This presentation presents the results of a study Comparing Internet use of Travel Motivation and Activity Based Segments.

1. 2nd World Research Summit for Tourism and Hospitality, December 15-17, Orlando, Florida,
USA
Comparing Internet use of Travel
Motivation and Activity Based
Segments
Juho Pesonen
juho.pesonen@uef.fi
University of Eastern Finland, Centre for Tourism Studies

2. Presentation structure
1.
2.
3.
4.
5.
Introduction to the topic
Background of the study
Data and methods
The results
Discussion and conclusions
Juho Pesonen
20.12.2013
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3. Introduction
Juho Pesonen
20.12.2013
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4. About online marketing
•ICTs have revolutionized the tourism industry
(Buhalis & Law, 2008)
– Travellers are increasingly using technology before,
during and after their trips.
•Use of technologies define the competitiveness
of tourism organizations and destinations
(Buhalis & Law, 2008).
•Companies can target their customer very
efficiently if they just know who their
customers are.
Juho Pesonen
20.12.2013
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5. Market segmentation
•A way to find new markets and serve existing
customers better.
– Identifying homogenous groups in the marketplace.
– A priori and a posteriori approaches.
•Marketing actions must be adaptable for different
segments.
– Connection to online marketing.
– Internet use behaviour of segments is important
part of targeting segments members in online
channels.
– But what segmentation base a company or
researcher should use?
Juho Pesonen
20.12.2013
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6. Comparing market
segments
•Obtaining segmentation solution is relatively
routine but the question of solution adequacy
is far from simple (Moscardo et al., 2001).
•Different segmentation bases used in tourism:
– Socio-demographics
– Benefits
– Activities
– Travel motivations
– Expenditure
– Etc…
Juho Pesonen
20.12.2013
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7. Rural tourism
- Importance of rural tourism in Finland
- Local people are important during peak
seasons but especially during off-seasons.
- SME enterprises
- Rural tourism based on peace, quiet, lanscape, lakes,
and activities.
- Cottages and farm accommodation.
- Limited resources and skills for ICT use.
Juho Pesonen
20.12.2013
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8. Research questions
•This study aims to compares Internet use behaviour of
two segmentation solutions based on travel activities
and travel motivations.
– What kind of travel activity segments can be
identified among Finnish rural tourists?
– What kind of travel motivation segments can be
identified among Finnish rural tourists?
– How travel motivation segments differ from travel
activity segments regarding their internet use?
Juho Pesonen
20.12.2013
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9. Data
• Banner advertisement on three Finnish rural tourism websites
during summer 2011
• 11 page long questionnaire.
– 2131 responses to the questionnaire -> 1754 usable responses for the
analysis of this study.
– Travel motivations (Bieger & Laesser, 2002)
– Information search behaviour (Jani et al., 2011)
– Activities (Moscardo et al., 2001)
– Socio-demographics
• Three stages of data analysis
1.
Hierarchical cluster analysis with Ward’s method
2.
Validation by comparing Internet use behaviour
3.
Comparing segmentation bases using eta (ANOVA) and tau
(cross-tabulations)
Juho Pesonen
20.12.2013
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10. Sample profile
• 71.4 % women.
• Mean and median age 39 years.
• 25 % less than 28 years old.
• Over 65 year old respondents almost non-existent.
Juho Pesonen
20.12.2013
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11. The results: travel motivation segments
Item
Family
and Nature tourists
nature tourists
(N=360, 20.5%)
(N=374, 21.3%)
Comfort
Partner
23 (3.6 %)
36 (9.4%)
130 (36.1%)
193 (30.3%)
173 (45.2%)
10 (2.8%)
64 (17.1%)
Relaxation
tourists
(N=383, 21.8 %)
56 (15.6%)
Nightlife
Couple tourists
(N=637, 36.3%)
637 (100 %)
12 (3.1%)
Family
374 (100 %)
32 (8.9%)
90 (14.1%)
180 (47.0 %)
Nature
328 (87.7%)
314 (87.2%)
366 (57.5%)
56 (14.6%)
Culture
118 (31.6%)
157 (43.6%)
200 (31.4%)
179 (46.7%)
Liberty
42 (11.2 %)
77 (21.4%)
112 (17.6%)
140 (36.6%)
Body
11 (2.9%)
18 (5.0%)
7 (1.1%)
18 (4.7%)
Sports
1 (0.3%)
66 (18.3%)
32 (5.0%)
28 (7.3%)
Sun
73 (19.5%)
68 (18.9 %)
136 (21.4%)
209 (54.6%)
Juho Pesonen
20.12.2013
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12. Travel activity segments
Water
activities
(N=396,
22.6%)
Passives
(N=270,
15.4%)
Nature activities Winter
(N=507, 28.9%) activities
(N=133, 7.6 %)
Actives
(N=448, 25.5
%)
Downhill skiing
28 (7.1%)
5 (1.9%)
32 (6.3%)
128 (96.2 %)
77 (17.2 %)
Cross-country skiing
17 (4.3 %)
10 (3.7%)
145 (28.6%)
57 (42.9 %)
189 (42.2 %)
Tour skating
8 (2.0%)
9 (3.3%)
22 (4.3%)
19 (14.3%)
88 (19.6%)
Snowmobiling
11 (2.8%)
9 (3.3%)
78 (15.4%)
52 (39.1%)
88 (19.6%)
Swimming
373 (94.2%)
25 (9.3%)
431 (85.0%)
101 (75.9%)
404 (90.2%)
Canoeing
50 (12.6%)
7 (2.6%)
94 (18.5%)
53 (39.8%)
276 (61.6%)
Rowing
300 (75.8%)
76 (28.1%)
148 (29.2%)
40 (30.1%)
390 (87.1%)
Fishing
241 (60.9%)
99 (36.7%)
122 (24.1%)
37 (27.8%)
346 (77.2%)
Berry picking or mushroom gathering
76 (19.2%)
89 (33.0%)
148 (29.2%)
8 (6.0%)
300 (67.0%)
Walking / hiking
177 (44.7%)
167 (61.9%)
458 (90.3%)
81 (60.9%)
418 (93.3%)
Golf
1 (4.5%)
8 (3.0%)
6 (1.2%)
10 (7.5%)
37 (8.3%)
Watching animals
110 (27.8%)
108 (40.0%)
213 (42.0%)
27 (20.3%)
224 (50.0%)
Cycling
49 (12.4%)
54 (20.0%)
225 (44.4%)
43 (32.3%)
311 (69.4%)
Item
Juho Pesonen
20.12.2013
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13. Activity segment online behaviour
Information sources
Water activities Passives (N=270, Nature activities
(N=396, 22.6%) 15.4%)
(N=507, 28.9%)
Winter
activities
(N=133,
%)
Actives
(N=448,
7.6 25.5 %)
χ2
Goodman
Kruskal’s
Tau
39.22**
0.022**
13.86**
0.008**
16.71**
0.010**
14.13**
0.008**
22.36**
0.013**
14.37**
0.008**
20.54**
0.012**
10.32**
0.006**
15.90**
0.009**
29.62**
0.017**
Information sources used when planning and booking
a holiday
128 (96.2%)
424
(94.6%)
129
(28.8%)
248
(55.6%)
111
(24.8%)
214
(47.8%)
72 (16.1%)
Internet
372 (93.9%)
226 (83.7%)
476 (93.9%)
Magazines
82 (20.7%)
49 (18.1%)
110 (21.7%)
Brochures
179 (45.2%)
116 (43.0%)
263 (51.9%)
Guidebooks
67 (16.9%)
42 (15.6%)
90 (17.8%)
Friends and relatives
147 (37.1%)
84 (31.1%)
214 (42.2%)
Travel agency
37 (9.3%)
22 (8.1%)
70 (13.8%)
Affiliate website
261 (65.9%)
156 (57.8%)
337 (66.5%)
Travel agency website
151 (38.1%)
82 (30.4%)
187 (36.9%)
Destination website
131 (33.1%)
88 (32.6%)
181 (35.7%)
Search engine
345 (87.1%)
203 (75.2%)
419 (82.6%)
DMO website
50 (12.6%)
30 (11.1%)
74 (14.6%)
27 (20.3%)
326
(72.8%)
189
(42.2%)
199
(44.4%)
398
(88.8%)
96 (21.4%)
20.72**
0.012**
Newspaper/Magazine web site
58 (14.6%)
24 (8.9%)
78 (15.4%)
18 (13.5%)
81 (18.1%) 11.64**
0.007**
Discussion boards / blogs
60 (15.2%)
37 (13.7%)
92 (18.1%)
29 (21.8%)
98 (21.9%) 11.41**
0.007**
74 (14.6%)
21 (15.8%)
76 (17.0%) 10.55**
0.006**
32 (24.1%)
59 (44.4%)
30 (22.6%)
57 (42.9%)
17 (12.8%)
Types of web sites used when planning and booking a
holiday
Social media
49 (12.4%)
24 (8.9%)
78 (58.6%)
48 (36.1%)
51 (38.3%)
118 (88.7%)
Juho Pesonen
20.12.2013
13

14. Activity segment online behaviour
Water
activities
(N=396,
22.6%)
Information sources
Purchased online travel
from the past 12 months
Passives
(N=270,
15.4%)
Nature
activities
(N=507,
28.9%)
Winter
Actives
activities (N=448,
2
(N=133, 25.5 %) χ
7.6 %)
Goodman
Kruskal’s
Tau
products
Accommodation
205 (51.8%) 109 (40.4%) 269 (53.1%)
Flight tickets
145 (36.6%) 73 (27.0%)
182 (35.9%)
Ticket to event / destination
59 (14.9%)
72 (14.2%)
None of the above
110 (27.8%) 116 (43.0%) 155 (30.6%)
Writes online reviews
117 (29.8%) 60 (22.3%)
30 (11.1%)
114 (22.5%)
76
(57.1%)
56
(42.1%)
30
(22.6%)
30
(22.6%)
257
(57.4%)
184
(41.1%)
90
(20.1%)
113
(25.2%)
35
(26.5%)
140
14.06** 0.008**
(31.4%)
Juho Pesonen
21.42** 0.012**
16.36** 0.009**
16.19** 0.009**
31.05** 0.018**
20.12.2013
14

15. Travel motivation segment online behaviour
Family
and Nature tourists Couple tourists
nature tourists
(N=360, 20.5%) (N=637, 36.3%)
(N=374, 21.3%)
Relaxation
tourists
347 (92.8%)
328 (91.1%)
603 (94.7%)
348 (90.9%) 6.89*
0.004*
Affiliate website
264 (70.6%)
226 (62.8%)
426 (66.9%)
242 (63.2%) 6.75*
0.004*
Newspaper/Magazine web site
42 (11.2%)
57 (15.8%)
91 (14.3%)
69 (18.0%)
7.37*
0.004*
Discussion boards / blogs
47 (12.6%)
75 (20.8%)
114 (17.9%)
80 (20.9%)
11.60**
0.007**
Social media
45 (12.0%)
44 (12.2%)
87 (13.7%)
68 (17.8%)
6.72*
0.004*
Accommodation
189 (50.5%)
181 (50.3%)
358 (56.2%)
188 (49.1%) 6.52*
0.004*
Flight tickets
111 (29.7%)
134 (37.2%)
255 (40.0%)
140 (36.6%) 11.02**
0.006**
Ticket to event / destination
54 (14.4%)
55 (15.3%)
90 (14.1%)
82 (21.4%)
0.006**
Writes online reviews
85 (22.7%)
109 (30.3%)
157 (24.8%)
115 (30.3%) 8.95**
Information sources
Goodman
Kruskal’s
Tau
χ2
(N=383, 21.8
%)
Information sources used when planning and
booking a holiday
Internet
Types of web sites used when planning and
booking a holiday
Purchased online travel products from the past 12
months
Juho Pesonen
10.81**
0.005**
20.12.2013
15

16. Comparing segment solutions
Information sources
Activities,
clusters
three Activities,
clusters
four Activities,
clusters
Age, F-test / eta
1.91 / 0.048
13.40 / 0.155
16.69 / 0.198
Gender, chi test / tau
6.82 / 0.004
30.46 / 0.018
Mean
11.39 / 0.007
Median
five Motivations, three
clusters
Motivations, four
clusters
Motivations
clusters
five
1.99 /0.049
1.90 / 0.059
1.81 / 0.067
31.25 / 0.018
6.98 / 0.004
10.29 / 0.006
10.69 / 0.006
15.30 / 0.009
17.21 / 0.010
189.31 / 0.108
208.95 / 0.119
209.87 / 0.120
10.71 / 0.006
15.05 / 0.009
16.32 / 0.010
141.00 / 0.081
159.91 / 0.091
160.72 / 0.092
Has been on a rural
11.17 / 0.006
holiday, chi test / tau
15.28 / 0.009
17.95 / 0.010
2.78 / 0.002
2.93 / 0.002
12.20 / 0.007
Is planning to go to a
rural holiday, chi test 17.08 / 0.006
/ tau
19.11 / 0.006
21.96 / 0.007
33.22 / 0.008
33.91 / 0.008
50.71 / 0.014
Travel party, chi test
/ tau
Information sources,
chi test / tau
Mean
7.06 / 0.004
12.70 / 0.007
13.52 / 0.008
2.44 / 0.001
3.24 / 0.002
4.57 / 0.003
Median
7.74 / 0.005
13.05 / 0.008
14.00 / 0.008
2.34 / 0.002
3.41 / 0.002
3.85 / 0.002
Mean
9.48 / 0.005
13.81 / 0.008
14.97 / 0.009
4.49 / 0.003
5.74 / 0.003
9.98 / 0.006
Median
7.03 / 0.004
11.35 / 0.006
11.64 / 0.007
3.46 / 0.002
5.63 / 0.003
10.93 / 0.006
Mean
5.36 / 0.003
12.13 / 0.007
14.01 / 0.008
4.41 / 0.003
5.98 / 0.003
9.29 / 0.005
Median
6.16 / 0.004
10.72 / 0.006
16.19 / 0.009
2.78 / 0.002
4.29 / 0.002
9.11 / 0.005
13.21 / 0.008
14.06 / 0.008
8.95 / 0.005
8.95 / 0.005
11.42 / 0.008
Websites used in
search, chi test / tau
Online purchases, chi
test / tau
Writing
online
13.11 / 0.008
reviews, chi test / tau
Juho Pesonen
20.12.2013
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17. So what?
• Contributes to examination of segment heterogeneity
• And to comparing market segmentation bases
• Travel motivations are more connected to who we are,
activities are about what we do.
– More activity segments more heterogeneous
• Important information for marketing managers of rural
tourism businesses.
• What is the meaning of traditional market segmentation
in online marketing?
– Segment accessibility
Juho Pesonen
20.12.2013
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18. Limitations and future research
• Only Finnish rural tourists
– Different segments in different countries?
– Different segments among foreign visitors?
• Online sampling method
– Skewed data
– Older people are not included
– Represents online using Finnish rural tourists at best
• Clustering methodology
• Strength of association is not measured, only that it exists
Juho Pesonen
20.12.2013
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19. Questions, comments?
Thank you!
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