transportation engineering laboratory, hiroshima university 39-1 development of car ownership and...
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Transportation Engineering Laboratory, Hiroshima University 39-1
Development of Car Ownership and Use Model Considering Intra-household Interaction
Junyi ZHANG, Akimasa FUJIWARA
Masashi Kuwano
Transportation Engineering Laboratory (TEL)
Graduate School for International Development and Cooperation (IDEC), Hiroshima University, JAPAN
SAKURA Meeting, Japan-France Integrated Action Program, INRETS, July 2, 2004
Transportation Engineering Laboratory, Hiroshima University 39-2
Motivation
Household decision making
Car ownership in local cities in Japan30% (23,664,000 / 76,893000)
Car ownership in developing countries
Transportation Engineering Laboratory, Hiroshima University 39-3
Urban Air Quality Management Group
Urban EcosystemManagement Group
Socio-economicAssessment Team
Transportationindices
Environmentalindices
Land useindices
Capacityindices by
actor
Institutionindices
Carrying-Capacity
Emission production
Capacityindices by
actor
Capacityevaluation model
Land use andtransportation model
Environmental Management in Developing Country: 21 Century COE (Center of Excellence) Program
Transportation Engineering Laboratory, Hiroshima University 39-4
Development of Evaluation Framework for Land Use and Transportation Policies from the Environmental Perspective
GISy3 = h (Trip distribution, inter-zonal level-of-service)
y2 = g (Trip generation and attraction, inter-zonal travel utility)
y4 = i (Car traffic volume, link capacity, link free speed)
Trip generation and attraction
Trip distribution
Distribution of residence and.employment, transportation network
y1 = f (Population, car ownership, employment,travel pattern)
Link traffic volume and speed
Car traffic volume
Land use model
EnvironmentalIntensity
Trip generation and attraction model
Trip distribution model
Modal split model
Traffic assignment model
Travel accessibility
Travel level-of-service
Travel utility
Car ownership model
Emission productionEnergy consumption
Urban formpreference model
Population and economic synthesizers
Environmental evaluationModel
PolicyEvaluationPolicyEvaluation
GISy3 = h (Trip distribution, inter-zonal level-of-service)
y2 = g (Trip generation and attraction, inter-zonal travel utility)
y4 = i (Car traffic volume, link capacity, link free speed)
Trip generation and attraction
Trip distribution
Distribution of residence and.employment, transportation network
y1 = f (Population, car ownership, employment,travel pattern)
Link traffic volume and speed
Car traffic volume
Land use model
EnvironmentalIntensity
Trip generation and attraction model
Trip distribution model
Modal split model
Traffic assignment model
Travel accessibility
Travel level-of-service
Travel utility
Car ownership model
Emission productionEnergy consumption
Urban formpreference model
Population and economic synthesizersPopulation and economic synthesizers
Environmental evaluationModel
PolicyEvaluationPolicyEvaluation
Transportation Engineering Laboratory, Hiroshima University 39-5
Outline
1. Review of existing research
2. Methodological issues
3. Development of discrete choice models with inter-agent interaction
4. Summary of survey data
5. Estimation results and discussion
6. Conclusions and future research issues
Transportation Engineering Laboratory, Hiroshima University 39-6
1. Existing research
Non-IIA discrete choice model
Exogenous choice set Endogenous choice set
Flexible variance-covariance matrix
MNP, HEV, Mixed MNL & MNP, GEV
GenL
Context dependence Mother Logit, Dogit, SP, Context-sensitive spatial choice model
r_MNL, r_NL, r_QNL
Hierarchical or sequential decision structure
NL, GNL, CNL, OGEV, PD, NPCL, Network GEV, EBA
r_NL
Discrete choice models: examples
Transportation Engineering Laboratory, Hiroshima University 39-7
1. Existing research
Focus on household, but not individual members
Focus on both household and its members
Husband & WifeHusband & Wife
Without intra-householdInteraction
With intra-householdInteraction
Type of household-related research
Transportation Engineering Laboratory, Hiroshima University 39-8
Thorndike, R.L. (1938) On what type of task will a group do well? Journal of Abnormal and Social Psychology 33, 409–413.
1. Existing research
Transportation Engineering Laboratory, Hiroshima University 39-9
1. Existing research
Arrow K.J. (1950) A Difficulty in the Concept of Social Welfare
Arrow K.J. (1951a) Mathematical Models in the Social Sciences
Arrow K.J. (1951b) Social Choice and Individual Values
Festinger L. (1954) A Theory of Social Comparison Processes
Harsanyi J.C. (1955) Cardinal Welfare, Individualistic Ethics, and Interpersonal Comparisons of Utility
Lorge I. and Solomon H. (1955) Two Models of Group Behavior in the Solution of Eureka-type Problems
Luce R.D. and Raiffa H. (1957) Games and Decisions
Nash J.F. (1950) The Bargaining Problem
Nash J.F. (1953) Two-person Cooperative Games
Samuelson P.A. (1956) Social Indifference Curves
Siegel S. (1957) Level of Aspiration and Group Decision Making
Simon H.A. (1955) A Behavioral Model of Rational Choice
Historical evidences: 1950s
Transportation Engineering Laboratory, Hiroshima University 39-10
Shopping behavior Wives did most of grocery shopping, with an awareness of products and brands that their families liked. Husbands and teenagers were frequently involved in new or different brands. The growing importance of men as buyers
Tourism Husband: mention initial idea to take a trip, suggest a
destination, and select an airline
Mutual decision: decision on where to go
1. Existing research
Historical evidences: 1960s~1970s
Transportation Engineering Laboratory, Hiroshima University 39-11
Housing and automobile (1) Buying home: husband (price range, whether to move)
wife (no. of bedrooms and other house features)
(2) Automobile: for the make: husbands dominant households (60%)
for the color: husband dominant households (25%)
husband > wife
The growing involvement of women in family decisions
1. Existing research
Historical evidences: 1960s~1970s
Transportation Engineering Laboratory, Hiroshima University 39-12
1. Existing research
In marketing research, studies of husband-wife influence have been justified to
(1) select the proper respondent in consumer research surveys,
(2) determine the content of advertising messages, (3) select advertising media,
(4) guide product designers to include features that appeal to
those who are most influential in the purchase decision, and
(5) assist in the location of retail outlets
Applications of household decision-making mechanisms
Transportation Engineering Laboratory, Hiroshima University 39-13
1. Existing research
Goals Strategy Ways of implementing
“Consensus”(Family members agree about goals)
Role structure “The Specialist”
Budgets “The controller”
Problem solving
“The expert”
“The better solution”
“The multiple Purchase”
“Accommodation”(Family members disagree about goals) Persuasion
“The irresponsible critic”
“Feminine intuition”
“Shopping Together”
“Coercion”
“Coalitions”
Bargaining
“The next purchase”
“The impulse purchase”
“The procrastinator”
By Davis H.L. (1976 )
Household Decision rules and heterogeneity
Transportation Engineering Laboratory, Hiroshima University 39-14
Kirchler E. (1988) Household Economic Decision Making, in Handbook of Economic Psychology, van Raaij W.F., van Veldhoven G.M. and Warneryd K.E. (eds.), Kluwer Academic Publishers.
1. Existing research
A household will seek to minimize social and economic costs in decision situations by trying to make an optimal choice after passing through a commonly satisfying interaction process.
Household decision-making: Decision rules
Transportation Engineering Laboratory, Hiroshima University 39-15
Relative Influence
Young childless couple
Couple with child under 6
Couple with dependent child
Couple with independent child
Old childless couple
Husband
Wife
Child
100 %
By Cosenza R.M. and D.L. Davis (1981)
1. Existing research
Household decision-making: Life cycle
Transportation Engineering Laboratory, Hiroshima University 39-16
1. Existing research (transportation)
Szalai (1972): The use of time: Daily activities of urban and suburban populations in twelve countries. The Hague: Mouton. 1) Large sample size: 30,000 time budgets drawn from 12 nations 2) 96 activities 3) 24-hour diary (types of activities (both primary and secondary activities), time, place and duration)
shows the relevance to household decision-making.
Transportation Engineering Laboratory, Hiroshima University 39-17
Household members interact in making decisions about the different activities that they perform and the related allocation of time.
(1) Joint activity participation(2) Household resource allocation(3) Task allocation(4) Role specification
1. Existing research (transportation)
Transportation Engineering Laboratory, Hiroshima University 39-18
Intra-household (temporal and spatial) interaction and inter-dependency among activities
Wife Husband
home restaurant
office
business
time Shared activity
Allocated activity
In-home activity
Independent activity
supermarket
Travel
Transportation Engineering Laboratory, Hiroshima University 39-19
1. Modeling approaches
(1) LISREL model (2) RUM (Nested-type logit model) (3) Mathematical programming model (4) Rule-based approach (5) Group decision-making theory
1. Existing research (transportation)
2. Survey methods
(1) Stated preference (2) Interactive agency choice experiments + Game theory
Transportation Engineering Laboratory, Hiroshima University 39-20
Wind (1976), Rogers (1976)
The view of consumers as individual decision makers is still very much alive despite commonsense observations that the family is the relevant decision-making unit and a growing research interest in the field of marketing research.
Current situation in the field of transportation: Most of the existing models typically assume an individual decision-making process.
1. Existing research (transportation)
Transportation Engineering Laboratory, Hiroshima University 39-21
2. Methodological issues
h : group (e.g., a household) i : group member j : alternative
Gumbel distribution
j hnjhijj1h
hnjhijj1hhj )v,...,v,...,v(fexp
)v,...,v,...,v(fexpP
hj)v,...,v,...,v(f
)u,...,u,...,u(fGUFMaximize
hnjhijj1h
hnjhijj1h
Principle of random group utility maximization: A concept of meta-utility
Transportation Engineering Laboratory, Hiroshima University 39-22
2. Methodological issues
(1) Mother logit model (McFadden, et al, 1977)
}vv{exp
}vv{expP
k j'j 'ikkik
j'ij 'jjijij
}v{exp
}v{exp
}v{exp
}v{expP
kt
0s siktks
t0s sijtjs
k ik
ijijt
j j'j t'ijt,ijt'ijjijt
j'j t'ijijtt'ijjijtijt )vv(wr
)vv(wrP
(2) Dynamic GEV model (Swait, et al, 2004)
(3) r_MNL model (Zhang et al, 2004)
Choice models based on meta-utility
Transportation Engineering Laboratory, Hiroshima University 39-23
2. Methodological issues
Scale measure: 3, 5, 10-point scale
Husband decided Jointly decided Wife decided
-------------------------------------------------------------
Interaction-based measure: Power
SP survey
Game theory
Endogenous estimation based on the attributes of decision makers
Measurement of relative influence of household members
Transportation Engineering Laboratory, Hiroshima University 39-24
2. Methodological issues
Car 1 Car 3
Member 1 Member 2
Car 2
Who makes the decisions?
Transportation Engineering Laboratory, Hiroshima University 39-25
2. Methodological issues
Multi-linear type
ni i'i
n1i
)uuww(uwGUFi'ii'iii
Iso-elastic type
i
1iiuw
11
GUF
Group utility functions
Transportation Engineering Laboratory, Hiroshima University 39-26
ni i'i
n1i
)uuww(uwGUFi'ii'iii
1xx to Subject
xxU Maximize
21
21
0xxL
0xxL
)xx1(xxL
12
21
2121
2/1xx 21
i'iuu can be used to reflect household members’
concern for achieving equality of utilities
2. Methodological issues
Multi-linear type of group utility functions
Transportation Engineering Laboratory, Hiroshima University 39-27
(1) Additive-type utility function
(2) Compromise-type utility function
(3) Capitulation-type utility function
n1i iiuwGUF
n1i i nuGUF
ii' i'1
in
1i ii
n1i ii
u)1n(u,uwGUF
uwGUF
2. Methodological issues
Special cases ofmulti-linear household utility functions
Transportation Engineering Laboratory, Hiroshima University 39-28
i
1iiua
11
HUFMaximize
α → ∞ Max{minimum utility}
α >1 Max{small utility}
α → 1 Maximum Average
α =0 Average Maximum
α <0 Max{large utility}
I,...,2,1i|uminmaxHUF i
iwi iuHUF
i iiuwHUF
2. Methodological issues
Iso-elastic type of group utility functions
Transportation Engineering Laboratory, Hiroshima University 39-29
2. Methodological issues
Similarity and dissimilarity
Multi-linear type
ni i'i
n1i
)uuww(uwGUFi'ii'iii
Iso-elastic type
i
1iiuw
11
GUF
Comparisons of multi-linear andiso-elastic group utility functions
Transportation Engineering Laboratory, Hiroshima University 39-30
< Iso-elastic Group Utility Function >
3. Development of discrete Choice Model with inter-agency interaction
'j i1
'hij'hij
i1
hijhij
hjvw
11
exp
vw1
1exp
P
hji
1hijhij
i
1hijhij vw
11
uw1
1GUF
G_MNL model
Transportation Engineering Laboratory, Hiroshima University 39-31
< Multi-linear Group Utility Function >
j i 'i j'hij'ihijiji hijij
i 'i j'hij'ihijiji hijijhj vwvwvwexp
vwvwvwexpP
3. Development of discrete Choice Model with inter-agency interaction
hji 'i j'hij'ihijiji hijij vwvwvwGUF
G_MNL model
Transportation Engineering Laboratory, Hiroshima University 39-32
3. Development of discrete Choice Model with inter-agency interaction
G_NL model
'm'm'm
mm
'dm'd'd
dmdmm|ddm )'vv(e
)'vv(e)vv(e
)vv(ePPP
10and))vv(eln('v'd
m'd'dm
Transportation Engineering Laboratory, Hiroshima University 39-33
HouseholdHousehold
Social network
The second car
The first carBuy?
Buy what car?
New or used car
Use
ScrapRenewal
Buy?
Buy what car?
Use
ScrapRenewal
Future expectation
Analysis framework of household car ownership and use
G_MNL
G_NL
Transportation Engineering Laboratory, Hiroshima University 39-34
4. Summary of survey data
Hiroshima Region
Survey Area
Transportation Engineering Laboratory, Hiroshima University 39-35
4. Summary of survey data
Survey Area
Transportation Engineering Laboratory, Hiroshima University 39-36
4. Summary of survey data
Car46%
Transit28%
Motor cycle7%
Walk/bicycle19%
3,4times/week
15%
1,2times/week
15%
3,4times/mon.
4%
Almosteveryday
61%
severaltimes/year
2%
1,2times/mon.
3%
Car use frequency
Modal share
Survey Results
Transportation Engineering Laboratory, Hiroshima University 39-37
4. Summary of survey data
0% 20% 40% 60% 80% 100%
LEV
Other cars
Previous car just before buying the current car
Current car
<= 660cc
660cc~1000cc
1001cc~1500cc 1500cc~2000cc
2001cc~2500cc
>=2500cc
Survey Results
Transportation Engineering Laboratory, Hiroshima University 39-38
5. Estimation results and discussions
G_MNL model
Transportation Engineering Laboratory, Hiroshima University 39-39
5. Estimation results and discussions
The first car
Head ofHousehold
Other member
<=1500cc
> 1500cc
genderage -job -license
main user wifegenderage -job -license
v11 v21
w11
car price income
Inter-dependency ?
× 1-w11 ×+
Heterogeneity
G_MNL model
Transportation Engineering Laboratory, Hiroshima University 39-40
5. Estimation results and discussions
G_ NL model
Transportation Engineering Laboratory, Hiroshima University 39-41
5. Estimation results and discussions
The first car
Head ofHousehold
Other member
<=1500cc
> 1500cc
gender +age +joblicenseincome -
main user childgender +age +joblicenseincome -
v11 v21
w11 car price +
Inter-dependency -
× 1-w11 ×
The second car
<=1500cc
> 1500cc
gender +age +joblicenseincome -
main user childgender +age +joblicenseincome -
V12 v22
w12 car price +
Inter-dependency -
× 1-w12 ×
Inclusive value (0,1)
McFadden’s Rho-squared=0.4457
Sample size = 114
G_NL model
Transportation Engineering Laboratory, Hiroshima University 39-42
Conclusions andFuture Research Issues
1. Development of a new class of discrete choice models with inter-agency interaction (G_MNL, G_NL models) Multi-linear group utility Iso-elastic group utility
• Estimation of other types of G_models• Comprehensive model system for household car
ownership and use incorporating the influence of group decision-making mechanisms