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2nd World Research Summit for Tourism and Hospitality, December 15-17, Orlando, Florida,
USA

Comparing Internet use of Tr...
Presentation structure
1.
2.
3.
4.
5.

Introduction to the topic
Background of the study
Data and methods
The results
Disc...
Introduction

Juho Pesonen

20.12.2013

3
About online marketing
•ICTs have revolutionized the tourism industry
(Buhalis & Law, 2008)
– Travellers are increasingly ...
Market segmentation
•A way to find new markets and serve existing
customers better.

– Identifying homogenous groups in th...
Comparing market
segments
•Obtaining segmentation solution is relatively
routine but the question of solution adequacy
is ...
Rural tourism
- Importance of rural tourism in Finland
- Local people are important during peak
seasons but especially dur...
Research questions
•This study aims to compares Internet use behaviour of
two segmentation solutions based on travel activ...
Data
• Banner advertisement on three Finnish rural tourism websites
during summer 2011
• 11 page long questionnaire.
– 213...
Sample profile
• 71.4 % women.
• Mean and median age 39 years.

• 25 % less than 28 years old.
• Over 65 year old responde...
The results: travel motivation segments
Item

Family
and Nature tourists
nature tourists
(N=360, 20.5%)
(N=374, 21.3%)

Co...
Travel activity segments
Water
activities
(N=396,
22.6%)

Passives
(N=270,
15.4%)

Nature activities Winter
(N=507, 28.9%)...
Activity segment online behaviour
Information sources

Water activities Passives (N=270, Nature activities
(N=396, 22.6%) ...
Activity segment online behaviour
Water
activities
(N=396,
22.6%)

Information sources

Purchased online travel
from the p...
Travel motivation segment online behaviour
Family
and Nature tourists Couple tourists
nature tourists
(N=360, 20.5%) (N=63...
Comparing segment solutions
Information sources

Activities,
clusters

three Activities,
clusters

four Activities,
cluste...
So what?
• Contributes to examination of segment heterogeneity

• And to comparing market segmentation bases
• Travel moti...
Limitations and future research
• Only Finnish rural tourists
– Different segments in different countries?
– Different seg...
Questions, comments?
Thank you!

www.uef.fi
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Comparing Internet use of Travel Motivation and Activity Based Segments

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

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Comparing Internet use of Travel Motivation and Activity Based Segments

  1. 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. 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 2
  3. 3. Introduction Juho Pesonen 20.12.2013 3
  4. 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 4
  5. 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 5
  6. 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 6
  7. 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 7
  8. 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 8
  9. 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 9
  10. 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 10
  11. 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 11
  12. 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 12
  13. 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. 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. 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. 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 16
  17. 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 17
  18. 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 18
  19. 19. Questions, comments? Thank you! www.uef.fi

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