Fuzzy Decision Process in Parental School Choice - Innovative Management in Information and Production - page 212

4 Empirical Analysis

4.1 Fuzzy Relative Weight of Educational Quality: Calculation

of Membership Grade of Expert

We establish fuzzy relative weight of educational quality from the membership
grade of educational experts. We get the fuzzy weight from fuzzy data as follows:

FW Teacher = 0 / very low + 0 / low + 0 / medium + 0 . 31 / high + 0 . 75 / very high

FW Administration = 0 / very low + 0 / low + 0 . 31 / medium + 0 . 30 / high + 0 . 40 / very high

FW Environment = 0 / very low + 0 / low + 0 . 18 / medium + 0 . 41 / high + 0 . 43 / very high

FW Curriculum = 0 / very low + 0 / low + 0 . 01 / medium + 0 . 40 / high + 0 . 65 / very high

We give the value of utility sequence as very low = 1, low = 2, medium = 3,

high 5. The multiplier of membership and value of utility

sequence is the fuzzy weight of every aspect. Then we calculate the fuzzy relative
weight, as shown in Table 3 .
The decreasing sequence of fuzzy relative weight is FRW Teacher =

= 4, and very high =

0 . 273,

FRW Curriculum = 0 . 267, FRW Environment = 0 . 235 , and FRW Administration = 0 . 226. The

difference of FRW of each aspect is not obvious.
The index of educational quality is defined as follows:

Index Educational quality = 0 . 273 × W Teacher + 0 . 226 × W Administration

+ 0 . 235 × W Environment + 0 . 267 × W Curriculum

Tabl e 3 Fuzzy relative weight of experts' membership of educational quality

Utility sequence

Fuzzy
weight

Fuzzy relative
weight Aspect Very low Low Midum High Very high

Teacher 0 0 0 0.31 0.75 5 0.273

Administration 0 0 0.31 0.30 0.40 4.14 0.226

Environment 0 0 0.18 0.41 0.43 4.3 0.235

Curriculum 0 0 0.01 0.40 0.65 4.89 0.267