Application of interpretive structural modelling for analysing.docx

Application of interpretive structural modelling for analysing
barriers to total quality management practices implementation
in
the automotive sector
G. Muruganantham
a
, S. Vinodh
b∗
, C. S. Arun
b
and K. Ramesh
b
a
Department of Management Studies, National Institute of
Technology, Tiruchirappalli 620 015,
Tamil Nadu, India;
b
Department of Production Engineering, National Institute of
Technology,
Tiruchirappalli 620 015, Tamil Nadu, India
In the recent era of globalisation and competitive scenario,
quality plays a vital role in
ensuring customer satisfaction. Total quality management
(TQM) involves the

implementation of appropriate tools/techniques to provide
products and services to
customers with best quality. In order to ensure the success of
TQM practices in a
modern automotive component manufacturing scenario, barriers
and their mutual
interactions need to be systematically analysed to enable
practicing managers for
effective deployment. In this context, this study depicts an
interpretive structural
modelling (ISM)-based approach to understand the mutual
influence of TQM
barriers. A total of 21 barriers have been identified for TQM
practices and ISM
model has been developed. The barriers are grouped under four
categories
(dependent, independent, autonomous and linkage) based on
MICMAC analysis. The
conduct of the study enabled the decision-makers to
systematically analyse the
influential barriers for effective deployment of TQM concepts
in modern automotive
component manufacturing, which is one of the rapidly growing
sectors in the Indian
scenario.
Keywords: total quality management; interpretive structural
modelling; barriers;
structural model; MICMAC analysis; Indian automotive sector
Introduction
During the past decade, manufacturing organisations have been
adopting total quality
management (TQM) as a philosophy for bringing about quality

improvements. TQM
enables the organisations to attain business excellence. TQM
emphasises continuous
improvement as one of the top goals and it enables
organisations to achieve business excel-
lence. TQM includes guiding principles and management
practices that lead to continuous
improvement in quality and providing quality products to
customers. TQM focuses on
management commitment and involvement, customer focus,
teamwork, motivation and
employee involvement. In addition, modern automotive
manufacturing organisations
have adopted advanced quality tools such as Quality Function
Deployment, Failure
Mode and Effect Analysis and Six Sigma. In order to compete in
the globalised market,
the organisations must inculcate TQM concepts into all
activities of the organisation effec-
tively (Mahapatra & Sekhar, 2004). TQM practices have been
widely acknowledged as a
disciplined management process in different sectors such as
manufacturing, and service in
order to deal with changes in the marketplace and focus on

product and service quality. It
provides a set of guidelines that will help to improve the
organisation performance.
# 2018 Informa UK Limited, trading as Taylor & Francis Group
∗ Corresponding author. Email: [email protected]
Total Quality Management, 2018
Vol. 29, No. 5, 524 – 545,
https://doi.org/10.1080/14783363.2016.1213627
mailto:[email protected]
http://www.tandfonline.com
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16.1213627&domain=pdf
A perfect strategic planning enables benchmarking
organisation’s activities and prac-
tices with reference to their competitors (Saravanan & Rao,
2006), as well as to utilise
available human resources effectively to overcome issues such
as inadequate use of
empowerment and teamwork, no proper benchmarking and
human resource barrier.
Automotive component manufacturing is the fast-growing sector
in the Indian context
and it significantly contributes to gross domestic product (GDP)
of the country (Bhadaur-

iya & Gupta, 2015). In order to sustain in the competitive
situation, the organisation has to
implement advanced quality concepts. Many factors facilitate
continuous improvement;
one among them is quality of products manufactured by
organisations, which enhances
customer base. Hence, in the automotive component
manufacturing sector, TQM practices
play a vital role to bring the product to market at higher quality
levels than customer
expectations. There is a significant impact of organisational
culture on TQM implemen-
tation in Indian small and medium-scale enterprises (SMEs) in
the auto components man-
ufacturing sector (Sinha, Garg, Dhingra, & Dhall, 2016). The
research gap addressed in the
present study is to deploy a structured approach for the
identification and analysis of bar-
riers that are influencing the adoption of TQM practices in the
automotive sector. Prior
studies focused on the service sector and no attempt has been
made to analyse the barriers
for TQM practices in the automotive component manufacturing
sector, which is one

among the fastest growing sector in the Indian scenario. The
research objective of the
present study is to identify and rank barriers for TQM practices
and to analyse interactions
among barriers using an interpretive structural modelling (ISM)
approach. Upon analysing
these barriers, management and practicing managers can
understand major barriers that
influence them and their linkages. Hence, the management
decision-making tool ISM is
used to analyse the interrelationship between each individual
barriers and to identify domi-
nant barriers that have to be assigned more importance. ISM is a
tool for understanding
complex situations and enables effective planning (Sarkis,
Hasan, & Shankar, 2006).
Based on literature analysis and expert opinion, appropriate
barriers of TQM practices
have been identified. The study presents a systematic analysis
of barriers of TQM implemen-
tation in the automotive component manufacturing sector using
an ISM approach. MICMAC
analysis is used for the categorisation of barriers into driver,
dependent, autonomous and

linkage clusters in this study. The novelty of this study is that it
presents an approach for
the systematic analysis of barriers of TQM practices in the
modern automotive sector.
Literature review
Successful implementation of TQM practices helps the
automotive sector to stay in the
competitive edge by providing better quality products to the
market. In addition, it
helps to achieve desired outcomes such as increased
organisation performance, profitabil-
ity and improved customer satisfaction. However, there are
certain barriers that hinder an
organisation from attaining those desired outcomes. This
literature survey aims to identify
major barriers that need to be considered and actions to be taken
during the implemen-
tation of TQM practices in the automotive sector, which
influences organisational per-
formance and enables customer satisfaction. Based on the
literature review and expert
opinion, a list of 21 barriers is identified and used in the study.
Identification of barriers to implementation of TQM practices

Kumar, Garg, and Garg (2011) performed a study to explore the
advantages of implement-
ing TQM practices and drawbacks of TQM and to explore
differences between the service
Total Quality Management 525
sector and the manufacturing sector. They collected certain
success factors from a litera-
ture review and surveyed among manufacturing and service
industries located in the north-
ern part of India. The identified success factors include
teamwork, employee training,
feedback, effective communication, management commitment,
customer satisfaction
and customer involvement. The survey was conducted to rank
these seven success
factors in both sectors and found that all seven factors possess
lower weightage for
TQM practices in service industries as related to manufacturing
industries in the Indian
scenario. They emphasised that both sectors recognised the
importance of committed man-
agement to TQM practices. Catalin, Bogdan, and Dimitrie

(2014) presented various bar-
riers for implementing TQM concepts in all sectors. Based on
literature studies and expert
opinion, they identified a list of 50 barriers and fitted them into
5 categories, namely stra-
tegic, structural, human resources, contextual and procedural.
Talib, Rahman, and Qureshi
(2011b) developed an ISM-based structural model to analyse the
barriers for implementing
TQM practices in service organisations. They identified 12
barriers from literature reviews
and expert opinion. They concluded that the lack of top
management commitment and lack
of coordination between departments are the most dominant
barriers, possessing high
driving power and low dependence power.
Lin and Chang (2006) explored TQM practices, manufacturing
goals and their
relationships with organisational performance progress using
stepwise regression and
canonical correlation analysis. They observed a strong linkage
of TQM and manufacturing
goal as well as organisational performance. In addition, they
concluded that for effective

TQM practice by firms, flexibility and delivery time are mostly
contributing towards
organisational performance. Firms should nurture their service
quality to improve their
performance. Hafeez, Malak, and Abdelmeguid (2006)
conducted a survey and identified
that organisations face much difficulty in translating TQM
concepts into practice. Only
few organisations successfully implemented a holistic approach
to TQM philosophy and
adopted technology elements of TQM. In addition, they stated
that companies have not yet
fully realised financial outputs and non-financial benefits of
implementing TQM practices.
Soltani, Lai, Sayed Javadeen, and Hassan Gholipour (2008)
investigated the role of senior
management commitment for the successful implementation of
TQM practices. In
addition, they also determined reasons for low commitment
from top management.
Rahman (2001) analysed the effect of quality management
factors on organisational per-
formance for SMEs in Western Australia with and without ISO
9000 certification. They

found that except for the factor ‘Process control’, results
indicated no significant differ-
ence between the impacts of TQM practices on organisational
performance for firms.
Also, they classified the firms into high, moderate and low
levels of TQM firms and ana-
lysed the influence of ISO 9000 certification in each type and
found that there is no sig-
nificant difference between the impacts of TQM practices and
organisational
performance for firms with and without ISO 9000 certification.
Jun, Shaohan, and Peterson (2004) studied the obstacles to TQM
implementation in
Mexico’s Maquiladora industry. They identified the prevalence
of TQM barriers such as
high employee turnover, employee training and employee
resistance to change. They
also found that poor education and training act as a top barrier
in the development and
deployment of a quality programme. Sebastianelli and Tamimi
(2003) identified a list
of 25 most commonly influencing obstacles to TQM practices.
They explored the relation

between obstacles and potential undesirable outcomes as a
result of TQM failure. They
performed factor analysis to extract obstacles and provided a
framework to assess their
relative impact on TQM success and found that inadequate
resources, inadequate
human resources development and management and lack of
planning are the most
526 G. Muruganantham et al.
influencing obstacles. Baladhandayutham, Devadasan,
Selladurai, and Senthil (2001) inte-
grated the concept of business process reengineering and TQM
and performed comparison
for different scenarios. They identified that the application of
advanced quality practices
will enhance productivity and customer satisfaction.
Implementation of quality practices
avoids reprocessing of products and improves customer
satisfaction. Also, they high-
lighted that employee attitude towards quality was an important
barrier in the effective
deployment of any quality programme. Whalen and Rahim
(1994) performed a study to

identify common barriers for the development and deployment
of a TQM programme
and they observed various factors influencing the role played by
top management in organ-
isational environment with TQM orientation and concluded that
quality implementation
programmes will ensure success with top management
commitment. Mohanty (1997) dis-
cussed various issues of TQM implementation and also
explained TQM as a revolution of
the present scenario to transform contemporary organisations to
the best position of
quality, to satisfy the needs of customers and to channelise it
into constructive means
through productive efforts.
Research gap
From the literature analysis, it has been identified that there is
no concrete study performed
to identify and systematically analyse various barriers
influencing the implementation of
TQM practices in the automotive component manufacturing
sector in the Indian scenario.
Systematic analysis of barriers provides a methodological

approach for practitioners to
understand the TQM barriers. In addition to that, there is no
clear framework existing
in the past studies depicting the influential barriers of TQM
implementation pertaining
to the automotive sector. It is necessary to have a clear
understanding of the framework
of influential barriers before proceeding for the implementation
of TQM practices as it
provides guidelines to identify the most influential barriers
systematically with minimal
efforts. In order to ensure practical relevance of the framework,
inputs from practitioners
working in automotive organisations were used to identify
dominant influential barriers
enabling smooth deployment of TQM concepts.
Identified barriers are presented in Table 1. B1 to B21 denotes
the barriers used in the
study.
Methodology
Figure 1 depicts the methodological steps followed in the
present study. A survey was
conducted among various experts who are involved in the

implementation of TQM
strategy in their organisations from automotive industries
situated in the Tamil Nadu
state of India. Based on the inputs from the survey and
literature analysis, 21 major
barriers influencing TQM implementation have been identified.
Then, an ISM approach
is used for developing the structural model and MICMAC
analysis is done to categorise
the barriers.
ISM methodology
In this study, an ISM approach is used for prioritising the
barriers influencing TQM
implementation.
ISM is a management decision tool, which analyses and
prioritises multi-criteria decision
factors combining both subjective and quantitative methods
(Kannan, Pokharel, & Kumar,
Table 1. Description of barriers.
Barrier

notation Barrier Description Author(s)/references
B1 Lack of top management
commitment
Top management commitment enables success of quality
implementation programme.
Leadership plays a vital role in implementing TQM
initiatives
Soltani, Lai, and Gharneh (2005); Soltani (2005);
Talib et al. (2011b); Whalen and Rahim (1994); Yahia
Berrouiguet, A. (2013); Mohanty and Lakhe (1998);
B2 Attitude of employees
towards advanced
quality practices
Application of advanced quality practices will enhance
productivity and customer satisfaction
Talib et al. (2011b); Mohanty (1997); Baladhandayutham
et al. (2001)
B3 Lack of proper training and
education
Poor education and training act as a major barrier for
quality programme implementation.
Effective training and employee empowerment enable
process and service quality
Jun et al. (2004); Ljungstrom and Klefsjo (2002);

Kumar et al. (2011); Whalen and Rahim (1994); Talib et al.
(2011b); Yahia Berrouiguet, A. (2013)
B4 Poor planning Lack of strategic planning results in
ineffective quality
improvement. Creating the vision, planning and
leading the organisational change by top management
ensures TQM success
Khanna, Sharma, and Laroiya (2011); Whalen and Rahim
(1994); Talib et al. (2011b); Sebastianelli and Tamimi
(2003); Mohanty (1997); Yahia Berrouiguet, A. (2013);
B5 Employee resistance to
change
Employee resistance to adopt change is a common barrier
faced by organisations while implementing any quality
improvement programme
Jun et al. (2004); Soltani et al. (2008); Talib et al. (2011b);
Raimona Zadry and Mohd Yusof (2006); Sohal and
Terziovski (2000); Khan (2011)
B6 Inadequate use of
empowerment and
teamwork
Employee empowerment and teamwork are vital for
TQM success
Talib et al. (2011b); Rahman (2001); Mosadeghrad (2005)
B7 Lack of continuous
improvement culture

Continuous improvement is vital for TQM success Talib et al.
(2011b); Kumar, Kumar, Grosbois, and Choisne
(2009)
B8 Lack of communication Proper communication between
departments enables
effective TQM implementation
Gunasekaran (1999); Yahia Berrouiguet, A. (2013)
B9 Non-usage of advanced
TQM tools
Maximum benefits of TQM practices could be realised
through comprehensive knowledge of several key
elements such as system, tools and techniques
Talib et al. (2011b); Baidoun (2003); Gupta, Wali, and
Deshmukh (2003)
B10 Lack of customer
involvement
Paying inadequate attention to customers or lack of
customer focus will result in TQM failure.
TQM initiatives are recognised as a failure if they fail to
delight customers and do not add value from
customers’ viewpoint
Yahia Berrouiguet, A. (2013);
Thiagarajan and Zairi (1997); Raimona Zadry and Mohd
Yusof (2006); Mosadeghrad (2005); Nizam and James
(2005)

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B11 Non-conduct of process
capability and Six
Sigma studies

Success of TQM initiatives depends on periodic conduct
of process capability and Six Sigma studies. Industries
need to continuously monitor sigma level of processes
and to become zero-defect enterprises
Mohanty and Lakhe (1998); Gupta et al. (2003)
B12 No proper motivation TQM initiates a wholesome
transformation in employee
spirit, thinking, behaviour and job-related practices
Jun et al. (2004); Mosadeghrad (2005); Mohanty (1997);
Nizam and James (2005)
B13 Ineffective measures of
quality improvement
TQM practices are positively associated with operational
performance. TQM is centred on monitoring
employees and processes. Effective measures need to
be developed for measuring quality improvement
Mosadeghrad (2005); Khanna et al. (2011); Whalen and
Rahim (1994)
B14 No periodic benchmarking Absence of benchmarking
prevents continuous quality
improvement culture and impacts competitiveness
Talib et al. (2011b); Bhat and Rajashekhar (2009); Catalin
et al. (2014); Khanna et al. (2011)
B15 Non-integration of voice
of customer and supplier

Success of TQM initiatives depends on integrating the
requirements of customers and suppliers
Appropriate mechanisms need to be developed for the
integration and subsequent processing for voice of
customers and suppliers
Khanna et al. (2011); Sohal and Terziovski (2000);
Nizam and James (2005); Samuel (1999)
B16 Inadequate resources Resource shortage or constraints
affects TQM success
Allocation of necessary resources is essential for TQM
success
Mosadeghrad (2005); Nizam and James (2005);
Whalen and Rahim (1994); Samuel (1999); Hafeez et al.
(2006)
B17 Short-term thinking Lack of long-term objectives and
targets leads to the loss
of credibility of a quality improvement programme
Mosadeghrad (2005); Whalen and Rahim (1994)
B18 High cost of implementing
TQM outweigh the
benefits
The primary obstacle identified in TQM implementation
is the high expenditure. Expenditures on TQM
implementation is to be considered as a strategic
investment
Hafeez et al. (2006); Sohal and Terziovski (2000); Khan

(2011); Samuel (1999)
B19 Lack of incentives and
human resource
practices
Lack of effective and efficient employees and lack of non-
monetary motivation mechanisms act as barriers to
implement TQM concepts
Mosadeghrad (2005); Hafeez et al. (2006); Salegna and
Fazel (2000)
B20 Lack of quality practices
and competent
employees
Most organisations are not able to realise real benefits of
TQM practices because of the implementation flaws
and lack of competent employees
Mosadeghrad (2005); Awan, Bhatti, Bukhari, and Qureshi
(2008); Salegna and Fazel (2000)
B21 Lack of participative
decision-making
Encouraging the employees to solve their problems and
involving them in the decision-making process will
increase their morale
Oakland (2011); Gupta et al. (2003)
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9
2009). ISM is a structured approach, which converts industrial
and academic expert
subjective data into quantitative values and provides a simple
structured model for a

complex system (Thakkar, Deshmuk, Gupta, & Shankar, 2005).
This methodology is inter-
pretative as the relationship of each variable with others is
identified and represented in a
matrix form. Using this matrix, driving and dependence powers
of individual barriers
have been identified, and barriers have been prioritised and
represented in a levelled
model. ISM methodology is more suitable for analysing barriers
in a structured way. It
organises barriers at different levels based on their importance
and interconnections are
also indicated.
Steps involved in the ISM technique (Raj, Shankar, & Suhaib,
2008) include the
following:
(1) Obtain various barriers that influence TQM implementation
from the literature
review and expert opinion.
(2) From the barriers identified, contextual relationship for each
barrier with others is
analysed and depicted in a structural self-interaction matrix
(SSIM) which indi-

cates pair-wise relationship between barriers.
(3) Reachability matrix is derived from the SSIM matrix and
transitivity is examined.
Reachability matrix converts subjective data into quantitative
values.
(4) The obtained reachability matrix is partitioned into different
levels.
(5) Barriers are categorised into four quadrants by applying
MICMAC analysis.
(6) The model is reviewed to examine inconsistency and
necessitate appropriate
modifications (if necessary).
Figure 1. Methodology.
Application of ISM methodology
Based on expert opinion and literature analysis, 21 major
barriers influencing TQM
implementation have been identified and analysed using the
ISM approach. A survey
has been conducted among 50 experts working in automotive
component manufacturing

organisations and who are responsible for TQM implementation
in their organisations.
A total of 35 responses were received. The response rate is
70%, which is acceptable
based on research studies (Barlett, Kotrlik, & Higgins, 2001).
Structural self-interaction matrix
The SSIM includes pairwise analysis among barriers and
relationship is depicted using
standard symbols based on a survey among experts. This survey
was performed through
online and electronic mail. The experts provided their opinion
based on a comprehensive
understanding of barriers and their interrelationships. The
consensus opinion of experts
has been used as inputs. The format used to gather input is:
‘Kindly assign the relation between Lack of top management
commitment and Atti-
tude of employees towards advanced quality practices in your
organisation (using V/A/
X/O)’.
Four symbols (V, A, X and O) have been used in this study to
denote the interrelation-
ship between two barriers i and j (Kannan et al., 2009; Vinodh,

Ramesh, & Arun, 2016):
V : Barrier i will lead to barrier j;
A : Barrier j will lead to barrier i;
X : Barriers i and j are interrelated; and
O : Barriers i and j are unrelated.
Using the contextual relationship, SSIM has been developed.
Based on expert opinion,
the relationship between barriers has been identified and SSIM
is shown in Table 2.
Reachability matrix
SSIM is transformed into a reachability matrix by translating
the symbols into binary
numbers 0s and 1s. The substitution of 1s and 0s is as per the
following rules (Govindan,
Azevedo, Carvalho, & Cruz-Machado, 2015; Kannan et al.,
2009; Raj et al., 2008):
(1) If (i, j) entry in SSIM is V, then (i, j) entry in the
Reachability matrix becomes 1
and (j, i) entry becomes 0.
(2) If (i, j) entry in SSIM is A, then (i, j) entry in the matrix
becomes 0 and (j, i) entry
becomes 1.

(3) If (i, j) entry in SSIM is X, then (i, j) entry in the matrix
also becomes 1.
(4) If (i, j) entry in SSIM is O, then (i, j) entry in the matrix
also becomes 0.
(5) Diagonal elements will be assigned 1 as both i and j are the
same.
Based on these relationships, the initial reachability matrix
shown in Table 3 is formed
which shows that the presence of entry 1 in the cell denotes the
existence of a relation
between the two barriers. Final reachability matrix shown in
Table 4 is iterated based
on a transitivity condition. It states that if barrier A is related to
barrier B and barrier B
is related to barrier C, then necessarily barrier A is related to
barrier C. Barriers with no
relationships are checked for transitivity and related using the
above condition. This indir-

ect relationship of each barrier provides a more accurate result
to build the ISM model.
Table 5 shows the formulation of driving and dependence power
matrix by summing up
values both row- and column-wise. Each row-wise addition
represents the driving
power of that barrier, which implies that these barriers drive the
barriers with which it
has a relation, and column-wise addition represents the
dependence power of that
barrier, which means that these barriers depend on the barriers
with which it has a relation.
Also, this metric is used as a base to build the level partition
shown in Table 6.
Level partitions
Level partition table is derived from the reachability matrix, in
which reachability and
antecedent sets are derived for individual barriers. The
reachability set is one which rep-
resents barriers that have an influence on it and the antecedent
set represents barriers that it
has an influence over. The intersection of these two sets
represents interdependence.
Levels are assigned based on driving power computed in the

SSIM.
This level partition is used as a basis for developing the ISM
model. Barriers with the
same reachability level and intersection level are positioned at
the same level in this matrix
and also represented in ISM hierarchy.
Developing the ISM model
The barriers prioritised using the above process are represented
in Figure 2. The model is
based on bottom to top approach. Lack of top management
commitment, poor planning,
lack of proper training and education, inadequate resources and
high cost of implementing
TQM are positioned at the bottom level of the model, indicating
significant driving power.
These barriers are root causes for other barriers at higher levels
within the ISM model.
These lower level barriers must be prioritised as major areas of
concern for managers
aspiring to implement TQM practices. Barriers at the top level
include lack of continuous
improvement culture, ineffective measures of quality
improvement, non-integration of

voice of consumer and supplier, attitude of employees towards
advanced quality practices
and non-usage of TQM tools, which have high dependence and
are not driving any other
factor. Any action on this factor will not affect any other factor;
however, any action on
any other factor will have an impact on these barriers due to
strong dependence.
MICMAC analysis
Matrice d’impacts croises-multiplication appliqué a un
classement (cross-impact matrix
multiplication applied to classification) is known as MICMAC
(Talib et al., 2011b).
The main objective of MICMAC is to cluster the barriers based
on their driving and depen-
dence power.
A graph is plotted with dependence power on X-axis and driving
power on Y-axis and
is shown in Figure 3.
The first quadrant represents linkage barriers; the second
quadrant indicates indepen-
dent barriers; the third quadrant represents autonomous barriers
and the fourth quadrant

indicates dependent barriers.
Managerial implications based on the findings from the
MICMAC analysis are as
follows:
Table 2. Structural self-interaction matrix.
B21 B20 B19 B18 B17 B16 B15 B14 B13 B12 B11 B10 B9 B8
B7 B6 B5 B4 B3 B2 B1
B1 V V V V V V V V V V V V X X V V V V X V X
B2 A A A A A A V A V A A A A X A A X A A X
B3 V V A A V A V V V V V V V V V V V V X
B4 X V V V A V V V V V V V V V V X X X
B5 V V A A V A V A V V V O V V V V X
B6 X X X O V A V V V V V A V V V X
B7 X A A X A A V X A A X A X A X
B8 A A O X V A V O A O A X V X
B9 A A A X A X V A A X X A X
B10 A A O V X A X A A X A X
B11 X A A A X A V X V A X
B12 X X A A A A A X V X
B13 A X A A A A X V X
B14 X V A A X A X X
B15 A A A A X A X
B16 A V V V V X
B17 A A A A X
B18 X X V X
B19 V V X
B20 A X

B21 X
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Table 3. Initial Reachability Matrix.

B21 B20 B19 B18 B17 B16 B15 B14 B13 B12 B11 B10 B9 B8
B7 B6 B5 B4 B3 B2 B1
B1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1
B2 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 0 0 1 0
B3 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0
B4 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
B5 1 1 0 0 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 0
B6 0 0 1 0 0 0 0 1 1 1 1 0 1 1 1 1 0 1 0 1 0
B7 1 1 0 1 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0
B8 1 1 0 1 1 0 1 0 1 1 0 1 1 1 1 0 0 0 0 1 0
B9 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0
B10 0 0 0 0 1 0 1 0 0 1 0 1 1 1 1 1 0 0 0 1 0
B11 0 0 0 0 0 0 1 1 1 0 1 1 1 0 1 0 0 0 0 1 0
B12 1 1 0 0 0 0 0 1 1 1 1 1 1 0 1 0 1 0 0 1 0
B13 0 1 0 0 1 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0
B14 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0
B15 0 0 0 0 1 0 1 1 1 1 0 1 1 0 1 1 1 0 0 0 0
B16 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0
B17 0 0 0 0 1 0 1 0 1 1 1 1 1 0 1 1 0 1 0 1 0
B18 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 0 1 1 0
B19 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0
B20 0 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0
B21 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0
5
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Table 4. Final Reachability Matrix.
B21 B20 B19 B18 B17 B16 B15 B14 B13 B12 B11 B10 B9 B8
B7 B6 B5 B4 B3 B2 B1
B1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1
B2 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 1
∗ 1 1∗ 0 1 0
B3 1 1 0 1
∗ 1 1∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0
B4 1 1 1 1 1

∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 1∗ 1 0
B5 1 1 0 0 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 0
B6 0 0 1 0 1
∗ 0 0 1 1 1 1 1∗ 1 1 1 1 0 1 0 1 0
B7 1 1 0 1 0 0 1
∗ 0 1∗ 0 0 0 1 1∗ 1 1 1 1∗ 0 1∗ 0
B8 1 1 0 1 1 0 1 0 1 1 0 1 1 1 1 0 0 0 0 1 0
B9 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0
B10 0 0 1
∗ 0 1 0 1 0 1∗ 1 1∗ 1 1 1 1 1 0 0 0 1 0
B11 0 0 0 0 1
∗ 0 1 1 1 1∗ 1 1 1 0 1 1∗ 1∗ 1∗ 0 1 0
B12 1 1 0 0 1
∗ 0 1∗ 1 1 1 1 1 1 0 1 1∗ 1 0 0 1 0
B13 0 1 0 1
∗ 1 0 1 0 1 1∗ 1∗ 1 1∗ 0 1 0 1 0 0 1∗ 0
B14 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1
∗ 0 0 0 1 0
B15 0 0 0 0 1 0 1 1 1 1 0 1 1 0 1 1 1 0 0 0 0
B16 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0
B17 0 0 0 0 1 0 1 0 1 1 1 1 1 0 1 1 0 1 0 1 0
B18 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 0 1 1 0
B19 1 1 1 1
∗ 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0
B20 0 1 0 1 1 0 1 1
∗ 1 1 1 1 1 1 1 1 0 0 0 1 0
B21 1 1 1

∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1∗ 1 0
1∗ entries are included to incorporate transitivity.
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Table 5. Driving and dependence power.
B21 B20 B19 B18 B17 B16 B15 B14 B13 B12 B11 B10 B9 B8
B7 B6 B5 B4 B3 B2 B1
Driving
power
B1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 21
B2 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 1
∗ 1 1∗ 0 1 0 9
B3 1 1 0 1
∗ 1 1∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 19
B4 1 1 1 1 1
∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 1∗ 1 0 20
B5 1 1 0 0 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 0 14
B6 0 0 1 0 1
∗ 0 0 1 1 1 1 1∗ 1 1 1 1 0 1 0 1 0 13
B7 1 1 0 1 0 0 1
∗ 0 1∗ 0 0 0 1 1∗ 1 1 1 1∗ 0 1∗ 0 12
B8 1 1 0 1 1 0 1 0 1 1 0 1 1 1 1 0 0 0 0 1 0 12
B9 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0 5
B10 0 0 1
∗ 0 1 0 1 0 1∗ 1 1∗ 1 1 1 1 1 0 0 0 1 0 12
B11 0 0 0 0 1
∗ 0 1 1 1 1∗ 1 1 1 0 1 1∗ 1∗ 1∗ 0 1 0 13
B12 1 1 0 0 1

∗ 0 1∗ 1 1 1 1 1 1 0 1 1∗ 1 0 0 1 0 14
B13 0 1 0 1
∗ 1 0 1 0 1 1∗ 1∗ 1 1∗ 0 1 0 1 0 0 1∗ 0 13
B14 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1
∗ 0 0 0 1 0 14
B15 0 0 0 0 1 0 1 1 1 1 0 1 1 0 1 1 1 0 0 0 0 10
B16 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 17
B17 0 0 0 0 1 0 1 0 1 1 1 1 1 0 1 1 0 1 0 1 0 11
B18 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 0 1 1 0 17
B19 1 1 1 1
∗ 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 18
B20 0 1 0 1 1 0 1 1
∗ 1 1 1 1 1 1 1 1 0 0 0 1 0 14
B21 1 1 1
∗ 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1∗ 1 0 19
Dependence
Power
11 14 8 11 18 5 20 13 21 18 17 17 20 15 21 16 13 10 7 19 1
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Table 6. Level partitions table.
Variables Reachability set Antecedent set Intersection Level
B1 B1,B2,B3,B5,B6,B7,B8,B9,B10,B11,B12,B13,B14,
B15,B16,B17,B18,B19,B20,B21
B1,B4 B1, 10
B2 B2,B4,B5,B6,B7,B8,B9,B13,B15
B1,B2,B3,B4,B5,B6,B7,B8,B10,B11,
B12,B13,B15,B14,B16,B17,B18,B19,
B20,B21

B2,B4,B5,B6,B7,B8,B13,B15 2
B3 B2,B3,B4,B5,B6,B7,B8,B9,B10,B11,B12,B13,B14,B15,
B16,B17,B18,B20,B21
B1,B3,B4,B16,B18,B19,B21 B3,B4,B16, B18,B21 8
B4 B2,B3,B4,B5,B6,B7,B8,B9,B10,B11,B12,B13,B14,B15,
B16,B17,B18,B19,B20,B21
B2,B3,B4,B5,B6,B7,B11,B16,B17,B21
B2,B3,B4,B5,B6,B7,B11,B16, B17,B21 9
B5 B2,B4,B5,B6,B7,B8,B9,B11,B12,B13,B15,B17,B20,B21
B1,B2,B3,B4,B5,B7,B11,B12,B13,B15,B16,
B18,B19,B21
B2,B4,B5,B7,B11,B12,B13,B15,B21 7
B6 B2,B4,B6,B7,B8,B9,B10,B11,B12,B13,B14, B17,B19
B1,B2,B3,B4,B5,B6,B7,B10,B11, B12, B14,
B15,B17,B19,B20,B21
B2,B4,B6,B7,B10,B11,B12,B14,B17, B19 4
B7 B2,B4,B5,B6,B7,B8,B9,B13,B15,B18,B20,B21
B1,B2,B3,B4,B5,B6,B7,B8,B9,B10,B11,B12,
B13,B14,B15,B16,B17,B18,B19,B20,B21
B2,B4,B5,B6,B7,B8,B9,B13,B15,
B18,B20,B21
3
B8 B2,B7,B8,B9,B10,B12,B13,B15,B17,B18,B20,B21
B1,B2,B3,B4,B5,B6,B7,B8,B10,B14,B16,B18,

B19,B20,B21
B2,B7,B8,B10,B18,B20,B21 5
B9 B7,B9,B11,B13,B15
B1,B2,B3,B4,B5,B6,B7,B8,B9,B10,B11,
B12,B13.B14,B15,B17,B18,B19,B20,B21
B7,B9,B11,B13,B15 1
B10 B2,B6,B7,B8,B9,B10,B11,B12,B13,B15,B17,B19
B1,B3,B4,B6,B8,B10,B11,B12,B13,B14,B15,
B16,B17,B18,B19,B20,B21
B6,B8,B10,B11,B12,B13,B15,B17,B19 4
B11 B2,B4,B5,B6,B7,B9,B10,B11,B12, B13,B14,B15, B17
B1,B3,B4,B5,B6,B9,B10,B11,B12,B13,
B14,B16,B17,B18,B19,B20,B21
B4,B5,B6,B10,B9,B11,B12,B13,B14, B17 4
B12 B2,B5,B6,B7,B9,B10,B11,B12,B13,B14,B15, B17,B20,B21
B1,B3,B4,B5,B6,B8,B10,B11,B12,B13,B14,
B15,B16,B17,B18,B19,B20,B21
B5,B6,B10,B11,B12,B13,B14,B15,B17,
B20,B21
4
B13 B2,B5,B7,B9,B10,B11,B12,B13,B15,B17,B18,B20
B1,B2,B3,B4,B5,B6,B7,B8,B9,B10,B11,B12,
B13,B14,B15,B16,B17,B18,B19,B20,B21
B2,B5,B7,B9,B10,B11,B12,B13,B15,B17,

B18,B20
3
B14 B2,B6,B7,B8,B9,B10,B11,B12,B13,B14,B15,B17,B20,B21
B1,B3,B4,B6,B11,B12,B14,B15,B16,B18,
B19,B20,B21
B6,B11,B12,B14,B15,B20,B21 6
(Continued )
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Table 6. Continued.
Variables Reachability set Antecedent set Intersection Level
B15 B5,B6,B7,B9,B10,B12,B13,B14,B15,B17
B1,B2,B3,B4,B5,B7,B8,B9,B10,B11,B12,
B13,B14,B15,B16,B17,B18,B19,B20,B21
B5,B7,B9,B10,B12,B13,B14,B15,B17 3
B16 B2,B3,B4,B5,B7,B8,B10,B11,B12,B13,B14,B15,
B16,B17,B18,B19,B20
B1, B3,B4,B16,B18,B21 B3,B4,B16,B18 8
B17 B2,B4,B6,B7,B9,B10,B11,B12,B13,B15,B17
B1,B3,B4,B6,B5,B8,B10,B11,B12,B13,
B14,B15,B16,B17,B18,B19,B20,B21
B4,B6,B10,B11,B12,B13,B15,B17 4
B18 B2,B3,B5,B7,B8,B9,B10,B11,B12,B13,B14,
B15,B17,B18,B19,B20,B21
B1,B3,B4,B7,B8,B13,B16,B18, B19,B20,B21
B3,B7,B8,B13,B18,B19,B20,B21 8

B19 B2,B3,B5,B6,B7,B8,B9,B10,B11,B12,B13,B14,
B15,B17,B18,B19,B20,B21
B1,B4,B6,B10,B16,B18,B19,B21 B6,B10,B18,B19,B21 8
B20 B2,B6,B7,B8,B9,B10,B11,B12,B13, B14,
B15,B17,B18,B20
B1,B3,B4,B5,B7,B8,B12,B13,B14,B16,
B18,B19,B20,B21
B7,B8,B12,B13,B14,B18,B20 6
B21 B2,B3,B4,B6,B7,B8,B9,B10,B11,B12,B13,
B14,B15,B16,B17,B18 B19,B20,B21
B1,B3,B4,B5,B7,B8,B12,B14,B18,B19,B21
B3,B4,B7,B8,B12,B14,B18, B19,B21 8
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(1) Linkage barriers: These barriers have a strong driving as
well as dependence
power, implying a careful consideration of these barriers, as any
action on these
barriers will have an effect on others and also a feedback
influence on each
other. They are represented in Quadrant I. Lack of
communication, lack of custo-
mer involvement, non-conduct of process capability and Six
Sigma studies, no
proper motivation, no periodic benchmarking, short-term
thinking and lack of par-
ticipative decision-making are found to be linkage barriers.
These barriers are very

important and should be highly concentrated. These barriers
must be eliminated
carefully since they have higher control of other barriers.
Elimination of these bar-
riers will greatly enable the implementation of a newer system.
(2) Dependent barriers: These barriers have a weak driving
power but strong depen-
dence power. They are represented in Quadrant IV. They are
greatly affected by
many barriers. Lack of continuous improvement culture,
ineffective measures of
quality improvement, non-integration of voice of consumer and
supplier, attitude
of employees towards advanced quality practices and non-usage
of advanced
TQM tools are found to be dependant barriers. Less importance
is given to
these barriers as they are controlled by other barriers.
Figure 2. Developed the ISM model.
(3) Driving barriers: They have a strong driving power but weak
dependence power.

They are represented in Quadrant II. These barriers are the
cause for various other
barriers. Lack of top management commitment, poor planning,
lack of proper
training and education, inadequate resources and high cost of
implementing
TQM practices are identified as the main driving barriers.
Elimination of these
barriers will provide greater support in implementation as they
drive various
other barriers.
(4) Autonomous barriers: These barriers have less driving and
less dependence power.
They are represented in Quadrant III. They are relatively
disconnected with few
links. There are no autonomous barriers in this study.
Results and discussions
By analysing the dominant barriers from the ISM model, the
difficulty involved in imple-
menting TQM practices in automotive industries can be
identified. The model provides a
framework for analysing the barriers and helps in understanding
the problems in the

implementation of a newer system. The ISM model shows the
order in which barriers
Figure 3. Results of MICMAC analysis.
need to be analysed. Reachability matrix shows the driving
values of each barrier; barriers
that have higher driving values are shown at the bottom of the
ISM model. Barriers at the
lower level have to be concentrated more and require immediate
action as they drive all
other barriers.
It can be inferred from the ISM model that lack of top
management commitment, poor
planning, lack of proper training and education, inadequate
resources, high cost of imple-
menting TQM outweighing the benefits, lack of incentives and
human resources and lack
of participative decision-making are at the bottom of the ISM
model with higher driving
power. These are the most dominant barriers for which an
organisation has to concentrate

and take additional efforts to eliminate them. These barriers are
source causes for barriers
located at top levels within the ISM model. For implementing
any newer system, manage-
ment commitment is most significant. Without management
commitment, bringing any
cultural change will not be possible. Implementation of TQM
involves compliance with
standard Quality Procedures, which requires proper planning
and training.
The barriers not considered in prior studies and addressed in the
present study are
described as follows: non-usage of advanced TQM tools such as
modified forms of
Quality Function Deployment and Failure Mode and Effect
Analysis which enable organ-
isations to attain higher quality performance; lack of customer
involvement in product
design and process execution; non-conduct of process capability
and Six Sigma studies
as organisations need to monitor process capability and sigma
level for attaining zero-
defect practices; no proper motivation for employees on
adopting quality practices; inef-

fective measures for quality improvement as quality
performance could be ensured using
appropriate measures in the absence of which quality
improvement could not be guaran-
teed; no periodic benchmarking with reference to quality
performance; non-integration of
voice of customer and supplier with reference to design and
manufacturing processes;
inadequate resources as without adequate resources,
implementation of quality practices
may be difficult; short-term thinking as quality concepts are
long-term oriented; high
cost of implementing TQM outweigh the benefits; lack of
incentives and human resource
practices; the organisation should encourage employees by
providing appropriate incen-
tives and supports, which creates a positive work culture; lack
of quality practices and
competent employees and lack of participative decision-making
as quality initiatives
involve decision-making at different levels. The organisation
should always consider sug-
gestions from all levels of the organisation, which also creates a
responsibility among

employees.
The barriers located at the middle of the ISM model having both
driving and depen-
dence show the interdependency of each barrier in the system.
Action taken on barriers
at the bottom of the ISM model helps to reduce the effort
required for removing these
middle-level barriers.
The barriers at the top level include lack of continuous
improvement culture, ineffec-
tive measures of quality improvement, non-integration of voice
of consumer and supplier
and attitude of employees towards advanced quality practices.
These barriers are depen-
dent type. Hence, concentration of bottom-level barriers enables
to cope with top-level
barriers.
Planning decides the success of any project that consumes
resources. To plan perfectly,
it becomes necessary to analyse and understand the influential
barriers influencing the
system. The present study focuses on the identification and
prioritisation of barriers influ-

encing the implementation of TQM practices in the automotive
sector, which provides
guidelines to top management, practicing managers and
decision-makers of the automo-
tive sectors. The results of this study are presented to the
practicing managers and their
opinion is that the modelling approach helped them to
implement the TQM system in a
systematic manner with less hurdles. The developed model acts
as a rational approach
through which barriers and their interrelationships are
characterised to prioritise and
implement the system in an effective way to deliver high-
quality products and increase
organisation efficiency.
As mentioned in Table 7, Talib, Rahman, and Qureshi (2011a)
developed a hierarchy
model of TQM practices that will help practicing managers and
experts pertaining to the
service sector in implementing TQM. They identified a list of
17 practices from the litera-

ture and used ISM methodology to develop a hierarchy model.
They found top manage-
ment commitment and communication as dominant practice
which an organisation has
to assign higher priority over others. Talib et al. (2011b)
developed a structural model
to analyse the barriers to TQM implementation in organisations.
They used an ISM tool
to analyse the relationship among the 12 barriers which are
derived from the literature
review and expert opinion. They identified that lack of top
management commitment
and lack of coordination between departments as the dominant
barriers having high
driving power and low dependency power. Their study mainly
focused on the service
sector. In the present scenario, the growth of the automotive
sector contributes signifi-
cantly to the country’s GDP. Hence, it becomes necessary to
concentrate on the automo-
tive sector and to identify the influential barriers of TQM
implementation in the
automotive sector. In the present study, 21 barriers influencing
the implementation of

TQM practices in the automotive sector have been identified
based on literature analysis
and expert opinion. Certain key influential barriers missed in
the past studies are also taken
into consideration and analysed in the present study. The
barriers are comprehensive to
reflect the managerial and technological advancements in the
present trend of the Indian
automotive sector. The present study results show that lack of
top management commit-
ment and poor planning are identified as the most dominant
barriers.
Conclusions
For effective implementation of TQM practices in the
automobile industry, barriers needs
to be identified and analysed. The barriers, if not eliminated,
affect the performance of
TQM practices, which in turn will affect the quality
performance of organisations. In
this context, this study presents an ISM-based approach to
analyse the interaction
Table 7. Comparison of results of the present study with prior
studies in the literature.
Research

Studies Focus of Study
Number of
factors/
barriers Dominant factors/barriers
Methodology
used
Present
Study
Barriers to TQM
practice in the
automotive sector
21 Lack of top management
commitment and Poor
planning
ISM
Talib et al.
(2011a)
TQM practices in the
service sector
17 Top management
commitment and
Communication
ISM
Talib et al.
(2011b)

Barriers to TQM
implementation
12 Lack of top management
commitment and lack of
coordination between
departments
ISM
among barriers of TQM practices in the automotive sector.
Based on the study, 21 barriers
have been identified as dominant barriers. The driver power-
dependence matrix provides
insight into the top management to understand the relative
importance and interdependen-
cies among TQM barriers. The most influential barriers are lack
of top management com-
mitment, poor planning, lack of proper training and education,
inadequate resources, high
cost of implementing TQM outweighing the benefits, lack of
incentives and human
resources and lack of participative decision-making. The
developed model provides a

clear understanding on the key influential barriers, which
enables managers to understand
the interaction among barriers to minimise or eliminate the
barriers.
Limitations and future scope
The present study focuses on the adoption of TQM practices in
the Indian automotive com-
ponent manufacturing sector. In the future, the scope for the
implementation of TQM prac-
tices can be examined in other sectors. Also, additional factors
also could be examined in
line with developments in quality management practices. And
the model could also be
validated using a structural equation modelling approach.
Disclosure statement
No potential conflict of interest was reported by the authors.
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AbstractIntroductionLiterature reviewIdentification of barriers
to implementation of TQM practicesResearch
gapMethodologyISM methodologyApplication of ISM

methodologyStructural self-interaction matrixReachability
matrixLevel partitionsDeveloping the ISM modelMICMAC
analysisResults and discussionsConclusionsLimitations and
future scopeDisclosure statementReferences
1
Political Science: Public Policy
Political Science: Public Policy
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Research Question
The most important question which is needed to research is how
public policies are proposed frequently. However, not all of the
policies are carefully proposed and implemented. In this regard,
this research aims to explore the myths and facts about public
policy and its implementation. Is this field of investigation
voluminous research already exists which can help to find the
desired questions. Therefore, this research targets to expose the
policy issues which are faced in the implementation of policies
and how such policies are influenced by our societies.

Note
In reference to the research question, a list of reliable sources is
added in this report which can help to support the research
questions along with the shreds of evidence. There are some
sources added in the list which verify that public policies are
proposed to a greater extent, but policies get affected due to
multiple myths and facts concerned to them. Thereby, related
literature reveals that by comparing and contrasting the myths
and facts the future policies can be proposed and implemented
effectively.
95
THE IMPACT OF TOTAL QUALITY MANAGEMENT ON
SERVICE
QUALITY, CUSTOMER ENGAGEMENT, AND CUSTOMER
LOYALTY IN
BANKING
Rosa Harimurti
1
, Tatik Suryani
2*
1
Department of Business and Marketing Management STIE
Perbanas, Jl. Nginden Semolo No.34-36,
Surabaya 60118, Indonesia
2

Master of Management STIE Perbanas, Jl. Nginden Semolo
No.34-36, Surabaya 60118, Indonesia
Email:
1
[email protected];
2
[email protected]
*Corresponding author
Abstract
The purpose of the research is to examine the impact of Total
Quality Management (TQM)
implementation on Service Quality, the effect of Service
Quality on Customer Engagement and Customer
Loyalty in banking industry. The other objective of the research
also to examine the effect of Customer
Engagement on Customer Loyalty. This research was conducted
in East Java Province which involved 209
State Owned Enterprises (SOE) bank customer’s as respondents.
All variables are measured by Likert scale
from bank customer perspectives. By Partial Least Square SEM
analysis, the research found that TQM
practices has positive effect on Service Quality, Service Quality
has positive effect on Customer Engagement
and Customer Loyalty and Customer engagement has positive
effect on Customer Loyalty. The implication
of this research is that SOE banks should implement TQM well
so that it has a positive impact on service
quality.

Keywords: Total quality management, service quality, customer
engagement, customer loyalty.
Introduction
The biggest challenge for global business is to
survive and achieve better business performance in
the global market (Zakuan, Yusof, Laosirihongthong,
& Shaharoun, 2010). Quality management has an im-
portant role for improving business performance.
Total Quality Management (TQM) practices will
affect the company's business performance (Psomas
& Jaca, 2016). Other research also found the positive
outcome of TQM implementation in banking (Petnji,
Marimon, & Casadesus, 2011).
State Owned Enterprise (SOE) banks as a global
business also faced many challenges to achieve better
performance. SOE banks in Indonesia have to com-
pete with foreign banks. SOE banks such as Mandiri,

BTN, BNI, and BRI should operate more efficiently
than foreign banks and provide world-class services in
order to win the competition. In fact, they are not as
efficient as Thailand and Philippines Banks (Mongid
& Muazaroh, 2017). In addition, the service quality
should be improved. Hence, in order to improve their
efficiency, it is important for SOE to improve their
TQM, their service quality and other business per-
formance. This competition is predicted to be even
higher in 2020 where the Asean financial sector inte-
gration will be carried out.
TQM research is essential because it could dis-
cover critical factor to support TQM implementation,
especially within the service sector which are rarely
studied (Al-Tabbaa, Gadd, & Ankrah, 2013; Mensah,
Copuroglu, & Fening, 2012). In detail, TQM research
is rarely done within banking service and its impact
toward marketing performance such as customer en-

gagement and customer loyalty.
TQM consists of five important dimensions such
as such as customer focus, management involvement,
continuous improvement, organizational context defi-
nition, and continuous improvement (Psomas & Jaca,
2016). In practice, to improve the banking service
TQM, company should consider these dimension.
This research is specifically focused in the effect
of TQM toward marketing performance which are
service quality (Psomas & Jaca, 2016). This is impor-
tant because customer engagement could affect custo-
mer engagement and loyalty (Hapsari, Clemes, &
Dean, 2017).
Total Quality Management (TQM)
Total Quality Management (TQM) is a way to
continuously improve performance at each level of
the process, in each functional area of an organization,

by using all available human and capital resources. By
implementing TQM, bank enable identifies customer
requirements, improve process to deliver services, and
reduce error in services (Baidoun, Salem, & Omran,
2018).
JMK, VOL. 21, NO. 2, SEPTEMBER 2019, 95–103 DOI:
10.9744/jmk.21.2.95–103
ISSN 1411-1438 print / ISSN 2338-8234 online
JURNAL MANAJEMEN DAN KEWIRAUSAHAAN, VOL. 21,
NO. 2, SEPTEMBER 2019: 95–103
96
The aim of TQM is to improve service quality in
the hope of fulfilling and satisfying the needs and
desires of the target customers. Previously studies
reported the benefits of TQM implementation such as
increasing the efficiency and productivity, market
share, employees’ morale, quality, employee perfor-
mance and competitive advantage (Sadikoglu &
Zehir, 2010; Zairi, 2013; Weckenmann, Akkasoglu,
& Werner, 2015; Rad, 2005).
The aim of TQM is to improve service quality in
the hope of fulfilling and satisfying the needs and

desires of the target customers. Psomas and Jaca
(2016), TQM components for the advancement of
service quality include: total employee involvement,
continuous improvement, ongoing training, team-
work, empowerment, commitment and support from
top management, democratic management style, cus-
tomer satisfaction focus and quality culture. After
reviewing the description above, this study focuses on
three dimensions of TQM are the quality of human
resources, customer focus, and employee knowledge.
Three of dimensions will be described in the follow-
ing explanation:
Human Resources (HR) Development Quality
TQM implementation is highly influenced by
top leaders’ commitment toward human resource
(HR) development. (Talib, Rahman, & Qureshi, 2013).
HR development result could be described as the
ability of employees to provide internal and consumer
services, such as speed of service and solutions to
applicable customer complaints in government banks
that apply to customers (Psomas & Jaca, 2016). The
company can develop HR through various programs
which enable employees to fulfill their job spe-

cifications, including on the job training (OJT), skills
training, and career development. Employee develop-
ment is also influenced by the commitment of each
employee to develop (Lau & Tang, 2009). The
quality of HR development is a measured based on
the competency development program or HR training
and employees’ commitment to develop competen-
cies (Psomas & Jaca, 2016).
Customer Focus
In TQM, customer focus is an essential part of
company to improve their service quality. Customers
focus consists of internal and external customers who
will determine the direction of the company's quality.
Internal customers are the company or employees
who are responsible for customers, whereas external
parties are customers who determine the direction of
the company's quality. The customer focus can be
measured based on several indicators (Psomas &
Jaca, 2016). These indicators are ease of customer
complaint, consumer evaluation, and consumer treat-
ment.
Employees Knowledges

Employee knowledge is important toward cus-
tomer service. Employee who has good or enough
knowledge could explain and solve customer pro-
blem. This knowledge is practiced when the emplo-
yee informs, handle complaints, and give other ser-
vices to the customers (Psomas & Jaca, 2016).
Service Quality
In banking industry, service quality has strategic
role for gaining competitive advantage. It’s difficult to
differentiate product in banking industry, so service
quality become one of the attribute to distinguish bank
from another bank. According to Khorshidi ̧ Naghash,
and Mohammadian (2014) high quality of services
enable bank achieving competitive advantage.
There are many definitions and concept about
service quality. Most of previously studies revealed
that satisfaction is the result of a process of com-
parison between customer’s expectations and percep-
tions of performance (Shayestehfar & Yazdani, 2019).
When customers perceive about many kinds of
service attributes, it means that they evaluate about
quality of services.
Zeithaml et al. (1988) in Lin (2012), identifying
SERVQUAL dimensions into five aspects as follows:
personnel appearance.
properly and accurately.

and provide prompt service.
-
ployees, as well as their ability to convey trust and
confidence.
service providers to their customers.
SERVQUAL model is chosen to measure
service quality because it could portrait service
dimensions and it could be measured based on the
banking service customer perspective (Fauzi &
Suryani, 2019).
An excellent service is a service that prioritizes
customers with high quality who prioritize fast, relia-
ble service, understand customer needs, in this case
customer focus (Rahmayanti, 2010). If the imple-
mentation of service quality is implemented in an
integrated manner, it will make customers feel valued.
https://www.emeraldinsight.com/author/Qureshi%2C+MN
Harimurti: The Impact of Total Quality Management on Service
Quality
97
TQM Implementation and Service Quality
Based on the description above, the imple-

mentation of TQM on the company will improve the
quality of service to customers (Calvo-Mora, Picón,
Ruiz, & Cauzo, 2014). TQM implementation could
affect quality service improvement (Psomas & Jaca,
2016). Company whose top management implement
TQM will have higher commitment to develop their
HR. Furthermore, they will also be more focused on
their customer as well having higher concern toward
employee knowledge. All these factors will affect the
company service quality toward its customer. Hence,
based on The first hypothesis in this study is:
H1: Implementation of the TQM Dimension has
positive significantly effect on service quality in
banking industry.
Customer Engagement (CE)
Customer engagement occurs on two parties
who will be involved in a relationship with marketing
are between consumers or companies. The occurrence

of involvement between customers and companies is
because there are dynamic relationships and emotio-
nal attachments in the transaction process. So et al.
(2012) in Hapsari et al. (2017) identify five dimen-
sions of customer engagement:
1. The level of a consumer’s perception or sense of
belonging to the brand (identification);
2. Levels of attention that focus and connect with the
brand (attention);
3. Level of passion and interest in brand (enthu-
siasm);
4. Pleasant conditions where the customer animates
with a positive response when playing the role of
the customer brand (absorption);
5. Various levels of participation that customers have
with brands (interaction).
Customer engagements play an important role in
a company, where in making customer engagement

or customer involvement as a company's marketing
strategy, it will achieve the company's goals of in-
creasing customer loyalty. Loyalty increases because
there is a positive response from consumers to the
company that raises interest in other consumers (So,
King, Sparks, & Wang, 2016). CE represents a per-
son's psychological state, characterized by a certain
level of intensity that plays a central role in the
process of customer involvement. Apart from that it is
an impact in the CE process. Thus, CE is defined as a
multidimensional concept consisting of cognitive,
emotional, and behavioral dimensions (Brodie et al.,
2011 in Fernandes & Esteves, 2016). According to
Hapsari et al. (2017), Dhasan, Suwanna, and Theingi
(2017), customer engagement is measured based on
two indicators: (1) a sense of pride in the company,
(2) Feel comfortable with the company.

Customer Loyalty
Customer loyalty is a deeply held commitment
to repurchase or rebuy preferred products or services
consistently in the future. (Ribbink, van Riel, Liljan-
der, & Streukens, 2004). Loyal customer will most
likely buy rather than a normal customer. Griffin
(2002) stated that a consumer is said to be loyal or
loyal if the consumer shows buying behavior regu-
larly or there is a condition which requires consumers
to buy at least twice in a certain time interval.
Kotler and Keller (2012) argue that, loyalty is a
commitment held deeply to buy or support a product
or service that is favored in the future even though the
influence of the situation and marketing efforts has
the potential to cause customers to switch. According
to Hapsari et al. (2017), Dhasan et al. (2017), custo-
mer loyalty is measured from consumer behavior
such as: their willingness to recommend to others,
their preferences to the product and intensity to con-
sume / buying products.
Customer loyalty is not only about attitude but

also behavior (Suryani, 2013). So, in many research
for measuring customer loyalty can be seen form atti-
tude (affective, cognitive, and conative components)
and behavior related with product or services.
Service Quality on Customer Engagement (CE)
and Customer Loyalty
Maintaining the quality of service so that it
remains good is very necessary for the company so
that the customer's perception of the company is
positive. The quality of service will have a positive
impact on companies CE by involving the compe-
tencies of each internal company to customers. The
decision is on the part of the customer that the quality
received can meet their needs and desires. If the
quality received by the customer is in line with ex-
pectations or even exceeds, the customer feels proud,
happy, satisfied, and their expectations are realized.
The research results of Dhasan et al. (2017)

which show that, from the functional side of service
quality, it has a significant effect on customer enga-
gement (CE) in the offline context. Consumers will
respond positively to services that are accepted by
recommending to others. Companies need to improve
service quality to maintain and increase consumer
loyalty. The positive response that consumers will
give when the quality received can be felt to meet the
NO. 2, SEPTEMBER 2019: 95–103
98
needs of consumers is to be loyal to the selected
product. Kotler and Keller (2012) also argue that
loyalty is a commitment held deeply to buy or support
a product or service that is favored in the future even
though the influence of the situation and marketing
efforts have the potential to cause customers to

switch.
Lin (2012), which states that multi - channel ser-
vice quality as measured by SERVQUAL dimensions
has a significant effect on consumer loyalty. These
dimensions are tangibility, responsiveness, and empa-
thy. In accordance with the opinion of Zeithaml et al.
(1988) in Lin (2012) Tangibility dimensions in the
form of physical evidence, facilities, and personal
appearance. The responsiveness dimension is willing-
ness to help customers and provide fast service, and
the empathy dimension is how service providers pay
attention to individuals by providing solutions to
customer complaints. In addition, the results of testing
So et al. (2016), which states that service brand
evaluation with indicators of service quality, perceiv-
ed value, and customer satisfaction, has a significant
effect on brand loyalty but not as much as other
variables. Then the second and third hypotheses of
this study are:
H2: Service quality has a significant positive effect
on customer loyalty in banking industry.
H3: Service quality has a significant positive effect
on customer engagement in banking industry.
Customer Engagement (CE) and Customer Loyalty
The customer concept plays an important role in
building customer loyalty to the brand. Interaction
with companies, facilitate better business decisions
and encourage customer loyalty. Dhasan et al. (2017)
in their research explored the impact of customers
online and their effect on customer brand loyalty. The
role of online experience has a greater influence on

the positive influence of customer loyalty on the
brand.
In addition, customers are willing to share their
experience and quality of service with their family
and friends and also with service providers, (Theingi
et al., 2016 in Dhasan et al., 2017). The company will
strive to gain a competitive edge on the quality of
service that given to customers, because customers
with a positive mindset will have an impact on
increasing positive WOM to relatives or other people.
So et al. (2016), also states that customer engagement
has a significant effect on brand loyalty. states that
overall customer engagement factors have the greatest
influence on loyalty when compared to other varia-
bles. So the fourth hypothesis of this study is:
H4: Customer engagement has a significant positive
effect on customer loyalty in banking industry.
Figure 1. The conceptual research framework
Research Methods
This study use survey methodology using ques-
tioner as the instrument to gather data. Variables were
measured by Likert scale with five categories of res-
ponses ranging from strongly disagree (score 1) to
strongly agree (score 5) where respondents were
asked to indicate the level of agreement or disagree-
ment with some statements related to the object
(Malhotra, 2010). Sample selected based on purpo-
sive sampling. They must be SOE bank customers in

Surabaya and Sidoarjo, and Gresik.
There are two steps required to gather data,
which are:
1. Finding Bank customer which meet certain
criteria, such as: customer of SOE bank who are
actively using the banking service at least one
every two weeks and live in Surabaya or Sidoarjo
or Gresik.
2. Customer fill the questioners, including their pro-
file and the questions regarding this study.
Purposive sampling technique where the sample
is selected according to several criteria (Sugiyono,
2015) is used in this study. The criteria used in this
study are people who have signed up as the bank
customer for at least two years, and within one month
the customer must interact minimum of two times
within the bank.
In total, 235 questionnaires were distributed to
respondents who meet the sampling criteria. Accord-
ing to the previous research conducted by Ghozali
and Latan (2014), the sampling size is sufficient to
represent the population. However, from 235 ques-
tionnaires twenty-six questionnaires were not returned
to the author. In the end there are 88.94% response
rate within this study.
WarpPLS 4.0 is used to analyze the data in this
study. WarpPLS 4.0 is one of many alternative
method for structural equation models (SEM), which
is to test simultaneously the relationship between

latent constructs in linear or nonlinear relationships
with many indicators in the form of A mode
(reflective), B mode (formative) and or M mode
Quality
99
(MIMIC) (Ghozali & Latan, 2014). The steps of this
research method include:
1. Model conceptualization
2. Determine the method of analysis algorithm
3. Determine the resampling method
4. Draw a path diagram
5. Evaluate the model
Results and Discussion
Validity and Reliability Analysis
The analysis of validity and reliability is present-
ed in Table 1. The items are valid if the loading factor
value is between 0.6–0.7. Hence, all the items are
valid (Ghozali & Latan, 2014)

Table 1
Indicator Loadings and Latent Variable Coefficient
Item
Factor
Loading
P Value
Cronbach's
Alpha
Composite
Reliability
HR1 0.892 <0.001 0.913 0.935
HR2 0.867 <0.001
HR3 0.817 <0.001
HR4 0.874 <0.001
HR5 0.854 <0.001
CF1 0.8 <0.001 0.886 0.913
CF2 0.82 <0.001
CF3 0.751 <0.001
CF4 0.815 <0.001
CF5 0.841 <0.001
CF6 0.758 <0.001
EK1 0.78 <0.001 0.868 0.905
EK2
EK3
0.833
0.738
<0.001
<0.001

EK4 0.861 <0.001
EK5 0.833 <0.001
SQ1 0.755 <0.001 0.917 0.932
SQ2 0.741 <0.001
SQ3 0.762 <0.001
SQ4 0.78 <0.001
SQ5 0.788 <0.001
SQ6 0.825 <0.001
SQ7 0.827 <0.001
SQ8 0.818 <0.001
SQ9 0.685 <0.001
CE1 0.786 <0.001 0.913 0.933
CE2 0.847 <0.001
CE3 0.814 <0.001
CE4 0.867 <0.001
CE5 0.85 <0.001
CE6 0.847 <0.001
CL1 0.874 <0.001 0.924 0.939
CL2 0.783 <0.001
CL3 0.845 <0.001
CL4 0.801 <0.001
CL5 0.817 <0.001
CL6 0.849 <0.001
CL7 0.827 <0.001
The reliability analysis in Table 2 show that the
AVE root value of HR development (HR) is 0.74.
Customer Focus (CF) value is 0.64, Employee Know-
ledge (EK) value is 0.66, and Service Quality (SQ) is
0.6, Customer Engagement (CE) value is 0.7 and

lastly Customer Loyalty (CL) value is 0.69. Accord-
ing to these results, all the instrument used to measure
the variable are all reliable. This is because the com-
posite reliability value range between 0.6-0.7
(Abdillah & Jogiyanto, 2015).
Table 2
Correlations Among Latent Variables and Errors
HR CF EK SQ CE CL
AVE 0.74 0.64 0.66 0.60 0.70 0.69
Descriptive analysis in Table 3 shows that all the
variables which are TQM implementation, Service
Quality, Customer engagement and Customer Loyal-
ty have mean in high category. It means bank have
implemented TQM in good conditions, they have
high service quality. From SOE bank it’s a good asset
for gaining advantage in facing competition with
private bank and financial institutions who deliver the

same services.
Table 3
Descriptive Analysis of Variables
Variables Mean Category
TQM Implementation 3.99 High
HR Development Quality (HR) 4.05 High
Customer Focus (CF) 3.91 High
Employee Knowledge (EK) 4.02 High
Service Quality 4.01 High
Customer Engagement 3.73 High
Customer Loyalty 3.80 High
Results of PLS-SEM Analysis
The result of data analysis conducted using
WarpPLS 4.0 is shown in Figure 2. The results show
that:
1. Human Resource Management development qua-
lity (HR), Customer Focus (CF), and Employee

Knowledge (EK) are the dimensions of TQM im-
plementation. HR development quality has posi-
tive effect significantly Service Quality (p value <
0.01 smaller than required, which is < 0.01). The
direction of the relationship between HR quality
and service quality is positive 0.274. Then the rela-
tionship between customer focus (CF) and service
quality (SQ) has also significant with p value <
0.01. The path coefficient value of 0.221 indicates
that the direction of the relationship between
NO. 2, SEPTEMBER 2019: 95–103
100
customer focus and service quality is positive. The
relationship between relationship between emplo-
yee knowledge (EK) with service quality is also
significant with a value of p value < 0.01.

Figure 2. Outer model framework
Table 4
Path Coefficient
HR CF EK SQ CE CL
SQ 0.274 0.221 0.436
CE 0.614
CL 0.315 0.591
The path coefficient value of 0.436 means that the
results show that the relationship between know-
ledge of employees (KE) and service quality (SQ)
is positive.
2. TQM implementation has positive effect signifi-
cantly on Service Quality (SQ) (p < 0.01) and the
coefficient value 0.31).
3. Service quality has positive significantly effect on
customer engagement (p value <0.01). The direc-
tion of the relationship between service quality

and customer engagement is positive because the
path coefficient value is 0.614. So the H2 hypo-
thesis which states service quality (SQ) has a
positive significant effect on Customer Engage-
ment (CE) is accepted.
3. Service quality has positive effect significantly on
customer loyalty (p value < 0.01). The direction of
the relationship between service quality and custo-
mer loyalty is positive with path coefficient value
is 0.315. So, H3 hypothesis which states service
quality (SQ) has a significant positive effect on
Customer Loyalty (CL) is accepted.
4. Customer engagement has positive effect sig-
nificantly on customer loyalty (p value < 0.01).
The direction of customer engagement and custo-
mer loyalty is positively with path coefficient
value is 0.591. It means that the H4 hypothesis
which states Customer Engagement (CE) has a

significant positive effect on Customer Loyalty
(CL) is accepted.
Discussion
The purpose of this research is to examine the
effect of the Implementation of Total Quality Mana-
gement (TQM) from customer perceptions on Service
Quality, Customer Engagement, and Customer
Loyalty in government bank.
Effect of the Implementation of TQM
on Service Quality
The result on this study show that the implemen-
tation of TQM could positively impact the service
quality of SOE banks. This result is also consistent
with the previous study conducted by Psomas and
Jaca (2016). Previous studies and this study showed
that the TQM implementation contributes to company

performance, such as financial performance, product/
service quality, customer satisfaction, and operational
performance (Psomas & Jaca, 2016).
These results indicate that better the quality of
human resource development, the better will it affect
the company TQM implementation. Similarly, the
better company employee knowledge will also affect
the company TQM implementation.
Research in small service organization in Malay-
sia also found that implementation of TQM has
positive significantly effect on satisfaction and service
quality (Ooi, Lin, Tan. & Chong, 2011). Service qua-
lity provided by the bank to its customer will also
improve it is supported by better human resource
quality and better human resource management.
Furthermore, other factor such as Customer
Focus play important role in TQM implementtation
(Psomas & Jaca, 2016). Customer centric company

view that ultimately the customer will judge the
company quality. Company who actively listen and
try to meet customer expectation will serve customer
better.
In addition, customer centric company will
involve customer in their product development.
According to Flynn et al. (in Herzallahah, Gutiérrez-
Gutiérrez, & Rosas, 2014), customer development in
product or service development will reduce future
potential risk problem within the production process.
By involving customer, the production process will
result in a product/service that meet the customer
needs.
Effect of Service Quality on Customer Engagement
(CE)
The result show that service quality has a signi-
ficant positive effect toward customer engagement in

SOE banks. This study is consistent with the previous
Quality
101
study conducted by Dhasan et al. (2017) which
showed that based from the the functional side of
service quality, it has a significant effect on customer
engagement (CE) in the offline context. The functio-
nal aspect within banking service quality consist of
products knowledge, ability to serve faster, ability to
help customer, willingness to overcome customer
complaints, and employee hospitality and courtesy
when serving the customer. If the banks give a quality
service toward its customer, customer are most likely
willing to engage with the bank. Furthermore, custo-
mer who had served with good quality service will
also engage with other customers (Dhasan et al.,

2017). This positive experience regarding the bank
service will drive customer engagement on the
company.
In this study, customers were giving good marks
on bank who provide secure online transactions. This
secure online transaction is shown by the availability
of PIN code change which could protect the custo-
mers. In addition, this initiative is positively perceived
by the customer. Therefore, customers are more will-
ing to engage with SOE banks. Security as a part of
service quality could determine the superiority of
service quality offered by a company. In the end the
good and bad service quality provided by the com-
pany could affect the customer engagement toward
SOE banks.
Effect of Service Quality on Customer Loyalty
The results show that service quality has a signi-

ficant positive effect on customer loyalty at govern-
ment banks. The results of the study are the same as
the results of previous research conducted by Lin
(2012), which states that the multi-channel service
quality supported by the SERVQUAL dimensions
have a significant effect on consumer loyalty. Cus-
tomer who perceived a good service quality will stay
loyal as a customer for the bank. They are less willing
to change their banks, which ultimately show their
loyalty toward the bank.
This study result also in line with the previous
study conducted by So et al. (2016), which proved
that service quality has a significant effect on loyalty.
There are three key element which contributes in ser-
vice quality, those are employee responsiveness when
serving its customer, the banking atmosphere which
result in more comfortable customer. All of these will
affect customer loyalty. Banks should view this as an

important factor because if it’s done correctly, the
could save their promotion budget. Furthermore, loyal
customer could also act as a good marketer for the
bank products and service. When the customer is
loyal toward a bank, customer will more likely to only
use the service or product offered the banks rather
than churning or using other banks (Kotler & Keller,
2012).
Effect of Customer Engagement (CE) on Customer
Loyalty
Based on the analysis, the results show that
customer engagement has a significant positive effect
on customer loyalty at government banks. This result
was consistent with the previous studies conducted by
Hapsari et al. (2017) which states that customer enga-
gement has a significant positive effect on passenger
loyalty. Customer who engage with the banks could
be viewed as a loyal customer and will most likely
stay with the same bank for a longer time or commit-
ment,
The results of the study also support the previous
study conducted by Dhasan et al. (2017) who found
that customer engagement in an offline context has a

significant effect on consumer loyalty. In this study,
the determinant of offline is that people say positive
things and recommend to others. In addition, the
research conducted by So et al. (2016), also states that
customer engagement has a significant effect on
brand loyalty. This research also found that overall
customer engagement factors had the greatest influ-
ence on loyalty when compared to other variables,
such as satisfaction.
The more positive customer involvement in the
company, the more it will increase customer loyalty to
the SOE bank they choose. The positive engagement
from customer toward the bank is shown as their
intention to promote the superiority of the bank pro-
ducts/service to the other customers, telling a positive
experience, and recommend the bank product/service
to their friends or banks customers. Customer who
engage with bank tend to show several behaviors such
as identification, enthusiasm, and absorption which
also included in the Customer Engagement variable
(So et al., 2012 in Hapsari et al., 2017).
Conclusion
The result of this study shows that the imple-
mentation of TQM which focused on three dimensi-
ons of TQM including Human resource development
quality, Customer Focus and Employee knowledge
could positively affect toward SOE bank service qua-
lity. Better service quality will result in improvement
toward Customer Engagement (CE) and SOE bank
customer loyalty. In addition, Customer Engagement
(CE) itself could positively affect SOE bank customer

loyalty.
NO. 2, SEPTEMBER 2019: 95–103
102
The implication of this study show that within
the implementation of TQM, SOE bank should acti-
vely seek to improve human resource development,
customer focus, and improve employee knowledge.
All of these three could contribute positively toward
the improvement of SOE bank service quality. In
order to improve employee knowledge, SOE bank
should conduct training program, coaching, and
knowledge sharing within the workplace. Thus, a
great service quality will positively affect customer
engagement and customer loyalty.
Secondly, the service quality SOE bank should
focus is to improve employee respond on solving cus-

tomer problem when they engage with their problem.
In result this will improve positive customer expe-
rience from the customer.
Thirdly, SOE Banks should not neglect their
technology quality to support their customer. The
development of digital technology enables customer
to access the banks without any constraint such as
time and place. Technology allow customer to get
faster information and it also improves customer ease
of access toward the banks. These are also viewed as
important in the perspective of customer.
There is also limitation of this study. The future
study should review all the TQM dimensions. This
will help company to discover the full implementation
within TQM. This study recommends future study to
refer to Voon, Abdullah, Lee, and Kueh (2014) TQM
implementation which includes total employee invol-
vement, continuous improvement, continuous train-

ing, teamwork, empowerment, top management com-
mitment and support. Additionally, there is also an
alternative dimension which were used by Talib et al.
(2013) who have more dimensions and tailored to the
banking industry. However, the consequent of using
that dimensions is to involve not only the customer
but also the bank’s employee.
Lastly, future studies could also be improved by
increasing the region scope and the bank type. If it is
possible future study should also cover the entire
banking industry in Indonesia. In addition, future
study could also improve the Bank scope which is not
only cover the SOE Banks, but also private Banks,
conventional and Islamic bank.
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