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1 September 2011 Airport Traffic Estimation Presentation for Karaikal Airports Private Limited Airport Traffic Estimation Presentation for Karaikal Airports.

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Presentation on theme: "1 September 2011 Airport Traffic Estimation Presentation for Karaikal Airports Private Limited Airport Traffic Estimation Presentation for Karaikal Airports."— Presentation transcript:

1 1 September 2011 Airport Traffic Estimation Presentation for Karaikal Airports Private Limited Airport Traffic Estimation Presentation for Karaikal Airports Private Limited

2 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 Feedbacks 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 3 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach

4 4 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach

5 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 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 hinterland Secondary hinterland LEGEND: KARAIKAL

7 7 Key traffic centres within the catchment area * Distances from Karaikal city centre

8 8 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach

9 9 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 traffic 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 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 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 airport Finding the correlation of airport traffic share with macroeconomic variables Estimating the share & traffic potential of Karaikal 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

10 10 1. Top Down Approach Potential 3.35 Lac annual passengers or 918 / day in Yr Yr 1 Cargo Traffic (tons)Yr 1 Passenger Traffic (000) Passenger Traffic Projection (000) Details

11 11 2. Bottom Up Approach Potential 4.08 Lac annual passengers or 1,118 / day in Yr Yr 1 Passenger Traffic (000) Passenger Traffic Projection (000) Details

12 12 3. Traveler Segmentation Approach Potential 4.16 Lac annual passengers or 1140 / day in Yr Yr 1 Passenger Traffic (000) Passenger Traffic Projection (000) Segment wise Traffic Distribution Details

13 13 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 Airport In 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 approach This approach is more granular, considers traffic on individual O-D pairs after taking into account passenger preferences and dynamics

14 14 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach

15 15 Potential v/s Realizable Traffic – Base year Traveler TypePotential Traffic After Trichy traffic adjustmentRealization factor Realizable Traffic Local residents69,98035,47670%24,833 NRI Travelers51,737 75%38,803 Velankanni88,23687,91470%61,540 Nagore17,12610,93770%7,656 Thirunallar171,929166,49370%116,545 Thirukadaiyur13,354 70%9,348 Pondicherry Traffic416,0123,650100%3,650 Total412,362365,911262,375 Trichy Traffic Adjustment 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 understanding This 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 passengers In the initial years aeroplanes wont be available for all routes

16 16 Traffic Projection Airport expected to be operational by , 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 Rate Base Case Growth Rate = TN GDP Growth Rate Optimistic Case Growth Rate = Puducherry Growth Rate BASE CASE TRAFFIC OPTIMISTIC CASE TRAFFIC CAGR = 8.08%CAGR = 8.50%

17 17 Origin-Destination of first year air traffic ( ) Chennai and Coimbatore contribute ~41% of all traffic Traffic OriginTotalNRI TrafficLocal ResidentsVelankanniNagoreThirunallarThirukadaiyur Chennai 50,085- 6,8728,6523,15822,0559,348 Coimbatore 63,752- 3,97510, ,088 - Madurai 24,630- 9,0812,1743,6109,765 - Cochin 17, , ,467 - Trivandrum 8,070- 1,0834, ,749 - Hyderabad 12, , ,450 - Bangalore 32,006- 2,2019, ,971 - Mumbai 2, , Delhi Calcutta 2, Goa Pondicherry 3, Colombo Dubai6,6976, France Germany 1, Holland Malaysia14,71912, , Kabul Singapore13,21812, Kuwait6, Total262,37438,80328,48361,5407,655116,5459,348

18 18 First year ( ) traffic characteristics (1/2) 262,374 Traffic share highly skewed in favour of Tamil Nadu destinations hence majority traffic within TN itself Direct traffic to other destinations limited in initial stages due to less traffic to those destinations More than 90% international traffic to South East Asia and Middle East Traffic comprises largely of NRIs i.e. labour migrations and movements to these regions from Tamil Nadu, which currently use Trichy and Chennai Airport Domestic vs. International International Passenger DistributionDomestic Passenger Distribution

19 19 First year ( ) 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 Passenger Categories

20 20 Weekly Aircraft Movement – Projections route wise Operations will start with 74 weekly flights in year going up to 158 weekly flights in year 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 Coimbatore Madurai 8142 Cochin Trivandrum Hyderabad 222 Bangalore Mumbai Delhi Calcutta Goa Pondicherry 1436 Colombo Dubai 444 France Germany Holland Malaysia Kabul Singapore 610 Kuwait TOTAL

21 21 Operations expected to expand from 158 weekly flights in year going up to 360 weekly flights in year 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 Coimbatore Madurai Cochin 1466 Trivandrum Hyderabad 6488 Bangalore Mumbai Delhi Calcutta Goa Pondicherry 7812 Colombo Dubai 2810 France Germany Holland Malaysia Kabul Singapore 888 Kuwait 10 TOTAL

22 22 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach

23 23 Cargo Projections Cargo traffic is expected to be 4266 tonnes in year 1 going up to 13,229 tonnes in year 31 Domestic + International Cargo (in tonnes) Expected Cargo Traffic

24 24 Chennai being a developed region will continue to hold a lions 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 Past trends in the Air Cargo market indicate a significant relationship of Air Cargo growth with GDP growth A 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) Expected GDP Share of Karaikal v/s Chennai

25 25 Thank You!

26 26 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach Back

27 27 Karaikal and Tamil Nadu GDP 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 future Identified correlation between air traffic share and GDP share in the region is expected to hold in future KARAIKAL GDP ASSUMPTIONS Pondicherry 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 correlation Growth elasticity expected to come down gradually to 1, at par with India GDP growth The optimistic and pessimistic Karaikal GDP growth rates are expected to be 5% higher and lower respectively than realistic GDP growth rate TAMIL NADU GDP ASSUMPTIONS Tamil Nadu GDP growth elasticity is expected to come down gradually over 20 years from 2011 to reach India GDP growth by and thereafter stay at India GDP growth levels Other Assumptions No other Airport is expected to come in either Tamil Nadu or Pudducherry till in the region Back

28 28 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 29 Expected Traffic in the first year of operations ( ) Cargo Traffic (tonnes) Passenger Traffic (000) MARKET SHARE OF KARAIKAL v/s TN AIRPORTS FOR (Moderate Scenario) Passengers Cargo Airport Domestic International Domestic International Chennai81.54%83.18%85.75%99.10% Madurai + Trichy + Coimbatore17.35%14.85%11.47%0.70% Karaikal1.11%1.97%2.78%0.20% A total passenger of 335,000 or 918 passengers per day means approximately flights (assuming mostly ATR) in the first year of operation ( ). Projected traffic growth is as follows Back

30 30 Airport expected to be operational by , 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 Scenario Pessimistic Case Growth Rate = 0.95 x Base Case Growth Rate Base Case Growth Rate = India GDP Growth Rate x Karaikal GDP Growth Rate Elasticity Optimistic Case Growth Rate = 1.05 x Base Case Growth Rate Domestic + International Passengers (in 000s) 4,009 Back

31 31 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach Back

32 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 available Extrapolate 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 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 RoadEstimation of likely mode shifts from Rail Total reservation traffic = 630,535Total Road passenger traffic = 3,908,014 Back

34 34 Potential Passenger Traffic in the first year ( ) ROAD CONTRIBUTION RAIL CONTRIBUTION 184,675223, , ,774 or 1,117 passengers/day with 12 aircraft operations per day ORIGIN WISE TRAFFIC CONTRIBUTION Back

35 35 Airport expected to be operational by ; 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 Rate Base Case Growth Rate = TN GDP Growth Rate Optimistic Case Growth Rate = Puducherry Growth Rate CAGR = 7.30% CAGR = 7.70% Back

36 36 Agenda Introduction to the project Passenger Traffic Potential Estimation Passenger Traffic Projection Cargo Traffic Projection Annexure A: Econometric Top Down Approach B: Econometric Bottom Up Approach C: Econometric Traffic Segmentation Approach Back

37 37 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 journey Realization 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. Back

38 38 Methodology Local Population Survey including NRITourist Survey Assumptions Extrapolation of Survey Results to the whole population Airport 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 travel Probability 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 1 st 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 Back

39 39 Projected Passenger Traffic In 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 Rate Base Case Growth Rate = TN GDP Growth Rate Optimistic Case Growth Rate = Puducherry Growth Rate CAGR = 7.33%CAGR = 7.74% Back

40 40 Expected Current Passenger Traffic in (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) Back

41 41 O-D wise Potential Traffic Traffic OriginNRI TrafficLocal Population TrafficTourist TrafficNRI TrafficLocal Population TrafficTourist Traffic Chennai - 7,75948, ,81761,733 Coimbatore - 4, ,67985,395 Trichy - 27,2729, ,50411,948 Madurai - 10,25417, ,97322,214 Cochin , ,908 Trivandrum - 1,2227, ,5479,983 Hyderabad , ,251 Bangalore - 2,48533, ,14442,579 Mumbai - 752, ,541 Delhi Calcutta -- 2, ,559 Goa Pondicherry ,650 Colombo Dubai 6, , France ,151 Germany - 1, ,302 Holland Malaysia 13, ,01517, ,549 Kabul Singapore 13, , Kuwait 6, ,623 - Total 40,89358,198229,72951,73773,630290,646 Back


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