Analysis on Fuzzy Comprehensive Evaluation Model of Overseas
Investment Risk of Chinese Enterprises in “One Belt and One Road”
based on Eviews Software
Jialong Mi
Business School of Hunan International Economics University, Changsha City, China
Keywords: Overseas Investment, Risk Monitoring System, Fuzzy Comprehensive Evaluation Model, One Belt and One
Road.
Abstract: This paper explains the present situation and the types of operational risk of Chinese foreign investment in
“One Belt and One Road (OBOR)”. Then, the operational risk monitoring system of Chinese enterprises'
overseas investment in “One Belt and One Road” is constructed. On this basis, it uses the fuzzy comprehensive
evaluation model to analyse Chinese enterprises' overseas investment risk in “One Belt and One Road”.
Furthermore, Eviews software is used to calculate the result of Chinese enterprises' overseas investment risk
in “One Belt and One Road”. Finally, it analyzes and summarizes the risks of Chinese enterprises' overseas
investment in “One Belt and One Road”.
1 INTRODUCTION
Since China proposed the “one belt and one road”
initiative in 2013, Chinese enterprises' overseas
investment in “one belt and one road” has increased
year by year. At present, the net stock of overseas
investment in “one belt and one road” by Chinese
enterprises has reached 110 billion US dollars,
including overseas investment from 65 countries.
More than 27,000 Chinese enterprises have
participated in overseas investment (Fu, 2020).
Overseas investment in “one belt and one road” needs
a complicated process, and the risks can not be
estimated. Overseas investment has become one of the
three major forces driving China's economy. Only by
giving full play to the role of overseas investment can
China's economy achieve steady development.
Therefore, we should pay more attention to how to
reduce investment risks in “one belt and one road”
(Callahan,
2017).
2 INDENTIFICATION OF
OPERATIONAL RISK
INFORMATION
There are many operational risks in Chinese
enterprises' overseas investment in “one belt and one
road” (Chen, 2018). The purpose of this paper is to
classify these risks and form an appropriate
combination set. In essence, overseas investment in
“one belt and one road” by Chinese enterprises can be
divided into five types, each of which contains
corresponding sub-factors. In a word, the risk types
include: political risk, operational risk, legal risk,
cultural difference risk, and specific industry risk
(Harjoto, 2018).
26
Mi, J.
Analysis on Fuzzy Comprehensive Evaluation Model of Overseas Investment Risk of Chinese Enterprises in â
˘
AIJOne Belt and One Roadâ
˘
A
˙
I based on Eviews Software.
DOI: 10.5220/0011720300003607
In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 26-30
ISBN: 978-989-758-620-0
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
3 CONSTRUCTION OF
MONITORING SYSTEM FOR
OPERATIONAL RISK OF
CHINESE ENTERPRISE
OVERSEAS INVESTMENT IN
“ONE BELT AND ONE ROAD”
3.1 Thought for Constructing
Monitoring System for Operational
Risk of Chinese Enterprise
Overseas Investment in “One Belt
and One Road”
It is a very complicated process for enterprise to do
overseas investment in “one belt and one road”, the
risk factors are various and uncertain, which makes
evaluation of investment risk difficult to be measured
by one or several indicators. The paper has adopted the
analytic hierarchy process combined with fuzzy
comprehensive evaluation to comprehensively
appraise risks from overseas investment in “one belt
and one road” of Chinese enterprise through the build-
up of a set of relatively objective indicator system
(Mohammed, 2016). The basic thought for appraising
Chinese enterprise overseas operational risk is as
follows:
1) Evaluating the fundamental factors constructed
against Chinese enterprise overseas investment risks
as well we the correlation among the factors;
2) The selection of appraisal indicators follows
comprehensive and objective principle as well as the
feature of comprehensive evaluation;
3) Result from the evaluation should not only sort
the evaluation objects, but also analyse the evaluation
result, through which the reason influencing the
overseas investment risk should be found out for the
purpose of providing Chinese enterprises with ideas to
improve and enhance their ability to manage overseas
investment risks in “one belt and one road”.
3.2 Principles for Constructing
Monitoring System for Operational
Risk of Chinese Enterprise
Overseas Investment in “One Belt
and One Road”
Constructing a scientific, objective and practical risk
evaluation monitoring system can effectively control
and avoid the possible risks confronted by
investments, so as to smoothly implement the
investment projects and realize maximum profit in
“one belt and one road” (Samet, 2017). The principles
that require Chinese enterprise to follow in
establishing investment risk monitoring system
include: 1) monitoring system should follow
comprehensive and scientific principles; 2)
monitoring system should be logical and stratified; 3)
monitoring system should be operational; 4) the
difference principle of indicator system.
3.3 Construction of Monitoring System
for Operational Risk of Chinese
Enterprise Overseas Investment in
“One Belt and One Road”
According to the thoughts and principles for selecting
the above indicators, in combination with the
categories of Chinese enterprise overseas investment
risks in “one belt and one road”, the monitoring
system for operational risk of Chinese enterprise
overseas investment in “one belt and one road” can be
set up from three layers: target layer, standard layer
and indicator layer (Bai, 2010).
4 COM PARISON AND
SELECTION OF CHINESE
ENTERPRISE OVERSEAS
INVESTMENT RISK
EVALUATION MODEL IN
“ONE BELT AND ONE ROAD”
4.1 Determination of Chinese
Enterprise Overseas Investment
Risk Evaluation Indicator System
According to the monitoring system features, the
analytic hierarchy process is adopted to determine the
weight of indicator system. The analytic hierarchy
process divides the complicated system into a few
groups of factors, which form gradual hierarchy after
being grouped according to dominant and subordinate
relationship. By comparing each two factors, relative
importance is determined and the relative importance
of the target program is determined for program to
choose. The whole process shows human analysis,
judgement and realizes the qualitative and quantitative
combination. The steps for determining the weight of
analytic hierarchy process are as follows (Zhang,
2010).
Analysis on Fuzzy Comprehensive Evaluation Model of Overseas Investment Risk of Chinese Enterprises in â
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AIJOne Belt and One
Roadâ
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A
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I based on Eviews Software
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4.2 Define the Problems to be Analysed
Before analysing problems, a clear idea of the
problems should be gained, including the scope
related to the problems and factors involved,
correlation and subordinated relation between the
factors should be determined, the final issue to be
solved should be extremely defined at the beginning.
4.3 Set up of Hierarchical Structure for
Problem Research
To set up a good hierarchical structure is the basis of
calculation and analysis, for constructing a
hierarchical structure to study the problems, we must
first analyse various factors in the system, form
different hierarchical relations by taking their possible
dominant and subordinated relations into
consideration. The subfactors are subject to the
domination of the superior levels, hence a hierarchical
structure is formed. The top of the layer is the target
structure, there is only one factor, which is the whole
decision objective. As a standard middle layer, that is
the conditional factors for consideration. The bottom
of the layer is the decision layer, where decision
makers can select the appropriate program through the
previous analysis.
4.4 Chinese Enterprise Overseas
Investment Risk Evaluation Model
in “One Belt and One Road”
Number from the matrix is used to obtain the accurate
weight of the indicators, the steps are as follows:
First, calculation of multiplying the factors on each
row of the judgement matrix
1
(, 1,2, , )
n
iij
j
M
aij n
=
==
∏
Second, calculate the n root of
i
M
n
i
i
WM=
Third, normalization calculation of vector
12
(, ,, )
T
n
WWW W=
, that is:
1
/(1,2,,)
n
ij i
i
ww w i n
=
==
After the normalization calculation,
12
(, ,, )
T
n
WWW W=
is the weight vector
obtained.
Fourth, the formula for obtaining biggest
characteristics root of the judgement matrix:
max
1
()
n
j
i
j
A
W
nW
λ
=
=
Where
()
j
AW
refers to the j factor of
A
W
vector.
Fifth, consistency test and random test of the
judgement matrix.
Judgement matrix constructed cannot be the
matrix with absolute consistency, its consistency
indicator can affirm the solution of practical problems
in a certain range, as long as the consistency meets the
requirement, some problems can be avoided, after
obtain the value of
max
λ
, consistency and random
tests should be conducted, here CI (measurement
deviation consistency index) is introduced, RI
(average consistency indicator), CR (random
consistency rate).
max
1
n
CI
n
λ
−
=
−
RI (average consistency indicator), as shown in
Table 1.
When the random consistency rate
0.10
CI
CR
RI
=≤
, judgement matrix has
satisfactory consistency, then the value obtained is
reasonable, otherwise more effort should be made to
adjust the judgement matrix until the satisfactory
consistency result is obtained.
Sixth, combination weight calculation and
consistency test If the indicator system is the n-layer
structure, then the combination weight of the n th
(each factor of the layer) against the target layer is:
() ( 1) (3) 2nnn
WW W
ωω
−
=• •
Where,
n
ω
is the matrix formed by line vector of
each factor in n th layer.
After the above calculation, in order to determine
whether the whole layer is conformed with the
consistency requirement, the analytic hierarchy
process requires combination consistency test, the
method is as follows: assume consistency of the nth
layer are
() ()
1
,,
nn
i
CI CI
, random disposable
indicator are
() ()
1
,,
nn
i
R
IRI
(i is the number of
factors of n-1layer).
Table 1: RI Value of 1-10 Order Judgement Matrix.
Order 1 2 3 4 5 6 7 8 9 10
RI 0.0 0.0 0.6 0.9 1.1 1.2 1.3 1.4 1.5 1.5
ICPDI 2022 - International Conference on Public Management, Digital Economy and Internet Technology
28
() () () ( 1)
1
() () () ( 1)
1
()
() ( 1)
()
,,
,,
,3,4,
nn nn
i
nn nn
i
n
nn
n
CI CI CI
RI RI RI
CI
CR CR n
R
I
ω
ω
−
−
−

=


=

=+ =
When the combination consistency rate
()
0.1
n
CR <
, the whole structure satisfies the
consistency needs, and passes the consistency
pressure-relief. Then corresponding appropriate
program can be chosen according to the combination
weight sequence, which provides basis for decision
making.
5 FUZZY COMPREHENSIVE
EVALUATION MODEL IN
“ONE BELT AND ONE ROAD”
5.1 Fundamental of Fuzzy
Comprehensive Evaluation Model
in “One Belt and One Road”
In the process of evaluating overseas investment risk
in “one belt and one road”, there are a large number of
monitoring indicators, the analytic hierarchy process
is used for layering, them fuzzy comprehensive
evaluation is conducted against the subfactors,
systematically and comprehensively evaluate the risks
in overseas investment, this is the process of
multistage fuzzy comprehensive evaluation, the
model established is called fuzzy comprehensive
evaluation model.
5.2 Steps for Constructing Fuzzy
Comprehensive Evaluation Model
in “One Belt and One Road”
1) Establish the Fuzzy Comprehensive Evaluation
Model in “one belt and one road.and bottom of
columns.
a) Establishment of universe of each factor
theory of the evaluation object, set as U. That is, from
what angle and what factor to evaluate the risk object,
this step has established the evaluation factor system.
12
(, ,, )
n
UUU U=
b) Set up universe of review rating V
12
(, , , )
m
VVV V=
Determine a process of the universe, that is a fuzzy
evaluation vector can be obtained after the fuzzy
comprehensive evaluation, each factor evaluated can
obtain the value of the degree of subordination from
the review registration, can be presented by the fuzzy
vector, this step reflects the fuzzy characteristic of the
evaluation. Universe of review rating are set into such
five orders as super low, relatively low, middle,
relatively high and super high.
c) Evaluation of the single factor on the second
layer, establish fuzzy relation matrix R
11 1
1
m
nnm
R
R
R
RR


=




Where
ij
r
refers to the subordination between
i
U
in factor U and
j
V
in order V, i.e,
i
U
is rated the
subordination of
j
V
.
ij
r
is the single factor evaluation
of ith factor against the evaluation object, fuzzy
comprehensive evaluation is based on the single
factors.
2) Set up evaluation weight vector A
Adopt fuzzy method to endow every factor with
different weights, the weight evaluation combination
obtained is a fuzzy subset in factor theory universe U:
{
}
123
,,,,
n
aa a a=
, and
1
1
n
i
i
a
=
=
.
3) Select composition operator for
comprehensive evaluation calculation
Formula of the basic model of fuzzy
comprehensive evaluation:
BAR=
Where “
” means the composition operator as in
{
}
123
,,, ,
n
B
bb b b=
, it is a fuzzy subset in
review set. If the fuzzy comprehensive evaluation
result
1
1
n
i
i
b
=
≠
, appropriate ways should be used for
normalization.
5.3 Steps for Constructing Multistage
Fuzzy Comprehensive Evaluation
Model in “One Belt and One Road”
1) Factors sets U are divided into several subsets. As
in
12
(, ,, )
p
UUU U=
, the ith subset
12
( , ,, ),( 1,2,,)
ii ik
UUU U i p==
, then
1
p
i
ki n
=
=
2) For each
i
U
, respective comprehensive
evaluation is conducted. And the factor weight
distribution is
i
A
,
i
U
fuzzy evaluation matrix is
i
R
,
then
12
(, , , ),( 1,2, ,)
iii ii im
BAR bb b i p== =
Analysis on Fuzzy Comprehensive Evaluation Model of Overseas Investment Risk of Chinese Enterprises in â
˘
AIJOne Belt and One
Roadâ
˘
A
˙
I based on Eviews Software
29
3) Take the comprehensive evaluation B.
i
B
of
i
U
in
12
(, ,, )
p
UUU U=
as p single factor
evaluation in U, the total fuzzy comprehensive
evaluation matrix is obtained:
1
2
()
ij pm
n
B
B
Rb
B



==



After a few times of fuzzy synthetic computing,
formula for grade-two fuzzy comprehensive
evaluation results is:
B
AR=
Chinese enterprises face various risks when
investing overseas in “one belt and one road”.
Through the above model, after analyzing the risks
with Eviews software, the risk probability is between
0.3 and 0.5, and the risk level belongs to the middle
and low range. We also find that operational risk,
political risk, legal risk and regulatory risk have a high
probability of occurrence. In addition, the probability
of occurrence of risk from cultural differences and
specific industries also needs the same attention.
Then, we can put forward corresponding strategies for
individual risk, thus providing countermeasures and
basis for the decision makers. In this way, Chinese
enterprises can avoid risks and achieve better
development by investing in “one belt and one road”.
ACKNOWLEDGMENT
My sincere appreciation goes to the
teachers and students from Hunan International
Economics University, who participated in this study
with great cooperation. This paper was carried out by
the Hunan International Economics University
Project Research on statistics and Countermeasures
of Chinese enterprises' investment risks to the
countries along the belt and road (subject number
2018K03).
REFERENCES
Bai Yuan, “Chinese Enterprise Direct Foreign Investment:
Risks from Opportunities”, International Economic
Cooperation, 2010,17(8): pp.11-15.
Callahan, C., & Soileau, J, “Does enterprise risk
management enhance operating performance”?
Advances in Accounting, 2017,37(2), pp.122- 139.
Chen, R. C. Y., Hung, S.-W., & Lee, C.-H, “Corporate social
responsibility and idiosyncratic firm risk in the different
market states”, Corporate Social Responsibility and
Environmental Management, 2018, 25(4), pp.642-658.
Fu, X., Buckley, P. J., & Fu, X. M, “The growth impact of
Chinese direct investment on host developing
countries”, International Business Review, vol. 2020,
29(2), pp. 10-16.
Harjoto, M., & Laksmana, “The impact of corporate social
responsibility on risk taking and firm value”, Journal of
Business Ethics, 2018,151(2), pp.353-373.
Mohammed, H. K., & Knapkova, A, “The impact of total
risk management on company's performance”, Procedia-
Social and Behavioral Sciences, 2016(220), pp.271-277.
Samet, M., & Jarboui, A, “How does corporate social
responsiblity contribute to investment efficiency”?
Journal of Multinational Financial Management., 2017,
40(2), pp.33-46.
Zhang Hao, “Analysis of Risk Prevention in Large-scale
Enterprise Direct Foreign Investment”, Northern China
Finance, 2010,21(5): pp.57-59.
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