A segmentation based analysis for measuring customer satisfaction in maritime transportation

Abstract

This study was conducted to profile customers according to the level of satisfaction with the service attributes of maritime public transport provided by Seabus Service Company (SSC), the sole provider of maritime transport in Istanbul. Such analysis needs to be conducted by considering market segments in terms of maritime transportation usage and post purchase behavior. This was accomplished by conducting quantitative research through face-to-face surveys of SSC passengers. According to the results by multivariate data analysis, including factor analysis and cluster analysis, six segments are revealed in terms of customer satisfaction level with the maritime service attributes. Moreover, there are significant differences among the segments in terms of usage frequency (travel frequency in this study), age and education level. Different strategies for different customer segments within the maritime passenger market to increase customer usage and satisfaction of maritime transportation in Istanbul are suggested from the findings. Thus, this paper provides guidelines for the Turkish Maritime Authorities as to how to expand maritime transportation usage in Istanbul, which is not only the largest city and the most crucial trade center of Turkey but also has the highest share of passenger maritime transportation in the country.

First published online 24 September 2015

Full text



 















TRANSPORT
ISSN 1648-4142 / eISSN 1648-3480
Article in press
doi:10.3846/16484142.2015.1079800
A SEGMENTATION BASED ANALYSIS FOR MEASURING CUSTOMER
SATISFACTION IN MARITIME TRANSPORTATION
Yeliz Ekinci1, Nimet Uray2, Füsun Ülengin3, Cem Duran4
1Istanbul Bilgi University, Turkey,
2, 4Istanbul Technical University, Turkey
3Sabanci University, Turkey
Submitted 17 April 2014; resubmitted 22 September 2014; accepted 1 March 2015;
rst published online
Abstract. is study was conducted to prole customers according to the level of satisfaction with the service attrib-
utes of maritime public transport provided by Seabus Service Company (SSC), the sole provider of maritime transport
in Istanbul. Such analysis needs to be conducted by considering market segments in terms of maritime transportation
usage and post purchase behavior. is was accomplished by conducting quantitative research through face-to-face
surveys of SSC passengers. According to the results by multivariate data analysis, including factor analysis and cluster
analysis, six segments are revealed in terms of customer satisfaction level with the maritime service attributes. Moreo-
ver, there are signicant dierences among the segments in terms of usage frequency (travel frequency in this study),
age and education level. Dierent strategies for dierent customer segments within the maritime passenger market to
increase customer usage and satisfaction of maritime transportation in Istanbul are suggested from the ndings. us,
this paper provides guidelines for the Turkish Maritime Authorities as to how to expand maritime transportation usage
in Istanbul, which is not only the largest city and the most crucial trade center of Turkey but also has the highest share
of passenger maritime transportation in the country.
Keywords: mass passenger public transport; statistical analysis; socio-economic characteristics; passenger transporta-
tion; customer satisfaction.
Corresponding author: Yeliz Ekinci
E-mail: ekinciyeliz@yahoo.com
Copyright © 2015 Vilnius Gediminas Technical University (VGTU) Press
http://www.tandfonline.com/TRAN
Introduction
European Union (EU) countries recently admitted that,
in terms of the environment, business eciency, health
and extending road capacity to levels that can keep pace
with predicted growth, current trends in trac are un-
sustainable. e rst attempts to develop objective meas-
ures to improve the EU transport network began in 1993
with the Maastricht Agreement. e introduction of the
Trans-European Network (TEN) and the integration of
political, institutional and nancial bases were realized
for this purpose. e aim of TEN is, rst of all, to ulti-
mately forge a truly unique Europe through economic
and social integration and to provide a balanced usage of
transportation modes throughout Europe (EC 2001). e
White Paper, published in 2011 (EC 2011b), identies
the challenges that the transport system is likely to face
in the future, based on evaluation of policies and devel-
opments in the recent past and on assessment of current
trends. It denes a long-term strategy that would allow
the transport sector to meet its goals by 2050. is report
is part of a joint impact assessment for initiatives by the
European Commission (EC) related to the transition to
a low-carbon economy by 2050– to ensure consistency
in both the modeling framework and the consequent de-
velopment of policies. e overall policy goal is to move
towards a low-carbon competitive economy that would
meet the long-term requirements for limiting climate
change to 2 °C. Increasing maritime transport as a share
of total transport is one viable way of achieving this.
Currently, as is underlined by the statistics of EU
Reports (EC 2011a), although three-quarters of the
globe is covered by the sea, passenger maritime trans-
portation as a means to transition to a low-carbon econ-
omy remains underutilized.
Ta bl e 1 s h ow s t ha t am o ng w or ld w id e p as s en ge r
transport values [in billion passenger-kilometers (pkm)],
the passenger car has the largest share among the vari-
ous transportation modes. Underutilization of maritime
transportation, as well as excessive passenger car use, is
clearly not a country-specic but a worldwide phenom-
enon.
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

2Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Reducing private transport use and increasing
public transport use two critical but challenging tasks
for dealing with the problem of urban transportation
(Lai, Chen 2011). Increasing the number of customers
as well as the travel frequency is a convenient way of
facilitating demand for specic goods or services. us,
increasing customer satisfaction through enhancing per-
ceived performance of a specic public transportation
service is a key factor to expand the usage of such public
transport by existing passengers. Now, more than ever,
public transport operators are forced to place particular
emphasis on monitoring and improving their services
(Tyrinopoulos, Antoniou 2008; Birnerova 2007; Valask-
ova, Križanova 2008) to increase customer satisfaction.
As customer satisfaction increases, travel frequency in-
creases as well. us, extending the maritime passenger
market by using eective intensive growth strategies
developed based on information about customer satis-
faction, such as by increasing the quality of service and
level of customer satisfaction, is highly feasible.
e basic aim of this study is to analyze the mari-
time passengers market in Istanbul, the city with the
highest share of maritime passenger transportation in
Turkey. e analysis is conducted by segmenting them
based on their satisfaction level. e second section pro-
vides an overview of innercity transportation in Istan-
bul and underlines the underdevelopment of maritime
transportation. e third section provides a literature
review on customer satisfaction in general, as well as
satisfaction with public transportation in particular. e
fourth section presents the research framework based on
a survey conducted on Seabus Service Company (SSC)
passengers. Finally, conclusions and further suggestions
are given.
1. Why Analyze Istanbul as a Case Study?
Istanbul is a unique city that has preserved its position
as an economic center throughout its history, as well as
being the capital city of three empires. Today Istanbul
accounts for nearly 20% of Turkey’s gross national prod-
uct, contributing 40% of the government’s budget while
taking only 7–8% of the government’s expenditure (IBB
2011a). In the Census carried out in Turkey in 2007, it
became evident that migration to Istanbul continues.
As of 2011, the population of Istanbul had reached over
12.5 million (IBB 2011b).
Automobiles account for 75% of vehicles in Istanbul
and approximately 500 new automobiles are registered
each day, making local trac intolerable. Considering
that the daily travel time per person is 2.5 hours, cor-
responding to a minimum loss of labor of 300 million
TL (Turkish Lira) per year, the transportation situation
is serious (Ocak 2006).
e transportation issue is important in Istanbul
not only because of its high population, but also because
Istanbul is on the main highway route between two con-
tinents– Europe and Asia– and is the industrial, trade,
cultural and tourism center of Turkey. According to the
statistics of the General Directorate for Highways for
2006, 250000–300000 vehicles are used every day. Such
trac congestion has an economic cost (POAS 2011).
As can be seen from Fig.1, highways carry 92.29%
of the total trac in Istanbul. More than half of highway
transportation is via private cars, taxis, minibusses and
minibus taxis. Nearly 44% of highway transportation is
by private cars while public buses account for 28.15%.
e number of bus stops, cardholders and lines has sig-
nicantly increased in recent years (IETT 2011) in paral-
lel with the increasing number of students and teachers
living in the city. If the trend continues, the demand for
public transportation including a share of maritime trans-
portation is expected to increase. However, this trend
needs to be accelerated by implementing eective poli-
tics and strategies to prevent more severe transportation
problems in a continuously growing city like Istanbul.
Although, urban settlement and current trac
congestion make maritime transportation advanta-
geous concerning to speed, maritime transportation
is only 2.20% of all transport, ranking a distant third
aer highways and the railway. SSC provides 8.14% of
the public transportation. Despite its low share of pub-
lic transportation in Istanbul, maritime transportation
Table 1. Worldwide 2008 passenger transport values [billion pkm] (EC 2011a)
EU27 USA Japan China Russia
Passenger car 4725.0 7201.8 769.1 1263.6
(including buses and coaches) –
Bus+ trolley-bus+ coach 546.7 243.0 89.9 124.8
Railway 409.2 37.1 404.6 777.9 175.9
Tram+ metro 89.0 21.1 included in railway pkm – 51.6
Maritime 40.9 0.6 5.5 7.5 0.9
Air (domestic/intra-EU-27) 561.0 977.8 81.0 288.3 122.6
Fig.1. Percentage utilization of transportation type and
public transport in Istanbul (IETT 2011)
92 29.
220. 550.
Highway
Searoute
Railway63 67.
709.
773.
636. 814.
038.
Bus
Train
Light rail
Subway
SSC
Tram
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

Transport. Article in press 3
has some important advantages compared to the other
transportation methods, including high capacity, low
facility costs, cheap tickets, safety, comfort and environ-
mental friendliness. Safety is emphasized strongly; for
instance, it was found to be the most important criterion
in the study of Jain etal. (2014).
In summary, although Istanbul’s maritime transpor-
tation has developed rapidly (Fig.2), it remains behind
the target level and is underutilized despite its suitability
for Istanbul. e high level of private car and highway
use has resulted in severe trac congestion and negative
environmental impact. e data in Fig.2 clearly shows
that SSC changed the slope of passenger data when it en-
tered the market and opened new intercity lines in 2004.
Only limited research has been conducted to ana-
lyze the demand side in general, and customer satisfac-
tion, in particular to nd strategic ways to increase the
demand for maritime transportation in Istanbul. How-
ever, by understanding the nature of customer satisfac-
tion by maritime transportation users and highlighting
the attributes to which they give primary importance as
well as their satisfaction with these attributes, specic
strategies can be developed to increase the frequency of
usage of this service and provide insights as to how to
attract more potential passengers (De Oña etal. 2014).
is study therefore aims to provide guidelines to the
Turkish Maritime Authorities and maritime transporta-
tion service providers such as SSC to ll the gap between
the expectations and perceived performance of passen-
gers, as well as providing useful data to help policy mak-
ers develop eective transportation policies for Istanbul.
To t h e be s t o f ou r kn o w le d g e, t h is re s e a rc h is t he r st a t-
tempt to investigate the maritime transportation market
in Istanbul on a micro-scale.
2. Literature Review
Satisfaction is an overall eective response to a perceived
discrepancy between prior expectations and perceived
performance aer consumption (Oliver 1980, 1999). e
concept of consumer satisfaction has a central position
in marketing thought and practice since it is a major
outcome of marketing activity and serves to link pro-
cesses that culminate in purchase and consumption. In
the early 1970s, consumer satisfaction began to emerge
as a legitimate eld of inquiry. Pfa (1972) was the rst
to report direct information on consumer satisfaction to
policy makers. Studies by Olshavsky and Miller (1972),
Anderson (1973) and Cardozo (1964) formed the foun-
dation for much of the later theory and experimental
research. ese studies made important contributions
that attracted attention to customer satisfaction, and
were followed by many studies proposing theoretical
structures and conceptual models to investigate its di-
mensions (Churchill, Surprenant 1982; Gustafsson etal.
2005; Williams, Naumann 2011).
Anderson etal. (1994) investigated the link be-
tween customer satisfaction and economic returns,
nding that higher customer satisfaction leads to su-
perior economic returns. Other studies also emphasize
that satisfaction increases protability through increas-
ing loyalty and word-of-mouth communication, and
decreasing marketing expenditure (Reichheld 2001;
Hallowell 1996). Widespread acceptance of another re-
lationship is also evident in the literature on customer
satisfaction and both perceived quality and value (An-
derson, Sullivan 1993, Chen 2008; Jen, Hu 2003; Petrick
2004; Malik 2012). Anderson and Sullivan (1993) state
that satisfaction is best specied as a function of the
perceived quality ‘disconrmation’, which is the extent
to which perceived quality fails to match prepurchase
expectations. ey further report that quality falls short
of expectations and has a greater impact on satisfaction
and repurchasing intentions than quality, which exceeds
expectations, thus emphasizing the importance of feed-
back from the market to draw implications to facilitate
repurchasing.
Although, the majority of studies in the literature
focusing on testing the link between customer satisfac-
tion and related constructs have been conducted in vari-
ous sectors, they have mostly been from the perspective
of for-prot companies. ere have been many studies
about the satisfaction of services such as retail banking
(Hallowell 1996; Culiberg, Rojšek 2010), e-markets (An-
derson, Swaminathan 2011), and health services (Tataw
etal. 2011). Few studies have analyzed transportation
services. Although, the studies mentioned above mostly
explore the satisfaction factors of for-prot companies,
all of them share a common nding that service qual-
ity, perceived value and customer satisfaction are closely
related concepts.
In parallel with the ndings of similar studies
conducted for non-prot organizations in dierent in-
dustries, Lai and Chen (2011) indicate that passengers
who perceive the quality of a public transit service as
being good are more likely to have a higher level of per-
ceived value and satisfaction, and so continue to use the
service. Fellesson and Friman (2008) provide a trans-
national comparison of the perceived service satisfac-
tion with public transport in eight European countries.
Using factor analysis, they identied three satisfaction
dimensions, namely, comfort, sta, and safety, present
in most but not all of the cities. ese ndings indicate
that there are dierences in how public transport is per-
Fig.2. Maritime passenger transport usage in Istanbul
Transport usage [pkm]
120000
80000
40000
32000
24000
20000
16000
12000
8000
4000
90 92 96 98 00 02 04 06 08 1094
Year
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

ceived according to location. us, while there are in-
dustry generic dimensions, it is also important to take
local conditions into consideration. ese ndings mo-
tivated us to explore the factors of a specic transport
mode– maritime public transportation– in a specic
city– Istanbul.
e present study identies the satisfaction patterns
of maritime transportation passengers as customers and
denes dierent customer segments based on the per-
ceived satisfaction levels of customers according to dif-
ferent service attributes. Customers will consider some
attributes as being more important than others and will
give dierent satisfaction ratings to a particular attrib-
ute (Lu 2003). us, analysis of customer satisfaction of
maritime transportation should consider all factors in-
uencing the satisfaction.
Previous literature has mostly focused on the
relationship between the antecedents (for example, ser-
vice quality, perceived attributes of services or products,
and perceived value) and consequences (for example,
loyalty and repurchase intention) of customer satisfac-
tion. Other studies have focused only on overall custom-
er satisfaction as a function of satisfaction with the com-
ponents of the service concept, that is, attribute-based
models of satisfaction. As Anderson etal. (2008) point
out, most service typologies in the latter studies focus
exclusively on discriminating characteristics of the ser-
vice concept. ey ignore customer characteristics and
implicitly treat all customers as identical. Few of these
studies consider demographic characteristics of the cus-
tomers as a tool for market segmentation together with
the service components. e literature indicates that the
attributes of the service/product itself, the attitude of
the service personnel, the physical environmental con-
ditions (such as comfort and cleanliness), as well as the
demographic characteristics of the customers (such as
age, gender and education level) have frequently been
considered to be critical components of customer satis-
faction in the service industries (Bedi 2010; Deng, Nel-
son 2012; Olawole, Aloba 2014).
Park’s (2007) study is one of the few studies on cus-
tomer satisfaction in the transport service industry that
highlights the importance of other elements inuencing
overall satisfaction. is study analyses passenger satis-
faction of airline transportation, nding 11 components,
including six dimensions of airline services, namely: in-
flight service, reservation-related service, airport service,
reliability, employee service, flight availability, perceived
price, passenger satisfaction, perceived value, airline im-
age and overall service quality. e results reveal that
passenger satisfaction perceptions dier significantly
across airlines, seat classes, usage and travel frequency.
Tyrinopoulos and Antoniou (2008) analyzed stud-
ies conducted by the Hellenic Institiute of Transport
in Greece. e primary aim of the Hellenic Institute of
Tr an sp or t’s qu a li ty c ont r ol pr og r am s f or p ub li c t ra ns -
port operators was to assess the relationship between the
quality and performance of the transit systems using a
variety of performance and quality indicators, including
on-time performance, average waiting time at terminals
and stops, vehicle load, average route speed, conditions
at terminals and stops, provision of safety information
and accessibility. e ndings demonstrated that a well
coordinated transportation environment should be the
primary aim of policy makers in Athens to satisfy pas-
sengers, followed by other quality attributes such as
service frequency and accessibility (Tyrinopoulos, An-
toniou 2008).
Lai and Chen (2011) explored the relationships
between passenger behavioral intentions and the vari-
ous factors aecting them using structural equation
modeling. ey used passenger survey data from the
Kaohsiung Mass Rapid Transit, a newly operating pub-
lic transit system in Taiwan, to test the validity of the
conceptual model proposed in their study. In addition to
the factors recognized by past studies, the present study
addresses the importance of the involvement of the pub-
lic transport service provider on passenger behavioral
intentions. e relationships between service quality,
perceived value, satisfaction, and behavioral intentions
provide important implications for public transit com-
panies. Passenger behavioral intentions and loyalty rely
significantly on passenger satisfaction. Moreover, two
antecedents– service quality and perceived value– must
be improved to enhance passenger satisfaction.
Givoni and Rietveld (2007) found that the qual-
ity and access to a station and personal space on the
train have an important eect on the general usage of
railways. Chou etal. (2011) also utilized a conrmatory
passenger behavior model to appraise the quality and
performance of high-speed rail services. eir empiri-
cal study concludes that the service quality indicators
‘access to a station’ and ‘personal space on a train’ need
to be addressed as a top priority to improve customer
satisfaction and corporate prots (Chou etal. 2011).
Ji and Gao (2010) developed a method to evalu-
ate the eciency of urban structure focusing on public
transportation systems. Taking Beijing as an example,
the impact of selected factors including service attrib-
utes and passenger characteristics such as demographics
and personal characteristics on satisfaction of passen-
gers were analyzed using a multilevel logistic regression
model to identify signicant factors of satisfaction. It was
found that the number of bus stops within a distance of
800 m, access to the main places of the city by one ride
on public transportation as well as passengers’ socio-
economic characteristics significantly aected residents’
satisfaction with public transportation services. Zhang
and Gao (2008) also presented an empirical analysis of
the trac problems in Beijing using a large-scale survey
that measured the residents’ degree of satisfaction with
the trac environment. Spatial dierentiations were
identied across social groups. is study highlights
that residents’ satisfaction is a comprehensive index,
reflecting the qualities of physical space and transporta-
tion service as well as the impact of personal attributes
and preferences. Table 2 summarizes the studies analyz-
ing passenger satisfaction according to the components
considered, the mode of transport examined and the
data analysis methods used.
4Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

Ta bl e 2 s ho w s t ha t a c om m on n d in g o f t he m a -
jority of the studies is that both the service quality and
perceived value have a signicant impact on passenger
satisfaction, and hence, must be addressed to enhance
passenger satisfaction. Attribute-based items found to be
signicant components of customer satisfaction in the
transport service where physical conditions of a station
and the transportation vehicle, availability, safety and re-
liability of the service, perceived price and accessibility
to the station. In the previous studies, the multivariate
statistical analysis was generally used to determine the
factors aecting passenger satisfaction and to analyse
dierences among passengers.
e majority of studies on passenger satisfaction
were conducted in cities/countries in which the eec-
tiveness of the public transportation is crucial because
of the high population. ese studies provide important
insights for policy makers and decision makers in the
related countries, facilitating the development of general
policies and strategies. However, the passenger market
could be analyzed in more detail by dividing into dif-
ferent groups according to the satisfaction level. is
would enable decision makers to more eectively tailor
policies and strategies to each type of passenger group
in the market.
e literature lacks a systematic, comprehensive
research approach to analyze passenger satisfaction
in maritime transportation. is is especially true for
Tu rk e y i n g en e r al , a n d Is t a nb u l i n p ar t i c ul a r, f r om t h e
perspective of a customer satisfaction framework. As
one of the most crowded cities in Europe, Istanbul is
an attractive research setting for analyzing customer sat-
isfaction of public services. For this reason, this study
aims to analyze satisfaction of passengers in maritime
transportation in Istanbul employing satisfaction-based
segmentation. In summary, the general objectives of this
study are to:
–divide the passengers into dierent segments ac-
cording to their satisfaction levels with the dif-
ferent attributes of the maritime transportation
service;
Table 2. Summary of literature review on passenger satisfaction
Study Aim Independent variables Mode of
transport
Data analysis
methods
Park
(2007)
determining
passengers’
perception that
inuence their
buying behaviour
–in-flight service;
–reservation-related service;
–airport service;
–overall service reliability;
–employee service;
–flight availability;
–perceived price;
–passenger satisfaction;
–airline image
airlines ANOVA
Tyrinopoulos,
Antoniou
(2008)
determining
passengers’
perceptions
of transit
performance
–on-time performance;
–average waiting time at terminals and stops;
–vehicle load;
–average route speed;
–conditions at terminals and stops;
–safety information provision, accessibility;
–service frequency;
–etc. (22 attributes in total)
bus, trolley
bus and
rail/metro
factor
analysis and
ordered logit
model
Lai, Chen
(2011)
understanding
behavioral
intentions of
public transit
passengers
–service quality;
–perceived value;
–satisfaction;
–involvement
railway structural
equation
modeling
Givoni,
Rietveld
(2007)
determining
passengers’
overall
satisfaction
with using train
–riding comfort related items;
–tangible facilities related items;
–access convenience related items;
–riding security related items;
–satisfaction related items (assessed through reasonable
price, ticket and service system, and overall satisfaction);
–demographic characteristics of customers;
–etc. (16 attributes in total)
railway regression
Chou etal.
(2011)
passenger
satisfaction index
calculation
–service quality;
–corporate image
railway structural
equation
modeling
Ji, Gao
(2010)
analysing
customers’
satisfaction
with public
transportation
–the number of bus stops within the vicinity of x meters;
–the accessibility to the main places of the city through
one ride by public transportation;
–socio-economic attributes;
–demographic characteristics of customers
bus multilevel
logistic
regression
model
Transport. Article in press 5
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

–determine the prole of each segment based on
demographics, socioeconomic characteristics of
passengers and perceived importance of service
attributes;
–prepare a guideline for maritime transportation
companies to help them develop dierent strate-
gies for passengers in dierent segments and to
give some insights to governmental bodies for
developing eective transportation policies.
3. Methodology
3.1. Data Collection Method and Instruments
is study is based on descriptive research through a
cross-sectional quantitative study on data collected
from maritime passengers using face-to-face interviews
through questionnaires. ree main groups of variables
are included in the study:
–the perceived importance of maritime transpor-
tation service attributes acting as dimensions of
satisfaction;
–satisfaction levels of the components of the mari-
time transport service;
–demographic and usage characteristics of pas-
sengers.
e rst two groups of variables were measured
based on statements rated using a ve-point Likert scale.
e survey aims to identify the level of customer satis-
faction on the dierent dimensions of maritime trans-
portation, their perceived level of importance as well as
the demographic characteristics of the customers.
e surveys were conducted with foot passengers
and included 63 items derived from both previous stud-
ies in the literature and the ndings of past studies con-
ducted by SSC. First, passengers were asked to state the
level of perceived importance of each dimension. ey
were then asked to give their level of satisfaction for each
dimension. In addition to these dimensions, the survey
included questions about demographics (age, gender,
educational level, and traveling frequency).
3.2. Sampling
3.2.1. Sampling Population
Although SSC serves both foot and vehicle passengers,
this study only focuses on foot passengers because of
their high share of the total number of maritime pas-
sengers. e survey was conducted through face-to-face
interviews over a three-week period. In this study, 261
interviews were carried out in the period 9–18 October
2010 (with a 95% condence level, ± 2.00% error margin
and 0.5 distribution rate). e passengers in the sam-
ple were chosen using a systematic sampling method,
which is a probability sampling and has the potential
to create a sample that is almost identical in quality to
sample created from simple random sampling. At the
predetermined time, intervals during ten days, based on
the skip interval calculated, every twentieth passenger
entering to the terminal was interviewed. Table 3 pre-
sents the prole of the sample in terms of demographic
and behavioral characteristics.
As can be seen from Table 3, the majority of pas-
sengers are males aged 30–34. Additionally, 39.08% of
the customers are high school graduates and there are no
uneducated passengers. A high share of the total, 22.99%
of passengers, travel daily by maritime transportation.
Table 3. Distribution of demographic data
of interviewed passengers
Age [%]
0–24
25–29
30–34
35–39
40–44
45–49
50–54
>55
15.32
18.39
21.46
15.33
12.26
7.66
5.36
4.22
Gender [%]
female
male
19.92
80.08
Education Level [%]
primary school graduate
secondary school graduate
high school graduate
university graduate and higher educated
10.73
13.79
39.08
36.40
Travel frequency [%]
every day
2–3 times a week
once a week
once every two or three weeks
once a month
infrequently
22.99
18.39
20.31
19.92
7.66
10.72
3.2.2. Underlying Dimensions of Satisfaction
e survey includes 63 items representing satisfaction
with the components of the maritime transport service,
that is, service attributes. e perceived satisfaction with
each attribute is measured on a ve-point scale. As the
most eective method to reduce large numbers of items
to smaller sets of underlying factor analysis, is used to
group the items (Ambrož, Lotrič 2009). Cumulative
loading is the variance explained by the factor and the
previous factors. Notice that Sat_Factor 1 accounts for
23.845% of the variance, Sat_Factor 1 and 2 account
for 28.706% of the variance, and so on (Kim, Mueller
1978). e total variance explained by the factor analy-
sis is 73.325%. Six factors with loadings greater than 0.5
were generated by the analysis and checked with KMO
(Kaiser–Meyer–Olkin) and Bartlett’s test of signicance
(Kim, Mueller 1978). e interpretation of the factors
and their variances are given in the tables. e factors
derived from the analysis are as follows:
–Satisfaction Factor 1– Supportiveness and
guidance of terminal personnel and physical
facilities: As can be seen from Table 4, this fac-
tor includes attributes related to the attitude of
the terminal personnel, informativeness of an-
nouncements and orientation signs, and condi-
tions at the terminal. Attitude of other personnel
working at the terminal has the highest loading
for this factor.
6Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

–Satisfaction Factor 2– Adequacy and accessi-
bility of information through technology-based
support systems: As is shown in Table 5, this
factor includes items about the website and call
center. Adequacy of the information provided by
the call center’s automatic answering system has
the highest loading for this factor.
–Satisfaction Factor 3– Quality and comfort of
physical facilities: is is composed of attributes
related to comfort of the passenger halls and seats
in the ship, physical conditions in the ship’s pas-
senger halls, transportation safety and security,
and promptness of ship departure times. Comfort
in ship’s passenger halls has the highest loading for
this factor (Table 6).
–Satisfaction Factor 4– Availability and quality
of information materials obtained through tra-
ditional (written and verbal) sources: is relates
Table 4. Satisfaction Factor 1 factor loadings
Sat_Factor 1: Supportiveness and guidance of terminal personnel and physical facilities Factor loading
1.1. attitude of other personnel working at terminal
1.2. adequacy of information given by passenger terminal sta
1.3. general cleanliness of passenger terminal
1.4. adequacy of orientation signs for vehicle waiting area
1.5. adequacy and clarity of announcements at terminal
1.6. general maintenance of passenger terminal building and environmental design
1.7. attitude of passenger terminal security personnel
1.8. cleanliness of terminal buets
1.9. attitude of box oce sta
1.10. product variety and quality of terminal buets
1.11. processing speed at box Oce
1.12. attitude of terminal buet sta
1.13. ease of accesss to ship from waiting room
1.14. comfort of terminal (waiting rooms, buet, telephone, internet, atmosphere, etc.)
1.15. ease of transport to terminal and transfer to other vehicles
1.16. aordability of terminal buet
1.17. cleanliness of toilets at passenger terminal (hygiene, equipment etc.).
1.18. aordability of ticket prices
1.19. safety and security of ship landing and ship boarding
1.20. image quality of terminal TV
1.21. content of TV broadcasts at terminal
0.799
0.780
0.770
0.763
0.760
0.756
0.756
0.754
0.753
0.751
0.749
0.726
0.720
0.715
0.710
0.710
0.699
0.684
0.671
0.642
0.509
Cumulative loading [%] 23.845
Table 5. Satisfaction Factor 2 factor loadings
Sat_Factor 2: Adequacy and accessibility of information through technology support systems Factor loading
2.1. adequacy of information given by call center automatic answering system
2.2. adequacy of information on website
2.3. access to call center customer representative
2.4. adequacy of information given by call center representative
2.5. attitude and comportment of call center customer representative
2.6. up-to-dateness of website
2.7. facility for using website
2.8. facility for using call center automatic answering system
2.9. internet access to website
2.10. access to terminal’s authorized sta when needed
0.848
0.835
0.815
0.814
0.801
0.792
0.756
0.744
0.682
0.658
Cumulative loading [%] 38.706
Table 6. Satisfaction Factor 3 factor loadings
Sat_Factor 3: Quality and comfort of physical facilities Factor loading
3.1. comfort of seats in ship’s passenger halls
3.2. comfort in ship’s passenger halls
3.3. air conditioning and ventilation of ship’s passenger halls
3.4. lighting in ship’s passenger halls
3.5. general maintenance of ship
3.6. general cleanliness in ship’s passenger halls
3.7. adequacy and clarity of annoncements in ship
3.8. transportation safety and security
3.9. adequacy of warning/orientation signs in ship’s passenger halls
3.10. promptness of ship departure times
0.795
0.789
0.740
0.719
0.688
0.664
0.646
0.625
0.623
0.604
Cumulative loading [%] 52.475
Transport. Article in press 7
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

to the availability of SSC’s magazine, adequacy of
information provided and clarity of tari book-
lets. e item availability of SSC’s magazine has
the highest loading for this factor (Table 7).
–Satisfaction Factor 5– Availability and conveni-
ence of transportation: is reects frequency,
promptness of ship arrival times and convenience
of transportation times. Regulation of transporta-
tion times in accordance with customers’ expecta-
tions h as th e h ig he s t l oa di ng fo r t hi s f a ct or (Ta bl e 8 ).
–Satisfaction Factor 6– Availability of new lines
and informative mass communication: As can be
seen from Table 9, this factor relates to the avail-
ability of new lines and information dissemina-
tion. Opening new lines by SSC has the highest
loading for this factor.
3.3. Satisfaction-Based Segmentation
Due to the fact that the sample size of the survey is
relatively small, we used Ward’s hierarchical technique
method in order to get clusters of approximately equal
size. Cluster analysis with Ward’s hierarchical technique
using squared Euclidean distances (Hair etal. 1995)
was employed to identify segments of customers ac-
cording to their loading on each of the six satisfaction
factors. Fig.3 shows a dendogram of the method: 261
respondents were assigned to six segments, Segments 1
to 6, comprising 114, 18, 18, 57, 12 and 42 respondents,
respectively.
Ta bl e 1 0 s ho w s t hat all the factors were found to
dier signicantly among the segments at the p < 0.05
signicance level according to the results of ANOVA,
which was used to examine which factors differed
among the segments (Hair etal. 1995). e analysis dif-
ferentiated the following six market segments:
–Segment 1– Passengers satised with continu-
ous support and communication: is segment
consists of customers highly satised with the
continuous support and communication activi-
ties of SSC. ese customers seem to expect and
are satised with a high level of service including
availability and content of magazines, and ade-
quacy of the information about new and canceled
trips from the service provider.
–Segment 2– Passengers satised with the avail-
ability of information through technology-based
support systems: is segment includes custom-
ers mainly satised with the technology-based
support service. To satisfy these customers a
technology component should be included in
SSC’s customer services. Although these pas-
sengers are not satised with communication
through traditional written and verbal sources,
convenience of transportation and availability of
new lines, they are satised with the primary ser-
vice, namely, the transportation service.
–Segment 3– Passengers satised with quality of
core service and comfort: is group consists of
customers whose perceived level of satisfaction is
Table 7. Satisfaction Factor 4 factor loadings
Sat_Factor 4: Availability and quality of information materials obtained through
traditional written and verbal sources Factor loading
4.1. availability of SSC’s magazine
4.2. content of SSC’s magazine
4.3. adequacy of information about new and cancelled trips
4.4. adequacy of information given by ship’s sta
4.5. adequacy information and clarity of tari booklets
4.6. access to authorized ship sta when needed
4.7. attitude of ship sta
0.747
0.648
0.641
0.582
0.579
0.574
0.514
Cumulative loading [%] 61.011
Table 8. Satisfaction Factor 5 factor loadings
Sat_Factor 5: Availability and convenience of transportation Factor loading
5.1. regulation of transportation times in accordance with customer’s expectations
5.2. convenience of transportation time
5.3. frequency of transportation
5.4. putting on a new transportation if necessary
5.5. noise level during transportation
5.6. promptness of ship arrival time
0.703
0.690
0.668
0.569
0.542
0.534
Cumulative loading [%] 68.816
Table 9. Satisfaction Factor 6 factor loadings
Sat_Factor 6: Availability of new lines and of informative mass communication Factor loading
6.1. opening new lines by SSC
6.2. advertising of SSC’S new lines and services
6.3. adequacy of SSC’s advertising about cultural and artistic activities
0.632
0.604
0.590
Cumulative loading [%] 73.325
8Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

based mainly on the quality of the primary ser-
vice, including safety, security and timeliness of
the transportation service. ey are also satised
with the complementary services such as comfort
of the passenger halls and seats in the ship, and
the physical atmosphere of the ship. erefore,
they do not perceive maritime transportation
solely as a transportation service but rather as an
augmented service with complementary facilities.
On the other hand, passengers in this segment
are not satised with the traditional or technolo-
gy-supported customer service system.
–Segment 4– Information-prone passengers:
ese are the customers whose perceived level
of satisfaction mainly results from the availabil-
ity and quality of information from written and
personal sources. e passengers in this segment
could be satised by increasing the quality and
availability of information-related attributes, for
example, being regularly informed about travel
frequencies and times. A continuous ow of
information between them and the company is
crucial to maintain satisfaction level. Another
nding is that the passengers in this segment are
not generally satised with other attributes of the
service.
–Segment 5– Continuous guidance-focused pas-
sengers: ese are customers whose perceived
level of satisfaction is mainly based on the sup-
portiveness and guidance of the terminal person-
nel and physical facilities. Although, this group is
satised with the quality of mass communication
and availability of new lines, they are unsatised
with the primary service.
–Segment 6– Passengers satised with availabili-
ty of technology and mass communication based
information: is segment consists of passengers
who are satised with SSC’s level of technological
responsiveness including newly opened lines and
the advertisements about them as well as SSC’s
cultural and artistic activities.
3.3.1. Prole of Segments According to Perceived
Importance of Service Attributes
For the third objective of this study– demographic and
usage characteristics of passengers– dierences between
segments in terms of the perceived importance of ser-
vice attributes are also analyzed. Before undertaking this
analysis, the items measuring the perceived importance
of service attributes were analyzed by factor analysis to
summarize and identify the underlying dimensions, and
to describe the prole of each segment more precisely.
e analysis identied six factors with 70.690% of the
total variance explained. e factors are dened briey
as follows:
–Importance Factor 1– Importance of quality of
physical environment of terminal and aord-
ability of the provided services: As shown in Ta-
ble 11, this factor comprises attributes related to
the cleanliness of the terminal, the attitude of the
Fig.3. Cluster analysis dendogram built using Ward linkage
72
200
191
227
131
179
178
43
208
104
76
236
25
94
206
69
113
167
136
36
203
238
4
96
229
226
53
59
146
213
0510 15 20 25
Rescaled d!stance cluster comb!ne
Table 10. Analysis of satisfaction factors among the segments
Segment1Segment 2 Segment 3 Segment 4 Segment 5 Segment 6 Signicance
Sat_Factor 1 0.370 0.141 0.049 –0.931 1.915 –0.369 0.000
Sat_Factor 2 0.284 0.411 –1.954 –0.276 –0.507 0.410 0.000
Sat_Factor 3 0.280 0.215 0.870 –0.320 –2.264 –0.141 0.000
Sat_Factor 4 0.392 –0.071 –0.368 0.406 –0.068 –1.409 0.000
Sat_Factor 5 0.190 –1.026 0.497 –0.396 –0.240 0.318 0.000
Sat_Factor 6 0.087 –1.996 –0.160 0.068 0.643 0.411 0.000
Transport. Article in press 9
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

terminal sta and aordability of tickets. General
cleanliness of the terminal has the highest loading
for this factor.
–Importance Factor 2– Importance of availabili-
ty and convenience of transportation: is factor
(Table 12) reects the promptness of ship arrival
times, convenience of transportation time, pas-
sage frequency and security. Promptness of ship
arrival times and convenience of transportation
times have the highest loadings for this factor.
–Importance Factor 3– Importance of accessi-
bility and adequacy of technology-based sup-
port services: As shown in Table 13, this factor
includes items about the website and call center.
Adequacy of the information on website has the
highest loading for this factor.
–Importance Factor 4– Importance of quality
of core service and of related physical facili-
ties: is comprises attributes related to transfer
(adequacy of orientations in the ship, comfort of
ship’s passenger halls, promptness of ship depar-
ture times and physical conditions in the ship).
Adequacy of warning/orientation signs in ship’s
passenger halls has the highest loading for this
factor (Table 14).
–Importance Factor 5– Importance of responsive-
ness to customer needs: As shown in Table 15,
this factor refers to responsiveness to passenger
wishes and complaints, opening new lines, and
advertising new lines and cultural activities. Giv-
ing satisfactory answers to wishes and complaints
has the highest loading for this factor.
–Importance Factor 6– Importance of availabil-
ity and quality of the written and visual com-
munication materials: is factor includes the
availability and content of magazines, image
quality of the ship TV and adequacy of informa-
tion and clarity of tari booklets. Availability of
SSC’s magazine has the highest loading for this
factor (Table 16).
Table 11. Importance Factor 1 factor loadings
Imp_Factor 1: Importance of quality of physical environment of terminal and aordability
of provided services Factor loading
1.1. general cleanliness of passenger terminal
1.2. attitude of terminal buet sta
1.3. cleanliness of terminal buets
1.4. cleanliness of toilets at passenger terminal (hygiene, equipment etc.).
1.5. attitude of other personnel working at terminal
1.6. aordability of terminal buet
1.7. comfort of terminal (waiting rooms, buet, telephone, internet, atmosphere, etc.).
1.8. aordability of ticket prices
1.9. product variety and quality of terminal buets
1.10. ease of accesss to ship from waiting room
1.11. adequacy and clarity of annoncements at terminal
1.12. adequacy of information supplied by passenger terminal sta
1.13. attitude of box oce sta
1.14. adequacy of orientation signs for vehicle waiting area
1.15. attitude of passenger terminal security personnel
1.16. general maintenance of passenger terminal building and environmental design
1.17. processing speed at box Oce
1.18. content of TV broadcasts at the terminal
1.19. ease of transport to terminal and transfer to other vehicles
1.20. image quality of terminal TV
1.21. safety and security of landing ship and ship boarding
0.860
0.853
0.838
0.816
0.800
0.785
0.784
0.782
0.776
0.771
0.743
0.738
0.736
0.694
0.693
0.670
0.662
0.630
0.576
0.545
0.527
Cumulative loading [%] 22.289
Table 12. Importance Factor 2 factor loadings
Imp_Factor 2: Importance of availability and convenience of transportation Factor loading
2.1. promptness of ship arrival time
2.2. convenience of transportation time
2.3. putting on a new trip if necessary
2.4. frequency of transportation
2.5. regulation of transportation times in accordance with customers’ expectations
2.6. adequacy of information about new and cancelled transportation
2.7. transportation safety and security
2.8. access to authorized ship sta when needed
2.9. noise level during transportation
2.10. attitude and comportment of ship sta
2.11. adequancy information of ship sta
0.779
0.777
0.767
0.765
0.750
0.655
0.580
0.569
0.554
0.529
0.527
Cumulative loading [%] 35.481
10 Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

Table 13. Importance Factor 3 factor loadings
Imp_Factor 3: Importance of accessibility and adequacy of technology support services Factor loading
3.1. adequacy of information on website
3.2. facility for using website
3.3. up-to-dateness of website
3.4. adequacy of information supplied by call center automatic answering system
3.5. access to call center customer representative
3.6. adequacy of information supplied by call center representative
3.7. ease of using call center automatic answering system
3.8. attitude of call center customer representative
3.9. internet access to website
3.10. access to terminal’s authorized sta when needed
0.853
0.850
0.845
0.815
0.814
0.803
0.801
0.794
0.779
0.669
Cumulative loadings [%] 48.271
Table 14. Importance Factor 4 factor loadings
Imp_Factor 4: Importance of quality of primary service and related physical facilities Factor loading
4.1. adequacy of warning/orientation signs in ship’s passenger halls
4.2. comfort in ship’s passenger halls
4.3. adequacy and clarity of annoncements in ship
4.5. promptness of ship departure times
4.6. comfort of seats in ship’s passenger halls
4.7. general maintenance of ship
4.8. lighting in ship’s passenger halls
4.9. air conditioner and ventilation in ship’s passenger halls
4.10. general cleanliness in ship’s passenger halls
0.770
0.67
0.652
0.647
0.646
0.588
0.587
0.536
0.512
Cumulative loading [%] 57.226
Table 15. Importance Factor 5 factor loadings
Imp_Factor 5: Importance of responsiveness to customer needs Factor loading
5.1. giving satisfactory answers to wishes and complaints
5.2. opening new lines
5.3. access to channels which will forward wishes and complaints from customers
5.4. advertising SSC’s new lines and services
5.5. timely solution of wishes and complaints
5.6. adequacy of SSC’s advertising about cultural and artistic activities
0.744
0.719
0.715
0.709
0.687
0.602
Cumulative loading [%] 64.484
Table 16. Importance Factor 6 factor loadings
Imp_Factor 6: Importance of availability and quality of written and visual communication materials Factor loading
6.1. availability of SSC’s magazine 0.806
6.2. content of SSC’s magazine 0.770
6.3. image quality of ship TV 0.535
6.4. adequacy of information and clarity of tari booklets 0.529
Cumulative loading [%] 70.690
e dierences and similarities among the seg-
ments in terms of the six importance factors derived
from the factor analysis are also analyzed using ANOVA.
Table 17 indicates that here are signicant dierences
at the 0.05 signicance level for all importance factors
in terms of perceived importance except for Importance
Factor4 (importance of quality of primary service and
related physical facities) and Importance Factor 5 (impor-
tance of responsiveness to customer needs). Since the clus-
ter analysis was generated based on the factors derived
from the satisfaction of service attributes, this result
conrms that the segmentation is also successful in dis-
criminating between the passengers on the basis of the
perceived level of importance of the service attributes.
As the Schee test shows, Segment 1 (passengers
satised with continous support and communication)
perceives importance of quality of physical environment
in terminal and aordability of provided services (Imp_
Factor 1) signicantly more important than Segment 4
(information-prone passengers).
Segment 3 (passengers satised with quality of
primary service and comfort) perceives importance of
availability and convenience of transportation (Imp_Fac-
tor 2) as more important than Segment 5 (continuous
Transport. Article in press 11
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

guidance-focused passengers). Since Segment 3 includes
passengers satised with quality of the primary service,
both the perceived satisfaction and importance levels are
in parallel.
On the other hand, perception of importance of
accessibility and adequacy of technology support services
(Imp_Factor 3) diers between Segment 1 (passengers
satised with continuous support and communication),
Segment 3 (passengers satised with quality of primary
service and comfort), Segment 5 (continuous guidance
focused passengers) and Segment 6 (passengers satised
with availability of technology and mass communication
based information). e nding that the levels of per-
ceived importance of accessibility and adequacy of tech-
nology support services of Segments 6 and 1 are greater
than that of Segments 3 and 5 is a positive nding for
the SSC. is shows that passengers who give more im-
portance to this factor are also satised in terms of the
availability of technology, mass communication-based
information and continuous support and communica-
tion.
Segment 1 (passengers satised with continuous
support and communication) perceives importance of
availability and quality of written and visual communi-
cation materials (Imp_Factor 6) as being more important
than Segment 6 (passengers satised with availability of
technology and mass communication-based informa-
tion). Since Segment 1 passengers give high importance
to availability and quality of written and visual com-
munication materials, and are satised with the level of
continuous support and communication, SSC can be
considered successful in satisfying these passengers in
terms of both factors.
3.3.2. Prole of Segments in Terms of Demographics
and Usage-Related Characteristics
Chi-square analysis (Hair etal. 1995) was conducted to
determine the prole of each segment in terms of age,
gender, educational level and travel frequency. e re-
sults of the analysis show that education level (Pearson
chi-square = 37.972, p= 0.000), age (Pearson chi-square:
24.227, p= 0.007) and travel frequency (Pearson chi-
square= 21.929, p= 0.015, at the p < 0.05 signicance
level) are signicantly related to the segment type. How-
ever, there is no signicant relationship between gen-
der and market segment (Pearson chi-square= 10.095,
p= 0.073, at the p < 0.05 signicance level). is may
indicate that the service provided by the SSC perfectly
covers all the common satisfaction attributes related to
dierent gender groups.
Ta bl e 1 8 s ho ws t ha t Segment 1 (passengers satis-
ed with continuous support and communication) has
the highest percentages of passengers aged 30–50, high
school graduates and people who travel less than three
times a week. Most of the people in Segment 2 (pas-
sengers satised with the availability of information
through technology-based support systems) are aged
under 30, have at least a bachelor’s degree and travel
every day. Informativeness is important for people who
frequently travel. erefore, we can infer that the com-
Table 17. ANOVA results for segments and importance factors (average factor loadings)
Segment 1 Segment 2 Segment 3 Segment 4 Segment 5 Segment 6 Signicance
Imp_Factor 1 0.2007922 0.3242883 –0.2190506 –0.48551316 0.52860917 –0.0726521 0.000
Imp_Factor 2 0.0895268 0.174681 0.5093806 –0.16572807 –0.75313 –0.1480693 0.003
Imp_Factor 3 0.207424 –0.36469 –0.82304 –0.0699093 –0.773956 0.279469 0.000
Imp_Factor 4 0.170711 –0.26862 –0.08029 –0.1959728 –0.019577 0.00488 0.188
Imp_Factor 5 0.165625 –0.5149 –0.19478 –0.1111416 –0.135824 0.066324 0.071
Imp_Factor 6 0.1925669 –0.2428822 –0.6918253 0.178768246 0.22310583 –0.4622993 0.000
Table 18. Cluster analysis of demographic characteristics and travel behaviour
Cluster [%]
123456
Age
<30
30–50
>50
29.80
59.60
10.50
66.70
33.30
0.00
55.60
27.80
16.70
22.80
68.40
8.80
25.00
50.00
25.00
38.10
57.10
4.80
Education level
<highschool graduate
highschool graduate
>highschool graduate
33.30
42.10
24.60
5.60
22.20
72.20
16.70
33.30
50.00
19.30
50.90
29.80
41.70
41.70
16.70
14.30
23.80
61.90
Travel frequency
everyday
at most 3 times a week
less
16.70
36.80
46.50
38.90
33.30
27.80
38.90
33.30
27.80
17.50
42.10
40.40
58.30
41.70
0.00
23.80
42.90
33.30
12 Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

pany is successful in this area. e prole of the major-
ity of the passengers in Segment 3 (passengers satised
with quality of core service and comfort) are aged under
30, have at least a university graduate and are frequent
travelers. In Segment 4 (information-prone passengers),
the highest values are for those aged 30–50, high school
graduates and not very frequent travelers. Continuous
guidance-focused passengers (Segment 5) include those
aged 30–50, mostly high school graduates and frequent
travelers. Since they frequently travel it is expected they
are information-prone. ose aged 30–50, holding uni-
versity degrees and traveling at most three times a week
have the highest percentages in Segment 6 (passengers
satised with availability of technology and mass com-
munication based information).
3.4. Results
e results of the present study have shown that the
market can be divided into six segments according to
passenger satisfaction levels: Segment 1 (passengers sat-
ised with continuous support and communication);
Segment2 (passengers satised with availability of infor-
mation through technology-based support systems); Seg-
ment 3 (passengers satised with quality of core service
and comfort); Segment 4 (information-prone passen-
gers); Segment 5 (continuous guidance focused passen-
gers), and Segment 6 (passengers satised with availabil-
ity of technology and mass communication). e largest
segment is Segment 1 (114 of 261 passengers), followed
by Segment 4 (57 passengers) and Segment 6 (42 passen-
gers). e smallest segment is Segment 5 (12 passengers).
Due to the growing importance of information dis-
semination and customer communication, SSC seems
to focus on information-based strategies to satisfy the
majority of its customers. In recent years, SSC has been
using technology as an important medium to deliver
information on its services. Consequently, a high num-
ber of passengers are satised with SSC in terms of the
availability of technology and mass communication-
based information. Hence, the SSC was able to increase
its passenger numbers satised with these attributes, that
is, Segments 1, 4 and 6. However, Segment 5 has a limited
number of customers satised with the support and guid-
ance of the terminal personnel and physical facilities.
is shows that SSC, as a service provider, failed to de-
velop eective strategies about two important marketing
mix elements, namely, people and physical environment.
A noteworthy fact about Segment 4 (information-
prone passengers; 57 passengers), the second largest af-
ter Segment 1 (114 passengers). Is those passengers are
only satised with the availability and quality of infor-
mation from written and personal sources, nding the
other services insucient? Since this segment includes
a high number of passengers, the SSC needs to create
strategies to increase their satisfaction with the other at-
tributes.
e smaller segments (Segments 2, 3 and 5) dier
from the larger segments according to the perceived im-
portances of some attributes. However, they also dier
from each other according to other attributes. For in-
stance, Segment 3 (passengers satised with the quality
of primary service and comfort) gives more importance
to the availability and convenience of transportation than
Segment 5 (continuous guidance-focused passengers).
is implies that it is necessary to develop strategies
to satisfy the passengers in Segment 3 both in terms of
availability and convenience of transportation and the
quality of the primary service and comfort.
Segment 1 (passengers satised with continuous
support and communication) gives more importance to
the quality of the physical environment of terminal and
aordability of provided services than Segment 4 (infor-
mation-prone passengers). is indicates that satisfying
information-prone customers do not depend mostly
on the price or physical environment of the primary
service.
Chi-square analysis conducted to determine the
prole of each segment in terms of demographic and
usage-related characteristics shows that, age, education
level and travel frequency are signicantly related to the
types of market segments. erefore, while developing
strategies to increase the satisfaction level of customers,
the SSC need not consider gender proles of its passen-
gers but should consider their age, education level, and
travel frequency.
Our ndings conrm ndings of previous studies:
(1) as underlined by Lai and Chen (2011), the relation-
ships between service quality, perceived value, satisfac-
tion, and behavioral intentions suggest important impli-
cations for maritime service transportation; (2) in paral-
lel with the ndings of Ji and Gao (2010), perceptions
among passengers dier according to socio-economic
group; and (3) supporting the ndings of Zhang and
Gao (2008), the qualities of physical space and transpor-
tation service as well as the impact of personal attributes
and preferences are signicant components of customer
satisfaction in transport services. In other words, service
quality, its perceived value and customer satisfaction are
closely-related components, and customer satisfaction
and the priorities given to dierent customer service
levels vary according to socio-economic or demographic
dierences (Tarigan etal. 2014).
Conclusions and Further Suggestions
Due to its economy and environmentally friendly na-
ture, maritime public transportation is attracting more
and more attention and interest worldwide. Increasing
the number of customers as well as their travel frequen-
cy is one way of stimulating demand for maritime pub-
lic transportation. As customer satisfaction increases,
both the usage and travel frequency will increase. us,
developing strategies to increase customer satisfaction
should facilitate expansion of the market share of mari-
time public transportation.
In the present study, we selected Istanbul, which
has the dominant share of domestic maritime passenger
transportation in Turkey, as a case study, and proposed
dierent strategies for dierent groups of maritime
transportation passengers based on a survey analysis,
Transport. Article in press 13
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

which revealed the state of passenger satisfaction with
maritime transportation and its determinants.
Our ndings also conrm that passengers’ percep-
tion of service attributes– such as service quality, value
and importance – directly inuences their level of sat-
isfaction. Moreover, certain demographic and personal
attributes such as socio-economic and demographic fac-
tors are also found to impact level of satisfaction. How-
ever, the majority of studies on passenger satisfaction
focus on a limited standard set of service attributes such
as station and transportation vehicle physical conditions,
availability, service safety and reliability, perceived price,
and accessibility, and satisfaction level of passengers on
each dimension. In contrast to previous studies in the
literature, this study analyzes the importance of a more
extensive set of service attributes and related levels of
customer satisfaction. We consider that various service
attributes are directly inuencing perceived value of the
service and consequent satisfaction by integrating nd-
ings from a wide range of studies on satisfaction in the
literature. Furthermore, the ndings of this study indi-
cate that maritime passengers can be segmented into dif-
ferent subgroups according to level of satisfaction and
that there are signicant dierences among the dierent
market segments in terms of age, education level and
travel frequency. is infers that not one strategy but a
number of dierent strategies should be implemented
to target the dierent maritime transportation user seg-
ments.
us, the ndings of the present study underline
the fact that satisfaction with maritime transportation
cannot be analyzed in a generalized format nor can a
prescription suitable for all countries be proposed. In
fact, the importance given to factors expected to inu-
ence the satisfaction level of maritime passengers may
vary from country to country as well as among cities
within a single country. erefore, maritime transporta-
tion of each country should be analysed in detail and
guidelines proposed to address the dierent customer
segments.
Although this study gives important and valuable
insights for developing eective strategies to expand the
satisfaction with and usage of maritime transportation
appropriate for each segment, it has some methodologi-
cal limitations and weaknesses. Within this context, as a
part of further research, cluster analysis should be con-
ducted on the levels of importance assigned by custom-
ers to the dierent service attributes. is would provide
more detailed data to decision makers to aid prioritiza-
tion of strategies. In other words, those attributes which
are given primary importance and from which the low-
est level of satisfaction is realized should be the initial
focus of the Turkish Maritime Authorities and maritime
service providers such as SSC.
Finally, this study could be extended to EU cit-
ies attempting to increase the ratio of domestic mari-
time passenger transportation to identify dierences in
priorities of dierent customer groups and to compare
dierences in demographic and socio-economic charac-
teristics of the passengers.
References
Ambrož,M.; Lotrič, B. 2009. Impact of a mediating role of re-
purchase intentions on customer retention, Promet– Traf-
c &Transportation 21(5): 341–348.
http://dx.doi.org/10.7307/ptt.v21i5.249
Anderson, R. E. 1973. Consumer dissatisfaction: the eect of
disconrmed expectancy on perceived product perfor-
mance, Journal of Marketing Research 10(1): 38–44.
http://dx.doi.org/10.2307/3149407
Anderson, E. W.; Fornell,C.; Lehmann, D. R. 1994. Customer
satisfaction, market share, and protability: ndings from
Sweden, Journal of Marketing 58(3): 53–66. http://dx.doi.
org/10.2307/1252310
Anderson,S.; Pearo, L. K.; Widener, S. K. 2008. Drivers of
service satisfaction: linking customer satisfaction to the
service concept and customer characteristics, Journal of
Service Research 10(4): 365–381.
http://dx.doi.org/10.1177/1094670508314575
Anderson, E. W.; Sullivan, M. W. 1993. e antecedents and
consequences of customer satisfaction for rms, Marketing
Science 12(2): 125–143.
http://dx.doi.org/10.1287/mksc.12.2.125
Anderson, R. E.; Swaminathan, S. 2011. Customer satisfaction
and loyalty in e-markets: a PLS path modeling approach,
Journal of Marketing eor y and Practice 19(2): 221–234.
http://dx.doi.org/10.2753/MTP1069-6679190207
Bedi, M. 2010. An integrated framework for service quality,
customer satisfaction and behavioral responses in Indian
banking industry– a comparison of public and private sec-
tor banks, Journal of Services Research 10(1): 170–183.
Birnerova, E. 2007. Assessment of customer satisfaction in
public transport companies, Promet– Trac &Transporta-
tion 19(3): 163–166.
Cardozo, R. N. 1965. An experimental study of customer ef-
fort, expectation, and satisfaction, Journal of Marketing
Research 2(3): 244–249. http://dx.doi.org/10.2307/3150182
Chen, C.-F. 2008. Investigating structural relationships be-
tween service quality, perceived value, satisfaction, and
behavioral intentions for air passengers: evidence from
Tai w an , Transportation Research Part A: Policy and Practice
42(4): 709–717. http://dx.doi.org/10.1016/j.tra.2008.01.007
Chou, J.-S.; Kim,C.; Kuo, Y.-C.; Ou, N.-C. 2011. Deploying
eective service strategy in the operations stage of high-
speed rail, Transportation Research Part E: Logistics and
Transportation Review 47(4): 507–519.
http://dx.doi.org/10.1016/j.tre.2010.12.004
Churchill, G. A.; Surprenant, C. 1982. An investigation into the
determinants of customer satisfaction, Journal of Marketing
Research 19(4): 491–504. http://dx.doi.org/10.2307/3151722
Culiberg,B.; Rojšek, I. 2010. Identifying service quality dimen-
sions as antecedents to customer satisfaction in retail bank-
ing, Economic and Business Review 12(3): 151–166.
De Oña,R.; Eboli,L.; Mazzulla, G. 2014. Key factors aecting
rail service quality in the Northern Italy: a decision tree
approach, Transport 29(1): 75–83.
http://dx.doi.org/10.3846/16484142.2014.898216
Deng,T.; Nelson, J. D. 2012. e perception of bus rapid tran-
sit: a passenger survey from Beijing southern axis BRT
line 1, Transportation Planning and Technology 35(2): 201–
219. http://dx.doi.org/10.1080/03081060.2011.651885
EC. 2011a. Statistical Pocketbook 2011: EU Transport in Fi-
gures. 136 p. Available from Internet: http://ec.europa.
eu/transport/facts-fundings/statistics/pocketbook-2011_
en.htm
14 Y. Ekinci et al. A segmentation based analysis for measuring customer satisfaction in maritime transportation
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015

EC. 2011b. White Paper: Roadmap to a Single European Trans-
port Area– Towards a Competitive and Resource Ecient
Tra ns por t Sys te m. COM(2011) 144 nal. 28.3.2011, Brus-
sels. Available from Internet: http://eur-lex.europa.eu/legal-
content/EN/ALL/?uri=CELEX:52011DC0144
EC. 2001. White Paper: European Transport Policy for 2010:
Time t o De cide . COM(2001) 370 nal. 12.9.2001, Brus-
sels. 124 p. Availabe from Internet: http://ec.europa.eu/
transport/themes/strategies/doc/2001_white_paper/lb_
com_2001_0370_en.pdf
Fellesson,M.; Friman, M. 2008. Perceived satisfaction with
public transport service in nine European cities, Journal of
the Transportation Research Forum 47(3): 93–103.
Givoni,M.; Rietveld, P. 2007. e access journey to the rail-
way station and its role in passengers’ satisfaction with rail
travel, Transport Policy 14(5): 357–365.
http://dx.doi.org/10.1016/j.tranpol.2007.04.004
Gustafsson,A.; Johnson, M. D.; Roos, I. 2005. e eects of
customer satisfaction, relationship commitment dimen-
sions, and triggers on customer retention, Journal of Mar-
keting 69(4): 210–218.
http://dx.doi.org/10.1509/jmkg.2005.69.4.210
Hair, J. F.; Anderson, R. E.; Tatham, R. L.; Black, W. C. 1995.
Multivariate Data Analysis: with Readings. Prentice Hall
College Div. 500 p.
Hallowell, R. 1996. e relationships of customer satisfaction,
customer loyalty, and protability: an empirical study, In-
ternational Journal of Service Industry Management 7(4):
27–42. http://dx.doi.org/10.1108/09564239610129931
IBB. 2011a. Nüfus ve demograk yapı. İstanbul Büyükşehir
Belediyesi [Istanbul Metropolitan Municipality– IBB].
Ava il abl e f rom Int ern et: ht tp: //w ww. ibb .go v.t r/S ITE S/ KS/
TR-TR/0-ISTANBUL-TANITIM/KONUM/Pages/Nufus_
ve_Demograk_Yapi.aspx (in Turkish).
IBB. 2011b. Ekonomi. İstanbul Büyükşehir Belediyesi [Istanbul
Metropolitan Municipality– IBB]. Available from Internet:
http://www.ibb.gov.tr/sites/ks/tr-TR/0-Istanbul-Tanitim/
konum/Pages/Ekonomi.aspx
IETT. 2011. Istanbul Electricity Tramway and Tunnel (IETT)
General Management. Available from Internet: http://www.
iett.gov.tr/en
Jain,S.; Aggarwal,P.; Kumar,P.; Singhal,S.; Sharma, P. 2014.
Identifying public preferences using multi-criteria decision
making for assessing the shi of urban commuters from
private to public transport: a case study of Delhi, Transpor-
tation Research Part F: Trac Psychology and Behaviour 24:
60–70. http://dx.doi.org/10.1016/j.trf.2014.03.007
Jen,W.; Hu, K.-C. 2003. Application of perceived value model
to identify factors aecting passengers’ repurchase inten-
tions on city bus: a case of the Taipei metropolitan area,
Transportation 30(3): 307–327.
http://dx.doi.org/10.1023/A:1023983627092
Ji,J.; Gao, X. 2010. Analysis of people’s satisfaction with pub-
lic transportation in Beijing, Habitat International 34(4):
464–470. http://dx.doi.org/10.1016/j.habitatint.2009.12.003
Kim, J.-O.; Mueller, C. W. 1978. Introduction to Factor Analysis:
What It Is and How to Do It. SAGE Publications, Inc. 80 p.
Lai, W.-T.; Chen, C.-F. 2011. Behavioral intentions of public
transit passengers: the roles of service quality, perceived
value, satisfaction and involvement, Transport Policy 18(2):
318–325. http://dx.doi.org/10.1016/j.tranpol.2010.09.003
Lu, C.-S. 2003. Market segment evaluation and international
distribution centers, Transportation Research Part E: Logis-
tics and Transportation Review 39(1): 49–60.
http://dx.doi.org/10.1016/S1366-5545(02)00022-4
Malik, S. U. 2012. Customer satisfaction, perceived service
quality and mediating role of perceived value, International
Journal of Marketing Studies 4(1): 68–76.
http://dx.doi.org/10.5539/ijms.v4n1p68
Ocak, İ. 2006. Kadıköy–Kartal raylı taşıma sisteminin yeraltına
alınmasının analizi [Analysis for taking Kadıköy–Kartal rail
system to underground], İstanbul Yerbilimleri Dergisi– Is-
tanbul Journal of Earth Sciences 19(1): 77–89. (in Turkish).
Olawole, M. O.; Aloba, O. 2014. Mobility characteristics of the
elderly and their associated level of satisfaction with trans-
port services in Osogbo, Southwestern Nigeria, Transport
Policy 35: 105–116.
http://dx.doi.org/10.1016/j.tranpol.2014.05.018
Oliver, R. L. 1980. A cognitive model of the antecedents and
consequences of satisfaction decisions, Journal of Marketing
Research 17(4): 460–469. http://dx.doi.org/10.2307/3150499
Oliver, R. L. 1999. Whence consumer loyalty?, Journal of Mar-
keting 63: 33–44. http://dx.doi.org/10.2307/1252099
Olshavsky, R. W.; Miller, J. A. 1972. Consumer expectations,
product performance, and perceived product quality, Jour-
nal of Marketing Research 9(1): 19–21.
http://dx.doi.org/10.2307/3149600
Park, J.-W. 2007. Passenger perceptions of service quality: Ko-
rean and Australian case studies, Journal of Air Transport
Management 13(4): 238–242.
http://dx.doi.org/10.1016/j.jairtraman.2007.04.002
Petrick, J. F. 2004. e roles of quality, value, and satisfaction in
predicting cruise passengers’ behavioral intentions, Journal
of Travel Research 42(4): 397–407.
http://dx.doi.org/10.1177/0047287504263037
Pfa, A. B. 1972. An index of consumer satisfaction, in Pro-
ceedings of the ird Annual Conference of the Association
for Consumer Research, 3–5 November 1972, Chicago, IL,
713–737.
POAS. 2011. OMV Petrol Osi A.S. Available from Internet:
http://gm.poas.com.tr/POASFIYAT/Fiyatlar.aspx?u=guest
(in Turkish).
Reichheld, F. F. 2001. e Loyalty Eect: the Hidden Force be-
hind Growth, Prots, and Lasting Value. Harvard Business
School Press. 352 p.
Tar igan, A. K. M.; Susilo, Y. O.; Joewono, T. B. 2014. Segmenta-
tion of paratransit users based on service quality and travel
behaviour in Bandung, Indonesia, Transportation Planning
and Technology 37(2): 200–218.
http://dx.doi.org/10.1080/03081060.2013.870792
Tat a w, D. B .; B a za rg a n- He j az i,S.; James, F. W. 2011. Health
Services utilization, satisfaction, and attachment to a regu-
lar source of care among participants in an urban health
provider alliance, Journal of Health and Human Services
Administration 34(1): 109–141.
Tyrinopoulos,Y.; Antoniou, C. 2008. Public transit user satis-
faction: variability and policy implications, Tran sp or t Pol ic y
15(4): 260–272.
http://dx.doi.org/10.1016/j.tranpol.2008.06.002
Valaskova,M.; Križanova, A. 2008. e passenger satisfaction
survey in the regional integrated public transport system,
Promet– Trac &Transportation 20(6): 401–404.
Williams,P.; Naumann, E. 2011. Customer satisfaction and
business performance: a rm‐level analysis, Journal of Ser-
vices Marketing 25(1): 20–32.
http://dx.doi.org/10.1108/08876041111107032
Zhang,W.; Gao, X. 2008. Spatial dierentiations of trac sat-
isfaction and its policy implications in Beijing, Habitat In-
ternational 32(4): 437–451.
http://dx.doi.org/10.1016/j.habitatint.2008.01.005
Transport. Article in press 15
Downloaded by [Istanbul Bilgi Universitesi] at 04:53 26 October 2015