Data Analysis & Findings

 

Demographic Statistic of the Sample Data

Variable	Category	Frequency	%
Gender	Male  Female	31  79	28.2  71.8
Age	16 - 25 years old  26 - 35 years old  36 - 45 years old  46 - 55 years old	101  2  3  2	91.80  1.8  2.7  1.8
Race	Malay  Indian  Chinese  Bumiputera Sarawak	108  0  1  1	98.2  0  0..9  0.9
Education	Foundation  Diploma  Bachelor/Degree  Postgraduate  A-Level	4  16  84  5  1	3.6  14.5  76.4  4.5  0.9
Status of Employment	Students  Employed  Unemployed	82  23  5	74.5  20.9  4.5
Monthly Income	< RM1500  RM1501 to RM3000  RM3001 to RM4500  RM4501 to RM6000  RM6001 to RM7500	87  14  1  2  6	79.1  12.7  0.9  1.8  5.5
States of Origin	Selangor  Perak  Melaka  Wilayah Persekutuan Putrajaya  Kuala Lumpur  Pulau Pinang  Negeri Sembilan  Sarawak  Pahang  Kedah  Johor  Terengganu  Kelantan  Sabah	23  9  10  1  22  6  3  1  11  11  7  1  4  1	20.9  8.2  9.1  0.9  20.0  5.5  2.7  0.9  10.0  10.0  6.4  0.9  3.6  0.9
Travel Frequency	1 - 5 times  6 - 10 times  10 times or more	93  9  8	84.5  8.2  7.3

Cross Tabulation between Gender and Age

Results on Tested and Validated Research Framework

Based on the figure above, it demonstrated the findings from the validated and tested research framework. Therefore, we can interpret from these diagrams that there are four independent variables and one dependent variable. There are two categories that divide the independent variables which are the tangible and intangible components. Thus, the two independent variables under tangible components are destination appeal (DA) and tourist infrastructure (TI). As for independent variables under tangible components are service quality (SQ) and destination image (DI). 

Figure 5: Average Variance Extracted (AVE)

The first hypothesis (H1) proposes that the marketing efforts of a rural tourism destination are closely related to its destination appeal. Since there is a negative relationship between these two variables, the findings of this study still support this hypothesis. Even though the destination appeal is less than 0.5, as shown in Figure 9 it is considered close to valid as our sample is only a small size of sample which is around 110 respondents only. A second hypothesis (H2) attempts to determine whether tourism infrastructure is correspondent with marketing initiatives at rural tourism destinations. The results showed that this hypothesis is feasible. Mandi et al. (2018) reached the same conclusion, as tourism infrastructure is one of the factors contributing to the development of rural tourist destinations.