An Analysis of Intra-Regional Air Travel in SAARC Region Prof. Amal S Kumarage, Ms D Piyathilaka, Ms K C S Ekanayake Department of Transport & Logistics Management University of Moratuwa Annual Sessions Chartered Institute of Logistics & Transport Sri Lanka 11 th August 2007
The Study Examines the present status of Air Travel in the SAARC region Emerging Trends and Patterns Using Past 5-6 years Statistical data Source: Civil Aviation Authority of Sri Lanka SAARC Regional Multimodal Transport Study (SRMTS) Final Report, December 2005
SAARC in Perspective Nearly 1/4th of the total world population, but only 2.1% of world GNP and 1.2% of world trade. One of the fastest economic growth rates (avg. - 5.1% p.a.) South East Asia - 2% per annum East Asia - 5.8% per annum (the fastest growing) Total intra-regional export trade in SAARC to total global exports - only around 5.0% Lack of integrated transport systems.
Significance of an Integrated Transport network in SAARC region and Present concerns Essential to promote land locked countries; Nepal and Bhutan. Essential to enhance connectivity of Island states; Maldives and Sri Lanka with the rest of SAARC (Maritime and air transport). Concerns Very low connectivity in terms of direct flights. High cost of travel Deficiency of investment in relation to the provision of modern terminals and additional runway capacity. Regulatory barriers Lack of strong hub operations for efficient regional transfers.
Comparison of Regional Aviation in SAARC with other Regions - 2002 Region Intra Regional Passengers Carried (million) Regional Trips Per 1000 Capita Africa 6.3 11 Asia/Pacific 47.6 13 Europe 125.4 133 Middle East 10.3 21 North America 125.4 381 South America & Caribbean 19.0 34 TOTAL 334.1 52 SAARC (given within Asia/Pacific) 1.8 1 Comment regarding travel within SAARC region Only 0.5% ; 1 in 200 of World wide regional traffic Lowest aviation use in the world, lower than sub-saharan Africa. Even though Air transport is correlated with increase in income, the extremely low indicators of use shows that aviation within SAARC is one of the least developed modes of transport particularly for intra-regional mobility.
Air Services Agreements in the SAARC region-2004 Country B desh Bhutan India Maldives Nepal Pakistan Sri Lanka Bangladesh 2 60 X n/a n/a 3 Bhutan 0 49 X 7 X X India 29 8 40 60 24 7*5 (metros) others unlimited Maldives X X 4 X X unlimited Nepal 7 3 41 X n/a X Pakistan 4 X 14 X 2 unlimited Sri Lanka 0 X 107 27 X 5 Weekly number of flights in operation at present The number of flights per week allowed in the present ASAs Maximum possible ASAs between the 7 countries; 21Total implemented; 14
The sixteen SAARC Gateways 16.Colombo 15.Lahore 14.Karachi 13.Kathmandu 12.Male 11.Hyderabad 10.Cochin 9.Trichy 8.Bangalore 7.Trivandrum 6.Kolkata 5.Chennai 4.Mumbai 3.Delhi 2.Paro 1.Dhaka 1.Dhaka 35,910 16,897 167,092 31,109 65,098 2.Paro 9,606 9,840 8,474 3.Delhi 2 3 264,346 62,750 34,780 81,406 4.Mumbai 2 1,693 16,269 77,476 75,225 5.Chennai 6.Kolkata 7.Trivandrum 8.Bangalore 9.Trichy 10.Cochin 11.Hyderabad 12.Male 13.Kathmandu 14.Karachi 15.Lahore 16.Colombo 453,662 23 5 36,886 80,140 107,683 13,841 92,889 84,876 48,345 26,288 1 3 271,998 7 3 31 2 3 2 17,364 4 3 5 2 36,018 6 7 7 36 12 7 10 11 7 27 5 The 28 direct flight connections out of 83 at present, between the 16 aviation corridors.
Observations Only 15 direct flights out of 28, among the top 8 of the corridors (Colombo, Delhi, Chennai, Mumbai, Male, Dhaka, Karachi and Kathmandu) (Directness Index 54%) Only within the top 4 aviation corridors (Colombo, Delhi, Chennai and Mumbai) there are direct flights between all of them. (Directness Index 100%) Only 9 connections between the 7 SAARC capitals, of a possible 21 direct connections are operative. (Directness Index 43%). The direct connectivity between the capitals in particular is extremely deficient.
Passenger Movements in selected Corridors From Dhaka Paro Delhi Mumbai Colombo Kathmandu To Flights per week (One way) % Increase of passengers 2001-2004 Distance (km) Aircraft kms operated 2004 Passenger kms Carried 2004 Delhi 2 169 887 184,496 31,852,170 Mumbai 2 76 1,171 243,568 19,786,387 Kolkata 23 2 146 349,232 24,395,359 Kathmandu 7-34 415 302,120 12,910,235 Karachi 4-5 1,464 609,024 95,303,472 Delhi 3 32 1,344 419,328 12,910,464 Kolkata 5 108 550 286,000 5,411,725 Kathmandu 3 56 488 152,256 4,135,312 Kathmandu 31 19 893 2,879,032 236,060,978 Karachi 3 29 1,064 331,968 66,766,000 Lahore 6 33 457 285,168 15,894,232 Colombo 7 83 2,444 1,779,232 198,956,264 Male 1 Kathmandu 2-25 Karachi 5-16 870 452,400 67,404,120 Colombo 7 156 1,530 1,113,840 115,093,485 Chennai 36 42 668 2,500,992 303,045,882 Trivandrum 12 3 360 449,280 38,765,700 Bangalore 7 806 586,768 74,868,534 Trichy 10 105 440 457,600 37,345,220 Cochin 11 502 574,288 24,268,939 Hyderabad 7 1,160 844,480 30,493,500 Male 27 31 829 2,327,832 225,486,342 Karachi 5 17 2,403 1,249,560 86,550,053 Kolkata 3 69 643 200,616 23,704,838 Bangalore 2-5 Karachi 2 Trivandrum Male 3 15 671 209,352 53,773,605
Air Travel within the SAARC
Table Summery 236 out of 251(94%) weekly return flights operated within SAARC are made between the 16 corridors. The four routes carry over 40% of the entire demand for intra-regional air travel within SAARC; Socio-cultural linkages - Colombo to Chennai 453,662 passengers, Dhaka to Kolkata 167,092 passengers. Tourism & Trade Colombo to Male 271,998 passengers, Delhi to Kathmandu 264,346 passengers
Summary cont. Passengers choose to fly to destinations that are cheapest to reach the end destination Colombo - Trivandrum 107,683 passengers (i.e. instead of flying to Chennai) and thereafter taking cheaper surface transport. Commercial and business travel within SAARC has still not grown to its full potential. Intra-regional corridors connecting the major commercial centres such as Mumbai Colombo, are still of moderate traffic levels, ranging between 15,000 to 80,000 passengers per year.
Cargo movements in selected Corridors From To Growth rate % 2001-2004 Distance (Km) Tonne kms 2004 Total Cost US$ per ton Freight Rate US$ per Ton km Dhaka Delhi 139 887 1,273,289 510 0.57 Mumbai (8) 1,171 1,090,201 355 0.30 Kolkata (36) 146 208,634 130 0.89 Kathmandu (27) 415 124,500 500 1.20 Karachi (49) 1,464 2,029,104 520 0.36 Paro Delhi 13 1,344 12,096 2,000 1.49 Kolkata 71 550 7,975 1,000 1.82 Kathmandu 300 488 11,712 1,000 2.05 Delhi Kathmandu 32 893 2,448,160 480 0.54 Karachi 48 457 221,417 - - Lahore 171 2,444 1,250,407 500 0.20 Mumbai Male - - 1,990 Kathmandu 31 - - - Karachi 99 870 1,348,065 210 0.24 Colombo Chennai 40 1,530 9,342,945 955 0.62 Trivandrum (15) 140 Bangalore 668 373,412 280 0.42 Trichy (29) 360 12,960 155 0.43 Cochin 806 280,488 240 0.30 Hyderabad 502 129,516 275 0.55 Delhi 80 1,160 1,526,560 975 0.84 Mumbai 188 - - 1,145 Male 31 829 8,138,293 335 0.40 Karachi 37 2,403 5,489,654 1,020 0.42 Kathmandu Kolkata (44) 643 123,071 310 0.48 Bangalore 33 - - - Karachi 132 - - - Trivandrum Male 19 671 659,258 325 0.48 TOTAL of the 16 Selected Corridors 25 36,101,715 TOTAL of all Corridors 26 36,171,784
Table summary Very low utilization of aviation for freight Freight tonnes to be carried on all international routes - 23,000 million tonnes; the movements within SAARC 36.6 million tonnes (0.15%). The heaviest freight flows centered on Colombo (> 50%) of the intra-regional freight movements. Colombo - Male corridor, Colombo Chennai - flows between 50 to 100 tons per week (both ways) per week. Average freight load is 2 tonnes per aircraft movement. Carried 36,602 tons of freight and produced 36.6 million freight tonne kms.
Conclusion Air travel in SAARC in comparison to other regions is lagging Identified possible reasons; Lack of integrated transport network High cost in travel
Fares and Rates between the selected corridors Flights per week Distance Return Economy Fare per From To (km) Fare($) km US$ Delhi 2 887 $455.50 $0.26 Mumbai 2 1,171 $509.00 $0.22 Kolkata 23 146 $134.00 $0.28 Kathmandu 7 415 $224.00 $0.27 Dhaka Karachi 4 1,464 $546.00 $0.19 Delhi 3 1,344 $630.00 $0.23 Kolkata 5 550 $380.00 $0.35 Paro Kathmandu 3 488 $488.00 $0.39 Kathmandu 31 893 $300.00 $0.17 Karachi 3 1,064 $247.00 $0.12 Lahore 6 457 $163.00 $0.18 Delhi Colombo 7 2,444 $570.50 $0.12 Male 1 Kathmandu 2 Karachi 5 870 $200.00 $0.11 Mumbai Colombo 7 1,530 $387.50 $0.13 Chennai 36 668 $175.00 $0.13 Trivandrum 12 360 $130.00 $0.18 Bangalore 7 806 $174.00 $0.11 Trichy 10 440 $139.00 $0.16 Cochin 11 502 $156.00 $0.16 Hyderabad 7 1,160 $300.00 $0.13 Male 27 829 $220.50 $0.13 Colombo Karachi 5 2,403 $325.00 $0.07 Kolkata 3 643 $260.00 $0.20 Bangalore 2 Kathmandu Karachi 2 Trivandrum Male 3 671 $200.00 $0.15 Cost of travel is relatively high when compared to other regions
Model : Economy Fares Vs Distance 700 US$ 600 500 400 300 200 Observed 100 Linear 0 1000 2000 3000 4000 5000 Distance (Km)
Multiple Regression Analysis To identify the best fit regression line based on Least squares method to explain the past trend in air fare. Linear relation-ship is assumed Use of Dummy variables to qualitative country specific factors Use of binary code scheme Backward Stepwise Regression Analysis Indicator variables are considered together and not individually Significance of the overall model was done using the F test.
Model 1 Variables Entered/Removed b Variables Entered NEPAL, BANGLAD E, MALDIVES BHUTAN, DISNEW, PAKISTAN INDIA a Variables Removed Method. Enter Model 1 Model Summary Adjusted Std. Error of R R Square R Square the Estimate.934 a.872.823 62.643 a. Predictors: (Constant), NEPAL, BANGLADE, MALDIVES, BHUTAN, DISNEW, PAKISTAN, IND a. All requested variables entered. b. Dependent Variable: Economy Rate Model 1 a. Regression Residual Total ANOVA b Sum of Squares df Mean Square F Sig. 482745.0 7 68963.567 17.574.000 a 70635.413 18 3924.190 553380.4 25 Predictors: (Constant), NEPAL, BANGLADE, MALDIVES, BHUTAN, DISNEW, PAKISTAN, INDIA b. Dependent Variable: Economy Rate
Model 1 Coefficients a Unstandardized Coefficients Standardi zed Coefficien ts B Std. Error Beta t Sig. (Constant) -85.992 67.143-1.281.217 DISNEW.114.013.893 8.955.000 BANGLADE 179.800 35.134.519 5.118.000 BHUTAN 276.163 43.472.605 6.353.000 INDIA 102.864 44.544.278 2.309.033 MALDIVES 73.714 57.683.135 1.278.218 PAKISTAN -1.012 38.734 -.003 -.026.979 NEPAL 70.358 39.968.190 1.760.095 a. Dependent Variable: Economy Rate Model 1 2 3 Model Summary Adjusted Std. Error of R R Square R Square the Estimate.668 a.447.423 112.970.814 b.663.634 90.001.905 c.818.794 67.592 a. Predictors: (Constant), DISNEW b. Predictors: (Constant), DISNEW, BHUTAN c. Predictors: (Constant), DISNEW, BHUTAN, BANGLA
Economy = 58.909+0.009D+251.206*BH+140.792*BA fare D= Distance (kms), BH = Bhutan, BA = Bangladesh Interpretation and conclusions To all 7 countries distance had been a significant factor in determining the rates. All connecting flights to Bhutan have had an additional avg. cost of 251 in determining the fares, when other dependent variables are held constant. All connecting flights to Bangladesh have had an additional avg. cost of 141 in determining the fares, when other dependent variables are held constant. No country has achieved a better advantage compared to another in relation to distance or country specific factors
Bangladesh and Bhutan Bangladesh High costs as a result of strict regulations Protection of National carrier Bhutan Due to the geographical location it is difficult to reach (Limited access) High operating costs associated
Sri Lanka and the Hub status What does it take to be a hub? A modern hub : A commercial center, a place to which goods and information are brought for distribution. Business information, news, connections, market intelligence, practical experience, relationship networks, business contacts. Uniqueness of a hub Being geographically placed (link regions with other locations of the world.) Have the right capabilities, expertise, technical and support services
Modern Concepts of Hubs Hubs pull resources (goods, financial resources, scientific excellence) from outside into them (if they do not possess them abundantly themselves) and use their own expertise and special environment to distribute them to the world economy and add an extra value to them. In the world economic geography the phenomenon of agglomeration is important. A hub should be a transport centre A high influence of foreign and multinational agents in these locations. Examples; London, New York and Tokyo as important international financial centers.