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Original Article

Port evolution and performance in changing

logistics environments

S u - H a n Wo o , S t e p h e n Pe t t i t a n d A n t h o n y K . C . B e r e s f o r d

Transport and Shipping Research Group, Logist ics and OperationsManagement Section, Cardiff Business School, Cardiff University,Aberconway Building, Colum Road, Cardiff CF10 3EU, UK.E-mail: jazzlike@hanmail.net

Abst ract In recent years there have been significant changes to the logistics

environment in which ports operate, which is now focused on supply chain management,

global networking and customer orientation practices. Furthermore, ports have adopted

different strategies concerning their level and form of integration into supply chains, service

quality and provision of value-added activities. Traditional port performance indicators focus

on specific ‘efficiency’ measures, whereas contemporary indicators are expected to be in-

clusive of all aspects of operations and to be consistent with the strategies of the organisation.

In this regard, this article analyses the changes currently taking place in the port industry and

develops a port performance framework that reflects these changes. The framework was

designed based on exploratory study, and the validity and reliability of the framework were

confirmed using Confirmatory Factor Analysis. It is concluded that port performance is

multifaceted, not limited to internal processes and also related to external service aspects

such as service quality and logistical elements such as value-added services. In addition, it is

shown that port operating companies and port authorities should strive to maintain a

balanced focus on both effectiveness and efficiency aspects of performance management and

improvement, aiming to meet the requirements of customers and other supply chain actors.

Maritime Economics & Logistics (2011) 13, 250–277. doi:10.1057/mel.2011.12

Keywords: port evolution; port performance; performance measurement;

Confirmatory Factor Analysis; effectiveness; efficiency

Int roduct ion

Performance measurement plays an important role in all areas of business

management in both the private and public sectors because it explains the

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extent to which companies and organisations have achieved their goals and

objectives, and gives guidance on how they can make improvements. Therefore,

companies and organisations are making an effort to measure their perfor-

mance in a proper way and researchers have been endeavoring to develop

performance measurement frameworks, or metrics, which are appropriate

for individual industries. In the port operations and management research

field, performance measurement has been one of the main issues. Most cases

compare performance or efficiency of international container ports (for

example, Tongzon and Ganesalingam, 1994; Tongzon, 2001; Cullinane et al,

2004). Some researchers have evaluated ports in a particular country (for

example, Sachish, 1996). Attempts to identify indicators (for example, Tongzon,

1995) or methods (for example, Talley, 1988, 1994) that are appropriate for port

performance evaluation have also been made.

However, it has been argued recently that most studies on port performance

measurement are biased and out of date (Marlow and Paixao-Casaca, 2003;

Bichou, 2004; Brooks, 2007). This argument is closely related to parallel views

on the rapidly changing logistics environment and the evolution of ports. Owing

to the trend towards globalising operations and management, the logistics

industry has not only become more competitive, but now also has to meet the

more complicated and diverse demands of customers. In response to this

challenge, port operators and port authorities are adopting new strategies for

improving service quality. As well as improving efficiency, approaches include

developing strategic integration along the supply chain and adopting customer-

oriented practices and value-added activities. However, despite the evolution

of ports, port performance measurement studies still focus on traditional

efficiency metrics while the new strategies that ports are adopting are associated

with effectiveness rather than efficiency.

The arguments for extending port performance beyond those considered in

traditional studies of port performance measurement can be represented as fol-

lows. First, traditional measures cover the efficiency of internal operations rather

than the effectiveness of ports or terminals in delivering what customers want.

Brooks (2007) argues that port literature has focused more narrowly on mea-

suring efficiency whereas other transport modes such as air, road and rail put

a greater emphasis on external perspectives such as customer orientation, relia-

bility and service. Bichou (2007) demonstrates that port performance measure-

ment systems are hardly ever used to capture both efficiency and external

effectiveness, and a single focus on either efficiency or effectiveness does not

seem to be the only way to increase performance. Panayides (2006) also suggests

that ports in the supply chain era, apart from cargo throughput, may have other

valid and useful measures of performance, such as leanness, agility and time

compression as well as the performance of other parties in the supply chains.

Port evolution and performance in changing logistics environments

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Second, traditional measures are fragmented and biased towards measures

related to throughput derived from sea transport, for example ship turnaround

time. For example, Bichou (2007) indicates that most port performance litera-

ture focuses solely on this type of measure, overlooks other port operating

system processes and ignores the interests of other members of the port’s

supply chain network. Third, efficiency studies using Data Envelopment

Analysis (DEA) generally evaluate or compare port performance by focusing on

the operational efficiency of container terminals (Bichou, 2007; Cochrane, 2007).

As DEA results are sensitive to the choice of, and weights attributed to, input-

output variables (Cullinane et al, 2004) it is important that the variables used are

not selected subjectively or arbitrarily and without thorough empirical analysis.

A number of studies suggest that performance evaluation systems should

be inclusive of all aspects of operations, and should also be consistent with

organisational goals (see, for example, Talley, 1994; Beamon, 1999). Otherwise,

performance evaluation is not able to provide policy makers, port authorities

and port operating companies with valid information, and could mislead them

into making wrong decisions. The primary objective of this article is to develop a

port performance measurement framework and instruments for the changing

logistics environment using Confirmatory Factor Analysis (CFA). In this study,

port performance measurement is assumed to be multifaceted and multi-

dimensional so that it can reflect all the significant factors affecting port evo-

lution. Measurement instruments, or scales, are developed when phenomena

that are believed to exist because of our theoretical understanding of the world,

but which cannot be assessed directly, need to be measured (DeVellis, 1991).

This study develops measurement instruments for port performance that cover

significant port evolution aspects and that need to be included in port perfor-

mance metrics. It also examines the validity and reliability of the instruments

with CFA. The following section identifies the key port evolution aspects from

the relevant literature and proposes a new port performance measurement

model. Subsequently, the research process and methodology that is applied in

this study is discussed. The results of an exploratory study and the adjusted

measurement model based on the results of the exploratory study are then

presented, followed by validation of the adjusted model through an empirical

study. The final section presents the research findings and the implications of the

research, discusses its limitations and suggests further possible research to build

on this study.

Port Evo lut ion and Performance Measurement Framework

Port management and strategies are both directly and indirectly influenced by

prevailing logistics trends, as the demand for port services is a double-derived

Woo et al

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demand (Marlow and Paixao-Casaca, 2003). Changing logistics strategies and

the demand patterns of manufacturing companies create many challenges to

which the logistics and transport industries have to respond. From the port

industry’s point of view the shipping industry’s response to change creates

major challenges and it is this industry that has the most direct impact upon it.

Specifically, this means that port operators and port authorities have to carefully

consider their reaction to change and act appropriately.

This article approaches port evolution from the perspective of the dynamics

among consumers and providers of logistics services. The evolutionary aspects

of port development have been identified from both existing literature and

previous research (Beresford et al, 2004; Woo et al, 2008) as shown in Figure 1.

Several researchers have demonstrated that manufacturing companies

realise the necessity of managing supply chains more effectively. In response to

globalisation of the economy and intensifying competition, they have adopted

new strategies such as Supply Chain Management, global sourcing and the

outsourcing of certain functions, for example logistics (Rabinovich et al, 1999;

Lambert and Cooper, 2000; Cho and Kang, 2001). These new strategies mean

that transportation companies are required to cover wider geographical spans,

and to provide a wider range of services to meet increasingly diversified de-

mand patterns with a lower price and higher quality than before (Slack et al,

1996; Heaver, 2001). To accommodate these changes, shipping companies

have integrated both horizontally (through mergers, acquisitions and strategic

alliances) and vertically (through the operation of dedicated terminals and

the provision of integrated logistics and intermodal services) (Notteboom,

2004). Further, shipping companies have rearranged service networks with

the dual aim of global coverage and diversification. The changes that shipping

companies have made have ultimately affected every facet of the maritime

industry, especially concerning port operations (Slack et al, 2001).

In order to measure these changes, the approach taken was to use CFA.

Structural Equation Modelling (SEM) is a powerful statistical technique that

combines a measurement model (CFA) and a structural model (regression

or path analysis) into a simultaneous statistical test (Garver and Mentzer, 1999).

Horizontal integration

Vertical integration

Network redesign

Efficient operationPrice competitionService quality improvementCustomer oriented practicesConnectivity to other transport modes

Value-added servicesPort cooperation and networking

Security and safety

Powerful clients

Intensifiedcompetition

Wider geographicalspan

Wider range of service

Cost and service

Shipping industryShipping industryLogistics chainsLogistics chains Intermediate impactIntermediate impact Intermediate impactIntermediate impact Port IndustryPort Industry

Supply chain m’ngt

Global sourcing

Logistics outsourcing

Figure 1: Port evolution in changing logistics environments.

Port evolution and performance in changing logistics environments

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The measurement model specifies the relationships between the observed and

the unobserved variables. Latent variables represent theoretical constructs that

cannot be observed directly and observed variables represent the scores from

the measurement instruments. The structural model specifies the hypothesised

causal relationships among the latent variables.

Many studies suggest that ports have had to evolve across the range of their

activities to cope with these new challenges (Notteboom and Winkelmans,

2001; Robinson, 2002; Carbone and De Martino, 2003). Eight aspects of port

evolutionary change were derived from the literature and previous research

(Beresford et al, 2004; Woo et al, 2008). These aspects were then aggregated

into three groups in terms of external perspectives, internal operational

perspectives and logistical perspectives (see Figure 2).

PortPerformance

Service(External)

Operation(Internal)

Logistics

Service quality

Customerorientation

Service price

TimelinessReliabilityLead timeCargo damagesAccuracy of information

ResponsivenessFlexibilityAnnual number of claims

Total port chargeCargo handling chargePort related service chargePort facility usage charge

Efficientoperation

ThroughputThroughput per hectareThroughput per workerThroughput per craneShip waiting timeShip working timePort related service TimeCargo time

Safety andsecurity

Compliance with regulationNumber of accidentNumber of accident prevented

Connectivity

Value-addedservice (VAS)

Cargo waiting time betweenmodesCargo working time betweenmodes

Cargo accruing from VAS

Value-added from VAS

Port cooperationand networking

Figure 2: Port performance measurement framework.Source: Authors

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The majority of indicators were derived from existing port performance

literature. However, some aspects such as Service Quality and Customer

Orientation were derived from supply chain performance literature and other

transport mode performance literature. In addition, indicators for ‘Port

Cooperation’ were not identified from the literature, and therefore are not

specified in Figure 2. When it comes to empirical analysis using CFA,

port evolution aspects are the constructs (the latent variables) and the

indicators are measures or scales (the observed variables). Thus ‘Service’,

‘Operation’ and ‘Logistics’ in Figure 2 are the second-order factors that com-

prise two or three sub-dimensions, respectively, and Port Performance is the

third-order factor comprising three second-order factors.

Research Process and Methodology

This study employed a three-stage process and two waves of questionnaire

survey, as shown in Figure 3, were conducted.

The first stage proposes a port performance measurement model using the

port evolution aspects derived from the literature described in the previous

section. The second stage, using the first questionnaire survey, explored how

significantly these aspects of port evolution are being considered within the

port industry. The survey asked questions about the aspects, and required

respondents to evaluate how significant these aspects are; how closely they

should be reflected in port performance; and how appropriate the given

indicators are for measuring the aspects. The survey was conducted over a

period of 2 months from March to April 2008. The questionnaires were sent to

100 potential respondents via email. Korean Port Operating Companies (POC),

Shipping Companies (SC), Public Sector Departments (PS) and Academic

Institutions (AC) were invited to participate in the first exploratory survey in

line with the principle that a comprehensive performance measurement system

should involve the interests of all relevant members and stakeholders. Of the

Step 1: Model Development

Step 2: Exploratory studyQuestionnaire Survey (First)Descriptive Analysis (Frequency, Mean, St. Deviation)

Questionnaire Survey (Second)

Empirical Analysis (Confirmatory Factor Analysis)

Literature ReviewIdentification of port evolution aspects

Step 3: Confirmatory study

••

••

•

•

Figure 3: Research process.

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100 questionnaires sent out, 72 questionnaires were returned as shown in

Table 1. The survey results were initially analysed using descriptive statistics,

that is percentage frequency, mean value and standard deviation.

The third stage validated the proposed measurement indicators using

CFA. The second questionnaire survey was designed to ask respondents to

evaluate the perceived performance of their ports or terminals. The survey

was conducted over 1 week during August 2008. Of the 100 questionnaires

sent via email 61 were returned. To analyse the data collected from the

second survey, CFA was applied to assess the validity and reliability of the

proposed measurements in the second questionnaire. CFA is concerned with

the extent to which the observed variables are confirmed by the underlying

latent constructs. With port evolution aspects being treated as latent variables

and the indicators as observed variables, the strength of the respective regres-

sion paths from the latent variables to the observed variables is of primary

interest.

Exploratory Study

The first questionnaire was primarily designed to explore how respondents

perceive the challenges the port industry faces and to identify the key aspects of

port evolution. Respondents were first asked to indicate the degree of agreement

about particular phrases and to evaluate the significance or importance of

particular indicators, and subsequently to assess how significant the port

evolution aspects are and the extent to which they should be reflected in port

performance measurement. Answers were scored on a Likert scale, from

Strongly Disagree (1) to Strongly Agree (5).

Table 1: Questionnaire responses in the first and second surveys

Survey Group Sent Notopened

Opened butnot responded

Responded Responserate (%)

First POC 30 3 7 20 67SC 20 4 3 13 65PS 30 3 1 26 87AC 20 6 1 13 65Total 100 16 12 72 72

Second POC 80 12 13 55 70PS 20 12 2 6 30Total 100 24 15 61 61

Abbreviation: POC stands for Port Operating Company.

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Challenges faced by the port industry

The main challenge ports face from the structural change in logistics chains is

that their main customers, the shipping lines, are becoming more powerful

with stronger bargaining power, and competition between ports is getting more

intense both at inter-port and intra-port levels.

The emergence of powerful clients

The simultaneous vertical and horizontal integration that has taken place

within the shipping industry has led to the well-documented emergence of

bigger shipping lines and a small number of global mega carriers. These in

turn have greater bargaining power in their negotiations with port operating

companies and port authorities (Heaver, 2001). Of all respondents 86 per cent

agreed (29.2 per cent) or strongly agreed (56.9 per cent) to the phrase ‘the

bargaining power of customers is getting stronger’. The aggregate average score

of 4.33 shows that the respondents generally view clients to be powerful.

In respect of the main clients of ports, shipping companies and shippers are

considered as the decision makers on port selection. Some researchers indicate

that shippers play the key role in determining port choice (Robinson, 2002;

Tongzon, 2002). Robinson (2002) suggests, for example, that ports are elements

embedded in a value-driven chain system and that it is important for the port

and its partners to offer greater value to their users compared to other

competing chains. However, current trends point towards shipping lines being

the key players in determining port choice with increasing attention given to

providing global logistics services through an integrated approach (Slack, 1985;

Fleming and Baird, 1999; Brooks, 2007). When asked to evaluate the

importance of clients for ports, ‘shipping company’ was indicated as the most

important client (4.61); ‘forwarder’ as the second most important (4.08); and

‘shipper’ as the third most important (3.65) (Table 2).

Competition intensification

Ports are confronted with the fact that they must continually compete to attract

shipping lines while simultaneously striving not to lose their existing

customers. As Table 3 shows, 97 per cent of all the respondents strongly agreed

(80.6 per cent) or agreed (16.7 per cent) that ports are facing more intense

competition than before. Regarding the source of competition, the development

of hub and feeder systems; shipping companies’ practices such as experi-

menting with new service networks; and the footloose nature of transshipment

can be considered. Some studies also indicate the expansion of port hinterlands,

to enlarge their catchment capabilities, as a reason for greater competition

among container ports (Wang and Cullinane, 2006). Respondents gave

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relatively equal weight to three sources of competition: shipping companies’

port selection strategy (3.86), overcapacity of port facilities (3.83), and devel-

opment of hub and spoke schemes (3.68). Port competition is also concerned

with the level at which competition is experienced; that is, inter-port interna-

tional, inter-port national and intra-port. Respondents considered competition

at an international level (4.29) to be more intense than competition between

ports in a country (3.60) or between terminals in a port (3.74).

Aspects of port evolution: The external perspectives

The ‘Service’ group is concerned with the external perspectives of performance,

namely a port’s relationship with its customers. Three aspects, Service Quality,

Service Price and Customer-Oriented Practices were identified.

Table 2: Descriptive statistics for the emergence of powerful clients

Items Response scale Mean SD

1 2 3 4 5 M

The bargaining power of customers is getting stronger 0.0 5.6 6.9 29.2 56.9 1.4 4.33 0.85

The following customers are the most important for ports:Shipping companies 0.0 0.0 6.9 18.1 73.6 1.4 4.61 0.60Shippers 0.0 2.8 13.9 41.7 38.9 2.8 3.65 0.99Forwarders 0.0 9.7 23.6 44.4 19.4 2.8 4.08 0.93Inland transport companies 1.4 19.4 50.0 20.8 6.9 1.4 3.07 0.86Other port operators 5.6 20.8 51.4 16.7 4.2 1.4 2.83 0.88General public 34.7 30.6 26.4 2.8 2.8 2.8 1.65 1.03

Note: M stands for missing data.

Table 3: Descriptive statistics for intensified competition among ports

Items Response scale Mean SD

1 2 3 4 5 M

Ports face more intense competition than before 0.0 0.0 1.4 16.7 80.6 1.4 4.74 0.43

Port competition occurs at the following levels:Inter-port/International 0.0 1.4 5.6 34.7 54.2 4.2 4.29 0.86Inter-port/national 0.0 4.2 22.2 48.6 18.1 6.9 3.60 0.90Intra-port 0.0 6.9 12.5 38.9 33.3 8.3 3.74 1.21

Port competition stems from the following:Hub & spoke system 2.8 5.6 19.4 41.7 26.4 4.2 3.68 1.08Lines’ port selection 0.0 5.6 12.5 44.4 31.9 5.6 3.86 0.92Overcapacity 0.0 6.9 23.6 34.7 31.9 2.8 3.83 0.93

Note: M stands for missing data.

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Service quality improvement

The trend towards consolidation, implying larger vessels and fewer ports of call;

a just-in-time strategy; and a door-to-door philosophy, require port operating

and stevedoring companies to provide a high-quality service that is reliable and

timely. Nearly 96 per cent of all respondents strongly agreed or agreed that there

is a greater requirement by customers for a higher quality of service than before,

with an average score of 4.58. Further, 90 per cent of all respondents strongly

agreed or agreed that ports are making greater efforts to improve their quality of

service with an average score of 4.33.

Regarding the importance of the indicators of Service Quality, respondents

attributed most weight to timeliness, followed by reliability. On the other

hand, the SC group showed stronger agreement with the idea of the increasing

requirement by customers for service quality compared to the other groups.

This may imply that shipping companies, as the main customers of ports,

view Service Quality to be more important than other aspects of port evolution

(Table 4).

Service price competition

Offering lower service price is undoubtedly one of the key strategies used to

attract lines that are themselves under huge pressure to reduce total shipping

costs. In reality, many port authorities and individual terminals attempt to

secure footloose transshipment cargo by lowering port charges for container

lines using their terminals as load centres. Similarly, port charges become a

major area where shipping lines are attempting to cut total operating

costs; therefore carriers usually prefer ports that can offer relatively low

service charges. This trend means that Cost Leadership is one of the ways

Table 4: Descriptive statistics for Service Quality

Items Response scale Mean SD

1 2 3 4 5 M

High-quality service is required by customersmore now than before

0.0 0.0 4.2 33.3 62.5 0.0 4.58 0.57

More efforts to improve service quality are nowbeing made by ports compared to before

0.0 1.4 8.3 45.8 44.4 0.0 4.33 0.69

The following aspects of service quality are the most important:Timeliness 0.0 0.0 2.8 30.6 66.7 0.0 4.64 0.53Reliability 0.0 0.0 2.8 48.6 45.8 2.8 4.32 0.55No damage to shipment 0.0 5.6 26.4 48.6 16.7 2.8 3.68 0.80Information provision 0.0 6.9 18.1 47.2 25.0 2.8 3.82 0.86

Note: M stands for missing data.

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efficiency-oriented ports can achieve competitive advantage, and ports often

become least cost providers to achieve this (Notteboom and Winkelmans, 2001)

(Table 5).

Approximately, 80 per cent of all respondents agreed or strongly agreed that

customers require more ports to provide services at lower cost than before. Thus

ports prefer a lower price strategy compared to other strategies to secure cus-

tomers, and are making greater efforts to be competitive in terms of price level

than before. The POC and SC groups clearly have different positions on this

issue. As can be seen from Table 6, the high average scores from the POC group

imply that ports prefer a ‘lower price’ strategy to other strategies, and are making

greater efforts to provide services at lower price than before. However, the SC

group shows a neutral or nearly negative position to these phrases, which im-

plies that shipping companies perceive that ports do not provide services at a

low price and do not necessarily make efforts to lower prices when they can.

Customer-oriented practices

Previous research suggests that successful seaports are customer focused

and continuously improve performance (Notteboom and Winkelmans, 2001;

Table 5: Descriptive statistics for Service Price

Items Response scale Mean SD

1 2 3 4 5 M

Lowering service price is required by customersmore now than before

0.0 4.2 15.3 40.3 38.9 1.4 4.10 0.84

Lower price strategy is preferred to otherstrategies to attract customers

0.0 5.6 18.1 44.4 30.6 1.4 3.96 0.85

Greater efforts are now being made to achieveprice competitiveness compared to before

0.0 6.9 16.7 50.0 25.0 1.4 3.89 0.84

Note: M stands for missing data.

Table 6: Descriptive statistics for Service Price by group

Items POC SC PS AC All groups

Lowering service price is required by customersmore now than before

4.60 3.69 4.04 3.85 4.10

Lower price strategy is preferred to other strategiesto attract customers

4.55 3.15 3.96 3.85 3.96

Greater efforts are now being made to achieve pricecompetitiveness compared to before

4.55 2.92 3.61 3.85 3.89

Abbreviations: POC � Port Operating Company; SC � Shipping Company; PS � Public Sector; AC – AcademicInstitution.

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Marlow and Paixao-Casaca, 2003). However, approximately 70 per cent of re-

spondents suggest that it is not always easy to satisfy customers’ needs, which

are increasingly diversified and complicated. Among specific customers’ needs,

Timeliness was rated highest, although all four given items achieved similarly

high average scores. Whereas the SC group rated ‘timeliness’ as the most

important (4.31) and ‘low cost’ as the least important (3.69), the POC group

rated ‘low cost’ as the most important customer need (4.75). This suggests that

the SC group puts more emphasis on ‘service quality’ such as timeliness and

reliability compared to ‘cost’, whereas the POC group tends to respond to ‘cost’

issues more sensitively. Where consideration is given by ports to services being

tailored to customers’ needs, 70 per cent of all respondents were positive but

around 30 per cent held a neutral or negative view, and this was largely attri-

butable to the SC group. The average score of the SC group on this item may

mean shipping companies are not satisfied with port services. The average

score entirely from the POC group also shows that the group is not confident

of providing customer tailored services, with some indicating a ‘neutral’ or

‘disagree’ position (Tables 7 and 8).

It is generally taken for granted that shipping lines require ports to provide

a high-quality service at a low price. For ports, attracting or securing customers

through competitive pricing this could be tempting in the short term, and is

in line with cost leadership and strategies focusing on economies of scale.

However, in the long term, a high quality of service, which is reliable and

timely, as well as efficient, is preferred by shipping companies, and this is more

sustainable. One respondent, a senior manager at a top 10 container line,

added a statement to his response that ‘service quality such as timeliness is now

being regarded as more critical than price as the number of mega container

vessels increases and the number of port calls decreases’.

Table 7: Descriptive statistics for Customer Orientation

Items Response scale Mean SD

1 2 3 4 5 M

Customers’ needs are getting increasingly diverseand complex

0.0 4.2 23.6 38.9 31.9 1.4 3.94 0.86

The following customers’ needs are important:Low price 0.0 2.8 8.3 36.1 51.4 1.4 4.32 0.76Efficient operation 0.0 1.4 6.9 51.4 38.9 1.4 4.24 0.66Reliability 0.0 1.4 2.8 50.0 44.4 1.4 4.33 0.62Timeliness 0.0 0.0 4.2 31.9 62.5 1.4 4.53 0.57

Ports are providing services fitted to customers’ needs 0.0 6.9 20.8 50.0 20.8 1.4 3.81 0.83

Note: M stands for missing data.

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Aspects of port evolution: The internal perspectives

Operational efficiency

Port efficiency and productivity have been greatly improved since liner shipping

companies and container ports, respectively, began to deploy dedicated con-

tainer ships and efficient container handling systems (Cullinane et al, 2004).

Specialisation and automation have increased, but at different rates according

to need, and increasing vessel size has led to the requirement for large-scale

investments in infrastructure, superstructure and channel dredging as well as

significant investment in information technology systems. However, there is

still wide variation in terminal size, design detail and equipment specifications

(Beresford et al, 2004).

Most respondents (97.2 per cent) agreed or strongly agreed that efficient

operation is now more necessary than before, with an average score of 4.65.

Furthermore, 95.8 per cent agreed or strongly agreed that greater efforts are now

being made to improve efficiency. As Table 9 shows, there was no major

difference between the sample groups on this issue. With regard to how to

improve efficiency, respondents indicated that the ‘introduction of new in-

formation systems’ was the most important issue.

Security and safety

Safety and security issues have, more recently, become linked to efficiency and

competitiveness, as safety and security has grown in importance as an issue

both internationally and domestically. Beresford et al (2004) point out that

‘a poor safety culture in the long run will obstruct an individual port’s com-

petitiveness’. Other literature suggests that if security is dealt with correctly, it

will have a huge impact on port efficiency and competitiveness in the long term,

regardless of how ports address this issue (Clark et al, 2004; Banomyong, 2005;

Lee and Chang, 2007).

More than 90 per cent of all respondents agreed or strongly agreed that

international and domestic regulation about safety and security is increasing.

Table 8: Descriptive statistics for customers’ needs by group

Items POC SC PS AC All groups

Low cost 4.75 3.69 4.35 4.23 4.32Efficient operation 4.30 4.00 4.19 4.46 4.24Reliability 4.45 3.92 4.23 4.77 4.33Timeliness 4.55 4.31 4.54 4.69 4.53

Abbreviations: POC � Port Operating Company; SC � Shipping Company; PS � Public Sector; AC – AcademicInstitution.

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Furthermore, around 85 per cent of all the respondents agreed or strongly

agreed that greater efforts are being made to improve safety and security.

However, ‘customer requirements on safety and security are growing’ was

considered to be much less important, scoring only 3.75. This would seem to

indicate that ports’ actions for safety and security are initiated by international

and domestic regulation rather than customer requirements. However, it is clear

that customers do have an interest in this issue as 50 per cent of all the re-

spondents indicated ‘agree’ for ‘customers’ growing requirement on safety and

security’. Respondents often hold a cautious position with regard to safety

and security issues, for example one respondent from the SC group suggesting

that ‘excessive regulation on safety and security increases total transport cost

which may hinder the competitiveness of ports’ (Table 10).

Aspects of port evolution: The logistical perspectives

Connectivity to other transport modes

The role of port authorities in the twenty-first century includes the promotion of

an efficient intermodal system in order to secure cargo under conditions of high

competition. In this study, connectivity to inland transport modes was ad-

dressed. Such transfers are impacted upon by factors such as the frequency of

sea and inland transport services to or from ports, and transfer time between

sea and inland transport (UNCTAD, 2004). Most (91 per cent) of the re-

spondents agreed or strongly agreed that connectivity with other transport

modes is more important to customers (average score 4.22) than it was before.

Similarly, there was consensus among respondents (average score 3.93) that

connectivity with other transport modes is more important for effective port

operations now than it was in the past.

Table 9: Descriptive statistics for Efficient Operation

Items Response scale Mean SD

1 2 3 4 5 M

Efficient operations are required by customersmore now than before

0.0 0.0 1.4 25.0 72.2 1.4 4.65 0.48

More effort is being made to improve operationalefficiency by ports

1.4 0.0 2.8 45.8 50.0 0.0 4.42 0.69

Operational efficiency can be improved by the following:Introduction of new equipment 0.0 0.0 12.5 63.9 20.8 2.8 3.97 0.58Labour reduction 1.4 13.9 36.1 30.6 16.7 1.4 3.42 0.98Introduction of new information systems 0.0 0.0 6.9 44.4 47.2 1.4 4.35 0.62

Note: M stands for missing data.

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AUTHOR COPYPort cooperation and networking

The development of strategic relationships with overseas ports (HIT in Felix-

stowe), between neighbouring ports (HIT at both Felixstowe and Thamesport)

and at inland ports (for example, ECT’s role at Venlo, southern Netherlands) are

suggested as some of the most important roles of port authorities in the new

millennium. Notteboom and Winkelmans (2001) suggest that even simple

forms of coordination could help to counterbalance carrier power, especially

when container flows towards the shared local hinterland of the neighbouring

ports are involved. The respondents generally agreed that port cooperation and

networking is helpful for strengthening competitiveness of ports as shown

in Table 11. However, there were also respondents who disagreed (2.8 per cent)

or strongly disagreed (2.8 per cent) with this phrase or indicated a neutral view

(8.3 per cent). Furthermore, more than half of the respondents showed negative

or neutral positions to the contention that ‘port authorities support port oper-

ating companies or make an effort to establish port cooperation and networks’.

Value-added services

During the 1980s, some ports diversified into the emerging field of logistics and

began to offer value-addition services as they became increasingly integrated

into the transport chain. The extent of integration varied depending on cargo

and customer requirements (Beresford et al, 2004). In a competitive environ-

ment, supply chains are often focused on the port and shippers choose between

those chains on the basis of competitive advantage and value gained (Robinson,

2002). The services offered by terminal operators, in order to be competitive,

may include low-end value-added logistical services. Of all respondents 91.7 per

cent strongly agreed or agreed that the provision of value-added services is

increasingly necessary. However, only 50 per cent of the respondents were

positive towards the phrase ‘port authorities support port operating companies

or make efforts to provide effective value-added services’, and 46 per cent of

the respondents were negative (15.3 per cent) or neutral (30.6 per cent). This

Table 10: Descriptive statistics for Safety and Security

Items Response scale Mean SD

1 2 3 4 5 M

International and domestic regulationson safety and security are increasing

0.0 1.4 6.9 33.3 58.3 0.0 4.49 0.69

Customers’ requirements on safety andsecurity are growing

0.0 5.6 29.2 50.0 15.3 0.0 3.75 0.78

More efforts to are being made byports improve safety and security

0.0 0.0 15.3 56.9 27.8 0.0 4.13 0.64

Note: M stands for missing data.

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implies that the respondents perceive that port authorities’ strategies to expand

value-added service provision and to increase port cooperation and networking

are not entirely successful. This is especially true where the strategies are seen

as the primary mechanism to improve port competitiveness.

Significance of the port evolution aspects

Two more questions investigated how the respondents perceive the significance

of port evolution. First, respondents were asked to evaluate the significance of

various aspects of port evolution, and subsequently to rate the extent to which

they should be reflected in port performance measures. Very similar patterns

of response to both questions were given, as shown in Table 12 and Figure 4. All

external perspectives achieved relatively high average scores, but the internal

perspective ‘efficient operation’ achieved the highest score. This implies that

efficient operations and efficiency are still regarded as the most important

factors for both port management and performance. The lowest ranked item

was ‘port cooperation and networking’, which has been suggested as being one

of the emerging important strategies for ports to increase bargaining power in

negotiations with powerful clients. This may imply either that port authorities

and port operating companies have not attempted to introduce this strategy, or

that respondents perceive this strategy is not effective in gaining a competitive

edge. The average scores of this aspect for both questions are around medium

Table 11: Descriptive statistics for the three aspects from logistical perspectives

Items Response scale Mean SD

1 2 3 4 5 M

Connectivity with other transport modes is in greaterdemand from customers now than before

0.0 0.0 6.9 56.9 34.7 1.4 4.22 0.77

Connectivity with other transport modes is consideredin port operation and development more now thanit was before

0.0 0.0 19.4 61.1 18.1 1.4 3.93 0.78

Port cooperation and networking is helpful tostrengthen the competitiveness of ports

2.8 2.8 8.3 51.4 31.9 2.8 3.96 1.00

Port authorities support port operating companiesand make more effort to establish port cooperationand networks than before

11.1 16.7 27.8 33.3 8.3 2.8 2.92 1.19

Value-added service provision is necessary to strengthenthe competitiveness of ports more now than before

0.0 1.4 2.8 38.9 52.8 4.2 4.31 0.83

Port authorities support port operating companies andmake efforts to provide effective value-added services

5.6 9.7 30.6 31.9 18.1 4.2 3.29 1.16

Note: M stands for missing data.

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AUTHOR COPY

level (¼ 3), and therefore it is suggested that it should be excluded from the list

of the port evolution aspects.

Second, respondents rated the appropriateness of the indicators for each

aspect of port evolution, which were derived from the relevant literature as

presented in Appendix Table A1 and Figure 2. The results show that there was

strong agreement among respondents on the appropriateness of the indicators

for measuring aspects of port evolution. In order to simplify the measurement,

model indicators where the mean value was lower than 4.0 were excluded.

Although this could be considered an arbitrary division, this allowed the Con-

firmatory Questionnaire to be simplified, which was thus based on the retained

port evolution aspects and indicators.

2.5

3

3.5

4

4.5

5

Port Evolution Aspects

Sca

le

SQ CO SP VASOE SS CON PCN

Figure 4: Average scores of the port evolution aspects.Note: SQ � Service Quality; CO � Customer Orientation; SP � Service Price; OE � Operation Efficiency;SS � Safety and Security; CON � Connectivity; PCN � Port Cooperation and Networking; VAS � Value-added Service.

Table 12: Descriptive statistics for significance of port evolution aspects

Items Significance Reflection

Mean SD Mean SD

External perspectivesService Quality (SQ) 4.33 0.73 4.49 1.00Customer Orientation (CO) 4.22 0.74 4.47 0.84Service Price (SP) 4.19 0.80 4.22 0.81

Internal perspectivesEfficient Operation (EO) 4.35 0.72 4.65 0.53Safety and Security (SS) 3.75 0.85 3.75 0.94

Logistical perspectivesConnectivity (CON) 3.72 0.61 3.96 0.76Port Cooperation and Networking (PCN) 3.40 0.86 3.49 0.84Value-added Service provision (VAS) 3.75 0.87 4.03 0.71

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Conf i rmatory Study

For empirical analysis, the second questionnaire was designed based on the

results of the exploratory study described above. The questionnaire and

the results are provided in Appendix Table A2. The collected data were analysed

with the AMOS software package (version 6.0). The sample size of 61 can be

categorised as ‘small’. As for normality, bootstrapping was applied to remedy

the non-normality problems, as the data set was generally negatively skewed

(Byrne, 2001). Table 13 provides a summary of the measurement results in-

cluding means and standard deviations.

Sub-dimensional measurement models

In this study, port performance is composed of three sub-groups: Service,

Operations and Logistics. First, the sub-dimensional measurement models and

subsequently the port performance measurement model are assessed in terms

of validity and reliability (Garver and Mentzer, 1999). Validity consists of

content validity, unidimensionality, convergent and discriminant validity. This

study assesses the proposed measurement model in order of content validity,

unidimensionality, reliability and construct validity as reliability can be

assessed only when unidimensionality is verified (Garver and Mentzer, 1999).

The measurement model was devised through a literature review and

modified through the exploratory study. Therefore content validity is confirmed

Table 13: Summary of measurement results

Construct No. ofitems

Mean SD Cronbach’sa

Compositereliability

Average varianceextracted

ServiceService Quality 5 3.96 0.74 0.80 0.81 0.52CustomerOrientation

4 4.03 0.83 0.88 0.88 0.65

Service Price 4 3.55 0.98 0.90 0.90 0.76

OperationEfficientOperation

4 4.08 0.8 0.77 0.79 0.60

Safety andSecurity

2 4.00 0.9 0.84 0.84 0.72

LogisticsConnectivity 2 3.65 0.95 0.88 0.88 0.78Value-addedService

3 3.43 0.93 0.89 0.89 0.72

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AUTHOR COPY

because content validity can be certified whenever the constructs are derived

from a comprehensive analysis of the relevant literature (Gerbing and

Anderson, 1988). For unidimensionality, Goodness-of-fit indices of CFA, which

are the adjusted maximum likelihood w2 statistic (w2/dfo2.0), GFI (40.9),

CFI (40.9), TLI (40.9) and RMR (o0.05) (Hair et al, 1998; Tabachnick and

Fidell, 2001), were applied, as it has been argued that traditional techniques

such as Cronbach’s a and Exploratory Factor Analysis cannot truly assess

unidimensionality (Garver and Mentzer, 1999).

Figure 5 shows the results of CFA for three sub-dimensional measurement

models. For a ‘Service’ measurement model, overall Goodness-of-fit indices

(w2/df¼ 1.56; CFI¼ 0.94; TLI¼ 0.92; RMR¼ 0.04) suggest that the proposed

model achieved a good fit to the observed data. For an ‘Operation’ measurement

model, overall Goodness-of-fit indices (w2/df¼ 0.94; CFI¼ 1.00; TLI¼ 1.00;

RMR¼ 0.03) show a very good fit into the observed data. For a ‘Logistics’

measurement model, the criteria of fit indices are also satisfied (w2/df¼ 2.7;

CFI¼ 0.96; TLI¼ 0.91; RMR¼ 0.03).

Table 13 clearly shows that reliability tests were passed. The composite

reliability of construct (40.7) and Average Variance Extracted (AVE) measure

(40.5) were applied along with Cronbach’s a (40.7) as researchers argue that

Cronbach’s a is inflated on a measuring scale that has a large number of items

and assumes that all the measured items have equal reliabilities (Hair et al,

1998).

Convergent validity, the extent to which the latent variable correlates to

items designed to measure that same latent variable, is assessed by determining

whether standard factor loadings for each measurement item are statistically

significant (Anderson et al, 1987; Garver and Mentzer, 1999). All factor loadings

for the latent variables were significant at the 1 per cent level and most of them

were greater than 0.6. However, some items that are presented in italics in

Table A2 were removed from the scales as their factor loadings were less than 0.5.

Discriminant validity, the extent to which the items representing a latent

variable discriminate that construct from other items representing other latent

variables, was assessed using a method devised by Fornell and Larker (1981).

Discriminant validity is achieved if: (i) the correlation between latent variables

is lower than 0.85 (Kline, 2005), (ii) the AVE of each construct is higher than

0.5 (Fornell and Larker, 1981), and (iii) the square-rooted AVE of each latent

variable is higher than inter-construct correlations. These are shown in

Table 14. All inter-construct correlations (values off the diagonal) are less than

0.85 and AVEs of all the constructs (values in parentheses on the diagonal) are

greater than 0.5. Finally, the square-rooted AVEs of all the constructs (value

on the diagonal, but not in parentheses) are greater than the inter-construct

correlations.

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Service

ServiceQuality

CustomerOrientation

ServicePrice

0.36

0.77

0.86

0.72

0.60 Timeliness 1

Timeliness 2

Lead time

Accuracy of information

Responsiveness 1

Responsiveness 2

Flexibility 1

Flexibility 2

Total price

Auxiliary service charge

Cargo handling charge

0.80

0.73

0.70

0.77

0.87

0.87

0.88

0.83

0.86

0.81

0.64

0.50

0.59

0.69

0.65

0.76

0.76

0.77

0.74

0.53

χ2=63.844 (df=41, p=0.013); χ2/df=1.56; CFI=0.94; TLI=0.92; RMR=0.04

Operation

Operationefficiency

0.14

0.74

0.50 Throughput per crane

Ship waiting time

Ship working time

0.99

0.79

0.99

0.62

Safety andSecurity

0.99Compliance to regulation

Number of accidents

0.81

0.89

0.66

0.80

χ2=4.695 (df=5, p=0.454); χ2/df=0.94; CFI=1.00; TLI=1.00; RMR=0.03

Logistics

Value-addedservice

0.68

0.79

0.82Cargo increase form VAS

VA increase from VAS

Facility adequacy

0.81

0.91

0.66

0.83

Connectivity

0.99Cargo waiting time

Cargo working time

0.85

0.92

0.73

0.84

χ2=10.911 (df=4, p=0.028); χ2/df=2.7; CFI=0.96; TLI=0.91; RMR=0.03

Measurement model: Service

Measurement model: Operation

Measurement model: Logistics

Figure 5: Sub-dimensional measurement models.

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Table

14:

Inte

r-co

nst

ruct

corr

elat

ion,

AVE

and

squa

rero

ot

ofAVE

Serv

ice

qual

ity

Cust

omer

orie

nta

tion

Serv

ice

pric

eEf

fici

ent

oper

atio

nSa

fety

and

secu

rity

Connec

tivi

tyVa

lue-

adde

dse

rvic

e

Serv

ice

Qua

lity

0.7

2(0

.52)

Cust

om

erOrien

tati

on

0.5

7**

0.8

1(0

.65)

Serv

ice

Price

0.4

6**

0.5

4**

0.8

7(0

.76)

Effici

ent

Oper

atio

n0.3

3**

0.4

4**

0.4

6**

0.7

7(0

.60)

Safe

tyan

dSe

curi

ty0.2

8*

0.5

7**

0.6

5**

0.5

5**

0.8

5(0

.72)

Connec

tivi

ty0.2

40.4

9**

0.6

5**

0.6

5**

0.5

6**

0.8

8(0

.78)

Valu

e-ad

ded

Serv

ice

0.3

7**

0.5

1**

0.6

2**

0.5

5**

0.4

5**

0.6

9**

0.8

5(0

.72)

Not

e:**Po

0.0

1;

*Po

0.0

5.

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Discriminant validity is therefore confirmed among the latent variables

examined in this analysis.

Port performance measurement model

In the model, port performance governs the three sub-dimensional second-

order measurement models. To validate the port performance model, the

observed variables in each of the latent variables were averaged to simplify

the original complex model (Garver and Mentzer, 1999). This method

enables researchers to test the complicated model by using only a small

sample (Lai et al, 2002). Consequently, the seven port evolution aspects that

were the latent variables and the first-order factors cascade downwards to

become the observed variables, and the three groups that were the second-order

factors likewise cascade to become the first-order factors as shown in

Figure 6. The overall Goodness-of-fit indices (w2/df¼ 2.6; GFI¼ 0.91;

CFI¼ 0.92; TLI¼ 0.83; IFI¼ 0.92; RMR¼ 0.04) demonstrate that they achieved

a good fit into the observed data. The factor loadings of the three second-order

factors are very high and significant at the 0.1 per cent level. A port

performance measurement model therefore can be conceptualised as a

multi-dimensional measure consisting of ‘Service’, ‘Operation’ and ‘Logistics’,

and is viable.

PortPerformance

Service

Operation

Logistics

0.68

0.98

0.97

0.93

0.82Service quality

Customer orientation

Service price

Efficient operation

Safety and security

Total price

Auxiliary service charge

0.42

0.68

0.87

0.79

0.71

0.76

0.21

0.46

0.58

0.76

0.62

0.51

χ2=26.077 (df=10, p=0.004); χ2/df=2.6; GFI=0.91; CFI=0.92; TLI=0.83; IFI=0.92; RMR=0.04

Figure 6: Port performance measurement model.

Port evolution and performance in changing logistics environments

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Conc lus ion

This article has explored the changes taking place in ports through a two-stage

research process using exploratory and confirmatory studies. This led to the

development of a multi-dimensional port performance measurement frame-

work that reflects the changes taking place in ports. From the exploratory study,

it was found that efforts to be externally effective as well as to be internally

efficient are made by ports in order to cope with the challenges stemming from

a changing logistics environment. In other words, ports are striving to meet

customers’ requirements such as high service quality with low service price

and customer-oriented service, and to provide value-added services and high

connectivity with other transportation modes. In addition, the study demon-

strated that the effectiveness aspects of port evolution should be reflected in

the port performance measurement framework. It was also inferred that ‘Port

Cooperation’ is not overtly considered or adopted as an effective strategy by

either port operating companies or port authorities. The different evaluation of

‘Service Price’ and ‘Service Quality’ between the POC and SC groups was

revealed in the study. Port operating companies assert that low price rather than

high service quality is most strongly required by shipping companies, and

lowering price is the most preferred strategy by ports. However, shipping

companies believe that ‘Service Quality’ is the most important requirement

and this aspect should be reflected in port performance measurement frame-

works. This implies that in the long term, port operating companies and port

authorities should seek to acquire competitive advantage from improving

service quality and by providing differentiated services rather than from low-

ering price.

The confirmatory study validated the multi-dimensional port performance

measurement framework that simultaneously incorporates internal efficiency

aspects, external effectiveness aspects and logistical aspects of ports using the

typical standards of scale development. This implies that respondents believe

that port performance is multi-faceted. Specifically, port performance is shown

not to be limited to internal processes but is also concerned with external

service aspects such as ‘Service Quality’, ‘Customer Orientation’ and ‘Service

Price’, and logistical aspects such as ‘Connectivity to other transport modes’

and ‘Value-added Service’. The managerial implication is that managers in port

operating companies and port authorities should strive to maintain a balanced

focus embracing both effectiveness and efficiency aspects of performance

management and improvement, aiming to meet the expectations of customers

and other parties such as inland transport service providers. The multi-

conceptualisation provides insights into the constructs of port performance and

its relationships with the underlying dimensions. At item and sub-dimension

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levels, the constructs provide direct and actionable information on port

performance. At a higher level, managers are provided with an opportunity to

look at port performance at a more detailed level of abstraction beyond the

individual item and sub-dimension tiers.

However, there are also some limitations that should be considered when

discussing the conclusions of this study. Both surveys in this research were

conducted on sample groups in South Korea, which means that generalising the

results and implications to other countries would require careful consideration

as there may, for example, be cultural pressures and working practices that may

be different to other countries. Further, the empirical analysis was conducted

with a relatively small sample size of only 61 respondents. In order to improve

model fit statistics, and to provide more precise and reliable results, the

sample size needs to be larger. A questionnaire survey method was used to

explore the internal changes taking place in ports, which can be termed ‘port

evolution’; this evaluation necessarily involves quantitative research methods.

Qualitative research methodologies such as interviewing would need to be

adopted for the exploratory stage of a study. This study employed only

measurement models (that is, CFA) from the overall SEM approach. For further

research, it would be both interesting and useful to identify any additional

relationships that may exist between the constructs in the validated measure-

ment model or between other variables. The present study discarded one

port evolution aspect, ‘Port Cooperation’, from the descriptive analysis.

Therefore the relationship of this aspect to port performance was not evaluated

and could be included in future research.

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Appendix

Table A1: Appropriateness of the indicators for the port evolution aspects

Aspect Indicator All groups POC SC PS AC

Efficient Throughput 4.32 4.60 4.00 4.38 4.08Operation Throughput per hectare 3.88 4.25 3.69 3.92 3.38

Throughput per worker 3.85 4.25 3.46 3.46 4.38Throughput per crane 4.33 4.75 3.92 4.23 4.38Ship waiting time 4.32 4.30 4.62 4.08 4.50Ship working time 4.29 4.45 4.15 4.19 4.38Time of port related services 3.67 3.60 3.92 3.85 4.00Time of cargo stay in port 3.83 3.75 3.92 3.73 4.08

Service Price Total cost involved in port 4.68 4.70 4.54 4.69 4.77Cargo handling charge 4.38 4.65 4.23 4.19 4.46Port related service charge 4.00 4.15 3.92 3.81 4.23Port facility usage charge 4.03 4.30 4.15 3.69 4.15

Service Timeliness 4.60 4.60 4.46 4.69 4.54Quality Reliability 4.46 4.35 4.46 4.46 4.62

Lead time to service delivery 4.24 4.40 4.23 4.04 4.46Level of cargo damage 3.89 4.05 3.85 3.62 4.23Accuracy of shipment information 4.01 4.15 4.15 3.85 4.15

Customer Orientation Responsiveness 4.56 4.65 4.46 4.50 4.62Flexibility 4.19 4.25 4.23 3.96 4.54Annual number of claims 3.85 4.20 3.85 3.50 4.00

Connectivity Cargo waiting time between modes 4.31 4.30 4.31 4.15 4.46Cargo working time between modes 4.13 4.15 4.38 3.96 4.15

Value-added Service Cargo accruing from VAS 4.06 4.00 4.00 4.12 4.08Value-added from VAS 4.11 4.00 4.00 4.15 4.33

Safety and Security Compliance with regulation 4.33 4.50 4.15 4.27 4.38Annual number of accidents 4.10 4.15 4.38 4.00 3.92Annual number of accidents prevented 3.71 3.75 3.92 3.54 3.77

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Table A2: Descriptive statistics for the second survey

Construct Observed variables Mean SD

ServiceService Quality Reliability Provide reliable service consistently 4.1 0.8

Timeliness 1 Handle cargo on quoted or anticipatedtime

4.2 0.7

Timeliness 2 Handle cargo on time customers require 3.9 0.6Lead time Service lead time is short 3.6 0.7Information Provide shipment Information accurately 4.0 0.9

CustomerOrientation

Responsiveness 1 Respond promptly to the need ofcustomers

4.1 0.8

Responsiveness 2 Have quick decision-making process 4.0 0.8Flexibility 1 Flexible in terms of volume and type of

cargo4.0 0.8

Flexibility 2 Dealing with unexpected events orsituations

4.0 0.9

Service Price Total price Our total price is low 4.2 0.9Cargo handling

chargeOur cargo handling charge is low 4.1 0.9

Auxiliary servicecharge

Our auxiliary service charge is low 3.8 1.0

Port charge Our port charge is low 2.1 1.1

OperationEfficientOperation

Throughput Making effort to increase cargothroughput

4.5 0.7

Throughput percrane

Throughput per crane is high 4.2 0.8

Ship waiting time Our ship waiting time is short 3.8 0.9Ship working time Our ship working time is short 3.8 0.8

Safety andSecurity

Regulation Our port is compliant to securityregulations

4.0 0.9

Accident The number of accident is low 4.0 0.9

LogisticsConnectivity Cargo waiting time Our cargo waiting time for mode transit

is short3.6 0.9

Cargo workingtime

Our time for mode transit is short 3.7 1.0

Value-addedService

Cargo Cargo is attracted by VAS 3.5 0.9

VA VA increase from VAS 3.6 1.0Facility We have adequate facility for VAS 3.2 0.9

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