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4.6 MULTIPLE LINEAR REGRESSION

Multiple Linear Regression to examine the linear relationship between independent variables and continuous,
dependent variable. The variables must be an interval or scale level variable and are normally distributed in the research to get
the results. The significant value is to determine whether the independent variables have a relationship with the dependent
variables as the results should show a positive result if the significant value is less than 0.05. However, the Standardized
Coefficients Beta value is to determine which independent variables has the most significant relationship that will be influenced
by the dependent variable.

Table 4.7: Multiple Linear Regression – Coefficients

Model Standardized Coefficients T Sig.
Beta
(Constant) 2.652 0.009
Service Innovation 0.184 2.137 0.035
Reliability 0.277 3.545 0.001
Brand Endorsement 0.448 5.569 0.000
Dependent Variable: Positioning

As seen from the result of Multiple Linear Regression in Table 4.7, illustrate that all the variables were found to be
statiscally significant which are Service Innovation (β = 0.184, sig = 0.035) , Reliability (β = 0.277, sig = 0.001) and Brand
Endorsement (β = 0.448, sig = 0.000) due to their significant value are lower than 0.05. Hence, the strongest factor that can be
seen to be influence by Positioning is Brand Endorsement as the result of its significant value is the lowest than other
independent variables.

Table 4.8: Multiple Linear Regression – R Square

Model R R Square Adjusted R Square SE of the Estimate
1 0.809 0.654 0.645 0.268

Table 4.8 shows that the value of R-square is 0.654. From this value, it shows that the independent variables of
Service Innovation, Reliability and Brand Endorsement contributed 65.4% factors to Positioning. Concurrently, an additional
34.6% factors to Positioning are derived from another independent variable which is not evaluated in this study.

■ 5.0 DISCUSSION AND CONCLUSION

The study shows descriptive findings concerning about the factors influencing the new service positioning of tour
and travel company. In this chapter, we will explain and assessed answer to all the research question that stated in the Chapter
1 of this study. Furthermore, summarization of all analysis will be explained in this chapter. All the findings stated in this study
would be beneficial to applied to the company that want to position their service well and recognized by their customer. This
chapter also will be discussed about researcher’s limitations throughout the research along with recommendations for further
research.

5.1 INDEPENDENT SAMPLE T-TEST AND ANOVA ANALYSIS DISCUSSION

An Independent Sample T-test was conducted in this research to test the demographic groups of gender and the
results shown that there is no significant difference of the group between the new service positioning of tour and travel
company. Thus, it reveals that the service positioning of tour and travel company do are not gender-related. As Tiram Travel
Sdn. Bhd. is a tour and travel company that arrange and organize Muslim to go for hajj and umrah, the demographic groups of
gender does not affect the new service positioning of tour and travel company because regardless of Muslim men or Muslim
women, surely all will want to go perform hajj and umrah. Therefore, Tiram Travel Sdn Bhd does not subdivide their customer
into the groups of gender in their service as it will not affected the new service positioning in tour and travel company.

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