Original Scientific Article
Examining the Seasonality of Travel-Related
Expenditure by Travel Purpose: The Case of Japan
Kenichi Shimamoto
Konan University, Hirao School of Management, Japan
ken_japan51@hotmail.com
Addressing seasonality for the travel industry has been a challenge for many tourist
destinations. Japan is no exception, and with its recent focus on developing into a
tourism nation, it has become even more critical to understand seasonality trends.
Methods to address seasonality, such as differential pricing, diversified attraction,
market diversification, and facilitation by the state will require the segmentation of
the market to form appropriate strategies. Therefore, to provide insight into the sea-
sonality of different markets, this paper categorises the travel-related expenditure
into six consumption items for three travel purposes: holiday travel, visiting friends
and relatives (vfr) travel, and business travel. It examines the trends and characteris-
tics of the seasonality and the fluctuation across the fiscal years from 2010 to 2017 for
domestic travel in Japan. The results show that amongst all three travel purposes, the
consumption items with relatively low seasonality and fluctuation across the obser-
vation period with stable highest and lowest expenditure months over the years, are
shopping/travel gifts expenditure for holiday travel; transportation and food/drink
expenditure for vfr travel; and transportation expenditure for business travel. In
contrast, the consumption items across the travel purposes with relatively signifi-
cant seasonality and inconsistent highest and lowest expenditure months over the
years are package holidays/tours expenditure and attraction/entrance expenditure
for vfr and business travel; and accommodation expenditure for business travel.
Keywords: tourism seasonality, consumption items, travel purpose, Japan
https://doi.org/10.26493/2335-4194.12.55-72
Introduction
Tourism is an attractive industry with the significant
impact it can have on the economy through not only
the additional income but also the effect it can have on
a wide range of industries. Japan has been introducing
policies to encourage inbound travel alongside the re-
inforcement of domestic tourismby Japanese residents
with the aim of becoming a tourism nation.
One phenomenon that has been widely studied is
the seasonality aspect of tourism. The influential work
by Bar-On (1975) provides a comprehensive study of 16
countries over 17 years. Bar-On (1975) and Hartmann
(1986) identify the leading causes of seasonality as nat-
ural factors and institutional factors. Natural factors
include climate, such as the duration of daylight, as
well as the amounts of sunshine, rain, and snow, which
are difficult to overcome (Hartmann, 1986; Lundtorp,
Rassing, &Wanhill, 1999). Institutional factors include
public and school holidays, which are affected by so-
cial factors, such as religion and culture (Hartmann,
1986; Allcock, 1989; Butler, 1994; 2001; Hinch & Jack-
son, 2000). Butler andMao (1997) suggest that the age-
ing society may affect seasonal patterns in the future
since they are less restricted in planning their travels.
This is identified in a number of literature resources
as an essential segment for countries, such as Sweden
Academica Turistica, Year 12, No. 1, June 2019 | 55
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
(Gustafson, 2002) and areas such as southern Europe
(Williams, King, Warnes, & Patterson 2000).
The adverse effects of tourism seasonality on the
economy have also been researched (Bar-On, 1975;
Murphy, 1981; Go, 1990; Lockwood & Guerrier, 1990;
Snepenger, Houser, & Snepenger, 1990; Faulkner &
Tideswell, 1997). Some of the economic impacts of
having an off-peak and peak times are the underutili-
sation and the overuse of the available capacity, which
affects employment and capital investment (Nadal,
Riera-Font, & Rossello, 2004). The inefficient use of
resources and facilities often causes loss of profit (Sut-
cliffe & Sinclair, 1980; Manning & Powers, 1984), and
the heavy reliance on the business during the peak
seasons makes it difficult to attract investors from the
private sector, which then may require public support
(Mathieson&Wall, 1982). The impact on accommoda-
tion and occupancy rate has also been discussed (Jef-
frey & Barden, 1999; Jeffrey, Barden, Buckley, & Hub-
bard, 2002; Fernández-Morales & Mayorga-Toledano,
2008; De Cantis, Ferrante, & Vaccina, 2011). The sea-
sonality impact on employment has been frequently
studied (e.g., Ball, 1988; Aswhorth & Thomas, 1999;
Krakover, 2000; Jolliffe & Farnsworth, 2003; Getz &
Nilsson, 2004).
There are also the social-cultural effects on tourists
and host destinations. Peak periods can cause con-
gestion and overcrowding of facilities, increase costs,
and reduce the quality of services, which impacts both
tourists and local residents (Hinch & Jackson, 2000;
Kennedy & Deegan, 2001). A higher number of peo-
ple could also lead to an increase in crime during peak
seasons (Mathieson & Wall, 1982). Extra facilities and
services such as public toilets, parking, and police may
be required. In this way, it has been argued that the
socio-cultural impacts put a strain on the social car-
rying capacity (Manning & Powers, 1984). There are
similar arguments concerning the environmental im-
pacts during the peak time, which could also impact
the carrying capacity of the environment (Manning &
Powers, 1984).
Considering the broad impact that seasonality has
on the economy, society, and the environment and
that the need to forecast tourism requires the under-
standing of the stability or instability of seasonality,
there are extensive studies that measure it to under-
stand the trends across many tourist destinations. For
example, Fernandez-Morales, Cisneros-Martinez, and
McCabe (2016) examine the seasonality of the num-
ber of tourists in the uk by using the Gini coefficient.
Duro (2016) analyses the trend of the seasonality of
the number of overnight stays in Spain, also by util-
ising the Gini coefficient. Coshall, Charlesworth, and
Page (2015) examine the inbound tourists’ trend for
vfr travel and holiday travel in Scotland. Moreover,
Juganaru, Aivaz, and Juganaru (2017) investigate the
seasonality trends, comparing Romania and other eu
countries, applying the mobile average method and
Struck method, for travel with overnight stays. A re-
cent study on tourism seasonality in Spain by Turrión-
Prats and Duro (2018) examines the impact of prices,
exchange rates, and income levels.
In these examples, studies on seasonality have been
conducted for various regions. However, the seasonal-
ity study focused on Japan is not well documented ex-
cept for the study byOi (2013; 2016). Oi (2016) analyses
the seasonality trends for domestic travel, examining
the number of tourists by categorising them into occu-
pational segments. Studying the number of overnight
stays, Oi (2013) analyses the seasonality and identifies
two types of tourists: tourists with the highmotivation
of leisure travel and tourists with the lowmotivation of
leisure travel for each region of Japan.
Possible solutions to address tourism seasonality
have also been well documented in previous studies.
The strategies to address seasonality impacts sum-
marised by Lee, Bergin-Seers, Galloway, O’Mahony,
and McMurray (2008) are differential pricing, diver-
sified attraction, market diversification, and facilita-
tion by the state. Differential pricing includes the in-
troduction of seasonal or promotional prices or of-
fers to increase or discourage visitation (Commons &
Page, 2001; Jang, 2004; Jeffery & Barden, 1999). Butler
(2001) suggests the closure of businesses during off-
peak season to reduce operational costs. Suggestions
for diversified attraction include the hosting of festi-
vals and events, such as sports in low seasons or the
development of new attractions and facilities (Witt &
Moutinho, 1995; Higham & Hinch, 2002; Goulding,
Baum, & Morrison, 2004). Off-season holiday pack-
56 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
ages and complementary offers and diversifying into
niche products or services are also suggested (Jeffery
& Barden, 1999; Witt & Moutinho, 1995; Goulding
et al., 2004; Jang, 2004). Approaches identified for
market diversification include marketing campaigns
to attract different markets during different periods
(Witt &Moutinho, 1995), the determination of the op-
timal segmentmix (Jang, 2004) and aligning with tour
operators and travel agents (Jeffery & Barden, 1999).
Areas recommended for facilitation by the state in-
clude the staggering of holidays, initiatives to increase
and encourage flexibility in the labour market, and the
provision of financial support such as loans, subsidies
and tax concessions (Witt & Moutinho, 1995; Gould-
ing, et al., 2004; Krakover, 2000; Baum & Hagen,
1999).
To develop such strategies, the segmentation of the
market will be necessary. Therefore, in order to pro-
vide insight into the seasonality of the different mar-
kets, this paper categorises the travel-related expendi-
ture into consumption items for holiday travel, vfr
travel and business travel. The most frequent mea-
surement unit of seasonality is the number of visitors
(Lundtorp, 2001). Other units include the number of
arrivals or departures, the number of overnight stays,
the length of stay, and the expenditures of the visitors
(Koc & Altinay, 2007; Karamustafa & Ulama, 2010;
Duro, 2018; Šegota & Mihalič, 2018). However, sea-
sonality research based on a range of travel-related
expenditures is limited.
For Japan, such studies do not exist and, to the
best of my knowledge, a study of the seasonality on
the different types of travel purpose has not been con-
ducted. This paper applies severalmethods to examine
the trends and characteristics of the seasonality and
the fluctuation across the fiscal years between 2010
and 2017 for domestic travel in Japan. It also exam-
ines the consistency of the highest and lowest expen-
diture months over the observation period for each
consumption item and travel purpose.
The structure of this paper is as follows. The next
section will describe the methods and data, and in the
third section, we will analyse the seasonality and the
fluctuation and the consistency of the highest and low-
est expenditure months across the fiscal years for each
travel purpose and each consumption item. The fourth
section will summarise the main results, followed by a
discussion section regarding policy implications. The
conclusion is provided at the end.
Methods and Data
The data applied are the domestic travel-related ex-
penditure by Japan residents for each consumption
item for each type of travel purpose from the JapanNa-
tional Tourism Survey from the Japan Tourism Agen-
cy for the period from 2010 to 2017 (http://www.mlit
.go.jp/kankocho/siryou/toukei/shouhidoukou.html?).
The Japan National Tourism Survey is a survey sent
twice a year to a random sampling of 2.5 million
residents in Japan (from the Basic Residents Reg-
istry). The total domestic travel expenditure is ob-
tained by the sum of the domestic travel expendi-
ture with overnight stays and the domestic travel ex-
penditure without such stays. There are three travel
purposes identified: holiday, vfr, and business. The
six consumption items for the travel expenditures are:
package holiday and tours expenses (package); trans-
portation expenses (transportation); accommodation
expenses (accommodation): food and drink expenses
(food&drink); shopping and ‘omiyage (travel gifts)’
expenses (souvenir); and entrance and attraction ex-
penses (attraction).
As an indicator for seasonality, the coefficient of
variation (cv) will first be adopted. The cv is calcu-
lated by dividing the standard deviationwith themean
in order to address the problem in which the variance
depends on themean. Thus, the equation is as follows.
cv =
1
p
i μt
√
1
n
∑
(pi ym,t −pi μt)2 =
p
iσt
p
i μt
. (1)
i refers to each consumption item. p denotes the pur-
pose of travel, which is classified as holiday, vfr, and
business. m represents months. t is fiscal year, pi ym,t is
the domestic travel-related expenditure by Japan res-
idents for a given month of a fiscal year for a specific
consumption item for each travel purpose. pi μt repre-
sents the mean monthly domestic travel-related ex-
penditure by Japan residents for a specific fiscal year
for each consumption item by travel purpose. n repre-
sents the number of months.
Academica Turistica, Year 12, No. 1, June 2019 | 57
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
As the second indicator of seasonality, the stan-
dard deviation of logarithms (sdl)will be utilised. The
equation is as follows.
sdl =
√
1
n
∑
(lnpi ym,t − lnpi μt)2. (2)
The logarithmic conversion enables an analysis of
fluctuations between months with low expenditure.
This indicator is also not dependent on a unit since it
is free from absolute values.
As the third indicator, we adopt the relative mean
deviation (rmd), which can be represented as follows.
rmd =
1
npi μt
∑
|pi μt −pi ym,t |. (3)
The numerator of the right-hand side of equation
(3) represents the difference between pi ym,t, the domes-
tic travel-related expenditure by Japan residents for a
given month of a fiscal year for a specific consump-
tion item for each travel purpose and pi μt, the mean
monthly domestic travel-related expenditure by Japan
residents for a given fiscal year for each consumption
item for each travel purpose, which is measured in ab-
solute values. As in the case with cv, in order for the
indicator to not depend on the mean, it is divided by
p
i μt. Therefore, this represents the relative dispersity
of domestic travel-related expenditure by Japan resi-
dents, which is measured in absolute values. If the do-
mestic travel-related expenditure for Japan residents
each month is equivalent, then the indicator is 0. In
contrast, if the expenditure for one month completely
makes up the entire annual expenditure, the indicator
will be 2(n − 1)/n. Thus, the smaller the indicator, the
smaller the dispersity between the months. However,
since this indicator relies on the absolute value differ-
ence of themonthly travel-related expenditure and the
mean monthly travel-related expenditure, it is unre-
sponsive to changes amongst months taht are above
or below the mean (Sen, 1973).
The fourth indicator applied to overcome this chal-
lenge is theGini coefficient. The indicator is defined as
follows. Suppose that the number of months in a year
is, n, the domestic travel-related expenditure by Japan
residents for a given month of a fiscal year for a spe-
cific consumption item for each travel purpose is pi ym,t
and the mean monthly domestic travel-related expen-
diture by Japan residents for a given fiscal year for each
consumption item by travel purpose is pi μt. Then, the
order from the smallest monthly expenditure would
be, i.e. pi ym=1st,t ≤ pi ym=2nd,t ≤ pi ym=3rd,t · · ·. From the
above, the Gini coefficient is represented as follows.
gini =
1
2n2 pi μt
∑∑
|pi ym,t −pi yl,t |. (4)
Here, the Gini coefficient represents the ratio be-
tween themean annual domestic travel-related expen-
diture and the mean of the absolute value difference
between travel-related expenditures of two randomly
selected months, m, l. Based on this indicator, if the
distribution of the domestic travel-related expendi-
ture for each month is entirely equivalent, gini is 0.
In contrast, if the domestic travel-related expenditure
is concentrated in one month and the other n − 1
months have no expenditure, gini becomes 1. The
characteristic of the Gini coefficient is its sensitivity to
central observations, giving greater weight to changes
that occur in the months situated around the mode
of monthly distribution (Duro, 2016; Turrión-Prats &
Duro, 2018).
Next, as the indicator of seasonality, the Theil in-
dex, which incorporates the entropy concept to in-
formation theory, is applied. The index utilises the
characteristics that the maximum value of entropy
is attained by a uniformly distributed random vari-
able. According to this index, the larger the difference
between the maximum value and the entropy of the
domestic travel-related expenditure is, the larger the
dispersity. The Theil index can be represented as fol-
lows.
ti =
1
n
∑ p
i ym,t
p
i μt
⎛⎜⎜⎜⎜⎜⎝ln
p
i ym,t
p
i μt
⎞⎟⎟⎟⎟⎟⎠
=
1
n
∑
p
i μtln
1
p
i μt
−
∑
p
i ym,tln
1
p
i ym,t
. (5)
Results
Seasonality for Each Consumption Item
by Travel Purpose
For each travel purpose, seasonality will be examined
for each consumption item for each of the fiscal years
58 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
.
.
.
.
.
.
       
(a) Package
.
.
.
.
.
.
       
(b) Transportation
.
.
.
.
.
.
       
(c) Accommodation
.
.
.
.
.
.
       
(d) Food&Drink
.
.
.
.
.
.
       
(e) Souvenir
.
.
.
.
.
.
       
(f) Attraction
Figure 1 Seasonality Fluctuation for Holiday Travel
Notes Light gray – relative mean deviation, dark gray – coefficient of variation, dark gray dashed – standard deviation of
logs, black – Gini coefficient, black dashed – Theil entropy measure.
observed. The seasonality indicator results from each
analysis will be examined in the following figures. The
first travel purpose reviewed is holiday travel. Figure
1(a) shows that, regarding package for holiday travel,
most indicators peak in 2011 and then decrease until
2014, followed by a gradually increasing trend. Next,
from Figure 1(b), the transportation results show that
all indicators slightly peak in 2011 and gently decrease
until 2014, followed by an increase and decrease for
every other year. Figure 1(c) indicates that for accom-
modation, most indicators slightly decline from 2011
to 2016 and then increase in 2017. Figure 1(d) indicates
that all indicators for food&drink show a modest de-
cline and then an increase in 2017. The results for sou-
venir in Figure 1(e) show a gentle U shape for almost
all indicators. The overall fluctuations are not large.
Figure 1(f) indicates that for attraction the fluctuations
between the years are rather large, with all indicators
increasing and decreasing every other year.
Next, with regards to vfr travel, the results for
each consumption item are as follows. Figure 2(a)
shows that for package, most indicators drop in 2011
and then peak in 2013 and 2016, indicating large fluc-
tuations in the seasonality across the fiscal years. Next,
from Figure 2(b), the results for transportation show
limited fluctuations for all indicators except for in-
creases in 2017. Figure 2(c) indicates a declining trend
for accommodation with large fluctuations for most
indicators. Figure 2(d) shows that most indicators for
food&drink show slight fluctuations with increases in
2017. For most souvenir indicators, Figure 2(e) shows
some small fluctuations over the years, with increases
in 2017. Figure 2(f) indicates that all indicators for at-
traction decline in 2011 and peak in 2012 and 2015 and
most remain flat after that.
Finally, wewill review the trends for business travel.
The indicators for package in Figure 3(a) show gen-
tle inverted U shapes with peaks in 2012 and declines
ending in 2014. They then increase for most indica-
tors. Moreover, the fluctuations in seasonality over the
observation period are large. Next, from Figure 3(b),
the results for transportation show gradual increas-
ing trends for most indicators, though the seasonality
fluctuations over the years are very small. Figure 3(c)
shows large fluctuations across the years for accom-
modation with drops in 2011 and 2014 and peaks in
2013 and 2016 for all indicators. Figure 3(d) indicates
that for food&drink almost all indicators show grad-
ual increasing trends with peaks in 2014. Figure 3(e)
indicates that for souvenir, all indicators show a slight
Academica Turistica, Year 12, No. 1, June 2019 | 59
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
.
.
.
.
.
.
.
.
       
(a) Package
.
.
.
.
.
.
.
.
       
(b) Transportation
.
.
.
.
.
.
.
.
       
(c) Accommodation
.
.
.
.
.
.
.
.
       
(d) Food&Drink
.
.
.
.
.
.
.
.
       
(e) Souvenir
.
.
.
.
.
.
.
.
       
(f) Attraction
Figure 2 Seasonality Fluctuation for vfr Travel
Notes Light gray – relative mean deviation, dark gray – coefficient of variation, dark gray dashed – standard deviation of
logs, black – Gini coefficient, black dashed – Theil entropy measure.
decrease in 2011 and a gradual increase after that with a
large increase in 2017. The results are large fluctuations
in seasonality over the observation period. Figure 3(f)
shows fluctuations for attraction with drops in 2011,
followed by inverted U shapes with peaks in 2013 and
ending in 2016 with large increases in 2017 for most
indicators. This indicates large fluctuations in season-
ality over the observation period.
Changes to Seasonality over the Observation Period
for Each Consumption Item of Each Travel Purpose
Next, the changes in the seasonality between the first
and last fiscal year of the observation period will be
compared for holiday travel, vfr travel, and business
travel to observe whether the seasonality is increas-
ing or decreasing over the years. From Table 1, busi-
ness travel shows that for all consumption items, all
the indicators are increasing. This suggests that busi-
ness travel has not been able to reduce the seasonality
during the observation period, compared to holiday
and vfr travel. For vfr travel, the indicators have
increased in four out of the six consumption items:
transportation, food&drink, souvenir, and attraction.
However, the monthly seasonality for package and
accommodation have decreased. Concerning holiday
travel, the indicators for half of the consumption items,
package, souvenir, and attraction have increased, while
they have decreased for transportation, accommoda-
tion, and food&drink.
Since the results for the different indicators (rela-
tive mean deviation, coefficient of variation, the stan-
dard deviation of logs, Gini coefficient and Theil en-
tropy measure) on seasonality show consistently sim-
ilar trends, the remaining analysis will focus on the
Gini coefficient, which is frequently used to examine
seasonality.
The Magnitude of the Seasonality for Each
Consumption Item by Travel Purpose
over the Observation Period
Next, the magnitude of the seasonality over the obser-
vation period will be examined for each consumption
60 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
.
.
.
.
.
.
.
.
.
.
.
       
(a) Package
.
.
.
.
.
.
.
.
.
.
.
       
(b) Transportation
.
.
.
.
.
.
.
.
.
.
.
       
(c) Accommodation
.
.
.
.
.
.
.
.
.
.
.
       
(d) Food&Drink
.
.
.
.
.
.
.
.
.
.
.
       
(e) Souvenir
.
.
.
.
.
.
.
.
.
.
.
       
(f) Attraction
Figure 3 Seasonality Fluctuations for Business Travel
Notes Light gray – relative mean deviation, dark gray – coefficient of variation, dark gray dashed – standard deviation of
logs, black – Gini coefficient, black dashed – Theil entropy measure.
item by travel purpose. The mean of the Gini coeffi-
cient for the observation period will be used to deter-
mine the magnitude of the seasonality.
From Figure 4(a) and Table 2, concerning holi-
day travel, the seasonality for accommodation is the
largest amongst the six consumption items during the
observed period. This is followed by the seasonality
for transportation and food&drink. Attraction is next
in most years with souvenir and package showing the
smallest seasonality. The seasonality for package is not
only low but is stable for the more recent years. This
suggests that travel agencies have been able to reduce
seasonality differences with effective group travel or
package tours throughout the year.
Next, from Table 2, as for vfr travel, the season-
ality for attraction is larger than others during the ob-
served period. In particular, as seen in Figure 4(b),
seasonality has been great in recent years. Table 2
shows that package has the second largest seasonal-
ity out of the six consumption items with substantial
changes by year. This is followed by accommodation
and food&drink. Figure 4(b) shows that accommo-
dation has large fluctuation in seasonality depend-
ing on the year. In contrast, Figure 4(b) shows that
food&drink seasonality is stable throughout the ob-
served years, maintaining the middle position over
the observation period. Souvenir achieves a lower level
of seasonality in the more recent years, achieving one
of the lowest positions.Transportationmaintains a low
position throughout the observation period withmin-
Academica Turistica, Year 12, No. 1, June 2019 | 61
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
Table 1 Comparison of Seasonality between the First Year of Observation and the Last Year of Observation
Item Holiday VFR Business
Package Increase in all indicators Decrease in all indicators Increase in all indicators
Transportation Moderate decrease in all indi-
cators
Increase in all indicators Increase in all indicators
Accommodation Moderate decrease in majority
of indicators
Moderate decrease in majority
of indicators and decrease for
remaining
Increase in all indicators
Food&Drink Moderate decrease in all indi-
cators
Moderate increase in more
than half of indicators
Increase in all indicators
Souvenir Increase in all indicators Moderate increase in more
than half of indicators
Increase in all indicators
Attraction Increase in all indicators Increase in all indicators Increase in all indicators
Notes ’Majority’: 4 out of 5 indicators; ’More than half ’: 3 out of 5 indicators; ’Moderate’: The ratio of difference of each
indicator between the first year and the last year to the indicator of the last year is ±0.1.
.
.
.
.
.
.
       
(a) Holiday
.
.
.
.
.
.
       
(b) vfr
.
.
.
.
.
.
       
(c) Business
Figure 4 Fluctuation by Consumption Item: Gini
Notes Light gray – package, light gray dashed – transporta-
tion, gray – accommodation, gray dashed – food&drink,
black – souvenir, black dashed – attraction.
imum fluctuation over the years, which suggests the
least impact of seasonality.
With respect to business travel, Table 2 shows that
attraction has the most substantial fluctuation in sea-
sonality out of the six consumption items for the pe-
riod observed. Figure 4(c) confirms that it is also the
largest in most years. This is followed by package and
Table 2 Mean of Gini Coefficient from 2010 to 2017
Item Holiday VFR Business
Package . () . () . ()
Transportation . () . () . ()
Accommodation . () . () . ()
Food&Drink . () . () . ()
Souvenir . () . () . ()
Attraction . () . () . ()
Mean . () . () . ()
Notes Numbers in parentheses represent the rank order.
then accommodation and souvenir. Figure 4(c) shows
that the fluctuation in seasonality for accommodation
is not consistent over the years. The seasonality for
food&drink is stable for themost recent fiscal years at a
consistently low level.Transportationhas the least fluc-
tuation over the years, mostly at the lowest level. This
is similar to the results of vfr travel.
Comparing the Magnitude of the Seasonality
between Travel Purposes
Table 2 shows that the seasonality of holiday travel is
the smallest of the three travel purposes with a value of
0.134. Business travel is second with 0.156. vfr travel
is third with 0.194, suggesting that it is the most unsta-
ble.
62 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
.
.
.
.
.
       
(a) Package
.
.
.
.
.
       
(b) Transportation
.
.
.
.
.
       
(c) Accommodation
.
.
.
.
.
       
(d) Food&Drink
.
.
.
.
.
       
(e) Souvenir
.
.
.
.
.
       
(f) Attraction
Figure 5 Seasonality Trends by Consumption Item
Notes Light gray – holiday, dark gray – business, black – vfr.
Comparing Seasonality Trends between Travel
Purposes for Each Consumption Item
Next, for each consumption item, we compare the an-
nual seasonality trends for each travel purpose. Con-
cerning package, Figure 5(a) shows that holiday travel
has the lowest seasonality difference during most of
the period observed. There is also an indication that
the fluctuations across the fiscal years are limited for
holiday travel.
In contrast, the difference in seasonality is high for
business and vfr travel, and the fluctuations across
the fiscal years are large for both. Hence, depending
on the year, business travel or vfr travelmay have the
largest seasonality.
Next, concerning transportation, Figure 5(b) indi-
cates that business travel consistently has the least sea-
sonality impact out of the three travel purposes for
the period observed. It also shows that the fluctuations
across the fiscal years for business travel are limited.
Holiday travel appears second concerning the level of
seasonality. Seasonality for vfr travel is the greatest
for most of the period observed and is consistently
high over the years.
With respect to accommodation, Figure 5(c) shows
that holiday travel is mostly in second place concern-
ing seasonality for most of the years, and the seasonal-
ity is stable across the period observed. Business travel
and vfr travel show large changes in the order of sea-
sonality. Business travel often shows the lowest season-
ality, but it appears as the highest twice, showing large
fluctuations depending on the year. vfr travel often
shows the largest seasonality, but it appears as the low-
est twice, which represents large changes in seasonal-
ity.
With regard to food&drink, Figure 5(d) shows that
the seasonality of vfr travel is consistently larger
than the others during the observation period and the
seasonality of business travel is smaller than the oth-
ers for most of the period. The seasonality for holiday
travel is the second largest and stable over the years
observed.
As for souvenir, Figure 5(e) indicates that the sea-
sonality of holiday travel is smaller than others for
most of the period observed, and the fluctuations
across the fiscal years are small. The seasonality of
business travel starts at the lowest level of the three
travel purposes, but shows an increasing trend, end-
ing with the highest level of seasonality. Excluding the
last two years, vfr travel shows the greatest season-
ality over the years.
Concerning attraction, Figure 5(f) shows that the
seasonality for business travel tends to increase. The
seasonality of vfr travel is larger than others formost
of the period observed. The seasonality of holiday
travel is relatively small and alternates between an in-
crease and decrease every year,
Academica Turistica, Year 12, No. 1, June 2019 | 63
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
Table 3 Spearman’s Rank Correlation Test:
Mean of Gini Coefficient
Item Holiday vs
VFR
Holiday vs
Business
VFR vs
Business
Spearman’s rho –. –. .
Pro. > |t| . . .
N   
Seasonality Characteristics for Each Consumption
Item by Travel Purpose
Next, the similarities between seasonality for the dif-
ferent travel purposes for each consumption item and
their characteristics will be observed. Table 2 shows
that the seasonality for souvenir is relatively small and
stable compared to the other consumption items for
each of the travel purposes. In contrast, Table 3 shows
that the seasonality for accommodation is substantial
in all of the travel purposes.
According to Spearman’s rank correlation coeffi-
cient of Table 3, the rank for the seasonality of the
consumption items for business travel and that of vfr
travel are significantly positively correlated, suggest-
ing that they are similar. For instance, in Table 2, the
seasonality for attraction and package for both busi-
ness and vfr travel are significant and, thus, unstable.
In contrast, the seasonality for transportation for both
business and vfr travel are smaller and more stable
than the others.Moreover, Table 3 shows that the rank-
ing between the seasonality for consumption items of
holiday travel and vfr/business travel are negatively
correlated, suggesting that they have opposite results.
However, it should be noted that the correlation is not
significant.
The Fluctuation of the Seasonality for Each
Consumption Item for Each Travel Purpose over the
Observation Period
Next, in order to observe the fluctuation of the season-
ality during the observation period, the standard devi-
ation of the Gini coefficient will be measured for each
consumption item.1 The aim is to examine whether
1Due to limitation of space, the results on the fluctuation of
the seasonal range have been omitted due to similar results
Table 4 Standard Deviation of Gini Coefficient between
2010 and 2017
Item Holiday VFR Business
Package . () . () . ()
Transportation . () . () . ()
Accommodation . () . () . ()
Food&Drink . () . () . ()
Souvenir . () . () . ()
Attraction . () . () . ()
Mean . () . () . ()
Notes Numbers in parentheses represent the rank order.
the year-to-year fluctuations of the seasonality of con-
sumption items for each fiscal year are large. The con-
firmation of such trends will aid in understanding the
stability and predictability of the market.
First of all, Table 4 indicates that, concerning holi-
day travel, the order of fluctuation over the fiscal years
concerning the seasonality of the expenditure, starting
from the largest, is attraction, accommodation, pack-
age, transportation, souvenir, and food&drink.With re-
spect to holiday travel, the fluctuations of the season-
ality for food&drink (0.013) and souvenir (0.016) are
particularly small, and attraction (0.020) and accom-
modation (0.019) are relatively large for holiday travel.
The mean of the fluctuations of the seasonality of all
consumption items for holiday travel is smaller than
those of the other travel purposes and is the most sta-
ble.
Next, concerning business travel, Table 4 shows
that the order of seasonality fluctuation amongst the
fiscal years, starting from the largest, is attraction,
souvenir, package, accommodation, food&drink, and
transportation. In particular, attraction (0.102), sou-
venir (0.059), and package (0.056) are large. Com-
pared to the seasonality fluctuations for all consump-
tion items for holiday and vfr travel, business travel
shows a relatively large fluctuation for all consumption
items, excluding transportation. The fluctuation for
attraction, souvenir, and package are especially large,
which means there are opportunities to address the
obtained from the standard deviation. Results can be pro-
vided upon request.
64 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
seasonality in business travel for these areas. Finally,
concerning vfr travel, Table 4 indicates that the sea-
sonality fluctuation amongst the fiscal years, in or-
der of size, is package, accommodation, attraction, sou-
venir, food&drink, and transportation. In order to re-
duce the seasonality in vfr travel, consumption items
with the largest fluctuation, such as package (0.046)
and accommodation (0.045), will need to be priori-
tised.
The Seasonality Fluctuation for Total Travel
Expenditure by Travel Purpose
across the Observation Period
From Table 4, the fluctuation amongst the fiscal years
concerning seasonality of the total travel expenditure
for holiday travel shows the lowest level of fluctuation
and that it is the most stable over the observation pe-
riod with a value of 0.017. The second is vfr travel
with a value of 0.033. The third is business travel with
a value of 0.051, suggesting that it is the most unpre-
dictable of the three travel purposes. Hence, business
travel is where there are the most significant oppor-
tunities to reduce the seasonality fluctuations and de-
velop a more stable market.
Characteristics of the Seasonality Fluctuation for Each
Consumption Item across the Observation Period
for Each Travel Purpose
Next, concerning the fluctuation of seasonality across
the fiscal years for each consumption item by travel
purpose will be examined for similarities and char-
acteristics. Table 4 shows that the seasonality fluctua-
tions across the fiscal years for attraction and package
are significant in each of the travel purposes. There-
fore, these businesses could be considered unstable
and challenging from a planning perspective. In con-
trast, Table 4 shows that the seasonality fluctuation
across the fiscal years for each travel purpose is small
for transportation and food/drink. Therefore, these can
be considered to be stable in each of the travel pur-
poses. According to Spearman’s rank correlation coef-
ficient in Table 5, the rank between the seasonality of
the consumption items for holiday travel and that of
vfr travel; between that of holiday travel and that of
business travel; and between that of vfr travel and
Table 5 Spearman’s Rank Correlation Test: Standard
Deviation of Gini Coefficient
Item Holiday vs
VFR
Holiday vs
Business
VFR vs
Business
Spearman’s rho . . .
Pro. > |t| . . .
N   
that of business travel, are all positively correlated,
suggesting that they are similar. However, it should
be noted that these correlations are not significant.
Highest and Lowest Expenditure Months for Each
Consumption Item by Travel Purpose
Next, the months with the highest and lowest expen-
diture for each consumption item by travel purpose
will be examined. The primary purpose is to under-
stand the months when expenditure is concentrated
and when it is light for each consumption item and
travel purpose.
Concerning holiday travel, Table 6 shows that Au-
gust has themost significant expenditure for all the fis-
cal years observed for all consumption items exclud-
ing package. It can be assumed that this is due to Au-
gust being themonthwhenmostworkers in Japan take
their summer holidays as well as children and students
being out of school for summer. Though August does
appear to have the largest expenditure for package in
some years, others show October and November to
have the largest expenditure. This is likely to do with
autumn being a popular season to take holidays to en-
joy the autumn foliage. Concerning the month with
the smallest expenditure, Table 6 shows that Febru-
ary is the smallest month for the majority of the fiscal
years observed, for all consumption items except for
package. This may be due to February being one of the
coldest months and the shortest one.
Next, concerning vfr travel, Table 7 indicates that
August has the largest expenditure for transportation,
food&drink, souvenir, and attraction for all of the fiscal
years observed. Concerning accommodation, though
August is the largest for most years, May, which has
the GoldenWeek holiday, also appears as the largest in
some years. Concerning the month with the smallest
Academica Turistica, Year 12, No. 1, June 2019 | 65
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
Table 6 Highest/Lowest Month: Holiday Travel
Year Category Package Transportation Accommodation Food&Drink Souvenir Attraction
Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest
 Month Aug Dec Aug Jan Aug Feb Aug Feb Aug Feb Aug Feb
ac            
 Month Nov Jan Aug Feb Aug Apr Aug Mar Aug Jan Aug Feb
ac            
 Month Nov Jan Aug Jan Aug Feb Aug Feb Aug Feb Aug Jan
ac            
 Month Nov Jan Aug Feb Aug Jan Aug Feb Aug Feb Aug Apr
ac            
 Month Oct Feb Aug Feb Aug Apr Aug Jun Aug Apr Aug Feb
ac            
 Month Nov Jan Aug Jan Aug Jun Aug Feb Aug Feb Aug Feb
ac            
 Month Aug Feb Aug Feb Aug Feb Aug Feb Aug Feb Aug Feb
ac            
 Month Oct Jan Aug Feb Aug Feb Aug Feb Aug Jan Aug Jan
ac            
Notes ac: the amount of consumption. Unit of ac: Million yen.
Table 7 Highest/Lowest Month: vfr Travel
Year Category Package Transportation Accommodation Food&Drink Souvenir Attraction
Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest
 Month Jan Sep Aug Feb Aug Feb Aug Feb Aug Feb Aug Jun
ac            
 Month Jul Mar Aug Oct May Jan Aug Oct Aug Jun Aug Nov
ac            
 Month Aug Dec Aug Feb May Feb Aug Feb Aug Feb Aug Feb
ac            
 Month Jan Feb Aug Feb Aug Feb Aug Feb Aug Feb Aug Jul
ac            
 Month Dec Apr Aug Feb Aug Apr Aug Feb Aug Apr Aug Feb
ac            
 Month Dec Feb Aug Feb Aug Jun Aug Feb Aug Feb Aug Nov
ac            
 Month Oct Mar Aug Feb Aug Jan Aug Feb Aug Feb Aug Jun
ac            
 Month Jan Oct Aug Feb Aug Jul Aug Feb Aug Feb Aug Feb
ac            
Notes ac: the amount of consumption. Unit of ac: Million yen.
expenditure for vfr travel, Table 7 indicates Febru-
ary is the most frequent for all the consumption items.
In particular, the frequencies are high for transporta-
tion, food&drink, and souvenir. Package does not show
a clear largest or smallest expenditure month.
Finally, concerning business travel, Table 8 shows
66 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
Table 8 Highest/Lowest Month: Business Travel
Year Category Package Transportation Accommodation Food&Drink Souvenir Attraction
Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest Highest Lowest
 Month Feb Nov Feb Aug Feb Aug Feb Oct Feb Dec Feb Nov
ac            
 Month Oct Mar Jun Jan Sep Jan Jun Apr Jul Apr Feb Sep
ac            
 Month Jul Jan May Jan Jun Jan Feb Jan Jul Jan May Dec
ac            
 Month Jul Mar Jun Jan Jan Nov Mar Aug Feb Mar Jun Dec
ac            
 Month Feb Dec Mar Aug Mar Aug May Aug Feb Apr Oct Jan
ac            
 Month Dec Feb Jun Jan Dec Oct Nov Jan Oct Jan Dec Sep
ac            
 Month Nov Apr Jun Jan Jun Jan Jul Jan Nov Mar Sep Oct
ac            
 Month May Jan Jun Feb Oct Feb Dec Jan Nov Jan Nov Aug
ac            
Notes ac: the amount of consumption. Unit of ac: Million yen.
that there is no clear largest or smallest month, except
for transportation where June is the largest month and
January the smallest.
Discussions
Themain results regarding seasonality are summarised
as follows.
• Based on total expenditure, holiday travel is found
to be the least impacted by seasonality and is the
most stable of all the travel purposes. This is fol-
lowed by business travel. Results from vfr travel
suggest that it is the most unstable of the travel
purposes. However, past studies by Fernández-
Morales, Cisneros-Martinez, andMcCabe (2016)
on the United Kingdom (uk) and by Fernández-
Morales (2017) on Spain, which compare the
seasonality of these three travel purposes, find
that holiday travel has the strongest seasonality
impact and business travel the weakest. These
studies examine the number of tourists, whereas
this paper examines travel-related expenditure,
which may be the reason for the difference, or
it could be the difference in market conditions
compared to Japan. Japan has 40–50more pub-
lic holidays than the uk and Spain do, and they
are spread out throughout the year. This suggests
that the state interventions in Japan to provide
a public holiday every month and the encour-
agement of the usage of paid holidays have been
effective in reducing seasonality and improve
productivity in the travel business (Morikawa,
2008; Yagasaki, 2015). The high seasonality in
vfr travel could be due to a social-cultural effect.
During the Bon Festival in August, the Japanese
often return to their home town.
• For each travel purpose, the seasonality for sou-
venir is relatively small and stable compared to
the other consumption items. The tradition in
Japan of giving ‘omiyage’ (travel gifts) to col-
leagues at work and neighbours may be work-
ing positively to limit seasonality in this instance.
In contrast, the seasonality for accommodation
is large and irregular. The seasonality for each
consumption item for business and vfr travel
are positively related, and thus, are similar. For
Academica Turistica, Year 12, No. 1, June 2019 | 67
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
example, while the seasonality of attraction and
package are large and unstable, the seasonality
for transportation is the smallest and most stable
of the consumption items for both business and
vfr travel. However, holiday travel and busi-
ness/vfr travel are negatively correlated, but sta-
tistically insignificant concerning the order of the
seasonality of the consumption items.
• The main results concerning the increase/decre-
ase in seasonality for each consumption item for
the period observed are as follows.
1. Concerning business travel, the seasonality
for all the consumption items increased. For
vfr travel, the seasonality for four consump-
tion items (transportation, food&drink, sou-
venir, and attraction) increased. In contrast,
those of package and accommodation decre-
ased. Finally, concerning holiday travel, the
seasonality for half of the consumption items
(package, souvenir, and attraction) increased,
and the other half (transportation, accommo-
dation, and food&drink) decreased.
2. For all travel purposes, the seasonality of sou-
venir and attraction increased for the period
observed.
Next, the main results concerning the fluctuation
of the seasonality over the fiscal years are as follows.
• Seasonality fluctuation for holiday travel was the
smallest and the most stable, followed by vfr
travel and then business travel, which was the
greatest. All the consumption items within hol-
iday travel show the smallest fluctuation in sea-
sonality over the fiscal years compared with the
other travel purposes. In particular, the season-
ality fluctuation for food/drink and souvenir are
small. These results are slightly different from the
intra-year seasonality result forwhich vfr travel
showed the greatest seasonality. The impact on
seasonality over the observed period on business
trips may be influenced by the economy, which
may have a larger impact on seasonality. Kulen-
dran and Wilson (2000) suggest that the impact
of economic variables is essential to understand-
ing business travel.
• Concerning business travel, the seasonality fluc-
tuation for attraction, souvenir, and package are
large, indicating substantial changes in the sea-
sonality depending on the year.
• Attraction and package are substantial for each of
the travel purposes in terms of seasonality fluc-
tuations across the fiscal years. This indicates
instability and unpredictability. In contrast, the
seasonality fluctuations for transportation and
food&drink are small for each of the travel pur-
poses across the fiscal years, which make them
easier to plan.
• The seasonality fluctuation of all the consump-
tion items between holiday travel and business
travel; between holiday travel and vfr travel;
and between vfr travel and business travel are
all positively-correlated, but the results are in-
significant.
Next, themain observations concerning the largest
and the smallest expenditure months are provided be-
low.
• Concerning holiday travel, August is the month
when the expenditure is the largest and Febru-
ary is the smallest. From the details of each con-
sumption item, transportation, accommodation,
food&drink, souvenir, and attraction, the largest
expenditure month for the observation period
is August. The spending on package is high not
only in August but also during the autumn fo-
liage season of October and November. The low-
est spending on transportation, accommodation,
food&drink, souvenir, and attraction is in Febru-
ary for most of the years observed. The same
trend is seen in vfr travel, except the concen-
trations in the highest and lowest months are
not as severe. The highest month for transporta-
tion, food&drink, souvenir, and attraction is again
August during the observation period. It is also
the highest month for accommodation in most of
the years observed. February is again the low-
est month for all the consumption items. The
concentration in February is especially high for
transportation, food&drink, and souvenir. These
observations indicate that for holiday and vfr
68 | Academica Turistica, Year 12, No. 1, June 2019
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
travel, the seasonality is stable overmultiple years,
which will enable the development of a targeted
strategy. Finally, concerning business travel, the
seasonality for the largest and smallest expendi-
turemonths aremore dispersed than holiday and
vrf travel are. In particular, the largemonths are
dispersed. Since the high seasonality months are
not consistent over the years, a more flexible plan
may be required to tackle the business travelmar-
ket.
• Next, we will identify the three consumption
items for each travel purpose concerning low
seasonality and fluctuation across the period ob-
served with stable2 largest and smallest months.
These are souvenir of holiday travel, transporta-
tion and food&drink of vfr travel and trans-
portation of business travel. Since these areas are
stable and predictable within each travel purpose,
they will not be as difficult to plan and manage.
In contrast, the three consumption items across
the travel purposes with relatively significant sea-
sonality and fluctuation and inconsistent largest
and smallest months over the years, are package
and attraction of vfr and business travel and ac-
commodation of business travel. The magnitude
of the seasonality and the fluctuation across mul-
tiple years will be substantial for these areas and
the peak and off-peak months will not be con-
sistent, which suggests unpredictable businesses
whichwill bemore challenging to plan andmain-
tain.
These results that identify the areas of strong sea-
sonality suggest future research opportunities to ex-
amine the determining factors behind the strong sea-
sonality. For example, why is the seasonality impact on
souvenirs weak and why is it strong for accommoda-
tions, and why is the seasonality for the consumption
items for business and vfr travel similar? Consider-
ing that the seasonality results obtained for the three
travel purposes were not consistent with previous re-
2Definition for stable in this section is if the largest (smallest)
consumption month is consistent in five of the eight years
observed between 2010 to 2017. For years or less will be con-
sidered unstable.
search studying other countries, which examined the
number of visitors as the measurement unit of season-
ality, it would be interesting to examine whether the
results differ if the number of visitors was applied as
the unit. This would provide insight into whether the
differences are influenced by the measurement unit or
if they stem from the markets examined.
Conclusions
As Japan aims to become a large tourist nation, it fo-
cuses on inbound policies and reinforcing domestic
tourism by Japan residents. The travel industry is re-
quired to reduce the seasonality in the travel business
in order to develop amore stable business with reliable
income and to provide more stable employment. This
paper aims to provide insight into the seasonality for
each travel purpose. It analyses Japan holiday travel,
vfr travel and business travel for each travel-related
expenditure by consumption item using data for the
fiscal years from 2010 to 2017 on domestic travel by
Japan residents to observe the trends in seasonality.
These results that identify the consumption items
that have predictable and stable seasonality as well as
those that are difficult to predict and show an increas-
ing seasonality trend provide several policy implica-
tions. The observation of the different travel purposes
could assist in the development of strategies in differ-
ential pricing, diversified attraction, market diversifi-
cation and facilitation by the state to address seasonal-
ity. Since the analysis is based on the expenditure of the
various travel-related consumption items rather than
the number of visitors, it provides insight to the ar-
eas that differential pricing may be effective and may
assist in decisions concerning areas of the business
to close during the off-season to reduce operational
costs. Based on this analysis, the areas identified with
seasonality challenges include package and attraction
of vfr travel. This suggests opportunities for differ-
ential pricing of package holiday/tours expenses and
entrance/attraction expenses aimed at families dur-
ing the vfr travel off-peak seasons. Concerning the
diversification of attraction, the timing or attracting
the hosting of sport events and festivals could be con-
sidered based on the seasonality of the attraction ex-
penditure. For example, during the off-peak of vfr
Academica Turistica, Year 12, No. 1, June 2019 | 69
Kenichi Shimamoto Examining the Seasonality of Travel-Related Expenditure
travel, attractions and events aimed at families could
be considered. Since package and attraction for busi-
ness travel were also identified as a seasonality chal-
lenge for Japan, the timing of conferences and exhibi-
tions during the off-peak seasons for business travel
may be an effective solution. Promotion to encour-
age corporate incentives and meetings during this
time and the development of packages could be con-
sidered. The analysis based on travel purposes and
a range of travel expenditure may also facilitate the
diversification of niche products and services. For ex-
ample, in order to help address the business travel ac-
commodation seasonality, the inclusivity of breakfast
buffets, which is the 2nd reason for the choice of ac-
commodation (Development Bank of Japan & Japan
Economic Research Institute Inc., 2017), could be de-
veloped as a niche product aimed for business travel.
The results of this paper also assist in identifying ar-
eas for market diversification. The observation of the
seasonality for package holidays/tours, for instance,
suggests an opportunity for tour operators and travel
agents to develop new products and services for the
vfr travel off-peak period, such as family-targeted
packages. Considering that accommodation of busi-
ness travel was also identified as an area with season-
ality challenges, there is an opportunity for lodging
and transportation businesses to cooperate and en-
courage business trips during the off-peak season for
business travel.3 This analysis could also help target
areas for state intervention. The seasonality challenge
with vfr travel identified in this analysis may be ad-
dressed with the encouragement of companies pro-
viding more flexibility to enable paid holidays to be
taken during the children’s school breaks4 or the stag-
gering of public holidays by region. The identification
of consumption items and travel purposes with sim-
ilar seasonality trends could also assist the local gov-
ernment in the development of relevant local business
partnerships as well as in targeting necessary financial
provisions such as loans and subsidies.
Granular analysis to support the segmentation of
3 jtb has introduced such packages.
4 In 2010, the Japan Tourism Agency set up the ‘Family Time
Development Project’ to support this.
the tourism market is now easier to utilise with the
development of the internet and social media. Local
businesses and destinations can target and promote to
an international niche audience. Information technol-
ogy also supports the monitoring of performance and
assists in planning differential pricing. With such pos-
sibilities in mind, this paper aims to support the ap-
propriate development of policies that encourage the
dispersity of tourism seasonality and support the sus-
tainable development of tourism.
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