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Car Rentals’ Knowledge and Customer Choice

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2020 International Conference on Emerging Trends i n In forma tion Technology and Engineering (ic-ETITE) 978-1-7281-4142-8/20/S31.00 ©2020 IEEE 10.1109/ic-ETITE47903.2020.331
2020 International Conference on Emerging Trends in Inf ormat ion Technology and Engineeri ng (ic-ETI TE)
Car Rentals Knowledge and Customer Choice
Saroj Koul
Center f o r Supply Chain and Lo gi st i cs
Management
OP Jindal Global University
Delhi NCR, India
skoul@jgu.edu.in
[Orcid ID: 0000-0002-3051-5625]
CSN Venkata Datta
Center f o r Supply Chain and Logist ics
Management
OP Jindal Global University
Delhi NCR, India
17igbs-cvenkatadatta@igu.edu.in
Rakesh Verma
Decision Sciences and Information
Systems
NITIE
Mumbai, Maharashtra, India
rakeshverma@nitie.ac.in
[Orcid ID: 0000-0002-3637-7788]
Abstract Indian market for car rentals has increased
ra pid ly d ur ing the past decade. M any cab services have opened
renting operations. Further, mobile applications of a particular
car rent al or cab service allow customers to book their cab
service or rent a car at any ti me from any location. This paper
attempts t o identif y factor s chosen by a customer whi l e choosi ng
a car re nta l servi ces by using Ana l yti c al Hier a r chy Process
(A H P) methodol ogy.
Keywords—Car rental, Consumer’s choice, Car Renters
Knowledge, An al yti cal Hiera rchy Process (AHP), I n dia
I. Int r o duct ion
In earlier days, borrowing a car from friends or relatives
was common, i f you did not own one. The emergence o f Car
Rental Service Companies in the Indian market rose as several
low budget cars, including Tata Nano, did not suffice for a
vacation with family. Further, the option of self-driving cars
available nowadays in the market has led to a steep boom in
established Car Rental Service Companies. While, the
organized sector o f Car Rental Service Companies
differentiated itself from unorganized sector in service
parameters such as good service quality, efficient and
excellent conditioned fleet, reliability, trained drivers, and
well-monitored prices.
In India, the market for self-drive rentals is moving very
fast. Signi ficant market players include Zoom Cars, Pandu
Cabs, and Revv; each is trying innovative methods by
improving technology and innovation; in-turn increasing
business by attracting the customers with their useful services.
The competition in the market of car rentals has increased;
different market players are trying various methods to attract
consumers, to grow their business and to withstand in the
market.
In the study, "Analytical Hierarchy Process (AHP)" tool is
applied to identify significant elements based on the
knowledge of consumer needs to consider while booking a
rental car. Next, we assign weightage to the items using
responses from the customers o f Car Rental Service
Companies - thus helping the companies to organize their
operations as per the weightage o f the factors so that they can
increase their sales to the optimal level.
II. Lit er a t u r e Review
This literature assesses articles available on AHP method
used in research associated wit h car rentals. Various
researchers have addressed the issues o f managing both fleet
and revenue in car rental with different approaches. Reference
[1] aims at solving short term car rental issues by optimizing
fleet utilization services while keeping in mind transportation
relationship, fleeting and de-fleeting, and multi-period
planning as the factors. A two-stage dynamic programming
model” is developed [2] to decide on the ideal “ fleet size” and
transfer policy” for a car rental serving two cities. And, in
case, the matching transfer policy became unsuitable in the
heuristic solution; the entire performance declined despite an
optimal fleet size [2]. Also, [3] discussed optimal utilization
of fleet by using the revenue management concept to develop
booking, inventory strategies and pricing for the car rental
industry. To get a higher “ customer satisfaction,” the car rental
indust ry has adopted “ Pool segmentation, Strategic Fleet
Planning and Tactical Fleet Planning” as the three decision
making steps. Reference [4] proposed a conceptual framework
to unravel a fleet management challenge at a car rental caused
due to cl ustering among the rental stations, selecting the
booking, deciding the price, its acceptance and assigning to
specific vehicles. Further, the rental services being uncertain
and price-sensitive, the fleet deployment decisions to meet
demand, including an upgrade or a vehicle transfer between
locations was inter-connected [5].
Different strategies adopted from losses to profitability
after the liquidation of National Car Rental are showcased [6].
Reference [7] studies the potential of AHP for internal audit
prioritisation and resource allocation in a rental car company.
Reference [8] intended taxing tourism, especially car rentals,
to reduce congestion externalities and to achieve a better
tr affic level. Reference [9] uses a heurist ic approach to meet
the reservation requirements that car rental companies must
transfer between the rental stations which consume much fuel,
affects the profit of the company. Reference [10] pointed at
the size of the fleet and the vehicle transfer policy where they
propose a hybrid heuristic approach to solve both the tasks fo r
Car Rental Service Companies with several outlets. Reference
[11] used an iterative model” fo r a car rental booking getting
accepted that permi tted one-way reservations and restricted
the number of cars to be maintained at each depot; and
concluded that managing a car rental services as complex.
Reference [12] discussed the car inspection system in the car
rentals with the focus to insurance and maintenance
companies. An empirical study on 199 US airports found that
an increase in the rental price by a 1 per cent leads to a
decrease in the passenger demand in airports by 0.36 per cent
[13]. Reference [14] aimed at profit management of Car
Rental Service Companies and used a birth-deat h process in
equilibrium with infinite size to overcome issues like security,
cabotage regulations and insurance. Another study proposed a
decomposition methodology to control the booking at a
single-station car-rental management system [15].
978-1-7281-4142-8/$31.00 ©2020 IEEE 1
2020 International Conference on Emerging Trends in Informati on Technol ogy and Engineering (i c-ETITE)
AHP methodology finds out various tangible and
intangible criteria, prioritise them and analyse them [16]. The
vast knowledge literature of 8441 papers using AHP and
published between 1979 and 2017 [17] lists one publication in
the car rental service area that describes a framework for
internal audit prioritisation and resource allocation using AHP
[7]. Further, during the period 2017 to 2019, articles published
in the domain refer to the evaluation of carpooling [18] and
ridesharing system [19], and as such no specific article
focused on the factors that a consumer envisages while
picking a car rental service.
So far, there has been being no relevant studies which are
focused on the factors that a consumer envisages while
picking a car rental service. Therefore, this study attempts to
use AHP methodology to identify factors that a consumer
should consider in choosing a car rental service.
III. Metho dol o gy
AHP is a useful tool which deals with problems of
complex decision making. I t diminishes the complex
decisions and synthesizes the result by prioritizin g them. AHP
considers a set of alternative options and evaluation criteria
among which the decision is to be made. The AHP generates
a score/weight for each criterion based upon the decision
makers’ pairwise-comparison’. The criterion that gets the
highest score/weight; the corresponding criteria is the better
option or decision to choose.
Through a Survey Questionnaire (Table 1) a total o f eight
factors are considered as (1) Car’s condition (2) Cars Model
(3) Price consciousness (4) Discounts and Redemption
Coupons (5) Security Deposit (6) Inclusions (7) Innovative
Services (8) Late Fee. Data was collected based on the Saaty’ s
Scaling [20] where: 1 = Equal importance; 3 = Moderate
importance; 5 = Strong importance; 7 = Very-strong
importance and 9 = Extreme importance” .
A. Steps in AHP
Step 1: I n the fir s t step, the col lected responses o f
pairwise criteria from the customers has to be
summarized into “ n * n pairwise-comparison matrix for
n criteria” .
Let us define the criteria of factors which consumers
consider while booking a car for rent as:
C = [C j | j = Model,Condition,..., Late Fee}
The evaluation matrix n * n contains the comparison of
the criteria from the set C. For example, the matrix is
... S u l
...
... Of f
...
Step 2: Based on the AHP hierarchy scale, a.. represents
the assessment of a pairwise-comparison’ between the
criteria (Table 2). If the criteria j is more important
than criteria i , then
represented as:
'alL fflE
/_[ = mL
n3L n s :
n4L
a .. = 9 and a..
J1 vay * 0 au = 1 aji =
Step 3: AHP here normalizes the matrix to obtain weights
by dividing the column entries with their respective
column sums and to obtain a normalized matrix model.
We get the priorities by calculating the average of each
row (Table 3).
Moreover, the largest eigenvalue Amax which is
concurrent with the principal eigenvector w of matrix A
determines precedence of the elements.
Aw = A w (1)
max
Step 4: Here consistency o f response matrices is
checked. AHP results are highly dependent on the
consistency of pairwise-comparison judgment’s” .
Analysis of consistency constitutes two steps. First, we
determine Equation.2 determines the Consistency Index
(CI) by secondly, Consistency Rate (CR) used is at (2);
where RI of the matrix depends upon the size o f the
criteria.
CI = Amax n
n -1
cr =CI
RI
(2)
(3)
The Consistency Rate arranges the consistency based on
pairwise assessments. As AHP 0.1 is the maximu m lim i t
o f CR, any analysis w hic h exceeds 0.1 should need
repetition in response to improve the ratio. As per the
analysis, the weightage of the factors that consumers
consider while booking a car for rent are in Table 4.
Pictorially the criteria rankings are at Figure-1.
IV. Analysis of the Res ul t
From the responses received f rom the customers of car
rentals, it is observed that most of the customers consider a
Cars Model as the most crucial factor while looking for a car
fo r rent. To attract more customers, Car Rental Service
Companies should maintain different varieties of car models
in their fleet, which most of the people like or desire to have.
In the hierarchy o f the factors next comes the Price
consciousness. Hence, Car Rental Service Companies should
take proper care while designing the prices of car rental.
Moreover, they must devise a reasonable price to attract more
customers. Not only the model and the price, but the
customers also look for quality, so the next factors come to the
car's condition.
Car Rental Service Companies should design a proper
schedule for the maintenance of its fleet and should take their
cars for maintenance support as per the schedule without fail.
If the vehicle is not in good condition, then no customer will
show interest in receiving the vehicles of that particular
company who does not maintain their cars properly. To get the
right number customers, the rental services need to pre-check
the state of their fleet of vehicles.
2
2020 International Conference on Emerging Trends in Informati on Technol ogy and Engineering (i c-ETITE)
Table 1: Survey Questionnaire
Name: Age: Gender: Place:
Criteria 1 Evaluation Criteria 2
Car’s condition 9 7 5 3 1 3 5 7 9 Car’ s Model
Car’s condition 9 7 5 3 1 3 5 7 9 Price consciousness
Car’s condition 9 7 5 3 1 3 5 7 9 Discounts
Car’s condition 9 7 5 3 1 3 5 7 9 Security Deposit
Car’ s condition 9 7 5 3 1 3 5 7 9 Inclusions
Car’s condition 9 7 5 3 1 3 5 7 9 Innovative Services
Car’s condition 9 7 5 3 1 3 5 7 9 Late Fee
Car’s Model 9 7 5 3 1 3 5 7 9 Price consciousness
Car’s Model 9 7 5 3 1 3 5 7 9 Discounts
Car’s Model 9 7 5 3 1 3 5 7 9 Security Deposit
Car’s Model 9 7 5 3 1 3 5 7 9 Inclusions
Car’s Model 9 7 5 3 1 3 5 7 9 Innovative Services
Car’s Model 9 7 5 3 1 3 5 7 9 Late Fee
Price consciousness 9 7 5 3 1 3 5 7 9 Discounts
Price consciousness 9 7 5 3 1 3 5 7 9 Security Deposit
Pri ce consciousness 9 7 5 3 1 3 5 7 9 Inclusi ons
Price consciousness 9 7 5 3 1 3 5 7 9 Innovative Services
Price consciousness 9 7 5 3 1 3 5 7 9 Late Fee
Discounts 9 7 5 3 1 3 5 7 9 Security Deposit
Discounts 9 7 5 3 1 3 5 7 9 Inclusions
Discounts 9 7 5 3 1 3 5 7 9 Innovative Services
Discounts 9 7 5 3 1 3 5 7 9 Late Fee
Security Deposit 9 7 5 3 1 3 5 7 9 Inclusions
Security Deposit 9 7 5 3 1 3 5 7 9 Innovative Services
Security Deposit 9 7 5 3 1 3 5 7 9 Late Fee
Inclusions 9 7 5 3 1 3 5 7 9 Innovative Services
Inclusions 9 7 5 3 1 3 5 7 9 Late Fee
Innovative Services 9 7 5 3 1 3 5 7 9 Late Fee
3
2020 International Conference on Emerging Trends in Informati on Technol ogy and Engineering (i c-ETITE)
Table 2: Parameter-wise Comparison Matrix
Car’
condition
Car Model
Price
consciousness
Discounts
Security
Deposits
Inclusions
Innovative
services
Late fee
Car’ s condi tion 1.0000 1.1117 1.6368 2.5479 4.2662 3.6529 3.2015 4.6006
Car Model 3.1511 1.0000 1.6662 3.3314 4.7848 4.4940 4.0578 5.7892
Price consciousness 2.7670 2.1022 1.0000 2.9111 4.9289 4.1333 3.9956 5.3956
Discounts 2.5547 1.6392 0.9429 1.0000 3.8292 3.2800 3.0281 4.4711
Security Deposits 1.4133 0.7551 0.5547 1.1397 1.0000 1.5600 1.7473 2.6444
Inclusions 1.6330 0.9206 0.5143 1.1213 2.2914 1.0000 1.8692 3.0356
Innovative services 1.3898 0.9221 0.8438 1.5187 2.7759 2.1596 1.0000 3.6737
Late fee 1.3270 0.6531 0.5278 0.9520 0.9378 1.0529 1.2372 1.0000
Table 3: Normalized Matrix
Car’
condition
Car
Model
Price
consciousness
Discounts
Security
Deposits
Inclusions
Innovative
services
Late fee
Priority
Car’s condition 0.066 0.122 0.213 0.175 0.172 0.171 0.159 0.150 0.154
Car Model 0.207 0.110 0.217 0.229 0.193 0.211 0.202 0.189 0.195
Price consciousness 0.182 0.231 0.130 0.200 0.199 0.194 0.198 0.176 0.189
Discounts 0.168 0.180 0.123 0.069 0.154 0.154 0.150 0.146 0.143
Securi ty Deposits 0.093 0.083 0.072 0.078 0.040 0.073 0.087 0.086 0.077
Incl usi ons 0.107 0.101 0.067 0.077 0.092 0.047 0.093 0.099 0.085
Innovative services 0.091 0.101 0.110 0.105 0.112 0.101 0.050 0.120 0.099
Late fee 0.087 0.072 0.069 0.066 0.038 0.049 0.061 0.033 0.059
Table 4: Ranking Matrix
Factors Weightage Rank
Car’s condition 0.153574 3
Car Model 0.194620 1
Price consciousness 0.188769 2
Discounts 0.142970 4
Security Deposits 0.076618 7
Inclusions 0.085455 6
Innovative services 0.098705 5
Late fee 0.059290 8
4
2020 International Conference on Emerging Trends in Informati on Technol ogy and Engineering (i c-ETITE)
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J? ^
&
10
8
6
4 — 3
.... . . y
cfr (fi cfi ^
8
y./ .y y y y y
’..4 "
Figure 1: Ranking o f Factors
Next, comes the redemption coupons and discounts.
Consumers prefer to purchase at companies who offer more
discounts. In the same way, i f a car rental company offers
discounts or redemption coupons attached to the purchase,
then the consumer would at least visit the website to have a
look at the offers, which w ill may lead to a booking. Thus, to
increase sales periodical discounts and redemption coupons
may be offered. Even though a consumer gets all the things he
needs, he loo ks f o r more.
In the same way, even though a car rental company taking
care of all the factors, i f it adds some innovative services
which other competing companies are not be offering, then it
w i l l attract more consumers towards that company. As a
result, there will be an increase in sales and profits. Next, in
the hierarchy o f the factors that car rental consumers consider
is ‘inclusions’. I f benefits such as fuel charges are included in
the same price or is a little higher than the actual price, then it
can attract more consumers though it is ranked sixth in the
consumer choice. Though ‘security deposit’ and ‘late fee’ are
in the last o f the consumer preference, they too are crucial in
decision making. Most consumers prefer a company that does
not charge a security deposit and charge a reasonable late fee.
V. Conclusion
The increase in competition o f car rental market allows
Car Rental Service Companies to find different ways to
increase sales and to sustain in the market. This paper uses
AHP to find weightage of all the factors that consumers
consider while booking a car for rent. A total of eight factors
in this exercise were identified, with the consumers giving
first preference to the Vehicle model, followed by price
consciousness, and the Cars' condition. As such, Car Rental
Service Companies must plan accordingly and improve their
services based on a hier archy to enhance their business. Future
research direction, this study can further be extended to
capture the linguistic judgment of consumers to rank the car
rental service company using some fuzzy multi-criteria
decision-making methods.
Ack no w l edg ment
The authors thank the anonymous customers that fil led the
surveys, and the Car Rental Companies in major metropolitan
cities of India for discussions from April 2019 to Sept. 2019.
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