This research distributed out a total of 425 questionnaires. Of the total amount, 225 of them were collected online and 200 of them in printed form. Subtracting those who had not purchase sports products within the last year, and those responses who were outliers, the valid amount of questionnaires came to 354. This gives us a validity rate of approximately 83.3%. Table 4.1 shows the overall descriptive statistics.
Table 4.1: Overall Descriptive Statistics for the Valid Samples Valid sample N=354
Information Frequency Percentage
Male 134 37.9%
Gender
Female 220 62.1%
Below 20 102 28.9%
21 to 30 111 31.4%
31 to 40 56 15.8%
Age
Above 41 85 24.0%
Under 10,000NT 130 36.7%
10,001-15,000NT 48 13.6%
15,001-20,000NT 25 7.1%
20,001-30,000NT 37 10.5%
30,001-40,000NT 29 8.2%
Income
Above 40,000NT 85 24.0%
Less than 3 years 109 30.8%
3 to 5 years 74 20.9%
6 to 8 years 51 14.4%
9 to 11 years 25 7.1%
Consumption experience
Over 11 years 95 26.8%
Less than 3 times 191 54.0%
Protective clothing 14 1.5%
Jackets 111 12%
Caps 15 1.6%
Sports balls 42 4.5%
Specialized sports equipment 52 5.6%
Accessories (choice of 3)
Others 4 0.4%
.
The respondents were mostly female, contributing to over 60% of the total sample. As for the age range, it is spread out quite equally for people within the 21 to 30 age range representing the most proportion, 31.4%. This shows that the sports
product that everyone consumes does not really have an age restriction. People of all ages still continue to buy sports products for them to engage in games or to exercise.
The income showed two dominant groups, below 10,000NT and over 40,000NT. Due to the fact that some subjects fall into the under 20 or 21 to 30 age group, their income is not very stable yet. For those who are over the age of 40, their income would then have a higher chance of earning over 40,000NT.
The consumption experience was also evenly spread out with the exception of the 9 to 11 years range. This implies that people do have a tendency to buy sports products and that they have continued to purchase them throughout their daily lives.
Within the past year, respondents replies that they did not buy sports products over three times, showing over half of the total amount, 54.0%. The second largest population was the 3 to 5 times range. From this, we can conclude that people do not go to buy sports products that often within one year due to the fact that the turnover ratio of are not very high. Money spent on sports products fall into the 1001 to 2000NT and the 2001 to 3000 NT category, accounting for 61.3%. Technically, some famous brands are more expensive than others, as we can see that people are willing to spend such money on these products.
For the brand preference, subjects can choose a maximum amount of two brands that they like the most. Nike showed the dominant brand choice for consumers as it has already developed a deep popularity among us. Adidas also had a high rate, earning 28.4% which came only behind Nike. New Balance and Converse added up to 19.4% due to the Taiwanese female’s taste in these brands’ shoes. A graph of brand preference is shown in figure 4-1 based on the numbers.
Figure4-1: Brand Preference for the Respondents
From figure 4-1, Nike had a high response with over 250 people choosing it as their favorite brand. Adidas can compete with Nike, with over 150 votes, standing in at the number two spot. Puma, Reebok and Under Armor does not show a high rate for we can tell that the popularity is not that high in Taiwan.
Subjects had the privilege to choose up to three accessories that they enjoy purchasing the most. Shoes were the dominant category, accounting for 35.1%
followed by shirts, which had 22.4%. Pants and Jackets were not far behind as both of them also showed over 10%. One thing to notify here is that protective clothing, sports balls and specialized sports equipment added up to only around 11.6%. This implies that Taiwanese people purchase sports products is mostly for the purpose of wearing or style instead of playing professional sports. Figure 4-2 has the overall numbers for consumers’ choice of accessories for sports products.
Figure4-2: Accessories Preference for the Respondents
Shoes earned over 300 votes followed by shirts with over 200. The next group falls into pants and jackets as they both had over 100 responses. Protective clothing, caps and sports balls did not have at least 50 replies, making them the last in this section.
The emotional value showed the highest mean of 5.35 of all the independent variables as shown in Table 4.2. This indicates that people agree very much to the statements when concerning buying sports products will make them happy. The second highest was the usage item under the functional value with an average of 5.08.
As for the low ones, the price was 4.17 and the conditional value was 4.20.
Table 4.2: Mean and Standard Deviation for Independent Variables
Independent
Variables Factors Items Mean Standard Deviation
Component Average
Component Standard Deviation IV 1 5.35 1.18
IV 2 5.15 1.18 Internal
Value
Emotional value
IV 3 5.39 1.25
5.30 1.21
IV4 5.10 1.29
The satisfaction and repurchase intention for dependent variables in table 4.3 showed high means of 4.94 and 5.68. This implies that customers are willing to come back and purchase products that make them satisfied.
Table 4.3: Mean and Standard Deviation for Dependent Variables
Variables Factors Items Mean Standard
Deviation Component
The mediation effect of information visibility in Table 4.4 showed an average of 4.66 with a standard deviation of 1.36.
Table 4.4: Mean and Standard Deviation for Mediator
Variables Factors Items Mean Standard Deviation
Component Average
Component Standard Deviation INV1 4.68 1.38
INV2 4.72 1.41 INV3 4.80 1.33 Mediator Information
Visibility
INV4 4.45 1.31
4.66 1.36
Looking it from a broader view, we can combine emotional and epistemic into internal value, social and conditional into the external value. Also, putting price, quantity, need and usage together would become the functional value. Table 4.3 has the average and standard deviation for all three categories.
Table 4.5: Mean and Standard Deviation for the Combined Independent Variables
Independent Variables Mean Standard Deviation
Internal value 5.10 1.29
External value 4.21 1.39
Functional value 4.75 1.38
The highest mean was the internal value, with an average of 5.10 while the lowest was external value, only 4.21.
For the component mean scores in Table 4.2 to Table 4.5, seven levels of Likert scale were adopted for the questionnaire in this research. 1 representing totally
disagrees, 4 representing moderate and 7 indicating totally agree. The higher the score is means the higher of the perceived agreement.
4.2 Reliability
This study uses the statistics software of SPSS 22 to conduct the data analysis.
We calculate the Cronbach’s Alpha coefficients of each component to test reliability and ensure they are internally consistent. The Cronbach’s Alpha coefficients of each part are show in Table 4.6.
For the Cronbach’s Alpha analysis below, the independent variables of emotional and epistemic are viewed as internal value; social and conditional as external value.
Price, quantity, need and usage are combined as functional value. Each subordinate factor corresponds to their Cronbach’s Alpha. Details are presented in Table 4.6 where item to Total and Cronbach’s Alpha if item deleted for internal, external and functional value are included.
Table 4.6: Cronbach’s Alpha for Independent Variables
Independent Variables Factors
Items Cronbach’s
Alpha Item to Total Cronbach’s Alpha if item
FV2 .780 .841
The Cronbach’s Alpha for emotional value is .860 and the Item to Total falls within the range of .688 to .790. Any item deleted will lower the value of Cronbach’s Alpha; therefore, no items need to be removed. Epistemic value’s Cronbach’s Alpha is .826 and the Item to Total is .637 to .728. No items should be removed as this will decrease the value of Cronbach’s Alpha. The Cronbach’s Alpha for social and conditional are .841 and .722. The Item to Total range is .514 to .731. The Cronbach’s Alpha will decrease if items are deleted so we should not remove any items. The functional value consists of price, quality, need and usage. Their respective Cronbach’s Alpha is .888, .839, .824 and .830. Item to Total are .601 to .850. Since every Item to Total is greater than 0.4, none of them should be deleted.
Table 4.7 shows the Cronbach’s Alpha for dependent variables including satisfaction and repurchase intention. The Cronbach’s Alpha are .910 and .829 respectively. The Item to Total is from .796 to .849 for the satisfaction variable. There is no need to delete any items as this will decrease the value of Cronbach’s Alpha. The Item to Total for repurchase intention are all greater than 0.4; as a result, no items are moved.
Table 4.7: Cronbach’s Alpha for Dependent Variables
Item to Total Cronbach’s Alpha if item
The Cronbach’s Alpha for the mediator, information visibility is .888 are shown in table 4.8. The Item to Total falls between .682 and .821. If any items are deleted, the value of Cronbach’s Alpha will decrease; therefore, no items should be removed.
Table 4.8: Cronbach’s Alpha for Mediator
Mediator Items Cronbach’s Alpha
Item to Total Cronbach’s Alpha if item
Prior implementing the factor analysis, we need to clarify whether it is suitable or not to continue the analysis. Therefore, some examinations should be conducted.
The KMO coefficient is one way to look at our data. The range of it would be from 0 to 1; the higher means a higher correlation among the variables. It would require a