Maritime transport planning:

- Optimization Perintis- Potential for cost reduction in inter-island container transport

Robert Verhaeghe (TUDelft)

Fitri Indriastiwi (Litbang MoT)20 oct 2014

ADB TA8045 (Phase 2)“Improving Domestic Connectivity”

CONTENT

1. Review: use of criteria (effectiveness of transport system, financial, economic,

social) for evaluation of transport, estimation of impacts for those categories

2. Illustration of the use of modelling for planning of Perintis transport Inter-island container transport

3. Conclusions – follow up Potential of the approach Expansions in view of current transport policy questions

1) Review on criteria and impact estimation

Framework for design and evaluation

Aspects in the evaluation

Scope of project analysis

Technical

Financial

Economic

Social

Optimization of project performance

Technical performance: process, efficiency (production function), supply-demand interaction, utilization, generation of basic alternatives

Efficiency - welfare optimization Direct effects: willingness to pay, location effects, cost savings Indirect effects: external and multiplier effects Shadow prices

Equity – welfare optimization: distribution effects between groups, locations and inter-temporal allocation

Profitability/cost effectiveness: cash flow balance, liquidity, cost recovery

Generation/modification of (additional) alternatives

Identify/develop sources of financing; cost recovery policies; public/private cooperation

Regulation, efficiency pricing

Taxation, tariff setting, social pricing

Feedback Specific measures

Different locations, positioning on demand segments, inter- temporal allocation

Mitigating measures, technological innovations

Scale-, productivity changes, supply-demand balance

Technical performance: process, efficiency (production function), supply-demand interaction, utilization, generation of basic alternatives

Profitability/cost effectiveness: cash flow balance, liquidity, cost recovery

Efficiency - welfare optimization Direct effects: willingness to pay, location effects, cost savings Indirect effects: external and multiplier effects Shadow prices

Equity – welfare optimization: distribution effects between groups, locations and inter-temporal allocation

Effectiveness of the transport system

• Example Perintis: – provide the transport service in the most

effective way fulfilling the demand for transport (frequency of service, minimum transport time),

– with the best input of ships and combination of ship tours

Financial impacts

• Example Perintis:– Standpoint of provider/sponsor

• Operation cost for providing the service• Revenue from the service for a particular price

setting• Cash balance: need for subsidy?

– Standpoint of user• cost of the service

Economic impacts

• Total effect of an improvement of transport on the welfare of the country/region

• Improved transport has a direct effect on some sectors of the economy but these effects propagate into related sectors

• Macro-economics has a modelling approach for this: Input-Output (I-O) modelling

• To include regional differences and transport a special version of I-O is available which includes trade between regions : a spatial I-O (Spatial Computable General Equilibrium model SCGE)

Economic impacts

• In macro-economics transport costs are called transaction costs; reduced costs improve trade and economic performance

• Problem: how well can the activities be supported by Perintis (small businesses, local) be included

in the SCGE? Little data on those activities; how well are they represented in the modeling?

Region A Region B

Trade

Transaction costs associated with

transport

Social impacts• Most difficult to determine and estimate; not included in

economic modelling

• Basically the analysis of how Perintis improves the lifes of people should be carried out at the micro-level

• Which standard of minimal service frequency should be provided?

• When can a transition be made to commercial service?

• An ability to pay analysis could indicate if commercial service can be afforded.

• However the remoteness of the place also a plays role because transport to such place maybe very expensive due to low load.

• Conclusion: evaluating/justifying transport subsidy to low income users and/or a disadvantaged part of the network is difficult (universal problem)

Quantification: challenge for transport planning

• Ability to quantify the functioning of the transport system and the impacts is necessary to compare alternatives

• In the present presentation focus is on quantification (modelling) to enable an assessment of transport effectiveness and financial impacts

• Applications

– Subsidized Perintis service

– Commercial inter-island container transport

2) Illustration of the use of modelling in

transport planning (Perintis, Inter-island container

transport)

Modelling basics

Transport analysis: supply - demand

Demand for transport

Supply of transport facilities

employmentsocial

transport modes

vehicle fleet(s)

infrastructure

trade

Transport market:equilibrium/performance

…

…

Value generated

Implementation cost

ADB TA8045: analysis framework

Demand for transport (O-D

matrix)

Transport supply system (infra,

routes,…)

Match of supply and

demand

Performance of transport system

(revenue, ….)

Design of improvements to the

transport system

Projection of economic

activity

Cost analysis (life-cycle)

Transport model (Omnitrans)

Base map (GIS)

Spreadsheets/ Matlab

SpreadsheetsMapinfo, Arcinfo

Demographic/ economic models

Survey + secondary data

Spreadsheets

Components of the framework

1) Demand estimation/monitoring: analysis of monitoring data, design and execution of a survey

2) Modelling: implementation of the Omnitrans transport analysis software including training

3) Cost analysis: derivation of life-cycle cost for shipping

4) Design of improvements to the Perintis service: Maluku case study

Analysis of Perintis

Implementation of transport software package at Litbang MoT

PANGKALAN AMBONTRAYEK R-31

Ambon -184- Geser -32- Gorom / Ondor -32- P. Kesui -17- P. Tior -36- Kaimer -12- P. Kur -28- P. Toyando -33- Tual -118- Dobo -118- Tual -33- P. Toyando -28- P. Kur -12- Kaimer -47- P. Tior -17- P. Kesui -32- Gorom / Ondor -32- Geser -184- Ambon -184- Geser -32- Gorom / Ondor -158- Tual -160- Dobo -132- Ambon

JARAK : 1.661 MIL FREKUENSI : 19 VOYAGELAMA PELY. : 19 HARI UKURAN KPL :

500 DWT/GT.325

KPA : Adpel AmbonKontraktor : PT. Pelayaran Dharma IndahDomisili : AmbonNama Kapal : KM. Cantika Pratama 02Kontrak : 3.265.634.925N.O.R : 04 Pebruari 2012

AMBON

GESER

GORAM/ONDOR

P. KESUI

P. TIOR

KAIMEAR

P. KUR

P. TOYANDO

TUAL

DOBO

Example: schematization of R-31

PANGKALAN AMBONTRAYEK R-31

Ambon -184- Geser -32- Gorom / Ondor -32- P. Kesui -17- P. Tior -36- Kaimer -12- P. Kur -28- P. Toyando -33- Tual -118- Dobo -118- Tual -33- P. Toyando -28- P. Kur -12- Kaimer -47- P. Tior -17- P. Kesui -32- Gorom / Ondor -32- Geser -184- Ambon -184- Geser -32- Gorom / Ondor -158- Tual -160- Dobo -132- Ambon

JARAK : 1.661 MIL FREKUENSI : 19 VOYAGELAMA PELY. : 19 HARI UKURAN KPL :

500 DWT/GT325

KPA : Adpel AmbonKontraktor : PT. Pelayaran Dharma IndahDomisili : AmbonNama Kapal : KM. Cantika Pratama 02Kontrak : 3.265.634.925N.O.R : 04 Pebruari 2012

AMBON

GESER

GORAM/ONDOR

P. KESUI

P. TIOR

KAIMEAR

P. KUR

P. TOYANDO

TUAL

DOBO

Links of the network (characteristics: distance, price,……)

Transit line defining the route (characteristics: frequency, ship characteristics, ….)

Data preparation …. Schematization transport system

LengthVelocity…..

Port dwell time

Data preparation …. Origin-Destination matrix

380

380

Results from modeling• Shortest route from Tual to Manokwari

R-49 : Sorong-Ternate loading-unloading

Results from modeling Connection of Sorong with the region : demand (O-D passengers and freight)

Results from modeling• Network performance: for example: trip time distribution

Results from modeling• Time to reach a larger place (services): for example access to

Ambon or Tual or Saumlaki for Maluku region

Maluku case (47 ports, 15 routes)

Locations to be connected (Maluku)

Base ports

Ambon

Saumlaki

Tual

47 ports

Criteria for design of the transport service

• Accessibility or Connectivity?

– Connectivity is usually used in the context of the economy: economists think about how the economy is connected and performing; better connection means less transaction costs and better economic performance

– Accessibility is usually used in the context of transport: a transport engineer/economist thinks in terms of improving the transport service; how well can a certain place be reached using the available transport facilities

• Basically the two concepts relate to the some thing in a different context

• Typical formulation

Criteria for design of the transport service• Typical formulation of Accessibility

– Usually a gravity type expression is used – The availability of public services can be considered proportional to the size of the population of a particular site. The accessibility of a site i will be proportional to the size of the population centers in the neighborhood and

inverse proportional to distance to reach those centers. Further of importance is the frequency by which the connection is provided, a higher frequency results in a higher accessibility.

Ai : accessibility Dij : distance to reach j from iPj : population in jFj : frequency by which the connection form j to i is providedm : nodes (population centers) in the network connected to iDij : shortest route to reach j from i with available transport (provided by Omnitrans)

• Typical formulation

ijj

m

jji DFPA

1.

1

Example accessibility

Set up of Maluku case

• Accessibility index: only relative indicator; gives overall impression of the differences in region, where most action is needed; not sufficient/detailed enough to make new design of the transport service

• Present approach: comparison existing situation with a new design using 5 more detailed criteria (elaborated below)

• Using rational concepts/judgement (reduced length of tours, avoid overlap, hub and spoke,…) a new set of 11 tours has been defined; this is compared with the existing situation (15 routes) using the 5 criteria

R34

R35

R36

R37

SORONG

R38

R39

R40

BIRINGKASI

R41

R42

TUAL

SAUMLAKI

AMBONR38

R43

POMAKOR44

R45

REO

R46

R47

R48

Bebar/Wulur

LuangLelang

MoaLakor

Kisar/Wonreli

EXISTING SITUATION(15 ROUTES)

R34a

R35a

R38a

SORONG

R37a

R46aREO

R47a

BIRINGKASI R41aR44a

POMAKO

R43a

R40a

R999

AMBON

TUAL

SAUMLAKI

AFTER RE-ROUTING(11 ROUTES)

Criterion 1: travel time performance

Criterion 1: travel time performance (cont.)

Criterion 2: access time

Criterion 3: number of visits - effectiveness

Existing 15 routes New 11 routes

Total number of visits 7460

Total number of visits 4910

Criterion 4: life-cycle cost

• Reduced number (4) of ships : saving 40 bln Rp/year

Criterion 5: passenger.miles – consumer cost

• Passenger miles: – Existing : 29 mln– 11 route : 21 mln

• Reduction consumer cost with 11 route: 1,5 bln Rp/year

• Subsidy = cost-revenue Existing (15 routes) 150 – 5,5 = 144,5 bln Rp/year

New (11 routes) 110 – 4 = 106 bln Rp/year

Evaluation summary• Criteria 1: travel time distribution is the same• Criteria 2 : slight improvement of the access time• Criteria 3:

– existing situation: very large variation of visits among the different ports– new route service: visits more equally distributed among ports but overall a reduced

number of visits to ports

• Criteria 4: – the overall cost for the ship operator/sponsor is the following: 40 blnRp/year (cost

savings) – 1.5 (reduced revenue because more efficient travel) = 38,5 blnRp (cost saving)

– Total Subsidy (Maluku) : from 144.5 to 106 bln Rp/year

• Criteria 5: reduced consumer cost : 1,5 blnRp/year (cost saving) • The new 11 route system represents a win-win proposal for

operator/sponsor and consumer

Evaluation summary (cont)

• Observation: visit to most ports is about 1 per week

• Socially acceptable?

• If visitation needs to be higher then this will increase the cost ; trade-off between social standard and cost

Analysis inter-island container transport

(how to reduce high transport/logistic cost?)

Existing container transport service (some characteristics)

• Wide range of ship sizes • Load factor

• Statistics on shipping service based on DGST data (2009)

Existing container transport service (some characteristics)

• Current cost container shipment: example– Pontianak to Tg Priok : 600 $/TEU

– China to Tg Priok : 400 $/TEU

• Imbalance between Inbound and Outbound flow (Java): examples

• What is the prospect for reducing transport cost?

Transport volume 2009 (TEU/year)

outbound inbound

Perak-Makassar 97.250 61.480

Priok-Belawan 233.430 114.030

Role of scale effects in maritime transport

• Globalization is driven by developments in maritime transport (world-wide: 90% of total ton.km) : scale effect, logistics harmonization in corridors

• Transport and Communication Costs Indexes, 1920-2000;

Role of scale effects in maritime transport

• To which extent can such scale effects be realized on the Indonesian network? What is needed to realize them?

• The following analyses have been carried out to find out:– Preparation of container transport cost model

(variables: demand volume, distance, ship size, load factor, logistic efficiency)

– Analysis of options for the national network (using transport model)

Illustration scale effect (using cost model)

Demand: 100 TEU/day Demand: 100 TEU/day

Optimal shipping size

• Optimum defined by : marginal cost for shipping = marginal cost for inventory

Distance: 3000 kmDemand: 100 TEU/dayTime value: 50 $/TEU.day

Optimum size: 700 TEU

What are the prospects for reduction of domestic container transport cost? Analysis approach

• We like to know what is possible in 2030

• Pro-active planning of improvements to shipping and network, and increased demand by 2030

• Set-up:

– Demand projection for 2030

– Design of supply system for 2030

– Matching demand-supply

Pro-active planning container transport 2030

• Domestic Network (26 strategic ports)

• Demand projection: Use is made of projection by [Indii, 2012]: demand 2030 = 5.4 * demand 2009

Potential for International flow

or

Pro-active planning container transport 2030 (continued)

• Design of transport supply infrastructure:– Shipping in 2030: line service (optimal shipping size)

– Port turn-around time: from 5 to 2 days

– Container handling cost: from 150 to 100 $/handling

– Network alternatives:• Alt 1 : international port at Sorong

• Alt 2 : “ “ Bitung

• Alt 3 : maritime highway (pendulum) and int. port at Sorong

International container flows (World Container Model, TUDelft, 2012)

Halim, R. A., Seck, M., Diouf, & Tavasszy, L. A. (2012). Modeling the global freight transportation system: A multi-level modeling perspective

Projected (WCM) international flow at Sorong

734000 TEU/year

Port Total Throughput (TEU) Fraction from International flow (%)Sorong 1,508,040 5.1

Tg Perak 8,653,203 29.2Tg Priok 16,406,638 55.3Tg Emas 479,392 1.6Belawan 2,615,310 8.8

Total International Flows 29,662,582 100

Matching supply and demand : Modelling (with Omnitrans) of the domestic network:

• Loading of the network (2030 demand + international flow through Sorong)

• Output : performance of the supply system for the 2030 demand

International flow

• Loading of the Pendulum direction Belawan-Sorong (2030 demand + international flow through Sorong + Pendulum)

Loading (west-east) of the maritime highway (1)

• Loading of the Pendulum direction Sorong-Belawan (2030 demand + international flow through Sorong + Pendulum)

Loading (east-west) of the maritime highway (2)

Challenge : Connecting Eastern Indonesia

Batam

Belawan

Malahayati

PadangJambi

Palembang

P. Bai

Panjang T. Priok

Banten

Cirebon

Semarang

Banjarmasin

PontianakBalikpapan

Samarinda

Bitung

Makasar

KupangBenoa

Surabaya

Ambon

Sorong

BiakJayapura

Timika

Merauke

P. Baru

Pendulum provides potential but eastern section commercially weak; potential contributions from:

- international flow- pricing- perintis

Results: contributions to the reduction of shipping cost in 2030

ship operation

port handling Total

Existing situation 320 300 620Scale effect in shipping 114 300 414

Improved turnaround time 75 300 375

Port handling 75 200 275

Average cost for container shipment ($/TEU)

Value of time Total

349 969

335 749

179 554

179 454

% contribution

43

38

19

Bitung versus Sorong

corridor length (km)

affected volume of domestic

containers (TEU/year)

international volume

(TEU/year)

Bitung + corridor

1945220,000

(2%)840

Sorong + corridor

2550414,000

(4%)734

Sorong + pendulum

52395,061,000

(50%)734

potential as hub for the

region

limited due to geographical position

strong potential; especially Papua

strong potential; especially Papua

service level

improved for North Sulawesi (from 100 to 182 trips/year)

strongly improved for East-I (from 70 to 182 trips/year)

strongly improved for East-I (from 70 to 182 trips/year)

3) Conclusions – follow up

Conclusions

• Observation: detailed quantification of the transport systems and their impacts strongly facilitates the analysis of alternatives

• Maluku case:

– optimization results in 25% reduction in cost (=40bln Rp/year) for same service;

– application to the total Perintis East-Indonesia (67 routes) may potentially result in a total savings of 18 tours (indicative 180 bln Rp)

• Inter-island container transport: strong reduction (50%) in the cost of container transport possible

Conclusions (continued)

• Economic/social justification of Perintis: represents most difficult assessment because of the social dimension of the service; difficult to determine the standard of the service, and to estimate its value to the welfare of the country

• Set up of a commercial transport service is much easier (supply can follow demand)

• Modelling provides a systematic tool to analyse the many alternatives for setting up a maritime highway and in particular address the challenges for East-I.

• Follow up:– Transport Demand estimation (passenger, cargo) linked to the national

(CBS) socio-economic data base would be an important expansion of the modelling and its data base

Demand projection from socio-economic/land-use data

National data base (CBS)

Monitored demand data

Estimation of relationship(s)

Projected socio-economic/land-use conditions

Projected demand