SOCIO-PHYSICAL FACTORS AFFECTING ENERGY
CONSUMPTION IN SINGLE FAMILY DWELUNGS: AN
EMPIRICAL TEST OF A HUMAN ECOSYSTEMS MODEL

Dissertation for the Degree of Ph. D.
MICHIGAN STATE UNIVERSITY
BONNIE MAAS MORRISON
1975

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ABSTRACT

SOCIO-PHYSICAL FACTORS AFFECTING
ENERGY CONSUMPTION IN SINGLE
FAMILY DWELLINGS:

AN EMPIRICAL TEST OF A
HUMAN ECOSYSTEMS MODEL

BY

Bonnie Maas Morrison

Selected socio-physical determinants were hypothe—
sized to affect both 1) belief in the reality of the
energy problem, and 2) total direct energy consumption
(BTU's) in single family detached dwellings. The re-
search undertaken here tested the viability of a second-
order input/output model of physical housing factors
and family factors derived from a broad human ecosystems
model based in systems theory. Multiple step-wise re-
gression and recursive path analysis were used as the
analytic mode.

Four hypotheses were generated which tested both
the net and gross aspects of the belief variable and the
energy consumption variable via hypothesized direction
of relationships (positive and negative signs), as well

as the rank ordering of magnitudes of relationships.

Bonnie Maas Morrison

Although minor changes in hypothesized signs
were observed and shifting of rank ordering occured, a
substantial amount of the variance for the belief vari-
able (R2 = .427) and the energy consumption variable
(R2 = .485) was explained.

The findings indicated that belief in the reality
of the energy problem is positively related to mean
(husband-wife) educational attainment, agreement (hus-
band-wife) on the availability of electrical energy and
reported total costs of all energy forms used in the
dwelling unit (June 1974-May 1974), suggesting that
belief is a factor in awareness of and experience with
energy consumption problems.

Energy consumption in single family dwellings
was found to be related to components of life-style and
behavior, as well as the physical housing factors. The
number of persons in the household, the number of major
appliances and the number of rooms in the dwelling unit
contributed most to the variance explained. Belief in
the reality of the energy problem does not effect a
change in energy consumption patterns.

Therefore, this study indicates that in the
short-run (energy crisis period, Winter 1973-74) energy

consumption was determined by aspects of family life

Bonnie Maas Morrison

style, which did not incorporate a new energy conserva—
tion ethic. Implications for future research, public
policy and educational programming based on these

findings are suggested.

SOCIO-PHYSICAL FACTORS AFFECTING
ENERGY CONSUMPTION IN SINGLE
FAMILY DWELLINGS:

AN EMPIRICAL TEST OF A

HUMAN ECOSYSTEMS MODEL

BY

Bonnie Maas Morrison

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Family Ecology

1975

Copyright by
BONNIE MAAS MORRISON
1975

ACKNOWLEDGMENTS

Undertaking the development and writing of a
doctoral dissertation can be made analogous to the systems
perspective found within the following pages. This
system can be viewed as an adaptive self-organizing
system reacting to convergent inputs, controlled by feed-
back from many sources; the output of which is printed
between these covers.

Each of the following persons comprise important
positions in this sytem for the functions they served
in the systems dynamic steady state. To each of these
persons I express my deep and sincere appreciation:

Dr. Beatrice Paolucci, who, as committee chair-
person, dissertation-director, mentor and friend, I owe
so much in terms of intellectual stimulation, encourage-
ment, challenge and sense of excellence.

Dr. Margaret Bubolz, who was one of the first to
introduce me to the notion of systems and its potential
for empirical development.

Dr. Robert Rice, who as my department chairman
and committee member, encouraged and supported my seeking
the Ph.D., via flexible teaching and research arrange-

ments .

ii

Dr. Joseph Woefel, who was a most important ad-
visor during the development of the recursive path
analysis and who graciously consented to be a committee
member in the absence of Dr. Donald Montgomery.

Dr. Linda Nelson, who also served as department
chairperson and who also remained flexible in relation
to teaching assignments.

Dr. Robert Boger, director of the Institute of
Family and Child Study, who both encouraged my involve-
ment in the interdisciplinary research team and gave
support to my position as project coordinator.

Dr. Sylvan Wittwer, director of the Michigan
Agricultural Experiment Station, who funded project
#3152, "Functioning of the Family Ecosystem in a WOrld
of Changing Energy Availabilities."

The interdisciplinary research team and graduate
assistants, who individually and collectively developed
the systems research perSpective out of which this inves-
tigation emanates. Special recognition goes to Dr.
Peter Gladhart, Dr. James Zuiches, and Dr. Mary Zabik
for the unselfish energies devoted to the research pro-
ject. LAlso special gratitude to Joanne Keith, whose
keen understanding, sincere efforts and precision made
this research experience especially rewarding. Mary Ann

Eichenberger and Michael Lawrence, also contributed

iii

 

long hours in the compilation of the energy consumption
data file. Also, I am grateful to the many persons who
worked on the research project: the interviewers, the
field supervisor, the coders and coder supervisors.
Without the many hours spent in collecting and compiling
the data, this study would not have occured.

Judy Pfaff, who served as my able, precise and
patient computer specialist during the develOpment of
the multiple regression and path analysis. We both
learned a great deal.

Sharon Loomis, whose service as typist through
hand written copy to finished product, indicates her
sincere interest and dedication.

Eva Blake, who as helper and friend, maintained
the household decorum, making this endeavor even more
possible.

Ariel Maas, who, along with my father, instilled
in me at an early age a sense of self—worth and competence
so very necessary in defining and pursuing life goals.
Ariel read with a critical eye the manuscript of this
dissertation and gave assistance in finalizing the bib-
liography.

Dr. Denton Morrison, husband, confidante, lover
and friend, who set the example 1: follow and who,
through the frustration and joys of this systems process,
remained supportive of both my intellectual and emotional

These listed persons are but a few of the many
linkages in the system that encompass a much broader
environment of family, peers, friends and scholars,
who have through their Special interest, insight or
strength, managed to both tantalize and encourage me

to pursue this course of action.

TABLE OF CONTENTS

LIST OF TABLES . . . . . . . .
LIST OF FIGURES . . . . . . .
LIST OF APPENDICES . . . . . .
Chapter

I. INTRODUCTION . . . . . .
Energy Dependency . . .
The Context of the Problem .

The Energy Problem: The

Distal Global and National
Environment . . .

The Energy Problem: The Imme—

diate Family Environment
The Study Problem, The Basic

Objectives and the

Assumptions . . . . .
Operational Definitions . .

II. REVIEW OF ENERGY LITERATURE .

Introduction . . . .
The Related Literature . .

Literature Related to Residential
Energy: Directly or Indirectly

Residential Energy . . .

Reviewed Research as Related

to Present Study . . .

III. SYSTEMS THEORY . . . . .

Rationale for a Systems Approach

Systems Approach: The
Energy Problem . . . .
Systems Approach:

The Family . . . . .
General Definition

of Systems . . . . .

vi

Page

xiii

xiv

12
15

20

20
21

25
41

45
47
47
48
49
51

Chapter

Ecosystems, Cybernetic Systems
and General Systems: Structure
and Control . . . . . . .
Structural Commonalities . .
The Functional Unity . . .
Systems Integration: Unique
Contribution to the DevelOp-
ment of the Conceptual
Framework . . . . . . .

IV. THE CONCEPTUAL FRAMEWORK AND
HYPOTHESES O O O C O O O O 0

Development of the Conceptual
Framework of this Study . . .

A Conceptual Framework: Human
Ecosystems Model . . . . .,

The Organism or Environed

Unit: The Family . . . .
The Environments of the Family
The Natural Environment . . .
The Built Environment . . .
The Behavioral Environment . .

The Utility of the Human

Ecosystems Framework . . . .
Deduction Toward the Hypotheses
The Generalized Family
Ecosystem Input/Output Model .
The First-Order Input/Output
Model and Variables of the
Study . . . . . . . . .
The Second-Order Input/Output
Model: The Model to be Tested .

The Statement of Study Hypotheses

V. METHODOLOGY . . . . . . . .

Introduction . . . . . .
The Survey Research Method . . .

The Survey Instrument and

Data Collection Procedure . .
Interview Schedules . . . .
The Interview Procedure . . .
The Procurement of Utility Data
Data Processing . . . . .

The Sample . . . . . . .

The Sampled Community:

The Near Environment . . . .
Sample Design and Selection .
The Urban Sample . . . . .

vii

Page

53
72
72

74

76

76
78
78
79
81
84

89
90

91

94

97
99

101

101
102

, 103"

104
105-
107
109
110

110
111
112

Chapter

VI.

VII.

The Rural Sample . . . . .
Demographic and Socio-economic
Characteristics of the Sub-

sample . . . . . . .
The Mode of Analysis . . . .
Path Analysis . . . . .

The Assumptions of Path
Analysis: A Recursive Model .
The Operational Variables . .

FINDINGS . . . . . . . . .

Introduction . . . . . .
Belief in the Reality of
the Energy Problem . . . .
Findings . . . . . . .
Discussion . . . . . . .
Total Amount of Direct Energy
Consumed in Single Family
Detached Dwellings . . . .

Findings . . . . . . .
Discussion . . . . .
Discussion of Some of the

Interesting Findings . . .

The Path Model . . . . . .
Tests for Recursiveness
and Linearity . . . . . .
The Gross Analysis . . . .
Belief in the Reality
of the Energy Problem . . .
Findings . . . . . . .
Discussion . . . . . . .
Total Direct Energy Consumption
Findings . . . . . . .
Discussion . . . . . . .
In Summary . . . . .. . .

SUMMARY, CONCLUSIONS AND IMPLICATIONS

Summary Overview of the
Research Problem . . . . .
Systems Approach and
Analysis Mode . . . . . .
Need for Residential Energy
Research . . . . . . .
Conclusions . . . . . .
Testing a Systems Model . .
Belief in the Reality of
the Energy Problem . . . .
viii

Page

113

115
120
120

121
124

127
127

131
131
133

137
137
140

142
146

149
151

151
152
152
153
153
153
154

156

156
157
158
159
159

160

Chapter Page

Analytic Conclusions . . . . . . 160
Speculative Conclusions . . . . . 161
Energy Consumption in Single

Family Detached Dwelling Units . . 162
Analytic Conclusions . . . . . . 162
Speculative Conclusions . . . . . 164
Study Limitations . . . . . . . . 168
Major Limitations . . . . . . 168
Other Limitations . . . . . . 169
Other Variables . . . . . . 169
Implications . . . . . . . . 170

n

Future Research 170
Public Policy . 171
Educational Programmi g 173

APPENDICES . . . . . . . . . . . . . 175

BIBLIOGRAPHY . . . . . . . . . . . . 209

ix

Chapter Page

Analytic Conclusions . . . . . . 160
Speculative Conclusions . . . . . 161
Energy Consumption in Single

Family Detached Dwelling Units . . 162
Analytic Conclusions . . . . . . 162
Speculative Conclusions . . . . . 164
Study Limitations . . . . . . . . 168
Major Limitations . . . . . . . 168
Other Limitations . . . . . . . 169
Other Variables . . . . . . . 169
Implications . . . . . . . . . 170
Future Research . . . . . . . 170
Public Policy . . . . . . . . 171
Educational Programming . . . . . 173

APPENDICES O O O O O O O O O O O O O 175

BIBLIOGRAPHY . . . . . . . . . . . . 209

ix

 

LIST OF TABLES

Table ‘ Page

1.--Comparison of Median-Family Incomes,
Selected Years 1947 to 1973 (In
current dollars) . . . . . . . . . 9

2.--Total Fuel Energy Consumption and Annual
Rate of Growth in the United States by
End use 0 O O O O O O O C O O O 11

3.--Total Residential Energy Consumption in
the United States by End Use . . . . . 12

4.--Total Energy (gas and electricity) Costs
and Percentages by Housing Types (Based ,
on power consumption predictions) . . . 14

5.--Review of Research Related to Residential
Energy Consumption . . . . . . . . 27

6.--Research Methods Employed and the Sample
Size, by Researchers . . . . . . . . 40

7.--Comparison of Closed and Open Systems
Characteristics . . . . . . . . . 71

8.--Outline of Study Input/Output Variables

and Their Measurement . . . . . . . 96
9.-—Family Type . . . . . . . . . . . 115
10.--Educational Attainment . . . . . . . 116

ll.--Occupationa1 Categories by Sex . . . . 117

12.--Income Characteristics . . . . . . . 118
13.--Age Characteristics by Sex . . . . . . 119
l4.--Housing Structural Types . . . . . . 119
.15.--Housing Tenure . . . . . . . . . . 120

Table Page
16.--Operational Variables . . . . . . . . 125

17.--Objective and Subjective Measures Within
the !Study 0 O I O O - O O O O O O O 1 2 6

18.--Standardized Regression Coefficients,
F-ratios, Probability of Sampling Error
and Multiple Correlations of Seven Inde-
pendent Variables on Belief in the Reality
of the Energy Problem . . . . . . . . 132

19.--Standardized Regression Coefficients,
F—ratios, Probability of Sampling Error
and Multiple Correlations of Seventeen
Independent Variables on the Amount of
Direct Total Energy Consumed in Single
Family Detached Dwelling Units . . . . . 139

20.--Standardized Regression Coefficients,
F-ratios, Probability of Sampling Error
and Multiple Correlations of Two Inde-
pendent Variables on the Belief in the
Reality of the Energerroblem . . . . . 152

21.--Standardized Regression Coefficients,
F-ratios, Probability of Sampling Error
and Multiple Correlations of Two Inde-
pendent Variables on Energy Consumption
in Single Family Detached Dwelling
Units . . . . . . . . . . . . . 153

22.--Fami1y by Type, Total Lansing SMSA Families,
Pilot Study Sample Families . . . . . . 188

23.--Educationa1 Attainment, Total Families
Lansing SMSA, Pilot Study Sample
Families . . . . . . . . . . . . 189

24.—-A Comparison of Occupational Character-
istics by Sex, Total Lansing SMSA and
Sample Families . . . . . . . . . . 190

25.-—Income Characteristics, Total Families
Lansing SMSA, Pilot Study Sample
Families 0 O O O C O O O I O O O 191

26.--Marita1 Status by Sex and Age, Total
Lansing SMSA, Pilot Study Sample . . . . 192

xi

Table Page
27.--Housing Structural Types, Total Lansing
SMSA, Pilot Study Sample . . . . . . . 193

28.--Housing Tenure, Total Lansing SMSA,
Pilot Study Sample . . . . . . . . . 194

29.--Study Means and Standard Deviations ‘. . . 207

30.--Raw Correlation Matrix V . . . . . . . 208

xii

LIST OF FIGURES

Figure
l.--Environment and Organism Interrelation .

2.--Schema of Closed Cybernetic System
Operations . . . . . . . . . .

3.--Continuum of Systems, Closed to Open .
4.--Schema of an Open Cybernetic System . .
5.--The Human Ecosystems Model . . . . .
6.--Inter~fami1y Social Behavior . . . .

7.--Social Relationship Between Society,
Family and Child and/or Individual . .

8.--Basic Input/Output Model . . . . .

9.--Generalized Family Ecosystem, Energy and
Information Input/Output Model . . .

Page
0 54
. 64
. 66
. 67
. 82
. 87
O 88
. 9O
. 92

10.--First—Order Hypothetical Input/Output Model.

Schema of Study Input/Ouput Variables and

Their Hypothetical Relationships: Determinants

of Energy Consumption in Single Family
Detached Dwellings . . . . . . .

. 95

ll.-—Second-Order Hypothetical Input/Output Model.
The Path—Analytic Model of the Hypothesized

Relationships to be Tested: Determinants
of Energy Consumption in Single Family
Detached Dwellings . . . . . . .

. 98

12.--Second-Order Specified Outcome Input/Output
Model of Energy Consumption in Single Family

Detached Dwellings . . . . . . .

xiii

. 148

LIST OF APPENDICES

Page
Appendix A.--Glossary of Terms . . . . . . . 176

Appendix B.--Major Variable Groups to be
Assessed in the Pilot Study . . . 184

Appendix C.--Tables of Total Lansing SMSA
Families and Pilot Study Sample
Families . . . . . . . . . . 187

Appendix D.--Operationa1 Variables and
Parts of Questionnaires . . . . . 195

Appendix E.—-Tab1es of Means and Standard

Deviations, Matrix of Raw
Correlations . . . . . . . . 206

xiv

CHAPTER I

INTRODUCTION

Energy Dependency

 

Humans are energy dependent. Two decades ago
Cottrell hypothesized that, ". . . the energy available
to man limits what he can do and influences what he will
do" (1955, p. 2). Thus, it would appear that human
potential, as well as the level of development and com-
plexity reached by human culture is highly related to
the amount, cost and forms of energy available. Odum
suggests, for example that:

. Energy is measured by calories, btu's,
kilowatt hours, and other intraconvertible
units, but energy has a scale which is not
indicated by these measures. The ability to
do work for man depends on the energy quality
and quantity, and this is measurable by the
amount of energy of a lower grade required
to develop the higher grade. The scale of
energy goes from dilute sunlight up to plant
matter to coal, from coal to oil to electri-
city and up to the high quality efforts of
computers and human information processing.
(Man/Environment Systems, 1974, p. 231).

This statement illustrates quite clearly the
relatively complex set of energy forms upon which

humans have become dependent.

Over human history on earth, the linkages between
peOple and energy can be traced from primitive low-energy
cultures to high-energy cultures of great diversity and
,complexity.1 Historically, the basic dependency on energy
has grown and changed through progressive stages. As
Cottrell indicates, both the level and form of energy
consumed today has taken society out of the realm of a
"low-energy" human-labor intensive state and placed
society in a "high-energy", techno-mechanical state.

This assertion is particularly true for most developed
nations of the world, especially the United States,2
although the develOping nations of the world also have
aspirations toward greater use of converted energy forms.

How modern day humans view energy resources has
been largely based on the primary assumption that an in-
finite supply existed. Cheap and apparently plentiful
supplies of energy have tended to reinforce a value posi-

tion that energy could be considered for all intents and

 

1It is not the intent of this essay to cover in
detail the historical developments of energy use by humans
over time, except to suggest that cultural development to-
wards complexity is paralleled by increased use of con-
verted energy forms. See: Cottrell, Energy and Society,
1955 and Starr, Energy and Power, Scientific American,
V01. 225, No. 3, September 1971, pp. 37-49 for a compre-
hensive coverage of the historical development.

2The U.S., with six percent of the world's pop-
ulation, uses thirty-five percent of the world's energy
(Cook, 1971, pp. 135-144).

purposes a free good upon which economic growth and
social evolution could be demanded as a human right.

The apparent energy shortage (referred to as the
"energy crisis," winter of 1973-1974), however, tended
to turn the viewPoint to a more conservative one based
on an assumption of the finiteness of certain energy re-
sources (particularly petroleum based fossil fuels) and
their increased value as a scarce economic good. The
outcome of this new awareness is the need for humans to
re-evaluate their relationships to and dependency on
energy. This need provides the primary focus for this
study.

Although the energy crisis was eventually rele-
gated to the status of a problem, albeit a serious inter-
national one; a general mood of "normalcy" was created,
especially with the end of the Arab oil embargo in March
of 1974. The energy problem, however, still remains a
serious unsolved environmental problem with both global
and national economic, political, social, technical and
ecological implications.

At issue is the question of the serious imbalance
apparently occuring between the growing requirements of
society and the capability of the natural environment to
deliver what is required (B. Morrison, 1974). Conserva-
tionists have for decades warned of the disasters impend-

ing if human society continued to ignore natural ecological

balances. 'More recently ecologists and environmentalists
have decried the sad misuse and abuse of the natural en-
vironment and its resources as demands to satisfy human
ends accelerate (D. Morrison, 1972).

Thus the issues first raised by the environmental
movement (early 1970's) and subsequently reinforced by
the "energy crisis" have served to stimulate research to
uncover the basic roots of the disequilibrium occurring.

Questions arise as to why the energy problem
occurred. What circumstances culminated in the situation
defined as an energy crisis? How does the public view
the energy problem; i.e., do they view it as real or
contrived; as a long-term or short-term problem? Does
belief in the reality of the energy problem affect energy
consumption? Finally, is there an emergent "new" energy
conservation ethic?

These questions are of primary concern to a society
whose dependencies on energy make it particularly vulner-
able to a multiplicity of complex energy-related problems
if answers are not sought and found. Of course, this
research endeavor will not search for empirical insights
into all these questions. Some of the questions will,
however, be discussed heuristically, others will become
the focus of the empirical work undertaken.

In general terms then, the present study considers

the energy problem in relation to:

l) The more distal global and national environ-
ment. This focus will be narrative in nature, lending
background insights into the roots of the energy problem.

2) The more immediate family environment. This

will be the empirical focus which encompasses the Specific

 

concerns that form the research problem and the hypothe-

ses of this study.

The Context of the Problem

The Energy Problem: The
Distal Global and National
Env1ronment

In broad perspective the crux of the energy pro-
blem at the global level is the growing dependency on
and competition for high energy resources. Many observers
of the energy problem have articulated in more specific
terms the conditions surrounding the problem. These
observations can be synthesized to a few essentials:

1) Human populations are growing exponentially at

an increasing rate (Bogue, 1969). On a world-wide basis

 

the annual rate of natural increase in population as of
1973 was 2.0 percent, for the United States that increase
‘was 0.6 percent for the same period (Freedman and Berelson,
.1974).3 This population growth rate corresponds to a

'Rmoubling time of 33 years" (Meadows, gt 31., 1972).

 

3"Thus even if the country's fertility persists at
a replacement level, the U.S. will not reach zero growth
for 50 or 60 years, at which time its population will be

2) Per capita energy consumption is growing ex-

 

ponentially for non-renewable fuel sources (Perry, 1972).
Globally, the annual per capita increase in energy con-
sumption is six percent, in the U.S. use of energy has
grown to more than four percent per capita per year

(Ford Foundation Report, 1974a, p. 1).

3) Expectations for more and better goods and

 

services are limitless (D. Morrison, 1974). "Mankind

 

collectively is in the midst of a 'revolution of rising
expectations,‘ involving a universal commitment to the
concept of economic growth as 'an irreversible and
irrepressible need'" (Jaguaribe, 1966).

4) Low-cost energy resources are limited (Perry,

 

1972). ". . .the earth's deposits of fossil fuels (coal,
petroleum, natural gas) are finite in amount and non-
renewable during time periods of less than millions of

years. . (Hubbert. 1969, p. 158).4

 

40 percent larger." (Freedman, R. and Berelson, B., 1974.
The Human Population, in Scientific American, Vol. 231,
No. 3, p. 32).

4The United States produces thirteen percent of
the world's coal, yet consumes forty-four percent. For
petroleum, U.S. production is twenty-three percent of the
world total but consumption is thirty-three percent. And
for natural gas the U.S. produces fifty-eight percent of
the world total, but consumes sixty-three percent. The
difference between production and consumption (between
five percent and thirty-one percent depending on the fuel
source) is a strong indicator of U.S. dependency on
"others" for the fuel supplied to support the present
life style (Meadows, 33 al., 1972, pp. 56-59).

 

 

 

These four complex interacting factors, three
which represent growth dimensions, the fourth a constraint
to the continuation of growth, are considered the major
components of the situation that culminated in the so-
called "energy crisis/'although, the Arab-Israeli War
(Fall of 1973) and the ensuing Arab oil embargo triggered
the event and elevated its intensity.

The Energy Problem: The Imme-
diate Family Environment

 

The energy problem, although a problem of global
and national preportion, has also had its affect on indi-
viduals and families. To be more specific a large pro-
portion of American families have been the benefactors
of the exponential growth in per capita energy consump-
tion. As a nation we consume 35 percent of the world's
energyzhuspite of the fact that we are 6 percent of the
world's population (Cook, 1971, p. 135).

Montgomery suggests that, "each American today
has the equivalent of 300 persons as 'energy servants'"
(1973, p. 17). This calculation is based on work done
by Rocks and Runyon in assessing the watts per capita
expended in industrial production in comparison to the
jbiological power of a person (1972, p. 8).

To become even more specific the annual growth of
(energy consumption in the United States is 4 percent per

year, for residential energy consumption the annual

growth rate is 4.8 percent (Ford Foundation Report, 1974a,
pp. 3-4).

This growth rate indicates that the level of
living enjoyed by many American families has been
highly dependent on a cheap and plentiful supply of
energy. Therefore, the shortages and increased costs
of energy experienced during the energy crisis period
have become a distinct threat to the very quality of
life American families not only expect but also
demand.

The increase in residential energy consumption
can be accounted for by several complex interacting fac-
tors. Those most discussed in the literature are given
below:

1) A growth in U.S. population. Although the
annual rate of natural pOpulation increase (0.6 percent)
is less than for any other regions or nations of the
world, (Freedman and Berelson, p. 39), during the 1960's

the U.S. population increased 11 percent (Ford Foundation

Report, 1974a: P- 2)-

 

5Residential energy consumption is used here as a
general measure of family energy consumption. This is
necessary as no standard measure is presently available
for family energy consumption. Residential energy use is
a measure for all dwelling unit types (single-family to
Inultiple dwelling) and would include single individual
jhouseholds (18.4 percent of total U.S. population) as
‘well as family households (81.6 percent of total U.S. pop-
'u1ation). Source: Dept. of Commerce, Bureau of Census,
(Surrent Population Reports, Series P-20, No. 200.

94'

2) A tendency towards smaller households. During

 

the 1960's household formation increased by 17 percent,
indicating, in spite of the 11 percent population in-
crease, a switch by the elderly and young adults to live
in their own places (Reilly, 1973).

3) An increase in median family income. There

 

has been a steady increase in median incomes for families.

Table 1 indicates this for selected years.

TABLE 1.--Comparison of Median Family Incomes, Selected
' Years 1947 to 1973. (In current dollars).

 

Median Family Income

 

Year In Current Dollars
1947 $ 3,031
1950 3,319
1960 5,620
1965 7,974
1968 - 8,634
1970 9,867
1973 10,236

 

Sources: Department of Commerce, Bureau of the Census,
Current POpulation Reports, Series P-60, No.
66, U.S. Bureau of the Census, Current Popula-
tion Reports, Series P-60, No. 80.

 

 

The percentage per capita increase in disposable
income between 1950-1970 has allowed the purchase of '
greater numbers of energy consuming items, resulting in
arrincrease of residential energy use by 50 percent dur-

ing the 1960's (Reilly, 1973).

10

4) Cheapgand plentiful energy_sources. Until 1972,
when the shift in both energy supplies and costs began to
occur, U.S. families were benefiting from an incentive
pricing structure for most energy sources that encour-
aged.energy use. The plan was basically "the more energy
used the less per unit the cost." This was true for fuel
oil, natural gas and more recently for electricity
(Tansil, 1973, p. 4).

This program, largely coming into question since
the energy crisis (Winter, 1973—1974), was, however,

a major factor in energy consumption practices during
the 1950's and 60's which resulted in the 50 percent in-
crease in residential energy consumption in the 1960's

mentioned before.

At the national level these four factors have con-
tributed greatly to both increased energy consumption and
to the energy problem. Obviously these are not the only
factors. Tran5portation, industrial and commercial sec-
tors of the economy also account for large proportions
of energy consumption and growth in annual rate of energy
use in the United States. Table 2 indicates the per-
cent of national total and annual growth rate accounted
for by each of these sectors.

It should be noted that for each sector, including
the residential, the rate of energy consumption has grown,

«emphasizing the broad internal national factors giving rise

11

TABLE 2.-—Tota1 Fuel Energy Consumption and Annual Rate
of Growth in the United States by End Use.

 

 

Percent of Annual
End Use National Total Rate of Growth (%)
Residential 19.2 4.8
Commercial 14.4 5.4
Industrial 41.2 3.9
Transportation 25.5 4.1
National Total 100.0 4.3

 

 

Source: Stanford Research Institute, Patterns of Energy
Consumption in the United States, prepared for
the Office of Science and Technology, Executive
Office of the President, 1972 (Modified for
inclusion here).

 

to the energy problem. However, as this study focuses
most specifically on the family and residential energy
consumption, Table 3 is an indication of direct residen—
tial energy consumption, both as a percent of total
national consumption and as a percent of total residen-
tial consumption, each given by end use.

Energy consumed directly by the residential sector
is very nearly one-fifth of the national energy budget.
Thus, it would appear important to study energy con-
sumption in relation to the family and its dwelling place
in order to shed light on the determinants of residential

energy consumption.

12

TABLE 3.--Tota1 Residential Energy Consumption in the
United States by End Use.

 

 

Residential Energy* Percent of Total
End Use National Residential

1968 1968
Space heating 11.0 57.0
Water heating 2.9 15.0
Cooking 1.1 6.0
Clothes drying 0.3 2.0
Refrigeration 1.1 6.0
Air conditioning 0.7 4.0
Other _2;1 10.0
Totals 19.2 100.0

 

Sources: 1) Stanford Research Institute, Patterns of
Energy Consumption in the United States, pre-
pared for the Office of Science and Technology,
Executive Office of the President, 1972. 2)
Agricultural Engineering Department, Michigan
State University, Energy in Michigan Agriculture,
March 1974, p. 7.

*This includes electrical energy as well.

 

 

.The Study Problem, The Basic
Objectives and the Assumptions

 

One of the difficulties in seeking a clear under-
standing of and,therefore, resolutions to the energy
problem is the complexity of the problem itself. Strongly
suggested in this recognition is the need for an inte-
grated wholistic approach or conceptual framework which
allows both a broad overview and particularistic insights
into the pertinent factors contributing to the consump-

tion of scarce energy resources. This would, of course,

13

be the case of all sectors of the economy; however, this
study is most concerned with residential energy consump-
tion, particularly in single family detached dwellings
and for these reasons:

1) Single family detached dwellings are the most
prevalent form of housing in this nation for families
at the present time. The 1970 census indicates that of
the 67 million, year-around housing units available in
standard metropolitan statistical areas, 69.4 percent
were single family dwellings, 62.9 percent of which were
owner-occupied (U.S. Bureau of the Census, 1970, pp.
846-847).

2) Single family dwellings are also considered
the most energy consuming type of dwelling unit. A come
parison of single family dwelling with multi-dwellings
indicates that the total cost of providing energy for
housing (natural gas and electricity) can be reduced as
much as 50 percent depending on dwelling type. Table 4
provides the evidence using single family dwellings as

the bench mark (100 percent) of the energy cost.

The problem of this research thus becomes an
attempt to identify the major determinants of mechanical
energy directly consumed in single family detached dwell-

ing units using an integrated, multi-dimensional systems

14

framework (hereafter termed human ecosystems conceptual

framework or model).

TABLE 4.--Tota1 Energy (gas and electricity) Costs and
Percentages by Housing Types (Based on power
consumption predictions).

 

 

Housing Type Cost ($) Percent (%)
Single-family conventional 484 100 (100.0)
Single-family cluster 483 100 (99.8)
' Townhouse clustered 340 70 (70.2)
Walk-up apartment . 278 57 (57.4)
High—rise apartment 248 50 (51.2)

 

Source: The Costs of Sprawl, Table 26, April 1974,
p. 60 (Modified for inclusion here).

 

 

The general objective of this study therefore is:

 

To test the viability of a. hypothetical systems input/
output model of energy consumed directly in single family
detached dwellings, deduced from a human ecosystems
conceptual model. I

The specific objectives of the study thus become:

1) To determine the total amount of direct
energy consumed in single family detached
dwellings (measured in British Thermal
Units--BTU'S).

2) To determine the relative importance of
a selected set of socio-physical factors
on the total amount of direct energy con-
sumed in single family detached dwellings.

3) To determine the relationships between the
family's belief in the reality of the energy
problem and the energy consumed in the single
family detached dwelling.

15

Within these objectives then, certain basic
assumptions have been accepted as reasonable. These are:

Assumption 1.—-Survey research methods are appro-

 

priate to gain both subjective and objective measures
from families and utility companies.

Assumption 2.--Determinants of residential energy

 

consumption can be garnered from the combination of the
subjective measures (belief and perceptual data from fam-
ilies), and objective measures (energy consumption data
from utility companies and tax record data).

Assumption 3.--It is possible to convert multiple

 

measures of energy depending on type (fuel oil, natural
gas and electricity) to a standard measure, in this case
the British Thermal Units (BTU's) without loss in measure-
ment reliability.

Assumption 4.--Through the deductive method it is

 

possible to narrow from a broad human ecosystems frame-
work, the systems components which become the tested

hypothesized relationships.

Operational Definitions

 

Energy is a measure of the ability or power to do
work. In this study the only energy measured and used
empirically (as the major dependent variable) is the
mechanical energy produced through the consumption of
refined or transformed fossil fuels. This study concen-

trates on electricity, natural gas and fuel oil. Human

16

physical energy is not measured or used in this research;
therefore any reference to energy (mechanical, residential,
direct, and such) can be assumed to mean refined or trans-
formed fossil fuels energy.

Direct residential energy.--is the energy measured

 

at the place of residence, i.e., the actual meter readings
in kilowatt hours of electricity, and cubic feet of natur-
al gas consumed, along with the gallons of fuel oil de-
livered to the dwelling unit. This mix depends on the
types of energy used within a particular residence. This
study does not measure or use energy consumed in the min-
ing, refining, production, transportation or transmission
of the energy source prior to their use in the place of
residence, i.e., no indirect energy consumed is measured
or used in this study.

Total direct residential energy consumption.--is

 

the summed amount of energy consumed, measured in British
Thermal Units (hereafter BTU's)6 in the place of residence
depending on household mix. Each source of energy for

each residence in this study was identified (a mixture of
electricity and natural gas or electricity and fuel oil)
using data supplied by utility and oil companies. These
data were received from the companies in the standard units

of energy measurement, i.e., cubic feet of natural gas,

 

5A British Thermal Unit (BTU) is the amount of
energy needed to increase the temperature of one pound
of water one farenheit degree.

17

kilowatt hours of electricity, gallons of fuel oil. Each
was then summed for a twelve month period (June 1973

to May 1974) and then converted to BTU's. Once the con-
version to BTU's for each energy source was accomplished
they were simply added toqether, depending on household
mix, to gain the EQEEl amount of energy consumed per
residential unit. The measurements conversion included
in this study are as follows:

1 cubic foot of natural gas = 1,031 BTU's
1 kilowatt hour of electricity = 3,413 BTU's
1 gallon of fuel oil = 130,000 BTU's

Single family detached residential dwelling or

 

onio.--is a housing unit which is physically separated
from other dwelling units, suitable as a living space
for ono family. This type of dwelling unit usually has
space around all sides (yard space) and has no common
walls, facilities or utilities with other dwelling units.
It is a physical, self-contained, basically self suffi-
cient entity which may be owned or rented and may also
be located in urban or rural areas.

The family.--is used in this study as the human

 

unit of analysis and is defined as a household with two

or more related persons, one over 18 years of age. There-
fore, husband-wife; husband-wife—child(ren); single
parent-child(ren) and bi-sex committed groupings were
included. Single person households; two or more males; two

or more female households were excluded from the survey.

18

For this study husband and wife scores on certain

items where aggregated within the family as the human

unit of analysis criteria. This was done only on the

two items in the study where both husbands and wives

gave responses: (1) the belief in the reality of the

energy problem item where recoding was done so that:

l)

2)

3)

if husband and wife agreed "yes" in the
reality of the energy problem, their
combined score was 4.

if the husband and wife disagreed about
the reality of the energy proolem, their
score was 3.

if the husband and wife agreed "no" in
the reality of the energy problem, their
score was 2 (see 3.23.1, Appendix D,
pages 198 and 199).

and (2) perceived problem in the availability of energy

by fuel source (electricity, natural gas, and fuel oil)

where recoding was done so that:

l)

2)

3)

if both husband and wife agreed there was
a problem in the availability of the fuel
source, they received a score of 2.

if both husband and wife disagreed about a
problem of the fuel source, tne1r score
was 1.

if both the husband and wife agreed that
tnere was no problem about the availa-
bility of the fuel source, their score
was 0 (see 3.23.2, Appendix D, p. 200
for details).

Belief in the reality of the energy problem.--

is the measure of awareness of the energy problem as it

existed during the winter of 1973-74. The measure of

l9

"belief" (for convenience) is a dependent variable in
the first multiple regression run in order to assess
. the factors that contribute to its make up. It becomes

an independent variable in the second multiple regres-

 

sion run as a factor hypothesized to affect energy con-
sumption in single family detached dwellings. Husband
and wife scores are aggregated within the family as the
unit of analysis criterion.

What follows then is a development of the pro-
blem through a systems perSpective, toward an analytical
model that will be specific to the relationships to be

hypothesized, tested, analyzed and discussed.

CHAPTER II

REVIEW OF ENERGY LITERATURE

Introduction

 

This chapter is basically a review of research
literature related to energy concerns, in particular
residential energy. The intent is to place this re-
search endeavor in perspective vis-a-vis other related
empirical works.

Often studies done gain insights from and are
therefore influenced by other similiar works. This
is not the case here. The major impetus for this study

is systems theory (to be developed in Chapter III),

 

which not only lends structure to the conceptual frame-
work for this problem, but also gives direction to the
analytic mode used.

The body of research to be reported here was
largely conducted within the same time frame as the
present study, thus making it unavailable as an influ-
ence in the development of conceptual structure, hypo-

theses generated or the research design of this study.

20

21

The Related Literature
Research centered on the technological develop-
ment of energy (extraction and conversion methods) is
abundant compared with studies of energy efficiency,
consumption and conservation. A review of energy liter-

ature summarized in Energy: A Bibliogrnpny of Social

 

Science and Related Literature (D. Morrison, 1975b) re-
reveals that the major emphasis in both the empirical and
non-empirical work in the field can be categorized into
the following areas:

1) Development of energy supplies.

2) Energy demand studies.

3) Energy policy at the state, national
and international levels.

4) The economics of energy.

5) The nature of energy industries and
their regulations.

6) Impact of energy resource development
on geographic areas.

7) Impact of energy on the environment.

8) Energy conservation.

Out of the 2,142 item bibliography only 35 items dealt
directly or indirectly with energy in the built environ-
ment (commercial, industrial, transportation and
residential combined), and only 15 of these items were
specific to the residential sector, 10 of these items

were research reports. This would suggest that the area

22

of residential energy is wide open as a field of inquiry.
It also highlights the fact that studies done are few and
very recent.

An historical overview of energy related litera-
ture would indicate four main stages of development:

1) The technological development stage
(empirical in nature), the Industrial
Revolution, circa 1800's to the present.

2) The energy and society stage (basically
non-empirical in nature), early 1950's
_to the present.

3) The energy and environment stage (both
empirical and non-empirical), late 1960's
(Earth Day to the present).

4) The energy crisis stage (empirical),
starting immediately prior to the winter
of 1973-74.

Until the late 1960's, early 1970's, very little
research on energy was done outside the realm of tech-
nological efforts. However, as early as the 1950's
various scholars were beginning to address themselves
to energy and society issues on a speculative basis.
Much of this work was related to energy and social and
economic evolution (Sinnott, 1949; White, 1950; Egerton,
1951; Tirospolsky, 1952; Ayres and Scarlott, 1952;
Cottrell, 1955; Mason, 1955; Thomas, 1956; Tanning,
1958; Jarret, 1958; Thirring, 1958; and Knowles, 1959).

The ecology-environmental movement marked by

Earth Day, April 1970, accelerated the need for more

23

information. Concerns about the impact of energy extrac-
tion methods and pollution caused by energy generation
were foremost. Creeping increased costs of energy
resources and the growing dependency on imported sources
by the United States created a need for a statistical
data base. Thus, most of the empirical work during

the period prior to the "energy crisis," was done to
close the statistical knowledge gap surrounding natural
energy resource stocks, and to define the energy con-
sumption patterns of various sectors of the economy.

This effort could be classified as information gathering,
national in scope and basically descriptive (Office of
Science and Technology, Patterns of Energy Consumption

in the United States, January 1972; Staff Study, Potential
for Energy Conservation, Oct. 1972; RANN Report, Energy,
Environment and Productivioy, November 1973).

The first effects of the real energy shortages
were felt during a period just prior to the energy crisis
(Winter 1973-74) although electrical brown-outs and
black-outs had been experienced in several parts of the
nation earlier; i.e., "Big Alice" the black-out exper-
ienced in 1969 by some sections of New York City is
considered the most serious. The period of energy
'uncertainty (during the winter of 1972-73 and the summer

(of 1973) encouraged a number of research starts, with

24

particular emphasis on alternative energy futures given
various economic and technological options (Ford
Foundation Energy Policy Project, initiated 1973).
Energy conservation also became important during this
period, along with new priorities established for energy
development and production research.

The energy crisis of the winter of 1973-74,
exacerbated by the Arab Oil Embargo, elevated to a new
level the urgency for energy research. The Federal
Energy Office (EEO), created in January of 1974 by the
Nixon Administration, initiated Project Independence,

a study not unlike that of the Ford Foundation's, to
investigate what it would take to bring the nation to
energy independence by 1980 (Project Independence Report,
November 1974).

The Federal Energy Office (FEO) became the
Federal Energy Administration (ERA) in July of 1974
as a formal recognition of the long term, serious nature
of the energy problem. In January 1975, the Energy
Research and Development Agency (ERDA) was created
to over-see federally funded energy research.

Michigan is 95 percent dependent on energy
imports from outside the state (Annual Energy Report
of the Governor, 1975). Therefore, Michigan was one of

the first states in the nation to establish a.State

25

Energy Office (March 1974)._ Michigan also created a
non-profit corporation to coordinate state energy re-
search efforts (Michigan Energy Resources Research
Association -- MERRA, December, 1974).

This short—term historical overview simply points
up the increased growth in interest and concern surround-
ing energy, generally. The concerns have changed over
time from energy as the basis for enhanced economic
growth and social development, to concerns for reducing
energy consumption as energy short-falls and increasing
costs threaten the economic and social fabric of this

nation.

Literature Related to Residential
Energy: Directly or Indirectly

 

 

A search of the literature related to residential
energy use was conducted prior to the field survey (May—
June 1974) from which this study evolved. Very little
was found which lent insight into or support for
this research problem. This is not surprising, taking
into consideration the short-term historical review just
discussed. What needs to be understood is that onio
research was designed and conducted simultaneously with
most of the research important to this study. Therefore,
rather than indicating an a priori influence on this
research, most of what will be discussed is retrospective

and hence comparative in nature. It must be kept in mind

26

that some of the research.concerned with residential
energy consumption was generated in the year prior to the
energy crisis and some during. Most, of course, were
investigations within the general time frame of what

was termed the period of "energy uncertainty,"

a period between the winter of 1972-73 and the energy
crisis, the winter of 1973-74. The time lag between
these research efforts and the research reports in
several cases made them unavailable for consideration
before the fall of 1974, when this research was well
beyond the theoretical or methodological development
stages. Therefore, prior research did not substantially
contribute to the development of this research problem.
The only exception to this is in the area of analysis;
this investigation has been able to gain valuable in-
sights from that dimension.

In order to cover effectively the literature
related to residential energy, a summary of each study
will be given in tabular form. Each will appear, by
author(s), date, title, research considerations (method,
theoretical concerns, hypotheses, variables) along with
modes of analysis and findings. This will allow a
broad, however, somewhat detailed overview of the pre-‘
sent state of the art, which will make eventual analytic
comparison to the present study possible. The following

then is the review:

27

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smuuco C9. ucztlic.:uir Liars

can muco>o tuiozcc_Iccna:eco
co >ocs:c;t_ 1;. ocieusuaa .5

aucLHLuJo

cu x.«v_E:; a:a seaueuueeou
cL :o..1_un> ecu oc_Etysoo .c

cowusuoeo acted—cam

Lo couscotw>co Loctyucfi
C:LELOC;Q .n

coicaEsmcoO

Races: to. amateur Leandra
eo cocauqcicuir ecu ECLELQL>Q .c
.Ezbnma coau:b_bum_v
L1O_:1;oes 1;. Lo soczczce
cc: >5coeoucey one ecespooy:
moped wci~03c can
aziueoz .o mucvcooeoc uo_=E
ozb x-tcczeqcyaxo 1:LELUS¢Q .N

egg :0 ubicue 5:.

.m

 

 

 

 

 

 

 

 

 

0“ cap co¢.=_ec> paces—exec: .m coasaeamcce sauce: dc.ucac~myu
I .aECscw >:En.m I .
:~«w Adieww . Low 1.6a one“ ecefituuoa .~
only E~L6em I
no assoc“ >~_sse an on: new . .II IIII IIII-I II--III
c« as be yucca csu cm a o . «razed ofiucim LC:__m mcitcsic.z co macaw
i H. . u «mm L z e no mmbsocv mvs~x :_ vcoebd: I
A~Ouuc0u em: we;t1 e5u_n xuuase on!
LasseCuv aucoczeiwc »;r: x: mmaam Comes Co couuascuwec I assoc“ cu cow.aiho> ob coma
vac—sinus on as pvqnilozmw Aces: vcsnuoqtoucuc seduced; I IuoeoLe .czz cca cowucuuc>
couuaLLe> ~oowuboyfim .n Azsoohver o.m.~c aefim I Hagumxre uiuuowmx 0L
Ambem: an uczcxa momscrczou co maexu N I o~bosan_tucc EL COLLuLua> omexaad bun no Esau
I m .. II:.-II-II- II . . . . .
snow as psi—ohucmo uocv “meane_be> .cecctmmms_ are .0 cc_utocoEe c.23 N Lobecoa cu soe>ov < n
neoconsccdc ~acorwom zo “Educ: Lemueem >-ouimxze use:
vmcwnaexu new cw co‘us«»a> .n . mzoea musooo :oaude:mcoo :wzuw) wondeII8oumxm
mafia: onzocczou nuaqawm I coqca~w_wus Amusce : co niec>. one so . co m sees a m JLOEO .
cousa63n=09 vmce~2mci 9.2) -< I xwtwcz :1 reason . . L «c.. L I L Law w . u c . .x N
IIIII I II. I .I U n0 .
auuuuo~e on: mew cauluan x-eoiuuou~1 Icaou ~o>o_Iua_em u__«ommw “:CLLEOJO guesswom cowuacw u see 3 A
couun~eCCOO acccuuwcw_m 02 .n owcowuiocoU Lia 9.9) -< I can ecciiIN "coauaucossuctmw
.«t: :cco: mceon o. nascuuauu13. bibsoo~a can adequcuci unaccecm coeauab o «season—dds:
03v seawatw coabeeamcoo zoo .N . . .,v use) mowaxose acceifigem ~i< I EpcoCzeeit oz h : xwuecm ECLEuoLo: muoucmm “3:3 z~o>a~ aidem mn_
mJoncm mac—w . m:_uae£ no. h).. w. . . I WI. ~00~LIM swatcuum wcm
oubsov cu 03v mwc_>em :60 .u xuuuqt COLLQLQLLOC new iehauec can: rugs: ~_< I .oeimms_ dehmcoo .coiuroao :uuaowex
II .IIII II-III. IIII,.. Amezsoccaok ~OQazv
"musics“; cowmmouwez Loos“; 9~e_u~ax "mo—na.»o> cu-ohccou possum ocoz vauaum ocoz cm_moo sausomoz ”wucoeahzexm
. . . . nzcie<mwaimzou . .
mzo_h<u~4e:~ oz< «oz—ozmm mcfi«r mmmri<z< no rmcii mm4m< x<> .w I , :9 4.7m
i we mze0a»: zox<umex xc\ez< seciemx0m=e oozemx x 1 x

A.>omuafi 392 .muv>«¢ CLIP

uxciczfifiou “saucevdmou 3m: sII zvsum c: coucsooqv

.>u_mbo>~c: ccbuocice .meivssm Haucascoui>cx use Caucuu .c .02 LuceuzIImNoL .cm wean ob

-o~ .~ x~sfi .uuomum mhmwwdui LEEWIWN.K%IIHthm:o: c“ cowuc>homsourxfluocm

 

 

.MNOL .LEQEeuoo

.)o~0uom Lennon use uuxmuccum guano~__m ”mucus: vu>sa nacho ubezo_x u.»n .uoxeum confined: ”Rem crew

30

.Lauuo
ob Agaxua uOIIwcahusuuo who
Ae>auosuumuc to o>~uushun:0oV
ace—“dept ~1u00m Lac: .~
wcauuauh mu c-b3e one Jo: .~

amouuo ob ncficcca Sco>o Leechedeq
cm as aunt oiuoeeuzxm mcfiuozuew
Lou avenues oucu ELLEmeu

"mmowunuLLNEM

 

.Bo~boun
scqosoeefi “mos LOCIIEuisote
“cebuoeeu auo> eo~nobm ambacm

 

who: passage» accrrco~uaunomtcuhh
Leo mu;w«_ cuss I

awed mcoanHQQQ Ex: I

been Gabe sun. I

”caozemmmm

 

 

"no“>~£vm coquu>uoa=oo vestoeox

eucowcu>:0u:« anon
IrsuaboLe :wqm: a Lo: use >O_ouauz

.coLSdESmcou

anoco pecans. co Shoe
sandbote awnoco

co camco~ Leona coinasuoexm
"one mcicesuno adbsoth
w:«u_ue Ecwdonau a>_u=:Leu~<
cane—La>e couuecuoemcchu

we watch o>iL=cLo-<
coquzbmuumuu dose Lou nocotucate
Eo~boLe

“sunbeds“ bros Co cofludouuam
coucc>uomcco o~ozzmzoz

 

mo—no_ba> acevamon

ous~e .0 eexh

uufiucm‘v o<a

Acoquaesouov caozomso; cw texts:

oEooc— >H~E=m

mumA—ac< coqundouuou neweguozm zuwo«uuoo_e
.oc._omcm .Hia Lose

 

 

.ucoseo~o>av

.q~o~ Aumsubom 2w30ucu
anog Losem>az co 49o:
arm ache zfiiyoz
Room .xo»ed<uzv

 

 

. . u as one a o o e :0 aces genus»
umououuw uo seesaw maze ~:«~0mao mauuuoeom acooLOm on enamoexov mMWLLWI>xLucm.M v «u H 2 he so u cc ~ EH U A~Aumo“v MWWLWW
”Awfiwmmwm momumuuqum e>uunutumea u~bs_.e> chccvmvcc_ cmuwum ucoz aboazu cod: woman “02 uneaseucov ~1:o_ucz
. mzofih<¢ma~mZCU
.. <U m: z< I . <t Z . vmgm<ux<> m Fr 4 .
nioie ~5 i a wuyiozie «as memsi<z< mo muse: mu m oa>= zoe<mmmm mo\oz< i<e_emeomze mixem: =o=<mume

 

.vko_ .>t:::mfi wamuwrwm ct~< we: ”Loci? _1c:;i: ”casceuuou cuibcx ”chascwum cashew ”weeps: .x mason

 

.NSNIana .ea .emoi .ei lice< .emie .ez .emi ._o> .weeeium
:.mwmiuu Ambush as“ ou oncoemyx ouabse mo coau2~o>m: .qmm_ .iine< .wxmtsnie .m ::~<
cc: ”.0xcaum Caster "coauwuuou .u shone: ”tugboatm .7 cae.>z ”to:iz .1 ~;.;Ii7 ”scht:z .z noesfi

.ecu;1_~bsec:i cuceym iswuac~ u:m.niuu >~L2:m: oz“ 0“ umconnzx oz: LoseEL ofiozyrzc: 1:“

31

.wcoLum so: Ea useESLEEOU

«duos Ci can po>hmwbo mflsouuiv
Soc «L Coi>1zon c. AcofiudEJmcoo
zwcuco :_ vacazoV mace: I»: on
apoccoo ou Loi>nzob yucya~uci cu
cwsoce uncuuw so: meowuocsm “snot

"unequeuu~ma~

 

.coaueasmCOo xwhecm :.
mascuw ~0u~c0c cc: ucossaous Cvdce
can Queues :Lonuon oocsuoeeiu oz

"wadiocum

~.s.d 0010 O1 x_isv one» muauusv
coLueesn:0o Amuuso OLCcuago _a:uu<

 

”we—oaiu1> .cepcomoa

 

.Aaocscouv co.soaL0w:« 02 .o
.o>oos
~ CL couaflaeucms mo~boaun>
over. was $2.; cowbsauoucfi
ccmsafisncOO amuuce vymnyhoc~ .n

xuMHmexcoezou .ELascw>Lcc_ .U
sdeose

Cacao co woecosqmmCOO ms_ .m

Low>c£on Co ewes ULEOCOOL .<

“Joann
acquaELoch made cofiudshoucfi
cofiuefiswcoo sweaty vozeeuuaa .N

.x~:o CoquoEuoucfi
c0-eE=mc0u waoco panmouooa .a

 

oocm_ue> Lo mum»_sc¢ unsibsuha> scyccoeooEH

.mamuhu mwcacu

Co msumwea cows

IauycmeOO out”

uc_xeh .meson
uneaueouu cumzuon o
aocouawCun oz u z

 

" H u acoefihaxm

.meaohw
ucueusvuu coyJLOA o
sucoLeCC_v o: co H z

”_ ucuewueuxm

.Aomo~ .Nuuolzum Homo~
.v:e~>o: “mesa .3ui23Oxv
assoc cc: .:oEc“EEoo ~sLoe
wcwbvcflm:oc .Co~>trua :3
mevsuduut .o accesaccu och

 

mzo_H<U_qA:_ az< muz~02~m xofi<z

.I . .1... .. .w«.el nIII.I,w...ru_ 1 us. 4 ...~.J.u._

m~mr4<z< no muss? mmcm<_m<>

“I.u=»II-,n....r

mMmm:HOer:

u _ Ii Baffle ”1.1.1.154. ._ a A u

Acanzv muiuem
uELH swerve
_s~caefltuexm

 

wZC_H<xmo_mzou

zux<Mmum m:\cz< 4<C_Hm10uzh

QC:HN: zum<mwmm

.Asoena cuzni~bsecsv rufiesou saucepan: cm cm cowbe63mcou ~1uwuuco_m

was mumfiuu xwuoce Czi

”coauoELoec_ cowsc>uemcoc .cmaw .ocafi

.cio—wabz .< E150;—

32

.maficzces;

euncouguoeotenic incax

uo: on Econ Chom:w cu aestmoue
couua.au~e ~n.ooem co assist < .N

.muacuo ma Has: m:

Load can vuao: :oiga~:m:. org:

one memo .uuccwaade acyioicca
egos :wsohzu :oiua>.om:cu .H

nwco«uecwwmmw

.:o«ueE:mc0u mew ~su=ucc
c. uocauowuwv o~LLL_ re> .m

.580oca “Nazca anuou .0

usauuue a we oboe and o» econ can
xu‘quou amuzco mmo— om: Loon ugh .~

"mwcmmmfim

Au:>_ootzev umou xwuocm

Am.ahm c“ tapamcoec Reagent: .m
.zuuumhu...a~._ ..I
«2.2 ACHSHEZ .~

couuQESECOC imbue: aszgcc

 

"mo—beuue>.ucyn:aeum

acuaucoe

couceuLOQECEEH can wcw>iq I
maumum oesocoooroioom I
mo_uacu> I

noucqu~ae< mean: swuocu I
mESmem xchsu: I

moezh wcw_~o)a I

osooci I
auwuxuunum a>auewuumoa

can mum>~nc< cowue~ouuou

 

"mo~nc.ue> “caucumVUCL

 

mzo_k<U~AAxH oz< moz~oz~m zofi<t

. n. - «JFNIN u:‘-.NI'III. I INN IN. IAN; - 11. .14... 1 5.0.3. I.

m_m>q<z< no Waco: mm4m<_x<>

~.uukl...,Niu.s...n.1n..nn. .I.uflanu.N..u."I ..n. .1... ..Iv.....NI§..en JENNIIMHI .,n.N.\ .IIII .u..IIl,In”I. "NC

a Laudqgu

.uaudnoum Lagoom mo Absum ecu no. xuaiuom org us vouceneue home;
noon 2;» can couscoL.>cm one .>u»o:m

. u I u NJ" .1...“ I. I I?! . III. .

.LEOO
xwueco cu ovum—v“
x—e>«uewo= nu encyc—

.couueasmcoO
xwuocu on coco—ah
x~o>uuemoe we saccc~ I

uncharged»: bandaged

ummxkcm>z

V5

 

.vmofi .codunncaom upon one AMMVHELL

muceocoezux

wcfi>usm momcseeou
wc_~_~; Co >e>bsm
Ameiczefiacz mme.~azc

who: see Loom och >o>u:m _ncoiuoz

mzo~H<xmo_mzou
mum xo\az< 4<U_PmmomZF

.n ”HID: “.14 u . an.» .1 u ,h .n,. I... a

3 .. ..
:Uz<fl a 1%»: =Um<dwmx

FIN IIIH. u.u..I.a_u_

52%: .ee

 

 

NOLLOL hwuocm z.ao.~es< "amoozo ob :Emhlfl cw

 

 

 

 

 

 

 

.ceaauomuc_ use Loom .Luwx

"usalmcou.Nm.1cm ceoeuoa< ELM .«nou .Leb0uuo
.emen .uwaw:< .avocwu .amuuucoz

.Aeueme cozmu~bsecsv

.amau .umsw:< .—au£om3 .a ciao ace casifiz .z assoEo:

33

.Acusficsu
mucosk coeca>queea 9>ico_9xv

awhoco :o .covceeeu 5.2: .m
Acoqc1uzvov «Lela Ono: .<

"museums ownsuozm Lo muooc_:
couumc_auhomfiv buoe access
has vowaucs>va >-n_com .~
.::~ umwco— ca coauticute
beacon an sceIIcau “Lozz c.
Coaguoohe xnoaIImuoocu Leia; .~
"racismWflmamH
.oowsuco>cs mwmm ecu Susanna
cousc_eunumuc momeuuocm Lesa
angOLLE uuos undamam oocuow>m .N
.Amceubuaalwc39>
you Leeuxav cowauce>cmvwv
>H~uvuom “madman ouccieuto
Iago omuutoce A>~c«ns ecu—ensue
Awueco ecu eucov_>o o~uu«_ xuo> .m

"m :_ccmm

msuaua aucowgaesuuo 304

muuuwisasm u>duaenumsa
use memx~mc< :o«.e~ouuou

.xciqqne~_s>e::
smuocu Co aco_ceaoLom

”mwfibwwuc> Scepcumvo

 

.m

Cnvuuduqivnu 331—.h
menu—CDC“ 3C; .0
Qumfillccz .m
mama—Fa...— .Q
mono» .m

:33“ .m

L

EELLLCocMz

mowwucm>cumflo «a_uom

 

"mu—nauue> Lcuscumoo:_

.mcmmCOJ can
nuuscco owaLLOLE
me mammcuuefi
coficecmswuomec

.mawss:e>uumqu
Lseuoz udaesdse
o>ez Lacs mascum
umciawa shoe

case vLcCLELIcch
momaunoxm xwhocm

.maaoum
vowsucs>comiz
xdflsquom um:«uxs
auqc_sduomic
mewauuorm subocm

.Am~o~

.comwuuot .o “NNOL .comuutoz .a
unmom .csao~uh noeaa .nuwofiuxv
aemquuucw uco2:3L_>co occbwe:
o. unneeua ms AmomeECOCq umou
IIucofi>o~eEcczv ox1_ce>tsmwv
pancakes“ Eocene ccwascc>vom_o
— >-n«u0m oak ”zuouzk LEJOL

.uuoeamlw-m

.Ausgm

«wean Luwusm 1 Lo:
AOoan Aze>o3 My
xe>usm occzev~oh

 

mzo~H<UHALZ~ oz< woz_az~m mofi<x

Fl... w .d. uu4.d.finuulanl.ITuuu TNNNNUEI- NINIJ .- 4 .1 I I WAII1 - I: «INN. I I In}. I .

. NAN... RN” a. 9 h5g1. c. 3.....UI I: . AxNuNui "I N

m~m>4<z< mo mmao:

mu4m<~x<>

tantamoue been;

era :0

mmmmzhomrz

LEAN.“ I ONIN 1. F

m20~h<xma_mzou

I,I.I I u. "VIII! 1.11;” III. N .uI

:Um<flmmm mc\Dz< 4<U~Fm10mzh

oozhmt =0m<mwmm

uNH.I.I.1.u. .u....I.I. ...u...,..i .I.

.GNOL .umsm:< .aoucau .aaouucoz .mso~ooCL choom Co spasm are .0. aboLOOm on» be

"mucuuozm are we can uuozm or»

.pzumucc>cczua >-suocm or. so Nuauuccm >uhecm 9;» mo Luaaa_ buoeomILHEm
.cnoa .umsw:< .ScouLamInumeLOw «econ new Nuucazum .m .H

34

.LxuSCOO dauoon .0 shed
a ma sawdusoOcu on as about
use “customs“ we Emwnvuu::_o> .N
.ucwbsom _awcom
wcwucsohhaz Co nmocxaul to
zswceubm 9;“ copucLACOO ends as
memo: osccci co comauow xOLLOE
o-n2e Luz“ moflaee_ mfizu
II~c33L>LnCL co caisson ~suuor
we: m_csne co ~o>u~ o_EOCCcE
quuom coaacob cogs: oocquE0ds_ .L

 

"mcoaueousflflmw

.m:_u.am aowoom .m—oaog>~o:_

Cw coconuts an ob Leeann
uwmuuo swuecm vtaacu avenuess< .q

.nceiu

I:u«bmc« Lozbo can “ceEcLo>ow

Co mcoiuquouelo was Eodncte

one C. Cou~vb psauxo postcauu
mtoi>a;on cowcs>uomccu .n

.mma~o agenda An neocowneexo
zacuws as: mumguu >uuo:m .N

.mccis

Igqumci cauibofi< co ubsfieec
we seem Akumnoav mumuuu Amtucm .~

"3.13

:o_un_ouuou
mcofice_:bch mmouu

Amom1L:uouiav
wuwuxisabm m>..cwbcmmo

mochaom d—E: can COLLssLo_:_

.cousuw
Oceanuo>ow .m> Auabcs_o> I
maucnzu c_>.w 5.“; I
mouuguate :o_L1>»omcou I
aumfiuu smuccm cc ALL—sum I
m_mwuu >mtucm be. 981—: I
ELELCU
Awumcm Lo muuwucs .sCOELye I
mimiuu embacm co mmucmsoiuum I

muauuu Awhocm ob success:

 

"ao~nfuue> acopcumwm

 

vooEEeeewiez .NL
Acwcasaou .~A
950: CO eunucoucdax .o_

O

m:c=LE scaE>o_eEm

a: John “coocoemou vowim
msbccm unueucx

vx<

xwm

cofiuumoe qecouceenuoo
~u>o~ _scoq~ec:cm

oeousw zuiEsm

. . . .
—-cI~\¢-fi~0r\m

"mo—newmw> Lcmvlumocm_

.Ea~no»e choce o.
mamcaemau ~oscm>_3:.
oocesdcca aa.)

moms» coachonzwnoz .n

.Eaunoue mwuaca

on oocs~eb moon“
Iwuuu pea who_>czta
~osvw>«c:_ mucus—ecu
-w3 newscasua

uca moz~o> xuuczflaou

o
N

.Eudbohe Axuuce o.
antenna» cu cognac;
EL .xoccoO Owsococa

quuOE n.~m:o«>_pc_ .—

uca«_es— memozuoexz

Ace>Lw RaucoLeuoL ozv

.Euanoue xxubco

on meECOQEUL _1:c_>_pcw

ob codenan nuiexb poo:

Iuonzmau: x—a co xxo_oe>uv
ulOuCOC unioOm voozuob;u«az .n

.ESHEOLQ >uhocz

acuust atoq>ozob mummdeww

0L coco—3L Amov:._c.s

deacon pee mus~c> qoco_v
uxaacoO —o_ooh xuicsasou .~

.Eu_bota

xuuoco 3L omc32mat use
“Raucou deepen m._m:u_>—pc_ .~

"Lo :o_.a:~w>; u;u

no. xLO)bBoL_ ~euosom use me
pom: no: cowbo~_:oxuo Lambda ob
zewoxc__ vcn uo_>nzob xCLa—e:

.Juw>cuscw 9.:cme on

.om:0em so

meme: ‘0 x:__LE:m
e>.gcbcumobeox
.Amoi__Eoc

canuzv mowed:DEEou
ozt< Listens 522‘“ .3
xU>L=m fiocoquoommOLu

 

 

 

m2:.~<u_4ar_ 32¢ wuz~oz_m ztw<x

I...JI~I¢.In.J.In11 1.“.Ita1I.Ia..-VI."

m—mw;<z< m: Image

mu4m<—x<>

Lonee

.455... .c-...,9I._I...: fix... a some Iii: i 5::

 

u.:~«~r:~

mmwmxhoerz

. :IJ I. . .I HI . ..I NE... .,. II. . .

 

 

 

»

 

I>.3.>L:.f. war ...._ n.2, _._...c.<I c<

mzo__<1maumzcu
:Ux<umux moxaz< A<u_HumCu=h

OOIHHZ zum<umux

.omo_ .ucsfi zwsouzu -Le< EOE. cassettes wovuw
.Auwnuouscp vsuufi ucxsz v5: ccm_:ouz .o %~_tuy>«:3 5:“ we “we: Sodom e .rc:_gc_;x _awhcmrc:_ 3:1

.r:;:o>_uocceu >.i::EEcc :. Gonzati 5:. >5 tusccc::s >c3~m

 

 

H92.. 3.32 3 .113

. fl: c...::§uo.v

wk;o%.v;u c.

muzccfivo: :3,wuovecm Nq_::EEDU can ~e1¢flimcmg .vno~ .tsbezuen .Luzuhcemax Comebm .Cbupcn .~ w~1coa

35

.maudbobe ~1.c:m Condo»;

OLIIxuoacs :G_L1>..31 .9 11;:
IuEDAO» “scams: 15:1 sczcx r.:+ I

.rue;_.; ;_L_L_:E

Rb cecwsnouuc 1; o. 326::xc

we sour) Lod>1zun ~o_czce .2:

neon ombaitc> Edutan < .Lci>1;;;
“second >__vnoh ac: 0v neczuecc< I

uwcoquduL—LE_

.::..
In>uuncoO waoco ~1tycquI.»:;;.
~ctcw>czobIocgmceeoO “sateen
rapes; e>hemc0u ob sue: Locortai I
.mmuuco ;>L;x:oo 0.
fine: _scomhue Lo 2.:1zieezcuv
catacoeew any) LstLO:m
Auhuco Lo. zuuawnLEEGQEuh
‘aCOmLoL .0 :oisdeuome cc:
Lou>ezab coius>.02:92 cJo n.9co
we ILQCQSUOZCCC “O Immochdn-JJ’. I
Arno“ Leuucucmbam r_
xwuoca 9>Lancoo 0» Eco: Lccomcoi I

”mflc.mcew

.Auo_>a;en ca>tezno uocII.L:dux
~mpow>tzenv :Omca>ubrc:o
xwuuco ~atocyw ooutcezm

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Azauoca u>om ouv mete: accentui I
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36

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38

The listed studies give evidence of the scope
and breadth of the research which has been done within
the context of the "energy uncertainty" period men—
tioned earlier. Of the fourteen items reported,
studies done by Murray, oo.ol., and Newman-Wachtel, were
issued first as papers or preliminary reports, and were
later published (Murray, 2E nl., April 1974, pp. 257-262;
Newman and Wachtel, 1974, pp. 113-130), thus reducing
the number to twelve separate, discrete pieces of
research. Both the Schwartzs' and Kilkeary mentioned
the unfortunate lack of related research from which to

build research efforts (1974; 1975).

Themes of the studies.--Of the studies done,

 

several themes emerge: (1) Energy demand and expen-
ditures (Heredeen, 1973; Hittman Associates, 1973;
Bullard, 1973); (2) Household response to the energy
crisis (Murray,e_t_ 31., 1974; Newman and Wachtel, 1974;
Kilkeary, 1975); (3) Energy conservation through tech-
nological innovations (Bullard, 1973; Hittman, 1973,
Fox, oo_nl,, 1973); (4) Conserving behavior (Heberlein,
1974, 1975; Winett and Nietzel, 1975; Kilkeary, 1975).
Most of the studies were concerned in some degree with
the implication that changes in behavior and/or techno-
logical modifications could or would have on future

energy consumption.

39

Conservation of energy was the most prevalent
theme. Eight out of the twelve studies either highlighted
or gave implicit attention to it. A second theme, the
impact of the energy crisis, was given attention in four
of the works and reflected the most immediate concerns

generated by the energy crisis itself.

Research methods.--A variety of research methods

 

were employed in the studies reviewed in Table 5. Table
6 is a summary of the methods used to indicate the di-

versity.

Household characteristics.--Eight out of the

 

twelve studies used some standard demographic data to
describe the households. In two cases criteria were
stated for selection of the respondents. Kilkeary and
Warren both specified head of households or spouse,
whereas the other six studies only implied using these
criteria.

The four studies that did not use some descrip-
tive variables of the households were the three simula-
tions and the Heberlein (1974) study. Heredeen simulated
sectors of the economy indirectly related to household
consumption, whereas Bullard simulated sectors of the
economy directly consumed by households, however, neither

included households per se.

40

TABLE 6.--Research Methods Employed and the Sample Size, by
Researchers.

 

 

 

Researchers Sample Size Research Method
Simulation:
Heredeen 367 Sectors of
Natl' Economy Input/Output analysis
Bullard 82 Sectors of

Hittman Assoc.

Fox, et a1.

Heberlein, 1974

Winett & Nietzel

Murry, et a1.

Heberlein, 1975

Newman & Wachlet

Schwartz & Schwartz-

Barcott

Warren

Kilkeary

State Economy

401 Townhouses

96 Apartments

31

Z
II

N = Approx.

700
N = 114
N = 1,455
N = 200
N = 766
N = 602

Input/Output analysis

Input/Output energy analysis
("The Characteristic House")

Experimental Research:

 

Comparison of two townhouse
architectural styles

Time series experimental design:
2 experiments; 3 experimental
groups, 1 control group

1 experiment; 1 experimental
group, 1 control group

SurveyiResearch:

 

National probability survey (con-
tinous weekly cross-sections)

State wide telephone survey

Natl' probability survey plus
survey of utility companies

State wide telephone survey
(modified panel study)

Survey of 8 Detroit area
communities

Survey of two New York
area communities*
Kingsbridge area of Bronx
Jackson Height area Queens

*In the Kilkeary study 2 areas mentioned in the Table were

included as control and experimental groups.

The Kingsbridge area

had not experienced a "black-out" since 1969, whereas the Jackson
Heights area had experienced an extended black-out in August of 1973.

41

Hittman Associates simulated a typical family
to be two adults and two children as a part of the
"characteristic household." It is not clear that any
demographic data were used as a basis for this simulation
decision. The body heat contributed by the presence
of the simulated family was the only characteristic
used in the programmed analysis. Heberlein in his 1974
study used the apartment dwellers as recipients of the
four experimental conditions concerning energy consump-
tion; however, on1y the electrical data were used to
measure changes in their behavior patterns vis—E-vis
the experimental treatments.

Fox, SE 31., indicated access to much data on the
families of Twin Rivers and some description of the
family characteristics were given; however, only income
and family size were used in the analysis, which did not
prove significant in relation to energy consumption.

The homogeneity of the town-house dwellers was implied
as the reason these factors washed out in the analysis

as compared to the physical housing variables.

Residential Energy

 

Out of the twelve studies reported, five were
directly related to residential energy (Hittman, 1973;
Fox, et al., 1973; Heberlein, 1974; Newman and Wachtel,

1974; Winett and Nietzel, 1975), the other seven were

42

indirectly focused on residential energy as a part of

 

total energy use (household and transportation energy
consumption), as a function of the energy problem
generally.

Those studies directly related to residential
energy were often most concerned with establishing a
measure of energy consumption within the household as
baseline data upon which to discover energy conserva-
tion guidelines. For example, the Hittman Associates
study (the simulated "Characteristic House") and the
Fox, 31 31., study (Twin Rivers, Townhouses) were both
detailed studies of environmental climatic conditions
and physical housing characteristics affecting energy
consumption.

The Newman and Wachtel study was designed to
study energy consumption and costs as related to family
socio-economic status (family income was used to establish
four groups: poor, lower middle, upper middle and well-
off households); however, some physical housing and
family transportation characteristics as well as energy
types were included to give greater descriptive value
to the study. This study was less interested in energy
conservation per se and more interested in recommenda-
tions toward ameliorating the inequities between socio-
economic groups which present energy policies appear

to reinforce.

43

Both the Heberlein (1974) and the Winette—
Nietzel studies were experiments set up to induce changes
in energy consumption behavior, giving less attention to
the detailed analysis of physical housing characteristics,
although, Heberlein controlled housing by studying only
apartments in six complexes with very similar physical
features.

All the five studies most directly related to
residential energy acquired, through utility companies
or meter readings, the exact amount of energy consumed
for the duration of the study. Hittman Associates, Fox,
o5 o1., and Newman and Wachtel gained the cooperation
of the utilities providing natural gas and electricity
to the areas or families studied. Heberlein used only
electrical data from meters read daily at a specified
time.1 Winett and Nietzel acquired both electrical and
natural gas data from bi-weekly meter readings done at
specified hours. In both of these cases, students were
trained and used as meter readers.

Three of the studies transformed or converted

primary energy measures (gallons of gasoline, cubic

 

lAccess was gained to meters located in the
apartment complex, through permission of the management.
Apartment dwellers were unaware of this access.

44

feet of natural gas, kilowatt hours of electricity) into
some other standard measurement. Therms and/or B.T.U.'s
are the most convenient and widely understood conversion
measurement employed.2

Hittman Associates and Fox, oo'o1., used the
therm in reporting energy consumption; Newman and Wachtel
used the BTU (including in the conversion for electrical
energy, the energy expanded in production and trans-
mission or the indirect as well as direct BTU count).

The two other studies used the primary forms of measure-
ment.

Heberlein (1974) was concerned only with kilo-
watt hours of electricity, whereas each of the other four
studies included both gas and electricity. In each of
these cases the energy source measured was studied
separately, except in the Newman and Wachtel research
where both separate and combined totals in BTU's were
used. The other seven studies did not use actual energy
data as a part of the research design, with the exception

of Bullard, who used aggregated energy data for the State

of Illinois measured in BTU's.

 

2A therm = 105 BTU

BTU = British Thermal Unit

45

Reviewed Research as Related
to Present Studyj’

 

 

Not much research has been done related to resi-
dential energy previously and, further, recent works
were generated simultaneously or nearly so with the
present research; therefore, most of what has been re—
ported here has had little effect on the research design,
the conceptual framework, the selection of sample or
variables or hypotheses in the present study. However,
there were a few exceptions. The telephone questionnaire
used in the Schwartz and Schwartz-Barcott (1974) study
was made available to the interdisciplinary research team
prior to the field survey from which this study emerged.
Some of the questions were included and some were modi-
fied for the energy portion of the self—administered
questionnaire of the pilot study (to be discussed in
Chapter V).

The Fox, 33 31., study gave insights into the
kinds of physical housing characteristics useful in
studying energy consumption; however, less detail was
requested from respondents of this present study.
Fundamentally,this pilot study was designed as a broad
overview of family functions related to energy consump-
tion, not simply as a study of family energy consumption.

This will also be discussed briefly in Chapter V.

46

The analytic mode adapted for this research was,
however, influenced by Heberlein's (1975) study of energy
conservation behavior, although neither the content nor
the theoretical frame of his study luni any bearing on
this work. Heberlein's variables and hypothesized rela-
tionships lend themselves well to regression and path
analysis. The Heberlein study is a model building exer-
cise whereby factor analysis singled-out the variables
of relative importance, the regression analysis indicated
the relative strength of the selected variables and the
path analysis gave both visual and correlational indica-
tion of the direction and strength of the variables as
they contributed to the variance explained in the outcome
variable. The determination of the variables explaining
an outcome variable is what the Heberlein study has in
common with the present work, however, a difference does
exist.

This study is a test of a pre—conceived and
structured model, thus it is not a model building exer-
cise, per se, but rather a model testing enterprise.
Multiple regression and path analysis will be the major

mode of testing the viability of the hypothetical model.

CHAPTER III

SYSTEMS THEORY

Rationale for a Systems Approach

 

Theory construction and thus theory validation
through empirical research have been hampered in broad
areas of knowledge by specialization. Laszlo suggests,
"As a result, the fields of knowledge are worked in
patches, each man concerned with no more territory than
his own, cultivating his own garden" (1972, p. 4).

In general, specialization has occasioned a
fragmented, disconnected set of postulates, theories and
empirical findings which tend to blind individual areas
of investigation to the wholeness, unity, order and
relatedness that exists within and between them.1 In
other words, there is a need that is not being fulfilled
by specialization. This need is articulated by scientists
and philosophers alike as indicated by these statements:

There is aneed today for bringing fresh and

reliable empirical information into philOSOphy
(and other endeavors); for overcoming the patch-

work approach in the use of knowledge as a means
of safeguarding ourselves against disaster due to

 

1Appendix A is a glossary of systems terms.

47

48

ignorance of the systematic interconnections in

nature; and for gaining insight into general pat-

terns of existence in this world as a means of

providing meaning for the brute fact of being

here (Laszlo, p. 7).
and

In recent years increasing need has been felt

for a body of systematic theoretical constructs

which will discuss the general relationships of

the empirical world (Boulding in Buckley, 1968,

p. 3).
Thus, for the scientific community, at least, there has
been a growing frustration with the barriers to communi-
cation which have developed with the specialization and
compartmentalization of knowledge and scientific endeavors.

Perhaps the time has come for a re-examination

of scientific goals, emphasizing the importance of inte-
gration and synthesis between and among apparently
disparate fields of inquiry. This, in fact, is being
called for both in the investigations surrounding the
energy problem and in the study of the family. As the
linkages between these two areas are of central importance
in this study, the rationale for the adoption of a variant
of systems theory will be developed here.

Systems Approach:
The Energy Problem

 

 

The energy problem does not exist in a vacuum
and, therefore, cannot be understood as an isolated

phenomena. Odum suggests, that to understand fully the

49

multi-dimensional aspects of the energy problem a systems
approach is required; i.e., a "common sense overview" is
indicated rather than the "tunnel-vision thinking" so
often apparent in our specialized economic,technological,
research approaches, where unidimensional paradigms focus on
only one part of the system at a time (1974, p. 227).
Odum calls for a systematic-holistic approach
to the study of energy, as illustrated in the following
statement: I
As long—predicted energy shortages appear,
as questions about the interaction of energy and
environment are raised in legislatures and parli-
aments, and as energy-related inflation dominates
public concern, many are beginning to see a unity

of a single system of energy, ecology and economics
(1974, p. 227).

Systems Approach:
The Family

 

 

The study of the family is no exception to the
rule of specialization, witnessed by the profusion of
conceptual frameworks that abound in the analysis of the
family. At least twelve different frames of reference
have emerged. They have been identified as: anthropo-
logical, structural/functional, demographic, institutional,
interactional, situational, psychoanalytic, social-
psychological, developmental, economic, legal and religious
(Christensen, 1964; Nye and Berardo, 1966; Hill and Hanson,

1968; Broderick, 1971). Although each of the frameworks

50

mentioned contributes insight into some aspect of family
behavior, either as it relates to the socio-cultural
system or as it relates to individual development and
interaction, they do not contribute to an integrated
understanding of the family as related to both its social
and physical environments from a systematic-holistic
perspective.

There is, however, evidence both in the theoreti-
cal literature and in the empirical work on the family
that indicates the fruitfulness of a systems approach.
Although the evidence is not strong, being limited in
scope and non-empirical, it does lend support to the notion
that families can be studied using systems frameworks.
Families have been conceptualized as a social system
(Parson and Bales, 1955), as an ecosystem (Hook and
Paolucci, 1970; pp. 315-318; Auerswald, 1973) as a func-
tional system (Giesmer, 1971; David, 1967), and further
from a general systems perspective (Kantor and Lehr,
1975).

Some evidence of the use of ecosystems models
for the study of the family have been identified.
These have for the most part been theoretical models
(Sims, 33 31., 1972; Vaines, 1974), that have been
tested using traditional statistical analysis. Causal
reflective models (with positive and negative feedback

100ps) have been recently used in family research

51

(Reiss, 1972; Black, 1972), however, no models of the
cybernetic-morphogenic (closed/Open) systems variety
has been developed for the study of the family (Black
and Broderick, undated paper). Hill has given serious
attention to the use of General Systems Theory in con-
junction with the family development framework, in order
to speculate about the systemness or systems isomorphic
between society at the macro- level and family as its
microcosm (Hill, 1971a; 1971b). To this author's know-
ledge this has not been empirically tested.

It would appear that the use of ecosystems,
cybernetic and general systems theory or some variant
of these in the study of the family is becoming a viable
approach to understanding the family from a wholistic,
systematic perspective.

General Definition
of Systems

 

 

A system, according to Webster, is an "assemblage
of objects united by some form of regular interaction or
interdependency; an organic or organized whole." Implicit
in this definition is the idea of parts that make up a
whole or unity. There is also implicitly expressed some
form of arrangement, organization, order. A system can
be organic or inorganic; physical, biological or socio-

cultural. In fact, a system can be a combination of

52

things or parts that form a whole. That whole can be of
any breadth or sc0pe and complexity ranging from very sim-
ple to multi-dimensional, macro- or micro-, finite to
infinite. Any of these attributes can be used to define

a particular system.

Systems notions are not new; they have been known
and studied for centuries, particularly as religious and
philosophic interpretations of the relationships between
man and nature.

The earliest systematic speculation of
mankind regarded the universe as a sphere of
order and harmony, and considered it man's
duty to fit himself into it with his conscious
purposes (Laszlo, 1972, p. 282).

Laszlo further contrasts Oriental and Western
thought, indicating that the Oriental ethic even today is
"oneness" of self with nature, i.e., a reverence for
nature as something to be held respectfully "for itself";
whereas, Western cultural thought since Christianity has
been dominated by the Puritan ethic "of using nature for
human ends" (1972, p. 282).

The most recent emphasis, however, in the study
of systems is the attempt to understand systems as a
whole or as Ackoff indicates to understand systems as
an "entity" rather than simply "a conglomeration of parts"
(1959). Thus, beyond the identification of the elements

or components of a system under definition, it has become

equally important to study the interactions within and

53

between systems to uncover their linkages and interde-
pendencies, i.e., to qualify and quantify the energy,
material and informational exchanges across systems
boundaries.

Three variants of systems theory will be dis-
cussed as an introduction to the more Specific applica—
tion utilized as the conceptual framework of this study.
Ecosystems, Cybernetic
Systems and General

Systems: Structure and
Control

 

 

 

EcosystemSZ.--The word "ecosystem? coined by the

 

late biologist, A.G. Tensley in 1935, is defined as "The
whole system including not only the organism-complex, but
also the whole complex of physical factors forming what
we call the environment" (1935, pp. 284-307). Most
accepted definitions of ecosystems inc1ude the idea of

a dynamic interaction, exchange, or interdependency
between an organism (O) or an aggregate of organisms and
the environment (E).

In the definition given earlier of a system there
is not an explicit reference to the concept "environment",
either as a setting for the interaction in the system or
as a part of the dynamics of the interaction; therefore,

a system is not an ecosystem except by definition.

 

j"Eco" means environment; systems indicates an
"interacting, interdependent complex" (Van Dyne, 1966,
p. 31).

54

The ecosystems approach was developed in the bio—
logical sciences as a means of studying flora and fauna
in symbiotic interrelationships with their natural habi-
tat (environment). The formal recognition of the related-
ness of organism and environment, introduces a unique
perspective on the nature of systems.

As L.J. Henderson took great pains to
point out in his book, The Fitness of the
Environment, the environment is just as
baSic as the organic system in the intimate
system -- environment transactions that
account for particular adaptation and
evolution of complex systems (Buckley,

p. 50).

 

 

Thus, within an ecosystems framework, organic
and physical environmental systems are seen interactively,
therefore, integratively. That is, the organism is con-
sidered interdependent with the environment, such that
to study each in isolation is to deny, thus not include,
important effects related to the interaction between

them. Figure 1 illustrates this interdependence:

E/‘N
K /0

Figure l.--Environment and Organism Interrelation.

The develOpment of an ecosystems perspectéye has

a history that can be traced to the writings of Darwin

55

(1892), who established the groundwork for what

later became the science of ecology in the biological
sciences mentioned above, and more recently in sociology,
geography, anthropology, psychology and home economics.

An ecosystems perspective in the natural sciences
focused on plants and animals as the organism of interest.
The term ecology, first used by the German biologist
Ernst Haekel in 1868 is derived from the Greek 91333,
means house or habitat (Hawley, 1950, p. 3). Sometimes
the emphasis is on the individual organism as in micro-
biology and at other times the unit of concern becomes
the community or aggregated organisms. The environment
of central interest is the natural physical environment.

The relationships of interest were identified
as the behaviors which were observed as the outcome of
the interaction between the organism and the environment.
Therefore, such notions as symbiosis, adjustment, adapta-
tion, territoriality, competition, dominance, invasion
and succession became the central interrelational concepts.
Emphasis was placed on "the processes of consequences of
change” (Adams, 1935); i.e., on the dynamic aspects of
the system rather than on the static dimensions.

As indicated, an ecological perspective eventually
developed in both sociology and geography -- labeled Human

Ecology.

56

Geography considers itself the science of human

 

ecology defining its concerns to be "the relationships
existent between the natural physical environment and

the activities of man" (Barrows, 1923). Investigations
in geography emphasize such deterministic variables as
climate, natural resources, natural routes and topography
as they influence human customs, beliefs, and attitudes
(White and Renner, 1961).

Sociology on the other hand considers human

 

ecology a subfield in the discipline that has been de-
fined as the "study of Spatial and temporal relations
of human beings as affected by the selective, distribu-
tive and accomodative forces in the environment"
(McKenzie, 1934, p. 288). Its particular focus is
human aggregates related to Spatial configuration in
the man—made physical environment including the block,
the neighborhood or some area of the city. The interre-
lative variables studied were social pathologies, such
as crime and mental illness (Park and Burgess, 1921;
Mckenzie, 1934; Paris and Dunham, 1939).

Anthropology also has contributed to an ecolo-

 

gical perspective by emphasizing the relationships be-
tween "cultural behaviors and environmental phenomena"
(Vayda, 1969). The organism of interest for the cultural

anthropologist has become the human aggregate; i.e., the

57

collective behaviors of particular groups. The environ—
ment of interest is the material world both natural and
man-made. And, the interrelationships which link the
behavior and environment are such variables as: values,
ideologies, traditions, norms, linguistic characteris—
tics, also including individual (personality structures)
as well as cultural life patterns.

There are two basic approaches to the Study of
the linkages between cultural patterns and the environ-
ment. The first is a systems approach, whereby behavior
is seen as a part of the total behavior/environment com-
plex (Lee, 1966; Thomas, 1973; Gould, 1963; Geertz, 1963;
Rappaport, 1967; Vayda, 1969). The second approach is
the environmental deterministic perspective; i.e., the
study of the extent to which environmental factors affect
the origin and development of cultural behavior (Duncan,
1961; Flannery, 1965; Kroeber, 1939; Whiting, 1964).

Most recently psychology has also developed an

 

ecological sub-area. Environmental psychology and eco-
logical psychology are the labels used to identify it.
The definition remains somewhat illusive due to the di-
versity of interests reflected within it. The human
individual is of concern; however, varied human groupings
and configurations are also studied. The environment of
special interest has been the physical built environment,

in particular the spatial arrangements within buildings

58

and housing arrangements (Sommer, 1969; Proshansky,
Ittleson and Rivlin, 1967; Rainwater, 1970; Altman,

1972; Newman, 1972). However, environmental psychology
has not been limited only to internal Spaces. Other
Spatial arrangements in the urban environment and even
natural environment also have been considered (Jacobs,
1961; Criak, 1966; Barker,l968; Michelson, 1970; Goffman,
1963; Cooper, 1975).

The interrelationships of concern have included:
privacy, crowding, density, territorality, locomotion,
perception and competence.

Nowhere in the fields mentioned above has the
family and its environmental interdependency been of
central concern. However, in the field of home economics,
early developments were very much within an ecological
perspective, largely due to the efforts of Ellen Swallow
Richards,3 who christened environmental science as
"Oekology" and further emphasized its importance as a
science stemming from everyday life which begins with
sound environmental conditions and practices in the home.

Home Economics as a profession was founded on
that principle. The definition developed in 1902 at

the fourth annual Lake Placid conference is as follows:

 

3Ellen Swallow Richards, during a period between
1870 and 1911, was the first woman student at M.I.T., its
first female faculty member and a vigorous researcher and
activist in the fight for pure water, air and food, good

59

Home Economics in its most comprehensive
sense is the study of the laws, conditions,
principles and ideals which are concerned on
one hand with man's immediate physical en-
vironment and on the other hand with his
nature as a social being, and is the study
specially of the relationships between those
two factors (AHEA, 1902, pp. 70—71).

A recent re-emphasis of this ecological perspec-
tive has been initiated in the field of home economics
with a change of name from Home Economics to Human
Ecology within various universities, i.e., Cornell.
University, Michigan State University, and the University
of Maryland.

The focal organism within this new re-emphasis,
has become the family as an environed unit: an ecosystem
within its near physical/biological and social/psycho-
logical environments (Hook and Paolucci, 1970; Steidl,
1969). The linkages between the family and other
systems is the theme of the re-emphasis. This includes
a particular interest in energy/matter/information flows
(exchanges across and within the family system boundary)
as processed and transformed by the family in everyday
living. Thus, empirically establishing the degree of
boundary maintainance within the family (its open or
closedness to other systems) taking into consideration

the social, economic, political and natural environmental

Iconstraints is central to a redefinition of the field.

 

nutrition, product labeling, safety and sanitation in both
the work place and in the home. (See Clarke, 1973 for the
detailed account of Ellen Richards' contribution to home
economics/human ecology).

60

The research endeavor undertaken here is indigen-
ous to and developed within this family ecosystems per—
spective.

Summarizing then, the central organizing concepts
around which all of the above mentioned ecosystems ap-

proaches have been developed are as follows:

1) Organism or environed unit (0),
2) Environment (E), and
3) The interrelation between the two (Sprouts,
1965, p. 25).
Ecosystems are structural interrelational systems
suggesting the interface between one system and another.

The following discussion of cybernetic and general systems

 

 

indicates something of systems function and control.

Cybernetic systemS.--Cybernetics, as proposed by

 

its founder, Norbert Wiener in 1948, ". . . is the science
of control and of information, whether applied to the
living world or to the inanimate machine" (Parsegian,
1972, p. 9).

Although the science of cybernetics is relatively
new, coming as it did into its own during World War II,
its historical roots can be traced back as far as Plato,
whose works contained the first known reference to the

word "Cybernetics" (Parsegian, 1972, p. 6).4

 

 

4Kyberns was the Greek term for steersman, which
gave root to the Latin term gubernator and finally to the
current term, governor.

61

The Cybernetics of man, as you

Socrates, often call politics. . .

(Plato, 428-348 B.C.).

The reference here is to governmental control,
however, its deeper implication is ". . . the idea of man's
controlling his own fate. . ." (Parsegian, 1972, p. 6).
This could, also, be expanded to include management in
the household.

Mechanical control devices have been known and
used by man in regulating aspects of his environment for
generations. Such mechanisms as the windmill, the steam
engine governor are early examples. More recently servo-
mechanisms from thermostats to guided missiles and in-
cluding guided manned space vehicles illustrate a few of
the many possible examples.

The theory of control syStems grew out of an
understanding of mechanical systems. The application of
the mechanical systems model to living systems was an
attempt therefore to use the laws and principles of
physical mechanics to explain the functions of organisms
and social units with more precision; i.e., borrowing from
the earlier success of physical scientists. Thus, such.
notions as time, space, attraction, fields of force, and
energy (along with the laws of thermodynamics and espec-
ially equilibrium) were translated into terms such as
social space (Lewin, 1947), social systems (Pareto,
Parsons, Homans and others), social dynamics and social

equilibrium (Buckley, 1967, pp. 8-9).

62

At one point such emphasis was placed on the
analogies between mechanical and living systems that life
was labeled "a living machine" and a counter force decried
the de-humanization or mechanization of mankind (Berta—
lanffy, 1968, pp. 134-141).

In Spite of the debate over the "fit" of the
mechanistic model, the theory of control systems became
the catalyst for a "crop of new approaches and theories."
Information, game, decision, circuit, automata theory and
systems analysis, to name a few, coalesced into the theory

of systems cybernetics. Wiener, in his book Cybernetics

 

(1948) formalized the discipline.

Although cybernetic systems can differ in the
focal system of interest (for example, mechanical, social,
organic, communications, neurophysiological, etc.) they
do, however, have certain features in common.

Parsegian suggests that these factors are:

1) Each of the Situations involves variables.

 

2) Each involves interactions of machines or
organisms with the environment, although
in the most general case limited.

 

3) Each involves an element of pur ose, or
object, and utilizes control pr1nc1ples
addressed to these purposes.

 

4) The interaction involves feedback, wherein
the results of any act are fedback to
modify the initial act.

5) The feedback may take the form of
information.

 

63

6) Each represents a dynamic situation in which
energy (human or mechanical) is utilized to
respond to changes and yet maintain stability
(cf. Parsegian, p. 2).

The above description of a "closed" cybernetic
system, including its general concepts and structural
features, indicates something of the necessary conditions
which must be present for the system to operate; however,
it does not indicate the system functions. Therefore,
the following will Specify a conceptual model of the pro-
cess dimensions of a "closed" cybernetic system. This
model has been adapted from Buckley's "social goal seek-
ing" model (1967, p. 197). Thus, any closed cybernetic

system generally exhibits:

l) A control center (1) which establishes goal
parameters toward self—regulation.

 

2) These goals are translated into action
outputs (2) which affect the state of
the system.

3) Information (3) about the state of the
system is fedback to the control center.

 

4) The control center compares (4) the state
of the system with the goal parameters,
and,

5) takes corrective action (5) if the system
is outside the parameters set (cf. Buckley,
p. 174).

 

Figure 2 is a schematic interpretation of this

process.

64

 

 

 

 

 

 

 

 

 

(l)
Cbnhxfl. ' (xel .
I (ZflknuonIJRxmts
center g... .Pfii'fitfiii Effect on
I Feeflxmk rnxxnve sumxaof
: TeFt 0n Acthml(5) SysUml
Feeflxck IBEOnmnfion
L of(1n$mms

 

(3)

 

 

Figure 2.—-Schema of Closed Cybernetic System Operations
(modified from Buckley's, p. 173).5

This representation has been modified from Buckley's
model of social goal seeking to exclude all exterior en-
vironmental systems effects which therefore allows the
label of "closed" cybernetic system. Open systems which
Buckley Suggests in his model will be discussed as part
of the general systems theory in the next section and a
comparison between open and closed systems properties
and conditions will be given at the end of the next sec-
tion.

In summary, then, cybernetic systems are generally:

1) Systems which are controlled, self-regulating
or adaptive self-stabilizing. *

2) Systems which have a purpose and therefore
are goal-directed.

3) Systems which respond to negative feedback
as the controlling mechanism in the system.

5This cybernetic model was compared to Kuhn's
(1974) detector, selector, effector process system and
found compatible. However, Buckley's model is included
because it is an "Operational" rather than a "conceptual"
model, demonstrating more clearly a systems Operation or
function.

65

4) Systems whose ultimate state is equilibrium
toward entrOpy (cf. Laszlo, pp. 38-41).

General systems theory.—-Bertalanffy's definition

 

of General Systems Theory (GST for convenience) is given
as, "an interdisciplinary doctrine elaborating principles
and models that apply to systems in general, irrespective
of their particular kind, elements, and forces involved."
(Bertalanffy in Laszlo, 1972, p. xvii).

Boulding considers GST a "system of systems" (in
Buckley, 1968, p. 4), whereas Caws considers it a ". . .
metatheory" (Buckley, 1968, p. 10), or a theory of
theory.

The notion of an all-encompassing theory of sys—
tems was introduced by Ludwig von Bertalanffy in 1937,
mainly in response to the need to explain biological
(living) systems in other than physical-mechanical "closed"
systems terms (mentioned earlier, p. 62) . Living systems
display certain attributes which are not consistent with
"closed systems" theory; i.e., closed systems require no
(or very limited) interaction with an environment, fix
goal parameters, self-stabilization through error reducing
negative feedback within fixed parameters toward an equili-
brium and increasing enthropy. Whereas, living (organic)
systems,in contrast, exhibit characteristics which are
counter to these. They display response to inputs from

the environment, acquisition of new parameters, instead of

66

predictable reaction to "fixed" parameters, amplification
of deviation as a function of positive feedback toward
self-organization, or increasing organization (decreased
entropY) thus, non-equilibrium or instability. These
characteristics are prOperties of an "Open" system.

Open systems are not, however, synonymous with
general systems theory. Rather, "the theory of open
systems is a part of a general theory of systems"
(Bertalanffy, 1968, p. 149). Although open systems gained
their impetus within the GST current and thus are often
discussed as the "more general case," recent developments
particularly the work of Laszlo (1972) would include a
continuum of closed to Open systems referred to in the
literature by various labels depending on the permeability

of their systems' boundaries. Figure 3 indicates these

 

distinctions.
Systems Permeability
Cldsed Opgk
MoIphostasis Morphogenesis
(Ma uyama)
Cybernetics I (Wiener) Cybernetics II

(Laszlo) (Laszlo)

Figure 3.--Continuum of Systems, Closed to Open.

67

A general model of the process dimensions of an

open system with characteristics listed below follows

for greater clarity. Thus, an open system generally

exhibits:

1) An input (1) that constitutes the control

2)

3)

4)

5)
6)

varlable.

A comparator element (2) that tests input
signal against the feedback.

 

A converter (3) that can amplify or
dampen down the input signal.

 

A source of energy (4) and other environ-
mental disturbances (5).

A feedback (6) information sensor.

And, an output (7) from the system to
the external environment.

Figure 4 is an illustration of an open system.

Dmnu:(l)
chn
enmhxmman:

 

 

 

 

he [he
. custudxumes
enmuxmman: ,

 

 

   
  

 

qumn:(7) E
to

Ifiwdnmment

 

 

 

 

—IInfimmatflx1 .
[semxnr(6)

Faxkadc

Figure 4.--Schema of an Open Cybernetic System (modified

from Parsegian, 1972, p. 73).

68

It becomes possible now to compare open and closed
systems (see pages 63 and 67). The greater complexity of
open systems comes mainly from environmental inputs, both
as control and as disturbance variables, as well as from
the ability of the open system to convert or transform
inputs.

In general, the greater the range of
effective interaction between the system and
environment, the greater the effect of per-
turbations (disturbances) introduced. . .
Consequently, the greater the requirements
on enduring systems for correcting. . ., i.e,
for adapting to conditions in the environment
. . . (Laszlo, 1972, pp. 61-62).

Monge has suggested that "in order to conceptua-
lize a phenomenon as an open system from the perspective
of GST," a set of necessary and sufficient conditions
must be meet (1972, p. 93). This listing follows:

1) Identification of the components of the system.
These are the parts, which together with interactions,
constitute the system. Parts may themselves be systems;
if so, they are subsystems of the major system.

2) Specification of relations in the system.

These are the laws of interaction among the components

which form the structure of the system.

 

3) Determination of system behavior. This implies

the identification of the processes which the system en-

 

gages in over time, as well as the prOperties which

these processes imply.

69

4) Stipulation of the environment. In open sys-
tems this is crucial because the system's exchange with
the environment, i.e., its inputs and outputs, must be
explained.

5) Determination of the system's evolution. Both

history and future are included here. hf.1bnge,l972,;u 93).

In summary, the central notions which general
systems theory contributes to a systems perspective are
the following:

1) The definition of systems as entities rather
than sets of discrete but related parts (Ackoff, 1961;
Bertalanffy, 1968; Laszlo, 1972).

2) The identification of systems hierarchies or
levels and the relationships between them. (Laszlo,
1972; Bertalanffy, 1968).

3) The distinction between intra- and inter-
systems hierarchies indicating both the "incorporative"
(within system elements) and the "coactive" (between
systems exchanges). (Laszlo, 1972).

4) The specification of the systems properties
which are applicable to all levels and complexity of

organized phenomena. This includes the natural system

 

functions as most recently developed by Erwin Laszlo

described by a functional model with these properties:

70

a) The systematic state property, i.e., the
wholeness and order of the system.

b) System-cybernetic I, i.e., the adaptive
self-stabilization of the system or systems
closeness. (Morphostatic model: Wiener, 1961,
Buckley, 1967; Bertalanffy, 1968).

c) System-cybernetics II, i.e., the adaptive
self-organization of the system or systems
openness. (Morphogenic model: Buckley,1967;
Black and Broderick,11¢iy;Maruyama, 1963).

d) The Holon-property, i.e., the intra- and
inter- systematic hierarchies, indicating
the nature of the relationship between
and within systems (Laszlo, 1972,;mu 35-53).

General Systems Theory is emerging as an integrat-
ing theory of systems which is tending to synthesize di—
verse systems paradigms (mechanical, organic, social,
ecological) into one unified field theory. Thus, the vast
diversity between Specialization is giving way to the
identification of the common systems prOperties underlying
both the structure and function of systems, including
levels from atoms to global systems.

Table 7 on the following page is a compari-
son of the major characteristic differences between
closed and open systems.

The description of systems perspectives sketches
in very broad outlines only the most general major contri-
butions each approach makes to the unifying concept of
systemness, i.e., toward a systematic, holistic frame of

reference. Although necessary in order to place each

systems approach into both a temporal and conceptual

71

TABLE 7.--Comparison of Closed and Open Systems Character-

 

istics.
Closed System Open System
(Cybernetics I) (Cybernetics II)

 

1) Isolation from environment. 1) Exchanges between en-
vironment and system.

2) Systems state pre-deter- 2) Systems state determin-
mined by internal con- ed and changing as influ-
ditions. encedlnrinternal and

external conditions.

3) Equilibrium—stability 3) Steady state some dis-
rather than steady state. tance from equilibruim
(equifinality or multi—
finality).

4) Negative feedback-reducing 4) Positive feedback-ela—

discrepancy between status borating structures to

quo & systems goals. meet changing condi-

(Morphostasis) tions surrounding goals.
(Morphogensis)

Q3

5) EntrOpy increases. 5) Entropy decreases.

 

Sources: Buckley, 1967, Sociology and Modern Systems
Theory, pp. 52-53, 58-59 and 70.
Black and Broderick, undated, Systems Theory vs.
Reality, pp. 17- -18, 23.
Monge, 1972, The Study of Human Communications
from Three Systems Paradlgms, unpublished Ph. D.
dissertatlon, pp. 93- 94.

 

frame, it does not go the full length toward making intel-
ligible the conditions which allow the theories to become
operational in empirical investigation. In other words:
1) What are the structural and functional
identities common to all systems

perspectives?

2) How are they made integral within this
study?

72

Structural Commonalities

 

It is possible to see the commonality, though
somewhat implicit, between these three conceptual systems
formulations. For each systems approach whatever the
label given, there is a focal physical or biological unit
of organization which becomes one system of intereSt;
there is a larger encompassing social or physical environ-
mental surrounding and; further, there is a sub-set of
physical, social and/or biological components which con-
tribute to the make-up of the system of interest. Thus,
for all systems perspectives mentioned there is a defini-
tion of a system of central concern as well as the identi-
fication of related inter- and intra- systems levels or

hierarchies.

The Functional Unity

 

For each of the systems approaches mentioned there
is also a reference to systems functions or processes
which takes into account the influence the system of
interest comes under and the processes of exchange (qual-
ities or quantities) between that system and its environ-
nental supra-system surrounds. And, further,the inner
workings of the system are also of concern; i.e. , the relation-
ship between sub-system or inter—system parts as they
influence the make-up and function of that system also are

key functional considerations. In the discussion of each

73

system, generally these functional or process dimensions

were labelled in several ways. For ecosystems they are

 

called the interrelationships or "observed regularities"
between the organism and the environment. Several of
these "regularities" were explicitly identified for each Of

the ecological approaches mentioned.

For controlled systems the function or process

 

aspects were made explicit in terms of the closed cyber-
neticity of the system; i.e., the internal pre-determined
control or comparator goal functions which necessitate
the systems Operation within a set of restricted para-
meters toward an equilibruim state and entropy.

When considering the general systems approach,

 

particularly as viewed by Bertalanffy and Laszlo, the
functions of the system are viewed within both a closed
and an open cybernetic model (Cybernetics I and II).
These cybernetic dimensions allow tracking the function-
ing of the system Of interest from the initial systems
state (point Of first observation) through its various
stages of adjustment and/or adaptation; i.e., either as
the system stabilizes toward an equilibrium state becoming
less open to external environmental (super-systems) in-
fluence or as it is organized toward a new complex state
level, Open to the external influences while further

adapting internal structures and functions to meet the

74

challenge Of the external influence, via negative and/or
positive feedback mechanisms.

Thus, as with the structural identity of the
different systems approaches, included here, certain
commonalities can also be detected within the functional
dimensions. Each system is seen as a process with dy-
namic qualities that can be viewed in terms of Spatial
or temporal changes or stability. Therefore, a degree
of interaction between and among systems levels can be
measured in some qualitative or quantitative form; i.e.,
exchanges of energy, material or information occurs
across or within system boundaries. "This exchange is
identified as input to and output from the system"
(Monge, 1972, p. 93).

Systems Integration: Unique
Contribution to the Develop-

ment Of the Conceptual
Framework

 

 

 

 

The major contributions made by each systems
approach to the framework used here will not, however,be
in the commonalities or unity found between them, but
rather will be in the unique aSpects each lends toward
the development of a Human Ecosystems framework as gener-
ally employed here and within which specific systems
relationships are empirically explored.

These unique factors will be highlighted and dis-

cussed briefly.

75

The ecosystem approach allows identification of

 

the structural components and the hierarchy of systems
levels considered of paramount importance to the concep-
tual framework. Thus, organism (environed unit) and
environment are generally conceived as the central systems
of concern. The organism being the central system; where-
as, the environment is the supra—system surround.

Both closed and Open cybernetic syStems attributes

taken from systems cybernetic and general systems theory

 

will be employed to give clarity to the functional link-
ages between the central systems of concern. These
linkages will Specify the relationships in the system
(particularly the inputs and outputs) which are the
crucial interactions that give the system structure. The
linkages between the organism and environment will be
first developed within a broad conceptual framework.

And, secondly, in Chapter IV the hypothesized relation-
ships between a more narrowly defined subset of systems
variables will be specified as the particular problem

under investigation in this research.

CHAPTER IV

THE CONCEPTUAL FRAMEWORK
AND HYPOTHESES

This chapter has two basic functions: first, to
discuss the broad human ecosystems framework from which
the more Specific set of relationships to be tested
empirically emerges and, second, to deduce the specific
subset of systems components whose relationships
(linkages) come under empirical test.

DevelOpment of the Conceptual
Framework of this Study

 

 

Prior to the research undertaken here, the author
developed a general analytic systems framework for the
purpose of overcoming "past definitional and conceptual
problems" related to the study Of man/environment systems
(B. Morrison, 1974, pp. 171—178). It will not be the
purpose to review the framework in its entirety, but
rather to extract portions of it to set the stage for

the empirical investigation Of this study.

76

77

This is by way of taking Ashby's "hypothetico-
deductive" (Laszlo, 1972, p. 208) route toward the study
of systems in contrast to Bertalanffy's "empirico-intui-
tive" approach (Buckley,l968, p.15). Each approach
has merit, depending on the intent of the systems re-
searcher. For example, Ashby's approach lends itself
particularly well to narrow systems analysis (the intent
of this research); whereas the Bertalanffy method allows
analogies to be drawn more broadly between systems; 1759- I
systems isomorphisms (not the intent of this research).
These two positions or methods can be distinguished more
clearly in Ashby's statement:

Two main lines are readily distinguished.

One, already well developed in the hands Of

von Bertalanffy and his co-workers, takes the

world as we find it, examines the various

systems that occur in it -- zoological,
phy51ological, and SO on -- and then draws

up statements about the regularities that

have been observed to hold. This method is

essentially empirical. The second method is

to start at the other end. Instead of first

studying one system, then a second, then a

third, and so on, it goes to the other ex-

treme, it considers the set of all conceivable
systems and then reduces the set to a more
reasonable size. . . " (Ashby as quoted in

Bertalanffy; Buckley (ed.), 1968, p. 15).

The latter position is the approach taken in this
research, because the intent of this analysis is to in-
vestigate the relatedness (linkages) between systems,
rather than the systems similarities (isomorphisms).

In other words, it starts with the general phenomenon,

attempts to see it wholistically and ends with a detailed

78

scrutiny of the subset of the parts. However, an impor—
tant qualification must be stated.

Although the Ashby approach is adapted generally,
the particular mode of analysis for this research is
different. Instead of using a series of differential
equations1 as the mode of analysis, multiple-regression
and path analysis were the analytic tools used (to be ex-
plained in the Methodology Chapter)- This is not to say
that great differences exist between these two analytic
modes, because they are in fact, quite similar; however,
the use of multi-variate statistical analysis was an
expedient taking into consideration the forms of analysis
most familiar to this researcher.

The following then is the portion of the analytic
framework considered useful in this research, modified
somewhat to meet the present need for a broad systems
perspective within which the specific problem can be
explored.

A Conceptual Framework:
Human Ecosystems Model

 

 

The Organism or Environed
Unit: The Family

 

 

Within human ecology the organism or environed

unit of concern are HUMANS, humans as individuals, humans

 

1For a review of summative and non-summative dife
ferential equations used in systems research see: Bertalan-
ffy, General Systems TheogxI 1968, Chapter 3, pp. 54-77.

 

79

as members of groups, humans as part of society. For
the purpose of this research the notion of organism (O)
as the first structural component will be expanded to
include a small aggregated human group or system, the
family.

Definitions of families have varied over time,
from the traditional parent-child kinship household
definition to a more contemporary view of "the family as
a pOpulation aggregate or system, that is, a corporate
unit which is circumscribed territorially within a house-
hold and which has some unit character differing from
the characteristic of its individual members. . ."
(Hook and Paolucci, 1970, p. 315).

Thus, the family (FS) is the system Of central
concern as the unit of analysis within this study.

The family Operates within and among several environ-
mental realms as super-systems surrounds, each of
which contribute to or hinder family life. These will
be identified as the natural, built and behavioral
environments.

The Environments
of The Family

 

 

The notion of environment (E) the second struc-
tural component in the ecosystem approach is also of

importance in the conceptual framework of this study.

80

Generally, environment is defined as "that which environs;
surroundings; specifically the aggregate of all the ex-
ternal conditions and influences affecting the life and
development of an organism, etc., human behavior, society,
etc.” (Webster, 1949). :~'- -; w
Hall and Fagan have given further clarity to the
relationships between systems and environment through this
definition:
For a given system, the environment is
the set of all Objects a change in whose
attributes affect the system and also whose
attributes are changed by the behavior of
the system. (In Buckley, 1968, p. 83).
As suggested earlier, there are several environ-
ments within which the family interacts. These have
been given definition by Luther Bernard, whose classifi-
cation Of environments follows, with some modification:
1) The natural environments (NE)
a) Physical or inorganic environments (P)
b) Biological or organic environments (B)
2) The built environments or derived environments
(MBE)
a) Socio-physical environments (S-P)
b) Socio-biological environments (S-B)
3) Behavioral environment (BE)
a) Socio~phychological (S-pys)
b) Institutional (IE)(Bernard, 1925, p. 325).
Figure 5 follows to illustrate graphically the

human ecosystems framework generally employed, showing

81

the linkages between environmental systems as derived

from Bernard's classification.

The Natural Environment

 

All life stems from the natural environment; it
is the genesis of life. Thus, it is the ultimate environ—
ment Of the individual and the family. In its unmodified
form it "Operates upon man and his social life" (Bernard,
1925, p. 325) through cosmic forces: the sun's heat and
energy, climate changes, and natural mechanical processes.
The natural environment is also the storehouse of organic
and inorganic materials and energies which have potential
for modification; i.e., natural materials (minerals,
metals and natural fuels) make up the base supply of
resources tapped by society, through skills and techno-
logy, in modifying or adapting nature to human needs and
requirements. In other words, the natural environment
is an uncontrolled ecosystem except to the extent that
humans "impose conscious control on it" (Kuhn, 1974,

p. 376 and 462).

Within this investigation climate, including tem-
perature and seasonal change will not be of empirical
interest. However, the inorganic resources in the
form of natural fuels (particularly, petroleum, natural

gas, and coal, to the extent it is used in electricity

82

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83

production) are of paramount concern. These resources
are the major modified energy inputs in the systems
framework. The consumption level, transformed to BTU's,
will be the measured output. hypothesized to be deter-
mined by natural environmental, physical housing and

family-social, economic and compositional factors.

The Built Environment

 

If the natural environment is the ultimate pro—
vider, the built environment allows life beyond mere
survival. The built environment plays a critical role
in mediating between the life of individuals and the
family and the hostile forces of nature. The built en—
vironment is a persons nearest and most immediate physical
environment and, in fact, is the primary environment for
most of mankind most of the time. The environment derived
from nature (cities, housing, clothing, transportation,
communication and production systems) - directly influences
and configures human life and human interactions. For
example, Studer suggested that the built environment is
"essentially a system of energy-matter elements which are
interposed between a collection of human participants and
the antithetical forces in the general, impinging milieu"
(1970, p. 58).

For the family one of the necessary built environ—

ments is the place of residence, the house. Thus, for

84

the purpose of the empirical work to be undertaken here,

i.e., the discovery of the major determinants of family

 

residential energy consumption, the single family detached

 

dwelling and its physical attributes will be the only
built environment considered in detail.

Physical housing attributes such as, size in
square feet, number of rooms, number of floor levels,
number of openings to the exterior (windows and doors),
insulation and type of construction, location and number
of major appliances, will be taken into consideration

as factors contributing inputs to energy use.

The Behavioral Environment

 

This environmental realm contains two systems
levels relevant in this investigation. These are:

l) The socio-psychological, more intimate
environment developed within the family.

2) The institutional environment which repre-
sents the social, economic, political, ethical
and other societal forces which impinge on
the family from outside.

Both systems levels involve information and de-

cision making flows (inputs and outputs) as compared to
the material and energy flows discussed previously (con-

trast the upper half of the conceptual framework with

the lower half, p. 82).

85

The institutional environment is organized around

 

or defined in terms of problems and the collective means
by which humans make adjustments to and manage their
environments. Laws, rules, costs, knowledge, and collec-
tive Values, expectations and goals, make up the aggregate
information and decision-making processing which affects
not only the consumption of materials and energies from
the natural environment, but also exerts external influ-
ence over the collective activity of the family. Tallman
suggests, for example, that linkages between the macro-
social structure and individual behavior 1J1: essentially
in two Spheres (institutional environments)i.e., the econ-
omic and political. He indicates that through the
economic sphere, pricing and wage mechanisms influence

the route to material goals. And, further, the political
Sphere influences through laws and other forms of regula-
tion, the distribution, and thus the availability of goods
and services (Tallman, n.d., p. 1).

Within this study the cost and availability of
energy supplies as regulated by the economic and politi-
cal institutions will not be hypothesized or tested,
they will, however, be indirectly examined through

family perceptions.

86

The social-psychological environment is the more

 

intimate environment of the family which reflects its
values, attitudes, beliefs, expectations, goals, customs
and traditions. It is the group informational exchange
and decision making realm, which affects not only the
family's internal interactions, but also affects its
decisions about the purchase and use of material and
energy resources.

As indicated before (Chapter III, page 49), most
of the traditional approaches to the study of the family
have been within one or both of these behavioral environ-
mental realms, often referred to as the social environ—
ment or milieu.

Kuhn, for example, simulates an internal model
of the family as "a small complex, multi-purpose, semi-
formal, cooperative organization (1972, p. 493), whose
internal interactions account for various social trans-
actions, including procreation, sex, child rearing,
mutual assistance and care for basic needs (1972,
pp. 415-425).

This set of behaviors can be viewed as sets of
social interrelationships between family members. Figure

6 illustrates:

 

Figure 6.—-Inter-family Social Behavior (depending on
number of family members).

In this case the family is conceived of as a
relatively "closed" behavioral environment, or system,
encompassing the social interactions that take place
within it. This behavioral environment can, therefore,

be characterized as an inter-familial social control

 

system. Its importance within this study is related

to the perceptual or subjective measures hypothesized

to determine family residential energy consumption.
Parsons and Bales (1955) have explored a broader

set of social behaviors that included not only the within

family exchanges and influences, but also social institu-

tional (societal) pressures exerted on the family from

outside the system; these are hypothesized to affect the

unit character of the family system and in turn the per-

sonality of the child within the family. This relation-

ship can be viewed in Figure 7.

88

 

 

IE AFS ) I/O

IE = Institutional Environment (society)
FS = Family (system).
I/O = Child and/or individual (as organisms)

Figure 7.--Social Relationship Between Society, Family
and Child and/or Individual.

Tallman has hypothesized a similar relationship
(see Figure'7above). He indicates that the family "is
conceived as a prime mediating agent between the social
structure and the individual" indicating that the repli-
cation of social structure within the family system is
mainly through "occupational roles" (n.d., p. 10).

Therefore, this behavioral environmental realm is
the environment providing information and,thus, external
control over the collective activity of the family.
These controls are imposed on the family from the outside,
thus, indicating the "openness“ of the family system to
influences (inputs) from society. These will be labelled

external-familial social controls.2 Within the study, the

 

indirect measurement of this form of control will be the

perceived cost and availability of energy resources and

 

 

2Both the internal and external familial controls
imposed by these two behavioral environments can be re-
garded in general as information exchanges from within
and between these environmental systems.

 

89

will be hypothesized to affect belief in the reality of
the energy problem as the intervening variable considered
to determine energy use.

The Utility of the Human
Ecosystems Framework

 

 

The usefulness of any conceptual framework, such
as the Human Ecosystems model, lies in its application.
The attempt has been to provide a broad and wholistic
perSpective of a total system, indicating its structural
components (organism and environment), their linkages
and the interdependencies. It is in a sense a general-
ized hypothetical model deve10ped for the purpose of

conceptualization and analysis.

 

Within the conceptual framework presented the
family has been identified as the central system of
interest. It will, therefore, become the unit of analy-

sis in this research. The environments (natural, built

 

and behavioral) with which the family interacts are
identified as the supra-system surrounds. The linkages
(inputs and outputs) have been broadly identified as
material, energy and information flows (inputs and out—
puts); however, these have not been made specific. There-
fore, in the following sections the hypothetical relation-
ships between a reduced subset of systems components will

be derived and tested empirically.

90

Deduction Toward
the Hypotheses

 

 

The family is an energy-driven ecosystem,
and the family members are inextricably linked
to the environment through energy flows
(Paolucci and Hogan, 1973, p. 12).

This statement is fundamentally the theoretical
hypothesis underlying this investigation, and as such it
is prophetic for this work in two essential domains: the
conceptual and the analytic.

Conceptually, thexnotion of "an energy-driven
ecosystem" suggests a process; whereas "energy flows"

indicate inputs from and outputs to the environment.

Figure 8 illustrates these notions graphically.

 

 

 

 

—-)[ INPUT H PROCESS H OUTPUT

rezmzzowH<zm1

 

 

lezmzzowH<zm|

Figure 8.-—Basic Input/Output Model (adapted from Burk,
1970, p. 319).

Analytically, the theoretical statement also indi-
cates the method most appropriate to test the notions.
In this case regressive path analysis was adopted as

the analytic mode (to be discussed in detail later) as it

 

91

allowed measurement of the linkages (paths of influence)
between the hypothesized inputs and outputs.

Thus, the bridge from the broad human ecosystems
framework to the deduced subset of systems components
(to be articulated as modeled hypothetical relationships)
is greatly enhanced by the delineating function this
statement performs. Therefore, from this point forWard
deduction is used logically to narrow and specify the
subset of systems components, first indicated in the
human ecosystems framework, toward the researchable pro-
blem.

The Generalized Family

Ecosystem Input/Output
Model

 

 

For the purpose of this study the family is
assumed to be a "living Open adaptive system", requiring
continual exchanges (inputs and outputs) with its en-
vironment in order to sustain itself and function at
survival levels and beyond. These inputs and outputs
are processed and/or transformed within the family
ecosystem and include the following:

1) Processing of materials.

2) Processing of energies (food & fuels).

3) Processing of information.

Examples of these processes are given to illus-

trate the pertinence of this set of notions. The family

transforms a number of material, energy and information

92

flows including: 1) material flows in the form of objects

(housing, equipment, transportation, clothing, etc.);

2) energy flows in the form of converted fossil fuels

(natural gas, petroleum, coal and electricity) and nutrient

flows in the form of food; and 3) information flows as

abstract or concrete messages which transmit notions

about reality (systems states).

This study is not concerned with nutrient or

material flows, per se; it is particularly interested in

energy and information flows, as illustrated in the

following more explicit, however, still somewhat general-

ized model of family ecosystem energy and information

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

Natural
OUTPUT Environment
. ENERGY .
Family Ecosystem I Consumption

Processing II Waste

(FBE & MBE)*
Information Institutional
I "Belief" in Environment
Energy Problem (Society)

flows. Figure 9 follows.
Natural
Environment INPUT

ENERGY

(FOSSll

‘ Fuels)

Institutional Information
Environment (Energy
(Society) Problem)
Figure
*FBE = Family Behavioral Environment
MBE =

 

Man-built Environment -- Residential Dwelling.

 

 

 

 

9.--Genera1ized Family Ecosystem, Energy and Information Input/Output Model.3

3Note the parallelism between this illustration and the material—energy and
information flows in the Human Ecosystem Framework, Chapter IV, page 82.

93

To elaborate further, the family transforms fossil
fuels as direct inputs to energize the various mechanical
processes within the place of residence (heating, cool-
ing, lighting, are examples) for comfort, convenience
and efficiency. The level of comsumption within the
1iVing place is the total amount of direct energy used
to support these mechanical processes (Output I), plus
heat loss and energy waste (Output II).

The level of energy the family consumes, however,
not only depends on inputs of the fuels, per se, but also
depends on information concerning the costs and avail-
ability of such fuels which, in this study, reflect pro-
cessed information about the energy problem (energy
crisis, Winter 1973-74).

The major concern of this study is to discover
the factors anticipating energy consumption in single
family detached dwelling units, including belief in the
reality of the energy problem. Therefore, such elements
as family income (being a good predictor of both energy
and housing consumption patterns: Newman and Wachtel,
l974),environmental factors, physical housing factors and
family compositional characteristics become the input
(independent) variables considered pre-existent to the

consumption of energy.

94

Educational attainment (generally a good predictor
of preceptions and beliefs) along with family income,
preceptions of the cost and availability of energy and
housing tenure are considered anticipatory of belief in
the reality of the energy problem. The "belief" variable
is itself considered an intervening input variable assumed
to be a percursor to energy consumption. The amount of
energy consumed is the output (dependent) variable assumed
to be determined by these factors.

The First—Order Input/Output

Model and Variables of the
Study

 

 

The prior discussion along with the presentation
of the first—order hypothetical model (Figure 10), follow-
ed by the tabled input/output variables (Table 8) specific
to the study, sets the stage for the final deductive pro-
cess; i.e., the presentation of the second-order hypo-
thetical model and the statement of the study hypotheses.
Figurellland Table 8 follow as transitive steps in the

deductive process.

95

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96

TABLE 8 .--Outline of Study Input/OJtput Variables and Their

Measurement.

 

INPUT/OUTPUT

 

INPUT

1.00 Natural Environment
1.1 - Seasonal changes
1.2 - Temperatures
1.3 - Energy Availability

2. 00 Built Environment
2.1 - Physical characteristics

of single family dwellings

3.00 Behavioral Ehvironment
3.1 - Economic constraints

3.
3.

3.2

11 - Cost of energy (actual)
12 - Availability of energy

(allocation programs)

- Family Characteristics

3.21 - Physical factors

.22 - Econcxmic factors

. 23 - Socio-psychological

factors

CIJTPUT

4.00 Built Environment
4.1 - 'Ibtal amount of energy

consumed in single family
dewelling

Variables not tested within

this study

2.21 - Total square feet

2.22 - Presence Of insulation
(ceiling, walls a. floor)

2.23 - Number of floor levels

2.24 - Total number of roams

2.25 - Number of roams heated

2.26 - Number of rooms air
omditimed

2.27 - Total number of windows

2.28 - Total number of doors
to exterior

2.29 — 'Iype of exterior cm-
struction material

2.30 - Number of major appli—
ances

2.31 - location of dwelling

3.21.

3.21.

3.23.

(rural/urban)

Variables not tested within
this study

Number of persms
living in dwelling
Family life cycle

- Educational attainment
(husband/wife)

- Gross family inccme
(1973)

- Housing tenure (owner/
renter)

- Belief in the reality
of the energy problem
(husband/wife)

- Perceived cost of energy

- Peroe ived availability
of energy by type

Measured in BTU's (British
Thermal Units)

 

97

The Second-Order Input/Output
Model: The Model to be Tested

 

This second-order hypothetical input/output model
indicates the specific set of relationships to be examined
empirically. The model containsaflJ.the variables to come
under consideration to predict and explain total direct
energy consumption in single family detached dwellings.

It demonstrates graphically the hypothesized relationships
including: the directionality of influence, as well as

the expected polarity of the relationships (positive or
negative correlations). The second-order hypothetical
model follows in Figure 11.

It should be noted that the natural environmental
factors (seasonal change, temperature and energy resource
availability) have been deleted from the second-order
hypothetical model (note Table £3, page 96). This dele-
tion occured for two reasons; namely:

1) Temperatures and seasonal changes are the
same for the sampled community (the greater metrOpolitan
area of Lansing, Michigan). Thus, for this study the
conditions do not vary; i.e., each household experienced
similar conditions during the energy consumption period

(June 1973-May 1974).

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99

2) There were no reliable measures of the change
in energy resource availability during the energy consump-
tion period (indicated above).4 Therefore, no measurement
could be included here.

The following then is the statement of study
hypotheses.

The Statement of
Study Hypotheses

 

 

Hyppthesis 1: Physical housing and family socio-
economic factors relate to belief
in the reality of the energy problem;

 

1) In the directions indicated by
the signs below:

2) In the rank ordered magnitude of
relationships stated below:

- Family heads educational attainment (+).

Gross family income, 1973 (+).

- Reported cost of energy consumed in
single family detached dwellings by
energy type (+).

- Perceived availability of electricity (+).

- Perceived availability of fuel oil (+).

- Perceived availability of natural gas (+).

- Housing tenure (+).

DONE-4
I

\lmU'lb

 

4Interviews with fuel oil dealers and officials
of the utility companies, surveyed for energy consumption
data were less than successful at tapping a measurement
of energy availability. Outside a description of the
"allocation program" for fuel oil, instigated during the
energy crisis (Winter 1973-74), none of those interviewed
had any hard data on how short energy supplies actually
were. In fact, the general impression given was that
no real problem existed in terms of shortages in energy
availability. Those interviewed consistently mentioned
increasing energy costs as an economic constraint to the
use of available energy supplies.

100

Hypothesis II: Physical housing and family socio-
economic factors relate to the
total amount (in BTU's) of direct
energy consumed in single family
detached dwellings;

 

1) In the direction indicated by

' the signs below:

2) In the rank ordered magnitude of
relationships stated below:

- Gross family income, 1973 (+).

- Total square feet in the dwelling (+).

- Presence of insulation in ceiling (-).

- Presence of insulation in walls (-).

Presence of insulation in floors (-).

- Number of floor levels (+).

- Number of rooms in the dwelling (total) (+).

- Number of rooms heated (+).

- Number of rooms air conditioned (+).

- Number of major appliances in the dwelling (+).
Type of construction material (+).

- Number of windows (+).

13 - Number of doors to exterior (+).

14 - Location of dwelling (urban or rural) (+).

15 - Number of persons living in dwelling (+).

16 - Family life cycle (+).

17 - Belief in the reality of the energy problem (-).

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Hypothesis III: Family socio-economic factors will
explain more of the variance than
housing physical factors for belief
in the reality of the energy problem.

 

Hypothesis IV: Housing physical factors will explain
more of the variance than family
socio-economic factors for total
direct energy consumption in single
family detached dwellings.

 

CHAPTER V

METHODOLOGY

Introduction

 

This investigation, focused on the socio-physical
determinants of energy consumption in single family de-
tached dwellings, is a part of an interdisciplinary study,
entitled "Functioning of the Family Ecosystem in a World
of Changing Energy Availability," funded by the Michigan
Agricultural Experiment Station.1

The initial funding period (January through June
1974) was prOposed for the purpose of designing and con-
ducting a cross-sectional field survey to act as a pilot
study to and a benchmark study for a five-year statewide
longitudinal study. The pilot field survey was conducted
within the greater metrOpolitan area of Lansing, Michigan,
during the months of May and June, 1974.

The discussion within this Chapter will center on
the following points:

1) The research method including: the justifi-

cation for its use, a description of the data

collection, and a brief description of the
data processing.

 

 

1Agricultural Experiment Station Project #3152,
Michigan State University. This researcher was the pro-
ject director from the date of initial funding, January
1974 thru December 1974.

101

102

2) The sample including: the sampled community,
the design and selection of the sample, and
tables describing the subsample charaCter-
istics.

3) The mode of analysis including: a description
of the independent, dependent and intervening
variables.

 

The Survey Research Method

The fundamental research design for the pilot
study was a cross-sectional field survey (a survey at
one point in time), undertaken for the purposes of
instrument testing, sample description and preliminary
determination of relationships.

In general, survey research is considered a
very efficient and effective mode of data gathering when
a particular situation is occuring or has occured affect-
ing a large pOpulation and about which description and/or
explanation is desired using a relatively large number
of variables. This mode of data acquisition is often
used during political campaigns and in market research as
a method to gain quick, representative bodies of infor-
mation upon which to base campaign strategy or product
distribution (Babbie, 1973; Moser and Kalton, 1972).

The cross-sectional survey research method was
considered logical and justifiable as the methodology for
the field survey on these grounds:

1) The energy crisis was a particular situation,

differentially impacting on a large prOportion of the

103

population, and about which both description and ex-
planation was desired.

2) The survey research method, in combination
with self-administered interview schedules (used as the
major means to elicit information) was considered the
most efficient and economically feasible approach within
the time and budget constraints of the initial funding
period.

Neither experimental research nor observational
methods would have allowed the collection of data on
such a vast number of variables (thirteen interview
schedule sections with approximately 46 major variable
categories), on such a large sample (217 families,
including 479 individuals questioned), in such a rela—
tively short time period (May and June 1974). Nor would
other research methods have encouraged or allowed the
development of a number of alternative explanatory models
to emerge from the data, each of which contributed insight
into the multi-dimensional energy problem. The research
undertaken here is but one of several models under in-
vestigation, within the initial study, made possible by
the survey research model.

The Survey Instrument and
Data Collection Procedure

 

 

Although the data analysis within this study draws

from a small portion of the data gathered in the field

104

survey, a discussion of the instrumentation and the
data collection procedure will be useful in understand-

ing the total system used for data procurement.

Interview Schedules

 

Three discrete sets of interview schedules were
developed and employed in the pilot study: 1) a set of
self-administered questionnaires concerned with energy,
food and the family; 2) a set of self-administered
questionnaires assigned by the interviewer to the
appropriate family decision-maker to gain information
concerning food, housing and transportation; and 3) a
set of interviewer-administered questionnaires to gain
data about the family demographics including income,
education, occupation and age.

The first set of self—administered questionnaires
was designed to elicit information from three family
members: husband, wife, and when present in the family,
one child over age twelve. In order to eliminate
confusion for the individual family respondents, packets
of interview schedules were labeled and color coded;2
i.e., each responding member was assigned a folder con-
taining questionnaires on energy, food and family atti-

tudes and perceptions. This first set of questionnaires

 

2Color coded folders and questionnaires were
assigned: Red = labeled husband or adult male; Blue =
labeled wife or adult female; Yellow = labeled child over
twelve years of age.

105

was designed to allow comparisons among family members
(individual scores) and also comparisons between families
(family scores).

The second set of interview schedules was answer-
ed by only one individual in the family; i.e., the
identified family decision—maker, depending on area of
questioning. The third set was also answered by one

family member. In most cases this was the adult female.

The Interview Procedure

 

The interview proceeded in three stages: 1) the
initial contact by the interviewer; 2) completion of self-
administered interview schedules by the families; and 3)

the re-contact and retrieval of the schedules by the interviewer .

Initial contact stage.--Twelve professional inter-

 

viewers were trained to conduct and monitor the field

3 The initial contact by the interviewer with an

study.
adult member of the household, introduced the purpose
of the study, determined fitness of the household to
the family criterion, gained permission for family par-

ticipation, and explained the interview procedure. The

interviewer also gave assurance of confidentiality and

 

3A day of training just prior to the field work
was conducted at the Institute of Family and Child Studies,
May 8, 1974 for the urban sample, and June 6, 1974 for the
rural sample. The field supervisor, along with members of
the interdisciplinary research team planned and conducted
these sessions.

106

instructed on the importance of the individuality of
each family member's reSponse indicating that payment
(a stipend of $10.00 per family) for c00peration would
be based on completion of the set of questions and the

individuality of the responses.

The self-administered stage.--A set of color-

 

coded materials for each identified family member was
left at the household. A period of approximately three
days was given for the completion of the self-adminis-
tered questionnaires. The family respondents each
answered a set of self-administered questionnaires
having to do with energy, family and food. Another set
of questions was assigned also to the family decision-
maker, according to his or her knowledge and level of
involvement with the area of questioning. These speci-
fic sets of questions were concerned with family trans-
portation, housing and food, including expenditures for

each.

The re-contact interview stage.--The interviewer

 

returned at an appointed time, checked the questionnaires,
and asked one adult family member (usually the female)
a set of questions concerning family characteristics

such as income, age, education and occupation.

107

The field survey provided data on many dimensions
of the family as suggested by the variety of topics
reflected in the three sets of interview schedules
(See AppendixIBfor a comprehensive listing); however,
this was not the only information gathered.

The Procurement of
Utility Data

 

 

Beyond the initial survey, two more limited
surveys were also conducted. The first was among the
utility companies providing the study sample with
energy (electricity, natural gas and fuel oil). The
second was a survey of tax assessment records to gain
precise information about the physical characteristics

of the family dwelling units.

Energy data.--Very early in designing the

 

research methodology for the initial study, it was
decided that precise energy consumption data were ab—
solutely necessary in order to measure actual levels of
energy use. Therefore, coOperation was gained from the
two utility companies4 providing electricity and natural
gas to the study respondents. Each company compiled a

set of data for each household which included month by

 

4Consumer Power Company provided data in cubic
feet of natural gas consumed. The Board of Water and
Light provided electrical data in kilowatt hours of
electrical power consumed.

108

month meter readings for a period between June 1973 and
May 1974. These data were coded in a form ready for key
punching and computerization.

Fuel oil data were also gathered through a three
stage process:

1) Letters were sent to all respondents who

used fuel oil, requesting their cooperation
and permission to seek their fuel consumption
data.

2) Respondents then returned a Signed, dated
permission slip which included the name and
address of their oil distributor. A stipend
of $3.00 was paid for each returned permission.

3) This researcher personally contacted each
dealer.5 The signed permission slips and a
letter of introduction proVided the necessary
entry and access to the requested data. All
dealers contacted were c00perative.

These fuel oil distributors provided data in
gallons of fuel oil consumed for each delivery date
correSponding to the time period for data gathered from
the utility companies. These data were in raw form and

had to be made ready for coding, before key punching and

computerization could take place.

Tax record data.--Data were gathered from tax

 

assessment offices in three townships, plus Lansing,

East Lansing and Holt. This survey of tax records6

 

5Some of these fuel oil dealers Operated in the
City of Lansing, making access to them convenient, others
were found in the outlying areas, requiring more effort
and many call-backs.

6Tax assessment records are open to the public,
therefore, no written permissions were sought from the
respondents.

109

for the study respondents provided accurate data about
prOperty value, size of dwelling in square feet, type
of construction, and other factors particularly impor-
tant to the hypotheses considered in this study.

Selected portions of the information gained in the
broader cross-sectional survey, along with the energy data
from the utility and fuel oil companies and the housing
assessment data.areused within this study as operational,
independent, dependent and intervening variables. These

will be discussed in a later section of this Chapter.

Data Processing

 

During the summer of 1974 the collected data
were coded, checked for coder reliability and accuracy,
key punched and verified. Code books were designed for
each section of the interview schedule and a system of
quality control was established for the coding. Two
persons supervised the ten coders and four persons re—
checked all the work of the ten coders. Coding instruc-
tion and resolution of coding questions was done only
by two process supervisors, again adding reliability and
consistency to the procedure. A commerCial firm was

contracted to do the key punching and verifying.

110

The Sample

 

The Sampled Community:
The Near Environment

 

 

The site selected and sampled for the pilot sur-
vey was the greater metrOpolitan area of Lansing, Michi-
gan. This Standard Metropolitan Statistical Area (S.M.S.
A.) was acknowledged to be a well defined social, economic,
political and ecological metropolitan system, Character-
ized uniquely by its diverse functions, being the seat
of state government, the location of both heavy and light
industry (basically related to the automotive industry),
the sight of a major state university (Michigan State
University), as well as being a central area of commer-
cial enterprise, surrounded by a productive agricultural
sector diversified by both crop and cattle production.

S.M.S.A. Lansing, Michigan, containing 1,702
square miles of contiguous land area, has a total popula-
tion of 378,000 persons and 89,610 families (1970 census).
This S.M.S.A. is a tri-county area with some portion of
Eaton, Clinton, and Ingham Counties falling within its
boundaries. It is considered to be a viable geographical
entity with a relatively heterogeneous population from
which a multi-stage probability sample of urban, suburban,
and rural families could be drawn. S.M.S.A. Lansing,
Michigan, therefore, offered the opportunity to study the

impacts of the energy problem, broadly defined by the

111

interdisciplinary research team and more specifically
defined by this investigator, on a relatively contained
geographical area with a diverse economic and social
environment. This has particular meaning for the problem
under investigation here because the community assured an
adequate sample both of family socio-economic character-
istics and of one unit housing structure types (single
family detached dwelling units) upon which the hypotheses

of this study could be tested.

Sample Design and Selection

 

The pilot field survey employed a multi-stage
area probability sampling technique in which the randomly
selected urban and rural areas of S.M.S.A. Lansing,
Michigan were successively subdivided into smaller and
smaller sampling units. In the urban area, sampling was
done from census tracts to blocks to individual addresses.
Outside the urban area sampling was done from counties,
to enumerated districts, to sections and last to indivi-
dual household addresses.

A goal of at least 150 urban and 50 rural families
was set, reflecting in general, the proportions of urban

and rural families in the S.M.S.A.

112

The Urban Sample

 

Two sources of household information for
the Greater Lansing Area were available: (1)
the 1970 Census Tract publication from the
U.S. Bureau of the Census, and (2) the 1973
Polk City Directory for Lansing and Suburbs.
Of the two possible procedures for sample
selection; i.e., directly from the City
Directory with a correction factor for new
construction, or an area probability selec-
tion from census tract information and enumer-
ation of all households in selected blocks,
we deve10ped a combination of the two proce-
dures. Either process alone would have en-
tailed added costs; the combined procedure
involved the sampling of geographical areas
from census tract and city block statistics,
but the final housing list was developed from
the City Directory. Such a compromise insured
first a representative sample of households
with the savings of a clustered sample and
the availability of a prepared list of house-
holds that needed only to be updated
(Zuiches, Morrison and Gladhart, Occasional
Paper No. 2, April 1975c, p. 3).

The compromise procedure used did, however,
encounter one problem. The two listings did not encom-
pass identical urban areas. Thus, a check was made and
the discrepancy between listings (eight tracts) were
discovered to be largely rural (built up area around
Lansing); since the rural sample was to be drawn separate-
ly, these tracts were simply omitted from the urban sampl-
ing frame.

The random selection of ten census tracts was
made with a total of 478 blocks (each tract and each
block having a known probability of selection prOpor-

tionate to the number of households therein). With a

113

random start blocks were selected (thirty—nine blocks were
dropped because they were apartment complexes on the
M.S.U. campus; a sample out of proportion to total pop-
ulation in the Lansing S.M.S.A. of students and faculty).
Thirty-four blocks then remained in the sample. In order
to insure a sample of families (not just households), in
keeping with the study criterion, two extra randomly
selected addresses per initially selected sample house-
hold (or 615 households) were included to cover reduc-
tions by screening, refusals, or other contingencies
(vacant, never at home and such).

A check of housing value and rents along with an
examination of median incomes within the selected tracts
indicated a reasonable approximation of socio-economic
levels in the Lansing metropolitan area, with a slight
over-representation of lower income areas, not considered

problematic (Zuiches, et al., 1975).

The Rural Sample

 

The rural sample was a random selection of the
townships taken from a listing of twelve townships within
the three counties indicated in the Lansing, S.M.S.A.

having no incorporated place or concentrated aggregation

114

of populations. This was done to insure the rural nature
of this portion of the sample. The three sections select-
ed were sampled and a listing of each household per
section was made. Again, each household had a known
probability of selection within the section and, again,

an over sample of two additional households per initially
selected address was included to cover reductions and

to insure at least 50 rural families as respondents.

Using the area probability sampling technique
employed (with every sampling unit possessing a known
probability of selection) does give some assurance of
the representative nature of the 217 families (160
urban, 57 rural families) that became the respondents,
within the population of families in the Lansing Metro-
politan area.

As stated earlier, only a portion of the three
surveys (discussed above) was used in this research, this
is also true for the sample. The subsample for this
study was controlled on three variables all considered
necessary for the precision of prediction desired in
testing the structural model developed for this Study.

The subsample for this study was selected using
three criteria: 1) families living in single family dee
tached dwelling units with, 2) a year's complete energy
data (total BTU's by household mix of electrical, natural

gas or fuel oil) for the period from June 1973 to May

115

1974, and 3) a precise measure of dwelling size in square
feet. This set of criteria served as controls and reduced
the sample of 217 families to 97.

Demographic and Socio-economic
Characteristics of the Sub-

sample

 

Tables 9 through 15 below report the basic socio-
economic and demographic data for the subsample. Appendix
C shows similar tables for the Lansing S.M.S.A. and the
large field survey sample. These latter tables are
provided for comparisons; none will be discussed in

the text.

TABLE 9.--Family Type.

 

Present Study Subsample:
Lansing S.M.S.A.

Family Type Number Percent

 

Husband-Wife

(with children) 65 (67.0)
Husband-wife

(without children) 26 (26.8)
Female heads

(with children) 6 (6.1)
Male heads

(no wife-with children) -— -—

TOTAL 97 (100.0)

 

116

Seventy-three percent of the study's subsample
have children living at home. The number of children
per family range from a mean number of 2.5 for urban
families to a mean number of 3.2 for rural families,
indicating small differences (0.7) in numbers of children

for this subsample (B. Morrison, March 1975a).

TABLE ]JL--Educational Attainment.

 

Present Study
Subsample: Lansing SMSA

Years of School (combines husband and Wife)

Completed Number Percent

 

0-8 years
(elementary school and

junior high) 38 (20.2)
9-11 years

(partial high school)
12 years

(high school completed) 76 (40.4)
1-3 years college 34 (18.0)

4 years or more
(college graduate and
professional training) 40 (21.3)

TOTAL 188 (100.0)

 

Seventy-nine, almost 80 percent of this subsample
(combined husband and wife) have completed a high school
education and beyond, indicating a high level of educa-

tional attainment in this study sample. This can be

117

explained by the educational opportunities available in
Lansing, which has two institutions of higher learning

(Michigan State University and Lansing Community College).

TABLE 11.--Occupational Categories by Sex.

 

Present Study Subsample:
Lansing, SMSA

 

 

 

Males Females
Occupational Categories # % # %
Professional 21 (23.6) 12 (12.3)
Managerial 9 (10.1) 4 ( 4.1)
Clerical & Sales 9 (10.1) 32 (33.0)
Skilled 27 (30.3) 4 ( 4.1)
Semi Skilled 22 (24.7) 9 ( 9.3)
Unskilled or Service
Workers 1 ( 1.1) 36 (37.1)
TOTAL 89 (100.0) 97 (100.0)

 

Males in this subsample Split on occupational
characteristics. They are divided between white-collar
(43.8 percent) and blue-collar (56.1 percent) occupations.
The Opportunities provided in the Lansing area, being the
seat of government, a university community, as well as
being a auto production center gives rise to this find?
ing. Females in this subsample appear in two main
categories: employed outside the home or homemakers. A

high prOportion have some form of employment indicated

118

by 62.8 percent in the labor force, a figure consider—
ably higher than the national average which is 44 per-
cent of all married women with husbands (Hayge, 1974,

p. 23).

TABLE 12.—-Income Characteristics.

 

Present Study

Income Categories Subsample: LanSing

 

(Family Gross Income SMSA

1973) Number Percent
Less than $4,999 6 ( 6.2)
$5,000 to $9,999 11 (11.3)
$10,000 to $14,999 28 (28.9)
$15,000 to $24,999 31 (32.0)
$25,000 or more 21 (21.6)
TOTAL FAMILIES 97 (100.0)

Median Income $15,000

 

The median income, 1973, for this study's sub-
sample is high, $15,000, compared to the national median
for 1973 which was $10,236 (see page 9 in Chapter I).
There is very nearly $5,000 difference between median
income for the same year. This indicates a relatively
affluent subsample, who are well educated and have a
high percentage of females in the labor force (62.5

percent).

119

TABLE l3.—-Age Characteristics by Sex.

 

Present Study Subsample:
Lansing SMSA

 

 

 

Male Female
Age Categories # % # %
under 18 years —- -— —- --
18-29 years 16 (17.7) 23 (24.2)
30-44 years 32 (35.5) 31 (32.6)
45-64 years 38 (42.2) 36 (37.8)
65 years & over 4 ( 4.4) 5 ( 5.2)
TOTAL 90*(100.0) 95* (100.0)

 

*Reduction due to respondents not reporting age (sub—
sample N=97).

A high proportion of the subsample are in the age
range between 30 and 64 years of age (77.2 percent for
males and 70.4 percent for females. This finding also
supports the level of affluence identified in Table 12,
as many of the individuals in the subsample are in their

most productive years.

TABLE 14.--Housing Structural Types.

 

Present Study Subsample:

Housing Structural Types Lansing SMSA

 

Units in Structure Number Percent

1 (including mobile homes) 96 (SHD) (99.0)
1 (MH) ( 1.0)

2 __ -_

3 and 4 -- --

5 or more -- --
TOTAL 97 (100.0)

 

120

This finding is self-explanatory, as the sub-
sample has been controlled on the criteria of single

family detached dwellings.

TABLE 15.--Housing Tenure.

 

Present Study Subsample:
Lansing SMSA

 

Housing Tenure Number Percent
Owner occupied 84 ’ (86.6)
Renter occupied 13 (13.4)
Vacant -- ---
TOTAL 97 (100.0)

 

The 86.6 percent owner-occupied housing tenure
is not surprising considering the single family detached
dwelling unit control. It is somewhat larger than the
1970 census, which indicates that 62.9 percent of single
family detached dwellings are owner-occupied. (See

Chapter I, page 13).

The Mode of Analysis

Path Analysis

 

Path analysis based on multiple-regression was
deemed the apprOpriate mode of analysis for this research
problem based on several theoretical and methodological
considerations: (1) The problem in this study is defined

as a test of the viability Of a model of hypothesized

121

relationships, the determinants of energy consumption
in single family detached dwellings; thus, some form

Of structured mathematical model is indicated. (2) Sys-
tems analysis suggested by the modelled input/output
process assumed in the research problem necessitates

the definition Of a causal structure whereby linkages
(path networks) are established, indicating the identifi-
cation Of the parameters Of causation or the quantitative
contributions each causal linkage has in determining

the overall variance.

"Given the dual goals Of specifying causal paths
and identifying causal parameters in a structural model"
is as Heise suggests, a complex consideration of the
relationships between variables, which is not concerned
with correlational sizes alone (1969, p. 41). Consider-
ation must also be given to how the variables are re-
lated; the spuriouness of the relationship and if
mutual causation, direct or indirect, exists.

The Assumptions of Path
Analysis: A Recursive Model

 

 

The specific hypotheses generated to be tested
from the second order hypothetical systems model (pages
99 and 100) are based on the intrinsic characteristics
of input/output models generally and, reinforced by the
assumptions underlying the mode of analysis; i.e., the

recursive path model.

122

The following assumptions are considered necessary
criteria to be met when the recursive path analytic mode
is employed:

1) Linearity; i.e., in the system of interest a

 

change in one variable occurs as a linear function of
changes in other variables (Heise in Borgatta (ed.),
1969, p. 44).

2) Recursive; i.e., the system of concern contains

 

no reciprocal causations or feedback loops; that is, if
X causes Y, Y cannot affect X either directly or through
a chain of other variables (Heise, 1969, p. 45).

3) Causal Priorities; i.e., the causal laws gover—

 

ning the system are established sufficient to Specific
causal priorities among variables (Heise, 1969, p. 52).
Time ordering is one method for inferring causal link-
ages.

4) Uncorrelated Disturbances; i.e., correlations

 

between variables are assumed not spurious. The assump~
tion is that the correlations in the model are functions
only of the variables being considered, and are not due
to mutual dependencies of some variables on others out-
side this model (Heise, 1969, p. 56).

These assumptions along with the basic assump-
tions which hold for multi-variate regression (sample
independence, homoscedasticity, independence of varia-

tion and reasonable approximations to ratio or interval

123

scales) are considered necessary requirements for de-
velOping linear recursive models and using path analytic
procedures.

In structuring the hypothetical second-order
input/output model from which the study hypotheses
emerge, all of these requirements are assumedly met,
within reasonable limits. The exception to this is the
assumption of a "reasonable approximation" to ratio or
interval scale, required by multivariate regression.
Some of the scales used to measure variables in this
study are ordinal. This is not considered problematic
in the preSent study for two reasons: 1) not all the
scales used in this study are ordinal, and 2) the issue
of ordinal verses interval and ratio measurement remains
an unsettled empirical question well beyond the ken of
this study.7

The assumptions of linearity and recursiveneSs

 

were investigated. It was not known prior to test-
ing the model if these assumptions hold. Therefore,

an examination of the results was done to test for

 

7Although a controversial issue, the use Of or-
dinal measures is often done in regression and path
analysis. In other words, the purist position is not
the accepted position. It has not been demonstrated
empirically that using ordinal measures makes any differ-
ence in the conclusion reached -— the opposite has, in
fact, been the case (Baker, et al., 1966; Borgatta,1953;
Labovitz, 1967). __ fl”

124

idiosyncrasies. Time ordering was used as the method for

 

inferring causal linkages in this research (refer to

discussion in Chapter IV, page 93 and 94).

The Operational Variables

 

Table 16 lists the operationalized dependent,
independent and intervening variables used in this study.
They are adapted from Table 8 developed in Chapter IV
(page 96), as input/output variables and their measure-
ment. These will appear once again (Table 16), using
the same numbered notations given in that previous list-
ing. The procedures used to operationalize the variables
appear in Appendix D.

Note should be taken of the fact that some of
the variables listed in Table l6can be classified as
objective measures while others are subjective. Objec—
tive measures include all data provided from sources
other than the respondents (utility companies, Oil deal-
ers and tax records), and also include some respondent
reported data of a factual nature. Subjective measures
include all data reflecting respondent beliefs and
perceptions. These are listed in Table 17.

A totally subjective study reflecting only family
perceptions (beliefs and attitudes) would not have given
the desired reliability of measurement needed to identify

the determinants of actual energy consumption; thus, a

TABLE l6.——Operational Variables .

125

 

Theoretical Variables

Operaticnal Variables8

 

INPUT (Independent)
2.00 Built Environment
2.1 - Physical characteristics
Of single family cbtacted
dwellings

3 . 00 Behavioral Environment
3.2 - Family Characteristics

3.21 - Physical factors

3.22 - Economic factors

3.23 - Socio-psychological factors

CUI‘PUT (Dependent)
4.00 Built Envirorment

4.1-Malamtofenergymled

in single family detached
dwelling

2.21 - Total square feet

2.22 - Presence or absence of
insulation

2.23 - Nunber of floor levels

2.24 - 'IOtal number of rooms

2.25 - Nmber of roans heated

2.26 - Nutber of roars air conditioned

2.27 - Total number Of windows

2.28 - Total nunber of doors to
exterior

2.29 - Type of exterior construction
material

2.30 - Nmber of major amliances

2.31 - location of dwelling
(rural/urban)

3.21.1 - Nurber of persons living

in dwelling
3.21.2 - Family life cycle
3.22.1 - Educational attainment
(husband/wife)
3.22.2 - Gross family income (1973)
3.22.3 - Housing tenure (owner/renter)

1 - Belief in the reality of

the energy problem

(husband/wife)

Perceived cost of energy

- Perceived availability of
energy by type (husband/wife)

4.11 -— Measured in B'IU'S (British
Thermal Units)

 

8

The measurement of operational variables are listed in Appendix D.

126

TABLE 17.-—Objective and Subjective Measures within the

Study.

 

Objective Measures

Subjective Measures

 

Data from outside sources

 

Climate data (1.1, 1.2)

Housing data (2.21, 2.23,
2.29, 2.31)

Energy data (4.11)

Factual reSpondent data

Housing data (2.22, 2.24,
2.25, 2.26, 2.28, 3.22.2)

Family physical factors
(3.21.1, 3.21.2)

Family economic factors
(3.22.1, 3.22.2, 3.22.3)

 

Data reflecting belief and
perceptions

 

 

Belief (3.23.1)

Perception (3.23.2,
3.23.3)

 

balance between subjective and

initiated to introduce greater

Objective measures was

rigor into the research

design. Table 17 indicates that the balance between

Objective/subjective measures in this study is weighted

in favor Of the Objective, thus assuring, to the extent

possible, a desirable level of

ments .

reliability in the measure-

CHAPTER VI

FINDINGS

Introduction

 

This chapter will be a presentation Of the study
findings with a twofold purpose. This is as follows:

1) To evaluate the relative effects (net and
gross) of a set of selected socio-physical factors as
determinants of the total amount of direct energy consumed
in single family detached dwelling units.

2) To assess in relative terms the viability of
the theoretical second-order, input/output model hypothe-
sized tO reflect the factors critical to the energy con-
sumption in single family detached dwelling units.

These goals will be accomplished by systemati-
cally presenting the components (the data array) that
make up, thus contribute to, the generated findings
including:

1) The structural equations.

2) The zero—order correlation matrix (AppendixIE,
page 208).

3) A table of means and standard deviations
(Appendix E . page 207 ) .

4) The tables displaying the essential data for
both dependent variables:

127

128

a) Belief in the reality Of the energy
problem.
b) Amount of total direct energy consumed
in single family detached dwelling units.
5) The path diagram including the standardized
path coefficients (8) and the amount of unex-
plained or residual variance (uU, vV)not
accounted for in the model.
6) The correlation coefficient between the
residuals (uU and vV), as a measure of
the extent of feedback existing in the
assumed recursive model.

7) A discussion of the test for linearity.

The model that is utilized in this study was pre-
sented in hypothetical form in Chapter IV (Figure 11, page
98). It is assumed that the paths do not violate any of
the theoretical assumptions (linearity, recursiveness,
mentioned in Chapter V), and further, it is assumed that
the independent or input variables are predetermined (ex-
ogenous) and therefore, determinants of the endogenous
(dependent) variables. This ultimately suggests a system
of simultaneous equations that permit the assessment of
the relative effects of the independent variables. The

structural or simultaneous equations used were:

X3.1 + P13.2 x3.2 + P13.3 x3.3 +

X +

X X +

1 = P14.1 4.1 P13.1

X + P 3.6 + P13.7 x3.7

x3.10 + P13.11 x3.11 +

x4.3 + P14.4

13.5 x3.5 + P13.6

X3.8 + P13.9 X3.9 + P13.10

+P X

P13.12 x3.12 3.13 + P14.3

X +P

13.13

X +P uU.

4.4 12 2 1

129

X4.2 + P24.1 x4.1 + P24.5 X4.5 + P2.46 X4.6

v
X4.7 + P24.8 X4.8 + P23.14 X + P V

P24.2

+P

24.7 3.14 2 °

Energy consumption

- Belief in energy problem

Physical housing factors

X3.1 = total square feet

X3.2 = ceiling insulation

X3.3 = wall insulation

X3.4 = floor insulation

X3.5 = number of floor levels

X3.6 = number of rooms

X3.7 = number of rooms heated

X3.8 = number of rooms air conditioned
X3.9 = number of major appliances
x3.10 = construction materials

X3.11 = number of windows

X3.12 = number of doors

X3.13 = location (rural/urban)

X3.14 = housing tenure (owners/renters)

Family factors

gross family income

mean education (husband and wife)

household size

family life cycle stage

reported energy costs

energy perception - electricity

energy perception - fuel oil

X
X
X
X
X
X
X
X

energy perception - natural gas

130

U 0 O 0
u = Unexplained re51dual and/or measurement error in the
energy consumption variable.
V O O 0
v = Unexplained res1dua1 and/or measurement error in the

belief variable.

Each of these model equations is multiplied
through by each Of the exogenous variables. Using a two-
stage least squares procedure, the subset of exogenous
variables that are thought to correlate best with the
endogenous variables are used to reduce the source of
estimation error. The process involves an ordinary re-
gression of each of the endogenous variables on all the
predetermined exogenous variables, termed an ordinary
regression on the independent variables. This technique
takes advantage Of the fact that the regressed values
are independent Of error terms and, therefore, yields
the exact number of simultaneous equations needed to
reflect the hypothetical model.

The analysis will not be directly concerned with
the means and standard deviations or with the zero-order
correlation matrix. Therefore, they are not included in
the findings Chapter, but rather will be found as Appen-

dix E, pages 207 and 208.

131

Belief in the Reality of
the Energy Problem

 

 

Findings

This research is designed to examine the net
effects of a set of theoretical values on total direct
energy consumption in single family detached dwelling
units. One of those values is an intervening variable
called "belief in the reality of the energy problem"
(hereafter "belief") thought to be the Outcome of several
exogenous (independent) variables. Thus, before estab-
lishing the total effects of all the independent variables,
including the "belief" variable on energy consumption,
the belief variable will be examined to allow an under-
standing Of its make up or determinants.

Hypothesis I indicates both the hypothesized
direction of the assumed linear relationships plus the
rank ordering of the independent variables as follows:

Hypothesis I: Physical housing and family socio-

economic factors relate to belief
in the reality of the energy problem;

 

1) In the directions indicated by
the signs below:

2) In the rank ordered magnitude Of
relationships stated below:

- Family heads educational attainment (+).

Gross family income, 1973 (+).

— Reported cost of energy consumed in single
family detached dwellings by energy type (+).

- Perceived availability of electricity (+).

Perceived availability of fuel Oil (+).

- Perceived availability of natural gas (+).

- Housing tenure (+).

WNH
I

\lO‘U‘lub
I

132

The findings of this multiple regression analysis
using standardized (B) regression coefficients are pre-

sented in Table 18.

TABLE 18.--Standardized Regression Coefficients, F-ratios,
Probability of Sampling Error and Multiple
Correlations of Seven Independent Variables on
Belief in the Reality of the Energy Problem.

 

Belkfifvarfiflfle
Pndxtulflarof
Smmflinglhmor,
Imkxendau:vacutfles 8 F Onefkdledflest

 

MamiFamflyflflmxethed

Attainment . 361 16 . 07 = . 001
Perception of Electricity
Availability .315 13.05 <.005
Reported Obst of Energy .183 4.58 <.05
Gross Family Income .113 1.33 >.25
ItmoqxioncfifNaUHel
Gas Availability .099 .75 >>.25
Penxmmflx10fFuelCfil
Availability .087 .61 >>.25
HOuSing Tenure .053 .37 >>.25
CNerall F 9.48 <.0001
R = .653 df regression 7
R2 = .427 df residual 89

 

Percentile points of F distribution at 6 and 88 degrees of freedom:

Percentile Tabled.F
75 = .25 1.74
90 = .10 2.76
95 = .05 3.74
97.5 = .025 4.96
99 = .01 7.06
99.5 = .005 9.12

99.9 .001 16.21

133

Discussion

 

Hypothesis I, Part I, indicates a positive (+)
directional relationship for all the independent variables
with the "belief" variable. This suggests that there is
an expectation for stronger belief (husband and wife
agreement) in the reality of the energy problem, with each
apprOpriate or designated change in the independent
variables. For each of the seven independent variables
the hypothesized positive relationships can be stated
thus:

1) As mean family educational attainment increases,
there will be more agreed belief in the energy

problem.

2) As gross family income increases, there will be
more agreed belief in the energy problem.

3) Families who report total yearly residential
energy costs will agree more in the reality of
the energy problem than non-reporters.

4) Families who agree on perceiving problems in the
availability or energy forms (separate hypothesis
for electricity, natural gas and fuel Oil) will
also agree on belief in the energy problem.

5) Families who own their dwelling unit will agree
more in the reality of the energy problem than
families who rent.

It is apparent from Table 18 that the hypothesized
positive direction of relationships holds true for all
seven variables. There is a positive correlation (8)
between each of the seven independent variables and the

"belief" variable, therefore, Hypothesis I, Part I is

supported by the findings.

134

Hypothesis I, Part 2, hypothesizes the rank or—
dering (the relative magnitude or strength) of the re-
lationships between the seven independent variables and
the "belief" variable. This hypothesis is 293 fully
supported. Some deviation from the modelled ordering
occurs.

Three of the independent variables hold their
hypothesized rank (educational attainment, reported
costs and housing tenure), whereas four variables shift
their ranked positions.

This shifting is not considered extremely proble—
matic, however, on the grounds that the second-order
hypothetical model tested here is considered a figgt
crude estimate of the relative magnitude Of relationships
between belief in the reality of the energy problem and.
the seven variables hypothesized as determinants.1

The important aspect, therefore, of this set of
findings is not so much in the deviation from rank order-

ing, but rather in the overall amount Of variance explained

 

1The rank ordering undertaken in this study (both
Hypothesis I and II) was not based on prior empirical and/
or theoretical insight, thus the importance of the ranking
wasrun:so much in testing the ranking per se, but rather
in this case it was important as a means to determine mean-
ingful, explainable magnitudes of relationships. In other
words, rank ordering prior to regression gives greater
explanatory capacity compared to entering the variables
randomly or without attempted structuring into the re-
gression. In this study step-wise regression was used.

135

by the seven hypothesized independent variables when con—
sidered as collective determinants. In this case 42.7
percent (or R2 = .427) of the variability in the "belief"
variable is explained by the multiple squared effects of
the independent variables. This is considered a rela-
tively substantial level of explanatory capacity in
social science research where R2.S of .30 or less are
Often considered of interest (Herberlien, 1975).

Some of the rank ordered findings are, however,
interesting in and of themselves. For example, mean
family educational attainment does remain (as hypothe-
sized) the most important explanatory variable (8 = .361,
p=.001). This is not surprising considering the fact
that education is generally a good predictor of attitudes,
perceptions and beliefs (as indicated in Chapter III,
page 94)-

Perception of electrical availability as a
problem ranks second in order (8 = .315, p<.005). This
finding is somewhat curious. However, when taking into
consideration the fact that all_of the study's subsample
depend on electrical power to some degree, and very

likely have experienced the inconvenience of interrupted

service, this finding becomes more logical.

136

The perception of fuel Oil availability as a
problem which ranked sixth in the findings (8 = .087,
p>>.25) is the most challenging to explain. During the
energy crisis period (Winter,1973—74), fuel oil was the
only energy source (considered in this study) to come
under government allocation. This would suggest that for
those using fuel oil it could have been considered a
problem. This, along with the wide media coverage of
petroleum shortages in general, and the allocation pro—
gram in Specific, should have, on logical grounds, made
it more important in affecting belief in the energy
problem.

There may be several reasons this rank ordering
shifted: 1) there were only 18 families in the study
(N=97) who used fuel Oil as a form of energy in their
homes and, as suggested before, this was not the sole‘
energy source; 2) as indicated earlier (footnote 4,
page 99) the fuel oil dealers did not report delivery
problems to consumers during the allocation period.
These reasons are seen as possible explanations for the

ranking discrepancy found.

137

Total Amount of Direct Energy
Consumed in Single Family .
Detached Dweliings

 

 

 

Findings
Hypothesis II is a test of the mgjg£_hypothetical
concerns of this study. The "belief" variable is now
included along with sixteen other independent input
variables to be tested as mg; determinants of energy con-
sumption in the single family detached dwelling unit.
Hypothesis II is restated below giving both
expected directional signs and the rank ordering of mag-
nitude.
Hypothesis II: Physical housing and family socio—
economic factors relate to the total
amount (in BTU's) of direct energy

consumed in single family detached
dwellings;

 

1) In the direction indicated by
the signs below:

2) In the rank ordering magnitude of
relationships stated below:

1 - Gross family income, 1973 (+).
2 - Total square feet in the dwelling (+).
3 - Presence of insulation in ceiling (-).
4 - Presence of insulation in walls (-).
5 - Presence of insulation in floors (—).
6 - Number of floor levels (+).
7 - Number of rooms in the dwelling (total) (+).
8 - Number of rooms heated (+).
9 - Number of rooms air conditioned (+).
10 - Number of major appliances in the dwelling (+).
11 - Type of construction materials (+).
12 - Number Of windows (+).
13 - Number of doors to exterior (+).
14 - Location of dwelling (urban/rural) (+).
15 - Number of persons living in dwelling (+).
16 - Family life cycle (+).
17 - Belief in the reality of the energy problem (-).

 

138

As in Hypothesis I, the signs give an indication
of the anticipated direction of relationships. A few
examples will be given for increased clarity; however,

in this case most are forthright and non-problematic.2

1) For rank orders 1, 2, 6, 7, 8, 9, 10, 12, 13
and 15 an hypothesis of increasing values in any of the
independent variables is considered concomitant with
increasing energy consumption in BTU's, therefore, posi-
tive signs are hypothesized.

2) For rank orders 3, 4 and 5 the hypothesis
being tested is that with the presence of insulation
(ceiling, walls, and floors) less energy will be con-
sumed, thus negative signs are hypothesized.

3) Rank order 11 is testing the hypothesis that
differences in exterior surface, construction materials,
differs positively with energy consumption.

4) Rank order 14 hypothesizes that rural dwell-
ing units will consume more energy than urban dwellings.

5) Rank order 16 hypothesizes that families in
the mid-cycle of life will have a more positive, direct
effect on energy use in the dwelling than families at

the younger or older end of family life cycle stages.

 

2See Appendix D for the Operational definition
of the variables used.

139

6) Rank 17, belief in the reality of the energy
problem is hypothesized to have a negative effect on
energy consumption. The more the agreed belief in the
reality Of the energy problem, the less energy consumed.

Table 19 indicates the outcome of this multiple

regression.

TABLE l9.--Standardized Regression Coefficients, F—ratios,Probability
of Sampling Error and Multiple Cbrrelations Of Seventeen
Independent Variables cm the Amount of Direct 'lbtal Energy
Consumed in Single Family Detached Dwelling Units.

 

Amount of Direct Total Energy
Cbnsumed

Probability of
Sampling Error,

 

Independent variables 8 F One Tailed Test
Household size .280 8.02 <.001
Major appliances .211 3.19 < .01
Number of rooms .173 1.30 z .25
Number of exterior doors .168 2.38 < .05
Number of rooms heated .165 1.71 < .25
Square feet .081 .56 >>.25
Family gross income .064 .35 >>.25
Number of floors .055 . 37 >>.25
Number Of windows .049 .24 >>.25
Insulation — floors .027 .94 >>.25
Construction materials .024 .73 >>.25
Family life cycle stage .024 .58 >>.25
NUmber of rooms air

conditioned -.007 .56 >>.25
Belief in energy problem -.095 1.02 > .25
Insulation - walls -.096 1.00 > .25
Location (rural/urban) -.127 2.14 < .05
Insulation - ceiling -.161 3.41 >.005
Overall F 4.38 >.0001

R = .696 df regression 17
R2 = .485 df residual 79

Percentile Points Of F distribution at 16 and 78 degrees of freedom:

 

Percentile Tabled F
75 = .25 1.36
90 = .10 1.87
95 = .05 2.25
97.5 = .025 2.63
99 = .01 3.12
99.5 = .005 3.49
99.9 = .001 4.37

140

Discussion

 

Hypothesis II, Part 1, is substantially supported
by the findings; i.e., most of the hypothesized direction-
al relationships hold. There were, however, two excep-
tions: 1) presence of insulation in floors, where a
negative relationship with energy consumption was ex-
pected, but a positive relationship was found; and 2)
rural dwellings, where a positive relationship was ex—
pected with energy consumption,but a negative relation—
ship was found.

In both of these cases the magnitude of relation-
ships tO energy consumption is near zero (8 = .027 for
floor insulation and B = -.127 for rural dwellings) which
indicates a weak standardized correlation exists between
these two variables and energy use.

In a further analysis of the data it was dis-
cerned that each of these variables had small cell numbers
out of the total (N=97). Only 10 families reported floor
insulation,3 and there were only 15 rural families in this

subsample.4 This helps explain both the weak correlation

 

3Floor insulation would not be common in mid-
Michigan where basements are prevalent, thus decreasing
the need for this form Of insulation.

4Controls for total energy consumption for a year,
and square feet measurement eliminated a number of rural
dwellers from this subsample.

141

(magnitude of relationships) with energy consumption and
the reversal in Sign directiOn (fluctuation + or - near
zero correlation).

Hypothesis II, Part 2, is not supported by the
findings. Most of the a priori rank orderings of magni—
tude shifted their positions in the outcome ordering
when using standardized correlations (B) as the measure.
This is considered neither surprising nor extremely
problematic. The rationale for rank ordering the inde-
pendent variables prior to the analysis was to have a
means to enter the data into the multiple step—wise
regression with some structure (rather than randomly),
as suggested for Hypothesis I, Part 2).

The selected variables and their rank ordering
were considered at the Offset a first approximation model
and, therefore, misjudgments were considered very much
in the realm of the possible.

The important finding here (as in Hypothesis I,
Part 2), is not so much the ranked input per se, but
rather: 1) the outcome, in terms of the rank ordering
after the step-wise regression occured, and 2) the
amount of variance in the energy consumption variable
explained.

Nearly 50 percent (48.5 percent or R2 = 485) of

the variance is explained by the array of seventeen

142

independent variables selected as predictors (determin-
ants) of energy consumption in single family detached
dwelling units. This is a most important finding be-
cause it appears that the variables selected to explain
energy consumption come a very great distance toward
doing just that.

Rarely in social science research will multiple
regression outcomes be near 50 percent of variance
explained. This may be due to any number Of factors:
1) poor measurement techniques; 2) flaws in the theory;
3) use of subjective measures; and 4) measurement and
random errors, to name a few. Using mainly objective
measures, as in this study (indicated in Chapter V,
page 126), may have cut down some of the factors giving
rise to lower explanatory or predictive power often
found in other studies.

Table 19 above, indicates the outcome rank
ordering which will be given some attention before pre-
sentation of the path model and findings.

Discussion of Some of
the Interesting Findings

 

 

Household size is the first variable of impor-

 

tance in magnitude of relationship (8 = .280) with energy
consumption. This finding is of particular interest
because it is contrary to the only study which is directly

comparable to this one. Fox, 3: 31., in the Twin River

143

study found that household size washed out as a critical
factor explaining energy consumption as compared to
physical housing factors. In their study, homogeneity

of household size (approximately three persons per house-
hold) was given as the reason it did not hold up in the
analysis.

In this study, however, a mean Of 3.96 persons
lived in the dwelling units, which ranged in number from
two to twelve persons per household. This greater vari-
ability could help explain why household size becomes
important as a predictor of energy consumption in this
study.

The other interesting aSpect of this household
size finding is that it shifts in rank ordering from
position 15 to position 1, thus outranking all other
factors including other family factors and all physical
housing factors in this study. The implications of this
finding suggest that it is the people within the dwelling

5

unit and their aggregate demands (habits, behaviors and/

or life styles) on energy using facilities that made the

 

5Gladhart in a recent analysis of a larger sub-
sample (N=l3l) from the same pilot study used here,
looked at per capita household energy consumption, which
indicates economies of scale involved in larger house-
holds. Although interesting, it does obscure aggregate
energy consumption or that the more persons in a house-
hold the more energy used, in spite of the fact that each
person uses less (B. Morrison, AHEA Speech, June 1975b).

144

difference, rather than the characteristics of the facil-
ities themselves. This has very important energy conser-
vation implications.

The number Of major appliances within the dwell-

 

ing place ranks second in order of importance (8 = .211)
in predicting energy consumption in the household. This
finding is of interest because it suggests that along
with the number of persons living in the dwelling, it is
the number Of energy consuming appliances used by these
persons which makes a difference in energy consumption,
as compared to the physical aspects of the dwelling place
alone. In this subsample the mean number of appliances
per household was 9.2, with a range from 4 to 16 major
appliances, depending on household. This also has im-
portant implications for energy conservation practices.
In the rest of the findings three or four others
stand out as interesting to discuss. Gross family income
which was hypothesized to be 322 ranking variable pre-
dicting energy consumption in the second-order model,
shifts to seventh position in the findings. The logic
behind ranking it first was that with greater family
economic resources, more energy would be consumed in the
place of residence. This turns out to be only partially
true. What was not taken into consideration was the
interdependency Of income with other variables included

here and perhaps with some not measured. In other words

145

gross family income turns out not to be solely and direct-
ly related to energy consumption, but was also related
indirectly through other variables (house size, number of
major appliances, home ownership, and such) to energy con-
sumption. Also not accounted for here is the use of
economic resources for other‘ expenditures such as

food, clothing, entertainment, education, medical expen-
ses, which would also reduce the amount of income avail-
able for energy and energy consuming items, thus making

it a less potent predictor of energy consumption alone.

Measurement of house size by square feet (tax

 

assessment records) was used as a control variable, indi-
cating its importance as a predictor of residential
energy consumption; in fact, it was ranked 2nd in

the hypothesis tested. In the findings it takes the 6th
position, whereas number of rooms in the dwelling unit
ranks 3rd. This finding indicates that the exact square
foot measurement (8 = .081) is superseded by a good
approximation (number of rooms) as a predictor of (8 =
.173) energy consumption, indicating that perhaps less
precise detail was needed in the hypothetical model than
thought prior to this analysis.

Insulation in the ceiling turns out to be a good

 

predictor of energy consumption in magnitude of relation-

ship (8 = -.l61). The negative direction of the

146

relationship was hypothesized; i.e., presence of insula—
tion in the ceiling should be related to decreased energy
consumption.

Insulation in the walls was similarly negatively

 

related to energy consumption; however, its magnitude of
relationship to energy consumption was less strongly
correlated (8 = —.096) . These findings tend to support
the practice of energy conservation through home insula-
tion.

Belief in the reality of the energy problem turns

 

out to have the negative directional relationship hypothe—
sized with energy consumption, but the magnitude of rela-
tionship is not strongly correlated with the energy con—
sumption variable (8 = -.095). This finding is important
because it indicates that although there was information
in the environment about energy shortages and increased
costs, this information does not have a serious impact

on the amount of total direct energy consumed in single
family detached dwelling units; in fact, the standardized
correlation was almost zero, indicating relatively no
effect at all. This finding also has important implica-

tions to be discussed in the following Chapter.

The Path Model

 

Having presented some of the more interesting

findings from the multiple regression analysis, it now

147

becomes important to see this in structural modelled form.
Thus, the second-order hypothetical model will be pre-
sented here, including all the path coefficients, the
residuals not explained in the model, as well as the
correlations between the residuals as an indicator of

the feedback present in this model.

The second-order Specified input/output model of
paths of relationships follows on page 148 as Figure 12.

The specified path model indicates again the
standardized path coefficient (8) as seen in Tables 18
and 19 for each of the independent variables with the
two dependent variables: 1) belief in the reality of the
energy crisis; and 2) total direct energy consumption in
single family detached dwelling units.

Beyond this, the path model also indicates the
amount of unexplained or residual variance (1- R2) not
explained in the model. For the "belief" variable, when
used as a dependent variable, the path from the residual
is l-R2 = .557 or in other words, 57.7 percent of the
belief variable remains unexplained.

For the energy consumption variable, where "belief"
becomes one of the seventeen independent variables, 51.5
percent (1- R2 = .515) of the energy consumption variable

remains unexplained. In both cases the residual which

remains may be due to sampling error or more likely to a

148

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149

combination of sampling errors and variables not examined

in the model. However, the overall F was significant for

 

each portion of the model (p<.0001), indicating that
there was negligible probability that the overall results
were due to sampling error. This gives rise to a search
for other variables that will help explain more of

the variance in both portions of the model in future
endeavors.

Tests for Recursiveness
and Linearity

 

 

Two of the assumptions which underlie the struct-
ural model and, therefore, the multiple regression and
path analysis in this study, indicated that this model

was assumed recursive; i.e., contained no feedback; and,

 

further, that the relationships within the model were
linear; i.e., a change in Y corresponds to a similar
change in X. These two assumptions could not be examined
prior to the analysis; therefore, they come under con-
sideration here.

The path model indicates a correlation between

U and vV. This coefficient indicates

the two residuals u
a test of any remaining Variance hypothesized in the paths
that is not accounted for in other ways. If the correla—

tion between the residuals is low or near zero, all or

nearly all of the variance has been accounted for in the

150

model, thus, no or very little feedback exists in the
system. The correlation between the two residuals is
-.l47 for this model, indicating a low (near zero) as
well as negative correlation between the residuals.

Thus, it is relatively safe to assume that a recursive

 

model, without feedback, was structured and tested in
this study.

Linearity between the dependent and independent

 

variables also comes under examination. Lintest6 was
used to establish if the assumption of linearity was
grdssly violated in this recursive path model. The
outcome of this examination indicates that linearity was
not violated in this model. Two variables appear to

be slightly less linear than all the others. These are:

l) exterior construction materials when examined indi-

 

cates four of the 23 possible relationships are greater
than .20; in other words, 17.4 percent of this variable

appears non-linear; and 2) number of windows, which shows

 

ll of the 23 relationships greater than .20, or 47.8 per-

cent of the variable appears non-linear.

 

6Lintest is a test for linearity devised and pro-
grammed by Dr. Bernard Finifter. It is a test of the
difference between ETA (the measuae of non—linearity) and
R2 (the measure of variance) or E —R2, considered a rea-
sonable measure of the degree of conformity to or devia-
tion from linearity. It does not give indications of
the shape of relationships, if non-linearity is found.

151

Lintest was performed mainly to detect non-
linear relationships. Since no gross violation of
the assumed linearity was found, no further analysis

of the situation was done.

The Gross Analysis

 

Hypotheses III and IV are an indication of the
expected gross relationships to be found in the two
modelled dependent variables: 1) belief in the reality of
the energy problem; and 2) total direct energy consump-
tion in single family detached dwelling units, when
factors are aggregated into two categories: 1) family
socio-economic factors, and 2) physical housing factors.

The following, then, is a presentation and dis-
cussion of these findings.

Belief in the Reality
of the Energy Problem

 

Hypothesis III: Family socio—economic factors will
explain more of the variance than
housing physical factors for belief
in the reality of the energy problem.

 

152

Findings

TABLE 20.--Standardized Regression Coefficients, F-ratios,
Probability of Sampling Error and Multiple
Correlations of Two Independent Variables on
Belief in the Reality of the Energy Problem.

 

Belief in Energy Problem

Probability of
Sampling Error,

 

Independent Variables B F One Tailed Test
Physical housing factors .053 .446 >>.25
Family factors .661 69.29 <.lO
Overall F 35.5 <.0001

R2 = .653 df regression 2

R = .427 df re51dual 94

 

Discussion

 

The findings in Table 20, above, overwhelmingly
support Hypothesis III. Family factors are highly corre-
lated (B = .661) with belief in the energy problem when
compared to physical housing factors (8 = .053). This
finding has important implications for future public
policy and educational programming toward energy conser-
vation. It now appears that in order for "belief" to
have a more important impact on energy consumption
patterns, which in this study it does not have (B = —.095),
more must be done with family perceptions either through
social reform or economic disincentives. This will,be

discussed in a total perspective in Chapter VII.

153

Total Direct Energy
Consumption

 

 

Hypothesis IV: Housing physical factors will
explain more of the variance than
family socio-economic factors for
total direct energy consumption in
single family detached dwelling units.

 

Findings

TABLE 21.--Standardized Regression Coefficients, F—ratios,
Probability of Sampling Error and Multiple
Correlations of Two Independent Variables on
Energy Consumption in Single Family Detached
Dwelling Units.

 

Energy Consumption

Probability of
Sampling Error,

 

 

Independent Variables B F One Tailed Test
Physical housing factors .573 58.26 <.10
Family factors .310 17.05 <.10
Overall F 44.28 <.0001

R2 = .696 df regression 2

R = .485 df residual 94
Discussion

 

Hypothesis IV is also supported by the findings.
In this case housing physical factors are more highly
correlated with energy consumption (8 = .573),when mea-
sured in a gross sense,than family factors. However, it
should be noted that family socio—economic factors have

a respectable correlation with energy consumption (8 = .310).

154

Therefore, both physical housing factors and
family factors need to be given serious consideration
as determinants of energy consumption in single family

detached dwellings.

In Summary

 

It would appear from the findings generated and
discussed in this chapter, that the exercise of specify—
ing an input/output model of the determinants of energy
consumption in single family detached dwelling units
has merit. The amount of variance explained in belief
in the energy problem (42.7 percent) and energy consump-
tion (48.5 percent) is relatively high for this study's
subsample.7

This along with the substantial support for all
but Hypothesis II, Part 2, gives further evidence for
the meaningfulness of this model structuring endeavor.
Caution should, however, be raised as the detailed
accounting of the correlations between the "belief"
variable (Table 18) and energy consumption variable
(Table 19) with the selected set of independent variables
does reveal a number of low and non-significant correla-
tions, indicating that some variables have very little

meaning when accounting for the explained variance found

 

7For the population as aAwhole the shrinkage in
the variance ex lained would be R2 = .382 for the belief

variable, and R = .375 for the energy consumption vari-
able.

155

This can, however, become important only in future
refinements of the model as presented and tested in this
study. The findings given here lend themselves to
either: 1) structuring a more parsimonious model with
fewer variables, or 2) including yet unspecified other
variables which could help increase the level of vari-

ance explained, or 3) a combination of the two.

CHAPTER VII

SUMMARY, CONCLUSIONS
AND IMPLICATIONS

Summary Overview of the
Research Problem

 

 

In today's world, the combination of a
rapidly growing pOpulation, extraordinary
changes in income distribution, and a revolu-
tion in expectations has put most resources
under great pressure. Symptoms of this
situation are worldwide inflation, energy and
resource shortages, concern about pOpulation
growth and food supplies, and the movement
toward greater planning in the conservation
of natural resources. In the United States,
families are making complex adjustments to
changes in the economic environment and
to changes in the rules by which resources are
acquired and allocated (Zuiches, 1975b).

Families are inextricably linked to several exter-
nal environing systems, social and physical, natural and
man-made, near and distal. These linkages are identified
as the flow of matter/energy and information which the
family receives, processes and transforms in its day to
day living.

Energy dependency and the information upon which
families make decisions about energy use are the crucial
concerns of this research. Implicit in the objectives
and research problem undertaken here is a measure of the
openness and closedness of the family system both to

156

157

energy flows and information changes. In other words,
beyond testing the viability of a systems input/output
model, via examination of direction, strength, and
variance explained in the hypothesized relationships,
there is a covert agenda. This agendapalthough not
tested explicitly in the research,will be discussed as
a basically preliminary and speculative step beyond
the research findings toward an indication of boundary
maintainance in the family; that is, knowing the factors
that contribute to energy consumption in the place of
residence gives some very tentative indication of the
present state of the family system, its Openness or
closedness to both energy and informational inputs.

Systems Approach
and Analysis Mode

 

 

The approach taken in this research was essen-
tially systems analysis, which gives rise to both the
overt test of the hypothetical model and the covert
Speculations about its meaning. The system input/output
model of energy consumption in single family detached
dwelling units was based in systems theory (ecosystems,
cybernetics and general systems theory), using an adapted
human ecosystems model as the wholistic integrative
conceptual and analytical frame from which (through the

process of deduction) a subset of selected and specified

158

systems components was derived; i.e., the subset of
hypothetical socio-physical determinants of energy con-
sumption.

Path analysis based on multiple regression was
used as the method of analysis. This model was con-
sidered suitable for this research problem on theoreti-
cal and empirical grounds. A systems problem requires
systems analysis, thus the need for a structural mathe-
matical model indicating causal direction and linkages
justified the use of path analysis. The assumption of
a process system without feedback justified the adoption

of the recursive path model.

 

Need for Residential
Energy Research

 

 

The area of residential energy consumption was
considered a particularly rich territory for research
for these reasons: 1) the energy problem, although
seemingly less critical than during the crisis period
(Winter 1973-74) remains a problem; and 2) not much
research has been done (eSpecially from a wholistic
systems perspective) which lends insight into the deter-
minants of direct energy consumption in the place of

residence.

159

Conclusions

 

Testing a
Systems Model

 

 

Testing the viability of a systems input/output
model of energy consumption in single family detached
dwelling units was the major explicit objective of this
research. To this end four hypotheses were deve10ped
which examined both the net and gross determinants,
first, of belief in the reality of the energy problem,

. and second, of energy consumption (See Chapter IV, pages
99 and 100 for stated hypotheses).

The hypotheses were generated mainly as non—
random points of entry for the step-wise regression
process, rather than as formal hypotheses to be re-
jected on the basis of the findings. The important
aspect of this research is not so much what was hypothe-
sized but what was found based on some initial specula-
tion by the researcher. This research does not test
an established theory of residential energy consumption,
nor is it a replication of prior research. Therefore,
the direction and magnitude of relationships hypothe-
sized were based on the considered judgements of the
researcher. Thus, the shifting which occured in the
rank order of magnitude (Hypothesis I and II, Parts 2)
was more expected than surprising, and gives rise to some

interesting speculations.

160

The most critical aSpects of this research are
the findings themselves, indicating the direction
(positive or negative correlations) and the strength
(magnitude of the correlations) in the relationships
found and especially the amount of variance explained
by the modelled socio—physical variables hypothesized

as determinants of belief and of energy consumption.

Belief in the Reality of
the Energy Problem

 

 

Analytic Conclusions

 

Treating belief as a dependent variable, indi-
cates that 42.7 percent of the variance was explained
by the modelled factors.

The findings of the BEE analysis (Hypothesis
I) suggest that family educational attainment, is posi-
tively and substantially correlated with belief as
expected (8 = .361, p2 .001). This along with perceived
problems in electrical availability (8 = .315, p< .005)
and the reporting of yearly costs of energy consumption
(8 = .183 , p< .05), were the major factors affecting
belief in the energy problem. Other factors, with non-
significant correlation, also contributedtx>the variance
explained (Table 18, page 132).

The findings of the gross analysis (Hypothesis

III) of the belief variable (family factors vs. physical

161

housing factors), indicated a substantially higher corre-
lation between family factors and belief (B = .661), than
between physical housing factors and belief (B = .053).
Thus, the net and gross analysis of the determinants of
the belief variable support the notion that elements in,
or characteristics of, the family contributedixaagreed
belief in the reality of the energy problem.

In the analysis for the belief variable, Hypothe-
sis I, Part 1, was supported by the findings, all of the
directional signs between the relationships hypothesized
hold. Hypothesis I, Part 2 was substantially supported,
with only minor shifting in the rank ordering hypothe-
sized and further, Hypothesis III was supported by the
highly correlated significant relationships between

family factors and belief in the energy problem.

Speculative Conclusions

 

The families who believe in the reality of the
energy problem are relatively open family systems. They
have achieved higher educational attainment; they have
perceived problems in electrical availability (perhaps
from experiencing electrical brown-outs or black-outs);
they have consistently reported the total yearly cost
of energy supplied to their residence.

To say it more succinctly, they have used both

information about energy costs and availability,.and

162

experiences with energy shortages as inputs into the
formulation of what they believe. The important
immediate question is, does this belief, created by the
Openness of this family system to information and exper—
iences, become activated in a conservative use of energy?
The following analysis of energy consumption will in part
address this question.

Energy Consumption in Single
Family Detached Dwelling Units

 

 

Analytic Conclusions

 

Examination of the portion of the model treating
energy consumption as the variable dependent on seven-
teen independent variables, including the belief vari-
able, indicates that 48.5 percent of the variance in
energy use is explained. The 222 analysis (Hypothesis
II) provides some interesting shifting in the rank
ordering of magnitude while holding quite consistently
to the posited direction of relationships (two ex-
ceptions were noted). The shift in ordering indicates
that the size of the household (number of persons living
in the dwelling unit) is the most important factor con-
tributing to energy consumption (8 = .280, p< .001),
followed by number of major appliances (8 = .211, p< .01),
number of rooms in the dwelling (B = .173, p2 .25), num—

ber of doors to the exterior (B = .168, p< .05»

163

and number of rooms heated (B = .165, p< .25). These
factors along with insulation in ceiling (B = «.161,

p< .005) and rural location (B = -.127, p< .05) were the
major factors contributing most to the variance explained
in residential energy consumption. Other factors also
contributed, however, to a much less significant degree
(Table 19, page 139).

The rank order shifting away from-gross family
income and square feet of dwelling was somewhat sur-
prising, although when income was given further consider-
ation (speculation concerning its interdependency with
other variables included in the model and perhaps
some not included), this ranked finding was made more
understandable. Number of rooms in the dwelling also
appears interrelated with the measurement of dwelling
Space in square feet, thus making the number of rooms
in the dwelling a better overall predictor of dwelling
size. The belief variable was hypothesized to be last
in the rank ordering and negatively related to energy
consumption. The negative relationship holds but it is
of a low order magnitude (8 = -.095), although not
the lowest (several other variables contributed less to
the variance in energy consumption explained).

The grggg analysis of the findings on energy

consumption (Hypothesis IV) where physical housing

164

factors are hypothesized to contribute more to the vari-
ance explained than family factors, shows both factors
to be substantially correlated with energy consumption.
Physical housing factors are more highly correlated with
energy use (8 = .573, p< .10); however, family factors,
though somewhat less correlated with energy consumption
(8 = .310, p< .10), still have a substantial and, there-
fore, essential relationship to energy use. The gross
analysis of the findings simply indicates that both
factors are important considerations in the consumption
of total direct energy in the single family detached

dwelling unit.

Speculative Conclusions

 

Families are apparently unrestricted in their
Openness to energy inputs from the environment. In
other words, as long as supplies of energy (in whatever
form) exist without undue constraints (critical shortages
and severe price increases), families will continue to
expect to use and, therefOre, make demands on energy
supplies.

This study strongly suggests that it is the
number of persons in the household and their aggregate
demands on energy consuming appliances, plus certain
aSpects of the dwelling unit that make the difference

in the amount of energy consumed. The weak negative

165

correlation between belief in the reality of the energy
problem1 and energy consumption gives further evidence
that even the energy crisis (Winter 1973-74) with its
concomitant increased energy costs added little to deter
energy use.

Thus, in spite of the families’openness to infor-
mational inputs (awareness of and experiences with the
energy problem), which affect their belief in the pro-
blem, the evidence is not strong that belief affects
actions (behavior changes, life style changes) toward
reduced energy consumption.

Evidence that further underscores this statement was

revealed in a survey (The New York Times , July 2 , 1975) con-

 

ducted since this research, that indicates that residen-

tial electrical consumption is on the upswing (national

 

comparison of electrical usage for the first five months
of 1974-1975) and,that the conservation efforts were
weakening, "despite record high utility bills, wide
spread unemployment and recession" (Stuart, July 1975,
p. 45 and 51).

The family in its present state, as implied by

this study, is one of openness: open to information and

 

1Belief in the energy problem was hypothesized
to have a negative direction of relationship and a low
order of magnitude with energy consumption, indicating
that it was thought to deter energy consumption, but
within the time frame of the study it was postulated
not to have much effect on energy use.

166

and to energy input; i.e., families are open to external
environmental impacts without internal familial con-
constraints. The very Openness of the family system is
allowing it to receive mixed messages about the energy
problem, its reality, and the need, therefore, to change
behavior in response to the problem. There are mixed
messages in the societal environment about the real
nature Of the nation's energy supplies, reinforced by
the absence of a national energy policy, reports of out-
rageous profit taking by energy suppliers, while simul-
taneously receiving higher energy bills in spite of
attempts to conserve. It would appear that during the
period of this study and since, families have not
known how to interpret the conflicting messages they are
receiving from the environment, in order to adapt to the
changing circumstances (adaptive self—organization
toward a new dynamic steady state in relation to the
supplies of energy).

Families appear to be (at least in the short-
run) in an unstable state (negative entropic state)
vis a vis the energy and information environment; i.e.,
they continue to increase demands for energy supplies,
despite the decreasing finite supplies of fossil fuel

IGSOUI’CBS .

167

The second law of thermodynamics reveals that
decreased entropy (negative entrOpy) withinauxopen
system (the family in this case) is always offset by
the increase of entrOpy (positivewequilibrating entropy)
in its surroundings (the finite fossil fuel supplies in
this case) (Laszlo, 1974, p. 44).

This statement suggests that in the long-run
(period greater than the period during and since the
energy crisis), families through external environmental
realities (forcings) will come to terms with the energy
problem through internal constraints; i.e., they will
acquire new parameters (less BTU's of energy consumed)
in their steady states, if they continue to be sub-
jected to the actionxlfaphysical constant (decreasing
fossil fuels) in their environment.

This study of energy consumption within single
family dwelling units reveals short—term reactions to the
energy problem, which suggest either very little reac-
tion or no change in past habits and behavior patterns
concerning energy usage. This study does not indicate
an adaptive self-organizing state of the family toward
new systems parameters of energy use. Only in the long-
run (longitudinal study) will this information become

apparent.

168

Study Limitations

 

Prior to discussion of the implications of this
research some comments on the study limitations are

suggested.

Major Limitations

 

The most critical limitation of this study is its
cross-sectional nature (study at one point in time, T1).
A cross sectional study does not allow comparisons over
time (T1 compared to T2, T3 . . . TX). As the Specula—
tive conclusions indicated, only short—term family
system reactions to the energy problem were identified
and,those amounted to little or no reaction at all. The
empirical analysis supports this contention via the low
correlation between the two residual variables (-.147),
as well as the low standardized correlation between the
belief variable-and energy consumption (8 = -.095).

Said differently, the test of the input/output systems
model of energy consumption in single family detached
dwelling units, based on cross-sectional data, was basi-
cally recursive (as hypothesized), with little feedback.
The use of cross-sectional data did not detect changes in

the family in relation to the energy problem.

169

Other Limitations

 

Some of the hypothesized relationships between
the independent variables had low and non-significant
correlations with the belief variable and the energy
consumption variable. This may have been due to: l)
poorly selected variables, 2) poor measurement of the
variables, or 3) the small sample used in the research.
However, in structuring and testing a first hypothe-
sized approximation model (as this model was), findings
of this kind are generally expected.

The sample size was barely within the lower
limits for multiple regression and path analysis (N=97).
Most regression texts suggest a large sample size as
best for multiple regression, thus assuring reasonable
numbers in all cells. The affect Of the sample size
on this research is hard to detect, but it probably has
some effect on the correlation between variables
(suggested above) and may have given rise to some of the

residual, unexplained variance.

Other Variables

 

Variables not included in this study might very
well contribute to the explanation of the two dependent
variables used, belief and energy consumption. Specula-
tion about this notion would include measurement of
changing environmental factors such as climate (humidity,

temperature, and wind) and measurement of changes both

170

in the availability and costs of energy forms. Physical
housing variables which might have been included are:
orientation of the house, comparison between single
family and multiple dwellings, indicators of heating

and cooling equipment efficiency, measurement of dura-
tion and frequency of appliance usage, to name a few.

Family factors might have included measurement of

 

changes in employment status and in family composition,
indicators of feeling-states about the energy situation,
the social milieu, and about themselves as family mem-
bers and as individuals. Some of these variables could
be examined for their possible importance for belief,
and others for prediction of energy consumption.

From these limitations and the study conclusions,
some implications for future research, public policy and

educational programming will be discussed.

Implications

 

Future Research

 

The ability to make comparisons from time—series
(longitudinal) data is considered essential in future
research concerning family energy consumption. Compari—
sons between time periods would expand the capacity
to trace changes in family behavior patterns in relation
to energy consumption. To put it in systems terms, time—

series data would allow empirical testing (rather than

171

speculation, as here) for the Openness or closedness of
the family system either as it adapts through self—
stabilization (Cybernetics I, closed system, Laszlo,
1972, p. 38-39) or through self-organization (Cyberne-
tics II, Open system with internal constraints, Laszlo,
1972, p. 41—47) to changes in the energy and informa-
tion from.the environment.

Future research needs to be done to test the
validity and reliability of the measurements used within
this research. At the point when these were sufficiently
established, the model could be used for the purpose of

simulating family energy consumption patterns. Simula-

 

tion based on refinements in this model (using the best
measurements of the most powerful variables) would give
efficient and effective predictive capacity to para-
metric changes in the model having the most effect on

family residential energy consumption.

Public Policy

 

The findings of this study indicate that, al-
though families are receiving messages about the energy
problem, they are not changing behavior in response to
the messages. This raises serious questions about the
ability of families to move voluntarily toward energy
conservation. During the energy crisis period (especial-

ly during the Arab oil embargo), when uncertainty about

172

fuel supplies was prevalent, an ethic of conservation

seemed to appear. The New York Times study called it "a

 

patriotic effort to reduce energy consumption" (1975);
Warren called it "evidence of the Protestant ethic"
(1974). However, since fuel supplies have become less
problematic, the efforts to conserve have dissipated,
despite increased energy costs. The implication here
is that private energy policies (familial internal
controls) are nOt working; therefore, public policy may
have to fill the voluntary conservation gap. Zuiches
reports on the acceptability of specific energy related
policies (data from the present pilot project), which
encompassed a wide range of voluntaristic policies as
well as policies requiring government intervention. In
general, Zuiches found that the more voluntary policies
received greater support (larger percentages of accep-
tance) than those requiring governmental restrictions
(draft of a paper, April, 1975a). Families, it appears,
do not support government controls over energy consump-
tion and yet the evidence from this research indicates
families are not controlling, through voluntary means,
their use of energy. This situation has its parallel
in Hardin's "Tragedy of the Commons" where he postulates
that "Each man (family in this case) is locked into a

system that compels him to increase his herd (in this

173

case energy consumption) without limit -- in a world that
is limited" (Hardin, 1968). Further, Hardin states

that "Ruin is the distinction toward which all men rush,
each pursuing his own best interest in a society that
believes in the freedom of the commons. Freedom in a
commons brings ruins to all" (1968, p. 1244). Although

a dire commentary, it nonetheless points out the necessity
for a sound public energy policy which will be acceptable
to residential energy consumers.

A sound public energy policy would not through
drastic, coercive means (quotas, rationing, and other
restrictive rules and regulations) turn energy consump-
tion patterns toward more conservative usages in a short,
disruptive period of time, but would, rather, ease the
residential consumer over a reasonable period of time
into using less energy in the dwelling unit. One of the
less restrictive and more palatable means of achieving
this goal would be through a public policy of energy

education (D. Morrison, 1975a).

Educational Programming

 

"Education can counteract that natural tendency
to do the wrong thing, but the inexorable succession of
generations requires that the basis of knowledge be con-

stantly refreshed" (Hardin, 1968, p. 1245).

174

Educational institutions are middle range in-
stitutions which operate between strict governmental
intervention and pure voluntaristic behavior. An energy
education policy which incorporated in its purview
the major residential energy consumers (the families
who pay the energy bills) as well as future energy con-
sumers would, given enough economic resources and time,
re-socialize the energy consumer away from the ethic of
rising expectations for energy consumption, toward a
more conservative ethic. Thus, a crucial implication
of this research is that more education about the Eggts
of the energy problem (both in the short run and over
time) would strengthen the belief in the reality of the
energy problem, thereby, increasing the probability of
incorporating the value of energy conservation not only
as an ethic, but also as an active reality.

A system that decreases entropy gathers informa-

tion (Laszlo, 1972, p. 44).

APPENDICES

175

APPENDIX A

Glossary of Terms

176

Glossary of Terms

 

Abstract System: a pattern system whose elements consist
of signs or concepts (Kuhn, 1974, p. 483).

 

Acting System (Action or Behaving) Systems: is a pattern
two or more elements of which interact (Kuhn, 1974,
p. 484).

 

Adaptation (Adaptive Behavior): behavior that in some ways
changes the relation of a system to its environment
(supersystem) or its internal components (subsystem),
either by alternating itself, the environment or
both (Kuhn, 1974, p. 484).

 

Behavioral System (Human): the system of the human that
selects the behavioral outputs and guides their
execution -- a control system in contrast to a main-
tainance system (Kuhn, 1974, p. 485).

 

In Individual the nervous system and associated
organs; i.e., eyes, ears that decode information
from its environment (Kuhn, 1974, p. 485).

 

In Society the social institution which Bernard calls
the composite or derivation control environments"
(1925, p. 325), which have been "organized around or
defined in terms of problems or ways of looking at
things or of making adjustments of man to his en-
vironment" (1925, p. 329) -- they are more in the
nature of institutions such as this non-exhaustive
list: economic, political, educational, aesthetic,
ethical, etc. (1925, p. 330).

Biological System (Human): the biological entity of the
individual human bounded by skin, hair, nails and
the like —— a maintainance rather than a control
system (Kuhn, 1974, p. 486).

 

Boundaries (of an Interaction): an interaction is bounded
analytically by specifying the systems involved,
and the time duration (Kuhn, 1974, p. 486).

 

Boundaries (of a System): logically the boundaries of a
system are defined by listing all the components of
the system; any elements not lIEEed are construed
as falling outside the system (Kuhn, 1974, p. 486).

 

177

178

Closed System: a system in which interactions occur only
among components of the system; i.e., there are ng
inputs from or outputs to the environment (Kuhn,
1974, p. 486). Closed systems in absolute terms
"do not exchange energy or information with any
body outside itself, although it may experience all
kinds of internal change. That is, the system is
completely isolated" (Parsegian, 1973, p. 28).
However, most would agree that "there is no such
thing as a completely closed system" (1973, p. 28).
The term closed system is used in a relativistic
sense to mean:

 

l) a very limited system that performs functions
without variation, or

2) a system in which the energy (information or
material) that is exchanged with the environment
can be identified and measured (1973, p. 28).

Closed Human System: a system which filters but cannot
reject energy and other inputs (Vaines, 1974, p. XV).

 

Controlled System (Cybernetic System): any acting system
whose components and their Interactions remain at
least within some specified range or return it to
within that range if the variable goes beyond it,
despite changes in forces that influence the state
or level of that variable (Kuhn, 1974, p. 489).

The success of a controlled system is the ability

to "hold the variable within acceptable departures
from the desired value" (Parsegian, 1973, p. 61).

A controlled system can also be defined as a goal-
oriented system. It must have identifiable detector
(also called sensory), selector (also referred to

as comparator), effector (also called generator)
subsystems (Kuhn, 1974, p. 45-54).

 

Cybernetics: the study of controlled systems.

 

Ecological System (Ecosystem): an uncontrolled system,
some of whose components subsystems are controlled,
namely, organisms. The ecological system is de-
fined precisely by the set of assumptions that con-
stitute the model of it (Kuhn, 1974, p. 491).

 

Energy: is the vitality of all living systems. It is the
capacity to do work or the powers to adapt, change
or maintain the system. The sun is the ultimate
source of energy.

179

Entropy: in the opposite of pattern and order; it is in
effect randomness, disorders, chaos; i.e., loss of
‘organization.

negentropy: is a system in a state of elaborating
structure, or a gain in organization and complexity.

 

 

Environment: anything outside the boundaries of a defined
system.

near environment are conditions having proximity to
the organism, thus having a more immediate effect.

 

distal environment are conditions either more dis-
tant Spatially or more abstract in concept, thus
having less immediate effect.

 

Eguifinality: the principle that: in a closed system the
final state of the system is unequivocally deter-
mined by the initial condition Of the system. In
an gpen system a given final state may be reached
from different initial conditions and by different
ways (Buckley, 1967, p. 60).

 

 

 

Equilibrium: a defined point or stated set of limited
parameters which tends to be maintained.

 

static equilibrium: a situation in which the forces
acting on or exerted by all components in an acting
system have come to a state of rest and no further
changes take place.

 

dynamic (steady~state) equilibrium: a situation in
which components of an acting system or their states
continue to move or change but are balanced so that
at least one variable remains within some Specified
range (Kuhn, 1974, p. 491).

 

DSE: a convenient reference for detector, selector and
effector system (Kuhn, 1974, p. 491).

detector (of a controlled system): the function by
which a system acquires information about its
environment (Kuhn, 1974, p. 490).

 

selector (of a controlled system): the function of
selecting a response to a given environmental
state (Kuhn, 1974, p. 505).

effector (of a controlled system): the function of
executing the behavior selected by the selector
(Kuhn, 1974, p. 491).

 

 

180

Fami1y_(as Organism): it is a system of individual organ-
isms, that is a complex organization with a history
and rules (Vaines, 1974, p. xxi).

 

gpen family system: it is an identified unit of inter-
acting organismSflwho have a common theme and goals,
having a commitment over time, and share resources
and living space" (Hook and Paolucci, 1970, p. 316).
This family system also processes energy/matter and
information from the environment in the course of

day to day living.

 

I

closed family system: a small, complex (if children
are involved), multipurpose, cooperative organiza-
tion with such dominant functions as procreation and
sexual relationships, child-rearing, mutual assis-
tance, and care of basic biological needs of its
members (Kuhn, 1974, p. 493).

 

Feedback: a mutual interaction between a system A and
some element in its environment B such that an
action by A on B produces a return action by B on
A (Kuhn, 1974, p. 493).

A“ ? B = a non-recursive system.
A——-)B = a recursive system.

negative (equilibrating) feedback: an oppositely
paired mutual interaction. The result is if A
changes from some initial state its action back on
itself through B moves it back toward, if not pre—
cisely to its initial state. Negative feedback is
also known as deviation-correcting (Kuhn, 1974,

p. 28).

pgsitive (nonequilibrating) feedback: a similarly
(not oppositely) paired mutual interaction. The
result is if A changes from some initial state its
action back on itself through B is to move it even
further from the initial state. This relationship
is known variously as self-aggravating, deviation-
amplifying, explosive (if the initial changes is
upward), or shrinking or decaying (if the initial
changes are downward) (Kuhn, 1974, p. 28).

 

 

Flow: the movement of matter/energy or information across
the boundaries of a system or across an arbitrary
boundary within it (Kuhn, 1974, p. 493).

 

Hierarchy of Systems: any relations between systems in
whiCh one is a subsystem or supersystem relative
to another system (Kuhn, 1974, p. 495).

 

181

Homeostasis: a condition in which a controlled system suc-
cessfully maintains a steady state equilibrium of
one or more system variables (Kuhn, 1974, p. 495).

 

Information (Contained): a system is said to contain or
possess information about its environment when some
state or pattern within it is functionally related,
as a dependent variable, to some state or pattern
in its environment (Kuhn, 1974, p. 496).

 

Input: any movement of matter/energy or information from
the environment across the boundaries into an acting
system (Kuhn, 1974, p. 496).

Interaction: reciprocal action, A acts on B, and in turn
AB acts on A.

 

Interdependence: mutual dependency (Vaines, 1974, p. xxvi).

 

Interface: a point of contact between two or more systems;
i.e., the interpenetration of boundaries -- one
system with the other (Vaines, 1974, p. xxvi).

 

Linkages: in this study linkages are the paths connecting
the independent input variables with the output
dependent variables. The measure of which is the
strength of the relationship (8).

Morphogenesis: refers to those processes which tend to
elaborate or change a systems given form, structure
or state. Biological evolution, learning and
societal development are examples (Buckley, 1967,
pp. 58-59).

 

Morphostatic: refers to those processes in complex
system-environment exchanges that tend to preserve
or maintain a system's given form, organization,
or state -- self regulation, homeostatic processes
of organism, customs, rituals and traditions in
cultural are examples (Buckley, 1967, p. 58).

 

Multifinalipy: refers to similar initial conditions which
may lead to dissimilar end-states -- a morphogenetic
process (Buckley, 1967, p. 60).

 

Parameter (of a System): any trait of a system that is
relevant to a particular analysis but does not
change during the course of the analysis (Kuhn,
1974, p. 501).

 

182

parameter (of a system's environment): any trait of a
system's environment that is relevant to a particular
‘analysis but does not change during the course of
analysis (Kuhn, 1974, p. 501).

 

Open System: a system that receives inputs from or pro-
duces outputs to its environment; i.e., it is
influenced by and influences its environment (Kuhn,
1974, p. 500).

 

Output: any movement of information or matter/energy from
any acting system across its boundaries to the
environment (Kuhn, 1974, p. 501).

State (of a System or Systems State): a condition of some
system variable, such asiits temperature, color,
rate of flow, magnitude, physical location, chemical
composition, degree of excitation, on-or offness, or
amount or type of information processed (Kuhn, 1974,
p. 25).

 

Steady State: the dynamic behavior of a system over time,
in which there are free exchanges of energy/matter
and/or information in response to the external
systems state (Kuhn, 1974, p. 491).

 

Structure: the pattern of an organization described in
terms of its subsystems and their roles (Kuhn, 1974,
p. 507).

 

Subsystem: a system that is a component of some larger
system (Kuhn, 1974, p. 507).

 

Supersystem (suprasystem): a larger system of which a
given system is a component (Kuhn, 1974, p. 508).

 

System: any pattern whose elements are related in a
sufficiently regular way to justify attention (Kuhn,
1974, p. 508).

Uncontrolled System: any acting system that does not fill
the definitiOn of a controlled system; i.e., it has
no goal, no variables are maintained within a given
range. No specific equilibrium (Kuhn, 1974, p. 509).

 

183

Systems Sybernetics I (Self—Regulation): stable equilib-
rium in systems; i.e., the capacity for self-
regulation by compensating for changing conditions
in the environment through coordinated changes in
the system's internal variables

 

- self-stabilization

- adaptive self—stabilization (Laszlo, 1972, p. 39).

Systems Cybernetics II (Adaptive Self-Organization): the
dynamics of the system itself and the action of
evolutionary forces on pOpulationS of such systems
produce structure, merges some subsystems, sub—
divides others, reduces total interaction on some
parts, gives spontaneous activity, organizes hier-
archy, and transforms discrete systems and fields
into each other (Levins, in Laszlo, 1972, p. 43).

 

APPENDIX B

Major Variable Groups to be Assessed
in the Pilot Study

 

 

184

A.

185

Major Variable Groups to be Assessed
in the Pilot Study

 

 

Present family socio-economic status
A.l. Total family income according to source
A.l. Income of each family member
A.2. Occupation and employment status of each
family member, including type of work,
industry, hours, wage, rate, length of
job tenure

A.3. Educational attainment of each family
member

A.4. Housing value

A.5. Family net worth, assets, obligations,

insurance

Family resource status

B.l. Housing structure described as to type of struc-
ture, number of units in structure, number of
stories, size and location of each window,
dimensions of rooms and attic. Types of rooms.
Construction material; extent and location of
insulation; type and Size of home heating/
cooling systems, type of fuel used; types and
sizes of major energy consuming appliances

B.2. TranSportation resources ~- number, size, age
and fuel consumption of family vehicles

8.3. Nutritional status of family members

Family energy use

C.l. Consumption of energy in the household, measured
by meter reading and utility records; fuel/
electricity/water

2. Costs of energy consumption measured in C.l

.3. Transportation expenditures -- fuels and other

4. Transportation patterns -— distance, frequency,
intensity of vehicle use

.5. Food consumption patterns, food consumption costs

Present household structure

D.l. Family size

D.2. Household size

D.3. Ages

D.4. Race

D.5. Religious preference

D.6. Political preference

D 7. Family life cycle/family formation

MMMMMMMM

1
2
3
.4
5
6
7

186

amily functioning

Self

Roles/inter-familial relations
Kinship/input-output dependency
Community/society -- social alienation
Division of labor

Decision making

Present state of family functioning:
High/Medium/Low

amily knowledge/definition of situation
1

Knowledge of energy crisiS/shortages-increased
costs

Belief in energy crisis/short-term/long-term
Knowledge of energy consumption costs and
amounts

Nutritional knowledge

Knowledge of transportation costs

Knowledge of alternate tranSportation forms
Environment sensitivity/belief in fixed nature
of resources

a ily expectations/values

F m
G l
G 2
6.3.
G 4
G 5
G 6

housing expectations/changes/improvements
family size eXpectations

tranSportation expectations

appliance purchase expectations

family income expectations

family food consumption expectations

Future
Future
Future
Future
Future
Future

Changes in energy/resource consumption

H.1.

Willingness to change energy and resource con-
sumption (household)

Energy conservation practices/heating/electri-
cal (household)

Willingness to change transportation patterns
Changes in transportation patterns/use/distance/
speed/type

Changes in food consumption patterns

APPENDIX C

Tables of Total Lansing SMSA
Families and Pilot Study
Sample Families

 

 

 

187

188

TABLE 22.--Family by Type, Total Lansing SMSA Families,
Pilot Study Sample Families.

 

 

Total POpulation Pilot Study
LANSING, SMSA Sample: Lansing,
1970 Census SMSA
Family Type Number Percent Number Percent
Husband-Wife
(with children) 47,351 (52.8) 138 (63.6)
Husband-Wife
(without children) 36,474 (40.7) 59 (27.2)
Female Heads
(with children) 4,815 (5.4) 19 (8.8)
Male Heads
(no wife-with
children) 970 (1.1) l (0.5)
TOTAL 89,610 (100.0) 217 (100.0)

 

Source: Lansing, SMSA data calculated from Table 156,
Detailed Characteristic, Michigan, U.S. Dept.
of Commerce, U.S. Census of POpulation, 1970,
p. 747.

 

189

TABLE 23.--Educational Attainment, Total Families Lansing
SMSA, Pilot Study Sample Families.

 

 

Total POpulation: .Pilot Study
Families Lansing Sample: Families
Years of SMSA LanSIng SMSA
School Completed Number Percent Number Percent
0-8 years
(elementary school
& junior high) 15,920 (17.8) 87 (21.2)
9—11 years
(partial high
school) 16,431 (18.3)
12 years
(high school
completed) 29,671 (33.1) 158 (38.4)
l-3 years college 12,074 (13.5) 78 (19.0)
4 years or more
(college graduate
& professional
training) 15,514 (17.3 88 (21.4)
TOTAL 89,610 (100.0) 411 (100.0)

 

fl

Source: Families by type and composition, Education and
Labor Force Participation of Head and Wife.
Table 158, Detailed Characteristics, Michigan,
U.S. Dept. of Commerce, Bureau of the Census,
1970, pp. 24-753.

190

TABLE 24.--A Comparison of Occupational Characteristics
by Sex, Total Lansing SMSAl and Sample
Families.

 

Total Population Em— Pilot Study

 

ployed, 16 years or Sample: Lansing
over, Lansing SMSA SMSA
Occupational Males Females Males Females
Categories % % % %
Professional 17.3 17.3 20.7 16.3
Managerial 9.6 2.9 10.9 4.7
Clerical & Sales 13.6 48.6 10.9 33.5
Blue-Collar 47.0 10.7 56.0 11.2
Service Workers,
Household, and
Farm Labor 12.5 20.5 1.5 34.3
TOTAL 100.0 100.0 100.0 100.0
(N) 91,823 57,608 193 215

 

lSource: Labor Force Characteristics of Population, 1970,

Table P—3.

U.S. Dept. of Commerce,
1970, p. P~21.

Census Tracts, Lansing, Michigan,

Bureau of the Census

191

TABLE 25,4-Income Characteristics, Total Families Lansing
SMSA, Pilot Study Sample Families.

 

 

gotaiTopglation:l PilotlStudy
. ami 1es an51n ami ies
. g
1973) Number Percent Number Percent
Less than $4,999 . 11,814 (13.2) 17 (8.0)
$5,000 to $9,999 25,235 (28.2) 43 (20.5)
$10,000 to $14,999 28,358 (31.6) 65 (31.9)
$15,000 to $24,999 19,716 (22.0) 56 (26.7)
$25,000 or more 4,487 (5.0) 28 (13.3)
TOTAL FAMILIES 89,610 (100.0) 210 (100.0)
Median Income $11,213 $13,425

 

1Source: Income Characteristics of the POpulation: 1970,
Table P-4, Census Tracts, Lansing, Michigan,
U.S. Dept. of Commerce Bureau of the Census,
1970, p. P-31.

192

TABLE 26.--Marita1 Status by Sex and Age, Total Lansing
SMSA, Pilot Study Sample.

 

 

Total Po ulation Pilot Study Sam—
Married: Lansing ple: Lansing
SMSA, 1970 Census SMSA
Age Male Female Male Female
Categories # % # % # % # %
under 18
years 107 ( 0.1) 405 (.005) —- -- -— _-

18-29 yrs. 21242 (25.6) 26869 (31.9) 58 (29.7) 72 (34.1)
30-44 yrs. 26758 (32.2) 26725 (31.7) 70 (35.1) 77 (36.5)

45-64 yrs. 26680 (32.1) 24764 (29.4) 56 (28.7) 53 (25.0)

65 yrs. &

over 8268 (10.0) 5533 (7.0) 11 (5.6) 9 (4.0)
TOTALS 83055(100.0) 84296(100.0) 195 (99.9)211(100.0)
1

 

Source: Lansing SMSA data calculated from Table 152,
Detailed Characteristics Michigan, U.S. Dept.
of Commerce, U.S. Census of Population, 1970,
p. 728.

193

TABLE 27.--Housing Structural Types, Total Lansing SMSA,
Pilot Study Sample.

 

 

. Total POpulationl Pilot Sample:

Hou51ng Structural . .
Types, Units in LanSTng, SMSA LanSing, SMSA
Structure Number Percent Number Percent
1 (including mobile

homes) 88,219 (76.0) 175 (80.6)
2 7,689 (7.0) 10 (5.0)
3 and 4 4,202 (4.0) 2 (1.0)
5 or more 15,676 (13.0) 30 (13.8)
TOTAL 115,786 (100.0) 217 (100.0)

 

lSource: Structural, Equipment, and Financial Character-

istics of Housing Units: 1970, Table H-2, Census
Tracts, Lansing, Michigan, U.S. Dept. of Commerce,
Bureau of Census, 1970, p. P-ll.

 

194

TABLE 28.--Housing Tenure, Total Lansing SMSA, Pilot
Study Sample.

 

 

Total POpulation1 Pilot Study
-Lansing, SMSA Sample: Lansing,
1970 Census SMSA

Housing Tenure Number Percent Number Percent
Owner Occupied 77,135 (66.6) 147 (67.7)
Renter Occupied 33,390 (28.8) 70 (32.3)
Vacant 5,264 (5.0) -- --
TOTAL 115,789 (100.0) 217 y (100.0)

 

lSource: Occupancy, Utilization and Financial Character-

istics of Housing, 1970 Census Tracts, Lansing,
Michigan, U.S. Dept. of Commerce, Bureau of
the Census, 1970, p. H-l.

APPENDIX D

Operational Variables and

 

Parts of Questionnaires

 

195

196

Operational Variables

 

Variables

Where Found

 

2.21 - Total square feet

(including basement)

2.22 - Presence or absence of insula-

tion recorded

Code - Ceiling pres. =
abs. =

Walls pres. =

abs. =

Floors pres. =

abs. =

Ol—‘OHOH

2.23 - Number of floor levels
Coded l-99 (actually levels)

2.24 - Number of rooms

Coded 1-99 (actually # of rooms)
2.25 - Number of rooms heated
Coded 1-99 (actual rooms heated)

2.26 - Number of rooms air conditioned q

Coded 1-99 (actual
2.27 - Total number
Coded 1—99 (actual
2.28 - Total number
Coded 1-99 (actual

#)

#)

2.29 - Type of exterior construction

material
Coded
01 = Wood
02 = Stone
03 = Brick
04 = Cement Block
05 = Stucco
06 = Combination of

several above

07 = Wood & Brick

08 = Brick & Aluminum
siding

09 = Metal (Mobile Home

10 = Stone & Aluminum

siding

)

rooms a.c.).

of windows

11
12
13
14
15

16
17
18
19
20

of doors to exterior q

Tax records

Housing facili-
ties.& Utilities

q 1.7

q 1.1 & 1.2

Environmental
evaluation, q 4

Aluminum siding

Wood & Aluminum siding
Brick & Stone

Siding (UNSP)

Brick, Cement Block &
Siding

Wood; Asphalt Brick Look
Brick & Siding

Shingle

Wood, Brick & Siding
Wood, Aluminum & Siding

197

O

 

Variables Where Found
2.30 — Number of Major Appliances H F & U, q 12
Coded
1. Electric Stove with surface
burners

2. Gas stove with surface burners
3. Self—cleaning electric oven
4. Electric oven

5. Gas oven

6. Dishwasher

7.

Micro—wave oven
8. Color television
9. Black & white television
10. Washing machine
11. Electric clothes dryer
12. Gas clOthes dryer
13. Electric Space heater
14. Humidifier (winter)
15. Dehumidifier
16. Room air conditioner (summer)
17. Central air conditioning (summer)
18. Self-defrosting electric refrigerator
19. Electric Refrigerator (without defrost)
20. Gas Refrigerator
21. Self defrost home freezer
22. Home Freezer (without defrost)
23. Electric water heater
24. Gas water heater

Recoded
— if household has = 1
- if household does not have = 0

Recoded
- Summed the 1's
2.31 — Location of Dwelling Housen File
rural = l Var. .001
urban = 0
3.21.2 - Number of Persons Living
in dwelling Var. 343
Raw Count of Persons
3.21.2 - Family Life Cycle Var. 344
Recoded

Young families without children = 1

Families with children under twelve = 2
Families with children at home over twelve = 3
Older families without children = 4

198

Variables Where Found

 

Housen File
Var. 305 & 317

3.22.1 — Educational Attainment

Mean husband & wife scores
3.22.3 - Gross Family Income (1973) Confidential Report

q.5
Coded
a) Under $2,000
b) $2,000 - $2,999
c) $3,000 - $3,999
d) $4,000 $4,999
e) $5,000 $5,999
f) $6,000 $6,999
9) $7,000 $7,999
h) $8,000 $8,999
i) $9,000 $9,999
j) $10,000 - $10,999
k) $11,000 $11,999
1) $12,000 $12,999
m) $13,000 $13,999
n) $14,000 $14,999
0) $15,000 $15,999
p) $16,000 $17,999
q) $18,000 $20,999
r) $21,000 $24,999
5) $25,000 $29,999
t) $30,000 — $49,999
u) $50,000 and above
3.22.3 - Housing Tenure Card 50
Owner = 1

Renter = 0
3.23.1 - Belief Variable

Do you believe that the energy
problem is real? (Check ( ) one).

Energy Questionnaire
q.2

 

1 Yes

2 Yes, but will be solved by the
recent end of the Arab Embargo.

3 No

4 No, but there might be in the
near future.

5 NO, but there might be in the

distant future.

199

Variables Where Found

 

These five responses were reordered
to accomplish a continuum.

yes
Yes, but. . . end to Arab Embargo
No, but in the near future

No, but in the distant future

NO

UluwaH
II II II II II

These were further recoded to:

l and 2 = 2
3-4—5 = 1

Then the Husbands (Var. 066) and the
Wives (Var. 005) responses were
summed in this fashion within the
family as unit of analysis criteria:

If both agree, yes = 4
If they disagree = 3
If both agree, no = 2

3.23.2 Perceived Cost of Energy Housing Facilities
& Utilities q.5
Total for 1973

*1. Electricity 5. Sewage
*2. Natural Gas 6. L.P. Gas

 

3. Garbage 7. Butane
4. Water *8. Fuel Oil
$ (3 columns)

 

Codes: Specify number of dollars
nearest whole dollar: If exactly
half (e.g. 50¢) round to the
nearest even dollar.

For example:

010 = $10.25

011 = $10.75

010 = $10.50

012 = $11.50

000 = Not Applicable. If N A, code
the next 4 columns 0000.

Blank = missing data (code only if

while section is skipped).

200

Variables Where Found

 

* Only these categories were used
in the study.~

Recoded to:
if they reported total
1973 costs = 1

if they did not report = 0

3.23.2 — Perceived Availability of
Energy by Type (Husband/ Energy Questionnaire
Wife) q.3

To what extent has each of the
following been a problem for the
peOple of Michigan, since the Fall
of 1973? (check ( ) 933 on each
line)

*1. A shortage of gas for cars.

2. A Shortage of electricity.

3. A shortage of natural gas for home
heating.

*4. A shortage of coal for home heating

5. A shortage of fuel oil for home

heating.
Coded: 1 = very great extent
2 = great problem
3 = some problem
4 = slight problem
5 = no problem at all

Recoded: very great problem
great problem 2
some problem
slight problem

1

no problem at all

Then the husbands (Vars. 068, 069, 071)
and wives (Vars. 007, 008, 010) were
summed in the following fashion within
the family as unit of analysis criteria.

Recoded:

if both agree (2) to problem = 2
if they disagree = 1
if both agree (1) no problem = 0

 

'iin this transformation of data both number 1 and number 4
were deleted as not being relevant to this study.

201

Variables Where Found

 

4.11 - Total Amount of Energy
(BTU's) Consumed in
Single Family Detached
Dwellings.

Total direct residential energy
consumption.—- is the summed amount of
energy consumed, measured in British
Thermal Units (hereafter BTU's) in the
place of residence depending on house-
hold mix. Each source of energy for
each residence in this study was iden-
tified (a mixture of electricity and
natural gas or electricity and fuel
oil) using data supplied by utility and
Oil companies. These data were received
from the companies in the Standard units
of energy measurement; i.e., cubic feet
of natural gas, kilowatt hours of elec-
tricity, gallons of fuel oil. Each
type of energy was then summed for a
twelve month period (June 1973 to May
1974) and then converted to BTU's. Once
the conversion to BTU's for each energy
source was accomplished they were simply
added together, depending on household
mix, to gain the total amount of energy
consumed per residential unit. The
measurements conversion included in this
study are as follows:

 

 

1 cubic foot of natural gas = 1,031 BTU's
l kilowatt hour of electricity = 3,413 BTU's

1 gallon of fuel Oil - 130,000 BTU's

A British Thermal Unit (BTU) is the
amount of energy needed to increase the
temperature of one pound of water one
farenheit degree.

 

ENERGY

INSTRUCTIONS: Please read all questions carefully and check (V) answers you believe to be right for you.
(There is no right answer.)

1. No doubt you have heard of the "energy crisis"; when did you grit hear about it? (check (V) one)

less than 6 months ago

 

about 6 months ago

 

about 1 year ago
about 2 years ago

PPS-01°"

over 2 years ago

2. Do you believe that the energy problem is real? (check (V) SE.)

yes

yes, but it will be solved by the recent end of the Arab Embargo
no

no, but there might be in the near future

no, but there might be in the distant future

P‘PPN.‘

3. To what extent has each of the following been a problem for the people of Michigan, since the Fall of
1973? (check (7’) 2g; on each line)

Very Great Great Some Slight NO Problem
Problem Problem Problem Problem At All

1. A shortage of gas
for cars

2. A shortage of
electricity __ __ __ __

3. A shortage of
natural gas for
home heating

4. A shortage of
coal for home
heating __ __ __ — —_

5. A shortage of
fuel oil for
home heating

4. How wide spread is the energy problem? (check (V) 9_n_e)

the whole world

 

the Western nations only
the United States only
the larger cities in the United States

 

P‘PS‘N.‘

other

(specify)
2 0 2

‘ MSU/May 1974

HOUSING FACILITIES AND UTILITIES

(for both owners and renters)

The following questions have to do with this particular dwelling, its space, size

the questions below as exactly as you can.

1. How many rooms are in this dwelling, not counting
bathrooms?

2. How many bathrooms?

3. How many bedrooms?

4. How many rooms are used for sleeping?

5. How many rooms are actually heated?

6. How many rooms are actually air-conditioned?

7. How many floor levels in this dwelling? (including
basements if used as living or play space. Also,
number of floors if this is an apartment building)

8. How many doors inside the dwelling?

9. How many doors to the outside of the dwelling?

 

10. How many windows in the dwelling?

Is this place insulated? (check (sf) ALL that apply)

1. in the ceiling?
2. in the walls?

under the floors, if no basement?

No.

No.

No.

No.

No.

 

No.

 

No.

No.

No.

 

and utilities. Please answer

of rooms

of bathrooms

of bedrooms

of rooms

of rooms

of rooms

of floors

of doors

of doors

of window:

How is this place heated? (check (V) ALL answers that apply to your dwelling place)

Portable heaters

 

Fixed space heaters

 

Baseboard heaters (electric)
Central furnace
Wood stove

Baseboard heaters (hot water)

 

 

9’9‘PP’N?

 

What type of energy is used to heat this place? (check (V) ALL answers that apply according to the type of

heating used)

Wood

Coal

Fuel Oil

Bottle Gas L.P.
Butane

 

 

l

 

 

Natural Gas

 

$9999.”?

Electricity

 

203

MSU/MAy 1974

For each utility in your home you receive a bill. We would like you to report the amount you paid for the
last billing period and tell us if it was by the month, by the quarter, by the season. (If by the month, please
give the amount you paid for February 1974.)

4

(EXCEPTION: For renters who have some utilities included in rent payment
give only dollar amounts for the utilities you pay.)

 

 

 

 

Bythe By the By the Total For
Month Quarter Season 1973 *See Below
(Feb. 1974)

1. Electricity S per __ __ S

2. Natural Gas S per __ S

3. Garbage S per __ __ 3

4. Water S per _______ __ __ S

5. Sewage S per __ S

6. L.P. Gas S per __ S

7. Butane S per __ S

8. Fuel Oil $ per __ $

 

*NOTE: (If you do not have your receipt stubs available, please try to estimate as closely as possible.)

Do you have a budget plan for fuel purchases? (check (VI one)
No, if no, go to question 7.

Yes, if yes, answer question A and B

A. What is your monthly payment on this plan? S

 

B. Total paid in 1973 on this plan? 3

 

Do you have a way to control the temperature in your place? (check (V) one

No, if no, answer questions 8, 9 and 10.
Yes, if yes, answer questions A and B, and skip to question 11.

A. What method do you have to control the temperature? (check (V) we answer that applies)

 

 

 

 

 

 

1. thermostat control
2. turning on and off radiators
3. turning on and off built-in space heaters
4. __other
(what?)
8. About what temperature have you and your family kept this place? (give approximate degrees)
Winter 1974 Winter 1973
Daytime .. degrees degrees
Nighttime degrees degrees

 

 

Go to Question 11.

204

12. Part of the energy used in the home comes from the use of individual appliances. How many, what age and how many times
r week are your family's appliances used?

 

INSTRUCTIONS: In the two spaces to the left of the appliance listed, please give:
(1) the number of each appliance your family has (0 if none, 1, 2, 3 etc.)
(2) the a_g_e_ approximately of each (model year or year of purchase)
In the spaces to the right of the appliance listed, please:
(1) check (V). the number of hours approximately the appliance is used per week.

 

 

 

Number of Age of Les than 1—4 5—10 11-50 51-100
each each one hour hours hours hours hours All the
per week per week per week per week per week time

_. Electric stove with surface
burners _

Gas stove with surface burners

Self-clearning electric oven

 

Electric oven

1

Gas oven
__ Dishwasher
Micro-wave oven
Color television

Black 8: white television

Washing machine

 

Electric clothes dryer

 

Gas clothes dryer

Electric space heater

Humidifier (winter)

Dehumidifier (summer)

 

Room air-conditioning
(summer)

__ Central air-conditioning
(summer)

Self-defrosting electric
refrigerator

__ Electric Refrigerator
(without defrost)

__ Gas Refrigerator

__ Self-defrost home freezer

 

Home freezer (without
defrost) _ .—

_ Electric water heater

 

H W
I

_ Gas water heater

 

205

APPENDIX E

Tables of Means and Standard Deviations,

 

Matrix of Raw Correlations

 

206

207

TABLE 29.--Study Means and Standard Deviations.

 

 

Variable Mean Standard Dev. Cases
HOUSEN 199.7708 58.3209 97
HOUSIZ 3.9691 1.9496 97
MAJAPP 9.1789 2.8210 97
NROOMS 8.0412 2.1598 97
NDOORS 2.7010 .9913 97
RHEAT 6.2887 2.0613 97
SQFT 1097.2474 490.3113 97
FAMING 14.1722 4.8356 97
NFLORS 2.4742 .7513 97
NWIND 15.9897 5.8157 97
INSUF .1031 .3057 97
EXTSID 7.2577 6.3971 97
FAMLC 2.4021 1.1149 97
RACOND 1.2062 2.4492 97
BEPIR 2.9175 .8375 97
INSUW .7113 .4555 97
LLRES .1546 .3634 97
INSUC .8866 .3187 97
MEDUCA 12.8247 2.6975 97
EPEREL .8969 .8099 97
RPCOST .4330 .4981 97
EPERNG 1.8557 .5202 97
EPERFO 1.7113 .7065 97
HHSTEN .1340 .3424 97

 

TABLE 30.-Raw Correlation Matrix.

208

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