. And though preliminary, the results did support the hypothesis that the more

people who have a say in the decisions involved in a construction project, the more likely it will be

designed and built sustainably, all else being equal. And even the Phase 1 research will provide some

insight into facilitating policies, messages, and procedures that increase the rate of effective sustainable

design/construction. Having owners reach out to employees, clients, tenants, etc., to solicit direct input

being a case in point. Now I try to avoid bad puns whenever possible, but this is going to require a

“group” effort to move forward. It will be a challenge, but on the bright side its one that we’re highly

adapted for in order to meet.

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The Decision to Go Green:
Individual vs. Group Influences on Our
Likelihood to Build Sustainably

Marcel Harmon, Ph.D., P.E., LEED‐AP

Built Environment’s Impact
48%
Buildings
27%
Industry
25% Transportation

U.S. Energy Consumption & GHG
Emissions By Sector
Source: Architecture 2030 & US Energy Information Administration

Buildings in the U.S.,
• Consume 71% of the electricity produced.
• Consume 12% of the total water used.
• Produce 65% of the waste generated.
Buildings worldwide,
• Consume 40% of the total materials & energy used.
• Consume 17% of the total water used.
• Consume 25% of the total wood harvested.
Source: US Green Building Council (USGBC)

LEED Registered Vs. Certified Floor Area

Source: GreenerBuildings and JohnsonDiversey Webinar, 11/05/09

LEED & Building Carbon “Wedge”

Source: GreenerBuildings and JohnsonDiversey Webinar, 11/05/09

Performance/Productivity
Compared to little or no daylighting,
classrooms with large amounts of daylighting
have been found to increase the rate of
student learning by:
20% in math
26% in reading
- Heschong Mahone Group. 1999. Daylighting
in Schools: An Investigation into the
Relationship Between Daylight and Human
Performance. Report submitted to Pacific Gas
and Electric. http://www.h‐m‐g.com.

IAQ Improvements:
save up to $58 billion in lost sick time
save additional $200 billion in worker
performance.

- Fisk, W. G. 2000, Health and Productivity Gains from
Better Indoor Environments and Their Relationship
with Building Energy Efficiency. Annual Review of
Energy and Environment 25(1):537‐566. Later
updated for 2002 dollars.

Increased tenant environmental control have
been found to provide average measured
workforce productivity gains of:
7.1% with lighting control,
1.8% with ventilation control, and
1.2% with thermal control.

- Kats, G., L. Alevantis, A. Berman, E. Mills, and J. Perlman,
2003. The Costs and Financial Benefits of Green Building: A
Report to California’s Sustainable Building Task Force.

Sustainable Building Benefits
Over 20 – 25 years, for a 16
typical service business: 14

Ratio of amortized 12
10
construction cost to
8
building operating costs to
6
staff salaries/business 4
operating costs = 2

1:1.5:15 0

Construction Bldg Business

- Commission for Architecture and the Built Operations Operations
Environment and the British Council for Relative Cost
Offices, London, UK, 2005.

Decision Making Systems

Analytical vs. Emotional

Stone‐Age Minds
Our analytical analyses and
emotional responses tend
to over emphasize those
events, threats, etc., that
have immediate impact in
our daily lives – i.e., job
loss, daily deadlines, etc.
vs. rising sea levels or GHG
emissions

Multi‐Level Selection (MLS)
Group

Evolutionary forces act at
Individual
all levels simultaneously,
and may be stronger at a
Cell
specific level at any given
time
Gene

Prosocial Vs. Selfish Behaviors
Prosocial
Selfishness
Behavior

Individuals & Larger
Small Groups Groups

Within Between
Group Group
Selection Selection

Short Term & Long Term &
Local Global

Hypothesis
The more people who have a say in the
decisions involved in a construction project
(particularly earlier in the design process), the
more likely it will be designed and built
sustainably (LEED or otherwise), all else being
equal.

Research Phases
Phase 1
• Developing the survey tool;
• Distributing it internally and externally for review comments and
preliminary data;
• Analyzing the review comments and data to evaluate/fine tune
survey tool and research process

Phase 2
• Possible partnering and funding requests;
• Wider distribution of final survey tool;
• Follow up and background research
• Data analysis, interpretation, and conclusions

Survey

http://www.formspring.com/forms/megroup‐project_sustainability_survey

Kendall Tau‐B Rank
Correlation Coefficients
Increasing Numbers of People
Increasing Agreement

Internal People External People
People Making Combined Combined
Influencing Final Influencing Final
Final Decision (1) 1 + 2 1 + 2 +3
Decision (2) Decision (3)
Sustainability
0.158 0.232 0.174 0.499 0.476
Indicator
Certification
0.369 0.472 0.397 0.651 0.605
Indicator

Generally Increasing Agreement

Reaching Out to Employees,
Customers, Tenants, Etc.

The Decision to Go Green: Individual vs. Group Influences on Our Likelihood to Build Sustainably

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