1. An Empirical Study On Willingness To Pay In Taiwan
Chun-Ho Kuo
Center of Energy Economics and Strategy Research, INER, Taiwan
Department of Economics, National Tsing Hua University
Cheng-Da Yuan, Fu-Kuang Ko

2. Neither Agree Nor Disagree
The Questionnaires
1200 qualified respondents in the study of willingness to pay in Taiwan.
41 items (variable) in 5-point Likert-type scales analyzed
41 observed variables are too many => Smaller number of unobserved variables => Factors => Linear Regression
No.
Item
Strongly Disagree
Disagree
Neither Agree Nor Disagree
Agree
Strongly Agree 1
I understand the issue of Taiwan's nuclear energy security and various types of power generation waste disposal 2 3 4 5
I understand what renewable energy I can use
The price of Taiwan's energy is relatively cheap 41
I'll post energy articles in Blog, FB or Line.

3. Motivation For the questionnaire:
One question → One Variable → Too many variables
The importance of each Variable unknown
The relationship between the variables unknown
On This Study:
Factor Analysis to extract few factors to explain the result of Questionnaire → Reduce the Cost
Linear Regression → Find out the relationships of factors

4. The analyzing processes
Reliability Test
Cronbach’s alpha to assess the reliability. The Cronbach’s Alpha is in our questionnaire. (α should be bigger than 0.9)
Bartlett's test of sphericity
Significance level = 0 (should be smaller than 0.05).
The KMO Measure of Sampling Adequacy:
The value of KMO: (should be bigger than 0.9)
Community value of Item No. 18: < 0.5  The item can be deleted.
(Alpha is bigger than 0.7 .) The resulting αα coefficient of reliability ranges from 0 to 1 in providing this overall assessment of a measure’s reliability. If all of the scale items are entirely independent from one another (i.e., are not correlated or share no covariance), then αα = 0; and, if all of the items have high covariances, then αα will approach 1 as the number of items in the scale approaches infinity. In other words, the higher the αα coefficient, the more the items have shared covariance and probably measure the same underlying concept.

5. Dimension Name/ Characteristics
Factor Analysis and the Factors
The eigenvalue >1, Varimax Rotation
Getting 6 factors (components) and cumulative of extraction sums of square loading is 66.42%.
Variables
Dimension Name/ Characteristics
Content (Item No.)
G1 (Renewable)
The perception of renewable energy
27, 28, 29, 30, 37, 38, 39, 40, 41
G2 (Ecological)
Perception of the risk of ecological environment
10, 13, 14, 15, 16, 17, 26
G3 (Nuclear)
The risk of nuclear energy
6, 19, 20, 21, 23, 24, 34, 35,
G4 (Consumption)
The behavior of electricity expending
7, 8, 9, 11, 12
G5 (Trust)
Public trust to government
31, 32, 33
G6 (Understanding)
Understanding to energy issues
3, 4, 5

6. Conclusion (0.000) (0.000) (0.004) (0.341) (0.008)
G4 = G G G G G6
(0.000) (0.000) (0.004) (0.341) (0.008)
(G5, not significant ; G3 & G6 small influence)
G4: The behavior of electricity expending
(Knowing how to charge the electricity bill and will try to save the bill)
G1: The perception of renewable energy
(Knowing more in renewable energy and interested in the issue of renewable energy)
G2: Perception of the risk of ecological environment
(Knowing the risk caused by the climate change)
G3: The risk of nuclear energy
(thinking the nuclear energy is safe)
G5: Public trust to government (not significant)
G6: Understanding to energy issues
(some issue, such like the price of electricity, constraint of resources…)