Technology in South Korea to enhance transport. Presented by Gyeng Chul Kim from KOTI, Korea's Transport Institute at Transforming Transportation 2014.
Role of technology enhancing transport Korea’s case - Gyeng Chul Kim - Korea Transport Institute (KOTI) - transforming transportation 2014 - EMBARQ The World Bank
Technology in South Korea to enhance transport. Presented by Gyeng Chul Kim from KOTI, Korea's Transport Institute at Transforming Transportation 2014.
Role of technology enhancing transport Korea’s case - Gyeng Chul Kim - Korea Transport Institute (KOTI) - transforming transportation 2014 - EMBARQ The World Bank
Presentation by Prof. Meng Xu & Dr Susan Grant Muller, presented at TRB 2015.
www.its.leeds.ac.uk/people/m.xu
www.its.leeds.ac.uk/people/s.grant-muller
http://pressamp.trb.org/aminteractiveprogram/Program.aspx
Case for smart transportation, detailing the catalysts for change and outlining the strategic imperatives required for success. Case studies reflect how a new approach makes transportation smarter.
The presentation provides an overall view of the urban transportation market in India. The presentation provides glimpse of development in different cities. It also tries to highlight the growth of ITS and AFCS market and the strategy of three key global players for India. You may send your feedback on jaaaspal@yahoo.com.
Presentation by Professor Mark Wardman delivered to an International Transport Workshop: Railway Transport Economics organised by Argentine Railways, June 2014.
New Generation Transport (NGT) www.ngtmetro.com
presentation by Louise Porter & Tom Hacker, delivered to postgraduate students at the Institute for Transport Studies (ITS) University of Leeds, UK. 27 November 2014
JnNURM Bus Financing - Delhi ExperienceJaspal Singh
This presentation describes the scheme of Bus Financing launched by Ministry of Urban Development and share the experience of Delhi.
A deep insight into the requirement of JnNURM funding requirement.
External seminar given at the Institute for Transport Studies (ITS), University of Leeds, on 21 November 2013.
Presented by Claire Sheffield from Transport for London (TfL) who leads TfL’s behavioural change unit.
Presentation includes the creative use of secondary data, collecting primary data using SP/SI and developing your own bespoke models, with a strong practical focus.
Guest presentation Dr Chikage Miyoshi, April 2015.
www.cranfield.ac.uk/about/people-and-resources/academic-profiles/satm-ac-profile/dr-chikage-c-miyoshi.html
www.its.leeds.ac.uk/courses/masters/itslectureseries
Ppp for solving public transport woes in indiaAmit Jain
The public transport in most of the cities are dependent on buses, auto rikshaws, cycle rikshaws which are not able to meet the demand, prone to accidents, delays & traffic jams. The cities need to create an efficient and affordable public transport services. The private sector may be invited through PPP to develop an integrated public transport system in a city. The private sector may charge an appropriate user fee (fare) from the users and earn revenue from commercial activities like advertising, renting & leasing of commercial spaces etc to cover his capital and recurring cost.
Presentation by Prof. Meng Xu & Dr Susan Grant Muller, presented at TRB 2015.
www.its.leeds.ac.uk/people/m.xu
www.its.leeds.ac.uk/people/s.grant-muller
http://pressamp.trb.org/aminteractiveprogram/Program.aspx
Case for smart transportation, detailing the catalysts for change and outlining the strategic imperatives required for success. Case studies reflect how a new approach makes transportation smarter.
The presentation provides an overall view of the urban transportation market in India. The presentation provides glimpse of development in different cities. It also tries to highlight the growth of ITS and AFCS market and the strategy of three key global players for India. You may send your feedback on jaaaspal@yahoo.com.
Presentation by Professor Mark Wardman delivered to an International Transport Workshop: Railway Transport Economics organised by Argentine Railways, June 2014.
New Generation Transport (NGT) www.ngtmetro.com
presentation by Louise Porter & Tom Hacker, delivered to postgraduate students at the Institute for Transport Studies (ITS) University of Leeds, UK. 27 November 2014
JnNURM Bus Financing - Delhi ExperienceJaspal Singh
This presentation describes the scheme of Bus Financing launched by Ministry of Urban Development and share the experience of Delhi.
A deep insight into the requirement of JnNURM funding requirement.
External seminar given at the Institute for Transport Studies (ITS), University of Leeds, on 21 November 2013.
Presented by Claire Sheffield from Transport for London (TfL) who leads TfL’s behavioural change unit.
Presentation includes the creative use of secondary data, collecting primary data using SP/SI and developing your own bespoke models, with a strong practical focus.
Guest presentation Dr Chikage Miyoshi, April 2015.
www.cranfield.ac.uk/about/people-and-resources/academic-profiles/satm-ac-profile/dr-chikage-c-miyoshi.html
www.its.leeds.ac.uk/courses/masters/itslectureseries
Ppp for solving public transport woes in indiaAmit Jain
The public transport in most of the cities are dependent on buses, auto rikshaws, cycle rikshaws which are not able to meet the demand, prone to accidents, delays & traffic jams. The cities need to create an efficient and affordable public transport services. The private sector may be invited through PPP to develop an integrated public transport system in a city. The private sector may charge an appropriate user fee (fare) from the users and earn revenue from commercial activities like advertising, renting & leasing of commercial spaces etc to cover his capital and recurring cost.
A presentation depicting what are the advantages of publicly owned and operated transportation system over privately owned and operated transportation system with suitable case studies of a few big cities.
Professor Amal Kumarage, Endeavour Executive Fellow, presented his research on Transport Planning as part of the SMART Seminar Series on Tuesday, 25th November 2014.
Hiroaki Suzuki presents on land value capture and the ways that this innovative financing mechanism can be used to fund transit-oriented development, with the ultimate goal of enhancing urban sustainability.
Transforming Transportation 2015: Smart Cities for Shared Prosperity is the annual conference co-organized by the World Resources Institute and the World Bank.
Attached is the proposal for branding on Kochin Metro.
Place your advertisement on kochi Metro via Metro Wraps or Inside metro branding via stickers and digital screens...
For best quotes ping us at +91-9953847639
What PRASA is doing to improve the passenger rail service in the Western CapeTristan Wiggill
A presentation by Mr Eddie Chinnappen (GM in the office of the GCEO: PRASA) at the Transport Forum special interest group proudly hosted by TCT in Cape Town on 10 December 2015.
The theme for the event was: "Encouraging Public Transport". The topic of the presentation was: "What PRASA is doing to improve the passenger rail service in the Western Cape".
More like this on www.transportworldafrica.co.za
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...BRTCoE
Camila Balbontin is a Postgraduate Research Fellow at the Institute of Transport and Logistics Studies (ITLS) of University of Sydney. In February 2018, she completed her PhD under the supervision of Professor David Hensher where she focused on integrating decision heuristics and behavioural refinements into travel choice models. She was awarded the ITLS prize for Research Excellence in Transport or Logistics 2017. Camila also holds a bachelor degree in the field of Civil Engineering with a diploma in Industrial Engineering and in Transportation and Logistics from Pontificia Universidad Católica de Chile. She did her MSc degree at the same university under the supervision of Professor Juan de Dios Ortúzar. Her MSc thesis estimated the valuation of households and neighbourhood attributes in the centre of Santiago.
As a Postgraduate Research Fellow, her main focus is choice modelling and travel behaviour. She is currently working on projects related to the BRT Centre of Excellence, business location decisions, hybrid modelling, value uplift, among others.
Working Paper - http://sydney.edu.au/business/itls/research/publications/working_papers
www.nhtnetwork.org/cqc-efficiency-network/home
The CQC Efficiency Network is a collaborative venture between ITS researcher Dr Phill Wheat and leading
performance and benchmarking company measure2improve (m2wi). Dr Wheat has used funding from the EPSRC
Impact Acceleration Account (IAA) to refine the tools to support m2i in developing the fast growing network. The IAA is an institutional award funded by EPSRC to help speed up the contribution that engineering and physical science research make towards new innovation, successful businesses and
the economic returns that benefit UK plc.
Posters summarizing dissertation research projects - presented by MSc students at the Institute for Transport Studies (ITS), University of Leeds, April 2017. http://bit.ly/2re35Cs
www.its.leeds.ac.uk/courses/masters/dissertation
Cutting-edge transport research showcased to Secretary of State during the event to officially re- open the Institute building www.leeds.ac.uk/news/article/4011/cutting-edge_transport_research_showcased_to_secretary_of_state
DR STEPHEN HALL, PROFESSOR SIMON SHEPHERD, DR ZIA WADUD; UNIVERSITY OF LEEDS, IN COLLABORATION WITH FUTURE CITIES CATAPULT
Also see https://theconversation.com/five-reasons-why-you-might-be-driving-electric-sooner-than-you-think-71896
Presentation Fiona Crawford - winner of the Smeed prize for best student paper at the UTSG Conference 2017
www.its.leeds.ac.uk/people/f.crawford
www.utsg.net/web/index.php?page=annual-conference
Efforts to reduce the emissions from car travel have so far been hampered by a lack of specific information on car ownership and use. The Motoring and vehicle Ownership Trends in the UK (MOT) project seeks to address this by bringing together new sources of data to give a spatially and disaggregated diagnosis of car ownership and use in Great Britain and the associated energy demand and emissions.
Data from annual car M.O.T tests, made available by the Department for Transport, will be used as a platform upon which to develop and undertake a set of inter-linked modelling and analysis tasks using multiple sources of vehicle-specific and area-based data. Through this the project will develop the capability to understand spatial and temporal differences in car ownership and use, the determinants of those differences, and how levels may change over time and in response to various policy measures. The relationship between fuel use and emissions, and the demographic, economic, infrastructural and socio-cultural factors influencing these will also be tested.
Consequently, the MOT project has the potential to transform the way in which energy and emissions related to car use are quantified, understood and monitored to help refine future research and policy agendas and to inform transport and energy infrastructure planning.
www.its.leeds.ac.uk/research/featured-projects/mot
The University's Annual Review covering the 2015-16 academic year. This new publication gives an overview of some of the most important initiatives and activities that the University has undertaken recently and a sense of the scale of the ambition for the future.
www.its.leeds.ac.uk/people/c.calastri
Social networks, i.e. the circles of people we are socially connected to, have been recognised to play a role in shaping our travel and activity behaviour. This not only has to do with socialisation being the purpose of travel, but also with enabling mobility and other activities through the so-called social capital. Another theme in the literature connecting social environment and travel behaviour is social influence, i.e. the investigation of how travel behaviour can be affected by observation or comparison with other people. Research about the impact of social influence on travel choices is still at its infancy. In this talk, I will give an overview of how choice modelling can be used to investigate the relationships between social networks, travel and activities. I will touch upon work that I have done so far, in particular I will describe my applications of the Multiple Discrete-Continuous Extreme Value (MDCEV) model to frequency of social interactions as well as to allocation of time to different activities, taking the social dimension into account. In these studies, I make use of social network and travel data collected in places as diverse as Switzerland and Chile. I will also discuss ongoing work making use of longitudinal life-course data to model the impact of family of origin and the “mobility environment” people grew up in on travel decision of adults. Finally, I will outline future plans about modelling behavioural changes due to social influence using the smartphone app travel data that are being collected in Leeds within the “Choices and consumption: modelling long and short term decisions in a changing world” (“DECISIONS”) project.
Shigeki Oxawa is Associate Professor at the Department of Integrated Informatics, Daido University and part-time Lecturer in Transport Economics at Hosei University. He is a transport economist with a strong interest in transport policy. He is currently an academic visitor at Leeds University (April 2016-March 2017) working in the area of intermodal transport (with a focus on rail freight transport) and in turn track access charges.
Abstract: In the national railway revolution in Japan, the passenger division was divided into 6 companies by regions. They operate trains and own/manage the rail track (vertical integration system). On the other hand, vertical separation was introduced into freight companies, therefore, freight companies have to access rail track owned/managed by passenger companies. The Japanese regulator regards track access transactions between passenger companies and freight companies as private business.
In the vertical separation system, freight companies cannot get access to the slots required and efficient allocation of rail track cannot be achieved. The vertical separation is a very significant issue in railway policy and freight transport policy in Japan. In the presentation, causes and possible solutions to the issue will be shown.
Shigeki is Associate Professor at the Department of Integrated Informatics, Daido University and part-time Lecturer in Transport Economics at Hosei University. He is a transport economist with a strong interest in transport policy. He is currently an academic visitor at Leeds University (April 2016-March 2017) working in the area of intermodal transport (with a focus on rail freight transport) and in turn track access charges. He has 20 years of experience in research and teaching.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
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Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
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As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
"𝑩𝑬𝑮𝑼𝑵 𝑾𝑰𝑻𝑯 𝑻𝑱 𝑰𝑺 𝑯𝑨𝑳𝑭 𝑫𝑶𝑵𝑬"
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Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
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➢ 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
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3. Background
• Mass transit railway services
– Safe, improve mobility, avoid congestion, etc.
– Ideal if financially sustainable, with affordable fares
and expedient quality
– The case of Hong Kong: all rail services are provided
under prudent commercial principles, renowned for
high quality and profitability, often considered as a
benchmark for urban rail transit projects
Public Transport in Hong Kong
• Public Transport in HK involves a multi‐modal
network
– Railways (MTR, LRT)
– Franchised Buses (over 600 routes)
– Red and green Minibuses (hundreds of routes)
– Taxi, ferries, tram, peak Tram
• All modes are financially sustainable without
direct government subsidy
6
6. Supply of transit services
Hong Kong London Singapore
Rail car-km (million) 255 414 89
Bus vehicle-km (million) 513 450 299
Population (million) 6.9 7.4 4.2
Rail car-km per capita 37.0 56.3 21.0
Bus vehicle-km per capita 74.4 61.2 70.5
Combined rail car and bus vehicle-km per capita 111.4 117.5 91.5
% total passenger-km on mass public transit 82% 30% 47%
Source: Lo, H., S. Tang and D. Z.W. Wang. 2008. Managing the Accessibility on Mass
Public Transit: the Case of Hong Kong. Journal of Transport and Land Use, 1:2, 23-49.
Land‐use and Transport Policy in Hong Kong
1. The policy on land development
2. The Policy of Limiting Private Car Ownership and Usage
3. The Policy of Transit Service Coordination and
Protection (1980’s)
4. The Policy of Service Proliferation and Competition
(1990’s)
5. The Policy of Service Rationalization and Consolidation
(2000’s)
12
Source: Tang, S. and H. Lo. 2008. The Impact of Public Transport Policy on the Viability
and Sustainability of Mass Railway Transit – The Hong Kong Experience. Transportation
Research Part A, 42, 563- 576.
8. 15
Example: TKO new town
The total
development area
of TKO is about
10.05 km², with a
population of
around 350,000.
The average
density is 35,000
per km²
Policy of Limiting Private Car Ownership
and Usage
• Passenger car ownership: 56 per 1000 people; US: 439;
Singapore: 121; Chile: 118 (World Bank Data 2009)
• New private cars are subject to the first registration tax
from 35% to 100% of the vehicle cost
• High fuel tax: Unleaded gas in Hong Kong is ~ HK$15/liter
or RMB 6/liter
• Private car trips constitute 10% of total daily passenger
trips, as compared with 95% in the US.
16
9. Transit service coordination and protection
(1980s)
• Higher priority given to off‐street public transit
• Rapid development of rail transit services, with protection
against direct competition from other modes
• Allowed the creation of a win‐win situation; the Govt could
rely on the private sector to provide for services based on the
user‐pay principle without subsidy
• But later criticized as protecting the existing sizeable operators
and unable to motivate their service improvement
Service proliferation and competition
(1990s)
• Encourage “healthy” competition between modes
– Remove the protection policy for the rail mode
– Massive expansions of both rail and bus services
• This policy was initially welcome, but at the expense of:
– Congestion externality – oversupply of buses on profitable
corridors
– Financial difficulties for operators – the demand was spread
too thin due to oversupply of services
11. Rail transit development model in Hong Kong
Property
Developer
Fund, build and operate the
railway, and pay back dividend
Define legal framework, derive
policies, drive and monitor railway
development, and grant land for
property development
Share property
development profit
Form joint venture to develop
property
Contribute to
economic
growth
Regulate
land use
and town
planning
Railway
Company
Government
Costs and revenues of MTR
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
year
million
Total Operating Cost after depreciation
Total Operating Cost before depreciation
Total Income including property profit
Fare Revenue
Turnover
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
year
million
Total Operating Cost after depreciation
Total Operating Cost before depreciation
Total Income including property profit
Fare Revenue
Turnover
Fare Rev
Op cost aft
depreciation
Op cost bef
depreciation
Total inc
14. …modeled by an analytical framework
A general equilibrium Residents’ location and
travel choices
System optimization
Residential location
Workplaces
Travel modes
Travel routes
Government/Planners
(Planning perspective)
TS-DM strategies:
Network expansion and/or
Road pricing, etc.
To be decided…To achieve… Stakeholders
Housing provision Developers’ decision( )r
S
r
s
m
p
( ) ( )
( , )
a ay ρ
A general equilibrium framework
– Bid‐rent Process (who to rent to and the resultant rent)
• Based on residents’ willingness to pay
• Auction process
• Bid‐rent at different locations (expected maximum rent)
– Residential location Choice (which location to rent from)
• Location choice: location accessibility, attractiveness
• Travel choice: transportation cost
• Utility maximization
– Developer housing supply problem
• Bid‐rent at different locations
• Cost of housing supply
• Profit maximization
28
Sources:
• Ma, X. and H. Lo. 2013. On Joint Railway and Housing Development Strategy. 20th International
Symposium on Traffic and Transportation Theory (ISTTT) and Transportation Research Part B,
57, 451-467.
• Ma, X., Lo, H.K., 2012. Modeling transport management and land use over time. Transportation
Research Part B, 46 (6), 687-709.
15. Combined Residential Location
Choice and the Bid‐rent Process
29
High
Lowr1
rr
s1
ss
High
Low
WP
WP
WP
WP
High
Lowr1
rr
s1
ss
High
Low
CS
CS
Residents’
perspective
r: location r: locations: working place s: working place
Landowners’
perspective
Resident
Demand
Housing
Supply
• The two choice processes are proven to be consistent and
produce identical allocations
Bid-rent
Process
Residence
choice
Bid‐Rent Process
30
High
Lowr1
rr
s1
ss
High
Low
WP
WP
WP
WP
r: location
/
∙
∑ ∑ ∙
∙ /
Willingness-to-Pay (WP): for a location r
is expressed as:
s: working place
Landowners’
perspective
: utility index by setting
: Income of class k
: Utility level (Non-housing spending)
: Attractiveness of Housing Units,
e.g. lot Size, Age, etc.
: Generalized Travel Cost
/Accessibility
The number of resident occupied in
location r:
Housing
Supply
Resultant housing rent: is expressed as the
log-sum term, adjusted by the housing supply
at that location
1
∙ /
1
Expected Maximum
Willingness-to-pay
Supply Effect
17. Developer housing supply choice
• Developers’ decision on housing provision
– Under the principle of profit maximization
( )r
S
22
22
( )
( )
2'( )
'
exp( )
Pr , 0, 1
exp( )
r nn
r
r nn
r R
n
2 2 2r n r n r n
Hb
(0)
2( )
( ) ( )
2
, 0
Pr ,
r
r
r
S n
S
S n
Following a quasi dynamic structure
Profit
Benefit distribution among stakeholders
• The impact of transport supply and demand
management on the benefit of
– heterogeneous income groups of residents
– housing developers
• General conditions
– Single time period
– One OD pair
– Fixed housing supply
18. • Proposition – transportation supply
– Under conditions
• (H0): One OD pair r and s, households with multiple income groups k
• (H1): One travel route p, travel time reduced by ∆t<0 with investment cost BT
• (H2): Homogenous value of time, votk=vot>0
– Any travel cost reduction due to transport infrastructure
improvement, either in time‐based or money‐based formulation,
will lead to an equivalent increase in land or rental value
– Consumer surplus (household)
– Housing supplier surplus
Benefit distribution among stakeholders
• Proposition – transportation supply
– Under conditions
• (H0)‐ (H1)
• (H3): Heterogeneous value of time, vot1<vot2<…<votk
• (H4): Money‐based travel cost formulation
– Residents with higher incomes/higher values of time benefit
more from transport improvement as compared with residents
with lower incomes/ lower values of time
– Consumer surplus (household) Lowest Highest
– Housing supplier surplus
Benefit distribution among stakeholders
19. Benefit distribution among stakeholders
• Proposition – demand management
– Under conditions
• (H0)‐ (H1)
• (H3): Heterogeneous value of time, vot1<vot2<…<votk
• (H5): Time‐based travel cost formulation
– Residents with higher incomes/higher values of time benefit more
from demand management, e.g. increasing link toll, as compared
with residents with lower incomes/lower values of time
– Consumer surplus (households’) Lowest Highest
– Housing supplier’s surplus
• A quasi dynamic structure
– Different time adaptabilities of sub‐systems
• Residents’ travel behavior
• Residents’ location choice
• Housing investment
• Transport/rail infrastructure investment
– Implying that given a time period τ, residents’ location and travel
choices are made under a fixed land use and transport system
Shorter
Longer
General equilibrium formulation over time
20. The problem is formulated as an equivalent Nonlinear
Complementarity Problem (NCP)
i.e. to find such that and
where,
*
0Ζ *
( ) F Ζ 0 *T *
( ) Ζ F Ζ 0
( )
,
( )
2
( )
, , , , , ,
= , ,
, ,
rsk
p m
r
k
f r s m p k
S r n
b k
Ζ
( ) ( ) ( )
, ,
( ) ( ) ( )
2
( ) / ( ) ( )
Pr , , , , , ,
( )= Pr , ,
Pr , ,
rsk rsk rsk
p m p m
r r
r k r k
r
f q r s m p k
S S r n
S H k
F Ζ
General equilibrium formulation over time
( ) ( ) ( ) ( ) ( ) ( )
( , ) ( ) ( , ) ( ) ( , ) ( ) 0T H T H T HNPV dr R R dr B B dr M M
Maximize social welfare (consumer and producer surpluses)
Optimal transport management strategies
Transport Supply and Demand Management,
e.g. Rail link expansion and fare pricing
Under a time‐dependent network following a quasi dynamic structure
With cost recovery conditions
Producer surplus
System optimization
(τ) (τ)
a a
( ) ( )
ρ ,
Maximize SW ( , ) +rsk rsk
y
rs k
dr q CS NPV
22. • Overall system performance I
– Transport management strategies increase overall social welfare
– TS‐DM is generally better than DM alone
– (* transport investment includes both construction cost for new expansions and
maintenance cost for all highway links)
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
140.0%
Scenario 0 100.0% 100.0% 100.0% 0 100.0% 100.0% 100.0%
Scenario I 83.5% 107.1% 97.2% 100% 100.9% 107.8% 104.8%
Scenario II 97.4% 122.4% 98.4% 89% 96.1% 103.6% 102.2%
Travel time Travel cost
Consumers'
Surplus
Transport
investors'
profit*
Housing
developers'
profit
Producers'
surplus
Welfare
Results
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
140.0%
Scenario 0 100.0% 100.0% 100.0% 0 100.0% 100.0% 100.0%
Scenario I 83.5% 107.1% 97.2% 100% 100.9% 107.8% 104.8%
Scenario II 97.4% 122.4% 98.4% 89% 96.1% 103.6% 102.2%
Travel time Travel cost
Consumers'
Surplus
Transport
investors'
profit*
Housing
developers'
profit
Producers'
surplus
Welfare
• Overall system performance II
– Travel time reduced through both transport strategies
– TS‐DM is better than DM alone in congestion relief
– DM alone introduces higher travel costs
– Consumer surplus reduced
Results
23. • Overall system performance III
– The overall producers’ surplus increased
– (Producer’s surplus = Transport investors’ + Housing developers’)
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
140.0%
Scenario 0 100.0% 100.0% 100.0% 0 100.0% 100.0% 100.0%
Scenario I 83.5% 107.1% 97.2% 100% 100.9% 107.8% 104.8%
Scenario II 97.4% 122.4% 98.4% 89% 96.1% 103.6% 102.2%
Travel time Travel cost
Consumers'
Surplus
Transport
investors'
profit*
Housing
developers'
profit
Producers'
surplus
Welfare
Results
• Transport investment and Housing market
– Developer surplus increases monotonically with transportation
supply due to increasing housing rents
– Consumers may benefit or suffer from transportation supply
depending on the tradeoff between travel cost reduction and
increased housing rents
95%
100%
105%
110%
115%
120%
125%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Level of transport improvement
Performance
Housing revenue
Consumers' Surplus
Producers' surplus
Social welfare
Housing rev - Trans invest
Developer's surplus
Sensitivity analysis of transport supply
24. What about joint rail and property
development?
–To what extent one can exploit the synergy
between rail and property developments?
• Property development brings in rail patronage, hence
higher fare revenue
• Improved accessibility due to rail increases values of
properties
• To what extent property value increases can be used
to cross‐subsidize rail infrastructure development
47
Source: Ma, X. and H. Lo. 2013. On Joint Railway and Housing Development Strategy.
Transportation Research Part B, 57, 451-467. Presented at 20th International
Symposium on Traffic and Transportation Theory (ISTTT).
Joint railway and housing development
Profit function
1.2
rail( ) ( ) ( )Pr Pr
H HT T
rv rv rs v rv
H TC TO
v r rs
rv rs rv
v r
cp h
R R B B
q b B st b w
- The housing location
- The housing type
- The proportion of investing housing type in location
- The number of housing type invested in location ,
Pr
rv rv
rv
r
v
v r
v r (Pr )
- The railway fare between
- The operational headway
- The number of trains, ( )
r
r
v
s
cp
h
rs
st st hw
w
Housing revenue Rail revenue Housing cost Rail cost
25. Mathematical Program with Equilibrium
Constraints (MPEC)
1.2
Pr , ,
Maximizerv rs rs H HT T
hw cp
R R B B
( ) 0G Z
1Pr
r v
rv
, ,hw h rw wh s
, ,rs
cp c rp pc s
s.t. Gap function for the combined
equilibrium
Joint railway and housing development
• Proposition – Effects on Residents
– The travel costs of residents monotonically increase
with headway and fare
– Changes in railway investment, e.g. headway or fare,
do not change residents’ consumer surplus because
any decrease (increase) in transport cost is absorbed
by corresponding rent increase (decrease)
– A regressive effect also prevails, high income groups
gain more from transport service improvements
2
50
Joint railway and housing development
26. • Proposition – Effects on Rail + Property Developer
– Housing rents monotonically decrease with transport cost increases
(e.g. headway and fare)
– If rail is the only transport mode, the combined producer surplus
does not change with fare changes, due to the internal transfer
between property and fare revenue.
– In the presence of a multi‐modal network, the combined producer
surplus (housing and rail) monotonically decreases with fare.
Therefore, the joint developer has incentive to keep fare at a
reasonably low level to maintain producer surplus at a high level,
since gain from housing revenue offsets reduction in fare revenue
2
51
Joint railway and housing development
What about optimal housing supply: the
perspective of developer vs residents?
Assumptions:
• (H0): A linear network with two residential locations r connected in series to one
central CBD. Links 1 and 2 have fixed travel time. Homogeneous housing types are
to be developed in origin 1 and/or origin 2
• (H1): Homogeneous income class, e.g. votk = vot > 0
• (H2): Heterogeneous income class, e.g. two income class, votk1 > votk2
• Total Supply is fixed
– 1000
52
Fig. 1 Two Residential locations Network
Source: Ng, K.F. and H. Lo. 2015. Optimal Housing Supply in a Bid-Rent Equilibrium
Framework. Transportation Research Part B, 74, 62-78.
27. • Under (H0) and (H1)
• Instead of placing all 1000 units in origin 1, which is closer to CBD, the
developer places 200 units in origin 2. Although origin 2 has a higher
transport cost and therefore lower rent, doing so the rent in origin 1 will be
higher as the supply there is reduced from 1000 to 800. Revenue is
maximized when the marginal effects of the two are equal.
• The exact optimal allocation depends on the difference in travel cost, or beta
• At any optimal solution, more housing should be in origin 1 than in origin 2
• Create some housing shortage in origin 1
Developer optimal housing supply strategy
• Proposition: The optimal housing supply for developer:
∗
∙
exp ∙
exp ∙ exp ∙
∗
→
53
Transport
Cost Effect
Supply
Effect
No. of housing
units
Residents optimal housing supply strategy
• Proposition: The optimal housing supply for residents:
• Under (H0) and (H1)
• Concentrated Development (all development in origin 1 or 2)
• Concentrated development pulls down the rent dramatically
• Consumer surplus is then maximized
54
No. of housing
units
∗
→ 0
28. To analyze the performance of housing revenue and total consumer surplus when
housing supply in different locations change.
Assumptions:
• (H2): Two income classes: High and Low income, e.g. different vot’s and incomes
• The BPR congestion function is used to model links 1 and 2
Results:
• Vary with beta, scaling parameter, and the relative proportions of income groups
– Case 1: small beta. Choice becomes more random
– Case 2: large beta. Choice becomes more deterministic
55
Fig. 1 Two Residential locations Network
Residents optimal housing supply strategy:
sensitivity analysis
56
645000
647500
647500
650000
650000
650000
652500
652500
652500
655000
655000
655000
657500
657500
657500
657500
660000
660000
660000
660000
662500
662500
662500
665000
665000
667500
667500
670000
672500
The proportion of Supply in Origin 1
TheproportionofHighIncomeClassDemand
Total Housing Revenue (Large beta)
100 200 300 400 500 600 700 800 900
100
200
300
400
500
600
700
800
900
Maximum, less than 45 line
Housing Revenue
• When the number of high income
residents is high, say 700, the
optimal housing supply is to
provide housing which is slightly
less than the number of high
income resident, create shortage
for high income residents
• When the number of high income
resident is low, say 300, increasing
the housing supply will result in a
higher revenue
• Result is consistent with
Proposition 1
• It is not always good to put all
housing units in a convenient
locations, e.g. origin 1
Developer perspective (large beta)