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Service quality analysis and improving customer satisfaction in automobile
- 1. INTERNATIONAL JOURNAL Research and Development (IJIERD), ISSN 0976 –
International Journal of Industrial Engineering OF INDUSTRIAL ENGINEERING
6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
RESEARCH AND DEVELOPMENT (IJIERD)
ISSN 0976 – 6979 (Print)
ISSN 0976 – 6987 (Online)
Volume 4, Issue 1, January - April (2013), pp. 41-51
IJIERD
© IAEME: www.iaeme.com/ijierd.asp
Journal Impact Factor (2013): 5.1283 (Calculated by GISI) ©IAEME
www.jifactor.com
SERVICE QUALITY ANALYSIS AND IMPROVING CUSTOMER
SATISFACTION IN AUTOMOBILE SERVICE INDUSTRY USING QFD
Thirumanas K R1, K C Joseph2
1
Asst Professor, Deptt. Of ME, IIET Kothamangalam, India.
2
HOD, Deptt. Of ME, Mangalam, Ettumanoor, India.
ABSTRACT
QFD is a technique used in the Total Quality Management (TQM) field for converting
customer’s vague language into technical language. Service quality can be defined as the
collective effect of servicing performances which determine the degree of satisfaction of a
user of the service. In other words quality is the customer’s perception of a delivered service.
In the present study, the customer satisfaction/ dissatisfaction has been measured using a five
point Likert scale. The QFD is used as a tool. The tool comprises of the following attributes
viz. customer needs (What), technical requirements (How), Relationship matrix, Ranking of
customer language, Ranking of technical language and Correlation matrix. Analysis of data
revealed that the present study helps in the organization to measure their service performance,
to guide and expedite the development of innovative services through the identification of
weak attributes which are crucial to customers. In many service development processes, the
resource and time allocation are wasted because of the lack of proper estimation service
quality attributes.
Keywords: Quality Function Deployment; QFD, Service quality analysis, Total Quality
Management (TQM) House of quality, Surveys Paper type Case study.
1. INTRODUCTION
The subject of service quality has aroused considerable recent interest among business
people and academics. Of course, buyers have always been concerned with quality, but
the increasing competitive market for many services has led consumers to become more
selective in the services they choose. Conceptualizing the quality for services is more
complex than for goods. A service is an act or performance offered by one party
to another .In this competitive era, for any organization such as Automobile service
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- 2. International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
industries it is necessary to provide quality service to retain their customers’. Service quality
has major influence on customer satisfaction as customers buy products or services and on
whether they continue to do so. With the aim of sustaining long term relationships with their
customers, many businesses have changed their strategic focus to emphasize customer
retention (Peng and Wang 2006). Preserving their long term customer relationships requires
that these businesses both measure and appropriately adjust the quality of their customer’s
service.
2. SERVICE INDUSTRY
Indian service industries form the backbone of social and economic development of
the country. Service sector in India today accounts for more than half of India’s GDP. India
stands out for the side and dynamism of its service sector. The contribution of the service
sector to the Indian economy has been manifold. It has a share of 55.2 % in gross domestic
product (GDP) and is growing by 10% annually.
3. SERVICE QUALITY
Quality is an extremely difficult concept to define in a few words. At its most basic,
quality has been defined as conforming to requirements .This implies that organizations must
establish requirements and specifications; once established, the quality goal of the various
function of an organization is to comply strictly with these specifications. Many analyses of
service quality have attempted to distinguish between objective measures of quality and
measures which are based on the more subjective perceptions of customers.
4. BACK GROUND
Due to the absence of tangible manifestations, measuring service quality can be
difficult but there are possible research approaches... It is not sufficient for companies to set
quality standards in accordance with misguided assumptions of customers’ expectations. A
further problem in defining service quality lies in the importance which customers often
attach to the quality if the service provider is distinct from its service offers – the two cannot
be separated as readily as in case of goods
Because of the intangible characteristics of service, the measurement and evaluation is
quite difficult. Also there exists a non-linear relationship between the customer satisfaction
and the perception of the service. Being this is the scenario; a country like India who has a
major GDP share from the service firms, the service quality issues should be well addressed.
5. KANO MODEL OF CUSTOMER SATISFACTION
The Kano Model of Customer (Consumer) Satisfaction classifies product attributes
based on how they are perceived by customers and their effect on customer satisfaction.
These classifications are useful for guiding design decisions in that they indicate when good
is good enough, and when more is better. The Kano Model of Customer satisfaction (Figure
1) divides product attributes into three categories: threshold, performance, and excitement. A
competitive product meets basic attributes, maximizes performances attributes, and includes
as many “excitement” attributes as possible at a cost the market can bear.
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6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
Kano model
6. QUALITY FUNCTION DEPLOYMENT
The origin of QFD is traced to the quality tables that were developed in Kobo
Shipyard, Japan in the year 1960. The formal appearance of QFD as the TQM technique was
made possible through the works of Yoji Akao in the year 1972 (Akao and Mazur, 2003).
Thereafter, the popularity of QFD spread across the world. Also, a large number of case
studies reporting QFD’s successful implementation and its benefits appeared in literature
(Chan and Wu, 2002). A few researchers have brought out different definitions (Zairi and
Youssef, 1995), leading to the proposition that QFD is a technique used for converting
customers’ vague languages into technical languages. Therefore QFD facilitates deployment
of customers’ voices in the practising environment. In this era of increasing competition,
QFD is supposed to reveal the hidden and open voices of customers and support the
organizational managers in meeting market requirements. The implementation of QFD
progresses through the development of a composite matrix known as House of Quality
(HOQ). The conceptual features of HOQ are shown in Figure 1. As shown, HOQ consists of
six main sub matrices (Kumar and Midha, 2001; Han et al., 2001). The construction of HOQ
begins by developing a customer language matrix, whose inputs are vague customer voices.
Consequently, the second matrix titled ‘ranking of customer languages’ is developed. The
values indicating the ranks of the customer languages are determined by considering the
competitors’ performance and companies’ affordability in fulfilling the customer languages.
The third matrix, consisting of the technical languages corresponding to the customer
languages, is developed. The fourth matrix is constructed by entering values to represent the
degree of relationships between customers and technical languages. The fifth matrix,
consisting of values representing the ranking of technical languages, is then formed. The
sixth and last major sub matrix of HOQ is the correlation matrix, which is constructed by
entering the values to represent the correlation among the technical languages. All the
matrices developed are joined to construct HOQ. The construction of HOQ requires the
involvement of personnel with adequate theoretical and practical knowledge about the
customers’ voices that are under consideration. Following the development of HOQ, the
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6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
engineers and production managers are required to study the completed QFD’s contents and
develop target values and process plans. Thus the customer voices are translated into
technical languages through the development of HOQ, which penetrates into the field of
practice. Initially, QFD was used as a product development (Lockamy and Khurana, 1995)
technique. However, during recent times, it has proven to be a feasible technique for several
applications where customer voices are required to be translated into technical languages
(Chan and Wu, 2002; Sahney et al., 2003; Sahney et al., 2004)
7. HOUSE OF QUALITY
The house of quality converts the customer requirements into design requirements
that meet specific target values and matches that against how an organization will meet those
requirements.
Figure 1: House of Quality
8. CASE STUDY
In order to examine the aspects of QFD in a service Quality, a case study was carried
out in a maintenance intensive automobile service station. The present study focuses on the
measurement of current service quality of a typical automobile dealership in an Indian city.
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6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
The main objectives of the present study are to test the reliability of the developed data and to
develop, propose a QFD for service quality improvement. Here the investigator administered
QFD from a sample of 71 customers in automobile service industry, i.e. a representative
survey of respondents, owners of one of the Branded vehicles. The reliability of tools was
checked using Cronbach’s alpha method and there by standardized.
QFD process utilizes a set of matrix diagrams which are related to one another. The
QFD matrix (house of quality) is the basis for all future matrices needed for the QFD
method. The number of matrices is depends on the scope of the project. The process
continues until each objective is refined to an actionable level (Besterticld, 2006). But
researchers give priority to the initial house of quality matrices (Park and Kirn, 1998; Tan
and Pawitra, 2001, 2003: Min and Kirn. 2008; Birdogan et a/, 2009), Through this matrix,
action plans are developed to improve the service quality. Identifying basic customer needs
named "Whats" constitutes the starting point of the HoQ and stand on the left of the house. It
follows defining the customer priority level of these needs by translating them into numeric
values.
8.1 Defining customer needs and customer priority level
As stated in the conceptual background, defining customer needs constitutes the first
step of the QFD model (Matzler and Hintehubcr, 1998). In the process of defining
importance, the 71 respondents were asked to mark the importance of attributes according to
a five point Likert scale. The left extreme of the scale is marked as least important and the
right extreme as the most important (Besterfield, 2006). The scale reliability analysis was
conducted. The Cronbach's alpha value was got as 0.991, which is in an acceptable level (De
Vellis, 1991). An arithmetic mean score for every service attributes was computed. The
results implied that the most important servicequality attribute in the category is the error free
vehicle service, followed by vehicle - delivery at the promised time, providingfast services,
willingness of staffs to help throughout and enough number of staff.
priority level for all items
Customer Needs Priority Value
On time delivery 144
Charge fairness 141
Accident Repair 137
Roadside assistance 131
After service cleanliness 127
Handover timing 126
Schedule flexibility 121
Comfortness of waiting area 117
Friendliness of service advisor 115
Explanations of service advisor 114
Responsiveness of service advisor 114
Rectification 110
Arranging service visit 98
Cleanliness of service station 89
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6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
8.2 Defining technical requirements
After defining customer needs and priority levels, technical requirements are defined by
the QFD team. The QFD team involves five service managers, two general managers, one
customer relation manager and the researcher Error tree vehicle servicing and no-delay in
delivery are found to be the critical faaoi affecting customers1 satisfaction. The major reasons
responsible for delay in delivery are the following.
a) Delay at spare parts counter.
b) Delay at washing station.
c) Delay due to overloading at technical repair station.
The QFD process identified the need of "express service and two-tech bay", "pick and
drop" facility, "post service follow up" (PSF), "on road services" (OS), enough parking space,
work completion-status monitoring, single window service, proper scheduling for washing and
technical repair etc. Finally, eighteen technical requirements were scrutinized. The technical
design requirements are
• Improve the recourses
• Open on weekends
• Regular Audit by Manager
• Modern Equipment’s
• Trained service advisors
• Offering road test to customer
• Online service booking
• Availability of Spare Parts
• Provide Maintenance Tips
• well trained field technicians
• Pre Assigning of service advisor
• Periodic servicing
• Washing & final check up
• Pricing policy
• Soft skill behavioral training
• Pre entering of vehicle details
• Fixed cleaning schedule
• Entertainment facilities
8.3 Constituting the relationship matrix
Thus, the choice of a relationship rating scheme is critical in QFD applications.
The study of Park and Kirn (1998) revealed thai most of the QFD works used a Rating
scale of 1-3-9 format, Other scales are 1-3-5, 1-5-9, 1-2-4, and 1-6-9 (Park and Kirn, 1998). None
of the applications provided an explicit justification for the choice of such a rating scale.“There is
no scientific basis for any of the choices” added Cohen (1995). Being the fact that a rating scale
of l-3-9 is used by most of the researchers (Park and Kirn, 1998), this work is also adopting a 1-
3-9 rating scale.
In this matrix, 1 shows weak relation while "3" implies medium relation and '9" implies
strong relation; An empty cell in the matrix implies that there is no relationship between the
customer need and technical requirement. The survey of five service managers conducted for
completing the matrix. The relationship level between customer needs and technical requirements
can be seen in HOQ table.
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- 7. International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 4, Issue 1, January - April (2013), © IAEME
HOUSE OF QUALITY
8.4. Performance score
Determining the target value of design requirement is a complicated process because
of the complexity in quantification (Iranmanesh, 2008). The current work follows the method
listed out by Besterfield (2006). In creating target values, first of all technical requirements
are evaluated based on current performance. The current technical performance is evaluated
in a 5 point scale (1for very low performance and 5 for very high performance) by the service
manager.
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A target value for each technical descriptor is included in the HOQ matrix. This is an
objective measure that defines values that must be obtained to achieve the technical
descriptor. How much it takes to meet or exceed the customer's expectation is answered by
evaluating all the information entered into the house of quality and selecting the target
values.
8.5 Degree of difficulty
Many users of the house of quality add the degree of technical difficulty for
implementing each technical descriptor. The scale range from I (very low difficult] to 5 (very
high difficult). The degree of technical difficulty, when used, helps to evaluate the ability to
implement certain quality improvement (Bestertield, 2006).
TECHNICAL DESCRIPTORS & THEIR COMPUTED SCORES
CORRELATED NORMALISED
Sl TECHNICAL CTI % NORMALIZED WEIGHTAGE OF VALUE OF PRIOROTY
No DESCRIPTION SCORE VALUE OF CTI TECHNICAL CORRELATED VALUE
LANGUAGE WEIGHTAGE
1 2 3 4 2+4
1 Online service booking 2490 4.857 9 6.522 11.379
2 Periodic servicing 1923 3.751 7 5.072 8.823
3 Improve the recourses 6493 12.665 24 17.391 30.056
Pre entering of vehicle
4 details 2034 3.967 1 0.725 4.692
Pre Assigning of
5 service advisor 2463 4.804 7 5.072 9.877
Soft skill behavioural
6 training 1759 3.431 4 2.899 6.330
Trained service
7 advisors 6443 12.567 3 2.174 14.741
Regular Audit by
8 Manager 3585 6.993 12 8.696 15.688
Fixed cleaning
9 schedule 1533 2.990 0 0.000 2.990
10 Entertainment facilities 1320 2.575 0 0.000 2.575
Availability of Spare
11 Parts 3447 6.723 6 4.348 11.071
12 Modern Equipment’s 5424 10.580 7 5.072 15.652
13 Pricing policy 1296 2.528 6 4.348 6.876
Offering road test to
14 customer 1851 3.610 12 8.696 12.306
Washing & final check
15 up 2556 4.986 3 2.174 7.159
Provide Maintenance
16 Tips 1825 3.560 10 7.246 10.806
well trained field
17 technicians 2412 4.705 8 5.797 10.502
18 Open on weekends 2414 4.709 19 13.768 18.477
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Customer Technical Interactive score= ∑ (Relationship values between customer voice and
technical languages )* (Expected value of customer voice).
Eg: Customer Technical Interactive score for ‘Availability of spare parts’ =
.
(3*121)+(9*141)+(3*144)+(9*110)+(3*131) = 3447
Percentage normalized value of customers Customer Technical Interactive score *100
technical interactive score sum of Customer Technical Interactive score
Eg: Percentage normalized value of customers Technical interactive score of availability of
spare parts
= (3447 / 51268) = 6.733
Percentage normalized value of Correlated weightage of Technical language
*100
correlated weightage Sum of correlated weightage
Eg: Percentage normalized correlated weightage against technical parameter ‘Availability
of spare parts’
= (4/138) * 100 = 4.34
Priority value = (Percentage normalized value of customers Technical interactive score ) +
(Percentage normalized correlated weightage)
Eg: Priority value of ‘Availability of spare parts’ = 6.733 + 4.34 = 11.075
8.6 Technical importance levels
Finally, technical importance levels were computed. For each customer need, the
score defining the relationship between customer need and technical requirements was
multiplied by the customer priority level in that row and these values are summarized for
each technical requirement (Birdoganet tit, 2009). For the ease of comparison, technical
importance levels were presented as percentages in the last row of the target values matrix.
TECHNICAL DESCRIPTION Priority Value
Improve the recourses 30.056
Open on weekends 18.477
Regular Audit by Manager 15.668
Modern Equipment’s 15.652
Trained service advisors 14.741
Offering road test to customer 12.306
Online service booking 11.379
Availability of Spare Parts 11.071
Provide Maintenance Tips 10.806
well trained field technicians 10.502
Pre Assigning of service advisor 9.877
Periodic servicing 8.23
Washing & final check up 7.159
Pricing policy 6.876
Soft skill behavioural training 6.33
Pre entering of vehicle details 4.692
Fixed cleaning schedule 2.99
Entertainment facilities 2.575
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9. SUMMARY OF THE RESULT
The results of the study indicate that the proposed methodology could make a
valuable contribution by enhancing the understanding of the perceived service quality of
service firm.. After filtering out the specific customer needs, HOQ frame work was used to
map the design requirements. The degree of technical difficulty and technical importance
level were also documented. In a technical importance point of view, the first three design
requirements are-"recruiting skilled employees", "technical training to workers" and
"availability of spares". Once the critical design requirements are more clearly known and
understood, the service providers will be in a better position to anticipate customer
requirements rather man to react to customer dissatisfaction.
10. CONCLUSION
The role of service quality has become critical to the success of organizations.
Therefore, it is important to use an effective approach to deal with service quality. The major
contribution to this work is the adoption of a more comprehensive approach to investigating
the service quality items tool (QFD). From a methodological perspective, it can be concluded
that the ability of designing services upon customer satisfaction make this approach a
powerful tool for service sectors.
QFD is a good system to be implemented in organization or industry, which can be
seen from the examples mentioned above. QFD does not design to replace the existing
organization design process by any means, but rather support the organization’s design
process. And it also helps bring the customer’s voice into the service process to reduce the
unnecessary cost. Cutting service time is also very beneficial to the companies. QFD forces
the entire organization to constantly be aware of the customer requirements. QFD chart is a
result of the original customer requirements that are not lost misinterpretations or lack of
communication. Marketing benefits because specific sales points that have been identified by
the customer can be stressed. Most importantly, implementing QFD results in a satisfied
customer.
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