Comparing Internet use of Travel Motivation and Activity Based Segments

Comparing Internet use of Travel Motivation and Activity Based SegmentsJuho Pesonen

[email protected]

University of Eastern Finland, Centre for Tourism Studies

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

Presentation structure

10.04.2023Juho Pesonen 2

1. Introduction to the topic2. Background of the study3. Data and methods4. The results5. Discussion and conclusions


Introduction

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.


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?


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…


- 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.


Rural tourism

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?



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)


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.


The results: travel motivation segmentsItem Family and

nature tourists(N=374, 21.3%)

Nature tourists (N=360, 20.5%)

Couple tourists(N=637, 36.3%)

Relaxation tourists(N=383, 21.8 %)

Nightlife 56 (15.6%) 23 (3.6 %) 36 (9.4%)

Comfort 64 (17.1%) 130 (36.1%) 193 (30.3%) 173 (45.2%)

Partner 10 (2.8%) 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%)


Travel activity segmentsItem

Water activities (N=396, 22.6%)

Passives (N=270, 15.4%)

Nature activities(N=507, 28.9%)

Winter 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%)


Activity segment online behaviourInformation sources


Passives (N=270, 15.4%)

Nature activities

(N=507, 28.9%)


Actives (N=448, 25.5 %)

χ 2Goodman Kruskal’s Tau

Information sources used when planning and booking a holiday

Internet 372 (93.9%) 226 (83.7%) 476 (93.9%)128 (96.2%) 424

(94.6%)39.22** 0.022**

Magazines 82 (20.7%) 49 (18.1%) 110 (21.7%)32 (24.1%) 129

(28.8%)13.86** 0.008**

Brochures 179 (45.2%) 116 (43.0%) 263 (51.9%)59 (44.4%) 248

(55.6%)16.71** 0.010**

Guidebooks 67 (16.9%) 42 (15.6%) 90 (17.8%) 30 (22.6%) 111 (24.8%) 14.13** 0.008**

Friends and relatives 147 (37.1%) 84 (31.1%) 214 (42.2%)57 (42.9%) 214

(47.8%)22.36** 0.013**

Travel agency 37 (9.3%) 22 (8.1%) 70 (13.8%) 17 (12.8%) 72 (16.1%) 14.37** 0.008**

Types of web sites used when planning and booking a holiday

Affiliate website 261 (65.9%) 156 (57.8%) 337 (66.5%)78 (58.6%) 326

(72.8%)20.54** 0.012**

Travel agency website 151 (38.1%) 82 (30.4%) 187 (36.9%)48 (36.1%) 189

(42.2%)10.32** 0.006**

Destination website 131 (33.1%) 88 (32.6%) 181 (35.7%)51 (38.3%) 199

(44.4%)15.90** 0.009**

Search engine 345 (87.1%) 203 (75.2%) 419 (82.6%)118 (88.7%) 398

(88.8%)29.62** 0.017**

DMO website 50 (12.6%) 30 (11.1%) 74 (14.6%) 27 (20.3%) 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**

Social media 49 (12.4%) 24 (8.9%) 74 (14.6%) 21 (15.8%) 76 (17.0%) 10.55** 0.006**


Activity segment online behaviour

Information sources


Passives (N=270, 15.4%)

Nature activities

(N=507, 28.9%)


Actives (N=448, 25.5 %) χ 2

Goodman Kruskal’s Tau

Purchased online travel products from the past 12 months

Accommodation 205 (51.8%) 109 (40.4%) 269 (53.1%)76 (57.1%)

257 (57.4%)

21.42** 0.012**

Flight tickets 145 (36.6%) 73 (27.0%) 182 (35.9%)56 (42.1%)

184 (41.1%)

16.36** 0.009**

Ticket to event / destination 59 (14.9%) 30 (11.1%) 72 (14.2%)30 (22.6%)

90 (20.1%)

16.19** 0.009**

None of the above 110 (27.8%) 116 (43.0%) 155 (30.6%)30 (22.6%)

113 (25.2%)

31.05** 0.018**

Writes online reviews 117 (29.8%) 60 (22.3%) 114 (22.5%)35 (26.5%)

140 (31.4%)

14.06** 0.008**


Travel motivation segment online behaviour

Information sources

Family and nature tourists

(N=374, 21.3%)

Nature tourists

(N=360, 20.5%)

Couple tourists

(N=637, 36.3%)

Relaxation tourists

(N=383, 21.8 %)

χ 2

Goodman Kruskal’s Tau

Information sources used when planning and booking a holiday

Internet 347 (92.8%) 328 (91.1%) 603 (94.7%) 348 (90.9%) 6.89* 0.004*

Types of web sites used when planning and booking a holiday

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*

Purchased online travel products from the past 12 months

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%) 10.81** 0.006**

Writes online reviews 85 (22.7%) 109 (30.3%) 157 (24.8%) 115 (30.3%) 8.95** 0.005**


Comparing segment solutionsInformation sources

Activities, three clusters

Activities, four clusters

Activities, five clusters

Motivations, three clusters

Motivations, four clusters

Motivations five clusters

Age, F-test / eta 1.91 / 0.048 13.40 / 0.155 16.69 / 0.198 1.99 /0.049 1.90 / 0.059 1.81 / 0.067

Gender, chi test / tau 6.82 / 0.004 30.46 / 0.018 31.25 / 0.018 6.98 / 0.004 10.29 / 0.006 10.69 / 0.006

Travel party, chi test / tau

Mean 11.39 / 0.007 15.30 / 0.009 17.21 / 0.010 189.31 / 0.108 208.95 / 0.119 209.87 / 0.120

Median 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 holiday, chi test / tau

11.17 / 0.006 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 / tau

17.08 / 0.006 19.11 / 0.006 21.96 / 0.007 33.22 / 0.008 33.91 / 0.008 50.71 / 0.014

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

Websites used in search, chi test / tau

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

Online purchases, chi test / tau

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

Writing online reviews, chi test / tau

13.11 / 0.008 13.21 / 0.008 14.06 / 0.008 8.95 / 0.005 8.95 / 0.005 11.42 / 0.008


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


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

Questions, comments?Thank you!

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Date post:	14-Dec-2014
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