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Older Tourists: An Exploratory Study on Online Behaviour
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Older Tourists: An Exploratory Study on Online Behaviour

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Older tourists: an exploratory study on online behaviour

Older tourists: an exploratory study on online behaviour

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  • The greatest proportion of ageing people is located in Europe (UN, 2009)
  • (Significant predictors of online travel purchase intent: e-WOM and previous online travel purchase) The findings extend previous literature to the older-tourist segment (Chatterjee, 2001; Godes & Mayzlin, 2004)

Transcript

  • 1. Older tourists: an exploratory study on online behaviour Vania Vigolo and Ilenia Confente Department of Business Administration University of Verona, Italy ENTER 2014 Research Track Slide Number 1
  • 2. Agenda ENTER 2014 Research Track Slide Number 2
  • 3. Introduction An ageing world Population 60+, % of total ENTER 2014 Research Track Slide Number 3
  • 4. Introduction The European context What opportunities for the tourism industry? ENTER 2014 Research Track Slide Number 4
  • 5. Introduction healthier healthier Older tourists more more active active wealthier wealthier ENTER 2014 Research Track Slide Number 5
  • 6. Introduction Older tourists and online behaviour The Internet has reshaped the way consumers can search for and purchase tourism products. Does it apply also to older tourists? OUR OBJECTIVE: To investigate the online behaviour of older tourists in an increasingly ageing context ENTER 2014 Research Track Slide Number 6
  • 7. Introduction The study context: Italy Age • In 2012, 40% of the population aged 50+ • By 2030, 25% of the population will be 65+ (European Commission, 2012) Internet usage • Only 19.5% of the 55+ population uses the internet (www.audiweb.it) ENTER 2014 Research Track Slide Number 7
  • 8. Literature overview Extant literature on older tourists • travel motivations (Jang, Bai, Hu, & Wu, 2009; Le Serre & Chevalier, 2012; Le Serre, Legohérel, & Weber, 2013) • psychological factors (Jang et al., 2009) • experience characteristics (Hunter-Jones & Blackburn, 2007; Batra, 2009) • service needs and perceptions (Wang, Ma, Hsu, Jao, & Lin, 2013; Chen, Liu, and Chang, 2013). ENTER 2014 Research Track Slide Number 8
  • 9. Literature overview Older tourist and online behaviour • Most published studies on online behaviour deal with the “Y generation” (Nusair et al., 2012) • Little research exists on the role of Internet in the senior travel market (Le Serre & Chevalier, 2012; Kohlbacher, 2012) GAP ENTER 2014 Research Track Slide Number 9
  • 10. Research questions • (1) What are the determinants of older consumers’ intention to buy tourism products online? • (2) Are there any differences between seniors and prospective-seniors in the propensity to buy tourism products online? ENTER 2014 Research Track Slide Number 10
  • 11. Model offline WOM offline WOM e-WOM e-WOM online info search online info search Online travel purchase intention prior online prior online purchase purchase prior online travel prior online travel purchase purchase prior online travel prior online travel purchase (other) purchase (other) education education ENTER 2014 Research Track Slide Number 11
  • 12. Method • Questionnaire design: - Predictors (dummy variables) - Dependent variable (1-5 Likert type) - self-administered, pre-tested among 20 older tourists • Sampling process - snowballing (Lee, Huang, & Yeh, 2010) - age-quota: 50+ years, prospective seniors (50-64) and seniors (65+) (Chen et al., 2013) • SPSS for analysis of results • N= 205, aged 50-81 years (average age 59.5) ENTER 2014 Research Track Slide Number 12
  • 13. Results Sample profile: demographics Age group Gender Education Prospective seniors Male (48.3) (78.9) Primary (30.7) Seniors (21.1) High school/university (68.8) Female (51.2) ENTER 2014 Research Track Slide Number 13
  • 14. Results Sample profile: travel behaviour and online experience Percentage Travelled in the last two years 88.8 Prior travel choice based mainly on e-WOM 22.0 Online purchase experience 45.4 Online travel purchase experience 38.5 Online travel purchase experience (other people) Online information search before travel purchase Wrote an online travel review ENTER 2014 Research Track 29.3 74.1 8.8 Slide Number 14
  • 15. Results (1) Predictors of online travel purchase intention offline WOM offline WOM e-WOM** e-WOM** online info search online info search Online travel purchase intention prior online purchase prior online purchase prior online travel prior online travel purchase** purchase** 51.7 % of variance explained (adj. R2) ** p< 0.01; *p< 0.05 prior online travel prior online travel purchase (other)** purchase (other)** education* education* ENTER 2014 Research Track Slide Number 15
  • 16. Results (1) Predictors of online travel purchase intention β Std Error Constant 1.074 0.232 e-WOM 0.665 0.212 0.166 3.136** 1.166 Prior online travel purchase Prior online travel purchase (other) 1.549 0.246 0.454 6.297** 2.168 0.475 0.184 0.131 2.585** 1.069 Education 0.455 0.194 0.126 2.341* 1.217 Offline WOM 0.217 0.185 0.058 1.168 1.044 Previous online purchase 0.413 0.263 0.124 1.570 2.589 Online information search 0.160 0.213 0.042 0.753 1.310 Determinants Std. β t F VIF 4.621** 31.828 R2 = 0.533; Adjusted R2 = 0.517 *p < 0.05; **p < 0.01 ENTER 2014 Research Track Slide Number 16
  • 17. Results (2) Differences between prospective seniors and seniors Prospective seniors (50-64)… …express higher intention:  to purchase online (t= 3.415, p< 0.01)  to purchase tourism products online (t= 2.884, p< 0.01) …are more likely:  to make travel decisions based on e-WOM (χ²= 10.929, p< 0.01), to search travel information online (χ²= 36.003, p< 0.01)  to write an online review about their travel experience (χ²= 3.975, p < 0.05) ENTER 2014 Research Track Slide Number 17
  • 18. Discussion • Context-specific online experience rather than generic (non tourism-related) online experience can enhance the likelihood to buy tourist services online. • Online information search was not a significant predictor  online commercial/promotional information is perceived as less reliable than UGC (Bruwer & Thach, 2013) • Highly-educated older tourists are more likely to make online travel purchases (Porter & Donthu, 2006; Lee et al., 2007). ENTER 2014 Research Track Slide Number 18
  • 19. Managerial implications In the next years, older tourists will be more sensitive to eWOM and will increase their propensity towards online travel purchase. Implications for tourism managers:  To rethink communication and distribution strategies to reach this target  To concentrate on peer-to-peer communication (UGC) rather than on commercial communication  To stimulate passive readers to become active senders, thus enhancing the role of e-WOM as an influential source for other older tourists ENTER 2014 Research Track Slide Number 19
  • 20. Limitations and further research • Sample selection • Sample size • This study focused on past behaviour and online experience. Other variables not included in this study (e.g. perceived risk, perceived price convenience etc.) could play a significant role in determining purchase intention. • Personal features may influence older tourists’ purchase behaviour. ENTER 2014 Research Track Slide Number 20
  • 21. THANK YOU! Any questions? vania.vigolo@univr.it ENTER 2014 Research Track Slide Number 21