study on economic cost of inter-state barriers in goods traffic

7/30/2019 Study on Economic Cost of Inter-State Barriers in Goods Traffic

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FINAL REPORT

STUDY ON ECONOMICS OF

TRUCKING INDUSTRY

Submitted to:

The Under SecretaryMinistry of Shipping, Road Transport and Highways

Department of Road Transport and Highways

Parivahan Bhavan

1, Sansad Marg

New Delhi - 110001


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Sl. No Contents Page Nos.

Annexure VII Classifications 135 136

Annexure VIIIDistribution of Transport Operating Units by Numberand Type of Vehicles Owned 137 141

Annexure IX Distribution of Transport Operating Units by Type of

Unit and Regular Employment 142 144

Annexure X Distribution of Transport Operating Units by GrossValue Added (GVA)

145 152

Annexure XI Calculations for BTKM per Vehicle & Total BTKMbased on Vehicles as per Survey

153 156

Annexure XII-A Basic data from Sample Cities of Orissa after applicationof multipliers

157 157

Annexure XII-B Calculations for estimates for contribution of Orissa tothe All India Estimates

158 158

Annexure XIII Calculations for TKM per Vehicle as per Survey 159 162

AnnexureXIV(a) Example Chattisgarh - Gross Value added by per unit andby GVA per worker

163 164

AnnexureXIV(b) Example Chattisgarh-Raw Data for GVA Calculations 165 165


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LIST OF TABLES


1. Table 1.1: Trends in Rail-Road Modes in Freight & Passenger Traffic 22. Table 1.2: Share of Various Modes of Transport in Gross Domestic

Product3

3. Table 1.3: Road Length (in 000 kms) in India (1950-51 to 2005-06) 44. Table 1.4: Growth in Number of Registered Motor Vehicles in India 55. Table 1.5: Projections of Number of Goods Vehicles Required

Annually During the Eleventh Five Year Plan (2007-08 to 2011-12)under 9% GDP Growth Scenario

8

6. Table 2.1: States Selected in Stratum-I of Different Regions. 147. Table 2.2: Process of Selection of States in Stratum-II 158. Table 2.3: States Selected for the Study 169. Table 2.4: Selected Urban Localities (Towns) in Different Strata in

the Selected States 18

10. Table2.5: Region wise Summary of Total UFS blocks and selectedUFS blocks 20

11. Table 2.6 Number of Identified Goods Transport Units in the SelectedBlocks 22


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15. Table 3.4: Distribution of Goods Transporting Units by Class ofCities and Legal Status 37

16. Table 3.5: Distribution of Goods Transporting Units by Type ofTransport Unit and Legal Status 37

17. Table 3.6: Distribution of Goods Transporting Units by Regions andtheir Legal Status 38

18. Table 3.7: Association Membership Status of Goods TransportingUnits 39

19. Table 3.8 Distribution of Goods transporting Units by Source ofBusiness (All States) 4020. Table 3.9: Distribution of Goods Transport Operating Units by

Operational Channels (All States) 40

21. Table 3.10: Distribution of Goods Transporting Units by Their UsualArea of Operation 41

22. Table 3.11: Distribution of Goods Transporting Units by EmploymentLevels 42

23. Table 3.12: Distribution of Transport operating units by type of unitand regular employment 42

24. Table 3.13: Distribution of Employees in Urban Areas by GoodsTransport Operating units and Type of Workers 43

25. Table4.1: Distributionof VehicleOwnersbyFleetStrengthin


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28. Table 4.4: Distribution of Goods Transport Vehicles by Type, ofvehicles and type of operators 50

29. Table 4.5: Distribution of Goods Transport Vehicles by Type, ofvehicles over cities of different size classes 51

30. Table 4.6: Distribution of Goods Transport Vehicles by Type, ofvehicles over cities of different size classes 51

31. Table 4.7: Proportion of Vehicles with National and Local Permits indifferent Regions 52

32. Table 4.8: Proportion of Vehicles with National and Local Permits indifferent Vehicle Ownership Patterns 5333. Table 5.1: Distribution of Utility of Vehicles by Different Regions 5934. Table 5.2: Distribution of Utilization of Vehicles Covered by Survey 6035. Table 5.3: Estimated Annual Volume of Freight Hauled Per Vehicle

for Different Classes of Vehicles in 2009-10 (in Million TKM) 62

36. Table 5.4: All India Estimates of Volume of Goods Carried perAnnum in 2009-10 expressed as Billion-Tonne-Kilometers (BTKM)State and Region Wise

64-65

37. Table 5.5: Distribution of Volume of Freight by Industrial Sector(2009-10) 66

38. Table 6.1: Gross Value Added (Rs. Lakhs) per Unit through GoodsTransportationbyRoadfor EachRegion 72


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41. Table 6.4: Gross Value Added (Rs. Lakhs) per worker through GoodsTransportation by Road for Each Region 75

42. Table 7.1: Distribution of Owned Vehicles by Age (in years) Region-wise 78

43. Table 7.2: Distribution of vehicles by type of vehicle and age ofvehicle from Drivers Survey 79

44. Table 7.3: Distribution of Owned Vehicles by Age (in years) by SizeClass of Cities 79

45. Table 7.4: Fuel consumption of Vehicles by Type and Age 8046. Table 7.5: Average Distance Covered by Trucks per Year by Age of

Vehicle 81

47. Table 7.6: Disposition of Trip Time by Activities 8248. Table 7.7 : Distribution of Drivers by Driving Experience 8449. Table 7.8: Pattern of Expenditure of Goods Transporting Units by

Type of Unit 84-85

50. Table 7.9: Changes in Delhi-Mumbai and Delhi-Kolkata FreightRates for 9-tonne Truck and Diesel Prices (2002 to 2010)

87

51. Table 8.1: Freight Rates (September 2008) 99


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Executive Summary


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EXECUTIVE SUMMARY

A) Objectives and Methodology1. This Report relates to a study on the economics of transportation of goods by

road. The study is one of three transport sector studies assigned by the

Department of Road Transport in the Ministry of Shipping and Road Transport

and Highways, Government of India (GOI) to JPS Associates Ltd New Delhi.

2. The Terms of Reference of the study covered a) identification of the structure ofthe goods transport by road industry, b) study of the organization of the industry,

c) estimating the volume of goods transported by road, sector-wise / States-wise,

d) estimation of the contribution of the goods transport by road industry to

national economy, e) estimation of various economic parameters relating to

productivity and efficiency in the industry, and f) making suggestions for

improving the performance of the industry.

3. The study made use of the results of a sample survey of goods transport unitscarried out by JPS Associates, as well as secondary data available from various

sources. In addition to the sample survey of goods transport units, a small sample

study of truck drivers was also undertaken.

4. The sampling methodology adopted is one of stratified multi-stage randomsampling of States, urban locations and villages within the States and Blocks

within the urban locations, as described below:

The country is divided into seven regions for the purpose of selecting the states

within them. The seven regions are as follows:


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(ii) Northern (Hills) Region (Himachal Pradesh, Uttarakhand and Jammu &Kashmir)

(iii) Western Region (Maharashtra, Gujarat, Goa, Dadra & Nagar Haveli, Diu& Daman and Lakshadweep)

(iv) Southern Region (Andhra Pradesh, Karnataka, Kerala, Tamilnadu,Andaman & Nicobar Islands and Pondicherry)

(v) Eastern Region (Orissa, West Bengal, Jharkand and Bihar)(vi) North Eastern Region (Assam, Arunachal Pradesh, Meghalaya, Mizoram,

Tripura, Manipur, Nagaland and Sikkim)

(vii) Central Region (Madhya Pradesh and Chhattisgarh)

5. In each of the seven regions, two strata of States have been formed the firststratum comprising the State with the largest number of registered mechanized

goods transportation vehicles (used as a proxy for the number of mechanized

goods transportation units), and the second stratum comprising all other States in

the region. While the State in the first stratum is invariably selected, the second

stratum has been covered on a sample basis with one State selected with

probability proportional to the size measured by the number of registered goods

vehicles in the State. Thus a total of 14 states were selected for the sample

survey.

6. In each state, 3 cities were selected. The Capital city was invariably selected andfrom the balance cities, on city of above I lac population and another of less than

1 lac population were selected on a random basis. Thus a total of 42 cities were

selected.

7 While itwas felt that thegoods transportunits invillages may notbesubstantial


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8. Sampling within the selected locations was carried out by selecting randomlyfrom the NSSO urban frame blocks categorized as Business/Industrial Blocksand Residential/other blocks. For the survey 20% of the Business/Industrial

blocks were selected and 2.5% of the Residential/Other blocks were selected.

Thus a total of 2306 blocks were selected from a total of 60648 blocks.

9. In each of the sampled blocks, listing of all goods transport units was done andall such units were covered on a census basis. In this manner a total of 1212goods transport units were covered and a total of 754 drivers were covered.

10. For estimation of various parameters the results will be combined to get estimatesof each location. Multipliers were derived for each location to extrapolate these

results for the state and then the region. The summation of all region gave us the

All India Estimates.

11. The Volume of Goods Traffic was estimated by using the survey results to arriveat the Tonne Kilometres per vehicle. This was then multiplied by the estimated

number of goods vehicles in-use derived from secondary data to estimate the

total Volume of Goods Traffic for ALL INDIA.

12. For estimation of GVA, data was collected on all the items relating to transportsector in the NSSO schedules used in 63rd round and CVA estimated as per

block 4.2 of the NSSO schedules.

B) Current Trends in Goods Transport Industry13. Estimates made by the Eleventh Plan Working Group on Road Transport

indicated that the share of road transport in movement of goods by railways and

road taken together, which was just 13.8 % in 1950-51, has grown enormously to

613% fth f i htt ffi b 2004 05


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century the annual growth rate has been 10.2 against 7.4 over the period 1951-

2001.

15. Projections made by the Working Group on Road Transport Sector for theEleventh Plan showed that the demand for goods transport by road is expected to

grow from 844 BTKM (billion tonne kilometers) in 2007-08 to 1,231 BTKM by

the end of the Plan period (2011-12) under the 9 % overall GDP growth scenario,

or by 10.8 % per year.

16. Road transport of goods is almost entirely is a private sector operation. It is alsocharacterized by operations of a very large number of individual truck-owners

and several layers of intermediaries like agents, brokers and transport operators.

17. Bad roads, aged vehicles, inter-State barriers and other interfaces withofficialdom, result in losses in efficiencies of operation and productivity. Transit

times are found to be nearly double those of developed countries. Equipment

utilization rates for the Indian trucking fleet, which average 60,000 km to

100,000 km per truck-year, are less than a quarter of those in developed

economies. Despite many such impediments, India has achieved a highly

competitive low-cost road freight transport industry, with highway freight ratesamong the lowest in the world.

C) Structure of Goods Transport by Road18. Barring some captive freight movement operations of the government and some

public sector enterprises, the entire goods transportation by road is in private

sector. An important aspect of the trucking industry is the existence of a chain of

intermediary transport entities. Between the actual consignor and the consignee,

the ultimate receiver of goods there exist a series of links in the form of


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19. Of the 1212 units covered in the main part of the survey, 5% were agents, 53%operators, 6% brokers and 35% vehicle owners. The classification boundariesare often blurred as many units classified as of one type also perform the roles of

units of other types. Thus, the industry is characterized by considerable extent of

informality.

20. About two-third (60%) of the units were individual proprietorships and one-third(34%) were private/public companies. Partnerships are rather rare, being only tothe extent of just 3%.

21. About two-third of the units (68%) were members of the goods transportersassociations (local or national).

22. About 13 % of the units employed between 1 to 5 employees and about 50 %employed between 6 to 15 employees.

D) Ownership Pattern23. The trucking industry continues to be dominated by small players.24. Among the units classified as vehicle owners, about 83% had between 1 to 5

trucks. Of these 41 %t had just one truck, 42 % had between 2 to 5 trucks.

Another 6% owned fleets of size between 6 and 9.

25. Apart from the units classified as vehicle owners, many units (about three-fourths) classified as transport operators also had their own fleets.

26. About 52 % of the vehicles had national permits.27. Analysis by type of vehicle showed that about 9 % of the vehicles owned were

multi-axle vehicles (MAVs) 33 % were heavy commercial vehicles (HCVs)


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28. The Drivers survey conducted as a part of this study also threw up a similarvehicle mix.

E) Nature and volume of goods carried29. The study attempted an estimate of the total volume of freight in terms of billion

tonne kilometers (BTKM) carried by mechanized road transport during 2009-10making use of the data on per vehicle annual distance and tonnage hauled

collected through the survey.

30. According to these estimates, the Volume of Goods hauled has been estimated at1291 BTKM per annum for 2009-10. The Working Group on Road Transport

Sector for the Eleventh Plan projected the likely demand for goods transport byroad at 844 BTKM in 2007-08 and estimated a growth rate of 10.8 percent per

year. On this basis our estimate is close to that of the working group upon adding

the projected growth.

31. Of the total freight carried, industrial products accounted for 40 %, andAgricultural Commodities accounted for 22 %. About 17 % of the freight was

made up of construction materials.

32. These above mentioned estimates of freight carried are sensitive to the estimatedtotal in-use vehicle population. We have estimated it for 2009-10 by projecting

the in-use vehicle population in 2006 from secondary sources. A vehicle

utilization factor of 0.78 has been determined based on the survey and has been

used for estimating the freight hauled per vehicle per annum.

33. The estimation of volume of road traffic movement of goods on the above basiscan be no permanent substitute for a more methodical system of data on actual


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F) Contribution of the Industry to the Economy34. Gross Value Added (GVA) by trucking units surveyed has been derived, in

accordance with the Factor approach, as the excess of total receipts over

expenses less indirect taxes and wages and salaries to the pay roll and non-

payroll staff and income of proprietors and unpaid family members.

35. Based on the total GVA by the surveyed units, estimates of GVA per unit andGVA per worker have been derived. For all the locations in the seven States put

together, GVA per unit came to Rs.11.8 lakhs and GVA per worker to Rs

123000.

36. Total contribution of the goods transport industry as a percentage of the nationalGDP has been estimated at 1.93% on current money basis. The ministry

estimates for the entire transport sector (mechanized and non-mechanized)

including passenger transport is 4.5%.

G) Productivity and other parameters associated with the Industry37. About 69% of all goods carrying vehicles were less than 10 years in age. About

30% were less than 6 years old. On the other hand, about 31% of the vehicles

were over 10 years of age.

38. In the category of vehicles below six years of age, the vehicles were covering anaverage distance of 88800 kms. per year. Those which are 6 to 9 years in age had

done 85000 kms per year, those vehicle which are 10 to 14 years covered 82000

kms. while those aged 15 years or more had done 78000 kms. per year

cumulatively.

39. On an average, a commercial vehicle gave 7 kms. per liter of diesel. Theconsumption rate was 3.5 kms for MAVs, 6 kms. for HCVs, 7.9 kms. for MCVs


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40. On an average, goods carrying vehicles were utilized to the extent of 76 per cent.41. The total turn-around time was 21 hrs for trips of less than 500 km, 50 hrs for

trips involving a distance of 500 to 999 km, and 110 hrs for distances longer than

1000 km. Of this total trip times, actual running times accounted for 33 % for

trips of less than 500 km, 36 % for trips of distance 500 to 999 kms and 43 % for

longer distances.

42. Check-post halts accounted for about 16 % of the total trip time and other officialdelays for another 8 %.

43. Overloading has not been admitted to by the respondents, even though thepractice appears to be rampant.

44. From the drivers surveyed it appears that maximum number of drivers are wellexperienced with 6 years or more experience.

45. It is seen that direct costs account for more than 80 percent. A lions share of thisexpenditure is consisted of diesel (around 40%) and wages (around 30% for

wages and payroll).

46. Similarly expenditure for taxes shows 5.5 percent of the total expenditure andexpenditure on interest and depreciation shows only 5.0 percent of the total.

47. Fuel is an important component of the operational expenditure of truck owners,and periodic increases in fuel prices erode the profit margins unless the vehicle

owners increase their rates periodically. The truck freight rates for a standard 9

tonne truck for the Delhi-Mumbai stretch during 2002- 2010 are increased by 28

% and for Delhi-Kolkata stretch during same period are increased by 20%.


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H) Problems and Suggestions48. Small owners should be encouraged to come together in cooperatives and operate

as a single unit. With the pooling of resources, it should be possible to invest for

technological up-gradation. Another advantage out of several small operators

coming together is that they can better resist the pressures from the consignors

and transport operators to indulge in overloading as a measure of cutting

transport costs. That will also result in better utilization of available vehicles.

49. More efficient multi-axle trucks are relatively hard to come by, though in recentyears there is a tendency on the part of the goods transport vehicle owners to

switch over to such vehicles. To further encourage the use of multi-axle

vehicles, suitable incentives such as lower transit tax and toll rates may be

considered. The cost of such incentives would be more than paid back by way oflower levels of damage to the road system.

50. Rising fuel costs and competition preventing corresponding hikes in freight rateshas been cutting into the margins of the transport operators. To ease the

problem, a policy of dual pricing of diesel favouring goods transportation could

be thought of, at the same time taking appropriate steps to prevent misuse of the

benefits.

51. There does not seem to be any need or justification for a regime to regulatefreight rates as there is enough competition in the industry to drive the freight

rates to reasonable levels.

52. Overloading trucks is a common problem, though not brought out by the presentstudy, and affects the quality of roads that have been built for lesser axle loads. A

system of penalizing for overloading is installed to discourage overloading but it

is not effectively implemented


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54. Halts at check-posts result in loss of about 16 % of the trip time. Simplificationof procedures, paper work and installing green channel system for movement of

specified vehicles would result in better performance.

55. Rationalization of taxation regime could also result in speedier passage of trucksalong the roads and improve the services.

56. Road transport of goods sector suffers from the absence of a sound statisticalcollection system. Apart from periodical special surveys on different aspects of

the industry, it is necessary to put in place regular automated data collection

systems on goods movement at least on national and state highways to begin

with. An accurate and up-to-date data base on vehicle owners will also help in

planning and executing sample surveys more efficiently.


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Summary of Findings and Recommendations

at a Glance

A. FindingsI . Organizational Structure

Vehicle owner : 35% Transport Operators: 53% Agents: 5% Brokers: 6%

II . Ownership Pattern

Single truck owner 41% 2 5 trucks 42% 6 -9 trucks 6% >10 trucks 6%

III. Volume of goods transported

Estimated No. of goods vehicles in use (2009-10) 39.4 lakhs Estimated volume of freight 1291(BTKM)

IV. Contribution of trucking industry to the economy

Share of Transport in GDP 4.38% Gross value added per unit of transporters Rs.11.8 lakh Gross value added per worker in transport sector Rs. 1,23,000

V. Economic Parameters of Trucking Industry


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Average distance covered /yr. 85000 kms.. (7083 km./month) Total average trip time 59 hrs. Exp. on fuel, maintenance & wages 80%

B. Recommendations In view of fragmented structure of the trucking industry, it is suggested that

small owners should be encouraged to come together and operate as a single

unit (like cluster concept being propagated in the case of MSMEs)

To encourage the use of MAVs, which are more cost effective, introductionof incentives such as low transit tax and toll tax may be considered.

In order to achieve better fleet utilization, consolidation of vehicle ownersinto co-operatives or similar entities should be considered so that loads can be

easily distributed.

Excessive overloading should be strictly curbed to protect the road networksince very often the consignors indulge in pressurizing the truck owners to

overload. A system of penalizing the consigner in addition to the vehicle

owner for overloading may be evolved.

Greater use of tractor trailer multi axle vehicles will improve turn-aroundtimes and reduce costs. World Bank estimates that a 10% increase in the

usage of such vehicles could reduce transport cost by Rs. 5 billion /Yr.

Introduction of lower excise and toll and permit charges for such vehicles

could encourage increased usage.

Th ti l t t th h k t b d d b h i t f


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There is a need to improve the statistical base to monitor the performance ofthis highly fragmented sector. It is suggested that all states should set up amonitoring unit in the transport department and provide regular feedback to

impact policy initiatives.

To contain rising cost, particularly of fuel and spares, dual pricing policyshould be evolved. While lower price of diesel used for freight movement

would work as a measure to check inflation the higher pricing policy shouldbe used in the industry and the private passenger vehicles. However, one has

to guard against the possibility of misuse of the duel prices and diversion of

fuel purchased for freight movement to other purposes.

Lnking the amounts of insurance premiums to the past records of accidentscaused by the vehicle, apart from the past insurance claims, might act as a

deterrent and improve road safety. This, however, requires an integration of

information on road accidents and vehicle insurance.

It is essential to identify all major data gaps relating to goods transport byroad and establish suitable statistical systems in place.


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Chapter 1: Introduction


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CHAPTER 1

INTRODUCTION

1.1 Road Transport and National Economy1.1.1 An essential prerequisite of rapid economic growth is the availability of adequate support

from the infrastructure sector that includes energy, transport and communications. One

of the factors that has been inhibiting faster growth than is currently achieved and

substantial inflows of foreign direct investment to the Indian economy is the relative

scarcity of high quality infrastructure vis--vis many of the East Asian and South East

Asian countries. It is estimated that the growth rate of 9 % per annum targeted by the

Eleventh Five Year Plan (2007-12) would require massive investments in the

infrastructure sector to the tune of 9 % of the GDP by the terminal year of the Plan

(2012) compared to just 5 % of GDP in the initial year (2007) 1.

1.1.2 The network of roads that enables transportation of people and goods is one of the mostvital components of the countrys infrastructure. Together with railways, the road

transport sector (including both the road network and the enormous edifice of road

transport services) forms the lifeline of the entire economy. Because of the existence of

wide road network, though not always the best possible, and easy accessibility to even

the remotest corners of the country irrespective of the terrain, flexibility of its operations,

availability of door-to-door service and reliability, transportation of passengers and


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51, has grown enormously to 61.3 % of the freight and 87.1 % of the passenger traffic by

2004-05. This trend has occurred in spite of the existence of several inter-State barriers

to the movement of goods and even passengers by road, which is an indication of the

extent of the relative edge road transport has over rail transport. Table 1.1 shows the

trends in the shares of railways and road transport in the movement of people and goods

over the period 1950-51 to 2004-05.

Table 1.1: Trends in Rail-Road Modes in Freight & Passenger Traffic

Goods(Billion Tonne KM ) Passenger(Billion Passenger KM)Year

Road Railways** Road Railways**

1950-51 6.0 (13.8) 37.6 (86.2) 23.0*(15.4) 66.5 (84.6)

1960-61 14.0 (16.2) 72.3 (83.8) 80.9 (51.0) 77.7 (49.0)

1970-71 47.7 (30.1) 110.7 (69.9) 210.0 (64.0) 118.1 (36.0)

1980-81 90.9 (38.1) 147.7 (61.9) 541.8 (72.2) 208.6 (27.8)

1990-91 145.1 (38.1) 235.8 (61.9) 767.7 (72.2) 295.6 (27.8)

1999-2000 467.0 (60.5) 305.2 (39.5) 1831.6 (81.0) 430.7 (19.0)

2000-01 494 (61.3) 312.4 (38.7) 2075.5 (82.0) 457.0 (18.0)

2001-02 515 (60.7) 333.2 (39.3) 2413.1 (83.1) 490.9 (16.9)

2002-03 545 (60.7) 353.2 (39.3) 2814.7 (84.5) 515.0 (15.5)2003-04 595 (61.0) 381.2 (39.0) 3070.2 (85.0) 541.2 (15.0)

2004-05(P) 646 (61.3) 407.4 (38.7) 3469.3 (87.1) 515.7 (12.9)Figures in parentheses indicate percentage of modal share (P)- ProvisionalNote : 1. Figures for Road Transport from 1960-61 to 1990-91 are estimated based on percentage share ofRoad Transport and Railways given in the Working Group Report on Road Transport, Tenth Five Year

Plan 2002-07

2. Figures for Road Transport from 1999-2000 to 2000-01 have been estimated by Transport ResearchWing, Ministry of Shipping, Road Transport & Highways, Government of India

3. Figures for Road Transport from 2001-02 to 2004-05 have been estimated by the Sub GroupSource : * Tenth Plan Document ** Data on rail freight traffic from Ministry of Railways

Source: Report of the Working Group on Road Transport for the Eleventh Five Year Plan

1.1.3 Road transport sector contributed to the nations Gross Domestic Product (GDP) to the


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contribution to GDP over the period 1999-2000 to 2006-07 is given in Table 1.2. The

data reveal that the entire increase in the percentage share of transport sector as a whole

in GDP since 1999-2000 has come from road transport sector only.

Table 1.2: Share of Various Modes of Transport in Gross Domestic Product

1999-

2000

2000-

01

2001-

02

2002-

03

2003-

04

2004-

05

2005-

06

2006-

07Sector As percentage of GDP(at factor cost and constant 1999-2000 prices)

Transport, of which: 5.7 5.8 5.8 6.1 6.2 6.4 6.5 6.4

Railways 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

Road Transport 3.8 3.9 3.8 4.1 4.3 4.5 4.5 4.5

Water Transport 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

Air Transport 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

Services * 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

* Services incidental to transport.Source Central Statistical Organization: The share in GDP of Railways is exclusive of Financial IntermediationServices Indirectly. Measured (F.I.S.M.); for other modes it includes F.I.S.M.

1.2 Road Length and Vehicle Population1.2.1 The steady expansion in the volume of demand for movement of people and goods by

road has been accompanied by an increase in the road length and the vehicle population

over the years. The total road length has increased significantly from 3.99 lakh Km as on

31.3.1951 to 9.15 lakh Kms in 1971 and further to 42.36 lakh Km as on 31.3.2008. This

translates to a CAGR of 4.2%. However, a bulk of this consists of rural roads (25.77 lakh

km or 60%). Less than 6 % of the total road length is made up of national

highways/expressways and State highways, which are of relatively better quality, though


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only 13 %. The quality aspect has been receiving considerable attention, particularly

since the last decade, with the initiation of Golden Quadrilateral and the East-West and

North-South Corridor projects and other projects to up-grade other segments of the

National Highways. Quantitatively, road length has expanded at an average annual rate

of 4.3 % since 1951, primarily in the form of rural roads (average annual growth rate of

4.5%). The length of national highways increased by no more than 1.5 % per annum over

the period 1951 1991, but since then a greater sense of urgency shown by the

government in the wake of liberalized economic policies initiated in 1991 resulted in an

acceleration of the growth to 5.1 % per annum during 1991-20022. As on 31.3.2010, the

road length under National Highways was reported at 70,934 kms.

Table 1.3: Road Length (in 000 kms) in India (1950-51 to 2008-09)

All Roads National Highways State HighwaysYearTotal Surfaced Total Surfaced Total Surfaced

1950-51 400.0 157.0 22.2 19.8 NA NA

1960-61 524.5 263.0 23.8 21.0 NA NA

1970-71 915.0 398.0 24.0 23.3 56.8 51.7

1980-81 1485.4 684.0 31.7 31.5 94.4 90.2

1990-91 1998.2 1024.4 33.7 33.4 127.3 124.82000-01 3325.8 1573.8 57.7 57.7 132.8 130.6

2005-06*

3929.4 1846.6 65.6 65.6 144.4 142.9

2006-07 4003.9 1910.8 66.6 66.6 148.1 146.3

2007-08 4140.5 1997.3 66.6 66.6 152.2 150.7

2008-09 4236.4 2090.2 66.8# 66.8 154.5 152.7Source: Government of India, Department of Roads and Highways, Basic Road Statistics of India (2004-05, 2005-06, 2006-0 & 2007-08)

* Provisional#As on 31.3.2010, the total Road length under National Highway is 70934 kms.

1.2.2 If the expansion of road length over the years has generally been sluggish, except in thet d t i d f i i ibl d th th th i


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all vehicles and 10.2 for goods transport vehicles. These are only slightly different from

the corresponding historical rates of 10.9 and 7.4 respectively over the period 1951-2001.

Table 1.4: Growth in Number of Registered Motor Vehicles in India

No. of registered vehicles(000s)

Annual Growth Rate duringthe period

Year

All vehicles Goods vehicles All vehicles Goods vehicles1950-51 306 82 - -1960-61 665 168 8.1 7.4

1970-71 1865 343 10.9 7.4

1980-81 5291 554 11.2 4.9

1990-91 21374 1356 14.8 9.4

2000-01 54991 2948 9.9 8.1

2001-02 58924 2974 7.1 0.8

2002-03 67007 3492 13.7 17.42003-04 72718 3748 8.5 7.3

2004-05 (P) 79473 4393 9.3 17.2

2005-06 (P) 85896 4782 8.1 8.9

% Growth 1951-2001 - - 10.9 7.4% Growth 2001-06 - - 9.3 10.2

Source: Government of India, Department of Roads and Highways, Reproduced from Ministry of Finance,

Economic Survey 2007-08, Statistical Table 1.28

P ProvisionalNote: All vehicles include heavy and light commercial vehicles, buses, cars, three and two-wheelers

The disparity between the expansion of road length and expansion of vehicle population has

pushed up the vehicle density (number of vehicles per km of road length) from 0.76 in 1951 to

31.7 in 2005-06. Among all registered vehicles, two-wheelers accounted for 71 %, followed by

cars with a share of 13 % and other vehicles (a heterogeneous category including 3 wheelers,trailers, tractors etc) with 9.4 %.


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1.3.1 As observed above, movement of freight by road was only to the extent of 14 percent in1950-51. This share has grown to 65 % by 2004-05. The National Transport Policy

Committee (NTPC) in its report submitted in 1980 had recommended that at least 67 %

of freight traffic should move by rail by the turn of the century (2000). However, this has

not happened, as evidenced by the pattern of freight transport by road vis--vis by rail.

Goods transportation by road has increased relatively faster than that by railways,particularly during the decade 1990-91 to 2000-01 when the Indian economy witnessed a

sea change because of the liberalization of the policy regime. The shift in freight

movement from railways to roads has taken place despite railways advantages in terms

of bulk freight movement, carrying potential and economical land and the disadvantages

of road transport of goods due to various inter-State barriers and other bureaucratic

hurdles.

0

20

40

6080

100

1950

51

1960

61

1970

71

1980

81

1990

91

2000

01

2004

05

year

Trend in shares of railways and road transport in movement of

goods

Railways Road

1.3.2 The demand for road transport has increased faster than the demand for other modes.Thi th ld b tt ib t d t b th d d id d l id f t O th


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routes, increased the modal share of roads4. Future demand for freight traffic is expected

to be strong, growing at 1.5 times the economic growth rate for freight and 2 times the

economic growth rate for passenger traffic5. Between 1992-93 and 2004-05, the demand

for freight transport by road is estimated to have grown at an average annual rate of 6.7

% against the GDP growth of 6.2 %. Considering that the Eleventh Plan aims at a growth

rate of 9 % per annum, it is expected that the demand for movement of goods by roadwould expand by at least 10 % annually over the five years 2007-08 to 2011-12. Using

the elasticity of 1.1 for billion tonne kilometres (BTKM) with respect to GDP observed

during the years 1992-93 to 2004-05, the Working Group on Road Transport Sector for

the Eleventh Plan projected the likely demand for goods transport by road to grow from

844 BTKM in 2007-08 to 1231 BTKM by the end of the Plan period (2011-12) under the

9 % GDP growth scenario adopted finally. Thus, the average annual demand for road

transport of goods during the Eleventh plan has been projected at 1028 BTKM. The

projected annual growth rate during the Plan period is, thus 10.8 percent.

Projected demand for goods transport by road during the Eleventh Plan

0

500

1000

1500

2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12

Year

BTKM

Demand for road transport of goods (BTK M)


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1.3.3 Data on vehicles actually plying on roads is not available. As per the RITES study onRoad Traffic Flows (1998), the number of trucks was expected to rise to 26.90 lakh by

the turn of the century and to 28.70 lakh in 2005. Here again, projections made by the

Working Group on Road Transport for the Eleventh Five Year Plan are available for

various growth and efficiency of truck use scenarios.

Table 1.5: Projections of Number of Goods Vehicles Required Annually During the EleventhFive Year Plan (2007-08 to 2011-12) under 9% GDP Growth Scenario

Average annual vehicle fleet requirement (thousands)Type of Vehicle

Without efficiency gains With efficiency gains*

Light Commercial

Vehicles

2416.4 1599.4

Medium and HeavyCommercial Vehicles

2673.5 1769.6

Multi-axle Vehicles 51.4 34.0

Note: With an efficiency gain of 10 percent increase in lead per year during the Eleventh Plan

Source: Report of the Working Group on Road Transport for the Eleventh Five Year Plan

1.4 Some Features of Road Transport of Goods Industry1.4.1 There are certain features of industry of transportation of goods by road that distinguish

it from railway mode of freight movement in this country. While railways are a well

organized departmentally undertaken industry of the central government, road transport,

particularly of goods, is almost entirely is a private sector operation. It is also


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barriers and other interfaces with officialdom, causing delays and additions to costs,

often unofficial, slow speeds of movement, particularly in congested areas, result in

losses in efficiencies of operation and productivity. Transit times are found to be nearly

double those of developed countries. Equipment utilization rates for the Indian trucking

fleet, which average 60,000 km to 100,000 km per truck-year6, are less than a quarter of

those in developed economies. Despite many such impediments, mainly concerning theexisting infrastructure, India has achieved a highly competitive low-cost road freight

transport industry for basic services, with highway freight rates among the lowest in the

world.

1.5 Lack of Regular Statistics1.5.1 Again, unlike transportation by railways, which has a well-organized system of

generating detailed operational and financial statistics that enables planning for improved

performance, transportation of goods by road suffers from a complete lack of essential

statistics. As observed by the Working Group on Road Transport for the Eleventh Plan

There is complete lack of regular and reliable data on freight movement, passenger

movement on private buses, trucking industry; transaction costs involved in inter state

movement of goods . the motor vehicle registration, apart being variable across

States, does not give any indication neither of the actual number of vehicles in use at a

particular place nor about the current owners of the vehicles. The Working group

suggested measures for making the registration data more useful and recommended

surveys on:


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Passenger movement by Road: Passenger movement and related parameters byprivate bus operators need to be captured.

Trucking Industry: Survey of domestic trucking fleet covering operating cost,financing, vehicle technology, vintage, turn around time, utilization etc.

Time Motion Surveys: Assess time spent on various activities related to documentcompliance/clearances at barriers to ascertain transaction costs faced by road

freight/passenger industry.

1.6 The Present Study1.6.1

It is in the above context that the Department of Roads and Highways in the Ministry ofShipping and Transport has decided to have a series of studies conducted on the road

transport industry in the country. M/s JPS Consultants, New Delhi, have been assigned

studies on the following three aspects:

a) Volume of goods and passenger traffic on Indian roadsb) Economic cost of inter-State barriers in goods trafficc) Economics of trucking industry

1.6.2 This report is based on the study conducted on the economic s of trucking industry. Asper the Terms of Reference, this study is expected to make available the following

outputs:

i) Ownership pattern of the trucking industryii) Organizational structure of the existing truck industry in India


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v) Other peripherals viz., vehicle productivity, operational cost, various costparameters, time spent on various halts and check posts running time ofvehicle performing the journey between origins to destination

vi) Suggestive measures to improve/systematization of trucking operation inIndia

1.6.3 The study has been conducted by M/s JPS Consultants during February August 2008.The field operations were carried out by the Society for Natural Resource Management

and Community Development, New Delhi, and data processing by M/s B.R. Software

Services, New Delhi.

1.6.4 While Chapter-1 deals with introductory references on trucking industry, Chapter 2 ofthe report presents the methodological details of the study. Chapter 3 analyses the

organizational structure of the trucking industry and Chapter 4 the ownership pattern of

trucking industry in India. An assessment of the volume of cargo handled per year is

presented in Chapter 5 and an estimate of the share of trucking industrys contribution to

GDP in Chapter 6. Issues like vehicle productivity, operational costs, various cost

parameters, journey time and time spent on halts at the check posts and other barriers are

covered in Chapter 7. Finally, some issues relating to goods transport industry and

suggestions for improving the trucking operations in the country are presented in Chapter

8.


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Chapter 2: Scope, Approach & Methodology


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CHAPTER 2

SCOPE, APPROACH AND METHODOLOGY

This Chapter outlines the scope of the present study and the approach and details of the

methodology adopted.

2.1 Scope2.1.1 Conceptually, transportation of goods by road has two distinct segments based on the

technology adopted in such transportation. The National Classification of Industries,

2004 thus distinguishes between freight transport by motor vehicles (NIC Sub-class

60231) and freight transport other than by motor vehicles (i.e. man or animal drawn

vehicles like bullock carts, cycle rickshaws and the like) (NIC Sub-class 60232). The

present study is confined to freight transport by motor vehicles only.

2.2 Objectives2.2.1 As required under the TOR, the present study aimed at collecting information on

a) The ownership pattern of trucking industry in India,b) The organizational structure of the trucking industryc) The volume of cargo handled sector-wise and State-wised) The contribution of goods transport industry to GDP


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2.2.2 Approval of Methodology:It may be mentioned that the methodology outlined below has been finalised on the basis

of various comments received from and discussions held with the Ministry of Shipping

and Road Transport who had constituted a panel comprising representatives of

Directorate of Transport Research, the CSO and NSSO to review and approve the

appropriate methodology for the study. The sampling methodology thus finalised is

completely probability based and has been approved by the Ministry vide their letter of

29th

July 2010, and the study has been carried out in accordance with the approved

methodology.

2.3 Sampling MethodologyThe sampling methodology adopted is one of stratified multi-stage random sampling of

States, urban locations and villages within the States and Blocks within the urban

locations, as described below:

2.3.1

Regions:

The country is divided into seven regions for the purpose of selecting the states within

them. The seven regions are as follows:

(i) Northern (Plains) Region (Haryana, Rajasthan, Delhi, Uttar Pradesh, Punjab andChandigarh)

(ii) Northern (Hills) Region (Himachal Pradesh, Uttarakhand and Jammu & Kashmir)(iii) Western Region (Maharashtra, Gujarat, Goa, Dadra & Nagar Haveli, Diu &

Daman and Lakshadweep)


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(vii) Central Region (Madhya Pradesh and Chhattisgarh)

2.3.2 Selection of States: In each of the seven regions, two strata of States have been formed the first stratum comprising the State with the largest number of registered mechanized

goods transportation vehicles (used as a proxy for the number of mechanized goods

transportation units), and the second stratum comprising all other States in the region.

While the State in the first stratum is invariably selected, the second stratum is covered

on a sample basis with one State selected with probability proportional to the size of

registered goods vehicle population. The Variable the number of Registered Goods

Transportation Vehicles is taken as the size measure of probability as it is expected to be

highly correlated with the variable mechanized goods transportation units in use;

Selection of states in stratum-I :

Thus, the seven states with the largest number of registered mechanized goods

transportation vehicles selected from various regions are:

Table 2.1: States Selected in Stratum-I of Different Regions

Sl. No. Region State Selectedfor Stratum I

No. of Registered GoodsTransport Vehicles (2004) in Lakh

1 2 3 4

1. North (Plains) Haryana 2.062. North (Hill states) Himachal Pradesh 0.44

3. West Maharashtra 4.99

4. South Tamilnadu 4.81

5. East West Bengal 2.41

6 C t l M dh P d h 1 07


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The seven States selected in Stratum I together accounted for about 45 percent of the total

number of such registered vehicles in the entire country.

a) Stratum IISimilarly the Process of selection of States from Stratum II with probability proportional

to size, size being the number of registered goods transport vehicles is explained in Table

2.2 and the selected states shown in the last Column of this table (Table 2.2).

Table 2.2 Process of Selection of States in Stratum-II

Region States in Stratum II(i.e. excluding theStates in Stratum I)

No. of regd.goods vehicles(lakhs)

Cumulativetotal in theregions (lakhs)

Randomnumberselected

Stateselected

1 2 3 4 5 6Chandigarh 0.09 0.09

Delhi 1.52 1.61Punjab 1.10 2.71

Rajasthan 1.87 4.58

North

(Plain)

Uttar Pradesh 1.52 6.10

(between 1 and

610)449

Rajasthan

(0.307)

Jammu & Kashmir 0.42 0.42North

(Hills) Uttarakhand 0.15 0.57

(between 1 and

57)

56

Uttarakhand

(0.263)

Dadra & N. Haveli 0.07 0.07

Daman & Diu 0.04 0.11Goa 0.26 0.37

Gujarat 3.87 4.24

West

Lakshadweep 0.00 4.24

(between 1 and

424)262

Gujarat

(0.913)

A&N Islands 0.02 0.02

Andhra Pradesh 2.10 2.12

Karnataka 1.92 4.04

Kerala 2.09 6.13

South

Pondicherry 0.04 6.17

(between 1 and

617)

258

Karnataka

(0.311)

Bihar 0.63 0.63

Jharkhand 0.63 1.26

East

Orissa 0.86 2.12

(between 1 and

212)

174

Orissa

(0.406)

Arunachal Pradesh 0.03 0.03

Manipur 0.07 0.10

North East (between 1 and

88)

Meghalaya

(0.149)


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2.3.3 Selection of Urban Locations

In each of the selected States in Stratum-I and Stratum II, the urban localities have been

stratified as follows:

Sratum A : The State Capital Stratum B: Large Towns other than State Capital Stratum C: Other Towns

In all States, towns with a population of a lakh or more (according to 2001 Census)

formed Stratum B and all other towns Stratum C. The only exception is Himachal

Pradesh, where there is no town with a population of over 50,000, except Shimla, which

has already been covered as State Capital. In this case, the cut-off point was taken as

20,000.

While the State capital town is selected invariably in all States, one town each (locations)

has been selected on simple random basis from the other two strata. Thus, a total of 42

urban locations have been selected from the 14 States in Stratum I and Stratum II.

In all cases the alphabetical lists of cities and towns in different States published by

Registrar General of India in their web-site www.censusindia.gov.in have been used

for random selection of towns in Stratum B and Stratum C. Selection from the Stratum

comprising the larger towns (Stratum B of localities) was completed first by assigning

serial numbers to the individual towns and selecting one of them at random. Selection for

Stratum C towns was then done from all the towns in that stratum randomly.

The locations so selected are shown in Table 2.4. Further details of selection are given in

th ANNEXURE I


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Table 2.4: Selected Urban Localities (Towns) in Different Strata in the

Selected States

State State Capital Town more thanone lakhpopulation

Town less thanone lakhpopulation

1 2 3 4

1. Haryana Chandigarh Rohtak Haileymandi

2. Rajasthan Jaipur Jodhpur Phulera

3. Tamilnadu Chennai Tiruppur Chetpet

4. Karnataka Bangalore Belgaum Karwar

5. Maharashtra Mumbai Solapur Chakan

6. Gujarat Gandhinagar Vadodara Kheda

7. Madhya Pradesh Bhopal Burhanpur Hoshangabad

8. Chhatishgarh Raipur Durg Sakti

9. West Bengal Kolkatta Raiganj Memari

10. Orissa Bhubaneswar Baleswar Jharsuguda

11. Assam Guwahati Tinsukia Makum

12. Meghalaya Shillong Tura William Nagar

13.HimachalPradesh

Shimla Chamba Kulu

14. Uttarakhand Dehradun Haldwani Pauri

Note: In Himachal Pradesh, the cut off population adopted was 20,000


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or urban areas in the form of owners of trucks and truck drivers residing in rural areas. Itis considered that omission of such rural based enterprises would not impact much on the

study of various parameters relating to the economics of trucking industry. However, the

situation relating to the density, pattern of operations and other characteristics of

rural-based truck owning units will be assessed through a small sample study of

villages.

For this purpose, in each of the 14 States selected as indicated above, one district

and one (CD) Block within the selected district and two villages in each selected

Block have been covered. Thus, in all, 28 villages have been covered. The list of

villages so selected is given in ANNEXURE II

2.3.5 Sampling within the selected locationsThe procedure for covering goods transport enterprises within the selected

localities/villages as approved by the panel constituted by the Ministry on 3 March 2010

was adopted.

a) Urban areasIn the case of urban locations, lists of the NSSO Urban Frame Blocks (available fromtheir 2002-07 Urban Frame Survey) were obtained for each of the selected locations,

categorised by Type of Block (business, industrial, residential, etc as per the

classification followed by NSSO). As the transport units would be located mainly inbusiness and industrial areas, blocks have been selected using the following sampling

fractions, and simple random sampling.

20% of the Business and industrial Blocks and

2.5% of other Blocks (residential, slum, hospital areas, etc.)In each of the sampled blocks, all the foods transport enterprises identified through listing

units have been covered on a census basis.

b) Rural areas


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c) Sample SizeThe rural sample, as mentioned above, consisted of 28 villages. In the case of the

42 urban locations, there were a total of 60,648 NSSO UFS Blocks, of which

4,400 are business/industrial blocks and 56,248 are residential and other blocks.

Using the sampling fractions of 20% for business and industrial blocks and 2.5%

for residential other blocks, subject to a minimum of 1 block of a type at the

locality level, the total number of sampled blocks came to 2,306, of which 886

were business./industrial and 1,420 others. The sample size of UFS blocks for

each locality and block type is given at Annexure III and a Region- wise

summary is given below:

Table2.5: Region wise Summary of Total UFS blocks and selected UFSblocks

S.No. Region TotalBA/IA

UFS blocks

TotalRA/Other

UFS Blocks

TotalUFS

Blocks

SampleBA/IA

SampleRA /

Others

SampleTotal

1. North (Plains) 634 6406 7040 126 161 2872. North (Hills) 112 1030 1142 24 28 523. West 1709 20256 21965 342 509 8514. South 975 14948 15923 197 376 573

5. East 495 8268 876399 209 308

6. Central 402 3875 4277 81 98 1797 North East 73 1465 1538

17 39 56


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2.4 Coverage of Transport Companies, Brokers and Agents, Truck Owners and Driversin the selected blocks/villages

2.4.1 Motorised goods transport industry is not made up of a single homogeneous set ofplayers. Between the consignor of the freight and the consignee who are the actual users

of the goods transport services, there is a long chain of entities, though not all of the links

of the chain necessarily play a part in all transport operations. In its simplest form, the

consignor may directly engage a truck owner to deliver the goods to the consignee. In

some cases, he may approach the truck owners through a broker. A more complicated

operation, common when the business is large, is the involvement of intermediaries like

transport companies and booking agents who are engaged by the consignor and who in

their turn reach the truck owner for the actual haulage of freight directly or through a

broker. Various models of operation are possible and exist. The study has targeted to

cover all the types of players in the road transport of goods industry, and also the actual

drivers of goods transport vehicles.

2.4.2 Since drivers are also a good source of information regarding the operations of the truckson road, all the drivers found in the selected blocks were also covered.

2.4.3 The number of goods transport enterprises identified in the selected blocks of the twotypes is shown in Table 2.6.


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Table 2.6 Number of Identified Goods Transport Units in the Selected BlocksRegion BA/IA RA & Others Total

1 2 3 4

North-East 4 17 21

North Region 98 49 147

North-Hill 18 11 29

Central Region 55 49 104

Western Region 289 170 459

Souther Region 162 136 298

Eastern Region 77 77 154

All India 703 509 1212

2.5 Development of Survey Instruments2.5.1 A composite questionnaire (Questionnaire A atANNEXURE-V) has been developed

for collecting the information from the sampled transport operating units on various

aspects relevant to address each of the items included in the TOR. In addition a separate

questionnaire (QuestionnaireB at ANNEXURE-VI) has also been developed for


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2.6 Field Operations2.6.1 The field operations were carried out by the investigators and supervisors engaged by

JPS. The investigators and supervisors were given adequate training in the concepts and

definitions used in the two questionnaires and in the techniques of data collection and

related matters. A pilot was also carried out at Rohtak, Jaipur and Phulera besides onevillage. The collected data were also scrutinized.

2.7 Reference Period2.7.1 Keeping in view the relevance, convenience and the need to minimize recall lapse on the

part of the respondents, different reference periods have been used for different types of

data. For instance, data on expenditure and receipts of the transport units collected

through Questionnaire A related to the financial year 2009-10. Data on number of

workers related to end of March 2010. Utilization of vehicles was collected with

reference to the month preceding the data of survey. Detailed information on the recent

trips collected through both the questionnaires was in respect of the week that ended on

the date of the survey.

2.8 Data from Secondary Sources Used2.8.1 Apart from the primary data collected through the sample survey of goods transport units

described above, material from a number of other secondary sources have been utilized in

this report. Such material included the serial official statistics on the number of goods

transport vehicles registered with the Directorates of Transport in different States and the


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2.9 Estimation ProcedureThe estimates of various parameters will be obtained first for each sampled location, then

combined to get estimates for each of the sampled States and then combined to get

regional level and national estimates. The procedure followed for estimation within any

particular selected location and then combining them is as follows:

The estimate of a parameter for a selected location is obtained first as the sample means

for each Type of Blocks and combined by weighting them by the inverse of the sampling

fractions for different types of blocks.

These location level estimates will then be combined for all selected locations in the

location stratum to get the estimates for each location stratum, and then the estimates of

the two location strata in the State are combined to get estimates for the selected State.

Derivation of estimates for the region and the country is straightforward extension of this

procedure. In all the states the sample estimates for the selected State is divided by the

probability with which it is selected to obtain the regional estimate, as the selection of the

state is with probability proportional to size.

Let X be the population total of the parameter to be estimated. Let x(ijkl)be the total of

the sampled valuesof the parameter for the lthblock type, in kth location type (or locality,

as only one locality is sampled for each location type), in jth

sampled state stratum (orState, as only one state is selected in each state stratum) and i

thregion.


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Estimate of the parameter total for the sampled locality k is given by

Est x{L(k)} =

where f(b) is the sampling fraction for the bth

type of NSSOs UFS blocks (b =1 for

industry/business blocks, and 2 for Others). In fact, the fractions proposed are f(1) = 20%

and f(2) = 2.5%

Estimate for the selected state as a whole is obtained by

Est x{S(j)} =

where p(k) is the sampling fraction for the localities of type k ( k=1 for State capitals,

2 for localities with large population (in most States 1 lakh) and 3 for localities with less

population). These fractions are in fact the reciprocals of the number of towns of that type

in the State as per 2001 census, as only one town of each type at most was chosen (forStates in Stratum I, State capital was already covered in the first phase of the survey and

hence not chosen in the second phase.)


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The estimate for Region i is then given by:

Est x{R(i)} = {1/(i)}*

where (i) is the probability with which the State is selected. (In State stratum I, newlocalities in the State already covered have been taken and hence (1) is 1 in all regions.

(2), however, differs from region to region)

Finally, the national estimate is derived as the sum of estimates for all the seven regions

as

The multipliers at various levels have been combined in to a single set of overall

multipliers which can be applied directly to the sample totals within the sampled

locality. These are shown in the table attached in Annexure IV.

Estimation for the rural sample followed a similar pattern, from village to block todistrict, state region and national levels.

Explanatory note on methodology used for Calculation of Overall (or composite)

Multiplier and its use in Estimation

It is clarified that the overall (or composite) multipliers used for estimation is not any

new concept, but only a computational convenience.


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which is essentially the product of the multipliers at various levels, provides anoperationally convenient short-cut, without affecting the results in any manner

whatsoever.

An example will make it clearer. Let us, for simplicity, assume that one State is selected

in a region with probability p. Suppose there are 3 locations to be selected in that State

the State capital, one out of the n1 other larger locations and one out of the n2 smaller

locations. In each location, 20% (or one in 5) of the business blocks and 2.5% (or one in

40) residential blocks are selected. There is no further sampling involved as the selected

blocks are completely surveyed for goods transport units. Let us assume (for simplicitys

sake, and this does not in any way affect the procedure or argument) that the sample

consists of 1 Business block and one residential block in each of the three locations.

Thus, the sample is made up of

Location 1 B1 (business) and R1 (residential)

Location 2 B2 and R2

Location 3 B3 and R3

Let us assume that the variable being estimated is X, and the total of the values of X for

all the goods transport units in the sample are x (b1) and x(r1) for the business and

residential blocks respectively in Location 1, x (b2) and x(r2) for Location 2, and x (b3)

and x(r3) for Location 3.


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Since there is no sampling at the block level, the multiplier at that level is 1 and theestimates for various blocks are simply the totals x (b1) and x(r1) for the business and

residential blocks respectively in Location 1, x (b2) and x(r2) for Location 2, and x (b3)

and x(r3) for Location 3. The multipliers for different types of blocks are 5 for business

block and 40 for the residential blocks, being the inverse of sampling fractions. Thus, the

total Location-wise estimates are

Estimate for Location 1 = 5* x (b1) + 40* x(r1)



Now, Location 1 is the State capital, and so its multiplier at location level is 1. For

Location 2, the multiplier is n1 as one out of the n1 large locations is selected. Similarly,

the multiplier for Location 3 is n2.

Thus, the estimate for the State is 1* {Estimate for Location 1} + n1*{Estimate for

Location 2} + n2*{Estimate for Location 3} =

1* {5* x (b1) + 40*x(r1)} + n1*{5* x (b2) + 40* x(r2)} + n2*{5* x (b3) + 40* x(r3)}

Finally, since the State is selected with probability p, the estimate for the Region would

be

=1/p* (estimate for the State), i.e,


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This is the same as

(1/p*1*5)*{x (b1)}+(1/p*1*40)*{x(r1)}+(1/p*n1*5)*{x(b2}+(1/p*n1*40)*{x(r2)}+

(1/p*n2*5){x(b3} + (1/p*n2*40) { x(r3)}

Thus, if intermediate level estimates are not required, the overall estimate may be derived

as the weighted sum of all the block level sample totals, the weights (the underlined

factors) being simply the products of all the relevant multipliers at various stages, which

may be called overall or composite multipliers. The numbers in each of the factors is

known in advance, and hence, the overall (or composite multipliers can be determined in

advance.

National estimates are simply the total of all regional estimates and do not involve any

estimation procedures.

2.10 Estimation of Gross Value AddedOne of the important objectives of the study is to estimate the contribution of the

mechanised goods transport sector to the gross domestic product. The study therefore

attempted to estimate the Gross Value Added by this sector. The principles laid down in

the CSO Manual 2007 on National accounts have been followed while computing Gross

Value Added. As a practical guide, the procedures adopted by NSSO in their 63rd

Round

(Economic characteristics of Enterprises in Service Sector) have been adopted. The

NSSO used the following definitions:

Operating Expenses: The total value of services purchased and other expenses incurred


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including value of products and by-products manufactured, if any, by an enterprise duringthe reference period.

Gross Value Added: GVA is taken as the additional value created by the process of

production of an enterprise to the economy, and is calculated by deducting the total

operating expenses from the value of receipts.


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CHAPTER 3

ORGANIZATIONAL STRUCTURE OF THE TRUCKINGINDUSTRY

3.1 General3.1.1 Barring some captive freight movement operations of the government and some public

sector enterprises, the entire goods transportation by road is in private sector. An

important aspect of the trucking industry is the existence of a chain of intermediary

transport entities. Between the actual consignor, the original sender, and the consignee,

the ultimate receiver of goods, there exists a series of links in the form of transport

booking agents, transport operators, brokers and the vehicle owners. When the consignor

feels the need to move his goods from one location to another, he contacts a transport

operator either directly or through a transport agent. The transport operator may or maynot have his own vehicles. Quite often, he does. In case he does not have his own fleet or

his fleet is inadequate or otherwise occupied he will contact other transport operators

(including vehicle owners) directly or through a broker. It is ultimately the vehicle

owners who actually transport the goods from the consignor to the consignee.

3.1.2 Thus, between the actual users of goods transportation services, viz., the consignor andthe consignee on the one hand and the actual provider of transportation, viz., the vehicle

owner, there are a number of intermediaries who facilitate the entire process. The basic


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Consignorsare individuals or organizations who give orders to transport operators for

transporting goods by road to desired destinations, where the goods are received by

individuals or organizations known as consignees.Transport operatorsare the entities,

again individuals or registered or un-registered organizations, who generally operate

through regular or ad hoc arrangements with the consignors and book orders for

transportation of goods. They may or may not own their own vehicles and operate

through brokers and small truck owners. Some of them are large with their own truck

fleets and other infrastructure like warehouses and offices at a large number of locations

all over the country.

Transport Corporation of India, for instance, has a fleet of about 7,000 trucks and 3,000

offices.Truck (or vehicle) ownersare the individual owners of a small number of trucks,

quite often one and owner-driven. They contact or are contacted by transport operators,

usually through brokers, and actually carry out the transportation of goods from one

location to another. Some of them, particularly those catering to transportation of

household goods, are also directly contacted by the customers. Brokers have relations,

usually informal, with the truck owners and transport operators and act as intermediate

agents between the two, introducing truckers to the transporters operators or even

consignors directly and work on a commission basis charged from either the transport

t th hi l Th l t t t i i f l

Consi nor Trans ort A ent TransportOperator

Vehicle Owner BrokerConsi nee


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carried by trucks, and are the link between the transport operators and the consignors.

Some of them may also provide finance and go-down facilities. The survey conducted by

CIRT in 1998 revealed that around 44 % of small operators themselves take up the

multiple role of a transporters, broker and booking agent.

3.1.3 The basic model illustrated above with all the major players in the goods transportationby road sharing the operations has a number of variations in practice. In the extreme case,

the consignor himself may own trucks and may directly undertake the transportation

himself, dispensing with all intermediaries. More often, the consignor may engage a

transport operator directly who in turn may contact vehicle owners through a broker.

Further, the above division of various transport entities into the categories shown in theabove model is not watertight and the roles of various entities often overlap. A transport

operator or a broker may himself be a vehicle owner, or a vehicle owner may himself be a

driver of the vehicle. Thus, the industry is marked by considerable degree of

organizational variation, flexibility, informality and dependence on intermediaries.

3.1.4 Size and reach of operations is an important source of variation among the transportoperators. As mentioned in the previous chapter, the ownership pattern of trucking fleet is

highly skewed in favour of small operators but the range of variation is sizeable. Also the

truck operators can be classified on the basis of spread and extent of operations into local,

regional and national carriers. Thus, while at one extreme of the spectrum are truck

owners with a single truck each catering to haul of goods confined to a small local area,

at the other are giants like Transport Corporation of India with around 7000 vehicles and

over 3000 offices spread all over the country claiming a substantial share of the market.


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Some fleet operators encourage their own employees to become owners of trucks by

providing financial assistance, subject to the condition that vehicles should be

permanently attached to companies.

3.2 Distribution of Goods Transporting Units by Activity3.2.1 The proportions of different types of units, viz., agents, transport operators, brokers and

vehicle owners, in different States covered in the present survey are given in Table 3.1. It

may be mentioned in this connection that the classification of the goods transporting units

into these four categories was based on the units own perceptions as their main activity

and several times they may be engaged in multiple activities.

Table 3.1: Distribution of Goods Transport Operating Units by Type of Units in DifferentRegions

Percentage of units which areStateAgents

Transportoperators

Brokers

VehicleOwners

All

No. ofreporting

units

North (plain) 7 22 6 65 100 92159

North (Hills) 0 0 0 100 100 15862

West 5 51 19 24 100 83472

South 5 63 4 27 100 682922

East 3 37 25 35 100 47160

Central 5 2 4 88 100 41620North East 6 12 3 78 100 9477

All India 5 53 6 35 100 972673

No. of unitsreporting 51854 514576 62793 343449 972673


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performing more than one role in the transportation of goods, as would be seen in the

next paragraph.

It may also be seen that as per the abovementioned estimates, there are a total of around

9.7 lakh units engaged in transport trade.

If we were to analyze the same information by class of cities, i.e. the pattern of

distribution of different type of units in bigger or smaller cities, we would get an idea of

the type of concentration of activities in different class of cities (Table 3.2 below).

Table 3.2: Distribution of Goods Transport Operating Units by Type of Units inDifferent Classes of Cities

Percentage of units which areState

Agents Transportoperators

Brokers VehicleOwners

All

No. of

reportingunits

Capital Cities 19 42 8 31 100.0 92159

Cities >1 LacPop 10 42 14 35

100.015862

Cities


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operator or a broker. The units were asked about their multiple roles during the survey

and the results are shown in Table 3.3.

Table 3.3: Multiple Activities of the Goods Transporting Units (All Regions)

Percentage of units also performing the role ofType of unit

Agent Transport

Operator

Broker Vehicle Owner

Agent 100 0 1 0

Transport Operator 0 86 0 88

Broker 0 0 100 0

Owner 0 41 0 100

All India 5.33 52.90 6.46 35.31 100.0

The sum of percentages in the rows exceeds 100 because of multiple responses

A majority of the classified as transport operators (86%) are also vehicle owners, while

41% of vehicle owners also operate as Transport Operator. Thus, the classification into

the four categories is extremely fluid.

3.3 Legal Status of the Units3.3.1 The units were classified as Public and Private Limited companies, individual

proprietorships or partnerships on the basis of information collected during the survey.

Overall, about 60 percent of all units were individual proprietorshipsand most of the rest

were limited companies. It was found that the pattern differed from one unit type to

th (T bl 3 4)


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Table 3.4: Distribution of Goods Transporting Units by Class of Citiesand Legal Status

Percentage distribution of units by legal statusUnitType

Pub. Ltd.company

Pvt. Ltd.Company

Individualproprietorship

Partnership Notknown

Total

No. ofreporting

units

Cap 11 52 23 10 3 100 27139

>1 lac 6 30 50 5 8 100 165556


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Percentage distribution of units by legal statusUnittype

Pub.Ltd.

company

Pvt. Ltd.Company



Total

No. ofreporting

units

No. ofreportingunits

13478 324693 584821 26595 23085 13478 972672

3.3.3 The data collected also indicate differences between different Regions, as brought out bythe chart below (Table 3.6). In particular, the patterns shown by units in North, North

East and Hills shows a preponderance of individual proprietorship whereas units in

western region had 58% limited companies, East had 48% and south at 36%.

Table 3.6: Distribution of Goods Transporting Units by Regionsand their Legal Status

Percentage distribution of units by legal statusUnit type

Pub. Ltd.company

Pvt. Ltd.Company



Total

No. ofreporting

units

North(plain) 1 2 89 3 4 100 92160

North(Hills) 0 0 100 0 0 100 15862

West 10 48 30 3 9 100 83472

South 0 36 62 0 1 100 682922

East 2 46 47 5 0 100 47160

Central 3 34 18 34 11 100 41620North East 0 0 60 37 3 100 9478

All India 1 33 60 3 2 100 972672

No of 13478 324693 584821 26595 23085 13478 972672


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3.4 Membership of Trade Associations

3.4.1 Not all of the goods transporting units reported themselves as members of the local, Stateor national level trade associations. Usually, it is to be expected that units above a certain

size (in terms of turn-over or fleet strength) would become members of such associations

to enjoy the benefits of collective clout. The proportion of units who were members

varied from Region to Region and with unit type (Table 3.7).

Table 3.7: Association Membership Status of Goods Transporting Units

Number of units classified by

Membership ofassociations

Registration Status Legal StatusType oftransportoperating

units Member Not Registered Not Pub.Ltd.

Pvt.Ltd.

Ind. Partner-ship

NR

Agent 100 0 15 85 4 9 76 0 11

Transport

Operator49 51 47 53 1 43 54 1 1

Broker 100 0 85 15 9 56 26 3 6

Owner 85 15 29 71 0 19 73 6 2

Total 68 32 42 58 1 33 60 3 2

3.5 Source of Business and Service Providers3.5.1 In order to explore the relative preponderance of various types of business models

operating in the goods transportation industry as indicated in paragraph 3.1, each of the

units surveyed was asked as to from whom they derived business and through whom they


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Table 3.8 Distribution of Goods transporting Units by Source of Business(All States)

Percentage of units by source of businessType of UnitConsignor Agent Transport

OperatorBroker Vehicle

Owner

Agent 21.73 19.93 14.94 18.30 25.11

Transport Operator 18.09 16.04 22.89 22.27 20.71

Broker 13.25 19.13 26.89 33.07 7.67

Vehicle Owner 9.32 18.94 32.71 5.10 33.93

Table 3.9: Distribution of Goods Transport Operating Units by Operational Channels (AllStates)

Percentage of units carrying business throughType of UnitAgent Transport

OperatorBroker Vehicle

OwnerOthers

Agent 227665 34.28 19.71 6.80 30.44

Transport Operator 1731482 6.06 32.21 31.23 30.21

Broker 101942 18.8 27.1 35.4 16.8

Vehicle Owner 456101 23.6 30.6 4.6 40.4

3.5.2 These data indicate that the industry is not governed by any rigid system and is generallyoperated through a large measure of informal interdependence even though formal


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3.6 Spread of Operations3.6.1 The responses of the units to the question on their usual area of operation are summarised

in the following Table (Table 3.10).

Table 3.10: Distribution of Goods Transporting Units by TheirUsual Area of Operation

Percentage of units with usual area of operationType of unit Totalnumberof units

Withindistrict

AnywherewithinState

Inter-Statealong

specificroutes

All-India

All

Agent 51854 29 2 2 67 100.0

Transport

Operator

514576 8 2 0 90 100.0

Broker 62793 23 7 8 63 100.0

Vehicle Owner 34349 17 11 8 64 100.0

All 972673 13 6 4 78 100.0No. of vehicles 126754 55001 34699 756219 972673

3.6.2 As may be expected, there is an increasing tendency for all goods transport units to alsoundertake All India Operations. Thus we find that 78% of the units report that they

undertake All India operations. Most transport operators claim that they operate All India

(90%). Of course this does not mean that 90% of their business comprises of All India

business, but only that they also operate on All India basis.

3.7 Employment3.7.1 Employment in a unit is a good measure of the units size. Table 3.11 gives the

distribution of various types of goods transport operating units by total regular

employment (on payroll) in them and also the average employment per unit Taking all


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Table 3.11: Distribution of Goods Transporting Units by Employment Levels

Distribution of employment (%)Type of unitsNone 1 to 5 6 to 15 15 to 25 26 or

more

ALL

Agent 0 32 31 29 8 264066

Transport Operator 0 16 56 11 17 4600191

Broker 0 10 78 9 4 592725

Owner 0 9 41 8 42 3863478

Total 0 13 50 10 26 9320459

Total (Nos.) 0 1247351 4703420 947150 2422539 9320460

3.7.2 The employment pattern can also be analyzed by class of cities (Table 3.12). It can beseen that maximum number of employees are in the smaller cities of below 1 lac

population. However, the percentage of units with 25 or more workers is the highest in

the large towns of above 1 lac population.

Table 3.12: Distribution of Transport operating units by type of unit and regularemployment

Distribution of employmentTypesof city

Percent(%) None 1 to 4 5 to 9 10 to 24 25 or

more

All

All India Cap % 0 7 31 29 33 4.0

All India >1 lac % 0 3 30 14 53 32.5

All India


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or so. They are mostly engaged in office work and organization. Of course many single truck

owners also drive their own vehicles.

Table 3.13: Distribution of Employees in Urban Areas by Goods Transport Operating unitsand Type of Workers

No. of workers by type (%)Type ofunits Office

staffDrivers Cleaners Laborers Working

prop /Partner

Unpaidfamily

member

Other

ALL

Agent 16 34 26 5 15 4 0 264066

TransportOperator

5 44 33 6 5 6 0 4600191

Broker 8 41 33 6 8 2 0 592725

Owner 5 47 34 6 4 5 0 3863478

Total 6 45 33 6 5 5 0 9320459

Total

(Nos.)528432 4163377 3105802 529912 466817 505856 10133 9320460


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Chapter 4: Ownership Pattern of TruckingIndustry in India


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4.1.2 Past evidence shows that in India too owners of small fleets not only formed the bulk ofthe operators but also accounted for the largest chunk of the vehicle population. A study

by the National Council of Applied Manpower Research9

found that in the early seventies

about 98 percent of the fleet was owned by operators owning up to 5 trucks each. The

study on economic cost of inter-state barriers in goods traffic

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