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Ac#vity Opportuni#es and Changing Travel Pa9erns: A case of Developing Na#ons

Varun Varghese| Under the supervision of Prof. Arnab Jana

26th September, 2015| Early Bird Session| 14th Behavior Modeling Workshop in TransportaJon Networks |The University of Tokyo

Contents •  Pubic transport crowding (A case of Ahmedabad city)

•  Measuring crowding •  Public percepJon of crowding •  Cost of crowding

•  AcJvity-‐travel behavior in Mumbai •  IntroducJon •  Research gaps •  Research objecJves •  Preliminary findings for Mumbai •  Ongoing work

•  Regional travel behavior (A case of inter-‐regional trips in India) •  DesJnaJon choice •  Mode choice

2

Pubic transport crowding (A case of Ahmedabad city)

India Gujarat

Ahmedabad

3

PopulaJon-‐ 5.6 million Area-‐ 464.14 sq.km

Public transport systems and crowding

4

Objec#ve measures of crowding

Average count-‐ 4.31 standing pax/m2 (4.54 for AMTS, 3.62 for BRTS) Higher during morning peak Crowding peak – 8.32 standing pax/m2

5

Subjec#ve measures of crowding

•  Average increase of 18.49 %

•  Some routes as high as 48%

•  PercepJon dependent on Jme of day, no. of choices, type of service, personal characterisJcs

6

Generalized cost

𝐺𝑒𝑛𝑒𝑟𝑎𝑙ized 𝐶𝑜𝑠𝑡 (𝑐𝑜𝑚𝑓𝑜𝑟𝑡)= 𝑝↓𝑖 +𝑤𝑡↓𝑖 𝑇↓𝑚 

-‐ 10.00 20.00 30.00 40.00 50.00

Generalized cost vs Out of pocket cost

Gc (र) Pi (र)

7

Adapted from Haywood and Koning (2013)

Cost of crowding

Sketch by: Shubhadeep Sengupta

-‐

10.00

20.00

30.00

40.00

1.52 1.00 1.10 1.20 1.30 1.40 1.50 1.60

GC-‐AMTS (र)

GC-‐AMTS (र)

-‐

10.00

20.00

30.00

40.00

50.00

1.32 1.00 1.10 1.20 1.30 1.40 1.50 1.60

GC-‐BRTS (र)

GC-‐BRTS (र)

8

Ac#vity-‐travel behavior in Mumbai

India

Maharashtra Mumbai

9

PopulaJon-‐ 12.5 million Area-‐ 603 sq.km

Ac#vity-‐travel behavior in Mumbai-‐ An Introduc#on Time

Space

H

W

W F

FL

LS

H

H

W

F

L

S

Home

Work-‐ Mandatory

Social connecJon-‐ Leisure

Cinema-‐ Leisure

Shopping-‐ Maintenance Travel-‐ Mandatory

Travel-‐ Leisure

Travel-‐ Maintenance

AcJvity Jme-‐ Mandatory

AcJvity Jme-‐ Leisure

AcJvity Jme-‐ Maintenance

Adapted from Jme-‐space prism developed by Hagerstrand (1970) 10

0

20

40

60

80

100

120

<5k 5k-‐7.5k 7.5k-‐10k 10k-‐20k >20k

Income wise distribuJon of acJvity purposes

Work Shopping School Social visit Entertainment

Health Personal Return to home Other

Data source-‐ Baker et. al (2005)

Travelling pa9erns in Mumbai: Descrip#ves

11

0

20

40

60

80

100

120

140

160

180

Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 6

Commute Jme (mins)

<5k 5k-‐7.5k 7.5k-‐10k 10k-‐20k >20k

Travelling pa9erns in Mumbai: Descrip#ves

Data source-‐ Baker et. al (2005) 12

Changing pa9erns

Data source: ITU (2014)

0.00 20.00 40.00 60.00 80.00

ICT in India

Internet Mobile Phone

© yourstory.com

13

Poten#al effect on travel behavior

H

W

W F

FL

LS

H

H W

W

Time

Space

S H

W

W L

LH

Use of a service which provides informaJon

Stays connected online Online JckeJng

Orders grocery home

W

W

LS

H

L

S

Use of ICT Low capability

Change of spaJal

structure

Socioeconomic factors HH size, relaJonships, gender, age, level of educaJon, vehicle ownership, type of housing, marital status, type of occupaJon, HH/individual income.

Spa/al factors Access to job, ameniJes (such as school hospital etc.). Distance to job centre, jobs to populaJon raJo.

ICT use

Use of smartphones, internet connecJvity, types of ICT based services used, in-‐home and out of home ICT use.

14

Research gaps & Idea#on

Discre#onary ac#vi#es like leisure etc.

(including social trips)

ICT use

Use of smartphones, internet connec#vity, types of ICT based services used, in-‐

home and out of home ICT use.

Socio-‐economic Parameters

HH size, rela#onships,

gender, age, level of educa#on, vehicle ownership, type of housing, marital status, type of occupa#on, HH/individual income.

Mandatory Ac#vi#es like

work, school etc.

Travel #me, mode of travel, mul#ple use of #me, travel #me ra#o, cost of travel, comfort, in-‐home #me spent,

subs#tu#on, complementarity, or modifica#on.

Spa#al parameters

Access to job, ameni#es (such as school hospital etc.), and public transport modes. Distance to job centre, jobs

to popula#on ra#o, neighborhood density, land rent, house rent, wage paid by business firms, no. of sub-‐

centres etc

Maintenance Ac#vi#es like daily shopping, health etc.

15

Research Objec#ves For a society with exis/ng disparity, travel contributes to produc/vity and individuals aren’t just looking to reduce travel but are looking for be=er access to different opportuni/es. In such a scenario, the effects of different endogenous and exogenous variables (pertaining to spa/al change and ICT use) on travel will vary based on the purpose of ac/vi/es and the socio-‐economic characteris/cs of individuals.

a)  To idenJfy network factors which affect residenJal choice at a local level in developing naJons taking the case study of Mumbai.

b)  To evaluate the importance of travel Jme savings for different socio-‐economic groups. c)  Comprehensively model travel behavior adopJng both spaJal parameters and parameters

related to ICT use, along with socio-‐economic, individual and household parameters. d)  To idenJfy the change in Jme uses for different cohorts (e.g. age, gender etc.) based on the

above menJoned parameters. e)  To evaluate the concept of value of access in context of a developing country like India,

succinctly idenJfying the parameters that can improve access to opportuniJes for a larger secJon of society.

f)  To suggest policy recommendaJons related to spaJal change and ICT use, which can improve the overall access to acJvity opportuniJes in a city. 16

Real estate pricing and transport network

K/E

H/EH/W

G/N

Selection of wards Creation of price analysis zones

Select best fiited model (least AICc

and high adjusted R2)

Generate local surfaces

If satisfactory

No

Creation of network dataset

Select the model

Select the model

No1)model performance 2)each explanatory

variable 3)model significance4)stationarity5)model bias 6)residual SAC

Satisfies 6 checks

Run GWR

Run OLS(Consider all

variables)

Varghese, V., Sarkar, S., Bardhan, R., Velaga, N. & Jana, A. (2015). Transport network characterisJcs and real-‐estate undercurrents: The effect of spaJal nonstaJonarity on property pricing in Mumbai. Paper accepted for presentaJon at the 3rd Conference of the TransportaJon Research Group of India (CTRG), Kolkata, India. 17

Access to train stations Access to parking Access to bus stands Access to taxi stands

Access to schools Access to shopping malls Access to business nodes

Access to train stations Access to shopping malls Access to business nodes

Access to train stations Access to parking Access to bus stands Access to taxi stands

Access to schools Access to shopping malls Access to business nodes

Effect of transport network characteris#cs on real estate prices-‐ Results

ResidenJal

Commercial

Office

Model parameters

Residential

Distance to nearest parkingDistance to nearest bus stationDistance to nearest taxi standDistance to nearest schoolDistance to nearest mall Distance to nearest business node

CommercialDistance to nearest mall Distance to nearest business node

Office

Distance to nearest train stationDistance to nearest parkingDistance to nearest bus stationDistance to nearest taxi standDistance to nearest schoolDistance to nearest mall Distance to nearest business node

Red color imply negaJve associaJon

18

Effect of transport network characteris#cs on real estate prices-‐ Concluding discussions

Residential Commercial Office

•  Real estate market is influenced by speculaJon, which is largely a local phenomenon.

•  Distance to train staJons negaJvely influenced residenJal property prices at Bandra-‐Kurla complex and distance to bus stops had a severe negaJve impact on housing prices in Dharavi, Dadar and Andheri.

•  Distance to schools also have negaJvely influenced both residenJal and office property prices, while the distance to shopping malls and business districts have emerged as a significant factor in esJmaJng property prices for all different types land use.

•  A strong correlaJon between office and residenJal prices hint towards the willingness of people to stay near their workplaces. 19

Travel #me savings or the value of access-‐ case study of Mumbai-‐ Concept

When people are less capable to enjoy “beings and doings” which add value to life, then people a;ach more importance to the produc=on aspects of travel, and gradually put more value on the consump=on aspects of travel with the increase in their capability.

1. Travel #me is significantly related to individual capability and is lower for less capable

2. The variance of travel #me, indica#ng the degree of freedom of movement, has posi#ve associa#on with individual capability

Chikaraishi, M., Jana. A., Bardhan, R., Varghese, V., Fujiwara, A. RevisiJng travel Jme in Mumbai: the value of Jme saving or the value of access? Paper submiqed at the 95th TRB annual conference. 20

Travel #me savings or the value of access-‐ case study of Mumbai: Study area and data collec#on

Type of housing Individuals Households

MIG 48 22

Slum 58 23

SRA 52 28

Total 158 73

21

Travel #me savings or the value of access-‐ case study of Mumbai: Results and discussion

•  The mean capability and travel Jme of individuals from MIG housing was found to be significantly higher than those of Slum and SRA.

•  The variance in travel Jme increased with the capability of the individual

•  Individuals with higher capability had the ability to spend more Jme to discreJonary acJviJes, whereas people in the lower order of capability were constrained to spend more Jme in mandatory acJviJes.

•  MIG have more flexible mode choices whereas other groups rely more on walking.

•  Travel Jme savings would substanJally unde resJmate the benefi t o f t he infrastructure investment.

•  Exploring the concept of value of access w.r.t. spaJal policies and ICT use 22

On going work

0% 20% 40% 60% 80% 100%

Smart phone/Internet use vs housing type

MIG SRA Slum 0% 10% 20% 30% 40% 50% 60% 70%

Smart phone/Internet use vs gender

Male Female

23

On going work

0% 10% 20% 30% 40% 50%

Online JckeJng

e-‐shopping

raJng app (complimentarity)

Social networking apps

Cab services

Games

Transport informaJon

Type of services used

0% 10% 20% 30% 40% 50%

Reading Listening to music

Uses internet Gets bored

Window gazing Sleeping

Playing games EaJng

Working Talking to other passengers

Time use while traveling

24

Inter-‐region travel in India-‐ Des#na#on choice

Upsurge in economic acJviJes

PolarisaJon of faciliJes in urban areas Regional disparity

leading to pilgrimage trips

increased social trips

Trips due to healthcare & other needs

“to analyse regional travel paqerns in India by studying social, health, and pilgrimage trips” This might be significant to (1) Beqer understand travel with respect to the exisJng disparity in infrastructure provisioning and economic opportuniJes (2) Analyse the purpose that prompted the travel acJvity, (3) CharacterisJcs of the trips based on mode used, duraJon of the trip and spaJal locaJon of the desJnaJon, and (4) Policy implicaJons related to long distance travel

MigraJon

SaJsfacJon enhancement

Gaps in infrastructure

Bardhan, R., Varghese, V., & Jana, A. (2015). Analyzing Regional Travel Patterns in India: Disaggregated Analysis of Social, Health and Pilgrimage Trips. Journal of the Eastern Asia Society for Transportation Studies (in press)

Destination within the district

Des/na/on outside the district but within the state

Des/na/on outside the state but within the country

Healthcare trips

Conceptual Framework

26

q  Is there any significant difference in travel paqerns with respect to ‘within district’, ‘outside district but within state’ & ‘beyond district’?

q  On what factors do long distance travel depend in India?

q  “Clustering of opportuniJes/infrastructure might hold the key to longer distance trips in India”

Research methodology

27

NSS data on domesJc tourism

MNL models Outcome variable: Trip desJnaJon

ESDA for social, health & pilgrimage trips Unit of analysis: District

MNL for overnight trips

MNL for sameday trips

Local Moran’s I in the type of trips viz. Social, health and pilgrimage trips.

Policy implicaJons, discussions and future scope


Healthcare trips

O/N trips (Findings)

28

Des/na/on outside the district but within the state Number of HH members in the trip (-‐) Number of places visited (+) Mode: Bus(+), Train (+), Own (+) Time of year: July to Sept (-‐) Purpose: Social (-‐), Health(-‐), Pilgrimage (+) Type of stay: Hotel (+), Friends (-‐)

Des/na/on outside the state but within the country Number of HH members in the trip (-‐) Number of places visited (+) Mode: Bus(+), Train (+) Time of year: April to June (-‐), July to Sept (-‐) Purpose: Social (-‐), Health(-‐), Pilgrimage (+)


Des/na/on outside the district but within the state Number of HH members in the trip (+) Number of places visited (+) Mode: Bus(+), Train (+), Own (+) Time of year: July to Sept (-‐) Purpose: -‐ Social (+), Pilgrimage (+) Type of stay: Hotel (+), Friends (+)

Des/na/on outside the state but within the country Number of HH members in the trip (+) Number of places visited (+) Mode: Train (+), Own(-‐) Purpose: Social (-‐), Pilgrimage (+)

Healthcare trips

Sameday trips(Findings)

29

I= 0.297

I= 0.147

I= 0.338

I= 0.158

Clustering and Spa#al Autocorrela#on

I= 0.01923

I= 0.0596

I= 0.097

I= 0.059

I= 0.2617

I= 0.207

I= 0.142

I= 0.082

Social trips

Pilgrimage trips

Health trips

Discussions

•  Lack of employment opportuniJes and other allied services such as educaJon, force people from rural areas to migrate to urban areas. •  Current healthcare planning in India hierarchically allocates healthcare faciliJes based on certain populaJon thresholds, which creates a lopsided distribuJon of sophisJcated health centres in urban areas. •  Study provides the basis for travel induced infrastructure delivery planning. Transport policies reducing impedances towards social and pilgrimage acJviJes, while provisioning of infrastructure to reduce the need for travelling for health acJviJes can subsequently lead to the improvement of quality of life.

31

ありがとうございます

You can reach me at [email protected] or [email protected] or hqps://twiqer.com/varunvarghese

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