|dc.description.abstract||Despite indications from past studies that young travellers are important contributors to the tourism industry, very little is known about this segment. In response to the call for better understanding of young travellers, this study presents a comprehensive evaluation of the factors that influence travellers aged 18-34 when they make decisions about commercial accommodation. While many studies have investigated what commercial attributes influence selection by various segments, including young travellers, there is a lack of studies conceptually incorporating the why factor—that is, personal purchase motives and constraints. Moreover, comparative studies between destinations are lacking for all segments (Cave, et al., 2008). Without sufficient proof, it is not wise to assume that results from one destination can be applied to another (Callan, 1996). It was also established over three decades ago that young travellers are not homogeneous (Vogt, 1976). Therefore, with these issues in mind, this study also intends to analyse how the heterogeneity of young travellers affects their accommodation selection, and compare findings between the geographically and culturally distant locations of New Zealand and Malaysia.
The data for this study were gathered via an interviewer-completion survey that was mainly conducted in the international departure lounges of three airports: Christchurch International Airport in New Zealand, and Kuala Lumpur International Airport and the Low Cost Carrier Terminal in Selangor, Malaysia. In addition, for wider coverage, respondents were approached at a main bus terminal, also in Selangor. In developing the survey, a small open-ended section for accommodation attributes was incorporated along with Likert scale questions, where the findings from the former supported the latter and gave more confidence in the findings. This between-method triangulation approach revealed the possibility that green/environmentally friendly accommodation may be overly emphasised and need more reviews and validation if implemented by accommodation providers. Also revealed was the viability of including a presently overlooked attribute, ‘variety of facilities/services’, in future studies and its implementation by accommodation providers.
A number of statistical tests were employed to analyse the data, from a basic descriptive analysis to pair-wise and independent t-tests and ANOVA using SPSS software, as well as linear structural equation modelling using AMOS software. As part of the framing process, the descriptive analysis provided the foundation for a comprehensive analysis by ranking the aggregated average mean values of dependent variables such as attributes location and cleanliness. The results showed that young travellers to Malaysia had stronger demands than those to New Zealand.
Pair-wise t-tests were used to group dependent variables with the same intensity levels into ranked bands. Through this method, easy-to-understand bands indicating the intensity of the dependent variables influencing selections were created to provide statistically significant groupings, which is an improvement on previous studies. In this system, variables in the top band should be interpreted as the most important factors for decision makers to take into account. Results from the bands for the two destinations showed that travellers to Malaysia were more focused in regard to accommodation attributes, with only one item in the top band (cleanliness), while travellers to New Zealand had three variables in the top band (cleanliness, price/value for money and location).
T-test analysis not only provided overall understanding of the significant differences between the two travel destinations, but also revealed the effects of travellers’ heterogeneity on accommodation purchase selection covering nine demographic profiles and tripographic variables. The inclusion of tripographic variables associated with travel behaviour (Hu & Morrison, 2002) provided useful information about the specific demands of different profiles, and how they differ between destinations. For example, among those travelling to New Zealand, significant differences were found between frequent and infrequent young travellers when it came to highly rated attributes, while for travellers to Malaysia the effect of travel frequency was inverted. Overall the effects of travel destination were more pronounced for product attributes than for personal factors. The analysis also provided an abundance of data, some intuitively straightforward and some counter-intuitive; particularly revealing were the dynamic interactions between accommodation attributes, motives and constraints. For example, safety was rated similarly between genders when referred to as an attribute, but rated very differently when referred to as a purchase motive.
Finally, this study presents findings from all of the aforementioned analyses in the form of realistic purchase selection model nesting a holistic and dynamic model-making approach into decision-making. AMOS was used to establish the strength of the relationships between variables, to provide further visible information on the distinctive effects across various traveller profiles. The models incorporate product attributes, personal factors and the heterogeneity effect of young travellers, and are comparable between the two destinations.||en