EXPLORING THE ACCOMMODATION TYPES DIFFERENCE BY AGE GROUPS

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24 April 2017, 30th International Academic Conference, Venice ISBN 978-80-87927-35-9 , IISES
DOI: 10.20472/IAC.2017.030.028
NOPPAMASH SUVACHART
Khon Kaen University, Thailand
EXPLORING THE ACCOMMODATION TYPES DIFFERENCE BY AGE
GROUPS
Abstract:
This paper aimed to identify accommodation type that best fits for each customers’ segment. The
study aimed determine how difference between customers groups when choosing types of
accommodation, based on a questionnaire survey and descriptive statistical analyses of ANOVA (age
groups). Results obtained may serve as a useful reference for the owners of accommodation. The
output of the ANOVA analysis for type of accommodation had a statistically significant difference
between type means. Therefore, there is a statistically significant difference in the all types of
accommodation except hotel between age groups which they had attended. Based on these results,
marketing implications were suggestion and discussed.
Keywords:
market segment, difference, accommodation, customer, marketing
JEL Classification: A10, A10
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Introduction
A key factor for increased tourism industry development is facilities for travelers such
as accommodation, transportation, security, and traveling information. Kasikornbank
research center (2016) reported that there is a growing trend in the accommodation
business sector due to the increasing number of travelers in 2016. The large
accommodation scale results in a significant expansion in both Bangkok and the other
provinces, including expanding business overseas. Medium and small accommodation
sectors invested in the design of a unique building to attract travelers from their new
experience including pricing strategy by value for money with service quality and lower
cost. This supported the government's campaign to, increase the frequency of
domestic flights and transportation alternates thereby, encouraging travelers to
broaden their travel destination to include minorcities and geographical area in
Thailand. Alternate accommodations refer to hostel sites such as guest houses,
service apartments and commercial homes that provide paid lodging to the customers
on short-term period. They differ from the traditional hotels in terms of the limited
services provided with intrinsic cues and local culture. Commercial homes refer to
accommodation where guests pay to stay in private homes, where interaction takes
place with a host and/or family usually living in the premises. Alternate
accommodations focus on satisfying customer needs in a competitive environment.
The owners provide customers with rooms that are clean and neat as they are able to
furnish, depending on the services quality level and standard of the accommodation.
Literature review
A number of studies have examined hotel selection, the impact of customer reviews
by travelers, and the factors that led some to choose the alternate accommodation,
and example, Gunasekaran N. and Victor Anandkumar (2012) found that there were
four factors, consisting of homely atmosphere, value for money, local landscape and
guest-host relationship, had an affect on customer decision to choose the alternate
accommodation. They found that value for money perception of the costomers
concerning alternate accommodation. The research area was at Pondicherry, a
heritage coastal town in India. Studies for rural lodging sites such as Litvin, Goldsmith,
& Pan, (2008); Ng, David, & Dagger, (2011) revealed that accommodation services
were a very important intangible feature. The purchase process was inherently risky,
because customers could not evaluate the services before check in. They
recommended increasing interpersonal communication on customers’ buying
decisions. They found that most customers prefer to purchase accommodation
services independently, rather than relying on professional advice from a travel agent,
and that the Internet had emerged as a primary source of rural lodging sites
information on rural lodging sites (Hernández-Maestro, 2010; Hernández-Maestro et
al., 2007). Trusov, Bucklin, & Pauwels, (2009) found that among the various
communication channels rural lodging sites use, highly influential online
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communication model relies on infomediaries, or web bloggers that gather information
from different accommodation service providers and customer reviews. When the web
bloggers post more information, it resulted in had greater value for readers. Studies
concerning the impact of customer reviews such as Chevalier and Mayzlin (2006),
Pathak et al. (2010), and Zhu and Zhang (2010) all revealed that the number of online
reviews positively affect its business performance. In other studies by Duan et al.,
(2008a, 2008b); Liu, (2006) and Ye et al. (2011) found that the volume of online
reviews, separated from the ratings, emerged as the primary influence on sales and
there were positive relationship between the number of reviews and the number of
bookings for hotels. Such measures refer only to the number of reviews, not their
positive or negative tone. Thus it appeared that more reviews increase consumers’
awareness of the lodging sites, such that any publicity (positive or negative) may be
good publicity (Cheung & Thadani, 2012; Duan et al., 2008a, 2008b; Liu, 2006;
Vermeulen & Seegers, 2009).
The research conceptual framework model that is being explored is shown in figure 1.
Independent variables Dependent variables
Ranking of
short-term
accommodation
preference
to be mesured
Figure 1. research conceptual model
This paper aimed to identify accommodation type that best fits for each customers’
segment as represented in figure 1 which depicts the studies conceptual framework.
The study aimed determine how difference between customers groups when choosing
types of accommodation, based on a questionnaire survey and descriptive statistical
analyses of ANOVA (age groups). Results obtained may serve as a useful reference
for the owners of accommodation.
The accommodation
types best fits for each
segment (Gen X Y Z)
1. Hotel
2. Resort hotel
3. Service apartment
4. Motel
5. Motor hotel
6. Guesthouse
7. Pension
8. Bed and breakfast unit
9. Bungalow
10. Time-share unit
11. Holiday home
12. Cottage on mountain
13. Hostel
14. Tent campground
15. Cabin
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Methodology
Research Design
Qualitative and quantitative methods were used for this study. The questionnaire was
based on the inductive approach with an initial proposal based on relevant studies for
qualitative synthesis. The measure of internal consistency of researchers was tested
by Cronbach's alpha coefficient value. The alpha coefficient for the 14 variables was
0.880, revealing that the variables had relatively high internal consistency.
Data collection
A self-administered questionnaire with two sections was developed for use as the data
collection. The survey instrument was organized in to two sections as follows:
Section 1 collected information on respondents’ demographic data and use frequency
distribution based on gender, age, education level, and income level.
Section 2 was designed to ranking and exploring the popular accommodation types for
short stay by age groups (Gen X=31-51, Gen Y=22-30, and Gen Z=18-21) by mean
score and the univariate null hypothesis of ANOVA (age groups).
Therefore, null hypothesis would be:
H0 : The mean rating for accommodation preference is the same in the gender groups.
H1 : The mean rating for accommodation preference is not the same in the gender
groups.
If the p-value (significance level) is less than 5% (.05) reject the null hypothesis and
accept the alternative hypothesis.
Data collection was conducted on randomly selected days over two-month period.
Target respondents included people in Thailand aged 18 – 51 years (Gen Z =18-21,
Gen Y =22-30 and Gen X =31-51) who have had leisure traveling experience. The
survey was conducted with people who were working and studying in Bangkok. A total
of 520 questionnaires were distributed on May-June 2016. It was found that out of
520; only 488 usable responses were completed (with a response rate of 93.8%). All
of whom responded to the 24 variables in the measurement scale, and were used for
further analysis.
Results
Respondent Profiles
Of the 488 suitable respondents, 59.8% were female, 40.2% were male. Resulting in
19.6% more female respondents than male respondents. The respondents were
composed primarily of Gen Y (22-30 years) accounting for 34.4%, Gen X (31-51
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years) 33.6% and Gen Z (18-21 years) 32% of the respondents. Other demographic
data are given in Table 1.
Table 1. Demographic Profiles of Respondents (N=488)
Frequency
Percentage
(%)
Gender
Female
292
59.8
Male
196
40.2
Age (years)
18-21
156
32.0
22-30
168
34.4
31-51
164
33.6
Education
College and below
155
31.8
University
306
62.7
Graduate school
27
5.5
Monthly household income (Baht/USD in
parentheses )
Less than 10,000 (285)
168
34.4
10,001-15,000 (286-427)
195
40.0
15,001-20,000 (428-570)
100
20.5
20,001 or above (571 or above)
25
5.1
Exploring the popular accommodation types for short stay by age groups
The univariate null hypothesis of ANOVA (age groups). The descriptive table (see
Table 2) provides some very useful descriptive statistics, including the mean, standard
deviation and 95% confidence intervals for the dependent variable for each age group
(Gen X=31-51, Gen Y=22-30, and Gen Z=18-21), as well as when all groups are
combined (Total).
Table 2. Mean preference rating by age groups
Types of Accommodation
Age
N
Mean
Std. Deviation
Hotel
18-21
156
3.88
.819
22-30
168
3.92
.709
31-51
164
4.06
.671
Total
488
3.96
.736
Resort hotel
18-21
156
3.87
.763
22-30
168
4.16
.712
31-51
164
4.05
.769
Total
488
4.03
.756
Service apartment
18-21
156
3.72
.793
22-30
168
3.37
.747
31-51
164
3.09
.750
Total
488
3.39
.803
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Motel
18-21
156
3.81
.825
22-30
168
3.36
.835
31-51
164
2.87
.818
Total
488
3.34
.910
Motor hotel
18-21
156
3.90
.914
22-30
168
3.66
.908
31-51
164
3.41
.913
Total
488
3.66
.931
Guesthouse
18-21
156
3.76
.851
22-30
168
3.68
.843
31-51
164
3.13
.921
Total
488
3.52
.915
Pension
18-21
156
3.76
.875
22-30
168
3.35
.812
31-51
164
2.95
.881
Total
488
3.34
.915
Bed and breakfast unit
18-21
156
3.92
.831
22-30
168
3.81
.861
31-51
164
3.43
.966
Total
488
3.72
.912
Bungalow
18-21
156
3.71
.827
22-30
168
3.60
.937
31-51
164
3.26
.899
Total
488
3.52
.908
Time share unit
18-21
156
3.86
.823
22-30
168
3.38
.894
31-51
164
2.93
.890
Total
488
3.38
.947
Holiday home
18-21
156
3.90
.856
22-30
168
3.76
.879
31-51
164
3.05
.958
Total
488
3.57
.972
Cottage on mountain
18-21
156
3.85
.978
22-30
168
3.61
.997
31-51
164
2.98
.984
Total
488
3.47
1.051
Cabin
18-21
156
3.78
.918
22-30
168
3.40
.974
31-51
164
2.90
.948
Total
488
3.35
1.011
Hostel
18-21
156
3.77
.841
22-30
168
3.44
.887
31-51
164
2.74
.826
Total
488
3.31
.951
Tent campground
18-21
156
3.79
.887
22-30
168
3.28
.972
31-51
164
2.75
1.011
Total
488
3.26
1.046
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ANOVA for types of accommodation
Table 2. shows the output of the ANOVA analysis for type of accommodation and
whether we have a statistically significant difference between type means. To
determine whether the one-way ANOVA was statistically significant you need to look
at the "Sig." column. We can see from the table that we have a "Sig." value of 0.000
and 0.002 which means p < .005, p-value which is below 0.005, and, therefore, there
is a statistically significant difference in the all types of accommodation except for
hotel between age groups which they had attended.
Therefore, the researcher concludes that resort hotel, service apartment, motel, motor
hotel, guesthouse, bed and breakfast unit, bungalow, time share unit, holiday home,
cottage on mountain, cabin, hostel, tent campground was significantly dependent on
age group which they had attended (p < 0.005).
Table 3. ANOVA for types of accommodation
Types of accommodation
Sum of
Squares
df
Mean
Square
F
Sig.
Hotel
Between
Groups
2.789
2
1.394
2.588
.076
Within Groups
261.307
485
.539
Total
264.096
487
Resort hotel
Between
Groups
7.199
2
3.600
6.434
.002*
Within Groups
271.340
485
.559
Total
278.539
487
Service apartment
Between
Groups
31.464
2
15.732
27.025
.000*
Within Groups
282.337
485
.582
Total
313.801
487
Motel
Between
Groups
71.982
2
35.991
52.699
.000*
Within Groups
331.229
485
.683
Total
403.211
487
Motor hotel
Between
Groups
19.141
2
9.570
11.517
.000*
Within Groups
403.023
485
.831
Total
422.164
487
Guesthouse
Between
Groups
38.617
2
19.308
25.366
.000*
Within Groups
369.178
485
.761
Total
407.795
487
Pension
Between
Groups
52.625
2
26.312
35.925
.000*
Within Groups
355.226
485
.732
Total
407.850
487
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Bed and breakfast
unit
Between
Groups
21.872
2
10.936
13.845
.000*
Within Groups
383.104
485
.790
Total
404.975
487
Bungalow
Between
Groups
17.574
2
8.787
11.092
.000*
Within Groups
384.221
485
.792
Total
401.795
487
Time share unit
Between
Groups
69.468
2
34.734
45.822
.000*
Within Groups
367.638
485
.758
Total
437.107
487
Holiday home
Between
Groups
67.740
2
33.870
41.888
.000*
Within Groups
392.161
485
.809
Total
459.902
487
Cottage on
mountain
Between
Groups
65.592
2
32.796
33.695
.000*
Within Groups
472.061
485
.973
Total
537.654
487
Cabin
Between
Groups
62.362
2
31.181
34.740
.000*
Within Groups
435.309
485
.898
Total
497.670
487
Hostel
Between
Groups
88.315
2
44.157
60.783
.000*
Within Groups
352.341
485
.726
Total
440.656
487
Tent campground
Between
Groups
86.279
2
43.140
46.847
.000*
Within Groups
446.620
485
.921
Total
532.900
487
* p < .005
The results of this ANOVA as following:
1. Generation Y (22-30 years) prefer resort hotel more than others.
2. Generation Z (18-21 years) prefer service apartment more than others.
3. Generation Z (18-21 years) prefer motel more than others.
4. Generation Z (18-21 years) prefer, motor hotel more than others.
5. Generation Z (18-21 years) prefer guesthouse more than others.
6. Generation Z (18-21 years) prefer bed and breakfast unit more than others.
7. Generation Z (18-21 years) prefer bungalow more than others.
8. Generation Z (18-21 years) prefer time share unit more than others.
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9. Generation Z (18-21 years) prefer holiday home more than others.
10. Generation Z (18-21 years) prefer cottage on mountain more than others.
11. Generation Z (18-21 years) prefer cabin more than others.
12. Generation Z (18-21 years) prefer hostel more than others.
13. Generation Z (18-21 years) prefer tent campground more than others.
Implications
In order to satisfy the customers, the alternate accommodations should focus security
together with recreational facilities, local landscape, and special services. A alternate
accommodation should offer local life experience with relaxed atmosphere in
accommodation surroundings, including rooms. The pricing strategy adopted by
alternate accommodations could be specified as economically priced. Alternate
accommodations distribution strategy heavily relies on information technology, social
media, and internet. Any promotion advertising themes should focus on security,
recreational facilities, local landscape, availability of special services, and the owner of
the accommodation.
Acknowledgments
The author would like to thank Business Administration and Accountancy Faculty,
Khon Kaen University for their academic guidance and support.
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