Figure 1. Research analysis model

We obtained a total of 240 responses during the six-day survey period. However, only Counter 1 was surveyed on the first day (the 24th). After confirming that the number of respondents was likely going to be lower than expected, the survey period was extended by one full day. The study scope was also expanded to include customers at Counters 1 through 4. In this regard, the following analysis excludes responses from the first day, instead, covering one week beginning on the 25th.

Table 2 shows the number of respondents on each day. As displayed, the fewest were surveyed on Thursday (27th), while the most were surveyed on Monday (31st). However, the 31st was also the last day of the month, which is generally associated with increased visitor numbers. Table 3 shows information on respondent gender and age. Looking at the bottom row (total), it can be seen that the largest percentage of participants were in their 70s, at 22.9% of the total. Breaking this down by gender, however, the largest percentage of male participants (23; 27.7%) were in their 70s, but the largest percentage of female participants were in their 60s (25; 20.7%). Table 4 shows the number of respondents for each counter on each day.

Figure 2 shows the results of the principal component analysis for each question in category Y. The principal component scores for the first and second components were added to the dataset as variables ZY1 and ZY2. Figure 2 also shows that YQ1 and YQ2 had significant effects on the first principal component, which we interpreted as ‘experience satisfaction and convenience’.