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Int. J. Productivity and Quality Management, Vol. 15, No. 4, 2015 511
Copyright © 2015 Inderscience Enterprises Ltd.
Designing a mathematical model for indicators of
service quality in the tourism industry based on
SERVQUAL and Rembrandt methods
Amir Karbassi Yazdi
Young Research and Elite Club,
Islamic Azad University,
South Tehran Branch,
Number 173, Third floor, Building of Research Deputy,
Tehran, Iran
Email:karbassi_amir@yahoo.com
Abstract: The present study investigates the ‘road map’ of service quality in
the tourism industry in Iran. The priority dimensions and indicators of
SERVQUAL for allocating limited resources such as time, budget, and human
resources to quality improvement programmes (QIPs) were determined. The
Rembrandt method, an improved form of analytical hierarchy process (AHP),
was used to prioritise indicators for implementation of QIPs in travel agencies.
To improve customer satisfaction, travel agencies must focus on various vital
issues with varied degree of preferences. Since their resources are limited, they
must also choose the most efficient QIPs to implement. The present study aims
to identify the most important dimensions and indicators of each issue and rank
them based on the quality of service. This ‘road map’ will enable travel
agencies apportion their limited resources more efficiently, in order to improve
their services.
Keywords: service quality; SERVQUAL; Rembrandt; road map; tourism
industry.
Reference to this paper should be made as follows: Yazdi, A.K. (2015)
‘Designing a mathematical model for indicators of service quality in
the tourism industry based on SERVQUAL and Rembrandt methods’,
Int. J. Productivity and Quality Management, Vol. 15, No. 4, pp.511–527.
Biographical notes: Amir Karbassi Yazdi is a Lecturer at Payam Nour
University in Mahallat and Islamic Azad University Shahre-Rey Branch, Iran.
He received his BSc in Industrial Engineering from the Azad University,
North Tehran Branch and MA in Industrial Management from the Azad
University, South Tehran Branch. His research interests are in operations
research, quality management, and strategy and organisational performance. He
has published in journals such as Benchmarking an International Journal,
Australian Journal of Basic and Applied Sciences, World Applied Sciences,
among others.
512 A.K. Yazdi
1 Introduction
In this competitive world, advanced technologies have profound influence on various
aspects of human life, leading to an increase in the expectation of people. Customers seek
goods of better quality and flawless services. Therefore, the world market has become
more and more competitive. The most important factor to overcome the competition is to
provide better quality. In general, organisations pay special attention to quality
improvement. The tourism industry (TI), just like other industries, follows the same
principle. TI can effectively contribute to the revenue of a country. Improving the quality
of TI services can increase the number of people availing it. Since its introduction,
SERVQUAL has been extensively utilised in a variety of industries such as airport
services (Shahin et al., 2012; Wang et al., 2011), banking (Al-Eisa and Alhemoud, 2009;
Al-Hawary and Metabis, 2012; Cui et al., 2003; Jabnoun and Al-Tamimi, 2003; Kumar
et al., 2010; Tavakoli and Shirouyehzad, 2013), healthcare (Bakar et al., 2008; Hu et al.,
2010; Mostafa, 2005; Sinimole, 2012; Wicks and Chin, 2008), tourism (Bouranta et al.,
2009) and so on. Researchers have employed certain methods with SERVQUAL to
determine the shortcomings between customer expectations and the performance of the
organisation. Quality improvement programmes (QIPs) are designed and implemented
based on the results of the assessment. However, designing an ideal customer-centred
improvement programme is difficult. Therefore, different organisations employ different
methods to determine high priority QIPs.
The multi-attribute decision making (MADM) method is more commonly used in
combination with SERVQUAL to determine high priority QIPs. This method sorts the
indicators of SERVQUAL to determine the most important indicators and sub-indicators
of an instrument because it is not possible for each organisation to implement all the
QIPs. Several studies have evaluated the feasibility and potential of ranking SERVQUAL
indicators in various industries.
According to SERVQUAL, an ideal QIP is one that determines the importance and
priority of each QIP. Organisations can use MADM methods to determine the most
important indicators. The Rembrandt method, which was used in this study, is one of the
MADM methods.
The advantages and disadvantages of the analytical hierarchy process (AHP) have
always been a source of controversy among experts of MADM method.
Some decision makers (DMs) believe that AHP must be used for cases with limited
alternatives, and others have attempted to focus only on its strengths.
The Rembrandt method, introduced by Lootsma (1992), is an improved model of
AHP from which weaknesses have been rectified to improve the efficiency of the model.
In this study, initially, a questionnaire of SERVQUAL’s indicators is designed based
on the Rembrandt method. Then, this questionnaire is distributed among customers of
travel agencies. Finally, the data collected via these questionnaires are analysed using the
Rembrandt software to determine the ranking of the indicators to which travel agencies
should allocate their resources.
This report has been divided into six sections. The first section ‘Introduction’
discusses the objectives of this study, which is followed by the review of literature of
SERVQUAL. The Rembrandt method is presented in detail in the third section. The
methodology of this study and the key empirical findings are presented in the fourth and
fifth sections respectively. The sixth section summarises the conclusions of this study.
Designing a mathematical model for indicators of service quality 513
2 Literature review
2.1 SERVQUAL
Many companies seek to increase the number of their customers by improving customer
satisfaction with better services and products. To this end, companies are obliged to
assess the quality of their services. In general, customer satisfaction is proportional to the
quality of service offered. There are several methods to evaluate the quality of service.
These methods are expected to take into account, both the internal and external factors of
the company, during evaluation. SERVQUAL is one of the most popular methods for
measuring the quality of service.
SERVQUAL, developed by Parasuraman et al. (1988, 1985), analyses the
shortcomings that exist between service quality and customer perception. In previous
studies, ten dimensions were identified for SERVQUAL (reliability, responsiveness,
competence, access, courtesy, communication, creditability, security, understanding, and
tangibles), whereas, in the latest versions of SERVQUAL, only five dimensions are
included.
The five dimensions of the current model are:
1 reliability: the degree of learned knowledge, skill, and accuracy in service delivery
2 responsiveness: the willingness to help customers and satisfy their needs
3 assurance: customer’s level of trust and confidence in company and its staff
4 empathy: the individual attention given to customers and the degree of convenience
in service delivery
5 tangibles: the appearance of the physical facilities, equipments, personnel, etc.
To analyse these dimensions, Parasuraman et al. (1988) introduced a 22-items
questionnaire designed to measure the gap between customers’ perspectives and service
quality.
As mentioned earlier, no company can implement all QIPs recommended by the
SERVQUAL method because of limitations in resources such as budget, human
resources, and time. Therefore, many companies seek high priority indicators of service
quality. Several studies have evaluated the prioritising of service quality factors.
Kannan (2010) reported a study based on SERVQUAL and AHP for benchmarking
the service quality of ocean container carriers in India. He clustered various attributes
related to ocean container carriers into seven categories and ranked them using AHP.
This framework illustrated the strengths and weaknesses of these carriers based on
service quality in implementing relevant strategies to improve their performance.
Moreover, this study determined some limitations of the AHP method employed to rank
carriers’ attributes. Jamali and Tooranloo (2009) prioritised academic library service
quality indicators using the fuzzy TOPSIS approach. They concluded that inner indicators
such as visible and tangible ones are more important than other indicators and deserve
more attention. Nejati et al. (2009) combined fuzzy TOPSIS and SERVQUAL to rank
quality service factors in Iran’s airline industry. This study concluded that factors of the
dimensions of reliability, responsiveness, and tangibles have a higher priority. Tsinidou
et al. (2010) used AHP and SERVQUAL to rank quality service factors in higher
education. They concluded that managers should focus on the personnel such as its
514 A.K. Yazdi
training, and infrastructure of teaching and laboratories. Filiz (2010) measured the service
quality of travel agents in Turkey and concluded that people are satisfied with their
service. Shirouyehzad et al. (2013) used AHP and DEA for ranking service units and
dimensions of SERVQUAL in the hotel industry. They designed five inputs (quality gap)
and one output (customers’ perceptions). The AHP method was used for finding the
weights of inputs. Integrated model of AHP/DEA was used for evaluating hotels based on
service quality. Shahin et al. (2013) used SERVQUAL, Internal Service Quality (ISQ)
and TOPSIS for evaluating the different departments at Isfahan Steel Company. They
ranked the ISQ departments such as transportation, restaurant and socio-cultural. The
highest priority was given to the socio-cultural department and lowest to the
transportation department. In the five dimensions of SERVQUAL model, the dimensions
in order of increasing priority were tangibles, empathy, responsiveness, assurance and
reliability. Moreover, the condition of service quality in this company needs a significant
improvement. Al-Hawary and Metabis (2012) studied the case of commercial bank of
Jordan and concluded that customers were satisfied about services offered. From the
customers’ point of view, assurance dimension had the highest priority among other
dimensions. Hence, assurance dimension and its relative indicators require a special
attention.
3 The Rembrandt method
Following the introduction of AHP by Saaty (1994), there was a considerable amount of
controversy regarding this model. Because of the variations in the results of studies
conducted on AHP, DMs believe that this model must be used in cases with fewer
alternatives. Lootsma (1992) introduced a new model which overcame the number of
weaknesses in AHP. To analyse estimated weights, the new model, called ‘Rembrandt’,
uses a logarithmic method instead of the nine-scale analytical hierarchical process and a
geometric method instead of arithmetical average.
Most researchers find the geometric methods to be more reliable than the other
methods for calculations. Rembrandt has a software package to implement this technique
(Lootsma, 1992, 1997).
In this study, our first step was to consider a group of g DMs (where, g ≥ 1) which
relates to evaluating m criteria (where, m ≥ 1). Assuming the criteria Ci, (where i = 1, …,
m) with the subjective value (Vi), and supposing that Vi is the same for all DMs in the
group, the m – vector of Vi values from the DMs’ verbal subjective judgments are
estimated by Rembrandt. Each DM was asked to judge pairs of criteria, Ci and Cj, and
record his/her graded comparative score in the decision matrix, Dmxn. The requirement is
the pair wise comparisons of (m – 1) and m(m – 1)/2 for a set of m criteria, i.e., the DM
records his preference for one attribute over another on a scale of weak, definite, strong,
or very strong. Then, a general procedure proposed by Lootsma (1997) is used to handle
incomplete pair wise comparisons. Considering the ratio information, the subjective
criteria weights are normalised, so that ΣiVi = 1 is obtained. In order to limit the range of
verbal responses, the DM’s pair wise comparison judgments are captured. Using the scale
in Table 1, each verbal response is then converted into an integer-valued gradation index,
δjld.
Designing a mathematical model for indicators of service quality 515
Table 1 The Rembrandt category scale
Comparative judgment Gradation index δjld
Very strong preference for Ci over Cj –8
Strong preference for Ci over Cj –6
Definite preference for Ci to Cj –4
Weak preference for Ci to Cj –2
Indifference for Ci to v 0
Weak preference for Cj to Ci +2
Definite preference for Cj to Ci +4
Strong preference for Cj over Ci +6
Very strong preference for Cj over Ci +8
The gradation index, δjld is converted into a value of geometric scale, γ. Thus, rjld, the
numeric estimate of the preference ratio (Vj/Vl), which is given by the DMd, is defined as
follows equation (1):
exp( ); , 1,,; 1,,.
jld jld
rγδ jl m d g==…=… (1)
Considering that there is no unique scale for human judgment, a plausible value of γ for
the group is ln 2 , implying a geometric scale with a progression factor of 2
(Lootsma, 1993). In the second step, V is approximated by the normalised vector v of
group weights which minimises:
()
2
1
ln ln ln ; 2, , .
g
jld j l
jld
rvul m
<=
−+ =
∑∑ … (2)
Let’s assume that a complete set of pairwise comparisons is offered by all DMs. Now
ρjld = lnrjld = γδjld and wj = ln
ν
j. Then, the vector of
ν
is determined by minimising
equation (3) as a function of wj (j = 1, …, m) as follows:
()
2
1
;2,,.
g
jld j l
jld
θρww l m
<=
=−+=
∑∑ … (3)
The set dependence of normal questions is calculated using equation (4) as follows:
()
1
0; 1, , ; 2, , .
g
jld j l
jjld
θ
ρ
ww j ml m
w==
∂=−+===
∂∑∑ ……
(4)
Now, let ρjld = ρljd and ρjjd = 0 for any j. Equation (4) can be written as follows
[equation (5)]:
11 11 11
;1,,.
ggg
mmm
jld j l
ld ld ld
γδ wwjm
== == ==
=− =
∑∑ ∑∑ ∑∑ … (5)
No unique solution to this set of normal equations can be found. For a particular solution,
the sum of the variables (Σwl) equals zero and reduces equation (5) to the following
unnormalised solution [equation (6)]:
516 A.K. Yazdi
11
11 ;1,.
g
m
j jld
ld
wγδjm
gm ==
==
∑∑ … (6)
Therefore:
()
11
11
exp exp
g
m
j
jjld
ld
vw γδ
gm ==
⎛⎞
==
⎜⎟
⎜⎟
⎝⎠
∑
∑ (7)
and
1
11
;1,,.
g
m
g
m
jjld
lg
vrjm
==
==
∏∏ … (8)
where equation (8) implies that the criteria weights of vj are calculated by a sequence of
geometric means. To determine the normalised solution vector v, the result of in
equation (8) is multiplied by the degree of freedom. In addition, since vj = f(exp(γδjld)),
the normalised criteria weights will be dependent on the scale parameter γ, without
changing the rank ordering of vj.
4 Methodology
4.1 Research structure
In this study, the sub indicators of SERVQUAL method that are related to TI are
identified. And the questionnaire based on SERVQUAL and Rembrandt methods is
designed. The structure of this study is based on survey questionnaires. The results of
questionnaire analyses provide the rank of main categories of SERVQUAL and sub
indicators of them. For analysing these data, a mathematical method is used.
4.2 Research questions
• What are the indicators of SERVQUAL in TI?
• What are the weights of these categories and indicators?
• Which one of these categories and indicators has a higher priority?
4.3 Target population for questionnaire survey
Questionnaires were distributed among passengers travelling to international and
domestic destinations. 565 passengers participated in the questionnaire survey, out of that
546 effective questionnaires were gathered.
4.4 Design of the questionnaire and measurement
Questionnaire of ranking CSFs consisted of the following dimensions:
Designing a mathematical model for indicators of service quality 517
1 reliability
2 assurance
3 responsiveness
4 empathy
5 tangibles.
These main categories have 22 indicators. The measurement of these indicators, results in
the ranking of the dimensions, which is performed by designing the mathematical model
of service quality in TI.
4.5 Data analysis
The questionnaire of this study is designed based on pair wise of main categories. The
indicators of SERVQUAL and Rembrandt software were used for analysing the data.
4.6 Reliability and validity tests
The indicators were identified and the questionnaires designed based on these categories,
indicators and the Rembrandt method. Subsequently, responses to the questionnaires
were obtained from the sample population. The questionnaires were distributed among
passengers and the responses were obtained through interviews. The researchers
evaluated the validity of this questionnaire with experts and managers of travel agencies.
The completed questionnaires were gathered and analysed using the Rembrandt software,
which also ensured the reliability of the collected data. The software does not analyse
data that are found to be unreliable. Figure 1 describes the methodology of this research.
Figure 1 Methodology of research (see online version for colours)
518 A.K. Yazdi
5 Data analysis
After gathering the completed questionnaires, the data were calculated using the
Rembrandt method. As mentioned above, if the data were not reliable, their weights were
not calculated. There are indicators of each dimension.
In the dimension of reliability, the indicators were:
1 accountability in obtaining feedback from customers
2 available information regarding the tour
3 timely service delivery
4 trustworthiness of staff.
The indicators of the dimension of assurance were:
1 sufficient knowledge of staff
2 workers’ knowledge of use of technology
3 proper service during trip
4 customer satisfaction with agency’s services.
Indicators of dimensions of responsiveness were:
1 prompt response to requests
2 solving customer’s grievances
3 interest of staff in providing service in a timely manner
4 willingness of staff to help and guide
5 providing proper services in a timely manner.
Indicators of dimensions of empathy were:
1 imparting confidence in customers based on the behaviour of employees
2 paying attention to needs and demands
3 non-discrimination toward customers
4 providing convenient services around the clock
5 attention of staff to customers.
The final indicators of SERVQUAL dimensions (tangible dimension) were:
1 neatness of employees
2 modern vehicles of transportation
3 suitable brochure
4 layout of agency.
Designing a mathematical model for indicators of service quality 519
Among the five SERVQUAL dimensions discussed earlier, empathy had the highest
priority. Tourist agencies must focus on the QIPs extracted from this dimension. The
second most important dimension was responsiveness. All QIPs related to this dimension
have priority, and travel agencies must allocate their resources to these factors. The next
highest priority goes to the reliability dimension. This dimension asserts that the
reliability of travel agencies for their customers is in the middle. The fourth dimension
was assurance which means that travel agencies must try to impart trust in them and
make them feel confident. The last dimension in the scale of priority was tangible.
Customers believe that the appearance of physical facilities, equipment, support services
and service personnel is of the lowest priority.
Table 2 illustrates these rankings.
Table 2 Ranking the SERVQUAL dimensions
Dimensions of
SERVQUAL Empathy Responsiveness Reliability Assurance Tangible Weights Priority
Empathy 1.48 1.83 9.4 7.4 0.386 1
Responsiveness 0.67 1.59 9.44 8.71 0.331 2
Reliability 0.544 0.627 1.98 6.42 0.181 3
Assurance 0.105 .106 0.503 9.98 0.076 4
Tangible 0.13 0.114 0.155 0.1001 0.026 5
The dimension with the highest priority was empathy, and its indicators were ranked as
follows:
The first indicator of this dimension is creating confidence in customers through
appropriate behaviour of employees. Paying attention to needs and demands of the
customers is followed by, non-discrimination towards customers, providing convenient
services around the clock, attention of staff to customers which occupy the third, fourth
and fifth indicators, respectively, of this dimension. Table 3 depicts the weights of these
indicators.
The dimension with the second highest priority is responsiveness. The ranking of its
indicators in order of highest to lowest priority are fast response to requests, solving
customer’s grievances, interest of staff in providing service in a timely manner,
willingness of staff to help and guide, and providing proper services in a timely manner.
Table 4 depicts the ranking of indicators of responsiveness.
Among the four indicators of reliability dimension, accountability in obtaining
feedback from customers, availability of information regarding the tour, timely delivery
of service, trustworthiness of staff are the indicators with highest to lowest priority.
Table5 shows the weights of these indicators.
The ranking order of indicators of assurance as the dimension with the fourth highest
priority are sufficient knowledge of staff, workers’ knowledge of use of technology,
proper service during trip, customer satisfaction with agency’s services.
The ranking of these indicators are shown in Table 6.
520 A.K. Yazdi
Table 3 Ranking the indicators of empathy dimension
Indicators of empathy dimension
Imparting
confidence in
customers
Paying attention
to needs and
demands
Non-discrimination
toward customers
Providing
convenient services
at all hours
Attention of staff
to customers Weights Priority
Imparting confidence in customers 1.46 3.317 2.623 2.414 0.346 1
Paying attention to needs and demands 0.682 1.474 2.707 2.525 0.257 2
Non-discrimination toward customers 0.301 0.677 2.932 3.712 0.205 3
Providing convenient services at all hours 0.381 0.369 0.341 2.725 0.115 4
Attention of staff to customers 0.414 0.395 0.269 0.366 0.077 5
Designing a mathematical model for indicators of service quality 521
Table 4 Ranking the indicators of responsiveness dimension
Indicators of responsiveness dimension
Prompt
response to
request
Solving
customer’s
grievances
Interest of staff in
providing service in
a timely manner
Willingness of
staff to help and
guide
Providing proper
services in a
timely manner
Weights Priority
Prompt response to request 1.606 1.985 2.711 6.581 0.34 1
Solving customer’s grievances 0.622 1.452 3.916 5.951 0.28 2
Interest of staff in providing service in a
timely manner
0.503 0.688 4.524 7.43 0.25 3
Willingness of staff to help and guide 0.368 0.255 0.221 9.474 0.109 4
Providing proper services in a timely
manner
0.151 0.168 0.134 0.105 0.021 5
522 A.K. Yazdi
Table 5 Ranking the indicators of reliability dimension
Indicators of
reliability
dimension
Accountability
in obtaining
feedback from
customers
Available
information
regarding
the tour
Timely
service
delivery
Trustworthiness
of staff Weights Priority
Accountability
in obtaining
feedback from
customers
1.47 1.65 3.46 0.35 1
Available
information
regarding the
tour
0.67 1.47 5.68 0.32 2
Timely service
delivery
0.603 0.67 8.309 0.28 3
Trustworthiness
of staff
0.28 0.175 0.12 0.05 4
Table 6 Ranking the indicators of assurance dimension
Indicators of
assurance
dimension
Sufficient
knowledge of
staff
Workers’
knowledge
of use of
technology
Proper
service
during trip
Customer’s
satisfaction
with agency’s
services
Weights Priority
Sufficient
knowledge of
staff
1.45 2.32 7.43 0.38 2
Workers’
knowledge of use
of technology
0.68 7.66 9.87 0.46 1
proper service
during trip
0.43 0.13 5.05 0.12 3
Customer
satisfaction with
agency’s services
0.13 0.101 0.197 0.04 4
The ranking of the indicators of the tangible dimension is as follows:
The indicator with the highest priority is employee’s neatness. A neat employee can
attract more customers for an agency. The next indicator is modern vehicles of
transportation. If an agency uses modern means of transportation, customers will have an
enhanced level of convenience. A complete brochure is the next indicator with the
highest priority. A brochure offering information about locations of sightseeing,
attractions, and other amenities can attract more customers and help them choose a
suitable tour. The indicator with the next highest priority is the layout of the agency. A
suitable layout makes the customers to feel at ease and increases customer satisfaction.
The ranking of these indicators are depicted in Table 7.
Designing a mathematical model for indicators of service quality 523
Table 7 Ranking the indicators of tangible dimension
Indicators of
tangible
dimension
Neatness of
employee
Modern
vehicles of
transportation
Suitable
brochure
Layout of
agency Weights Priority
Neatness of
employee
1.54 9.79 8.96 0.53 1
Modern vehicles
of transportation
0.65 6.67 7.66 0.36 2
Suitable brochure 0.102 0.15 1.509 0.06 3
Layout of agency 0.11 0.13 0.66 0.05 4
6 Conclusions
6.1 Managerial implication
The main purpose of this study is to find high priority indicators of service quality in
Iranian TI for allocating rare resources for implementing relevant QIPs. Iran is a country
with historical importance and spectacular natural beauty. Although the TI is still in its
early stages in Iran, it is developing at a quick pace. Iran has the potential to become a
tourist’s first choice of countries to visit. Therefore, identifying and prioritising service
quality factors of the TI in Iran can provide a suitable benchmark for the tourism
industries in other countries. Service quality is the most important tool for increasing the
number of customers. When customers realise that a company respects their needs and
attempts to meet them, their satisfaction and loyalty will equally increase. Therefore,
many companies attempt to understand and measure service quality indicators. This study
presents a ‘road map’ of service quality for the TI, based on SERVQUAL and Rembrandt
method. In summary, this work has identified twenty two indicators for evaluating
service quality. Survey questionnaires which are designed based on service quality
indicators and Rembrandt method are distributed among sample population. The findings
of this study show that among five main dimensions of SERVQUAL, empathy had the
highest priority and tangibles the lowest. Among the twenty-two indicators, behaviour of
employee, attention to customer’s needs and demands, non-discrimination toward
customers, provision of full-time convenient services, and attention to customers needed
more focus. Moreover, from the customers’ point of view, the tangibles indicator needed
less attention, and employee neatness, modern transportation vehicles, suitable brochures
and agency layout were up to the mark in Iran.
Findings about prioritising indicators of service quality are shown as follows:
The first indicator was imparting confidence in customers through pleasing behaviour
of employee. Travel agencies have to implement QIPs for creating confidence in their
customers, because customers suspect that some agencies attempt to sell tours at prices
higher than the real price. If the staffs sell tours at higher prices, they could earn more
money. The second indicator is attention to customer’s needs and demands. If one agency
does not pay attention to their needs, customers might shift to another agency, and the
agency will lose money. Moreover, the unsatisfied customer will tell others about his/her
dissatisfaction, and the agency might lose many more customers.
524 A.K. Yazdi
The third indicator is non-discrimination towards customers. Some agencies
discriminate between their customers based on their financial status. Such acts of
discrimination might impress certain number of customers, but will cause dissatisfaction
among others. Providing convenient services around the clock is the fourth indicator.
Agencies have designed websites or other services that are available most of the time.
The fifth indicator is staff’s attention to customers. When a customer receives attention
from the staff, he perceives convenience, and this might make him loyal to the agency.
Among the second category of highest priority indicators (indicators of responsiveness
dimension), the first indicator is prompt response to requests. A prompt response makes
the customers to feel that they are important for the agency leading to increased customer
satisfaction. Solving the grievances of customers is the second highest priority indicator.
Solving grievances of customers leads to an increase in the number of customers by
gaining their satisfaction. The third indicator is interest in providing service in a timely
manner. Managers and staff attempt to provide services in a timely manner. Authorities
need to encourage this in the form of incentives or other benefits to the staff, failing
which will make the staff lose interest in their obligations. The willingness of staff to help
and guide the customers is the fourth indicator. Customer satisfaction will increase if
customers experience the staff’s willingness to help and guide them. The last indicator is
provision of proper services in a timely manner. This indicator has a low priority. Most
agencies provide proper services on time, but it is important from the customer’s point of
view. Agencies must attempt to maintain or improve their timely provision of service.
Without this improvement, agencies may lose customers.
The first indicator of reliability dimension is the accountability of obtaining feedback
from customers, which helps agencies better understand their weaknesses and strengths.
Availability of accurate information regarding a tour is the second indicator. Customers
require this to be able to analyse the cost, select locations, and facilities of tours in order
to make a decision. Some agencies advertise low-priced tours with various facilities.
When customers want to choose these tours, they will find that these tours do not offer
added facilities. The third indicator is timely delivery of service, which can increase
customer satisfaction. Some agencies offer customers that they obtain visas and other
relevant documents in time, but they fail to do so within the proposed time.
Trustworthiness of staff is the indicator with the next highest priority. If an agency has
trustworthy employees, customers will accept their suggestions. Some agencies contact
customers and tempt them to buy a tour at a discount. Although these agencies give
discounts in their tour prices, they increase other prices associated with the tour, so that
customers actually receive no discount and will therefore be unsatisfied. Knowledge of
workers in using the latest technology is the highest priority indicator of tangible
dimension. If an agency’s staffs are knowledgeable in the use of advanced technology,
they can work with higher accuracy and speed and respond to a customer’s needs in a
timely manner. The second indicator is sufficient knowledge of the staff. If the staffs
have sufficient knowledge, they can perform better and in turn, help customers.
Accordingly, the trust of the customer will increase. The next highest indicator is proper
service during a trip. Providing proper services during a trip increase the satisfaction and
trust of customers in the agency. Customer satisfaction towards the services offered by an
agency is the final indicator. If customers realise that an agency will respond quickly to
their requests and their staffs behave appropriately with them, then customer satisfaction
will increase and so does their trust in that agency.
Designing a mathematical model for indicators of service quality 525
6.2 Limitations of the study and future prospective
Some limitations of this study are discussed in this section.
1 Subjects who do not want to answer the questionnaire.
2 Responding to the pair wise questions were too hard for the subjects and much time
was spent on explaining how to answer the questions.
3 The choice of people. The method of choosing sample population was done
randomly.
Hence, when the questionnaire was given to the subjects, they were inquired if they had
bought any tour from travel agency or not.
For future research, this model can be applied in various aspects of the TI. As
mentioned above, TI has a positive impact on the economy of a country. Hence, focusing
on this aspect will significantly increase the revenue of a country. This model can also be
applied to transportation in tourism, provision of services in hotels, restaurant and so on.
Moreover, industries can also measure the effects of these indicators and dimensions by
DEMATEL method.
The road map of this study is presented in Figure 2.
Figure 2 The result of research (see online version for colours)
526 A.K. Yazdi
Acknowledgements
The author would like to thank the anonymous reviewers and the Editor for their
insightful comments and suggestions.
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