Table 4-1 emotion clusters
4-3 Correlations between service features and emotions
Finally, participants who filled the questionnaire were 47 office workers (includes 12 male and 35 female) who took bus as a transportation tool. And there were 22 questionnaires via the internet, 25 questionnaires by face to face visit. The data from questionnaire was analyzed by quantification theory type I in this section.
Quantitative Type I analysis was applied for 5 times for each abstract feeling: “afraid”,
“disappointment”, “distress”, “reproach”, and “fatigue”, concrete feature of each were listed below.
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Figure 4-4 the modified EGM diagram
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4-3-1 Reproach
According to the Quantification Theory Type I analysis, the item “bad attitude (0.679)”
has the highest correlation coefficient and it should results in eliciting the sense of reproach. Besides, the category “unconcern (1.927)” with highest and positive score could be the main feature making people feel reproach, and the multiple correlation coefficient in table is 0.759, the coefficient of determination is 0.577, as shown in Table 4-2. The item “other passengers’ effect” has a close coefficient, and the item also was considered in the later discussion section.
Table 4-2 result of reproach analysis
Abstract feeling item category value coeffient
out of schedule -0.153
late when it rain 0.536
many buses come in the same time -0.646 pass stop without stopping 0.220
payment problem -0.811
small bus for lots people 0.561
catch up schedule with high speed 0.467
easy to fall down -0.435
drive before people sit down -0.022 turn a corner with high speed -0.981
bad gear skill 0.408
suddenly brake 0.268
pass stop without stopping -0.072 drive before people sit down 1.520 catch up schedule with high speed -0.339
unconcern 1.927
bad answering to passenger -0.321
all are passengers' fault 0.006
drive fast when getting off -0.729 using phone with high volume -0.520 fight for boarding/getting off 0.030
noise -0.816
fight for the seats -0.552
no yield seats to elderly people 0.905 priority seats are not enough -0.070
smell bad 0.185
stuck in the middle of bus 0.120
R = 0.759 K=3.881
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4-3-2 Distress
The item “other passengers’ effect (0.413)” has the highest correlation coefficient and it should results in arousing the sense of distress. Besides, the category “priority seats are not enough (0.428)” with highest and positive score could be the main feature making people feel distress, and the multiple correlation coefficient in table is 0.513, the coefficient of determination is 0.264, as shown in Table 4-3. The item
“management problem” has a close coefficient, and the item also was considered in the later discussion section.
Table 4-3 the result of distress analysis
Abstract feeling item category value coeffient
out of schedule 0.121
late when it rain 0.447
many buses come in the same time -0.531 pass stop without stopping 0.077
payment problem -0.104
small bus for lots people 0.457
using phone with high volume -0.191 fight for boarding/getting off 0.354
noise -0.384
fight for the seats -0.818
no yield seats to elderly people -0.041 priority seats are not enough 0.428
smell bad 0.311
stuck in the middle of bus -0.419
umcomfortable single seat 0.657
screen flicker 0.059
no regular maitenance of old 0.065
off bell fault -0.081
aesthetic damage by many daub -0.030 scrolling text marquee fault -0.119
R = 0.513 K=2.774
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4-3-3 Afraid
The item “un-safety driving (0.414)” has the highest correlation coefficient and it should results in arousing the sense of afraid. Besides, the category “catch up schedule with high speed (0.538)” with highest and positive score could be the main feature making people feel afraid and the multiple correlation coefficient in table is 0.530, the coefficient of determination is 0.282, as shown in Table 4-4.
Table 4-4 result of afraid analysis
Abstract feeling item category value coeffient
out of schedule -0.248
late when it rain -0.228
many buses come in the same time 0.092 pass stop without stopping -0.055
payment problem 0.122
small bus for lots people 0.194
catch up schedule with high speed 0.538
easy to fall down -0.582
drive before people sit down -0.330 turn a corner with high speed -0.138
bad gear skill 0.204
suddenly brake 0.163
pass stop without stopping -0.291 drive before people sit down 0.660 catch up schedule with high speed 0.289
unconcern 0.239
bad answer to passenger -0.190
all are passengers' fault 0.073
drive fast when getting off -0.015 umcomfortable single seat -0.241
screen flicker 0.394
no regular maitenance of old -0.408
off bell fault 0.073
aesthetic damage by many daub 0.186 scrolling text marquee fault -0.424
R = 0.530 K=2.957
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4-3-4 Fatigue
The item “un-safety driving (0.657)” with the highest correlation coefficient and it should results in arousing the sense of fatigue. Besides, the category “suddenly brake (0.470)” with highest and positive score could be the main feature making people feel fatigue and the multiple correlation coefficient in table is 0.716, the coefficient of determination is 0.512, as shown in Table 4-5.
Table 4-5 result of fatigue analysis
Abstract feeling item category value coeffient
out of schedule 0.469
late when it rain 0.452
many buses come in the same time -0.038 pass stop without stopping -0.399
payment problem 0.733
small bus for lots people 0.207
catch up schedule with high speed 0.106
easy to fall down -0.804
drive before people sit down -0.684 turn a corner with high speed -0.422
bad gear skill -1.347
suddenly brake 0.470
pass stop without stopping 0.229 drive before people sit down 1.920 catch up schedule with high speed -0.279
unconcern 0.557
bad answer to passenger -0.197
all are passengers' fault -0.256 drive fast when getting off 0.535 using phone with high volume -0.514 fight for boarding/getting off 0.263
noise -0.449
fight for the seats 0.537
no yield seats to elderly people 0.274 priority seats are not enough 0.049
smell bad -0.397
stuck in the middle of bus -0.250
R = 0.716 K=3.472
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4-3-5 Disappointment
The item “management problem (0.488)” with the highest correlation coefficient and it should results in arousing the sense of disappointment. Besides, the category “out of schedule (1.742)” with highest and positive score could be the main feature making people feel disappoint, and the multiple correlation coefficient in table is 0.566, the coefficient of determination is 0.320, as shown in Table 4-6. The item “other passengers’ effect” has a close coefficient, the item also was considered in the later discussion section.
Table 4-6 result of disappointment analysis
In brief, in this section the correlations between service features and emotions were delivered. In the next chapter, the context between each item would be explained and discussed.
Abstract feeling item category value coeffient
out of schedule 1.742
late when it rain -0.416
many buses come in the same time 0.077 pass stop without stopping -0.554
payment problem -0.336
small bus for lots people 0.335
using phone with high volume -0.827 fight for boarding/getting off 0.406
noise -0.050
fight for the seats -0.656
no yield seats to elderly people -0.696 priority seats are not enough 0.817
smell bad -0.317
stuck in the middle of bus 0.620
R = 0.566 K=3.032
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