Determinants of tourist spending: regression analysis
While tourism is a source of economic good for many countries, it is influenced by a number of factors and these factors actually influence the revenues accruing to the given tourist destination country. In order to ensure that a country gets the optimal income from tourism, it is important for the specific tourist destination to know the relationship that exists between and among the various factors in the industry.
Given that tourists come from diverse places, the mode being informed or getting knowledge of a particular tourist attraction is unlikely to be the same; or at least the mode is related to the place of origin of the tourist. This is notwithstanding the differentials in development from place to place (implying that the same mode of advertisement is least likely to be formality for all the places of origin). Since promoting a tourist destination to interested tourists will lead to a number of questions, an evaluation of the underpinning factors will help in carrying out the exercise beneficially. For instance, what mode of advertisement should the tourist destination use for UK originating tourists? What kind of recreation facilities do we put in place to attract them? Do they bother about recreational facilities at all? Is there relationship between the number of adult tourists and their total spending? So should we or should we not advertise for package tourism? These are among the key questions that if answered they may boost the process of decision making.
In the following analysis, an evaluation of the above factors is carried out based on data collected by Sabah Tourism Board in 2007. The main objective of collecting and evaluating the data is to assess the relationship, if any, that exists between and among various factors that relate to each other to cause an influence on the origin of tourists attracted to the Sabah Tourist centre. The data is analyzed using SPSS version 16.0 and the results or output from the analysis is given in the tables.
In the chart 3 above, the parameters are the total numbers of adults, total number of days of holiday and the mean spending. The chart indicates that though South Korea’s tourists are fewest, they spend longest number of days for their holidays. Their mean spending is however lower than that of UK despite the fact that the UK tourists spend almost as equal the number of days as the number of tourists.
Statistical analysis and rationale for the analysis
The Sabah Tourist Board collects data for visiting tourists in terms of number of days a tourist or group of tourists stays in their tourist destination, the amount spent during the trip or tour, the mode of advertisement that was involved in attracting the particular tourist or tourists. The other statistics collected by the board about the tourist are the number of adult tourists in a given group and also their origin in terms of the country they come from or nationality. According to the data therefore, although the revenues that accrue from tourism are basically as a result of the spending by the tourists, spending in itself is a function of two main variables: the number of adult tourists and the number of days stayed by the tourists
In terms of the number of days, Japan still has the highest scoring 10 days followed, in order, by S. Korea having 9 days then Taiwan and UK tying with 8 days. In order to come up with a conclusive report from a regression analysis, it was necessary to find a multiple linear regression equation for each nationality, for the group spending on the number of days stayed and the number of adults.
Regression Table- Table 9
i. South Korea
Spending = 99.869 No of days + 96.820 No. of Adults + 87.564
According to the equation produced for the tourists from South Korea, spending is a function of about 100 times the number of days stayed, 97 times the number of adults in the tourist package and an additional constant of about 87.6 dollars. Thus, the number of days spent slightly outweighs the number of adults in determining the level of spending for the tourists from South Korea. This means that Sabah Tourism Board should initiate advertisement that encourages the South Korean tourists to stay longer.
Spending = 99.520 No. of days + 115.120 No. of Adults + 19.135
For tourists from Taiwan, it is the exact opposite of South Korean case. Spending is highly determined by the number of adults than the number of days the tourists stay. Therefore, more package tourism should be advertised.
Spending = 135.000 No. of days + 129.470 No. of Adults + 4.217
For Japan, the number of days spent highly determines amount spent by the tourists than the number of adults in the group. For all the regression equations, it is important to note that South Korea has a higher constant than all the other tourist origins.
The following are the coefficients of correlation and determination for each of the above regression equations.
I. South Korea: coefficient of correlation= 0.926: coefficient of determination= 0.857
II. Taiwan: coefficient of correlation= 0.909; coefficient of determination= 0.827
III. Japan: coefficient of correlation= 0.917; coefficient of determination= 0.841
IV. UK: coefficient of correlation= 0.915; coefficient of determination= 0.836
Looking at the regression and relating it to chart 3, we can see the reason why the coefficients for Japan for number of days and adults are higher than other nationalities. This as can be seen from the spending column of the chart, the Japanese tourists spend more during their holidays as compared to the other tourists despite the fact that the mean number of days for UK is even greater than that of Japan. Even the mean number of adults for UK is also greater than the one for Japan. However, it must be noted that if the number of days and the number of adults is held constant, Japanese tourists are likely to generate the least revenue from tourist spending. Thus, more advertisement to Japanese must be bolstered to ensure that the number of tourists from Japan and the number of days they spend increase.
The mode of advertisement is also found to be strongly related to the origin of the tourist in that tourists from a particular place will be better reached by specific modes of advertising. This agrees with the findings of Beerli et al (2003) who contend that because of difference in cultural aspects among other factors, tourist attraction in terms of country of origin is highly related to mode of advertising set to attract them.
Beerli, C., A., Josefa, J. D. & Martín D. (2004) “Tourists’ characteristics and the perceived image of tourist destinations: a quantitative analysis—a case study of Lanzarote, Spain” Tourism Management 25(5): 623-636.
Bruin, J. (2006) “New test: command to compute new test” UCLA: Academic Technology Services, Statistical Consulting Group; Available Online from URL: http://www.ats.ucla.edu/stat/stata/ado/analysis/.
Hinton, R. P. (1997) “Statistical Guide for Social Science Students” NY (USA); Rutledge:
UCLA (2006) “Introduction to SAS” Academic Technology Services, Statistical Consulting Group; from http://www.ats.ucla.edu/stat/sas/notes2/.