THE ISSUE OF DWELL TIME CHARGES TO OPTIMIZE CONTAINER TERMINAL CAPACITY

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

THE ISSUE OF DWELL TIME CHARGES TO OPTIMIZE CONTAINER TERMINAL CAPACITY By Filip MERCKX* * Research Assistant, Department of Transport and Regional Economics, University of Antwerp, Keizerstraat 64, 2000 Antwerp, BELGIUM Tel: +32 3 275.51.40, Fax: +32 3 275.51.50, E-mail: [email protected]

Keywords: container dwell times, terminal capacity, storage yard capacity, charging policies, port pricing, supply chain management Abstract: The capacity of a container terminal depends on a number of factors. One of these factors - often disregarded in capacity planning - is the dwell times of containers on the stacking area. The container dwell time is the average time a container remains stacked on the terminal. The shorter the dwell time, the higher the potential utilization of a container terminal (expressed in TEU per hectare terminal surface per year and for a given stacking height). In theory, reducing the average dwell time of containers is to be considered as a cost-effective measure to optimize terminal throughput. In particular, at terminals where the available stacking area or storage yard limits the throughput capacity even marginal dwell time reductions have a major impact on the storage yard capacity. However, given the fact that stacking areas/storage yards of container terminals are utilized by shippers/consignees (both for import and export cargo) as overflow nodes in their supply chain, dwell times tend to be dictated by the shippers and have a tendency to increase. Especially in the current market conditions of strong growth in the container sector, these increasing dwell times of containers result in capacity bottlenecks on terminals. With regard to import cargo a quicker landside removal of containers would result in a reduction of dwell times, improving the level of terminal services and avoiding capacity bottlenecks. A just-in-time delivery of export cargo to meet the intended vessel on the other hand would also reduce container dwell times and improve the storage yard capacity The common practice to use terminal stacking areas as overflow nodes in logistics chains can partly be explained by the absence of charging schemes to penalize excessive dwell times. This paper deals with the issue of dwell time charges to optimize container terminal capacity. The following aspects are dealt with: ‐ An analysis of average dwell times based on cargo flow patterns (import, export and transhipment); ‐ The introduction of pricing mechanisms to reduce dwell times on container terminals, based on an extensive literature overview of port pricing systems; ‐ Assessment of the impact of dwell time charging schemes on the terminal capacity and the future role of terminals as buffers in logistics chains. As such this paper provides a theoretical background for the introduction of dwell time charges on containers to improve the throughput capacity of container terminals. The content of this paper is based on ongoing research and includes a road map of future research on the issue of container dwell time charges.

1

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

THE ISSUE OF DWELL TIME CHARGES TO OPTIMIZE CONTAINER TERMINAL CAPACITY 1. INTRODUCTION The operations performed on a container terminal consist of a number of different processes. In order to optimize the throughput capacity1 of a container terminal, these processes are implemented in a logic sequence. As such, it is possible to represent the layout of a container terminal for import, export and transhipment container flows as in Figure 1. Figure 1: Typical layout of a container terminal

Remark: the Ship Operation Area also includes barge and feeder operations

Source: Steenken et al, 2004, pp. 6

Sgouridis and Angelides (2002) define the different operational activities performed in each functional area of an all-straddle-carrier container terminal. Important to mention in this respect is the fact that the throughput capacity of a container terminal depends on a rapid succession of the different terminal processes. Generally, the container flow through a container terminal system (CTS) is split up in four subsystems/operations: ship-toshore, transfer cycle, storage and delivery-receipt area. Henesey (2004) provides a brief description of these subsystems. Figure 2: Schematic overview of a container terminal system (CTS)

Source: Henesey, L.E., 2004, pp. 5 1

Maximum number of containers which can be processed by the container terminal system. Hereby, the throughput capacity of a container terminal system depends on various constraints

2

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

In this paper we will mainly focus on the influence of container dwell times on the operational capacity of the terminal stacking area or storage yard2. In contrast to the available set of simulation papers on container terminal capacity, the aim of this seminar paper is to provide a theoretical framework to evaluate the impact of container dwell times on the container terminal capacity.

2. PARAMETERS INFLUENCING CONTAINER TERMINAL CAPACITY In order to define the capacity of a container terminal it is important to cover peak moments. Given the definition of the National Ports Council the annual terminal throughput capacity is defined as ‘the maximum throughput of cargo which the operator believes can be achieved on a continuing basis without incurring severe delays and disruptions’ (NPC Bulletin, 1980:53). Winkelmans (2004) points out that this definition deals with a specific value – referred to as throughput – which is influenced by the assessment of the terminal operator and that it is determined for an activity on a permanent basis without delays or interruptions. In this respect the study of the National Ports Council defines two different types of throughput/capacity: ‘maximum attainable throughput’ (MAT)3 and the ‘highest efficient attainable throughput’ (HEAT)4 (see Figure 3). The distinction the National Ports Council has made to indicate the port capacity can also be extended to the representation of the intrinsic (CHI) and effective handling capacity (CHE) of a container terminal (NPC Bulletin, 1980:53). Figure 3: Schematic representation of MAT and HEAT of a container terminal Throughput

MAT = CHI

HEAT = CHE

Over occupation

Under utilization

Time

Source: Winkelmans, W., 2004, based on NPC Bulletin, 1980 and Manalytics, 1976 2

In the remainder of the seminar paper we will refer to the terminal stacking area as the storage yard and in our view this area comprises the land surface of the terminal, excluding the apron, the area dedicated for administrative buildings and the area to perform hinterland operations. 3 The top limit at which the factor can be utilized even when the provision of every other factor is favourable 4 Capacity to process a specific volume of cargo on a permanent basis without detrimental effects (e.g. unacceptable waiting times)

3

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus MAT = CHI HEAT = CHE

TROUGHPUT

SLACK CAPACITY OVERCAPACITY SLACK CAPACITY

TROUGHPUT

SLACK CAPACITY

UNDERCAPACITY

Source: Merckx, J-P., 1991, pp. 2

A container terminal designed for a specific container throughput will only operate on a fraction of his intrinsic capacity. This level of utilization depends on a number of interrelated systems, critical components and strategic/operational considerations of the terminal operator. The storage yard is influenced by four parameters of which the dwell time is the primary factor focused on in this paper. As shown in Figure 4, it is obvious that the throughput capacity of a container terminal (CHE or HEAT) is determined by numerous components and thus can vary significantly from the intrinsic capacity (CHI or MAT). Figure 4: Different parameters/factors influencing the intrinsic container terminal capacity (in TEU) Scope of this paper

Source: Lemper, B., 1996

Figure 2 presents the factors influencing the throughput capacity of a container terminal as a continuous process, whereby each segment constitutes a certain operational capacity constraint. Consequently, the final throughput capacity of a container terminal will be determined by the segment with the smallest diameter or biggest capacity constraint. In order to increase the throughput capacity it is vital to have a clear understanding on the capacity constraints in other segments of the container terminal system.

4

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

In the remainder of this paper we will assume that the terminal stacking area (cf. storage yard in Figure 2) is the bottleneck in increasing the throughput capacity. Moreover the terminal stacking capacity5 is not only affected by technological/spatial constraints of deployed container terminal equipment, but also by container dwell times. Given the fact that terminal operators have no direct effect on container dwell times they are looking at indirect measures to affect this parameter. In this respect, we will analyse the effect of container dwell times on the storage yard capacity. 2.1. Storage yard capacity Traditional measures to increase the storage yard capacity are rather space intensive. Given the limited space available to expand terminal activities, this option nowadays has also become increasingly capital intensive. As such container terminal operators are looking for different possibilities to optimize their storage capacity: either by introducing new stacking and/or handling technologies, by increasing the stacking height (e.g. stacking 6 rows high instead of 3) or by improving the annual turnover rate6. As stated earlier in this paper we will focus on the latter: how to reduce container dwell times and improve cargo turnover rates? 2.1.1. Dwell time concept In general terms, the container dwell time is the average time a container remains stacked on the terminal and during which it waits for some activity to occur (Manalytics, 1979:31). According to this definition dwell time also refers to the efficiency of terminal operations. The shorter the dwell time the more efficient the performed operation and vice versa. Important to highlight in this respect is that dwell times can be influenced by many factors, some of which are unrelated to the service quality. For instance, commercial customers often use the storage yard as an overflow node in their supply chain creating an intentional delay. This situation distorts dwell time data since some of the commercial customers place their export cargoes on the terminal well before the time required to meet the intended vessel and may leave their import cargoes on the terminal yard for an extended time after their arrival. Another aspect of the dwell time is the amount of time required to process the paperwork for the release/intake of a container. However, with the increasing level of information and paperless documentation procedures in (maritime) transportation this specific element is becoming less relevant. In order to analyse data on container dwell times it is important to take these aspects into account. 2.1.2. Literature review on dwell times The literature on dwell times mostly emphasizes operations research oriented issues of container terminal capacity. The general framework of how to calculate port/terminal 5

In the remainder of this seminar paper referred to as storage yard capacity The annual turnover rate is the complement of dwell time. For example, at full capacity utilization when the average container dwell time is 5 days the cargo in these slots will on average ‘turnover’ 73 times per year (Manalytics, 1979:31) 6

5

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

capacity is presented in NPC Bulletin (1980), Manalytics (1979), De Monie (1981 and 1985) and Lester et al (1986). Watanabe (2001) analysed capacity constraints, productivity, selectivity and flexibility of different container handling systems in function of the type and size of the terminal. Steenken et al (2004) cover the different operational aspects of a terminal structure, including the deployment of handling equipment. Furthermore, this paper touches upon the different optimisation processes in container terminal operations and different types of relevant simulation systems. A second set of papers can be classified as simulation-based papers aiming to model the sequential flow of operations to improve terminal performance. Hereby, a distinction can be made between strategic, operational and tactical simulation models. Within this research field Veenstra and Lang (2004) describe a conceptual approach and present a framework for analysing the economic performance of a container terminal design, using operational indicators. In both streams, the subject of container dwell times is dealt with only from a capacity restrictive point of view. To our knowledge, no academic publications look at dwell times as an evaluation tool to improve annual turnover rates. In addition to the existing literature, this paper presents the role of dwell times to optimize terminal capacity. 2.1.3. Mathematical framework of how to calculate the storage yard capacity Table 1 gives an overview of how to calculate the storage yard capacity of a container terminal. In this calculation the container pool is split up in four different types (FCL & LCL7, empty, reefer and hazardous containers) which are stacked in designated yards with specific characteristics. In practice, each of these stacking yards is furthermore divided in import, export and transhipment containers. But this extra dimension is not taken into account in the storage yard capacity calculation in Table 1. Adding up the storage capacities of the above-mentioned yards indicates the annual storage yard capacity of the container terminal. Table 1: Mathematical framework to calculate storage yard capacity of a container terminal Storage Yard Capacity Total (TEU) = StoreFull + StoreEmpty + StoreReefer + StoreHazardous

(1)

For each yard (FCL & LCL, empty, reefer and hazardous goods): Storage Capacity (TEU) = Number of ground slots (TGS8) Whereby: Number of ground slots (TGS) = Slot Density (TGS/ha) Resulting in: Storage Capacity (TEU) = Slot Density (TGS/ha)

× Stacking Height (TEU/TGS)

× Yard Area (ha)

7 8

(3)

× Yard Area (ha) × Stacking Height (TEU/TGS*)

Storage Yard Capacity (TEU/pa9) = Storage Capacity (TEU)

×

365days / pa MeanDwellTime( days ) × Peakingfactor

FCL & LCL: Full Container Load and Less than Container Load TGS: Twenty-Foot Ground Slot

6

(2)

(4) (5)

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus Remarks: 1) The storage yard capacity of reefer containers is determined by the number of available connections and less by the available space, whereby the average number of plugs is based on expected traffic flows. Seasonality in reefer traffic is accommodated by diesel driven alternators to generate power supply; 2) All capacities in the proposed mathematical framework are expressed in TEU. When the capacities are indicated in number of containers it is important to adjust these figures with a TEU factor; 3) By including the peaking factor in equation 5 it ensures the terminal operator that there will be sufficient storage capacity available to accommodate peaks in container traffic. This peaking factor resembles a safety factor and incorporates the difference between the MAT and the HEAT. The peaking factor exceeds 1, e.g. a peaking factor of 1.20 represents a safety margin of 20% and seems to be realistic (Chu and Huang, 2005 and Watanabe, 2001); 4) Dally (1983) elaborated Equation 4 with an additional parameter indicating the number of available working slots per yard as a proportion of the total storage capacity; 5) Dharmalingam (1987) on his turn modified Equation 5 and introduced a slot utilization factor. Source: adopted from OneStone Intelligence GmbH, 2003, pp. 90

In order to calculate the storage capacity of each yard a number of additional performance data are required to perform some intermediate calculations. Given the fact that each stacking yard resembles a rectangle, it is possible to calculate approximately the daily storage capacity in TEU by multiplying the number of Twenty-Foot Ground Slots (TGS) with the stacking height (TEU/TGS) (Equation 2). This calculation assumes that all containers are stacked in the same way and have a similar density. Containers can be stacked according to different stacking methods and various slot densities. Consequently, a more fine-tuned method to calculate the number of ground slots in function of a slot density per hectare for each respective yard is required (Equation 3). Thus, the slot density of each yard depends on a number of strategic decisions taken by the terminal operator, such as the type of infrastructure deployed on the container terminal. For example which type of stacking method is applied: rubbertyred gantry cranes (RTGC), rail-mounted gantry cranes (RMGC), straddle carriers (SC) or a combination of the aforementioned stacking methods. Next to stacking method the terminal operator has also to decide on the level of automation of the container terminal. Both decisions have a direct impact on the slot density of each stacking yard. Figure 5 shows that the slot density in total ground slots per hectare (TGS/ha) of a terminal equipped with rubber tyred gantry cranes or rail mounted gantry cranes is generally higher than the density of an all straddle carrier (SC) container terminal. The former stacking method makes it possible to stack containers in blocks, without leaving any space in between the container rows. Nowadays RTGC and RMGC with a width of 9 rows are in operation. When a container terminal is deployed with straddle carriers a wheel space of in between 1.5 and 2.0 meter in width between each row in a certain block has to be provided in the terminal layout. Furthermore, each block should be separated by an access aisle way of about 20 meter. This space allows straddle carriers to manoeuvre at any time to the exact location (UNCTAD, 1985).

9

pa = per annum, on a yearly basis

7

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus Figure 5: Slot density for different types of stacking methods Straddle carrier storage yard

Rubber tired gantry cranes/ Rail mounted gantry cranes

Source: own research

The final storage yard capacity (in number of TEUs per year, TEU/pa) is calculated by multiplying the storage capacity for each yard with the annual turnover rate (Equation 5). The annual turnover rate indicates how many times a twenty-foot ground slot (TGS) – as a unit of storage - has been utilized over a certain period of time. The annual turnover rate is the complement of the mean dwell time (expressed in days) of the specific type of container10. In order to anticipate sufficient terminal capacity a peaking factor has been introduced in Equation 5. This peaking factor ensures the terminal operator that there will be storage capacity available to accommodate peaks and seasonality trends in container traffic. 2.1.4. Impact of mean dwell time on the storage yard capacity According to Vickerman (2000) reducing the mean dwell time by one half doubles the storage yard capacity of a container terminal. As such reducing the mean container dwell time seems to be a cost-effective measure to optimize the potential throughput capacity of the terminal without investing in new capacity. Recalling the assumption that the storage yard forms the bottleneck in increasing the throughput capacity indicates the importance to limit container dwell times. Table 2 shows the effect of varying container dwell times on the storage yard capacity of a dummy container terminal. Hereby, applying Equation 5 of Table 1 for each of the considered container types (FCL & LCL, empty, reefer and containers with hazardous goods) the potential effect of dwell times on throughput capacity has been analysed and acknowledges the assertion of Vickerman (2000) that reducing the dwell times by one half doubles the storage yard capacity of a container terminal.

10

For example, at full capacity utilization when the average dwell time of full TEUs is 5 days the cargo in these slots will on average ‘turnover’ 73 times per year.

8

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus Table 2: Sensitivity analysis of mean dwell times on storage yard capacity of a dummy container terminal Assumptions: FCL & LCL Empty Reefer Hazardous goods

# of ground slots Stacking height (TGS) (TEU/TGS) 10,000 3,000 500 500

Slot density (TGS/ha)

Yard area (ha)

Mean Dwell Time (# of days)

400 600 100 100

25 5 5 5

5 14 3 5

3 6 2 3

Storage capacity (TEU): (Equation 4 & Equation 1 in Table 1)

Corresponding peaking factors:

FCL & LCL Empty Reefer Hazardous goods Total

FCL & LCL Empty Reefer Hazardous goods

30,000 18,000 1,000 1,500 50,500

1.20 1.10 1.00 1.10

Storage yard capacity (TEU/pa): (Equation 5 in Table 1) FCL & LCL Empty Reefer Hazardous goods Total

1,825,000 426,623 121,667 99,545 2,472,835

Sensity analysis of mean dwell times (MDT): MDT*3

MDT*2

Assumed MDT

MDT/2

MDT/3

15 42 9 15

10 28 6 10

5 14 3 5

2.5 7 1.5 2.5

1.67 4.67 1.00 1.67

FCL & LCL Empty Reefer Hazardous goods

Adjusted storage yard capacity (TEU/pa): (Equation 5 in Table 1) FCL & LCL Empty Reefer Hazardous goods Total

MDT*3

MDT*2

Assumed MDT

MDT/2

MDT/3

608,333 142,208 40,556 33,182 824,278

912,500 213,312 60,833 49,773 1,236,418

1,825,000 426,623 121,667 99,545 2,472,835

3,650,000 853,247 243,333 199,091 4,945,671

5,475,000 1,279,870 365,000 298,636 7,418,506

Storage yard capacity (in TEU, * 1,000)

6,000

FCL & LCL

5,000

Empty 4,000

Reefer Hazardous goods

3,000 2,000 1,000 0 MDT*3

MDT*2

Assumed MDT

MDT/2

Source: own research, based on data of anonymous terminal operators

9

MDT/3

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

2.1.5. Data on container dwell times Due to the different characteristics of each container terminal it is rather impossible to present a general fact sheet on container dwell times. The dwell time on container terminals depends on a number of terminal-specific parameters, such as: ‐ in which region the terminal is located (with regard to the availability of land) and which hinterland the terminal is serving; ‐ the frequency of the sailing schedules calling at the terminal; ‐ which mix of cargo flow patterns is handled on the terminal (split of import, export and transhipment containers); ‐ which type of containers form part of the cargo mix (FCL & LCL, empty, reefer and hazardous goods containers); ‐ for empty containers the dwell times are also related to the functional role the terminal fulfils for the shipping companies (classic import-export container terminal, terminal with empty container depot function or mixed container terminal); ‐ the modal split of hinterland connections (in other words by which transport modes the containers are delivered to and retrieved from the terminal); ‐ the openness and management structure of the terminal (dedicated terminal, semi-dedicated terminal or public terminal). Given this highly interactive character data on container dwell times is rather limited. The few sources indicating some facts on this issue are consultants’ reports - e.g. Drewry, OSC, ISL, Onestone Intelligence, Transystems, etc. - although this data is only partially available. The data gathered in this section is based on contacts with various terminal operators and shipping companies in the Hamburg-Le Havre range (see Table 3). Due to the confidential aspect of this data the sources relied on will be kept anonymous. Table 3: Average container dwell times (in number of days) for different container types on terminals in the Hamburg-Le Havre range Cargo flow pattern Container type FCL & LCL Empties, dwell time depends on type of container terminal: - Import-export container terminal - Terminal with depot function - Mixed container terminal Reefer Hazardous goods

Import

Export

Transhipment

6,5

5,5

3

10 14-20 10-14 4-6 3

10 14-20 10-14 3-5 2

n/a n/a n/a n/a n/a

Source: own research, based on data of anonymous terminal operators

Table 3 shows the dwell times of different types of container (FCL & LCL, empty, reefer or hazardous goods) on terminals in the Hamburg-Le Havre range taking into account their cargo flow pattern. The cargo flow pattern indicates whether the container is in import, export or transhipment on the container terminal.

10

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

Analysing the obtained information on average container dwell times for the different container types, the empty containers have the highest dwell times (both for import and export containers). Given the fact that hazardous goods and reefer containers have to be treated specifically both by the terminal operator as well as the shipper can explain the lower dwell times for these types of containers. The dwell times of FCL and LCL situate in between the earlier mentioned container types. In general the import container dwell times exceed the export container dwell times. Because of the above-mentioned terminal specific parameters generalizing the data of Table 3 for all container terminals in the world is impossible. During the author’s field research it has become obvious that container dwell times are also determined by which transport mode the containers are delivered to or retrieved from the terminal. Generally, containers which are shipped by road generate the shortest dwell times. However, container terminals which are connected by rail or barge services often faster distribute seaborne containers to and from the network of interconnected inland terminals. To some extent the evolution of container dwell times also depends on the availability of transportation means. Apparently, situations occur that containers cannot be picked up or delivered to the container terminal because there are no trailers and/or slots on a block or shuttle train available. In such conditions the container dwell times are influenced by external factors on which the terminal operator has no influence. The slow landside removal or early delivery of containers is contradictory to the faster cycle times which are eyed by the terminal operators in order to increase the terminal capacity. Current practice whereby container terminals are used as cheap (mostly free), temporarily overflow nodes in the supply chain seems to be embedded in port logistics. Because of the boom in container transportation and the consequent lack of storage capacity terminal operators are looking at container dwell time charges to optimise their throughput capacity.

3. IMPACT OF DWELL TIME CHARGES ON CONTAINER TERMINAL CAPACITY According to Table 2 reducing the container dwell times, thus improving the annual turnover rate increases the storage yard capacity and vice versa. Given the fact that the throughput capacity depends on capacity constraints in different segments of the container terminal pipeline, an unremitting pressure to reduce dwell times will result in capacity problems in other segments of the container terminal system (see Figure 2). In this section we present a theoretical framework to optimize container dwell times resulting in an optimal container terminal capacity. This theoretical framework is a supply driven approach whereby the optimization process is looked at from a terminal operator’s point of view. Hereby, we described some pricing policies to achieve the optimal dwell time and thus increase the potential storage yard capacity. Furthermore, we will focus on the future role of terminals as buffers in logistics chains. 3.1. Theoretical framework to optimize container dwell times The proposed theoretical framework is a simplification of current practices in container terminal management and is based on the following assumptions:

11

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

‐ the container dwell time is the trigger in the optimization process of the storage yard capacity; ‐ in the analysis two capacity constraints determine the optimal dwell time: namely the quay capacity and the gate capacity (reflected in function of the level of gate utilization), whereby the quay capacity determines the gate capacity; ‐ the waterfront of the terminal has no capacity constraints, meaning that all vessels do arrive well distributed over time and sufficient berths are available; ‐ the terminal operator has no financial constraints to invest in quay capacity (e.g. gantry cranes), transfer-cycle capacity or horizontal transportation means (e.g. straddle carriers, forklifts, reach stackers, etc.) and gate capacity to meet any increase in storage yard capacity. Figure 6 shows the optimal container dwell time (d) given a certain level of quay capacity (qc) whereby the throughput capacity of a terminal is optimized. Any decrease of the dwell time results in a capacity level which cannot be attained by the available quay capacity (shaded area). An increase of the dwell time on the other hand will result in an underutilization of the available quay capacity. Based on the results in Table 2 the yard capacity (yc) is represented as a linear decreasing function of the dwell time. From this starting point we will elaborate the theoretical framework, for the considered cargo flow patterns: namely import (foreland-terminal-hinterland), export terminal traffic (hinterland-terminal-foreland) and transhipment. A decrease of container dwell times (from d to d’) would imply a quay capacity bottleneck. As such the eyed storage yard capacity cannot be attained without any additional investments in quay capacity. In order to accommodate a decrease of dwell times (d’) – and consequently to reach a higher level of storage yard capacity – additional investments should be made to increase the quay capacity from qc to qc’. Figure 6: Optimal dwell time given a constraint in quay capacity Capacity

Capacity

yc

yc

Yard Capacity

Yard Capacity qc’

Quay Capacity

qc

d

Quay Capacity

qc

Dwell time

Source: own research

12

d’

d

Dwell time

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

In Figure 6 we did not consider the effect of any quay capacity improvement on the gate utilization. Logically, we can assume that with a decreasing storage yard capacity the gate utilization level will also decrease (and vice versa). Supposing the quay capacity will be expanded from qc till qc’ this means that the gates will be over occupied, resulting in gate congestion. As such it would be sensible from the terminal operator’s point of view to aim for a dwell time of d’’ instead of d’ (whereby d’’>d’) (see Figure 7). Figure 7: Optimal dwell time given an additional constraint in gate capacity Capacity Utilization

Capacity Utilization yc

yc

Yard Capacity

gu

Yard Capacity

Gate Utilization Quay Capacity

qc

d

qc’ gu

Gate Utilization Quay Capacity

qc

Dwell time

d’ d’’d

Dwell time

Source: own research

Combining the proposed theoretical framework represented in Figure 6 and Figure 7, we can theoretically define a terminal equilibrium whereby the container dwell time is optimized based on a given quay capacity and gate capacity. 3.2. Terminal equilibrium: in search of the optimal dwell time The optimal dwell time (d) on a container terminal is the intersection of the constraining parameters – in the proposed model the storage yard capacity, the quay capacity and gate capacity (reflected in function of the level of gate utilization). When the terminal operator intends to decrease container dwell times, capacity improvements both on the ship-toshore segment (quay capacity) and delivery-receipt area (gate capacity) are required. Given the quay capacity increase from qc to qc’ and the anticipated gate capacity increase from gc to gc’, the container dwell time of d’ remains optimal (see Figure 8). As such for the terminal operator it is important to approach the terminal equilibrium as close as possible, because at this point the throughput capacity is optimized. In order to achieve this objective terminal operators are looking at different mechanisms to approach the optimal dwell time.

13

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus Figure 8: Terminal equilibrium given a capacity increase in quay and gate capacity Capacity Utilization

Capacity Utilization yc

yc

Yard Capacity

Yard Capacity gu’ qc’

gu qc

Quay Capacity

gu qc

Quay Capacity

Gate Utilization

d

Gate Utilization

Dwell time

d’

d

Dwell time

Source: own research

In the case of a changing cargo flow pattern on the container terminal will also affect the optimal dwell time. For example whenever a substantial amount of containers is no longer handled as import or export cargo (e.g. a shift towards transhipment containers) this will have an effect on the gate utilization. In our example the gate capacity would become underutilized because a significant share of the containers will be handled at the waterfront. As such the gate capacity can be decreased from gc to gc’ while providing the same service level (see Figure 9). Together with the reduced gate capacity the optimal dwell time increased from d to d’. In this situation containers can remain stacked for a longer period on the storage yard without creating a shortage on yard capacity. Figure 9: Terminal equilibrium given a capacity decrease in quay and gate capacity Capacity Utilization yc

yc

Yard Capacity

Yard Capacity

gu qc

Quay Capacity

gu qc

Quay Capacity

Gate Utilization

Gate Utilization gu’ qc’

d

Dwell time

Source: own research

14

d

d’

Dwell time

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

In the next section we will highlight the introduction of different pricing mechanisms to reduce dwell times on container terminals. Furthermore, we will also refer to the existing literature on port pricing and present some existing charging systems. Secondly, we point out the potential role of inland terminals to reduce container dwell times on seaport terminals. 3.3. Mechanisms to achieve optimal container dwell time As mentioned above the terminal operator has some possibilities at his disposal to approach the optimal dwell times. Hereby, we primarily focus on the effect of dwell times charges. By introducing dwell time charges the terminal operator intends to realize an impact on the container dwell times. The eventual impact of this measure will largely depend on the height of the dwell time scheme, but also on some related aspects such as the type of terminal on which the charge has been applied, the type of customers serviced at this terminal, the value of the goods confronted with the dwell time charge, etc.. The calculation of the price elasticity of dwell times is an important element is this respect, but has not been included in the scope of this paper. This research question will be dealt with by the author in future research on this topic. Next to the dwell time charges imposed by terminal operators we will also highlight the potential role of inland terminals to reduce container dwell times at seaport terminals. The idea of satellite (inland) terminals as a local solution to hub congestion has been suggested by Slack (1999) and this idea is applied to the issue of container dwell times. 3.3.1. Schemes of dwell time charges on containers Before zooming in on the different dwell time charging schemes on container terminals a relevant element in this respect are pricing theories and policies available to terminal operators. Wiegmans (2003) analysed the selling power of ‘public’ terminal operators and concluded that their negotiating power vis-à-vis the carriers is limited. Given the introduction of dedicated terminals their selling power is further curtailed. He concludes that the prices terminal operators negotiate with the carriers are based on: firstly the willingness-to-pay for these services and secondly, prices comparable to those of the competitors. Thus, the buying power of the big shipping companies is the main driver in contract negotiations with the terminal operators. In this setting terminal operators grant discounts on handling prices based on the expected cargo volume of the customers. The summarized pricing policies also reflect the usage of dwell time charging schemes by terminal operators. Generally, a distinction can be made between two dwell time charging schemes on containers: namely a flat charge (without any relation to the terminal costs) and a variable dwell time charging scheme which approaches the real costs of occupying a container slot. For the latter category a subdivision can be made on the type of container. Moreover, the benefits of reduced dwell times are primarily reaped by third parties (e.g. the terminal operator himself because of the additional created storage yard capacity, the port authority which witnesses an increase of the ports’ container capacity without having to invest in any infrastructure and any future shipping customer benefiting from the capacity made available) and not necessarily by those who are charged. This aspect also

15

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

makes it difficult for terminal operators to unilaterally oppose dwell time charging schemes. 3.3.1.1. Flat dwell time charging schemes In case the terminal operator is not contractually bounded to the shipper, it is rather difficult to enforce a penalty for containers staying on quay too long. In this respect the shipping company is the only party they have a direct contractual relation with. As such, when the terminal operator intends to introduce a dwell time charge this scheme is often based on a fixed amount, mostly irrationally diversified over time. In practice this type of dwell time charges are not linked to the actual terminal costs of a container occupying the terminal slot for a certain period of time. Moreover, because the dwell time charges form part of the contract negotiations with the shipping companies the height of this amount varies depending on the commercial interests. The more traffic a certain shipping company/shipping line represents the more flexible the terminal operator takes position on this issue in contract negations. Consequently, the height of such fixed dwell time charges is often marginal and hardly covers the real costs of occupying a container slot for a certain period of time. Table 4: Flat dwell time charging scheme at MSC’s Home Terminal11 (Antwerp, Belgium)

Period of occupation (in days) 0-7 8-15 16-30 > 30

Rate per day per container or part thereof Up to 20’ Above 20’ Free Free €5 € 10 € 10 € 20 € 15 € 30

Remarks: 1) The above-mentioned figures indicate which rental prices are charged to the shippers by MSC 2) This charging scheme is only applicable on import containers (import reefer containers and transhipment containers are excluded) Source: Van den Bossche, B., 15 April 2004

Shipping companies on their part often include container demurrages in their rates to shippers. When a shipping company is confronted with a dwell time charging scheme imposed by the terminal operator, this cost element can be set to recover the duty. Maersk Sealand for example recently announced that “as of May 1, the demurrage charges for dry import containers at most US port, rail terminals and inland depots increased to USD 225 a day, and to USD 400 per day for reefers;, after the expiration of the free time.” (Leach, 2005) This increase in demurrage charge is combined with a reduction of free time “at most port terminals and inland deports to four days for dry containers and two days for reefers.” (Leach, 2005) In the case of Maersk Sealand the higher charge has been communicated to the shippers as a pass-through of the increased charges imposed by (intermodal) terminal operators.

11

Joint-venture of PSA/HNN and MSC

16

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

However, some shipping companies include container demurrages in their tariffs even when they are not charged for this cost or oppose container demurrages which are higher than what they are charged by the terminal operator. 3.3.1.2. Variable dwell time charging schemes When terminal operators have more direct relations to shippers dwell time charges can be – given their selling power and few substitutes available – more easily imposed. In this case shippers also have a clear view on the opportunity cost directly linked to the use of a container terminal as overflow node in their supply chain. As such the height of the variable dwell time charging schemes approximates the actual terminal costs of a container occupying a slot for a certain period of time. Shippers confronted with direct collection for stacking their containers on the container yard will be urged to reconsider their supply chains to overcome the extra taxation. Moreover they will use the imposed dwell time charge as a shadow price in negations with other parties involved in their supply chain. 3.3.1.3. Dwell time charging schemes to optimize storage yard capacity Before turning to the pricing structures in practice Figure 10 represents the different parameters determining the financial viability of a container terminal operator. In order to calculate the dwell time charge to approach the dwell time which optimizes the storage yard capacity, we start from a basic model of terminal supply based on Strandenes (2004). Figure 10: Flows of revenues and costs on a container terminal Shippers/ Receivers

Container lines

Sub-lessees CFS/ others

REVENUE BASED ON TARIFFS Concessionnaire Terminal Operator OPERATING COSTS

Labour and Staff Suppliers

CAPITAL COSTS

CAPITAL RECOVERY Contractors Equipment manufacturers

LEASE RENT

FINANCIAL COSTS Banks Other finance providers

TAX ROYALTY ON CHARGE REVENUE

Government/ Port Authority

Government

NET REVENUE

Concessionnaire T.O.

Source: De Monie, 2005

A company running a container terminal should cover his variable costs to operate the terminal at optimum capacity. In terminal circles the net revenue per year is based on negotiated tariff for various terminal operations with different customers, less the specific 17

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

terminal costs: such as operating costs capital costs, royalty charges, taxes on revenue (see Figure 10). The net revenue is the objective value in this maximization problem. As argued by Strandenes (2004) traditional infrastructure pricing and cost-based pricing of terminal operations generally do not induce terminal efficiency. Referring to the literature on port pricing she describes a number of pricing structures which may optimize terminal utilization levels: namely congestion pricing, priority pricing and prices set by auction procedures. Given the ongoing research on this topic, the usage of the above-mentioned pricing structures on the container terminal management will be subject of a forthcoming paper. In this paper an in-depth analysis of the different pricing mechanisms available to the terminal operator to optimize the container dwell times will be dealt with. The second paper on this issue will also be part of the author’s Ph.D. research track. As mentioned above the shipper will look for alternatives to reshuffle the overflow nodes in his supply chain. In addition some terminal operators are anticipating this general trend. Some terminal operators are evolving towards freight integrators, offering related logistics services to their customers. The potential role of inland terminals to reduce container dwell times is assessed in the next section. 3.3.2. Potential role of inland terminals to reduce container dwell times at seaport terminals Given the recent investments of terminal operators in inland barge terminals (e.g. stakes of ECT in TCT, Willebroek – Belgium and DeCeTe, Duisburg – Germany, stake of P&O Ports in DIT, Duisburg – Germany, etc.), these inland terminals can be incorporated in their strategies to reduce container dwell times on seaport terminals. Next to the investments made by terminal operators and the consequent expansion of the network of inland terminals the recent success of inland container barging in the ports of Antwerp and Rotterdam offers possibilities for dedicated shipments to and from their hinterland hubs. Notteboom and Konings (2004) presented this evolution in a spatial development model for a hypothetical port-linked container barge network. As such terminal operators have to make the strategic decision ‘whether their core business is to store containers or to load, unload and forward containers fast and reliable’ (Ilmer, 2004:12). As such the inland container terminals act as a bridgehead in order to reduce container dwell times at seaport terminals. Within this seminar paper on container dwell times the economic viability of the strategic option to include inland terminals in the portfolio of terminal operators in order to reduce container dwell times at seaport terminals is not worked out in detail yet and will form part of future research. The following issues will be addressed in this respect: who will pay for the transport by barge, how will the extra handling costs (two extra moves) be recovered, which strategic decisions have to be taken by the terminal operator to succeed, is all information available to the terminal operator, how much containers etc.?

18

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

4. FUTURE RESEARCH ON THE ISSUE OF CONTAINER DWELL TIME CHARGES The objective of this seminar paper is to indicate the importance of dwell times on the throughput capacity of a container terminal. Given the limited attention which has been given to this subject in the economic evaluation of container terminal management, we believe that future research in this field would contribute to the existing literature on container terminal management. In order to get more acquainted with container dwell times and to gain more insights in the issue of container dwell time charges interviews were performed with leading terminal operators. In a second phase we foresee to perform an in-depth analysis of data sets on container dwell times. Negotiations with leading terminal operators to secure this data are ongoing. Apart from the in-depth analysis of container dwell times, the elaboration of the concept of dwell time elasticity is another subject. Future research on the concept of dwell time elasticity is in the pipeline and will be performed from a logistics – shippers - point of view. This research will be conducted within the framework of the author’s Ph.D. research track.

5. CONCLUSION This seminar paper dealt with the impact of dwell times on container terminal capacity and provides a theoretical framework of which constraints a terminal operator has to take into account in order to optimize the container terminal capacity by altering container dwell times. As such the paper described the different dwell time charging schemes on containers and summarized a number of pricing mechanisms available to terminal operators to optimize the terminal capacity. In conclusion the general guideline is to implement a terminal charge which affects the dwell time so that the available quay and gate capacities are optimized. An in-depth analysis of the pricing structures to optimize terminal utilization levels (including the price elasticity of dwell times and willingness-topay of terminal customers) is being researched and will be subject of a forthcoming paper in the author’s research track. Next to the issue of dwell time charges to reduce the dwell times on seaport container terminal the potential role of inland terminals has been included.

ACKNOWLEDGEMENTS The author would like to thank all members of his Ph.D. Commission (Prof. Dr. Willy Winkelmans, Dr. Theo Notteboom and Dr. Wout Dullaert) and Mr. Bert Vernimmen for their comments and contributing remarks on this paper. Furthermore, we would like to thank a number of unspecified leading terminal operators and contact persons for supplying data and feedback on different economic aspects of container terminal management.

19

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

REFERENCES Chu, C.-Y., Huang W.-C., 2005, “Determining Container Terminal Capacity on the Basis of an Adopted Yard Handling System”, Transport Reviews, Volume 25, Number 2, Taylor & Francis Ltd., March 2005, 181-199. Dally, H. K., 1983, Container Handling and Transport — A Manual of Current Practice, London, Cargo Systems IIR Publications Ltd. De Monie, G., 1981, “The determination of port capacity”, Proceedings of Port Management Training Course (17 November – 12 December 1980), UNCTAD/Nigerian Ports Authority, Lagos (Nigeria). De Monie, G., 1985, “Container Terminal Pricing”, Proceedings of the Seminar on Container terminal capacity (19 September - 7 October 1983), UNCTAD/APEC, Antwerp (Belgium), August 1985, 573-638. Dharmalingam, K., 1987, “Design of storage facilities for containers — a case study of Port Louis Harbour, Mauritius”, Ports and Harbors, September, 27–31. Drewry Shipping Consultants Ltd, 2002, Global Container Terminals - Profit, Performance and Profitability, October 2002, 35-37. Drewry Shipping Consultants Ltd, 2004, Annual Review of Global Container Terminal Operators - 2004, July 2002. Henesey, L.E., 2004, Enhancing Container Terminal Performance: A Multi Agent Systems Approach, Licentiate Series No 2004:06, Blekinge Institute of Technology, Department of Systems and Software Engineering School of Engineering, Karlshamn, Sweden. Ilmer, M., 2004, “Change of paradigm in container transportation – is Duisport up to the challenge?”, 2003 Annual Report of the duisport Group, 12-13. Leach, P., 2005, “Maersk Sealand to pass on demurrage and detention fees”, Journal of Commerce online, 8 April 2005. Lemper, B., 1996, Die Funktionsfähigkeit des Marktes für Seehafencontainerumschlag in der Nordrange, Diss., Institut für Seeverkehrswirtschaft und Logistik (ISL), Bremen. Manalytics, Inc., 1976, Methodology for estimating capacity of Marine Terminals, Vomule I: Standardized Methodology, February 1976. Lester, A., Hockney, P.E., Lawrence, L., Whiteneck, P.E., 1986, Port Handbook for Estimating Marine Terminal Cargo Handling Capacity, November 1986. Notteboom, T., Konings, R., 2004, “Network dynamics in container transport”, Belgian journal of geography - BELGEO, Volume 5, Number 4, 461-478.

20

IAME 2005 Annual Conference 23-25 June 2005, Limassol, Cyprus

NPC Bulletin, 1980, Annual throughput capacity of berth and its relationship to available facilities, UK National Ports Council, July 1980. OneStone Intelligence GmbH, 2003, “Part 3: Container Terminal Benchmark”, Container Terminal Focus 2007 (Market Report), OnestoneReports. Promotie Binnenvaart Vlaanderen, 2003, Map of inland container terminals. Sgouridis, S.P., Angelides, D.C., 2002, “Simulation-based analysis of handling inbound containers in a terminal”, Proceedings of the 2002 Winter Simulation Conference. Slack, B., 1999, “Satellite terminals: a local solution to hub congestion?”, Journal of Transport Geography, Elsevier Science, Volume 7, Issue 47, December 1999, 241-246. Steenken, D., Voß, S., Stahlbock, R., 2004, “Container terminal operation and operations research – a classification and literature review”, OR Spectrum, Springer-Verlag GmbH, Volume 26, Number 1, January 2004, 3-49. Stenvert, R., Penfold, A., 2004, Marketing of container terminals, Ocean Shipping Consultants. Strandenes, S.P., 2004, “Port Pricing Structures and Ship Efficiency”, Review of Network Economics, Volume 3, Issue 2, June 2004, 135-144. United Nations Conference on Trade and Development (UNCTAD), 1985, Port Development — A Handbook for Planners in Developing Countries, TD/B/C.4/175/rev. 1, New York, New York, United Nations. Van den Bossche, B., 2004, “MSC recent na zeven dagen kaaiverblijfkosten aan in Antwerpen”, De Lloyd-Le Lloyd, 15 April 2004. Veenstra, A., Lang, N., 2004, “Economic analysis of a container terminal simulation”, International Journal of Logistics, Carfax Publishing, September 2004, Volume 7, Number 3, 263-279 (17). Vickerman, J., 2000, Panel of Transcomp 2000 seminar, National Industrial Transportation League - Transcomp 2000 seminar, 11-12 November 2000. Watanabe, I., 2001, Container Terminal Planning - A Theoretical Approach, World Cargo News Publishing, Leatherhead, UK. Wiegmans, B., 2003, Performance conditions for container terminals, Ph.D. thesis, Vrije Universiteit Amsterdam, Nijkamp, P., Rietveld, P. (Promoters), Amsterdam, 7 April 2003. Winkelmans, W., 2004, Port Capacity: a theoretical and practical approach, Advanced Port Economics, ITMMA-University of Antwerp, Academic year 2003-2004.

21