Appendix inc fill-ins.pdfStrategies for personal mobility: A study of consumer acceptance of
subscription drive-it-yourself car services
Department of Civil and Environmental Engineering
Submitted for the Diploma of the Imperial College (DIC), PhD degree of Imperial College
London
2
This study is dedicated to Natasha, and to the future
Acknowledgements
I am indebted to many for their advice, support and inspiration that made this study
possible.
My supervisors Aruna, John, and Martin went beyond the call of duty on many occasions,
and this research could not have proceeded if not for their encouragement and guidance. I
would also like to thank my examiners Kay and Dan, and Alison for placing her faith in me by
providing me the opportunity to teach whilst undertaking this research.
This study would not have been possible if not for financial support from the RAC
Foundation, and I would also like to thank Elizabeth for her insights and suggestions along
the way which have led to a better project.
Warm thanks are due to Carplus, City Car Club and RAC Breakdown Services for providing
access to customers of theirs willing to take part in the fieldwork, and to the study
participants who generously chose to share their time. Further gratitude is extended to
Benefit Technology Inc, DfT’s NTS team, Imperial’s HPC team, NatCen, and SRA for their
support of this research in a variety of ways.
Discussions with a number of public sector staff, academics, and industry partners helped to
shape the contours of this study, and I would like to thank each of you for your time and
thought. (The usual statement applies: any remaining errors are my responsibility.)
I could not have taken on a multi-year assignment of this nature without the unflinching
support of my family and friends, in particular those friends who have become like family to
me during the course of this research.
The research presented here is my own, except where the work of others is referenced.
3
Abstract
This thesis investigates consumer acceptance of subscription drive-it-yourself car services [SDCSs],
which are an evolution of car hire that began entering the commercial marketplace in the mid-
1990s. The aim of this research is to develop techniques to forecast how consumer demand for
SDCSs may develop.
On the basis of research reported in this thesis, it is argued that a person’s [strategic] decision to
subscribe to an SDCS can be reasonably considered to have a dependency with their expectation of
[tactically] using it to access particular out-of-home personal activities. It is shown that people can
also be thought to view subscribing to an SDCS as part of a larger ‘portfolio’ choice of travel options.
Traditional analyses of people’s travel choices are insensitive to these two issues.
Two datasets, one revealed-choice and the other stated-choice, were designed in order to provide
empirical data to test the proposed ‘strategic/tactical’ and ‘portfolio’ analytical form. The revealed-
choice dataset made use of web-based data-mining techniques, whilst the stated-choice survey is
novel in several respects to address the challenges presented by the SDCS context.
The methodological innovations proposed in this research proved successful in forecasting consumer
demand for SDCSs in the empirical application, and appear promising for wider use within the
transport domain and related research fields.
4
Chapter 3: Gaming-simulation task page 48
Chapter 4: Analytical framework page 58
Chapter 5: E-NTS dataset page 75
Chapter 6: AVATAR survey page 103
Chapter 7: Independent analyses of E-NTS and AVATAR datasets page 129
Chapter 8: Substantive results page 158
Chapter 9: Summary & conclusions page 183
Appendix A: Comparison of ‘distinct’ and ‘combinatorial’ model forms
Appendix B: Derivation of the ‘plateau effect’
Appendix C: Detailed specification and results from the analysis of simulated data
Appendix D: Further results from joint (E-NTS/AVATAR) estimation of parameters
Appendix E: Sample gaming-simulation survey instrument package
Appendix F: Sample AVATAR survey instrument package
5
Figure 1.2: Workflow of this study
Figure 2.1: Schematic of the course of a person’s car club SDCS engagement
Figure 2.2: Time trend in car club members worldwide and in the UK
Figure 2.3: Month-on-month retention of subscribers for the Communauto car club in 2004
Figure 2.4: Schematic of alternative trajectories for carsharers
Figure 2.5: Overview of studies which have forecasted the potential market penetration of SDCSs
Figure 2.6: Daily usage patterns of the Communauto car club for the year 2004
Figure 4.1: Summary of 'Distinct' and 'Combinatorial' structures
Figure 5.1: Map of England's Government Office Regions
Figure 5.2: Cumulative distribution plot of the number of journeys performed by NTS respondents
that are within the E-NTS sample
Figure 5.3: Workflow of web scraping task
Figure 5.4: Screen capture of formatted HTML output from the Journey Planner travel planning
service
Figure 5.5: Plot of observed and predicted journey speed by time-of-day for car journeys
Figure 5.6: Plot of observed and predicted journey speed by time-of-day for public transport
journeys
Figure 5.7: Plot of residual values from the web scraping task, disaggregated by mode of transport
Figure 5.8: Plots of residual values from the web scraping task, separate plots for each mode of
transport
Figure 6.1: Sample screen introducing the survey respondent to her [his] avatar
Figure 6.2: Sample of the main survey screen (as re-designed following field testing)
Figure 6.3: Screen capture of the request to [female] survey respondents to advise their avatar
Figure 6.4: Sample of the main survey screen prior as pilot-tested (prior to re-design)
Figure 6.5: Cumulative distribution of the duration of the interviews
6
Figure 7.1: Response of likelihood function to varying the mode-choice-level alternative-specific
constant for car passenger travel, using dataset G (Run G2)
Figure 7.2: Response of likelihood function to varying the mode-choice-level alternative-specific
constant for taxi/minicab travel, using dataset G (Run G2)
Figure 7.3: Response of likelihood function to varying the mode-choice-level alternative-specific
constant for driving a personal car, using dataset G (Run G2)
Figure 7.4: Response of likelihood function to varying the portfolio-choice-level alternative-specific
constant for owning a personal car, using dataset G (Run G2)
Figure 8.1: Cumulative distribution of the change in the number of car driving journeys per week
between the baseline scenario and Scenario #1 by the 19 people predicted to subscribe to a car club
SDCS in scenario #1
Figure 8.2: Response of likelihood function, using the ‘portfolio’ specification and the E-NTS dataset
only, to successive increases in the ‘observed’ number of each journeys performed by each person
Figure 8.3: Response of values of the salience (gamma) parameters to increases in the number of
people’s journeys which are taken into account
7
Table 2.2: Examples of SDCS studies employing qualitative market research techniques
Table 4.1: Matrix of the set of means of travel enabled by various resource portfolios
Table 5.1: Comparison of online travel planning services
Table 5.2: Spatial match quality for journey origins and destinations
Table 5.3: Proportion of journeys for which no itineraries for various travel modes were reported by
the web scraping task
Table 5.4: Summary of descriptive statistics for travel time of journey itineraries, by observed
method of travel
Table 5.5: Average residual errors (predicted minus observed) disaggregated by source of spatial
match for journey from the web scraping task
Table 5.6: Results of diagnostic mode choice model run using the E-NTS dataset
Table 6.1: Sample asymptotic variance/co-variance matrix, containing dummy values
Table 6.2: Matrix of correlations from the AVATAR survey results
Table 7.1: Comparison of data and model form characteristics for estimating the 'mode' and
'portfolio' choice models
Table 7.2: Summary of observed portfolio choices in the E-NTS and AVATAR datasets
Table 7.3: Summary of observed mode choices in the E-NTS and AVATAR datasets
Table 7.4: Correlation matrix of observations (‘portfolio’ holdings and ‘mode’ usage) from the E-NTS
dataset
Table 7.5: Correlation matrix of stated choices (‘portfolio’ holdings and ‘mode’ usage) from the
AVATAR dataset
Table 7.6: Listing of simulated datasets and characteristics
Table 7.7: Results from estimation using simulated data
Table 7.8: Comparison of target and obtained parameter values for run F2
Table 7.9: Results from parameter estimation of ‘portfolio’ choice using only the E-NTS dataset
Table 7.10: Results from parameter estimation of ‘portfolio’ choice using only the AVATAR survey
dataset
8
Table 7.12: Results from parameter estimation of transport mode choice using only the E-NTS survey
dataset
Table 7.13: Results from parameter estimation of transport mode choice using only the AVATAR
survey dataset
Table 8.1: Results from parameter estimation of ‘portfolio’ choice using the combined E-NTS and
AVATAR survey datasets
Table 8.2: Results from parameter estimation of mode choice using the combined E-NTS and
AVATAR survey datasets
Table 8.3: Comparison of ‘values of time’ estimates for non-SDCS modes of transport
Table 8.4: Comparison of ‘values of time’ estimates for SDCS modes of transport
Table 8.5: Summary of results from baseline scenario & Scenarios #1 through #7
Table 8.6: Correlation matrix of simulated choices (‘portfolio’ holdings and ‘mode’ usage) from the
baseline scenario (#0)
Table 8.7: Cross-tabulation of observed and predicted (baseline scenario) ‘portfolio’ holdings
Table 8.8: Correlation matrix of simulated choices (‘portfolio’ holdings and ‘mode’ usage) from
Scenario #1
Table 8.9: Correlation matrix of simulated choices (‘portfolio’ holdings and ‘mode’ usage) from
Scenario #5
Table C.1: Target parameter values for the simulated datasets
Table C.2: Obtained parameter values for runs with simulated dataset A
Table C.3: Obtained parameter values for runs with simulated datasets B & C
Table C.4: Obtained parameter values for runs with simulated datasets D & E
Table C.5: Obtained parameter values for runs with simulated datasets F & G
Table D.1: Results from parameter estimation of ‘portfolio’ choice using the combined E-NTS and
AVATAR survey datasets
Table D.2: Results from parameter estimation of mode choice using the combined E-NTS and
AVATAR survey datasets
. 0 2=#
"" A( >3 # +
& 3 & BED
" &"$
# ( )#
! !
"$ !
+ ,"- + #" ,
$
# " "
. , #" ( #
( )# )

=
( # " = >
/ $ %.7
%&88&/
? 4@ 2-
) $
$ !D *$ L22(
$$ %.<&88/E 228; !
%(88888 %.4 &8B &88/C
6H1
*&88 9%%0
5 " "6
* ! $
$
$$ ! %
N 22-.A9 !N4 $?
HN%&88. =NC &8.A/
1:!!
$

'

.$ /
, $$ , %
$ %$
$$ $
%

'+

? $$ ;. ;/
%*$
&88&42-2/ $ $
$,$ ,
$$
# $
)
$
# $
# $ A0 #
#<8 $$. $
$
#B
$ 2
# 02.
$ # 9 : !474;4<6

$ &#$#
#!;4'()*+, G'()*+, HI J KLMNO44PQRSTU9VPQRSTUWX DEF
"!;4'()*+, Y G'()*+, HI J KLMNO44PQRSTU9VPQRSTUWX DEF Z- .!;4'()*+,
<5&#( $ $ 2/% = 1 5 0. 2# : . 2 2 $

0 . 7 G'()*+, #:
"![4 YJ #!;474 ;4<6 Z - .![4
H \ . ?3#<5 &#* <5&#+ .!;4 .![4
#
;4 # ;4 0. =2 $
"! #!$%$&'()*+, - YJ ;4 9 G'()*+, HI J KLMNO44PQRSTU9VPQRSTUWX DEF
74 ;4 Z- .!
#!$%$&'()*+, J #($%$&'()*+, (<=a(!
_ ( A# 3 #!$%$&'()*+,$ 5 #!'()*+,# 8_` #D;4'()*+,
A$
#($%$&'()*+,# G'()*+, / #D;4'()*+,
1 / ;4 #1 5 g% ;4 9 G'()*+, HI J KLMNO44PQRSTU9VPQRSTUWX
DEF h ;4 9 hG'()*+, HI J KiY MNO44PQRSTUh Z9hVPQRSTUjX
DEF
(1 >8 A G'()*+,# )1 >8 A ;4 #
/ 2
&##' 0
.7

$
#
$
! $

'! ! !+!;
@; & !!

! '!'
! !&

**@ 5! ;8 # #
*9 I' !9
,9 = 8H9
4 ** - %/(- *
< :

I'
' ! (
#9M&L>#8 9M&L M8 >#9
! 8
9 ' '&
&,)*5! ' ' B '
'!H=& ( 7
, 3 *&-*, 22. )3 ,) * ,&.3*
3 )0 ),- ** 3 3 .-
3 23 *2 3 *. ) )-.
3 - , 3 ) 3 0
' #& ! 220O8)3&9&
$5! 8-,O9 # /
# 03 ) I
'! ' #E 5! & '!
:#! '%68.)O),O9
$ ' E&' ' '!
4 ! !
' + 5!
' & '!5!
).,3
,).3
.)G *38,,9 ))8,39
, -8)29 ,8*39 ,8)29
,8)-9
=5!&8 9 33,.2 R33)
=5!& 8 9 33, R33)
=5!&!8 9 33,.3 R33)
=5!&(>'8 9 33*, R33)
=5!&' 8 9 33**, R33)
=5!& #8 9 33,.3 R33)

4! & & Q)3>!
; # CC'9
. 7*33 '
!5! ' B #
;=/> 0 2
! ? %
= > $=
"> "#

! ! % "= "
//"> !
2'( !
- !'
$/ "46 ".5 "5 "5. ".. "3 1"61
$ 1" 3 4"4 ".4 "6 "3 ."1. ".
$1 "3 1"4 "5. "66 1"61 ". 4"/ & ' ( )*
# = '$$(>= ')$(
&+



'
7;< 7!= 7>; 70< 7>? 700 700 7"? 70= 7"> 7!@ 7!? 70> 7>; 7!; 7<0 7<> 7"= 70= 7!! 7!; 70A 7"> 7"< 7"A 7!> 7"? 7!! 7"0 7!A 7"A 70< 7!A 70!
7!; 7<= 70= 7<0 70" 7!; 7!A 7!; 7"> 7!< 7"; 7!; 7>< 70A 7>A 7>; 7"< 7!@ 7"= 700 7>; 7"! 7"> 7"? 70" 7"0 7"0 7!! 7!! 70" 70; 7!? 70A
7=< 7<! 7>= 70" 70> 7"" 7!" 7!0 70; 7!! 7"0 7!= 700 7"! 7"! 7"< 7<" 7!= 7"= 7"? 7!0 7"> 7"? 7"< 7!? 7!! 7"< 7"A 7"> 7!? 7!? 7!=
7>? 7>@ 7!? 7!! 7!> 7"< 7"@ 7"> 7!= 7"? 7!! 7"< 7!; 70> 7"! 7"A 7"@ 70" 7!0 7!; 7"< 7"! 7!= 7!= 7"0 7!" 7"! 7"< 7!= 7"? 7"!
7?= 7!= 7!@ 7!< 7"A 7<A 7>! 70> 7<@ 70; 7"? 7"" 7"0 7"0 7<= 7"? 7"= 7!= 7!@ 7"@ 7"< 70< 70< 70? 7!" 7"; 70? 7>; 7"; 70;
7!> 7!@ 70@ 7!= 7<< 7>0 70> 7<? 7>@ 70= 7"? 7"= 7"! 7>A 7!= 7!< 70> 700 7!> 7"0 7!@ 7!@ 7!= 7!A 7"" 7!; 7<> 7"> 7>A
7?A 7!A 7!< 7"! 7!" 7"= 7!" 7"= 7"" 7"A 7!! 7>> 70> 7"A 7"A 7"< 7!0 70" 7!> 7!< 7!0 7"A 7!= 7"= 7"; 7"" 7"! 7"0
7!? 7!; 7"! 70" 7!! 7!> 7!0 7"; 7"> 7"" 70= 700 7"< 7"> 7"= 7"; 7!< 7"; 70! 70" 7!= 7!! 7"= 7!" 7"> 7"< 7"0
7A@ 7"; 7"> 7!> 70; 70; 7!< 70< 7!; 7"@ 7"< 7"; 7!; 7"= 7!; 7"0 7"> 70" 7!= 7"0 7"= 7"= 7!A 70! 7"< 7!?
7!@ 7"= 7!; 7!0 7"> 7!< 7"> 7"@ 7"> 7"! 7"! 7!< 7"; 7!! 7"@ 7"0 7"" 7"> 7!> 7"0 7"0 7!; 7"= 7"@ 7"!
7"< 70> 70@ 7"; 7"A 7>! 7>= 7"> 7"< 70; 7"A 7"< 7!" 700 70" 7!0 7!" 7!= 7>! 7>! 7!0 7"> 7"< 7!?
7"< 70> 70! 7"= 7"0 7"! 7"> 7>= 7!" 70? 7"= 7!? 7!! 7"= 7"= 7"" 7!A 7"= 7"@ 7!! 7!> 7!? 7!@
7!> 7"> 7>" 7!? 70< 7"= 70" 7<> 7"@ 7"@ 7!" 70< 70A 7>! 7!? 70A 70= 7>! 7"= 7>" 7"= 7"?
!" # $ 7=" 7"> 7!> 70< 7"< 7!@ 7>" 70! 7"< 70< 7"0 7"0 7!> 70< 7"! 7"= 7"A 7"A 70< 7"! 70@
%&' 7"? 7=> 7<! 7"! 70< 7>0 70= 7"; 7!A 7"= 7"! 7>@ 70= 7"@ 70A 7"= 7!" 7>< 7"A 70<
# # 7!; 70! 7"! 70> 7"A 70< 7"= 7!" 7"! 70" 7>! 7>0 70@ 7!A 70? 7"" 7!= 7"! 7!@
(' 7A; 7!> 7!= 7"< 70; 7!< 7!< 7"> 7"< 7!< 7"= 7"= 7"< 7>> 7"@ 7!= 7"! 7";
) #' $ 7"< 7!! 7!< 70> 7!@ 7!@ 7"A 7"> 7"A 7!< 7!! 7!! 7>! 7"0 7!< 7"! 7";
* + 7"? 7"0 7"" 7"> 7"0 7"= 7"< 7"0 7"! 7"0 7"= 7"@ 7"> 7!" 7"< 7"?
,# 7"0 7!; 7"= 70= 7"< 7"< 7>! 7!; 70" 7"! 70@ 70" 70A 7!@ 70;
%&+# 70! 7>A 7!@ 7!A 7"@ 7"> 7"@ 70" 7!= 7>A 70= 7"" 70< 7"<
- 7"0 7!! 7"= 7!@ 70< 7!< 70! 7!? 7>" 7"! 7"? 70> 7!"
+%# !.-/0.($ 7"0 7"= 7"? 7!" 7"? 7!; 7!> 70" 7!= 7"! 7"! 7""
-&'# 7<> 7>" 7"A 7!? 7!= 7>0 700 70? 7<@ 7>0 70?
1 + #&' 7?0 7!A 7"@ 7"A 7"@ 7!@ 7"> 7!? 7"A 7!A
1 + + 70= 7!; 7"A 7"= 70@ 7"< 7"; 7!! 7"; )' #++' '
#2 7@! 7<A 7!? 7!? 7!< 7!= 7!< 7!>
# 3 43 +&
56 & #&3437
3 8 ' ' '
-+9 +# 7>0 70A 7<< 7!< 7>A -+9+# &
&+# 7!< 7"? 7"0 7>!
%
"! "
" . $
.* ++ ++ ++ ++ ( 8 > (>
.? - (> (> ( ' > >
?6 ++ ++ ++ ++ ( 8"( > 8">
.?* ++ ++ ++ ++ 8" > 8">
) & 1- (> '> ' <> &>


.

.
5 .56
! $!! !+

























!" #$ "% #! #& "# #' ((
"! (! #! #( "# #) ")
'$ ") #! "" #! "$
#* #' "& #& "$
(# #' #( #*
#' #& #*
#& #"
#"

+ ,-
+ # )
+ """
+ """
+ # )


'-

) $#*%%# +$,
#$ %%((
+ ! *+)#
("<"
? !
A .H .
?' A A A A A A A I I +1 -"-
A A
' A A A A A A A I I +<1<"(
6 A A
A A A
6' A A A A A A A I I + &"
6( A A
A A A
A' A A A A A A A I I +&'"
B A A
A A A

"$ ! +81"'"
6 :
! "
$ %&.(!) : $ )
6 :
1
6 :
) ,$)


". ++
!
)+$ +'1("8
+$ +'8 +'1"' +1"' +'("& +"' +'" +1" +"'>?/9 >? 8"8-/8"8( 8"8 /8"8 8"-/8"( 8"&/8"1 8"&</8"1& 8"&&/8"1& 8"-/8"( 8"&&/8"1&
C " & 8"'( 8"'- 8"'& 8"'< 8"'< 8" 8"'<
3% 4.@! +8"&- +8"(838"4 +8"&-( +8"&11 +8"< +8"<- +"< +8"<
3% 4.@! +8"'- "'< <" <"< "(( "( " "((

3: 4.0 ++ ++ +"( +8"1 +8"(<38"4 +8"( +"8& +8"1
38"-4
3: 4.6 ++ ++ +8" &' 8" 8"('38"8 4 8"-&8 +"8( 8"(-
3: 4. ++ ++ 8 8
A B?% ++ +8"8 +8"8'' +8"8''< +8"8'-- +8"8'-- +8"8'&1 +8"8'--
A B?%9 ++ ++ +8"8' 138"&4 +8"< +8" < +8" & +<"( +8"'8<
# 3B4 ++ ++ ++ ++ ++ +8"8<< ++ ++
# 304 ++ ++ +8"8( +8"88'' +8"8 ++ +8"81 +8"88('
# 3 4 ++ ++ +8"8( +8"88( +8"88( ++ +8"8 <8 +8"881<'
3L4; 79 ++ ++
38"<4
L3 4 ++ ++
)+$ +< <"
+$ +&8<" +&8&"- +11 " +1(1"( +1("< +1-&"' +1((" +1("<>?/9 >? 8"/8" 8"/8" 8"-/8"( 8"<8/8"1 8"<(/8"1 8"&/8"- 8"<'/8"- 8"</8"1
C 8"&< 8"(& 8"1( 8"881 8"8'- "''+- 8"888& 8"'
3% 4.@! 8"8-
38"&(4 8"1&38"'<4 +8"(&&38"(14 +8"'38"''4 +8"8&838" 4 8"(& 38"-4 +8"8 < 38" 4 +8"8&838" 4
3% 4.@! +8"<(( 8" & 38"1<4 " 38"(84 "138"( 4 "--38"--4 -"8838"' 4 -"(38"-4 "--38"--4
3% 4.@!
$ +8"1'& 8"8(138" <4 +" 838"-4 +8"-(&38"-&4 +"<38"&4 +8"- 38"&'4 +8"<(38"(-4 +"<38"&4
3% 4. +'" +'"< +("8 +("1- +'" +'" +'"( +'"
3% 4.

3: 4.0 ++ ++ +"138"8&4 +8"8&'838"1&4 +" '38"(4 +'&"3"884 +("<&38"-&4 +8"-8138"' 4
3: 4.6 ++ ++ +8"--(38"(84 +8"8&&(38"( 4 +8"&-38"- 4 8"&-138"1&4 +1"1838"'4 +8" &38"-&4
3: 4.6 ++ ++ -"- '"'8 1"&38"8-4 +-("<38"(-4 '&"(38" 4 "138"814
3: 4.6; 7 ++ ++ +"<(38"8-4 +8"<38"'4 +"'(38"14 +" &38" 84 +"<38"'<4 +8"138"'14
3: 4. ++ ++ 8 8


A B?% ++ +8"88-(&38"('4 +8"8-138"8 4 +8"88 1 38"14 +8"8''38"&4 +8"88(38"&4 +8"8 <38"8-4 +8"8''38"&4
A B?%9 ++ ++ +8"( 38"14 +8" +"1 +8"<(38"'14 +&" 838"<4 +8"'8'38"8&4
# 3B4 ++ ++ ++ ++ ++ +8"8(8 ++ ++
# 364 ++ ++ 8"881838" 84 8"8838"&4 8"8('38"<(4 ++ 8"(<(38"' 4 8"88'&138"<-4
# 304 ++ ++ +8"8--(38"'4 +8"8(8 +8"38"8<4 ++ +8"(( 38"<4 +8"8 38"8-4
# 364 ++ ++ +8" +8"8< +8"-138"8 4 ++ +"<38"84 +8"81&
# 36; 74 ++ ++ 8"8-(-38"-&4 8"8(<38"(4 8"38"'4 ++ " 38"'4 8"8 38"(-4
# 3 4 ++ ++ +8"8< 38"&4 +8"8-- +8"8&<38"-4 ++ +8"8838"8&4 +8"8<<
3L4; 79 ++ ++
L3 4 ++ ++
L3 4 ++ ++
"
8"&38"(4 +8"81 38"<14 8"-38"&84 8"1-(
L3!$4 ++ ++


4
8"1 (
# 0-3E0<4 ! 7
6 5
63; 74!
K-8/ K'8/
; 7 "2 ! 6
E3E$ 4 !
6 E 3""

+$ +8'&"- +&&-<"- +& ( "& +-&& ">?/9 >? 8"'/8"' 8"''/8"'' 8"'/8"' 8"'/8"'
C ("1( 8"'8 8"'( "'&
# 3B4 ++ ++ +8"8< ++
38"'4

%&'.(! ) ) $
/! $#*# %%# +$,$

+7 !"
0( ! ! ! 0
; 7;7 $! "
!8 ' . / 0
)+$ +8-"- +<8"-
+$ +18("- +'-1" +(-"8 +-"8>?/9 >? 8"8/8"8 8"''/8"' 8"'8/8" 8"/8"8
C -"(' 8"( 8"-1 8"((
.6 +"11 "8138"&4 8"11&38" 4 +8"<<38"(84
.6; 7 +8"<&( +8"138"-&4 +8"8(&
38"<&4 +"8
.% +" +8"'' 38"4 8" (38"&4 8"<'
.D$ +" - 8"-''38"8<4 +8"'
38"'84 "-
# 3B4 ++ ++ +8"8&& ++
38"(84
38"&(4
# 3 4 ++ ++ ++ ++

%&'/(! ) ) $ !
$##
# ! ;+ 7 34
"= !


-&


FGHI JGK$%&'()$"(B"LME N&%N)OPQRSQ? GKTU#VO%L(W? 2 GK$%&'()$"(B"LME N&%N)OPQRSQ GKTU#VO%L(WX ++ E 8"-8"<8 + 8"("
# ! 0&! !
2 /"0. 5 22.23
7
. " "
" -
</-+ /- /- '
)2*
5& 72B ";(+( ""
5& 72B @; ""
5& 72B ! ; ""
5C 72$5/"0.7 ;+5;7 ""
5C 72$522.237 '(
5;+7 ""
. 5 7 ";;' ' ""
E) *9 ;;5;7 ""
$$4 ?':;1
$) *4 ?(;(1
2 ""
"9 9 . OPJHQ R PJH2 ST U ;6 /"0.22.23 .
( H
/
=PJHQ R PJH2 ST = ""2 /"0. 5:++= .667 !
5' .67 22.23 G
+ /
B "
2$ ; ""
. 5 7 ";; ""
! 75$.';7
$ ,
'
$
+7 2 J $9 K5 ,
$ 7
67 2 J )*
/"0." 5 .6(7 '
4 ' K * 9 (K
&
$
) *$
& (6K (@ K (+@K (@+K (@+K (((K (6+K ((+K
& :K 6K :(K 6K K @K @K K
& '6@K ' 'K ' @K ' 'K ' 'K '6+K ' 'K '66K
'6K '@K '@K '6K '@K '@K '6K ';K
8! :K :K '(K ';K ';K :K K ';K
.,1 'K (K +K (K (K (K (K (K
$ "" ;@K (K ;6K ;6K ;K ;;K ;K
) *$
"" "" "" "" "" ( K ;;K ( K


@:

7

('K9 5'@K'6K7
('K ,1 9 5(K'K7
;@K9 $ . 9 1!
$
9 G
K 50
7. G
8 9
(1 0(
J' , $ B
" J
B9 *
;'K ! 5+@;K+@K7

9 5'@K 7
(K,1 9 5(K(K7
'K$9 5;K(K7
( K9 ) *$
) *
,. "$
) *
5 ;;, 7
$ ! $5 75V WXRXYXXQWZQWZX[ \ V WXRX
7.


.
! !
!
. "
D 57
/"0. )* !
' 8 *
,$ 52 ';7
5 .7
( 0 9 -;
- 22.23
5/"0.M22.237) * 9 . /"0.
K ) * # B E_EH@ B E_E ``BG%6K )* #_B`H@_B` DaaG% . ""-
, " 4K1(K1( K1( K(M !1"'
!1 1 5A ';7
<'
'' . ""


) # $ 3 4 )
" ,7,
7, !
+ ( !)*
E F"
8( 0 $)#)
7, !1
-G H ! H"## (# $)#)
IJ K ! K"I LJL 9 LKL 9 ! 9 IK"I !
" ( &!1(#$)
MN O 9 PQ R@STUVWXY Z A [\S ,
$)## R@STUVWXY Z A [\S )

)) %
MN O 9 PQ bR: STUVWXY_ ; ] R@ STUVWXY_ A [\S` a c
; # $)### %% 3MN4) #0
dMNd08DCe1 f gh O

,!
,&
,'

R :^

&
R: STUVWXY_ ; : STUVWXY_ ; R@ STUVWXY_ A [\S` a
# 2
# # ## 5+
98 #%8<)## 1 1 1 5! 1 1 1
98 #%8<)# 1 1 1 5 1 1 1
98 #%8<)#

=8 #%88 % 1 1 1 1 1 1 5!
=8 #%8"-@#% 1 1 1 1 1 1
=8 #%89# 1 1 1 1 1 1 !
=8 #%8+ 1 1 1 1 1 1 &
A- # B,9 511 511 511 511 1 511 511
A# B,9 51 51 51 51 1 51 51
"% ?%# 511. 511. 511. 511. 1 511. 511.
"% >## 511. 511. 511. 511. 1 51 511.
"% 8 % 51 51 51 51 1 51. 51
"% "-@#% 51 51 51 51 1 51! 51
"% 9# 51 51 51 51 1 51!. 51
"% + 51 51 51 51 1 51& 51
#C6 #7 1. 1
C 10. 1
D5+ 5$&''0
5+ 50&0/ 50&0/ 50&0/ 50&0/ 0./ 50&0/ 50&0
mn@ mn 1'.@1'' 1'.@1'' 1'.@1'' 1'.@1'' 1''@1'& 1'.@1'' 1'.@1''
%: - 111&' 1/0 1/0 1/0 1/. 1/0 1/0
98 #%8<)## 51..1!& 51..1!& 51..1!& 51..1!& 1'!!1! 51..1!& 51''01!
98 #%8<)# 510 1&0 510 1&0 510 1&0 510 1&0 1!010' 510 1&0 51/'01''
98 #%8<)#

=8 #%8>## 111& 1./11 1'11 1.1 1 5! 11!1 1.!11.
=8 #%8?%# 1& &1'! 1!0/1'1 11..!1'1 1!'01' 5 11' .1' 1&1'1&1
=8 #%8 1 1
=8 #%88 % 55 55 55 55 55 55 55
=8 #%8"-@#% 55 55 55 55 55 55 55
=8 #%89# 55 55 55 55 55 55 55
=8 #%8+ 55 55 55 55 55 55 55
A- # B,9 5111/ 5111/ 5111/ 5111/ 5111/0 5111/ 5111/ .
A# B,9 51. 51! 511!!' 5111 511.. 511!1 51
"% ?%# 511! 0 511!1 5111' 5110 111.&& 5111&0. 511
"% >## 511' 511! ' 5111.0 511!/& 5111.1'/ 5111.!/ 511!/
"% 511 1& 511/&. 511!0 511./ 50 511' 511.
"% 8 % 55 55 55 55 55 55 55
"% "-@#% 55 55 55 55 55 55 55
"% 9# 55 55 55 55 55 55 55
"% + 55 55 55 55 55 55 55
#C6 #7 1/'0 1 !1 '/1 1& &.0 .& 1 .
C 10!0 1& .0 . '& .00 10
C $ $ 101& 1 .1
! '&' .. 1
C)+# 1/&/ 1 1' '.! 1 & ' .1. 1 '1
O8DCe1 1/&1 1 / '' 1 .1
.1
1
##>58 5
!' (

/

! " ! "
5+ 5/' 5/' 5/ .. 5// 5// 5/'
mn@ mn 1' @1' 1' @1' 1'@1' 1&/@1&. 1&/@1&. 1&.@1&.
%: - 1'0 1'0 1 1 & 1 & ''!






=8 #%8"-@#% 55 55 55 55 55 55
=8 #%89# 55 55 55 55 55 55
=8 #%8+ 55 55 55 55 55 55






"% "-@#% 55 55 55 55 55 55
"% 9# 55 55 55 55 55 55
"% + 55 55 55 55 55 55
#C6 #7 1! 01' 1& /1/ 1&.1!1 & 1 1
C 1. 10 0 10'. 1 0 1. 1
C $ $ 11 && 1 11 1 .0 1
C # && 00 .1 1 &1 1 1 1
C)+# &' 0 . 11 1 / 1

.!! .1
.1!
"' ( )


5+ 5 //! 5 //! 5 0! 5 0 5$&&&'
mn@ mn 1!@1!0 1!@1!0 1!@1!0 1&!@1& 11@111
%: - 1!11 1!11 /1. 1! 11/!/
98 #%8<)## 500 500 5!1 5! 51'1/
98 #%8<)# 1''1 1''1 51 11 5&10 5'&11/
98 #%8<)#

=8 #%8>## 1!!&1!! 1!..1!' 1 1'!1'. 5! 1&&
=8 #%8?%# 511/'0100 5110'1100 1 1& 1/ 1!1.
=8 #%8 1 1
=8 #%8"-@#% 55 55 55 55 55
=8 #%89# 55 55 55 55 55
=8 #%8+ 55 55 55 55 55
A- # B,9 5111 5111 511 511 111& 11

"% ?%# 511&& 511& 511. 511.1 51! 1&
"% >## 511'1. 511'/' 511. 511'0 11&''
"% 5110/1 511/ 51 511 11.1
"% 8 % 55 55 55 55 55
"% "-@#% 55 55 55 55 55
"% 9# 55 55 55 55 55
"% + 55 55 55 55 55
#C6 #7 1 1 ' 1 100 //1
C 1 . 1/ 1 1/ 1/'!1!1
C $ $ 11 10' 1 11 1.01!.
C # 1 .' 1&& 1 1 .& &5&!11

#' ( )




! " ! "
D5+ 5&''0
5+ 501' 50!/ 50!& 5$1&!0 5$1!/& 5$1!/&
mn@ mn 1'0@1'/ 1'/@1'/ 1'/@1'/ 1!&@1!! 1!'@1!& 1!'@1!&
%: - 1/ 1 !1/ 1!1/ '05! 15&
98 #%8<)## 511 1/10! 1 1
51!/1& 1
1'10 1
1
5!!' 51 !0.
50 1
55 55
=8 #%88 % 55 55 55 55 5!'.1 & 5!&&1./
=8 #%8"-@#% 55 55 55 55 !' .1011
=8 #%89# 55 55 55 55 !1! ..
=8 #%8+ 55 55 55 55 . .0
A- # B,9 51110& 511 511
5111/ 511
511
51'& 51





"% 9# 55 51!!111 55 55 55 55
"% + 55 51!1 55 55 55 55
#C6 #7 0
$' ( )



!" #$%&'( )(*
(5 %# %6 % #E >') # #
D5+ 5!$''00
5+ 5!$!11 5!$&'1 5!$1!. 5$ /00 5$ .0 5$ 0/! 5!$11 & 5$ .0
mn@ mn 11@11 1&@1& 10@1/ 1 /@1 1!11@1 1 1 &@1' 1@10 1!1@1
%: - !/ 1!. 11/' 1&! 11. &!'5' 1111&!0 1&!
#p # *5D" !' !.1 1. / &1 '1 &. &1
98 #%8<)## 51'0 511'0/
1!0
98 #%8<)# #+ 51&& 100 '. '
1 1 . 1.&/
1
98 #%8 ### 5&!! 5& 50. 5'&. 5'! 5&0& 5&! 5'!
98 #%8 #6 7 1
1/1
1&
51'&
1!!
=8 #%8?%#*5D" 55 55 510.& 11./ 1'
1
1/
=8 #%8?%6 7# 55 55 5/' 51!.
1'
5//
1
1
1
1


A- # B,9 55 511. 511&1 511!01 511!.& 511!&& 511!.1 511!.&
A# B,9 55 55 5110/ 510. 5& 510// 50/ 51&0
"% B# 55 55 55 55 55 511!&/ 55 55
"% ?%#$">
1!
"% >## 55 55 511&0' 5111 511./0 55 51! 511.
"% ?%### 55 55 511./ 511/0 51'.' 55 5'! 51!0
"% ?%6 7# 55 55 1.!. 11!'. 1/ 55 1/ 11'0.
"% 55 55 511!&0 5111.1 511!! 55 51 & 51110 !
#HC "> 55 55 &1 / /0 .. .& !
C6 #7 55 55

C $ $ 55 55
C # 55 55
C)+# 55 55
1
-
5+ 5$0.&' 50$1& 50$&.// 5&1$ '.
mn@ mn 1!&@1!& 1&1@1&1 1! @1! 1!.@1!.
%: - ! . 1 1!
8?%### 5&& 51. &1&. 510&'11 5.
8?%6 7# 5100' 510&' 51.11 5&
88 % 51 . 51! 51. 51/'
8"-@=#% 5!/ 5/' 50 5&!
89# 5 51' 51/ / 5!0&
8+ 5& 51.&0 51.. 111/1 !
A# B,9 55 511/0 511&'! 511.
"% B# 55 55 511 55
"% ?%#$*5D" 55 5110 55 111 ''
"% ?%#$"> 55 111&!
55 51.1
"% ?%##?8# 55 5111/!/101 55 1101.
"% ?%6 7# 55 1110!1/ 55 11.
"% 8 % 55 511.. 55 110
"% "-@=#% 55 511! 55 11!1
"% 9# 55 5111 55 11.!
-


! "
"
/ ,


( 6 6 & 37 $ 8 8 # # / 8 ( $ # ' ! # 9 % 9 ' - ' 9 ( :) % :3 ;;<< ( ' / ' $ . ' ' ' # ' ' : : : ' ( 8 ' 8 # # 8! # ' ' . ' :& # ' . '
( 8' ' . ' ;; << # ' ( 8 / , ;;/ 8 << ;; <<& ;; << 37 $ & 0 , 6 ;; << / 6$6 = / ;; * << $







!"
#


!
"
" #

$
%
&
'
(

&

)

$%
&'(
) %




!"
#
*
*
&

"+,


-
-
'
.
/



* &



!"
#
#

-
(

%
5655
5755
5855
3555
3355
3955
3:55
3;55









$ "
!" # # " % ' ( ) * + , "#
- . -



$ "
!" # # " % ' ( ) * + , "#
- . -

&


$ "
!" # # " % ' ( ) * + , "#
- . -
S Le Vine thesis
>? # @ 6 ./ 0&
3, >A ?A @ B6
9 * !/ ' 3 6
J
5, >A ?A @ B8
9 * !/ ' 5 8
J
) *
$ %$#



) +, ,

&

-, , '(
!
./


"

-.
+


! "
#$% & " "

































'


(%) # ")* % % + +$ % +$ " ,- !-. / +$ * $

0,9%,'#$%/&%8,5,*+/)1(1#,4,/#$%2)0(1#%&


;



! " # $ %
& " ! " " '

( " ) "" ! # %






























!/
*
" > # 9*$ 5!!
= " > # ,$ ?8M
" / " / 8 #+J
<2*9#="# ( $9">8*#> # %#
## N!1
8 !11$) ( # 3$%%&5 )
9+
'9' $" > # $5
J "#
9 " > # 8 D = " $9#
? $=!11'#! ( " "
!.=#
' E" > # >#H10$0'5!
>$ $D : *##B) * := %2$
O
- ! ,/ ' 0 B (
7 ! " $ +*##*## $!1
A $$N /0$)' " " (
/ " &.$&05.'
;K
*-# 8
$8)
9" %
49 ! ),$:$A8*## #
: $?$!11/' "" 2 "
" > # 9?" *%.0$'1.5'0
$;K
# #- $*" 8#
> # & !!'5!!0
K $>$B $9$+$=$!11/ " ""
# ' " + ( " ## 9
&= " > # ,$ ?8
( " #
9 J #"%
&!5.0
,#$B!11.$ ! ( * ,* $!
*$N O
B :S9 *" 8#
$=!11'$+D ( "" " S$= M
5B $= 1$! " "" (
! ! +DJ " $ $;% $+
=$* $!11B B , " #
= +$>!111$# # : ! , ,"" $9 ? $?
- $" 8%> # 9>D1
&!'& 5'!!
) $M!110J***J"8#EE&15
&<#!110M
$;K
!1
! $%6% " : A# #$;
" J 8 $*%; &!.$&&5&'!
" ( # " $M =
" > # ,$ ?8M
4 $;K

8" 8
" ' 1 * 0 * : 0 * #
>$KN '! / J***8#9#
$=O8#
$ $M; "%, %*8 M$* %$! 5.!
>$,!11.$)1) @
> $!11$ %5$&<#
! G # ' ( # " '
J5 " = A)+ $= # $"$
" > # 9,$'&!$!05!!
/ " " " > # 9,'!$& .5'1/
9 $A#
#$>$> $N=!11 "" " (
# + ( M. =
" > # ,$ ?8M
$$$?$8 $)# , ( *
&
# #'$'5/&
"3" 4!11= 9#" ## % $
;K
" !11$M8# M$;K
"% +$$K $?$ 0'J ( ##.$
! 0 : $%%K " > # >#$!.0$/5 '
$BJ "#
P + #9 0 " > # ,$
Q$"$K$>$K 2)$K!11 " (
" # " # #0.!.&5/
$= # J "#