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I. ................................................................................................................. 3
II. .............................................................................. 3
...................................................................................................... 14
......................................................................................................... 18
................................................................................... 19
AHP ..................................................................................... 20
.......................................................... 38
......................................................................... 47
3
I .
1. -
2.
- -
3.
1. 4.
I I . 1.
2.
3.
,
1 Merriam-Webster
4
. 4.
= =1 ,
i- - i-
= 1=1
= -
= - ,
= 1| |
{ ; } -
min, max, opt
-
1)
5.
5
the Analytic Hierarchy Process, AHP
AHP
.
PEST- 2
:
(P) (E) (S) (T)
P)
2 Williams, Teresa The Business Approach to Training. Vermont: Gower Publishing Ltd. 1997
6
1)
Institutions - The Global Competitiveness Report 2009 Economic F
3.
2)
3)
-
4. -
,
) 4)
(E)
, .
1)
2)
3 http://www.transparency.org.ru/
4 http://www.oecd.org
7
3)
.
5.
4)
(S)
: 1)
.
2)
(Global Entrepreneurship Monitor, GEM) (T)
-
1)
5
Global Entrepreneurship Monitor, GEM)
www.hse.ru
8
Infrastructure - The Global Competitiveness
Report, World Economic Forum. 2)
Forbes.
PEST- .
,
AHP
n-
11 1
1
n
1
1
n 1
9
= 1 , i, j
i-‐ j-
n(n-‐1)/2 .
6
eigenvector)
= ,
A
eigenvalue).
6 Saaty, Thomas L. A Scaling Method for Priorities in Hierarchical Structures. // Journal of Mathematical Psychology, issue 15, volume 3. 1977
10
( ),
I - n*n ,
( )
= = 0
n
eigenvalues).
n
n
n n
==1
=1 = 1
-
11
n
A-‐ - A (eigenvector).
= complex)
(real) (imaginary) +
1 2 = 2 1 = 0
Hermitian
MathCad, MathLab, Stata - R,
12
nosym<-read.table("nosym.txt", header=TRUE)
lds<-( as.real( (eigen(nosym, symmetric=FALSE)
$vectors)[,1]) )/
sum ( as.real( (eigen(nosym, symmetric=FALSE)
$vectors)[,1]) )
lambda<-as.real(eigen(nosym,
symmetric=FALSE)$values[1])
nosym
lds
lambda
nosym
lds
lambda
1) 2)
3) 4) 5)
Compatibility Index)
=1
13
CI
RCI Random CI)
(CI/RCI) Consistency Ratio CR)
=
CR . CR=0CR=1 CI=RCI
CR>20
AHP)
AHP
14
P -
1 - -- -
- +
2
- - - -2.1- - -
- +
3 - - - - 5-
- +
4 - - - - -
- +
5 - 2- --
- -
6 -
7
--- -
- +
8
- - --
- +
9 (%)
- -
15
10 -- - -
- -
11
-
12
-
13
-
14
--
- -- - -
-
- - -
- -
15 --
- +
16 -
-- - -
-
- -
16 -
- --
2,4-
- -
17 +
E -
18
-
opt
16
opt opt
opt
opt opt
opt
opt opt
19
- opt
20 7- -
- +
21 - -
22 +
23 +
24 +
25 +
S -
26
+
27 + 28 +
29
- +
30 - +
31 - +
17
32 +
T -
33 +
34 - -- -
- -
35 +
36
-- -
- -
37
-
38
+
39 - - -
40 - -
41 -
- - 4- - -
- -
18
-‐
-‐
-‐
-‐
19
1
3
5
7
9
2,4,6,8
20
A HP
22
2.
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.
1 2 3 4
. . .
. 1
.
1
1
.
1
1.
1 2 3 4
23
1
1
1
1
2.
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.
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1
1
-‐
1
3.
1 2
24
.
. 1
1
4.
1 2
1
1
7
1.
1
- - - -
-
7
25
2
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-
3 :
1- 2- - - -
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4
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-
1 2 3 4
1 1
2
1
3
1
4
1
2.
1 - - -
-
-
2
3 --
- -
-
1 2 3
26
1 1
2
1
3
1
3.
1 .
- -- -
-
2
-
3
- -- -
-
4
5
6
1 2 3 4 5 6
1 1
2
1
27
3
1
4
1
5
1
6
1
4.
1 --
- - - --
--
2- -
-
2 .
- -
-
3 -
- -- - -
-
4 -
- -- -
-
5
1 2 3 4 5
1 1
28
2
1
3
1
4
1
5
1
2
1.
1 -
*
2 *
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1 2
1 1
2
1
2.
1 - -
-
2 -
29
3
1 2 3
1 1
2
1
3
1
3.
1 2
1 2
1 1
2
1
4.
3
1.
30
1
2 3
-‐
1 2 3
1 1
2
1
3
1
2.
1
-
2
-
3
-
4
4
1.
1
2 - - -
-
-
3
31
4 -- -
-
5
6
1 2 3 4 5 6
1 1
2
1
3
1
4
1
5
1
6
1
2.
1 - -
2 -
3
-- - -
5- -
-
32
1 2 3
1 1
2
1
3
1
33
1. ?
1
2
-‐
1 2
1 1
2
1
34
2.
?
1)
1
2
3
4
1 2 3 4
35
1 1
2
1
3
1
4
1
3. ?
1
2
-‐
1 2
1 1
36
2
1
4. ?
1
2 ?
3
1 2 3
1 1
2
1
37
3
1
5. ?
1
2 ?
1 2
1 1
2
1
38
5
40
2.
___________________(
1)
2) 3) 4) 5)
6) 7)
8) 9) 10) 11)
12)
13) 14)
15)
16)
17)
41
3.
-
1
2
3
4
5
42
6
7
8
-
8
:
-
8
43
9
10 ?
11
12
_______________________(%)
13
9
- 9
44
14
15
16
17 ?
7-
1-
45
18
_______________________
19 -
)?
-
20 ____________%
-
46
7-
1-
21 ____________________
-
22
47
49
2.
-
1
2
3
4
-
50
7-
4-
1-
5 - ______________