1 September 2011 Airport Traffic Estimation Presentation for Karaikal Airports Private Limited
Mar 31, 2015
1
September 2011
Airport Traffic Estimation Presentationfor
Karaikal Airports Private Limited
2
This document does not carry any right of publication or disclosure to any other party. The information in this document has been compiled by Feedback Infrastructure Services Pvt. Ltd. (Feedback) based on various public domain sources, primary surveys and interviews and Feedback’s proprietary research.
This document is incomplete without reference to, and should be viewed solely in conjunction with, the oral briefing provided by Feedback. Neither this presentation nor any of its contents may be used for any other purpose without the prior written consent of Feedback
3
Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
4
Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
5
The proposed airport is located near city of Karaikal
The proposed airport site is located between the villages of Ponbethy, Puthakudy, & Varitchakudy in Nedungadu Commune
The airport aims to serve the traffic coming to religious and tourist locations near Karaikal town
Chennai, Madurai & Trichy are the three nearby airports serving the region at present
KARAIKAL
6
The proposed airport targets a small catchment area with very high travel rate
Catchment area of the airport would include
Parangipettai in North, Point Calimere in South, & Kumbakonam, Needamangalam, Alangudi, & Tippirajapuram in East
The catchment area spreads to approx.
80 km in North, 70 km in South, &56 km in East
Primary hinterlandSecondary hinterland
LEGEND:
KARAIKAL
7
Key traffic centres within the catchment area
S. No Location Type of location Distance from Karaikal*
1 Thirunallar Temple Religious 6 km
2 Thirukaddayur Religious 22 km
3 Nagapattinam Religious / Tourism 21 km
4 Chidambaram Temple Religious 64 km
5 Velankanni Church Religious 31 km
6 Nagore Dargah Religious 14 km
7 Mayiladuthurai Religious 39 km
8 Thiruvarur Religious 42 km
9 ONGC Field, Kuthalam Industrial 49 km
10 Marg port Industrial 12 km
11 Point Calimere Sanctuary Tourism 70 km
12 Poompuhar Religious / Tourism 25 km
13 Tranquebar Beach Tourism 14 km
* Distances from Karaikal city centre
8
Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
9
Identification of top incom e
segm ents for m ode shift
analysis
Calculation of route w ise
m ode shift probabilities
based on econom etric
analysis of m ode shift
survey data
Application of probabilities
on O D data to find potentia l
traffi c
Identification of top income
segments for mode shift
analysis
Calculation of route wise
mode shift probabilities
based on econometric
analysis of mode shift
survey data
Application of probabilities
on OD data to find potential
traffic
Approach to traffic potential estimation
Defining total passenger traffic in the region using all
modes of transport and on all traffic routes (OD)
Estimation of potential traffic
for the airport from base trafficTOP DOW N APPROACH
Consolidation of a ir traffi c of a ll a irports in the region
Finding corre lation of a ir traffi c w ith re levant
m acroeconom ic variables and se lecting the ones w ith
h igh im pact on traffi c
Projecting future traffi c in re lation to the se lected
variables
TOP DOWN APPROACH
Consolidation of air traffic of all airports in the region
Finding correlation of air traffic with relevant
macroeconomic variables and selecting the ones with
high impact on traffic
Projecting future traffic in relation to the selected
variables
PASSENGER SEGM ENTATION APPROACH
Segm enting total traffi c into local residents, NRI
travellers, & dom estic / fore ign tourists & finding the
segm ent sizes
Estim ate annual traffi c & prepare route & m ode w ise O D
m atrix based on econom etric surveys done at various
locations
PASSENGER SEGMENTATION APPROACH
Segmenting total traffic into local residents, NRI
travellers, & domestic / foreign tourists & finding the
segment sizes
Estimate annual traffic & prepare route & mode wise OD
matrix based on econometric surveys done at various
locations
BOTTOM UP APPROACH
O D & CVC studies / secondary data for key ra il / road
locations
M apping route & transport m ode w ise annual passenger
traffi c in the region
BOTTOM UP APPROACH
OD & CVC studies / secondary data for key rail / road
locations
Mapping route & transport mode wise annual passenger
traffic in the region
Realizable TrafficPotential TrafficBase Traffic Mapping
Projection of likely
traffic at the airportFinding the corre lation of
a irport traffi c share w ith
m acroeconom ic variables
Estim ating the share &
traffi c potentia l of Karaikal
a irport
Finding the correlation of
airport traffic share with
macroeconomic variables
Estimating the share &
traffic potential of Karaikal
airport
Com parison of
potentia l traffi c
num bers from the
three approaches
Selection of
potentia l traffi c
num bers based on
level of detail,
existing air traffi c
and experience
Route w ise analysis
to establish the
like ly traffi c on each
route
Realistic traffi c
estim ates for the
airport
Comparison of
potential traffic
numbers from the
three approaches
Selection of
potential traffic
numbers based on
level of detail,
existing air traffic
and experience
Route wise analysis
to establish the
likely traffic on each
route
Realistic traffic
estimates for the
airport
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1. Top Down ApproachPotential 3.35 Lac annual passengers or 918 / day in Yr 2014-15
Yr 1 Cargo Traffic (tons)Yr 1 Passenger Traffic (‘000)
- 500
1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000
3,047
226 335
4,009
4,894
Scenario 1 Scenario 2 Scenario 3
Passenger Traffic Projection (‘000)
Scenario 1 Low Scenario 2 Moderate Scenario 3 High -
50
100
150
200
250
300
350
400
178 190 203
140 145 150
318 335 352
Passenger Domestic Passenger InternationalPassenger Total
Scenario 1 Low Scenario 2 Moderate Scenario 3 High -
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
834 927 1,019
4,247 4,266 4,285
Cargo International Cargo Domestic Details
11
2. Bottom Up ApproachPotential 4.08 Lac annual passengers or 1,118 / day in Yr 2014-15
Yr 1 Passenger Traffic (‘000)
Passenger Traffic Projection (‘000)
12.38%
22.33%
12.64%7.37%
2.99%
10.46%
5.11%
14.86%
4.99%6.87%
Origin wise traffic contribution
ChennaiCoimbatoreTrichyMaduraiCochinTrivandrumHyderabadBangaloreMumbaiDelhi
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500 4,041
322 725
3,533
Optimistic Scenario Base Scenario
Optimistic Case Base Case - 50
100 150 200 250 300 350 400 450
232 223 195 185
427 408
Road Traffic Rail Traffic Total TrafficDetails
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3. Traveler Segmentation ApproachPotential 4.16 Lac annual passengers or 1140 / day in Yr 2014-15
Yr 1 Passenger Traffic (‘000)
Passenger Traffic Projection (‘000)
Segment wise Traffic Distribution
Details
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
3,431
4,120 Traffic (Base) Traffic (Optimistic)
Base Case Optimistic Case - 50
100 150 200 250 300 350 400 450 500
52 55 74 78
291 306
416 438
NRI Local PopulationTourist Traffic Total
12%
18%
21%4%
41%
3%
NRILocal ResidentsVelankanniNagoreThirunallarThirukadaiyur
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Through comparison of outputs of the three approaches, passenger segmentation approach selected as the indicator of potential traffic
Projected traffic through passenger segmentation approach lies between the other two approaches and is a more realistic assessment of the potential traffic for the AirportIn the initial years, the projected traffic lies above the other two approaches and then comes back to central position due to high GDP correlation in the top down approachThis approach is more granular, considers traffic on individual O-D pairs after taking into account passenger preferences and dynamics
- 500
1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 3,818
3,533
3,431
Top Down Bottom Up Passenger Categorization
2011
-12
2012
-13
2013
-14
2014
-15
2015
-16
2016
-17
2017
-18
2018
-19
2019
-20
2020
-21
- 50
100 150 200 250 300 350 400 450 500 550 600 650 700
226
329
664
Top DownBottom UpPassenger Categorization
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Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
15
Potential v/s Realizable Traffic – Base year 2011-12
Traveler Type Potential Traffic
After Trichy traffic adjustment
Realization factor
Realizable Traffic
Local residents 69,980 35,476 70% 24,833
NRI Travelers 51,737 51,737 75% 38,803
Velankanni 88,236 87,914 70% 61,540
Nagore 17,126 10,937 70% 7,656
Thirunallar 171,929 166,493 70% 116,545
Thirukadaiyur 13,354 13,354 70% 9,348
Pondicherry Traffic 416,012 3,650 100% 3,650
Total 412,362 365,911 262,375
Trichy TrafficAdjustment
Trichy is at distance of 150 km from Karaikal (3.5 hrs by Road and Rail) Due to short distance, taking a flight is infeasible in terms of time and cost factors i.e. time saved does not justify extra cost of flight hence any potential air traffic between Trichy and Karaikal is considered irrelevant
Realization Factor
Realization factor is based on current air traffic & regional understandingThis factor has been included based on the premise that the airport would not be able to achieve 100% of potential traffic because
It will take some time in changing the spend patterns of target passengersIn the initial years aeroplanes wont be available for all routes
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Traffic ProjectionAirport expected to be operational by 2014-15, with expected 2.59 Lac passenger expected (Base Case)
While projecting traffic, we have assumed two scenarios – Base Case Growth rate and the Optimistic Case Growth RateBase Case Growth Rate = TN GDP Growth RateOptimistic Case Growth Rate = Puducherry Growth Rate
BASE CASE TRAFFIC OPTIMISTIC CASE TRAFFIC
CAGR = 8.08% CAGR = 8.50%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
262 494
729
1,075
1,580
2,164
2,901
Base Traffic (000 passengers)
-
500
1,000
1,500
2,000
2,500
3,000
3,500
287 546
827
1,230
1,807
2,475
3,317
Optimistic Traffic (000 passengers)
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Origin-Destination of first year air traffic (2014-15)Chennai and Coimbatore contribute ~41% of all traffic
Traffic Origin
Total NRI TrafficLocal
ResidentsVelankann
iNagore
Thirunallar
Thirukadaiyur
Chennai 50,085 - 6,872 8,652 3,158 22,055 9,348
Coimbatore 63,752 - 3,975 10,234 455 49,088 -
Madurai 24,630 - 9,081 2,174 3,610 9,765 -
Cochin 17,299 - 563 13,269 - 3,467 -
Trivandrum 8,070 - 1,083 4,239 - 2,749 -
Hyderabad 12,917 - 142 3,326 - 9,450 -
Bangalore 32,006 - 2,201 9,834 - 19,971 -
Mumbai 2,545 - 66 2,047 432 - -
Delhi 255 - 255 - - - -
Calcutta 2,492 - - 2,492 - - -
Goa 295 - 28 267 - - -
Pondicherry 3,650 - - -
Colombo 518 - - 518 - - -
Dubai 6,697 6,467 - 230 - - -
France 806 - - 806 - - -
Germany 1,612 - - 1,612 - - -
Holland 58 - - 58 - - -
Malaysia 14,719 12,934 - 1,784 - - -
Kabul 284 - 284 - - - -
Singapore 13,218 12,934 284 - - - -
Kuwait 6,467 6,467 - - - - -
Total 262,374 38,803 28,483 61,540 7,655 116,545 9,348
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First year (2014-15) traffic characteristics (1/2)
262,374Traffic share highly skewed in favour of Tamil Nadu destinations hence majority traffic within TN itselfDirect traffic to other destinations limited in initial stages due to less traffic to those destinationsMore than 90% international traffic to South East Asia and Middle EastTraffic comprises largely of NRIs i.e. labour migrations and movements to these regions from Tamil Nadu, which currently use Trichy and Chennai Airport
217996; 83%
44378; 17%
Domestic PassengersInternational Passengers
Domestic vs. International
International Passenger Distribution
27937; 63%
13164; 30%
3277; 7%
South East AsiaMiddle EastRest of World
Domestic Passenger Distribution
142117; 65%
70292; 32%
5587; 3%
Within Tamil NaduOther Southern RegionsRest of India
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First year (2014-15) traffic characteristics (2/2)
Year wise Weekly Aircraft movement Aircraft type wise
Aircraft operations dominated by ATR type aircraft due to lesser passenger traffic and movement to various destinations
38803; 15%
28483; 11%
61540; 23%
7655; 3%
116545; 44%
9348; 4%
NRILocal ResidentsVelankanniNagoreThirunallar Thirukadaiyur
Passenger Categories
2014-15 2025-26 2035-36 2045-460
50
100
150
200
250
300
350
400
1440
84
0
3862 70 82
10 4 0 01234
52
136
028
106
154
60
128
228
372
Private JetATRCat B (90)Cat C (180)Cat D (220)Total
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Weekly Aircraft Movement – Projections route wiseOperations will start with 74 weekly flights in year 2014-15 going up to 158 weekly flights in year 2024-25
2014-2015 2024-2025 Category Category
Private Jet (6)
ATR (80)
B Cat (90)
C Cat (180)
C Cat (220)
Private Jet (6)
ATR (80)
B Cat (90)
C Cat (180)
C Cat (220)
Chennai 10 4 14 2 8
Coimbatore 10 4 14 6 8Madurai 8 14 2Cochin 8 10 2 2TrivandrumHyderabad 2 2 2Bangalore 2 4 8 4 4MumbaiDelhiCalcuttaGoaPondicherry 14 36ColomboDubai 4 4 4FranceGermanyHollandMalaysiaKabulSingapore 6 10KuwaitTOTAL 14 38 10 12 0 36 62 4 30 26
21
Operations expected to expand from 158 weekly flights in year 2024-25 going up to 360 weekly flights in year 2044-45
2034-2035 2044-2045 Category Category
Private Jet (6)
ATR (80)
B Cat (90)
C Cat (180)
C Cat (220)
Private Jet (6)
ATR (80)
B Cat (90)
C Cat (180)
C Cat (220)
Chennai 14 6 28 14 28 28
Coimbatore 14 10 28 14 28 38Madurai 14 6 6 14 12 14Cochin 14 6 6 14 14 14TrivandrumHyderabad 6 4 8 8Bangalore 14 10 8 14 4 28MumbaiDelhiCalcuttaGoaPondicherry 78 12ColomboDubai 2 8 10FranceGermanyHollandMalaysia 2 8 8 10KabulSingapore 8 8 8Kuwait 10TOTAL 78 70 0 48 104 0 82 0 130 148
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Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
23
Cargo ProjectionsCargo traffic is expected to be 4266 tonnes in year 1 going up to 13,229 tonnes in year 31
Dom
esti
c +
In
tern
ati
on
al
Carg
o (
in t
on
nes)
Domestic Cargo International Cargo -
500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 4,247
834
4,266
927
4,285
1,019
Low ScenarioModerate ScenarioHigh Scenario
Expected Cargo Traffic 2014-15
-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
11,795
13,229
4,266
13,706 Scenario 1 Scenario 2 Scenario 3
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Chennai being a developed region will continue to hold a lion’s share of the Cargo traffic supported by a high GDP growth in Tamil Nadu
Chennai holds more than 70% of total air cargo market in TN; Due to the high GDP growth rate and a well developed Air cargo facility, Chennai will dominate the air cargo market in the region in future
0% 10% 20% 30% 40% 50% 60% 70% 80%0%
20%
40%
60%
80%
100% CARGO Vs GDP Past trends in the Air Cargo market indicate a significant relationship of Air Cargo growth with GDP growthA high elasticity (1.194) of domestic air cargo growth v/s GDP growth means higher the GDP higher the cargo traffic growth rate
Cargo= (1.5226*GDP of Service Area2) - 0.0243
2011
-12
2013
-14
2015
-16
2017
-18
2019
-20
2021
-22
2023
-24
2025
-26
2027
-28
2029
-30
2031
-32
2033
-34
2035
-36
2037
-38
2039
-40
2041
-42
2043
-44
2045
-46
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Expected GDP Share of Chennai
Expected GDP Share of Karaikal
Expected GDP Share of Karaikal v/s Chennai
25
Thank You!
26
Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
Back
27
Karaikal and Tamil
Nadu GDPAssumptions
Assumptions
The objective at this stage is to identify the relationship between regional income and its impact on Air Traffic growth in Tamil Nadu, Pondicherry and Karaikal regions
Air Traffic v/s GDP Correlation
Past trends of GDP and traffic growth correlation are expected to continue in futureIdentified correlation between air traffic share and GDP share in the region is expected to hold in future
KARAIKAL GDP ASSUMPTIONSPondicherry UT GDP growth elasticity to Indian national GDP growth rate has been assumed at 1.2 in order to have realistic GDP growth rate expectations for Karaikal, instead of 1.34 as determined from correlationGrowth elasticity expected to come down gradually to 1, at par with India GDP growthThe optimistic and pessimistic Karaikal GDP growth rates are expected to be 5% higher and lower respectively than realistic GDP growth rate
TAMIL NADU GDP ASSUMPTIONSTamil Nadu GDP growth elasticity is expected to come down gradually over 20 years from 2011 to reach India GDP growth by 2030-31 and thereafter stay at India GDP growth levels
Other Assumptions
No other Airport is expected to come in either Tamil Nadu or Pudducherry till 2045-46 in the region
Back
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Approach
Collection of Macro Economic Data
Developing Demand Forecasting Model
Application of Data to Model to determine
total traffic
Macro economic data was
collected
This data formed the basis for
further analysis
The correlation model, modified as
a time series econometric model,
has been used for forecasting the
aviation demands in this study
Correlation between traffic and
GDP
Karaikal GDP Estimation
Estimating passenger/cargo
growth
Determining airport wise traffic
share
Year on yea GDP data for India,
Tamil Nadu, & metro regions of
Chennai, Coimbatore, Madurai &
Tiruchirapalli
Population data of these regions
GDP of the districts
Population of the districts
Passenger and Cargo Traffic
Year on yea GDP data for India,
Tamil Nadu, & metro regions of
Chennai, Coimbatore, Madurai &
Tiruchirapalli
Population data of these regions
GDP of the districts
Population of the districts
Passenger and Cargo Traffic
Elasticity of aviation demand in
Tamil Nadu region is estimated
Using forecasted TN GDP growth
rates, aviation growth rates of
the region is obtained for future
years.
Subsequently, future aviation
demands are obtained for the
region
Elasticity of aviation demand in
Tamil Nadu region is estimated
Using forecasted TN GDP growth
rates, aviation growth rates of
the region is obtained for future
years.
Subsequently, future aviation
demands are obtained for the
region
Regression analysis with GDP
data to determine the correlation
of traffic to GDP growth
Identify trends for the passenger
and cargo traffic
Airport wise traffic share
correlated with GDP share of the
representative region & traffic
shares determined
Regression analysis with GDP
data to determine the correlation
of traffic to GDP growth
Identify trends for the passenger
and cargo traffic
Airport wise traffic share
correlated with GDP share of the
representative region & traffic
shares determined
Using this approach, we determine how Karaikal Airport is expected to benefit from the growth and increasing income levels in the Tamil Nadu and Pondicherry region. We
determine the air traffic as Back
29
Expected Traffic in the first year of operations (2014-15)
Scenario 1 Low Scenario 2 Moderate Scenario 3 High -
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
834 927 1,019
4,247 4,266 4,285
Cargo International Cargo Domestic
Cargo Traffic (tonnes)
Scenario 1 Low Scenario 2 Moderate Scenario 3 High -
50
100
150
200
250
300
350
400
178 190 203
140 145 150
318 335 352
Passenger Domestic Passenger InternationalPassenger Total
Passenger Traffic (‘000)
MARKET SHARE OF KARAIKAL v/s TN AIRPORTS FOR 2014-15 (Moderate Scenario)
Passengers Cargo
Airport Domestic International
Domestic
International
Chennai 81.54% 83.18% 85.75% 99.10%
Madurai + Trichy + Coimbatore
17.35% 14.85% 11.47% 0.70%
Karaikal 1.11% 1.97% 2.78% 0.20%
A total passenger of 335,000 or 918 passengers per day means approximately 10-12 flights (assuming mostly ATR) in the first year of operation (2014-15). Projected traffic growth is
as followsBack
30
Airport expected to be operational by 2014-15, when footfall expected to be 335,000 (Base Case) and 352,000 (Optimistic)
While projecting traffic, we have assumed 3 scenarios – Pessimistic Scenario, Base Case Scenario and Optimistic ScenarioPessimistic Case Growth Rate = 0.95 x Base Case Growth Rate Base Case Growth Rate = India GDP Growth Rate x Karaikal GDP Growth Rate ElasticityOptimistic Case Growth Rate = 1.05 x Base Case Growth Rate
2011
-12
2012
-13
2013
-14
2014
-15
2015
-16
2016
-17
2017
-18
2018
-19
2019
-20
2020
-21
2021
-22
2022
-23
2023
-24
2024
-25
2025
-26
2026
-27
2027
-28
2028
-29
2029
-30
2030
-31
2031
-32
2032
-33
2033
-34
2034
-35
2035
-36
2036
-37
2037
-38
2038
-39
2039
-40
2040
-41
2041
-42
2042
-43
2043
-44
2044
-45
2045
-46
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
335
Scenario 1 Scenario 2 Scenario 3
Dom
esti
c +
In
tern
ati
on
al
Passen
gers
(in
00
0s) 4,00
9
Back
31
Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
Back
32
Approach to annual traffic estimation in the catchment area & OD matrix preparation
List of 19 Railway junctions identified in and around Karaikal
Base road traffic estimationBase rail traffic estimation
Passenger data for 9 availableExtrapolate to 19 junctions in proportion to population
Data from sample surveys conducted at 6 railway stations were used to prepare the OD map for the region
Total annual traffic mapped out along all key routes
Total reservation traffic = 630,535
CVC studies conducted at 5 key nodes acting as the outlets of the catchment area of the airport
Sample projected for annual traffic including factors for high weekend traffic and seasonal peaks
Each region mapped to one airport as its primary, secondary or tertiary hinterland Share of air traffic at 100%, 50% and 33% if the region falls within the primary, secondary or tertiary hinterland respectively of Airport
Total Road passenger traffic = 3,908,014
The objective of the above exercise is to estimate the total passenger traffic in the region. Since there is no airport in the region (in and around Karaikal), passengers travel either by
road or rail. Back
33
Methodology
OD matrix is refined by clubbing origin & destination regions according to the nearest airport
Grid showing expected total traffic between 11 Airport regions
Traffic to and fro Karaikal filtered & 18 pairs to/from Karaikal identified
Probable travelers by air based on time and cost evaluation of Rail v/s Air Transport
OD matrix is refined by clubbing origin & destination regions according to the nearest airport
Grid showing expected total traffic between 11 Airport regions
Traffic to and fro Karaikal filtered & 16 pairs to/from Karaikal identified
Probable travelers by air based on time and cost evaluation of Rail v/s Air Transport
This approach gives us the total expected passengers expected to shift from rail and road to Air transport via Karaikal Airport to various origins. The expected traffic is explained as
Estimation of likely mode shifts from Road
Estimation of likely mode shifts from Rail
Total reservation traffic = 630,535 Total Road passenger traffic = 3,908,014
Back
34
Potential Passenger Traffic in the first year (2014-15)
ROAD CONTRIBUTION RAIL CONTRIBUTION
184,675 223,099407,774
EXPECTED MODAL SHIFT
Origin Rail Road
Chennai 2,566 46,386
Coimbatore 49,350 42,331
Trichy - 49,779
Madurai 6,249 23,257
Cochin 12,756 -
Trivandrum 37,570 6,475
Hyderabad 21,280 439
Bangalore 15,429 44,240
Mumbai 16,461 4,425
Delhi 23,014 5,768
Total 184,675 223,099
407,774 or 1,117 passengers/day with 12 aircraft operations per day
12.00%
22.48%
12.21%
7.24%3.13%
10.80%
5.33%
14.63%
5.12%
7.06%
ChennaiCoimbatoreTrichyMaduraiCochinTrivandrumHyderabadBangaloreMumbaiDelhi
ORIGIN WISE TRAFFIC CONTRIBUTION
Back
35
Airport expected to be operational by 2014-15; footfall potential expected to be 407,774 (Base Case) and 426,867 (Optimistic Case)
While projecting traffic, we have assumed two scenarios – Base Case Growth rate and the Optimistic Case Growth RateBase Case Growth Rate = TN GDP Growth RateOptimistic Case Growth Rate = Puducherry Growth Rate
CAGR = 7.30%
CAGR = 7.70%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
408 602
888 1,310
1,925
2,637
3,533
Base Traffic Growth
Base Traffic Growth(000s passengers)
- 500
1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500
427 662
1,006 1,498
2,201
3,015
4,041
Optimistic Traffic Growth
Optimistic Traffic Growth(000s passengers)
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Agenda
Introduction to the project
Passenger Traffic Potential Estimation
Passenger Traffic Projection
Cargo Traffic Projection
AnnexureA: Econometric Top Down ApproachB: Econometric Bottom Up ApproachC: Econometric Traffic Segmentation Approach
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Assumptions
NRI traffic assumptions
Projections were made based on traveler segments namely, NRI, Local Residents and Tourists. Analysis of conversion of tourists to airport was done tourist location wise
Local residents traffic assumptions
Tourist traffic assumptions
10 districts in and around Karaikal with population (2011) considered
Only 6 districts considered relevant for NRI population using Karaikal Airport
Survey results are representative of the whole population
Every visiting NRI would undertake two way journeyRealization factor at 75% of potential travelers
10 districts in and around Karaikal with population (2011) considered
Only 6 districts assumed relevant for local popn.
High income population 3% of total Survey results representative of the whole population
Probability of local population using Air travel follows similar pattern as tourists. Realization factor – 70%
Survey results are representative of the whole population
Relevant high income tourists assumed at 5% of total tourists
Traffic for Thirukadaiyur assumed to originate from Chennai mainly
Realization factor – 70% of potential travelers.
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Methodology
Local Population Survey including NRI
Tourist Survey Assumptions
Extrapolation of Survey Results to the whole populationAirport wise travel OD matrix preparation
O-D Matrix showing pair wise (Airport regions) passengers both local and foreign travelers using all modes of transport
O-D Matrix adjusted for probability of passengers shifting to Air travelProbability of shifting = _____________Utility derived from air travel_____________
Sum of current utility and derived utility for air travel Determination of potential passengers traveling by Air
Potential passengers adjusted for realization factor (category wise)
Projected Passengers for 1st year of operations
This approach gives us category wise and origin wise total expected passengers expected to travel to/from Karaikal Airport. The expected traffic is represented as
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Projected Passenger TrafficIn the first year of operations the potential traffic is 416,012 in the base case and 438,298 in the optimistic case
While projecting traffic, we have assumed two scenarios – Base Case Growth rate and the Optimistic Case Growth RateBase Case Growth Rate = TN GDP Growth RateOptimistic Case Growth Rate = Puducherry Growth Rate
- 500
1,000 1,500 2,000 2,500 3,000 3,500 4,000
416 614 906
1,336
1,963
2,689
3,603
Base Traffic
Base Traffic (000s passengers)
- 500
1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500
438 678
1,027 1,527
2,244
3,075
4,120
Optimistic Traffic
Optimistic Traffic (000s passengers)
CAGR = 7.33% CAGR = 7.74%
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Expected Current Passenger Traffic in 2014-15 (1/2)
416,012
Domestic Passenger Distribution (‘000)
The expected passenger traffic for first year of operation is of 416,012 or 1140 passengers/day. Projected traffic growth is as follows
Traffic share highly skewed in favour of Tamil Nadu destinations hence majority traffic within Tamil Nadu itself
Direct traffic to other destinations limited in initial stages due to less traffic to those destinations
Domestic vs. International (‘000)
Passenger Category Distribution (‘000)
51.7367596639052; 12%
73.6299127736392;
18%
88.236714412627;
21%
17.1251963794172; 4%
171.929403961808;
41%
13.3542594338542; 3%
NRI
Local Travelers
Velankanni
Nagore
Thirunallar
Thirukadaiyur
356.31; 86%
59.702; 14%
Domestic Passengers
International Passengers
247.912; 70%
100.418; 28%
7.981; 2%
Within Tamil Nadu
Other Southern Regions
Rest of India
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O-D wise Potential Traffic
2011-12 2014-15Traffic Origin
NRI Traffic
Local Population Traffic
Tourist Traffic
NRI Traffic
Local Population Traffic
Tourist Traffic
Chennai - 7,759 48,794 - 9,817 61,733Coimbatore - 4,489 67.497 - 5,679 85,395
Trichy - 27,272 9,444 - 34,504 11,948Madurai - 10,254 17,558 - 12,973 22,214Cochin - 636 18,897 - 805 23,908
Trivandrum - 1,222 7,890 - 1,547 9,983Hyderabad - 160 14,426 - 202 18,251Bangalore - 2,485 33,655 - 3,144 42,579Mumbai - 75 2,799 - 95 3,541
Delhi - 288 - - 364 -
Calcutta - - 2,813 - - 3,559Goa - 32 301 - 41 381
Pondicherry - 2885 - - 3,650
Colombo - - 585 - - 740Dubai 6,816 - 260 8,623 - 329France - 910 - - 1,151
Germany - 1,820 - - 2,302Holland - 65 - - 82Malaysia 13,631 - 2,015 17,246 - 2,549
Kabul 321 - - 406Singapore 13,631 321 - 17,246 406
Kuwait 6,816 - - 8,623 -
Total 40,893 58,198 229,729 51,737 73,630 290,646
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