THE CUSTOMER LOYALTY OF PATAS PURWAKARTA TRAIN SERVICE USERS
The Customer Loyalty o f Patas Purwakarta Train Service Users
Muhamad Sapta Riyaldi
Amrizal
Tiur Merry Bunga Silalahi
STMT Trisakti stmt@indosat.net.id
STMT Trisakti
STMT Trisakti
stmt@indosat.net.id
stmt@indosat.net.id
ABSTRACT
The aim of this research is to ind out the inluence of service quality, ticket price, and customer satisfaction to the customer loyalty. It is a quantitative research using the data analysis method of Path Analysis. The results indicate that both variables of Service Quality (X1) and Ticket Price (X2) have a signiicant direct inluence to the variable of Customer Satisfaction (Y1), whereas the variable of customer satisfaction has a signiicant indirect inluence to the variable of Customer Loyalty (Y2) [through intervening the variable of customer satisfaction]. It is found in a sequence that the variables most inluential to the increase of Customer Loyalty are: Service Quality, Customer Satisfaction, and the Ticket Price in the last rank. The results of path analysis indicate that service quality can directly inluence the customer loyalty. It can be optimistically improved as maximal as possible through 5 factors having positive inluences in enhancing customer loyalty. Meanwhile, Ticket Price still indirectly inluences the customer loyalty and it can pesimistically still
be enhanced through the policy on tariff and it is dificult to implement, only can be driven if the ticket price provided by the transport service provider is more competitive and more various as well as affordable for the consumer purchase power of that transport sevice.
Key words : Service Quality, Ticket Price, Customer Satisfaction, Customer Loyalty
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
ISSN 2355-4721
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INTRODUCTION
Local Economy-Class Train of Purwakarta, frequently called Patas Purwakarta or abbreviated as Patas PWK, has been operating since 1971. Patas PWK is an economy class train serving the route of Purwakarta-Jakarta Kota round trip and one of the favorite commuter lines in Jabodetabek area. People often call it as odong-odong.
The service provided by this Patas train over four decades has been miserable. All passenger coaches are always fully loaded. Passengers sit and stand in crowds. Passengers’ luggage contributes to narrowing the coach space. Moreover, hundreds of passengers of such an odong- odong train occupy all the coach roofs for sitting, as well as tens of passengers hanging on the right and left sides of the Locomotive. It is because this train is for people in middle-low class with very low tariff.
The poor operation management of Patas Purwakarta train has made prospective passengers get on the train without buying ticket in prior. Such a condition is a “model mental” or social disease which is dificult to be eradicated. The cause is that almost all stations for the route of Purwakarta- Jakarta Kota round trip are not fenced, and the entrance/exit gate is not supervised byb the station oficers. Only three stations of middle class category, i.e. Cikampek, Bekasi, and Jatinegara have been fenced and supervised by the oficers.
Based on the information from the station oficers along the route of Purwakarta-Jakarta Kota round trip, only 20% out of all the passengers hold their tickets. It can be imagined the gloomy age of PT KAI by suffering from loss in a fairly long time, so it is not surprising that PT KAI, especially the Local Economy-Class Train of Purwakarta or such an odong- odong, has been subsidied every year. In addition, many issues have spreaded that not only the Local Economy-Class Train of Purwakarta or such an odong-odong suffer from loss, but almost all economy class trains like KRL and KRD. Even the government intentionally subsidies the economy class trains of Surabaya Pasar Turi, Surabaya Gubeng and others in order to keep the economy run smoothly.
The Management of PT Kereta Api Indonesia (PT KAI) should try to optimize the improvement of service quality to its consumers or passengers because it has a positive impact on the consumer (customer) loyalty. Measuring the level of customer loyalty in the quality service dimension, according to Parasuraman (1985: 41-50 and 1988: 12-40) and marketing experts (Zeithaml, Valarie A., A Parasuraman, Berry, Leonard L., 1990: 67) can be done through 5 factors: Tangible, Reliability, Responsiveness, Assurance and Empathy. The ive dimensions of service quality are often used by researchers (a multidimensional deinition/understanding). In this study, the ive dimensions of service quality are independent variables which, according
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
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The Customer Loyalty o f Patas Purwakarta Train Service Users
to Richa Widyaningtyas (2010: 49), can Consumer satisfaction will be represent 13 indicators of Independent achieved if the quality of product or service Variable (X1) or as research indicators provided by a company matches to the which determine whether the services consumer want, since service quality delivered by PT KAI, especially Patas much depends on who provides and how it Purwakarta Train, have been optimal or is delivered. Customer satisfaction is a key not.
success of a company; when the consumers are satisied, they will be loyal. Customer
According to Febri Tri Bramasta loyalty is obtained through a combination
Putra (2010: 15), independent variable of satisfaction and complaints. The higher
is a measure of how good the delivered the independent variable, the higher the
service can fulill or match to the consumer customer satisfaction level will be. This
expectation. Based on this statement, if is in accordance with Rambat Lupiyoadi
Patas Purwakarta Train want to satisfy its and Hamdani, A (2001: 98) stating that one
consumers, thus the service delivered to of the main factors the company should
consumers should be the same as or exceed pay attention in improving customer
their expectation in order to satisfy them, satisfaction is the independent variable.
and the control over this excellence is to fulill the customers’ want (Philip Kotler, Moreover, price also determines 2002: 83). Whereas Fandy Tjiptono (2007) customer satisfaction in the service use states that Independent variable is an effort because the tariff established is related to to satisfy consumers’ needs and wants as the passengers income. The higher tariff well as its punctual delivery in response of will make passengers think twice to use their expectation.
the transportation service. In contrast, the lower tariff make the passengers tend to use
Today, high independent variable the transportation service without many
is considered as a tool for transportation considerations. This is also in accordance
service company like Patas Purwakarta with the statement of Rambat Lupiyoadi
Train to have competitive advantages and Hamdani, A., (2006: 195) that price
over the competitors. The beneit of is one of the factors inluencing customer
good independent variable among others satisfaction. Therefeore, it is interesting to
are passengers loyalty, new prospective study customer loyalty in the train service,
passengers attraction, commitment and especially Patas Purwakarta Train.
satisfaction of all employees, improved image of Patas Purwakarta Train in the Fluctuation in the number of people’s eyes. These are intended to make passengers that tends to decline and people feel comfortable with the facilities complaints that indicate negative gaps and service provided and feel astonished between independent variable (X1) given with the transportation service performance by the transportation service provider of Patas Purwakarta Train.
and the independent variable perceived
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
by the passengers have caused a negative questionnaires; the researchers (authors) controversy among people so that both the directly accompany each of 125 respondents customer satisfaction (Y1) and the customer to be surveyed one by one. The object of loyalty (Y2) of Patas Purwakarta Train are the research is the regular passengers or not achieved. Based on the background customer who use the service of Patas that has been described, the authors are Purwakarta Train more than twice, thus not interested in studying or choosing the title all the population has the same probability Customer loyalty of Patas Purwakarta Train to be the sample. Service.
In order to know the inluence among The research is carried out using variables it can be explained through the
a “survey method” through fulilling following framework:
HX 1i : r 2 X 1i > 0.6
THEORETICAL FRAMEWORK
ALPHA CRONBACH > 0.6 e 1 X 1.1 Y 1 = Intervening Variable
e 2 X 1.2 e 3 X 1.3 e 4 X 1.4 e 5 X 1.5 e 6 X 1.6 e 7 X 1.7 e 8 X 1.8
e Service
9 X 1.9 Quality H 4 : Coeff. Reg c 1 >0
e 10 X 1.10 (X 1 ) e 11 X 1.11
HY 2i : r 2 Y 2i >0.6 e 12 X 1.12 HY
H 1 : Coeff. Reg a 1 >0
1i : r 2 Y 1i > 0.6
H ALPHA CRONBACH > 0.6
e 13 X 1.13 ALPHA CRONBACH > 0.6
Co :
R SquareChange= R 2 h 1 Y 2.1
g 1 Y 1.1 Consumer eff. Re
F Change = Fuji Test
Durbin-Watson Test g 2 Y 1.2 Satisfaction g Loyalty
g 3 (Y
2 Y 1.3 3 > h 4 Y 2.4
2 R SquareChange = R 2 0 HX 2i : h r Y X 2i > 0.6 F Change= Fuji Test r 2 (X i ) > 0.6 5 ALPHA CRONBACH > 0.6 2.5 Durbin-Watson Test
: Coeff. Reg a R SquareChange= R 2 H 2 2 >0 2 F Change = Fuji Test
f 1 X 2.1 r (Y 1 )> 0.6 Durbin-Watson Test f 2
2 X 2.2 Ticket
H 5 : Coeff. Reg c 2 >0 r (X i , Y 1 ) > 0.6 f 3 X 2.3 Price (X 2 ) r 2 (Y 1 , X i ) > 0.6
f 4 X 2.4
R SquareChange= R 2
F Change = Fuji Test Durbin-Watson Test
Figure 1 : Conceptual Model & Functional Relationship: Among Independent variable (X 1 ), Ticket price (X 2 ), Consumer satisfaction (Y 1 ), and Consumer Loyalty (Y 2 ). Estimated Results (Multiple Regression) to determine whether the function is Normally Distributed.
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The Customer Loyalty o f Patas Purwakarta Train Service Users
Regression Model I :
variable (X2v.i ) and the relationship both Variable and Dimension of Average in
Y 1 = a 0 + a 1 X 1 + a 2 X 2 + e 1 Path Analysis Method can be explained as Y 2 = b 0 + b 1 Y 1 C alc + e 2 follows:
Y 2 Calc = c 0 + c 1 X 1 + c 2 X 2 +
H X 1 2 :r X 1 >0:
Y 2 Calc = d 0 + d 1 X 1 + d 2 X 2 + d 3 Y 1 Independent variable (X 1 ) + e 4
H X 3v 2 :r X 3v >0:
Dimension of Averaged Independent variable (X 3v )
Regression Model II:
X 1 = e 0 +e 1 X 1.1 +e 2 X 1.2 +e 3 X 1.3 +
X 1u.i :r X 1u.i >0:
4 X 1.4 +e 5 X 1.5 +e 6 1.6 +
5 Main Dimensions (Total) of
e 7 X 1.7 +e 8 X 1.8 +e 9 X 1.9 +
Independent variable (X 1u.i )
e 10 X 1.10 +e 11 X 1.11 +e 12 X 1.12 +
e 13 X 1.13 +e 5
X 2 = f 0 + f 1 X 2.1 + f 2 X 2.2 + f 3 X 2.3
H 1 : HX 1u.1 = Tangible is the function of + f 4 X 2.4 +e 6 Independent variable
Y 1 = g 0 + g 1 Y 1.1 + g 2 Y 1.2 + g 3 Y 1.3 Indicator (X 1.1 to X 1.4 ) + e 7
H 2 : HX 1u.2 = Reliability is the function
of Independent variable
Y 2 = h 0 +h 1 Y 2.1 + h 2 Y 2.2 + h 3 Y 2.3 +
h 4 Y 2.4 + h 5 Y 2.5 + e 8 Indicator (X 1.5 to X 1.7 )
H 3 : HX 1u.3 = Responsiveness is the function of Independent
Path Analysis Method
Standardized Coeficients:
variable Indicator (X 1.8 to
Y = ρ X +ρ X +ε X 1.9 1 ) 1 1 2 2 9
Y 2 = ρ 1 X 1 +ρ 2 X 2 +σ 1 Y 1 +ε 10 H 4 : HX 1u.4 = Assurance is the function of Independent variable
Dimensional Variable (Relationship Indicator (X
1.10 to X 1.11 )
between Variable and Dimension)
H 5 : HX 1u.5 = Empathy is the function of The relationship among Independent Independent variable
variable (X1), 5 Main Dimensions (Total) Indicator (X
1.12 to X 1.13 ) of Independent variable (X1u.i ) and 5
Dimensions of Averaged Independent
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
H X 1v.i 2 :r X 1v.i >0
HY 2 1 :r Y 1 >0:
5 Dimensions of Averaged Variable of Consumer satisfaction Independent variable (X1v):
(Y 1 )
1 : HX 1v.1 = Tangible positively
HY 3v :r Y 3v >0:
inluences the variable of Dimension of Consumer satisfaction consumer satisfaction.
(Y 3v )
H 2 : HX 1v.2 = Reliability positively
inluences the variable of
HY
2 3v.i :r Y 3v.i >0:
3 Dimensions of Consumer consumer satisfaction.
satisfaction (Y
H 3v.i ):
3 : HX 1v.3 = Responsiveness positively inluences the variable of
(1) The service conforms the customer consumer satisfaction.
expectation,
H 4 : HX 1v.4 = Assurance positively (2) Customer’s willingness to
inluences the variable of recommend to others, and
consumer satisfaction.
H 5 : HX 1v.5 = Empathy positively (3) Satisfaction on the independent inluences the variable of
variable experienced. consumer satisfaction.
HY 2 2 :r Y 2 >0:
HX 2 2 :r X 2 >0: Variable of Consumer satisfaction
Variable of Ticket price (X 2 )
Dimension of Averaged Ticket price Dimension of Consumer satisfaction
(X 4v )
(Y 4v )
HX 4v.i 2 :r X 4v.i >0:
HY
2 4v.i :r Y 4v.i >0:
3 Dimensions of Averaged Ticket
3 Dimensions of Consumer price (X 4v.i ):
satisfaction (Y 4v.i ): (1) Conformity of price with the service
(1) Service reuse
quality delivered (2) The service is positively internalized
(2) Conformity of price with the service in customer’s mind
experienced (3) Always become the customer’s main
(3) Conformity of price with the facilities choice.
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The Customer Loyalty o f Patas Purwakarta Train Service Users
Path Analysis Method
where:
X 1.1 = Tangible = ( X1u.1 )
Standardized Coeficients:
X 1.2 = Reliability = (X 1u.2 )
Y 1 = ρ 1 X 1 +ρ 2 X 2 +ε 9
X 1.3 = Responsiveness = (X 1u.3 )
Y 2 = ρ 1 X 1 +ρ 2 X 2 +σ 1 Y 1 +ε 10
X 1.4 = Assurance = (X 1u.4 ) where:
X 1.5 = Empathy = (X 1u.5 ) Y 1 = Customer satisfaction
X 1.6 = Independent variable = (X 1 ) Y 2 = Customer loyalty
X 1.7 = Ticket price variable = (X 2 ) ρ 1 = Coeficient of Independent variable
X 1.8 = Consumer satisfaction variable = ρ 2 = Coeficient of Ticket Price variable
(Y 1 )
σ 1 = Coeficient of the variable
X 1.9 = Consumer loyalty variable = (Y 2 ) intervening Customer satisfaction
X 1.10 = Dimension of Averaged ε = Error Term
Independent variable = (X 3v )
X 1 = Independent variable
X 1.11 = Dimension of Averaged Ticket
X 2 = Ticket price
price = (X 4v )
X 1.12 = Dimension of Averaged Consumer satisfaction = (Y 3v )
Multi-Linear Regression Analysis
The analysis used to measure the strength of relationship between two or X 1.13 = Subsitute Dimension of Averaged more variables also indicates the direction Independent variable KP X 3v to KP of the relationship between dependent X 1 = [SubX 3v (X 1 )] variable and independent variable (Imam
X 1.14 = X = Independent Variable, as Total Ghozali, 2001). Such a research model
Score of Data with Category (the can be explained using linear regression
irst number)
equation model (A T. Ferdinand, et al., 2006) as follows:
Y = Dependent Variable, as Total Score of Data with Category (the
Y = e0 + e1 X1.1 + e2 X1.2 + e3 X1.3 + second number) e4 X1.4 + e5 X1.5 + e6 X1.6 +
e 0 ,e 1 ...... e 14 = the Coeficient of e7 X1.7 + e8 X1.8 + e9 X1.9 +
Regression for the 14 e10 X1.10 + e11 X1.11 + e12 X1.12
Independent Variables + e13 X1.13 + e14 X1.14 + e11
e 11 = Error Term
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
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RESULTS AND DISCUSSIONS
Model I, Regression Model II and Regression Model III (Multiple Regression)
The results of all calculated functional and functional Model of Path Analysis
estimations (Unstandardized Coeficients), Methoid (Standardized Coeficients) are as
including all regression models: Regression
follows:
HX 2 ALPHA CRONBACH = 1i : r X
1i = 0.812
0.986 RESULT OF EMPIRICAL CALCULATION
Y 1 = Intervening Variable
6.14 X 1.1 8.35 X 1.2
X 1.5 19.7 X 1.6 20.6 X 1.7
X 1.9 nt variable
c 1 = 0.287
10.0 X 1.10 (X 1 )
X 1.11 8.13
1 = a 0.207
HY : r 2 2i Y 2i = 0.775
1.34 1i :
HY r 2 Y 1i =
-20.3 X 1.12 ALPHA CRONBACH =
X 1.13 ALPHA CRONBACH = 0.908 c 2.41 Y 2.1
R Square = 0.962 3
F Ratio = 6.416
D-W Test = 2.571 3.34 Y 1.2 Konsumen
Y 2.4 2 R Square = 0.948 2.28 Y
1.3 (Y ) (Y ) -0.92
HX 2i : r X 2i = 0.846 F Ratio = 12.172
R Square = 0.910
ALPHA CRONBACH = 0.939 D-W Test = 2.514
r 2 (Y 1 2 )= 0.874
a = 0.066
9.79 X 2.1
F Ratio = 6.744
r D-W Test = 2.500 2
(X i ,Y 1 )= 0.984
X 2.2 Ticket
r (Y 1 ,X i )= 0.984
price (X 2 ) r 2
21.2 X 2.3 (X i ) = 0.893
R Square = 0.939
F Ratio = 10.184 D-W Test = 2.500
Figure 2 : Conceptual Model & Functional Relationship: Among Independent variable (X 1 ), Ticket price (X 2 ), Consumer satisfaction (Y 1 ), and Consumer Loyalty (Y 2 ). Estimated Results (Multiple Regression) to determine whether the function is Normally Distributed.
Unstandardized Coeficients: Regression Model II: Regression Model I :
X 1 = 38.000 + 6.138 X 1.1 + 8.351 X 1.2 - 2.210 X 1.3 - 5.507 X 1.4 -
Y 1 = 1.646730 + 0.207432 X 1 +
4.753 X 1.5 + 19.660 X 1.6 + 0.065966 X 2
20.596 X 1.7 - 0.311 X 1.8 - Y 2 = 0.429787 + 1.648747 Y 1 Calc 27.837 X 1.9 + 10.044 X 1.10 +
Y 2 Calc = 0.424256 + 0.287059 X 1 +
8.126 X 1.11 - 20.261 X 1.12 +
0.135069 X 2 + 0.241550 Y 1 1.340 X 1.13 Y 2 Calc = 0.424256 + 0.241550 Y 1 +
0.287059 X 1 + 0.135069 X 2
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The Customer Loyalty o f Patas Purwakarta Train Service Users
X 2 = 16.167 + 9.786 X 2.1 - 9.821X 2.2 +
Purwakarta train service provider can be 21.154 X 2.3 - 17.104 X 2.4 improved, then the customer satisfaction
(Y 1 ) will improve as well; b) The value
Y 1 = 11.369 - 1.431 Y 1.1 + 3.343 Y 1.2 +
of regression coeficient for ticket price 1.265 Y 1.3
variable (X 2 ) indicates positive value 0.088
Y 2 = 24.333 + 2.408 Y 2.1 + 0.071 Y 2.2 +
and signiicance at α = 0.713 [and has a 1.824 Y 2.3 - 0.924 Y 2.4 + 2.281 Y 2.5 very big conidence interval (or fairly much
varies)]. It means, if the ticket price set by
Path Analysis Method
the transportation service provider is more
Standardized Coeficients:
competitive and more varied as well as affordable for consumers (Patas Purwakarta
Y 1 = 0.912 X 1 + 0.088 X 2 train service users)’ purchasing power Y
is applicable, then customer satisfaction
2Calc = 0.750 X 1 + 0.107 X 2 + 0.144 Y 1
1 ) will improve as well; c) Based on the Y
(Y
or
value of regression coeficient, the most
1 = 0.912 X 1 + 0.088 X 2 Y
2Calc inluential variable to improving customer = 0.144 Y 1 + 0.750 X 1 + 0.107 X 2 satisfaction (Y 1 ) is independent variable
(X 1 ). This is indicated by the value of Indirect Inluence of Independent regression coeficient for independent Variable and Ticket price on Customer variable which is bigger than the regression
Satisfaction
coeficient for ticket price (X 2 ), where the signiicance α = 0.05 meaning that the
1. Regression Equation
independent variable (X 1 ) is signiicant Based on the examination against the whereas the ticket price variable (X 2 ) is not inluence of independent variable and ticket signiicant, but the ticket price still can be price on consumer (customer) satisfaction, enhanced because its positive regression the results are obtained at Table 1.
coeficient is still big enough.
Based on the estimation result 2. Testing Hypothesis
of Model I (Multi-Linear Regression)
Test of Hypothesis 1: The Inluence of
indicated by the Standardized Coeficients, it can be stated by the following equation: Independent Variable on Customer
Satisfaction
Y 1 = 0.912 X 1 + 0.088 X 2 The hypothesis testing indicates
This multi-linear regression equation that independent variable has impact
shows that : a) The value of regression on customer satisfaction as intervening
coeficient for independent variable variable; it is proven that value of t
(X
1 ) indicates positive value 0.912 and 4.203 is signiicant at α = 0.025, whereas signiicance at α = 0.025. It means if the at the signiicance of 0.05 and degree of independent variable provided by Patas
count
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
freedom (df) = 3, so that t count = 4.203 > t table then consumer satisfaction will decline or = 2.353 is also still signiicant. It means that the product or service will have a negative the independent variable that is given can vakue to consumer satisfaction, and the
be enhanced, and then it can improve the consumer loyalty will decline as well. It customer satisfaction. This is in accordance also applies for the opposite according to with Hendy Irawan Juwandi (2004: 37) Rambat Lupiyoadi and Hamdani, A, et.al., stating that one of the factors driving (2006). Thus ticket price is in the position consumer satisfaction is the enhancement of very critical signiicance. Therefore, the of independent variable
ticket price offered should be more varied and more competitive and affordable for
Based on the result of hypothesis the users, so that it can still be tolerated in
testing it can be concluded that the improving consumer satisfaction.
test accept the irst hypothesis, so the assumption on the existence of positive Based on the result of hypothesis testing inluence of independent variable on it can be concluded that the test accept the customer satisfaction is proven or second hypothesis, so the assumption on acceptable. This research is consistent with the existence of positive inluence of ticket the one carried out by Rachel (2007) that price on customer satisfaction is proven or Quality has a signiicant inluence on the acceptable. This research is in line with the consumer satisfaction and loyalty.
one carried out by Ambar Setya Ningtyas (2008) that price has a signiicant inluence
Test of Hypothesis 2: The Inluence of
on the consumer satisfaction.
Ticket Price on Customer Satisfaction The Inluence of Independent Variable
The hypothesis testing indicates that
and Ticket Price on Customer Loyalty
Ticket price has positive impact on the
through Customer Satisfaction as the
improvement of customer satisfaction. The
InterveningVariable.
value of t count 0.405 is not signiicant at α
= 0.713, since the value of t count = 0.405 < 1. Regression Equation
t table = 0.713. In this test Ho is accepted and Based on the estimated result for
Ha is rejected. It means that the test has Model II (Multi-Linear Regression) Table 2
no signiicant impact at α = 7.13 % and indicated by the Standardized Coeficients,
still signiicant at α = 10 % (and the most it can be stated in the following equation:
important is that the coeficient of estimated result give positive value as in the theory). Y 2 = 0.750 X 1 + 0.107 X 2 + 0.144 Y 1
Multi-Linear Regression statement of Rambat Lupiyoadi and equation indicates that : a) The value of
This result is in accordance with the This
Hamdani, A, et.al., (2001), that if a product regression coeficient for independent requires consumers to pay a higher cost variable (X 1 ) in the regression equation than its marginal utility that they receive, model II indicates positive value of 0.750
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The Customer Loyalty o f Patas Purwakarta Train Service Users
and it is signiicant at α = 0.018. It means of empirical test in this research has found that if the independent variable given by the the theoretical implication and additional provider of Patas Purwakarta train service justiication for some antecedents which can be enhanced, then customer satisfaction positively inluence customer loyalty
(Y 1 ) will improve, so it positively inluences altogether, so it is stated that ticket price (X 2 ) the improvement of customer loyalty (Y 2 ); is weaker than independent variable (X 1 ) in
b) The value of regression coeficient improving both customer satisfaction (Y 1 ) for ticket price variable (X 2 ) indicates and customer loyalty (Y 2 ). positive value of 0.107 and it is signiicant
2. at α = 0.118 [and has conidence interval Testing Hypothesis
which is very high (or much varied)]. It Test of Hypothesis 3: The Inluence of means that if ticket price offered by the Independent Variable on Customer provider of Patas Purwakarta train service Loyalty through Customer Satisfaction
is more competitive and more varied The independent variable test on
as well as affordable for the users, then consumer loyalty through intervening
customer satisfaction (Y 1 ) will improve,
variable, i.e. consumer satisfaction, found so it positively inluences the improvement
the value of standardized beta 0.912
of customer loyalty (Y 2 ); c) The value
which is signiicant at α = 0.025, meaning of regression coeficient for customer
that independent variable has impacts
satisfaction variable (Y 1 ) indicates positive
on customer satisfaction. If independent value of 0.144 and it is signiicant at α =
then customer 0.304. It means that customer satisfaction
variable
improves
satisfaction will improve as well. The value can be improved. With the improvement
of standardized beta 0.912 is the value of of customer satisfaction, it will also
path p3.
positively inluences the improvement of customer loyalty (Y 2 ); d) Based on the In the regression equation as described result of empirical test on the regression in Model II, the value of standardized beta equation model II Path Analysis Method, it for independent variable is found as 0.750 is found that the most inluential variable and customer satisfaction as 0.144 all which
for improving customer loyalty (Y 2 ) is the show signiicant impact. The value of variable that indicates bigger regression standardized beta for independent variable coeficient value B (Unstandardized as 0.750 is the value of path p4 and the Coeficients) or the value of signiicance value of standardized beta for consumer Beta or β = the smallest (Standardized satisfaction as 0.144 is the value of path p5. Coeficients). Based on these requirements,
The value of that path is e1 = [(1- 0.750)] 1/2 the most inluential variables for improving
= 0.500 and e2 = [(1- 0.144)] 1/2 = 0.925.
customer loyalty (Y 2 ) are independent
variable (X 1 ), customer satisfaction (Y 1 ), The value of direct inluence of and ticket price (X 2 ) respectively. The result independent variable on customer loyalty is
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
0.750, whereas the value of indirect inluence coeficient (0.088) x (0.107) = 0.009. should be calculated by multiplying the Regarding the direct coeficient is bigger indirect coeficient (0.912) x (0.750) = than the value of regression coeficient for 0.684. Regarding the direct coeficient indirect relationship, it can be concluded is bigger than the value of regression that in actual there is a direct relationship coeficient for indirect relationship, it can between ticket price and consumer
be concluded that in actual there is a direct satisfaction. relationship between independent variable
The Inluence of Customer Satisfaction
and consumer satisfaction.
on Customer Loyalty Test of Hypothesis 4: The Inluence
The research shows that the value
oif Ticket Price on Customer Loyalty
of tcount for customer satisfaction is
through Customer Satisfaction
1.369 which is signiicant at α = 0.304. From the test of ticket price on This indicates that there is a signiicant consumer loyalty through intervening inluence of customer satisfaction on variable, i.e. consumer satisfaction, it customer loyalty. This is in line with the is found the value of standardized beta research carried out by Wenny Maylina as 0.088 which is not signiicant at α = (2003), where satisfaction has positive 0.713. It means that ticket price inluences signiicant inluence on consumer’s brand consumer satisfaction. If ticket price is loyalty. Based on the hypothesis test it enhanced then consumer satisfaction will can be concluded that the test accept the improve. The value of standardized beta ifth hypothesis, so the assumption on 0.088 is the value of path p3.
the existence of inluence of customer satisfaction (Y1) on customer lotalty (Y2)
In the regression equation as described
is acceptable.
in Model II, the value of standardized
beta for ticket price is found as 0.107 and Multi-Linear Regression Analysis
customer satisfaction as 0.144 all which The estimated results, Table 3,
show signiicant impact. The value of Table 4, Table 5 (multiple regression) of
standardized beta for ticket price as 0.107
14 independent variables classiied as is the value of path p4 whereas the value of
Customer satisfaction variables toward standardized beta for consumer satisfaction
Dependent Variable: Y = Dependent as 0.144 is the value of path p5. The value
variable (Data in the Category of Total of e1 = [(1- 0.750)] = 0.500 and e2 =
II) representing Customer loyalty from all [(1- 0.144)] = 0.925.
respondents of this research indicate the The value of direct inluence of ticket model precision which is signiicant at α price on customer loyalty is 0.107, whereas = 5 % and F 0.05 (v 0.05 ,v 010 ) with the value the value of indirect inluence should be of FRatio is big, and able to explain the calculated by multiplying the indirect variance of Customer loyalty with the value
12 Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
ISSN 2355-4721
The Customer Loyalty o f Patas Purwakarta Train Service Users
of Determination Coeficient or Adjusted R The most inluential variable for Square (R 2 ) 0.988. It means that 98.8% of improving customer loyalty (Y
2 ) is the the customer loyalty variance is explained one that shows bigger value of regression
by all its independent variables, while the coeficient B (Unstandardized Coeficients) rest of 0.012 or 1.2% is explained by the or the smallest value of signiicance Beta variables not included in this research.
or β (Standardized Coeficients). The variable is Reliability = X1u.2, which is
Regarding the individual impact proven to fulill the demands for good
of each independent variable, there are 4 services and positive impression the irst
variables that have negative impoact on time passengers get on Patas Purwakarta
Customer loyalty, namely: (1) Tangible = train; the services suitable with passengers
X 1u.1 , (2) Empathy = X 1u.5 , (3) Independent expectation; and for ability to tackle the variable (X 1 ) and (4) Customer loyalty problems of customer service in a good variable (Y 2 ), signalling that the effort top way to make the customers loyal to Patas maximize the improvement of Customer Purwakarta train service. loyalty through both Main Dimensions
(Total) of Independent variable (X 1u.i ) has The reability, as exempliied by not been optimal yet.
Lerbin Aritonang (2005), of three indicators of independent variables in sequential
The transportation service provider number: (5) Honesty in providing
should try to renew and improve the explanation, (6) Hospitality, and (7) Speed
displayed Tangibles by increasing the of service, according to Tjiptono (2000),
number of coaches or railway trains which includes two essential things, namely:
are ready to operate so that it does not take (i) Performance and (ii) dependability.
a long time for the passengers to get on It means that the company delivers its
Patas Purwakarta train and by improving services right the irst time. It also means
the facilities within Patas Purwakarta train that the company fulill its promise. The
to establish loyal customers every year. reliability for transportation services is
Meanwhile, the Emphaty that should be exampliied by such things as: (a) Serving
given by the service provider is establishing passengers well the irst time they use the
loyal customers, improving the service available service, (b) Serving at the time
quality (independent variable) to passengers promised, and (c) Paying sincere attention
in the form of Emphaty Dimension. The to consumers (passengers) by showing the
decline of two Main Dimensions (Total) of
vacant seats.
Independent variable (X 1u.i ), i.e. Tangible and Empathy has negative impacts on Based on the empirical test, two- Independent variable (X 1 ) and (4) Customer third of 5 Main Dimensions (Total) of loyalty variable (Y 2 ).
Independent variable (X 1u.i ) are proven to have positive impacts in improving customer loyalty. This empirical test
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
explicitely supports the statements of makes the passengers or customers Rambat Lupiyoadi and Hamdani, A, et.al., impressed, satisied, and even loyal to the (2001) and marketing experts (Zeithaml, transportation service offered. Valarie A., A Parasuraman, Berry, Leonard
Meanwhile, the ability of Ticket L, et.al., (1990) that one of the main
price to improve Customer loyalty (Y 2 ) factors a company has to pay attention
is categorized weaker than the ability in improving customer satisfaction is
of independent variable (X 1 ). It is much independent variable, which can be
determined by the non-physical factors measured through 5 factors, i.e. tangible,
that should be considered in terms of reliability, responsiveness, assurance,
economics, “tradeoff” for incuring costs empathy.
as the carrying fee (ticket price) compared
CONCLUSION
with the marginal utility received by the consumers or customers, making dificult
Based on the empirical test therough to implement the service provider’s policy
multi-linear regression analysis using to set up the transportation tariff. Beside
Path Analysis Method, it is found that it is a boomerang for the transport service
both Independent variable (X 1 ) and Ticket
provider due to its negative impact of price (X 2 ) have signiicant direct inluence
declining consumer satisfaction, it is also
on Customer satisfaction variable (Y 1 ).
a tradeoff for a series of policies made by Whereas customer satisfaction variable
the provider because it makes consumers has signiicant indirect inluence on
or customers become disloyal. Responding
Customer loyalty variable (Y 2 ) [through
such a condition, the last weapon in setting the intervening variable of customer
up Ticket price through the policy on satisfaction]. It is found that the most
tarnsportation tariff can only be driven if inluential variables for improving
the ticket price set up by the provider is Customer loyalty are Independent variable,
more competitive and more varied as well Customer satisfaction, and Ticket price
as affordable for the purchasing power of respectively.
the service users. In the other words, the The superiority of Independent consumers or customers are faced only
variable over Ticket price in improving with two alternatives:”buy the ticket or Customer loyalty is determined by the not” or “use Patas Purwakarta train service direct optimization done simultaneously or other modes of transport”. through 5 factors that have positive
Based on the empirical test through impact on improving customer loyalty,
multi-linear regression analysis which
i.e. Tangible, Reliability, Responsiveness, estimates 14 independent variables, thus
Assurance, and Empathy both physically involving all the data in the variables related
and non-physically in order to get an to—and complete—the Path Analysis
optimum quality service which, in turn, Method, it is found a research model
14 Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
ISSN 2355-4721
The Customer Loyalty o f Patas Purwakarta Train Service Users
which has good itness with goodness of it Hadi, Sutrisno. 2001. Metodologi Research. regression models and all the hypotheses in
Yogyakarta: UGM. this research are normally distributed (after
Hair, JR, Joseph F, Rolp E. Andeson, passing through various statistical tests)
Ropnald L. Tathan & William with the value of Determination Coeficient
2 C.Black. 1995. Multivariate Data or Adjusted R Square (R ) 0.988. It means
Analysis with Reading. Forth Ed, that 98.8% of the customer loyalty variance Prentice Hall International, Inc. is explained by all its independent variables,
whereas the rest of 0.012 or 1.2 % is Juwandi, Hendy Irawan. 2004. Kepuasan explained by other variables not included
Pelayanan Jasa. Jakarta: Erlangga. in this research.
Kotler, Philip. 2002. Manajemen
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The Customer Loyalty o f Patas Purwakarta Train Service Users
ATTACHMENTS Table 1 Regression Equation Model I The Inluence of Independent Variable and
Ticket Price on Customer Satisfaction Coeficients a
Unstandardized
Standardized
Model Coefficients
Coefficients
t Sig. 1. (Constant)
B Std. Error
Beta
.372 .704 Independent variable
4.203 .025 Ticket price
a Dependent Variable: Y 1 = Consumer satisfaction (Observed)
Source: Primary Data from Survey, processed by the authors, 2013
Table 1 Regression Equation Model I The Inluence of Independent Variable and Ticket Price on Customer Satisfaction Coeficients a
Model Unstandardized
t Sig. 1. (Constant)
B Std. Error
Beta
.307 .788 Independent variable
7.253 .018 Ticket price
2.643 .118 Consumer satisfaction
a Dependent Variable: Y 2 Calc (One-Stage Regression as Observed) = Consumer loyalty (Calculated) Source: Primary Data from Survey, processed by the authors, 2013
Tabel 3 Model Summary b
Model R R Square
Adjusted R
Std. Error
Change Statistics
R Square
F Change
df 1 df 2 Sig. F Watson
a. Predictors: (Constant), X = Independent Variable (Total value), Dimension of AveragedIndependent variable = X 3v , Independent variable = X 1 , Dimension of Averaged Consumer satisfaction = Y 3v , Consumer loyalty variable = Y 2 , Consumer satisfaction variable = Y 1 , Subsitute Dimension of Averaged KP X 3v
to KP X 1 = SubX 3v (X 1 ), Empathy = X 1u.5 , Assurance = X 1u.4 , Responsiveness = X 1u.3 , Reliability = X 1u.2 , Dimension of Averaged Ticket price = X 4v , Ticket price variable = X 2 , Tangible = X 1u.1 b. Dependent Variable: Y = Dependent Variable (Total II)
Source: Primary Data from Survey, processed by the authors, 2013
Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016
M. Sapta Riyaldi, Amrizal, Tiur Merry Bunga S.
ISSN 2355-4721
Table 4 ANOVA a Model
Sum of
Df Mean Square
F Sig.
Squares
Regression b 4150022.349 14 296430.168 709.404 .000 1 Residual
a. Dependent Variable: Y = Dependent Variable (Total II) b. Predictors
Source: Primary Data from Survey, processed by the authors, 2013
Table 5 Coefficient for Estimated Results Coefficients a
Sig. Collinearity
Tolerance VIF (Constant)
B Std. Error
Tangible = X 1u.1 -.909
Reliability = X 1u.2 .582
Responsiveness = X 1u.3 .234
Assurance = X 1u.4 .104
Empathy = X 1u.5 -.046
Independent variable = X 1 -.039
Ticket price variable = X 2 .193
Consumer satisfaction variable = Y 1 .184
Consumer loyalty variable = Y 2 -.142
.360 .017 58.598 variable = X 3v Dimension of Averaged Ticket price =
Dimension of Averaged Independent
.558 .017 59.526 X 4v Dimension of Averaged Consumer
.062 .658 1.520 satisfaction = Y 3v Subsitute Dimension of Averaged
Independent variable KP X 3v to KP X 1 =
SubX 3v (X 1 ) X = Independent Variable (Total Value)
a. Dependent Variable: Y = Dependent Variable (Total II) Source: Primary Data from Survey, processed by the authors, 2013
18 Jurnal Manajemen Transportasi & Logistik (JMTranslog) - Vol. 03 No. 1, Maret 2016