From the EFA, the study had a total of sixteen items. To understand the strength of the relationships, and to show the association among variables in order to infer meaning or approach generalization, it was elected to use correlation logic (Neuman, 2007, pp. 389, 390). Correlation analysis is preferred in this study as it shows not only the strength, but the direction of the relationships within the variables (Pallant & Manual, 2007, p. 126).
The items to be run on the correlation table were quite many, and we ran the risk that the correlation table would be extremely bulky and not easy to follow. At this point, the study’s focus was on describing the relationship within the five components, excluding the lifestyle component.
Having three questions from the sensory to compare with five questions from the cognitive and so on, would prove quite voluminous and not easy to follow. It was decided to weigh the items and give a single compounded variable number for each component. So instead of describing relationships between sixteen questions in the correlation analysis which would total to about one hundred and twenty different relationships, we would be describing approximately ten relationships between the five components. By accounting for only significant correlations, the number of relationships to be explained would probably be lesser than has been stated, but still quite numerous. The process of giving a weight is the process of averaging the numbers (in this case the factor loadings) to a total of one, and then multiplying the weight and mean value and adding this to the weight and the mean of the next question until the questions for that particular
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component are done. This leaves us with just one figure to represent one component. This will be demonstrated in the table below.
(S_11) Perception of Different sounds and music (S_12) Perception of different smells at the Lobby
(S_19) How would you rate the help you got to solve problem in a difficult situation?
Cognitive
(S_15) Rate speed and efficiency of check-in and how it made you feel?
(S_16) Rate conversation with reception during check-in and how it made you feel?
(S_17) How would you rate your entire check-in experience at last hotel (S_36) How would you rank your last check-in to all other check-in experiences?
(S_22) Was the information provided easy to understandable and useful for your stay?
Emotional
(S_34) If you were welcomed by a hotel staff on arrival, how did this make you feel?
(S_35) If you were not welcomed by a hotel staff on arrival, how did this make you feel?
Pragmatic
(S_8) perception about the appearance of the Lobby?
(S_10) How did the appearance of the Lobby make you feel?
(S_23) Were the Hotel facilities and design of things functional and not complicated?
Relational
(S_25) Do you like it when the hotel gives you special favors e.g a free city tour?
(S_26) Do you like it when the hotel gives you personalized service e.g finding your favorite drinking water brand for you?
(S_27) Do you actively try to keep a good relationship with the reception staff?
0.738
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Table 5 above shows the five components and their factor loadings as obtained from the EFA.
The weight column was obtained by summing up the factor loadings for each component individually and averaging them to a total of 1. By multiplying the weight and the mean value, then adding to the weight and the mean value of the next for all the items in that specific component, we were able to come up with the singular compounded figure, also known as the weighted average mean.
Example (Sensory Component):
Weight for item 1 in the component is: 0.738/ (0.738+0.747+0.599) = 0.354 Weight for item 2 in the component is: 0.747/ (0.738+0.747+0.599) =0.358 Weight for item 3 in the component is: 0.599/ (0.738+0.747+0.599) = 0.287 The composite variable sensory for the first observation (respondent) becomes:
0.354*answer for item 1+0.358* answer for item 2 +0.287*answer for item 3
0.354*K2(6)+0.358*L2(5)+0.287*T2(6) =5.636 (Adopted from excel table for the weighted measure of 1 out of 276 respondents in the sensory component)
By following the formula, this was done for all the two hundred and seventy-six respondents and for all the five components. The result was that five new compound variables were created from our sample size of two hundred and seventy-six respondents. The correlation table would have five components instead of the sixteen (five compounded variables). These five are the components that were used in the correlation analysis. The significance of this table shall also be seen in the results chapter, as the hierarchy of importance is discussed.
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**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
The correlation table above represents the five components and the relationships revealed.
Kozak (2009, p. 86) asserts that students should not be taught any limits that are to help interpret correlation due to the problem of boundary values; for example, 0.49 is weak but 0.50 is strong.
He asserts that correlation coefficient is part of statistics, a method of interpretation in which logic
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plays an important role. In following this, the study employed the following notations to explain the findings of the correlation analysis r =.00-.19 ‘very weak’, .20-.39 ‘weak’, .40-.59 ‘moderate’, .60-.79 ‘strong’, .80-1.0 ‘very strong’.
The cognitive component had a moderate positive correlation to the pragmatic component at 0.483**. This was the strongest correlation noted within our correlation table. The cognitive component also had a weak positive correlation to the sensory component at 0.366**. There was a very weak, positive, and significant correlation between the cognitive component and the emotional component at 0.152*. There was also an insignificant/no correlation between the cognitive component and the relational component at 0.016 and significance levels of 0.790. The pragmatic component had a weak positive correlation to the sensory component at 0.294**, a very weak and positive correlation to the emotional component at 0.177** and a very weak and insignificant/no correlation to the relational component at 0.106, with significance levels of 0.078.
The sensory component had a positive and insignificant correlation/no correlation to the emotional component at 0.057, significance levels of 0.344 and a positive and insignificant/no correlation to the relational component at 0.106 and significance levels of 0.078. Lastly, there was a negative and insignificant/no correlation between the emotional component and the relational component at -0.089 and significance levels of 0.141.