FREIGHT FLOW ANALYSIS AT MAJOR PORTS IN INDIA GOPAL R PATIL - PowerPoint PPT Presentation

FREIGHT FLOW ANALYSIS AT MAJOR PORTS IN INDIA GOPAL R PATIL Assistant Professor Department of Civil Engineering Indian Institute of Technology Bombay (Contribution from Prasant Sahu, PhD Student) Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014 1

INTRODUCTION - 200 ports - 54 ports in east coast - 146 ports in west coast 7516.6kms coastline - India’s seaborne trade 95% by volume & 77% by value of international trade - Indian Ports Act, 1908 allows Maritime States to set up their own port systems Port Locations - Major Port trust Act, 1963, regulates 12 major ports Thematic Diagram of Major Port Locations ( Source: www.mapsofindia.com ) 2 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Growth Dynamics: India’s Port Sector • Overall average annual growth (major & non-major) 9.2% (2000-2012) • Major ports (7.3%) & Non major ports (13.7%) • Total Traffic, 2000-01: 383.85 Million tons Growth:143% • Total Traffic, 2012-13: 933.66 Million tons • Capacity utilization around 90-98% at Major ports • Highest annual growth in container traffic (15%) 3 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Annual average cargo share for major ports (2002-2011) Annual Average Sl. No. Port Name Port Code Cargo Share (%) 1 Kolkata 1001 8 2 Paradip 1002 10 3 Visakhapatnam 1003 12 4 Chennai 1004 10 5 Tuticorin 1005 5 6 Cochin 1006 3 7 New Mangalore 1007 6 8 Mormugao 1008 7 9 Mumbai 1009 10 10 JNPT (Mumbai) 1010 11 11 Ennore 1011 2 12 Kandla 1012 16 4 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Traffic Variation at each Major Port 100 2011-12 90 Cargo Volume (million tons) 2012-13 80 70 60 50 40 30 20 10 0 Chennai Cochin Ennore JNPT Kandla Kolkata Mormugao New Mangalore Mumbai Paradip Tuticorin Visakhapatnam 5 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Cargo Volume at Indian Ports (2001-2013) Cargo(million tons) Major Minor port port Year Major Minor Total Ports Ports Volume Share (%) Share (%) 2001-02 287.58 96.27 383.85 74.92 25.08 2002-03 313.55 105.17 418.72 74.88 25.12 2003-04 344.79 120.84 465.63 74.05 25.95 2004-05 383.75 137.83 521.58 73.57 26.43 2005-06 423.56 145.53 569.09 74.43 25.57 2006-07 463.78 186.12 649.9 71.36 28.64 2007-08 519.31 203.62 722.93 71.83 28.17 2008-09 530.53 213.20 743.73 71.33 28.67 2009-10 561.09 288.86 849.95 66.01 33.99 2010-11 570.03 314.85 884.88 64.42 35.58 2011-12 560.13 353.02 913.15 61.34 38.66 2012-13 545.79 387.87 933.66 58.45 41.54 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014 6

Growth in Indian Seaborne Trade 16 12 8 4 Growth (%) 0 -4 Indian Seaborne Cargo -8 Indian GDP World Trade Volume -12 World Seborne Cargo -16 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 Year 7 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Commodity wise traffic at Major Ports Commodity 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 group POL 142.094 153.548 168.299 174.384 179.104 185.981 Iron ore 79.217 80.584 91.993 94.091 60.401 28.472 Fertilizers 12.196 14.136 16.662 18.198 20.386 14.738 coal 68.827 60.351 64.739 70.594 78.785 86.660 Container 62.009 73.469 92.283 93.123 127.876 127.525 Others 59.225 81.694 84.808 79.979 101.364 110.118 Total 423.568 463.782 519.314 530.379 560.137 545.790 75% of containers are handled by JNPT and Chennai Port POL: Kandla (27%), Mumbai (18%), New Mangalore (12%) 8 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Cargo at Mumbai Port (1900-2012) 70 Tonnage value (million tons) 60 Inbound tonnage Outbound tonnage 50 Total tonnage 40 30 20 10 0 1900 1920 1940 1960 1980 2000 2020 Year 9 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Commodity Share at Mumbai Port (10 Years) 60 CRL: Crude oil 50 POLP: Petrol Oil and Lubricant Commodity share (%) Inbound share (%) 40 Products Outbound share(% ) ISTL: Iron and Steel 30 BCHM: Bulk Chemicals 20 FTL: Fertilizers RPHP: Rock Phosphate 10 SLPH: Sulfur 0 EDBL: Edible Oil CRL POLP BCHM FTL RPHP SLPH ISTL EDBL Commodity Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Cargo Demand Estimation (Mumbai Port) • Univariate Regression Models • Multi-variate Regression Models • Time series Models Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Univariate Regression Models M1 and M2:  0.477 Inbound 20.820( GDP )  0.733 Outbound 0.348( GDP ) Models M3 and M4:      6 Inbound 3.219 5.010*10 GDP 66.747 FGP 0.188 CRLP      6 Outbound 4.232 1.001*10 GDP 22.277 FGP 0.382 CRLP GDP: Gross Domestic Product in ‘ 000 crore INR (ten billion Indian Rupees) CRLP: Crude Oil Production in million tons FGP: Food Grain Production in million tons 12 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Statistical parameters for Univariate Models t-statistics Adj. (p-values) Tonnage Model R 2 F-value R 2 GDP FGP CRLP β 0(i) ( β 1 ) ( β 2 ) ( β 3 ) 16.11 2.49 M1 0.836 0.833 254.878 (0.000) (0.016) Inbound 2.31 11.24 3.55 -3.23 M3 0.942 0.938 259.862 (0.025) (0.000) (0.001) (0.002) 11.87 2.19 M2 0.734 0.729 137.969 (0.000) (0.023) Outbound 2.06 2.03 -2.81 4.45 M4 0.815 0.809 70.487 (0.045) (0.048) (0.025) (0.000) 13 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Multivariate Linear Regression Model Models M5 and M6:      6 Inbound 2.485 10.013*10 GDP 50.362 FGP 0.372 CRLP      6 Outbound 3.862 8.002*10 GDP 18.864 FGP 0.474 CRLP Statistical parameters for multivariate models t-statistics (p-values) R 2 Adj. R 2 Tonnage Model F-value GDP FGP CRLP β 0i ( β 1 ) ( β 2 ) ( β 3 ) 2.11 2.79 5.40 -2.34 Inbound M5 0.967 0.967 468.848 (0.039) (0.007) (0.001) (0.023) 2.22 3.46 -2.53 6.94 Outbound M6 0.868 0.862 105.212 (0.000) (0.001) (0.024) (0.001) 14 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Residual analysis, variance inflation factor (VIF) 2.0 2.0 1.5 1.5 1.0 1.0 Standardized residuals Standardized residuals 0.5 0.5 0.0 0.0 -0.5 -0.5 -1.0 -1.0 -1.5 -1.5 -2.0 -2.0 0 5 10 15 20 25 30 35 40 0 4 8 12 16 20 Predicted inbound tonnage (million tons) Predicted outbound tonnage (million tons) Residual Plots Variance Inflation Factor Variable VIF GDP 11.31 FGP 7.47 CRLP 10.1 15 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Validation of Regression Model (16% data) Prediction error (%) of regression models with validation data Cargo Modeling Prediction Model Operation Approach Error (%) Univariate regression M1 12.84 (nonlinear) Univariate multiple Inbound M3 15.89 regression Multivariate regression M5 8.81 Univariate regression M2 18.90 (nonlinear) Outbound M4 Univariate regression 17.28 Multivariate regression M6 9.65 16 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Validation of Regression Models contd. 25 40 Actual outbound tonnage Tonnage value ( million tons ) Tonnage value ( million tons ) 20 Predicted outbound tonnage 30 Actual inbound tonnage Predicted inbound tonnage 15 20 10 10 5 0 0 1954196519701972198819891997200520082009 1954196519701972198819891997200520082009 Year Year Predicted outbound tonnage (million tons) 40 Predicted inbound tonnage (million tons) 24 32 18 2 =98.3% R 24 R2=98.8% 12 16 6 8 0 0 6 12 18 24 4 12 20 28 36 Actual outbound tonnage (million tons) Actual inbound tonnage (million tons) 17 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

Vector autoregressive model Model Structure:              1 1 Y c Y               1 t 1 11 12 1 t 1 1 t                  1 1     Y c Y    2 t 2 2 t 1 2 t 21 22        1 1 Y c Y Y   1 t 1 11 1 t 1 12 2 t 1 1 t        1 1 Y c Y Y   2 t 2 21 1 t 1 22 2 t 1 2 t Y 1t = Inbound freight flow at time t Y 2t = Outbound freight flow at time t 18 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014

VAR (1) MODEL Models M7 and M8:     Y 0 . 1377 1 . 0214 Y 0 . 0429 Y  1 t 1 t 1 2 t 1     Y 0 . 1612 0 . 0863 Y 0 . 9316 Y  2 t 1 t 1 2 t 1 t- value p- value Parameter Estimate c 0.1377 8.790 0.0318 1  1.0214 36.39 0.0001 1 Inbound 11  1 0.0429 4.220 0.0238 12 c 0.1612 9.820 0.0137 2  1 0.0863 2.730 0.0075 Outbound 21  1 0.9316 23.58 0.0001 22 19 Workshop on Urban Freight Transport: A Global Perspective9-10 April 2014 4/15/2014