La presentazione di Aurkene Alzua Sorzabal, direttrice di CICtourGUNE, sui nuovi modelli di business turistici - WEF è internazionalizzazione e cosmopolitismo (23 marzo 2014)

1. CICtourGUNE
Coopera've
Research
Center
in
Tourism
Turismoko
Ikerketa
Zentro
Koopera'boa
Centro
de
Inves'gación
Coopera'va
en
Turismo
Donos'ako
Parke
Teknologikoa
Mikeletegi
Pasealekua,
71
·∙
3.
Solairua
E-­‐
20009
Donos'a/
San
Sebas'an
·∙
Spain
Tel.:
+34
943
010885
·∙
Fax:
+34
943
010846
tourgune.org
Web
Economy
Business
Intelligence
Aurkene
Alzua-­‐Sorzabal

2. 2
BACKGROUND
CYBER-­‐
PHYSICAL
CONVERGENCE
The
present
'me
has
been
recognized
as
an
technology
mediated
world,
with
compu'ng
and
communica'on
en''es
interac'ng
among
themselves,
as
well
as
with
users.
Real-­‐world
components
interact
with
cyberspace
thus
driving
towards
the
Cyber-­‐Physical
World
(CPW)
convergence,
adap'ng
human
behaviour
and
social
dynamics
(Con'
et
al.,
2012)
.

3. 3
BACKGROUND
CYBER-­‐
PHYSICAL
CONVERGENCE
People
are
empowered
to
express,
share,
create,
consume,
and
organize
informa'on
in
a
new
manner
The
advance
of
internet
and
the
new
technology-­‐mediated
world,
has
significantly
changed
and
even
transformed
the
structure
of
tourism
value
chain.
It
not
only
affects
the
choices
available
to
the
consumer,
but
also
the
business
models
and
marke'ng
strategies
adopted
by
the
various
channel
par'cipants,
stakeholders.

4. 4
NEW
PARADIGM
BUSINESS
INTELLIGENCE
CHALLENGES
Beyond
tradi'onal
web
analy'cs,
des'na'on´s
stakeholders
are
needed
of
innova'ons
to
support
the
intelligent
monitoring
of
the
visitors,
in
order
to
an'cipate
and
improve
their
performance.
They
must
find
out
to
whom,
what,
how
and
when
to
refer.
Challenge
to
face
is
how
can
we
provided
insights
in
terms
of
knowledge
creaDon
and
knowledge
management
in
complex
industries
such
as
the
hospitality
field.
Business
Intelligence
based
on
Internet
provides
the
opportunity
to
an'cipate
and
es'mate
consumer
habits
on
a
changing
environment
(Alzua-­‐Sorzabal,
Gerrikagoi'a,
&
Torres-­‐Manzanera,
2013).

5. Culture
of
data
and
Analysis
• Privacy
• Access
(Open
Data)
• OpenPDS
(Personal
Data
Storage)
architectures
• What
should
analyze?,
Why?
Smart
Ci)es
• New
business
models
• Beneficial
for
city
systems
(energy,
transport,
healtcare,..)
• Building
of
ICT
plalorms
based
on
FI
(Future
Internet)
Computa)onal
Social
Science
• Human
ac'vity
in
digital
footprint(Social
Indicators)
• Collabora've
process
(Social
Sc
vs
Computer
Sc)
:
Decision
-­‐
making
Features
(5V)
• Volume
• Velocity
• Variety
• Veracity
• Value
Big
Data
5
BACKGROUND
CYBER-­‐PHYSICAL
CONVERGENCE
ROW
MATERIAL
Has
Should
encourage
the
Oriented
to
Applicability

6. 6
AIM
OF
THE
PRESENTATION
(1) describe
the
capaciDes
of
the
monitors
(
technologies)
as
a
novel
approaches
(2) understand
the
role
of
ICT
in
the
evoluDon
and
transformaDon
of
tourism
informaDon
systems
and
knowledge
management

7. 7
TOURISM
INTELLIGENCE
WAHT
CAN
WE
LEARN
FROM
THE
WEB
Sta's'cal
System
Dynamic
Pricing
Monitor
Mobility
on
des'na'on
Social
Media
Monitor
Tourism
Des'na'on
Web
Monitor

8. 8
BUSINESS
INTELLIGENCE
DYNAMIC
PRICING
MONITOR
Price
compe''veness
is
an
essen'al
component
in
the
overall
compe''veness
of
any
tourism
des'na'on
or
industry.
• Countries
and
industries
have
developed
or
use
price
indicators.
Price
is
one
of
the
most
important
factor
in
decisions
about
whether,
and
where
to
market
tourism
products
and
services
Hotel
price
indexes
are
being
developed
like:
• Trivago
HPI:
most
popular
EU
ci'es
• Expedia
HPI:
hotels.com,
18.000
global
loca'ons

9. 9
BUSINESS
INTELLIGENCE
DYNAMIC
PRICING
MONITOR
Dynamic
Pricing
Monitor
gathers
the
pricing
and
availability
informa'on
provided
by
online
distribu'on
channels
(IDS)
It
comprises
a
web
crawler
which
uses
screen
scraping
techniques
in
order
to
acquire
prices
and
availability
for
twin
bedded
rooms
on
every
available
hotel
for
a
given
IDS,
geographical
and
'me
scope
ETL
Extrac'on
Transforma'on
Loading

10. 10
DYNAMIC
PRICING
MONITOR
• Every
24
hours,
data
on
accommoda'on
prices
are
collected
automa'cally
• The
system
asks
for
the
price
and
availability
of
a
overnight
for
the
1-­‐28,
30,
45,
60
and
90
days
-­‐>
Future
price
varia'on
Process

11. 11
DYNAMIC
PRICING
MONITOR
Data
volume
Hotels
Records
Daily
recs.
Hist.
Series
Spain
11.569
140M
195K
5/2011
France
13.784
135M
300K
10/2011
Ireland
742
5M
18K
11/2012
Coastal
tourism
Sample
Croacia
86
323K
2k
2/2014
Egypt
33
123K
1K
Greece
431
138K
10K
Italy
1.105
2,5M
18K
Morocco
217
812K
6k
Portugal
163
141K
4k
Tunisia
28
89k
1k
Turkey
678
2,3M
16k

12. 12
DYNAMIC
PRICING
MONITOR
What
is
the
average
rate
for
3
star
hotels
in
Bilbao
on
a
given
day
Which
European
city
showed
the
most
economical
room
rates
during
Easter.
Madrid,
Paris
or
Rome?
How
many
hotels
(specific
'me
and
space)
are
in
a
given
IDS
channel
?
Which
one
is
the
op'mal
'me
to
book
a
room
for
Christmas
in
Vienna
?
How
does
a
big
event
affect
hotel
occupancy
and
room
rate?
…
It
may
address
quesDons
such
as..

13. 13
INSIGHTS/
PRODUCTS
FORECASTING
Dynamic
Pricing
Monitor
Forecast
Price
and
occupancy
on
Biscay
for
the
next
14
days

14. 14
INSIGHTS/
PRODUCTS
IMPACT
STUDIES
Dynamic
Pricing
Monitor
Hotel
Price
varia'on
in
July.
The
impact
of
The
fes'val
of
San
Fermín
in
Navarre

15. 15
INSIGHTS/
PRODUCTS
BENCHMARK
type
of
accomodaDon
Dynamic
Pricing
Monitor
Accommoda'on
rural
regions
of
Spain
in
August
2013
0
10
20
30
40
50
60
70
80
90
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Asturias
Cáceres
Cantabria
Cuenca
Granada
Navarra
Segovia

16. 16
INSIGHTS/
PRODUCTS
BENCHMARK
any
country
Dynamic
Pricing
Monitor
Average
Hotel
prices
in
Galway
in
June
2013
Weekend
effect

17. 17
INSIGHTS/
PRODUCTS
CITY
BENCHMARK
any
Dme
framework
Dynamic
Pricing
Monitor
Barcelona,
Madrid,
Valencia
from
10th
of
June
to
10th
July
2013

18. 18
INSIGHTS/
PRODUCTS
CITY
BENCHMARK
any
Dme
framework
Dynamic
Pricing
Monitor
50
100
150
200
ago 05 ago 12 ago 19 ago 26
PreciomediodelaHDE(euro)
Localidad
Agadir
Alanya
Antalya
Corfú
Dubrovnik
Faro
Monastir
Rimini
Sharm El Sheikh
Thira
Mediterranean
coastal
des'na'ons
August
2013

19. 19
INSIGHTS/
PRODUCTS
BENCHMARK
Dynamic
Pricing
Monitor

20. 20
INSIGHTS/
PRODUCTS
Price/channel
Dynamic
Pricing
Monitor

21. 21
BUSINESS
INTELLIGENCE
WEB
MONITORING
Prior
to
their
visits:
Tourists
generate
entries
when
they
consult
digital
maps
or
DMO
Websites
During
their
visit:
Tourists
leave
traces
on
wireless
networks
Aer
their
visit:
Tourists
might
add
online
reviews
and
photos
Passive
tracks
are
ler
through
interac'on
with
an
infrastructure,
such
as
a
mobile
phone
network,
that
produces
entries
in
loca'onal
logs.
AcDve
prints
come
from
the
users
themselves
when
they
expose
loca'onal
data
in
photos,
messages,
and
sensor
measurements.

22. 22
BUSINESS
INTELLIGENCE
WEB
MONITORING
The
DWM
System
Des9na9on
Web
Monitor,
DWM:
“A
system
to
measure,
analyse
and
model
the
behaviour
of
visitors
in
different
virtual
areas
(region,
territories,
tourist
brands,
associa9ons,
capitals,
districts,
municipali9es)
in
which
a
des9na9on
is
promoted
and
with
the
objec9ve
of
providing
benchmarking
ra9os
that
facilitate
strategic
surveillance
and
intelligent
marke9ng
policies”.
The
design
of
the
DWM
sa'sfies
the
five
levels
of
the
Web
Analy'cs
maturity
model
(WAMM)
(Gassman,
2008)

23. 23
DESTINATION
VISITOR
Who
does
visit
the
Web?
How
have
they
found
us?
What
is
the
behavior
and
taste
of
the
visitor?
How
much
'me
do
they
spend
in
each
content?
Which
are
the
common
characteris'cs
of
successful
products
and
services?
…
…
MWD
BUSINESS
INTELLIGENCE
WEB
MONITORING

24. 24
The
social
Media
SOME
System
The
Social
Media
Monitor
(SOME)
extracts
and
analyzes
the
content
that
has
been
revealed
by
the
users
in
social
networks
(User
Generated
Content,
UGC).
With
this,
it
is
expected
to
get
a
par'cular
vision
of
the
image
that
users
have
about
the
business,
and
therefore,
to
achieve
an
efficient
management.
51%
say
it
is
actually
more
important
than
the
opinions
of
their
friends
and
family,
and
far
more
trustworthy
than
website
content.
BUSINESS
INTELLIGENCE
WEB
MONITORING

25. 25
BUSINESS
INTELLIGENCE
WEB
MONITORING
Get
your
brand
visibility
in
the
social
sphere
and
in
search
engines,
and
get
control
over
your
online
reputa'on.
The
study
of
digital
footprints
also
lets
us
uncover
the
digital
desire
lines:
• Understand
the
audience
(segments)
• Define
products
(culture,
sport,
landscape,
ecology,
alterna've
...),
• Increase
the
number
of
followers
(adapted
to
the
profile
of
visitors)
• Communica'on
campaigns
(most
suitable
'mes
of
the
year
to
put
the
messages)

26. 26
BUSINESS
INTELLIGENCE
South
American
Market
• Source
markets
for
interna'onal
tourism:
• Emerging
economies
show
fast
growth
over
the
recent
years
• In
2012,
the
Americas
(South
and
North
America)generated
172
million
interna'onal
tourist
arrivals
worldwide
(17%
of
the
world
total)
Source:
UNWTO,
2013

27. 27
BUSINESS
INTELLIGENCE
South
American
Market
Europe
received
26
million
arrivals
from
the
Americas
in
2005
Source:
UNWTO

28. 28
BUSINESS
INTELLIGENCE
South
American
Market
Country
of
origin
Total
arrivals
%
Annual
variaDon
rate
ArgenDna
306,759
0.5%
11.0
Brazil
369,909
0.7%
53.4
Chile
37,671
0.1%
112.8
Mexico
259,028
0.5%
39.5
Venezuela
109,360
0.2%
113.5
Others
South-­‐
America
450,720
0.8%
-­‐13.6
Total
internaDonal
arrivals
56,176,884
100%
6.6
Source:
CICtourGUNE
from
data
of
IET
(2011)
• Spain
has
benefited
by
La'n-­‐American
outbound
tourism
• According
to
Frontur
Survey
(IET),
the
total
arrivals
from
La'n
America
in
2011
were
as
follows:
Arrivals
to
Spain
from
the
Outbound
La'n
American
market

29. 29
BUSINESS
INTELLIGENCE
South
American
Market
CountryKey
Visits
Time
(Seconds)
Av.
Time/Visits
(min.)
*
AcDons
AcDons/Visits
Bounds
P.
of
bound
(%)
Brazil
91,006
14,249,907
2.6
218,349
2.39
60,302
66.26
ArgenDna
69,275
13,104,138
3.15
200,292
2.89
42,781
61.75
Colombia
25,920
2,880,805
1.85
50,982
1.96
19,354
74.66
Venezuela
25,777
3,809,882
2.46
59,659
2.31
17,357
67.33
Peru
17,553
1,815,996
1.72
31,590
1.79
13,402
76.35
Chile
15,867
1,725,339
1.81
31,055
1.95
11,643
73.37
Ecuador
9,861
870,477
1.47
17,068
1.73
7,557
76.63
Uruguay
7,180
1,221,783
2.83
19,064
2.65
4,574
63.70
Bolivia
2,802
283,951
1.68
5,034
1.79
2,152
76.80
Paraguay
1,513
132,981
1.46
2,659
1.75
1,167
77.13
Source:
CICtourGUNE
from
the
data
supplied
by
Euskadi
Turismo.
From
2013-­‐08-­‐01
to
2014-­‐01-­‐31
DESTINATION
WEB
MONITOR
(DWM)

30. 30
BUSINESS
INTELLIGENCE
South
American
Market
CountryKey
Visits
Time
(Seconds)
Av.
Time/Visits
(min.)
*
AcDons
AcDons/Visits
Bounds
P.
of
bound
(%)
Robots
ArgenDna
3,199
1,399,261
7.29
19,156
5.99
106
3.31
700
Venezuela
616
334,240
9.04
4,257
6.91
22
3.57
124
Chile
601
221,498
6.14
3,115
5.18
37
6.16
170
Uruguay
522
315,067
10.06
3,472
6.65
12
2.30
82
Brazil
456
262,655
9.60
3,324
7.29
28
6.14
78
Colombia
437
163,719
6.24
2,004
4.59
14
3.20
109
Peru
279
99,726
5.96
1,094
3.92
13
4.66
62
Ecuador
151
57,279
6.32
684
4.53
10
6.62
48
Bolivia
52
13,815
4.43
206
3.96
4
7.69
8
Paraguay
30
9,068
5.04
114
3.80
2
6.67
6
Source:
CICtourGUNE
from
the
data
supplied
by
Spain.info.
From
2013-­‐08-­‐01
to
2014-­‐01-­‐31
DESTINATION
WEB
MONITOR
(DWM)
*
Arer
the
cleaning
process
&
Piwik
digital
footprint

31. 31
BUSINESS
INTELLIGENCE
South
American
Market
Source:
CICtourGUNE
From
2013-­‐08-­‐01
to
2014-­‐01-­‐31
DESTINATION
WEB
MONITOR
(DWM)
VISITS
YEAR
MONTH
IET
–
FRONTUR
(Spain)
EUSTAT-­‐Hotel
(Basque
Country)
MWD
(Spain)
MWD
(Basque
Country)
2013
August
192,338
19,423
460,352
1,353
September
218,938
23,654
464,673
1,222
October
171,883
26,610
469,579
1,357
November
96,616
27,913
474,138
1,135
December
100,294
29,603
477,552
1,021
2014
January
177,138
16,225
450,130
1,382
TOTAL
(Six
Month)
957,207
143,428
2,796,424
7,470
Percent
Real
/
Digital
world
0.34
0.05

32. 32
VISITS
YEAR
MONTH
IET
-­‐
FRONTUR(Spain)
EUSTAT-­‐
(Basque
Country)
%
FRONTUR-­‐
EUSTAT
MWD
(Spain)
%
FRONTUR-­‐
MWD
MWD
(Basque
Country)
%
MWD-­‐
MWD
%
EUSTAT-­‐
MWD
2013
August
192,338
19,423
10
460,352
2
1,353
0.3
7.0
September
218,938
23,654
11
é
464,673
2
1,222
0.3
5.2
ê
October
171,883
26,610
15
é
469,579
3
1,357
0.3
5.1
ê
November
96,616
27,913
29
é
474,138
5
1,135
0.2
4.1
ê
December
100,294
29,603
30
é
477,552
5
1,021
0.2
3.4
ê
2014
January
177,138
16,225
9
ê
450,130
3
1,382
0.3
8.5
é
TOTAL
(Six
Month)
957,207
143,428
2,796,424
7,470
0.3
5.2
Percent
Real
/
Digital
world
0.34
0.05
BUSINESS
INTELLIGENCE
South
American
Market

33. 33
BUSINESS
INTELLIGENCE
South
American
Market
FRONTUR
/
MWD
Source:
CICtourGUNE
445,000
450,000
455,000
460,000
465,000
470,000
475,000
480,000
-­‐
50,000
100,000
150,000
200,000
250,000
FRONTUR-­‐MWD
FRONTUR-­‐MWD
IET
-­‐
FRONTUR(Spain)
MWD
(Spain)
192,338
460,352
218,938
464,673
171,883
469,579
96,616
474,138
100,294
477,552
177,138
450,130
Covarianza:
-­‐339130377
Pearson:
-­‐0,678679926
p-­‐significación:
0,138

34. 34
BUSINESS
INTELLIGENCE
South
American
Market
EUSTAT
/
MWD
Source:
CICtourGUNE
-­‐
200
400
600
800
1,000
1,200
1,400
1,600
-­‐
5,000
10,000
15,000
20,000
25,000
30,000
35,000
EUSTAT-­‐MWD
EUSTAT-­‐MWD
EUSTAT-­‐Hotel
(Basque
Country)
MWD
(Basque
Country)
19,423
1,353
23,654
1,222
26,610
1,357
27,913
1,135
29,603
1,021
16,225
1,382
Covarianza:
-­‐588943
Pearson:
-­‐0,779290576
p-­‐significación:
0,068

35. 35
BUSINESS
INTELLIGENCE
South
American
Market
MWD
Spain
/
MWD
Basque
Country
Source:
CICtourGUNE
-­‐
200
400
600
800
1,000
1,200
1,400
1,600
445,000
450,000
455,000
460,000
465,000
470,000
475,000
480,000
MWD
(Spain
)-­‐
MWD
(Euskadi)
MWD
(Spain
)-­‐
MWD
(Euskadi)
MWD
(Spain)
MWD
(Basque
Country)
460,352
1,353
464,673
1,222
469,579
1,357
474,138
1,135
477,552
1,021
450,130
1,382
Covarianza:
-­‐1167126,6
Pearson:
-­‐0,80404303
p-­‐significación:
0,054

36. 36
New
way
to
measure
[SOME]

37. 37
BUSINESS
INTELLIGENCE
APPTRACK
All
events
(georeference
points)
Europa
16/07/2013
-­‐
30/09/2013
Infographic
on
the
use
of
San
Sebas'an
App.
App
is
downloaded
and
use

38. 38
BUSINESS
INTELLIGENCE
All
events
(georeference
points)
North
of
Spain
Summary
16/07/2013
-­‐
30/09/2013
Infographic
on
the
use
of
San
Sebas'an
App.
App
is
downloaded
and
use

39. 39
BUSINESS
INTELLIGENCE
APPTRACK
The
use
on
a
day
Downtown,
DonosDa
20/08/2013
Infographic
on
the
use
of
San
Sebas'an
App.
App
is
downloaded
and
use

40. 40
BUSINESS
INTELLIGENCE
APPTRACK
Comparison
2
weeks
of
AUGUST
Infographic
on
the
use
of
San
Sebas'an
App.
App
is
downloaded
and
use

41. 41
BUSINESS
INTELLIGENCE
APPTRACK
All
users
in
August
Semana
1
de
Agosto
Semana
2
de
Agosto
Semana
3
de
Agosto
Semana
4
de
Agosto
Semana
5
de
Agosto
49
105
118
72
48
0
5
10
15
20
25
Usuarios
can'dad

42. 42
BUSINESS
INTELLIGENCE
APPTRACK
DistribuDon
by
city
zone
and
hour
0
500
1000
1500
2000
2500
3000
3500
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Total
Zubieta
Loiola
Martutene
An'guo
Centro
Aiete
Altza
Amara
Añorga
Ategorrieta
Ibaeta
Miracruz
Landarbaso
Gros
Igeldo
Egia
Intxaurrondo
Miramon

43. 43
BUSINESS
INTELLIGENCE
APPTRACK
UNINSTALED
PLACES
0
50
100
150
200
250
300
350
400
450
Fuera
De
SS
Centro
An'guo
Gros
Egia
Amara
Ibaeta
Aiete
Loiola
Igeldo
Ategorrieta
Altza
Miracruz
Miramon
Intxaurrondo
Martutene
Áreas
de
Desinstalación
de
la
aplicación
can'dad

44. 44
LOOKING
TOWARD
THE
FUTURE
BUSINESS
INTELLIGENCE
• New
methods
for
displaying/
monitoring
• Correla'on
analysis
between
specific
indicators
providing
a
global
vision
• Latest
techniques
applied
to
data
concerning
the
following
knowledge
fields:
spa'al
eConometric,
Network
analysis,
UGC,
DataMining
and
(Usage,
Content
y
Structure)
It
makes
easier
the
construc'on
of
an
holisDc
vision
of
the
different
Des'na'ons.
It
empowers
the
accomplishment
of
policies
according
to
the
reality
of
Tourism
Des'na'ons.
Targets
Tools

45. CICtourGUNE
Coopera've
Research
Center
in
Tourism
Turismoko
Ikerketa
Zentro
Koopera'boa
Centro
de
Inves'gación
Coopera'va
en
Turismo
Donos'ako
Parke
Teknologikoa
Mikeletegi
Pasealekua,
71
·∙
3.
Solairua
E-­‐
20009
Donos'a/San
Sebas'an
·∙
Spain
Tel.:
+34
943
010885
·∙
Fax:
+34
943
010846
tourgune.org
Thanks
Grazie
45
Aurkene
Alzua-­‐Sorzabal