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This paper is a case study on the tourism scene in Australia. Primary data was collected from tourists and analysed to identify the notable trends at the time. It was then objectively studied.
Section 2 describes the data collection methodology and structure of the data. Section 3 lays down the research methodology and the objective along with rationale. The findings are compiled in section 4. The paper then concludes with the answers to the questions as well as providing recommendations and identifying the limitations of the study.
The data used for the case study is a primary dataset that was collected through survey method. Primary data analysis was chosen to collect current data as per the suitability of the defined research objectives which are elaborated in the methodology section (Walliman, 2017). The data was collected in four parts by four separate individuals, whereby the respondents were chosen randomly using simple random sampling rationale from tourists to Australia which can be considered independent (Peck, Olsen & Devore, 2015). Simple random sampling is a simple and robust data collection method which assigns equal chance to every member of the population in being included in the sample (Burns, Bush & Sinha, 2014). This allows for unbiased, robust, simple and cost efficient method of data collection in primary research. This ensures equal and fair representation and unbiased estimation of statistics (Yin, 2017). In this case tourists were randomly chosen and data was collected from the population of all tourists in Australia in 2018. Primary data analysis using quantitative data can be used to objectively identify valuable insights (Creswell & Creswell, 2017).
Each individual collected 10 observations each and these were merged to form the complete data of size 40 observations, The dataset had 7 variables which were all categorical in nature, namely, gender of the tourist (with categories, male or female), country of origin, destination visited, occupation of the tourist that is, whether student, retired or employed; and reason for visit that is, whether business trip, holiday trip, meeting up with friends or for the purpose of studying, which were all nominal. The variable age of the tourist was ordinal with age being denoted as age divided into intervals in years (Anderson et al., 2016).
The design is cross-sectional, with data collected around the same time for multiple tourists. This was because the scope of the study is to explore current scenario (Bryman & Bell, 2015). The study is a descriptive study. The demographic variables, age, gender and country of origin were first summarized using frequency distribution in numerical and graphical format. The response to the items in the dataset was then explored by mean of various charts to form a descriptive analysis (Veal, 2017). The collected data were analysed using tools of descriptive statistical analysis by means of Microsoft Excel tools. The research objective is to study the trends in tourism in Australia. The analysis targeted the data for trying to answer the following research questions.
- What are the most popular reasons for visiting Australia?
- How many days does a tourist spend in Australia?
- What is the popularity of the destinations in Australia?
- How many days would a tourist spend holidaying in Australia?
- How many days would a tourist spend in a business trip in Australia?
- Age of people on Holiday in Australia?
- Popularity of destination as per reason for visiting Australia?
Data Collection Methodology and Structure
The sample of data acquired therefore had the following demographic profile. 50% were aged between 20 and 30, 27.5% were aged above 40, 20% were aged between 30 and 40 and 2.5% were aged less than 20. Again, 47.5% were males and 52.5 % were found to be females among the collected sample. 12.5 % were from China, UK and Italy was reported 10% each, Vietnam and Japan was reported by 7.5% each, Nepal other parts of Australia, Singapore, India and Malaysia constituted of 5% each, Egypt, Turkey, Cambodia, France, Belgium, Scotland, Argentina and Spain all constituted 2.5% of the sample. The following figures give the graphical summary of the same. The data thus reveals that much of the tourists to Australia are Chinese. As per Pham, Nghiem & Dwyer (2017), one of the key drivers of Chinese tourists is that of affordable cost of travel. Hence it is suggested that the tourism in Australia could have satisfied those requirements to draw such Chinese attention. Again, Madhavan (2014) had studied what drives tourist’s motivations for travel, especially keeping in mind senior tourists. This study also concludes that higher prices and under-developed accommodation facilities, serve to demotivate travels. Given that the data found the second highest proportion of tourists to be above 40 years of age, it is suggested that Australian tourism also keeps the same in mind to provide ample affordable travel facilities.
Figure 2: Gender of Tourists
Figure 3: Country of origin of people in the sample
As per the sampled data, 55% of the tourists were visiting Australia for holiday purpose. The second most popular reason identified was to study, with 32.5% reporting the same. It is to be noted in relation to this finding, that as per Wearing et al. (2016), education tourism is an emerging market in Australia with considerable scope for growth. 10% reported that they were here for business and 2.5% said that they were visiting friends.
Research Methodology and Objective
Figure 4: Cause for Visit
The Opera house was found to be the most popular destination with 20% reporting that they wanted to visit the place. The Queen Victoria Bridge, Harbour Bridge and Circular Quay had 17.5% people naming them each. The rocks had 15% of the votes. Hence these are the most sought after destination in Australia. These are followed by the Royal National Park withb7.5% and Anzac park and the city of Sydney with 2.5% each.
Figure 5: Destinations in Australia by popularity
25% of the tourists in the sample were found to be retired individuals, 40% were students and 35% were employed.
Figure 6: Occupation of the tourists
Out of the total number of people who are reportedly holidaying in the sample, the majority, 40.91% were found to be on a 7 to 15 days trip. Around 31.82% were visiting for a 3 to 7 day trip. So, about 72.73 % holiday for 3 to 15 days. 13.64%. 13.64% reported that they were holidaying for 1 to 3 days. 4.55% said that their trip was between 15 to 30 days and 9.09% came to holiday for over a month. These numbers describe the probability distribution of the days of stay of a person holidaying in the city (Salkind, 2016).
Findings
Figure 7: Days spent holidaying in Australia
75% of the tourists in Business trips were found to spend 3 to 7 days whereas 25% were found to be there for more than 30 days. This may be interpreted as the probability of an individual on a business tour to be in the city for 3-7 days and greater than 30 days respectively (Rumsey, 2015).
Figure 8: Days spent on Business Trips in Australia
The most popular destinations with foreign students were found to be the Harbour bridge and Opera house. The opera house attracted all kinds of tourists. Circular Quay, QVB and the rocks were the most favoured spots for those on Holidays. Those on business trips were found to be limited to Sydney, the Rocks and the Opera House. The following stacked column chart shows the popularity of each destination for each group (Winston, 2016). Now, taking into account a study by Gardiner, Grace & King (2014) which found that hedonistic experiences are the primary drivers of tourists in Australia today, it is corroborated with the findings where sites like the Opera house draw more attention than other sites which may be more aligned with functionality. In fact all the top destinations lean more towards hedonistic experiences. This is also reflected in how holidaying forms the top most reason for visiting the country.
Figure 9: Destination popularity as per tour reasons
Recommendations
Conclusion:
The most popular reason to visit Australia was found to be holidaying. However education was also identified to be a notable reason. A tourist holidaying in the country was mostly found to spend between 7 to 15 days. Chance of people on business trips spending 1 to 3 days is 75% and 25% spend over a month. The most popular destination was found to be the Opera house which had attendance from all identified groups of tourists, especially students and people meeting friends. Those on business trips were found limited to Sydney. The Harbour Bridge was yet another spot popular with students and Circular Quay was found to be the destination where most holiday goers went.
The study is limited in terms of data and variables. The volume of tourists to the country per year is large. However the sample size is very small in comparison. The study should increase the size of data and variety of variables for more in-depth and reliable results (Walliman, 2017). The study also does not take into account impact of any changes arising out of seasonal variation which may reveal significant trends as per Veal (2017).
It is recommended that the tourism authorities look towards developing education tourism further as the number of students visiting the country is seen to be noteworthy. It is also recommended that more attractions be invested in Sydney for drawing short term attention, for those who may be in the city for Business purposes. Finally, it is recommended that cost of travel be kept affordable and it is ensured that enough accommodation and transport facilities are set up and maintained.
Reference:
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2016). Statistics for business & economics. Nelson Education.
Bryman, A., & Bell, E. (2015). Business research methods. Oxford University Press, USA.
Burns, A. C., Bush, R. F., & Sinha, N. (2014). Marketing research (Vol. 7). Harlow: Pearson.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Gardiner, S., Grace, D., & King, C. (2014). The generation effect: The future of domestic tourism in Australia. Journal of Travel Research, 53(6), 705-720.
Mahadevan, R. (2014). Understanding senior self-drive tourism in Australia using a contingency behavior model. Journal of Travel Research, 53(2), 252-259.
Peck, R., Olsen, C., & Devore, J. L. (2015). Introduction to statistics and data analysis. Cengage Learning.
Pham, T. D., Nghiem, S., & Dwyer, L. (2017). The determinants of Chinese visitors to Australia: A dynamic demand analysis. Tourism Management, 63, 268-276.
Rumsey, D. J. (2015). U Can: statistics for dummies. John Wiley & Sons.
Salkind, N. J. (2016). Statistics for people who (think they) hate statistics. Sage Publications.
Veal, A. J. (2017). Research methods for leisure and tourism. Pearson UK.
Walliman, N. (2017). Research methods: The basics. Routledge.
Wearing, S., Tarrant, M. A., Schweinsberg, S., Lyons, K., & Stoner, K. (2015). Exploring the global in student assessment and feedback for sustainable tourism education. In Education for sustainability in tourism (pp. 101-115). Springer, Berlin, Heidelberg.
Winston, W. (2016). Microsoft Excel data analysis and business modeling. Microsoft press.
Yin, R. K. (2017). Case study research and applications: Design and methods. Sage publications.
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