American Journal of Industrial and Business Management, 2013, 3, 382-388
http://dx.doi.org/10.4236/ajibm.2013.34045 Published Online August 2013 (http://www.scirp.org/journal/ajibm)
Analysis on Influencing Elements of Enterprise Logistics
Risk Early Warning: Based on Manufacturing Industries
in Beijing Area*
Yongsheng Liu, Rong Yu
School of Business, Beijing Wuzi University, Beijing, China.
Received May 26th, 2013; revised June 26th, 2013; accepted July 16th, 2013
Copyright © 2013 Yongsheng Liu, Rong Yu. This is an open access article distributed under the Creative Commons Attribution Li-
cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Enterprise logistics risk early warning is an essential part of enterprise logistics risk management, which has been in-
creasingly drawing the attentions of both practical and academic world. However, enterprise logistics risk early warning
hasn’t been radically put into practice yet. Therefore, the factors hinder the proceeding of enterprise logistics risk early
warning become the key to starting the engine of enterprise logistics risk early warning. In this paper, review of re-
searches on enterprise logistics risk early warning is provided, a questionnaire has been designed according to both ex-
terior and internal factors influencing enterprise logistics risk early warning and a survey on manufacturing industries in
Beijing area has been carried out, logistics risk early warning status and influencing elements have been analyzed based
on previous survey and advices proposed are concluded to provide valuable references.
Keywords: Enterprise Logistics; Risk Early Warning; Influencing Elements
1. Preface
In China, enterprise logistics risk has not gained suffi-
cient watch due to the ignorance of perception of risk
among corporate management and inability of risk con-
trol, which contributes to the outbreak of enterprise risk
accidents and increases that probability. It’s proved true
that effectiveness achieved by prevention work before
the outbreak of risk accidents outweighs that of post-
accident emergency management, hence the significance
of enterprise logistics risk early warning. Both practical
and academic world should pay attention to related re-
searches.
2. Status Quo of Researches on Enterprise
Logistics Risk Early Warning
So far, related researches on enterprise logistics risk early
warning mainly focus on logistics service risk, outsourc-
ing risk, reverse logistics and enterprise logistics, but the
empirical researches seldom appear.
Liu (2007) [1] applied fuzzy comprehensive evalua-
tion method to logistics service risk early warning man-
agement, formulating an index system of logistics service
risk early warning and predicting logistics service risk
status in both single early warning mode and compre-
hendsive early warning mode, and provide a set of warn-
ing signals match with logistics service risk classification.
Q. Cheng (2010) [2] analyzed causes of formation of
logistics service operation risk according to the connote-
tion and categories of logistics service operation risk, and
discussed the methodologies, models, substances and
requirements of early warning, also provided an index
system and some strategies of logistics service operation
risk early warning. Y. S. Liu et al. (2010) [3] analyzed
causing factors of risk during supply chain logistics ser-
vice of logistics corporations, designing a corporate lo-
gistics risk early warning index system based on balance
score card, and applied fuzzy evaluation—AHP to logis-
tics corporations risk early warning.
L. H. Liu (2005) [4] conducted a preliminary design of
logistics outsourcing, integrating fuzzy comprehensive
evaluation method with outsourcing risk evaluation. G. B.
Xu (2007) [5] proposed a method of corporate logistics
outsourcing risk early warning based on case reasoning,
*This work is supported by Project supported by the Philosophy and
Social Science Planning of Beijing (Grant No. 11JGB053) and Project
supported by Academic Human Resources Development in Institutions
of Higher Learning under the Jurisdiction of Beijing Municipality
(
PHR
(
IHLB
))
under
(
Grant No. PHR2012
)
.

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
383
applying analogical reasoning method to corporate logis-
tics outsourcing risk early warning. Y. T. Hong et al.
(2008) [6] analyzed corporate logistics outsourcing risk,
and created a corresponding index system.
D. H. Yang et al. (2008) [7] designed an evaluation in-
dex system of reverse logistics risk early warning. W. Y.
Duan (2010) [8] established reverse logistics risk early
warning system, utilizing MATLAB tool kit to build up
corporate reverse logistics risk early warning model and
to prove BP neural network absolutely fit reverse logis-
tics risk early warning model.
M. Q. Zhang et al. (2008) [9] analyzed risk types and
causes of each basic logistics activity, and set up an early
warning index system of activity risk, discussing the op-
eration management mechanism of risk early warning.
Xie et al. (2009) [10] researched into internal logistics
early warning management of middle and small busi-
nesses based on tag card system, through which overall
operation procedures, quality and quantity can be super-
vised in a dynamic way, which can improve the early
warning and control system. Y. S. Liu et al. (2009) [11]
analyzed the concept of corporate risk early warning and
causes and signs of corporate logistics, discussed enter-
prise logistics risk early warning mechanism based on
supply chain management. Cheng et al. (2010) [12] re-
searched in logistics balance early warning of steel in-
dustries ports, discussing methodologies of raw material
inventory early warning, achieving logistics balance and
matching industry port raw material with internal raw
material supplying logistics. L. Ji (2010) [13] applied
forced decision method to China’s corporate logistics
risk level, and fuzzy comprehensive evaluation to post-
risk effectiveness degree, and concluded the correspond-
ing evaluation classification according to the data ac-
quired by on-site researches, offering enterprises bene-
ficial references of logistics risk early warning work.
Above researches mainly utilize normative research
method, discussing logistics risk early warning at the
enterprise level, which contributes little to improve logis-
tics risk early warning. This paper utilized investigation
and statistics analysis to analyze influencing elements of
corporate logistics risk based on previous researching
results, aiming to provide more scientific references to
improvement of enterprise logistics risk early warning.
3. Methodology and Design
3.1. Research Route
Firstly through analyzing references, influencing ele-
ments of enterprise logistics risk early warning are con-
cluded. Then though surveying manufacturing enter-
prises in Beijing area by questionnaires, the perception
status of corporate logistics risk influencing elements of
staffs of each level in manufacturing enterprises are
summed up. At last, SPSS software is used to carry out
quantitative analysis so as to calculate the related sig-
nificance of those influencing elements to enterprise lo-
gistics risk early warning. SPSS software is used to cal-
culate weights of each influencing factor in this research.
3.2. Design of Investigation Content
Based on analysis on references and preliminary investi-
gation, investigation content in questionnaire is divided
into two parts: one is about basic status of enterprise lo-
gistics risk early warning, the other is focusing on influ-
encing elements.
Basic status of enterprise logistics risk early warning
includes: 1) how do objects know about enterprise logis-
tics risk early warning. 2) Whether enterprises surveyed
take any measures of logistics risk early warning. 3)
Whether enterprises surveyed offer staff training on risk
early warning. 4) Relations among goal hit rate of enter-
prises’ logistics risk early warning and degree of percep-
tion of risk early warning of staffs and effectiveness of
risk early warning activities. 5) As for enterprise logis-
tics risk early warning, which of below items should be
solved (multiple choices allowed)?
1) How to identify and evaluate logistics risk.
2) To understand the content of logistics risk early
warning process.
3) How to select proper index of enterprise logistics
risk early warning.
4) To understand the organizing procedure of enter-
prise logistics risk early warning.
5) Others (please explain in detail).
The influencing elements of enterprise logistics risk
early warning are illustrated in Table 1.
Table 1. Influencing elements of enterprise logistics risk
early warning.
External factors Internal factors
Uncertainty of natural
environment Emphasis put by senior executives
Uncertainty of political
environment
Qualification of staffs in risk
management
Uncertainty of legal
environment Logistics management level
Uncertainty of economic
enviroment n
Improvement of logistics risk
management institutions
Advancement of logistics risk
management technology
Logistics development phase

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
384
3.3. Research Object
In this research, Beijing area as a benchmark in the de-
velopment of corporate logistics is selected as research
geographic scale, and the manufacturing corporates are
chosen as research objects, which refer to electronic
manufacturing industry, electro-mechanics manufactur-
ing industry, transportation manufacturing industry and
pharmaceutical manufacturing industry. The researching
investigation requires objects should work in different
departments, including purchasing, production, sales,
logistics and finance, and work in different levels, in-
cluding first-line staff, supervisor, middle manager and
senior executives. Thus an inclusive and convinced result
can be showed.
3.4. Questionnaire Survey and Result Analysis
200 questionnaires have been handed out, 183 of which
have been retrieved. With incomplete 3 deducted, the
final sum of effective retrieved questionnaire is 180, 90%
of hand-out.
1) Description of objects
Based on 180 effective retrieved questionnaires, male
to female ratio is 38.3:61.7. Basic information of objects
is showed in Table 2.
2) Reliability analysis
The Cronbach Alpha coefficient in SPSS software is
used to testify reliability of questionnaires. 10 influenc-
ing elements of enterprise logistics risk early warning are
of acceptable criteria, with the Cronbach Alpha coeffi-
cient of 0.763, higher than 0.7, which manifests that the
questionnaires are well-reliable.
4. Analysis on Basic Status of Enterprise
Logistics Risk Early Warning
After analyzing 180 effective questionnaires, basic status
of enterprise logistics risk early warning of manufactur-
ing corporations in Beijing area is obtained, as shown in
Table 3, from which the followings can be explicitly
concluded.
1) Enterprises have insufficient understanding of lo-
gistics risk early warning. As investigation result shows,
63.33% objects have no or little understanding of enter-
prise logistics risk early warning, with the comparison
that only 8.34% know or pretty know this concept, which
indicates that knowledge of enterprise logistics risk early
warning need to be popularized. 71.67% corporations
surveyed take no measures of enterprise logistics risk
early warning. As for training on risk early warning,
73.89% corporations have no trainings on risk early
warning, let alone enterprise logistics risk early warning.
It can be seen that corporations attach less importance to
logistics risk early warning, which need to be solved.
2) To achieve the goal set by enterprise logistics risk
early warning, rich knowledge of enterprise logistics risk
early warning and beneficial effectiveness of risk early
warning is required. As research indicates, 47.78% ob-
jects think that corporations are not qualified in risk early
warning has (a lot) to do with their knowledge and effec-
tiveness of warning activities, while only 16.11% don’t
think so. Therefore corporations that are intend to
achieve the goals set by enterprise logistics risk early
warning need to improve two things, which one is
strengthening related training, the other is improving the
effectiveness of risk early warning activities.
3) As for knowledge of enterprise logistics risk early
warning, the content of enterprise logistics risk early
warning process and selection of index does really matter.
Seen from research result, 39.44% objects think that un-
derstanding of the content of enterprise logistics risk
early warning process is important, 28.33% think that
selection of risk early warning index should be put on
emphasis, 20.56% think that understanding of organizing
procedure of enterprise logistics risk early warning is
essential, and 20% think that identifying and evaluating
enterprise logistics risk is critical. Besides, a small pro-
portion of objects put inclusive and systematic training
offered to staffs should be improved.
Table 2. Basic information of objects.
Work seniority Less than 1 year 1 - 10 years 11 - 20 years More than 20 years
Objects/sum proportion 15.60% 68.30% 11.10% 5.00%
Position First-line staff First-line manager Middle manager Senior executive
Objects/sum proportion 38.90% 20.60% 33.80% 6.70%
Department Purchasing Production Sales Logistics Finance Others
Objects/sum proportion 3.30% 6.10% 14.40% 6.10% 30.00% 40.10%
Industry Electronic
manufacturing
Electro-mechanic
manufacturing
Transportation
manufacturing
Pharmaceutical
manufacturing Others
Objects/sum proportion 15.60% 15.60% 18.30% 16.10% 34.40%

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
385
Table 3. Basic status of enterprise logistics risk early warning.
Question Choice Sample Percentage
Expert 5 2.78%
Understand it 10 5.56%
Know about it 51 28.33%
Know less about it 65 36.11%
Degree of understanding of enterprise logistics
risk early warning
Do not know 49 27.22%
Yes 42 23.33%
Yes, but not of logistics risk 9 5.00%
Whether corporations take measures of
enterprise logistics risk early warning
No 129 71.67%
Yes. Specially 13 7.22%
Yes. But not specially 34 18.89%
Whether corporations offer trainings on risk
early warning
No 133 73.89%
Significant 31 17.22%
Near significant 55 30.56%
Modest significant 65 36.11%
Insignificant 14 7.78%
Relation between corporation’s hit rate of
logistics risk early warning and richness degree
of knowledge and effectiveness of risk early
warning activities
Not at all 15 8.33%
How to identify and evaluate enterprise logistics
risk 36 20.00%
Understanding of the content of enterprise
logistics risk early warning process 71 39.44%
How to select proper index 51 28.33%
Understanding of organizing procedure of
enterprise logistics risk early warning 37 20.56%
As for enterprise logistics risk early warning,
problems need be solved in terms of mastering
knowledge of risk early warning (multiple
choices allowed)
Others (such as systematic knowledge of
enterprise logistics risk) 3 1.67%
5. Analysis on Influencing Index of
Enterprise Logistics Risk Early Warning
5.1. Analysis on Information of Influencing
Index of Enterprise Logistics Risk Early
Warning
Based on 180 effective questionnaires, categorized by
external and internal influencing elements of enterprise
logistics risk early warning and their effects, basic in-
formation of influencing elements come into being,
shown as Table 4.
Seen from Table 4, although external factors have
different effects on enterprise logistics risk, less objects
don’t think external factors have radical effects, with
22.64% think the effects are slight and 31.66%, signifi-
cant. Mostly, 45.70% objects think the effects are just
mild. More detailed information of each external factor’s
character can be found in Table 4.
Unlike perception of external factors, most objects
consider internal factors have significant effects on en-
terprise logistics risk early warning, with the total of
61.67%, and only 4.81% consider that effects are slight.
Among the rest, 33.52% think that effects are modest.
What’s more, three internal factors including attention
attached by senior executives, logistics management
level and quality of staff are considered that have tre-
mendous effects by respectively 75%, 76.67% and
69.45% objects.
5.2. Factor Analysis of Influencing Elements of
Enterprise Logistics Risk Early Warning
1) Factor analysis of external influencing elements
Factor analysis function in SPSS software is utilized to
conduct quantitative analysis on external influencing
elements of enterprise logistics risk early warning. Re-
sults are showed in Tables 5-7.
Seen from Table 5, KMO value of external influenc-
ing elements is 0.660, higher than 0.5, and Bartlett test
value, sig. = 0.000. The relation among variables is insig-
nificant, hence the factor analysis.
Concluded from Tables 6 and 7, four external influ-
encing elements including natural environment, legal
environment, political environment and economic envi-
ronment can be represented 86.211% by 3 factors

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
386
Table 4. Basic information of influencing elements of enterprise logistics risk early warning.
Question Choice Sample Percentage
Expert 5 2.78%
Understand it 10 5.56%
Know about it 51 28.33%
Know less about it 65 36.11%
Degree of understanding of enterprise logistics
risk early warning
Do not know 49 27.22%
Yes 42 23.33%
Yes, but not of logistics risk 9 5.00%
Whether corporations take measures of
enterprise logistics risk early warning
No 129 71.67%
Yes. Specially 13 7.22%
Yes. But not specially 34 18.89%
Whether corporations offer trainings on risk
early warning
No 133 73.89%
Significant 31 17.22%
Near significant 55 30.56%
Modest significant 65 36.11%
Insignificant 14 7.78%
Relation between corporation’s hit rate of
logistics risk early warning and richness degree
of knowledge and effectiveness of risk early
warning activities
Not at all 15 8.33%
How to identify and evaluate enterprise logistics
risk 36 20.00%
Understanding of the content of enterprise
logistics risk early warning process 71 39.44%
How to select proper index 51 28.33%
Understanding of organizing procedure of
enterprise logistics risk early warning 37 20.56%
As for enterprise logistics risk early warning,
problems need be solved in terms of mastering
knowledge of risk early warning (multiple
choices allowed)
Others (such as systematic knowledge of
enterprise logistics risk) 3 1.67%
Table 5. KMO and Bartlett’s Test on external influencing elements.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.660
Approx. Chi-Square 78.030
df 6 Bartlett’s Test of Sphericity
Sig. 0.000
Table 6. Total variance explained by external influencing elements.
Initial eigenvalue Extracted sum of squares loaded rotated sum of squares loaded
Component Sum Variance %Accumulated % Sum Variance %Accumulated %Sum Variance % Accumulated %
1 1.845 46.128 46.128 1.845 46.128 46.128 1.316 32.905 32.905
2 0.905 22.616 68.745 0.905 22.616 68.745 1.098 27.444 60.349
3 0.699 17.466 86.211 0.699 17.466 86.211 1.034 25.862 86.211
4 0.552 13.789 100.000
Table 7. Matrix of rotated components of external influencing elements.
Component
Influencing elements 1 2 3
Degree of effect of natural environment on risk early warning 0.084 0.964 0.038
Degree of effect of natural environment on risk early warning 0.650 0.405 0.266
Degree of effect of natural environment on risk early warning 0.924 −0.021 0.103
Degree of effect of natural environment on risk early warning 0.182 0.055 0.976

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
387
extracted. First factor represents degree of effect of legal
and political environmental change on enterprise logis-
tics risk early warning. Second, level of effect of uncer-
tainty of natural environment on enterprise logistics risk
early warning. Third, level of effect of uncertainty of
economic environment on enterprise logistics risk early
warning. Therefore, three new factors can be extracted as
political-legal environment factor, natural environment
factor and economic environment factor.
To control external influencing elements, those three
new extracted factors can be used to simplify the sur-
veillance on enterprise logistics operation process. In
practice, to enhance the efficiency of logistics risk early
warning, updated political-legal disciplines and all kinds
of environmental information such as weather forecast
should be considered at all times, also international eco-
nomic environment should be paid attention to grasp the
initiative.
2) Factor analysis on internal influencing elements
Factor analysis function in SPSS software is utilized to
conduct quantitative analysis on internal influencing
elements of enterprise logistics risk early warning. Re-
sults are showed in Tables 8-10.
Seen from Table 8, KMO value of internal influencing
elements is 0.774, higher than 0.7, and Bartlett test value,
sig. = 0.000. The relation among variables is insignificant,
hence the factor analysis.
Concluded from Table 9, internal influencing ele-
ments can be represented 87.780% by 4 factors extracted.
First factor represents quality of logistics risk manage-
ment staffs and logistics management level. Second, im-
provement of logistics risk management institutions and
advancement of logistics risk management technology.
Third represents degree of effect of logistics develop-
ment phase. Forth represents degree of effect of attention
attached by senior executives. Therefore, four new fac-
tors extracted can be defined as logistics management
soft technology, logistics management hard technology,
phase of logistics development and attention attached by
senior executives.
While controlling internal influencing elements, those
four new extracted factors can be used to simplify the
effectiveness of enterprise logistics risk early warning.
As for logistics management soft technology, one of four
new extracted factors, it refers to enhancement of quality
of staffs of enterprise logistics risk management, such as
strengthening trainings. Due to the requirement of logis-
tics management hard technology, enterprise ought to
carry out new R&D or import new logistics software and
Table 8. KMO and Bartlett’s Test on internal influencing
elements.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.774
Approx. Chi-Square 322.435
df 15 Bartlett's Test of Sphericity
Sig. 0.000
Table 9. Total variance explained by internal influencing elements.
Initial eigenvalue Extracted sum of squares loaded rotated sum of squares loaded
Component
Sum Variance % Accumulated% Sum Variance %Accumulated% Sum Variance % Accumulated%
1 2.973 49.551 49.551 2.973 49.551 49.551 1.645 27.412 27.412
2 1.053 17.547 67.099 1.053 17.547 67.099 1.508 25.126 52.538
3 0.656 10.936 78.035 0.656 10.936 78.035 1.065 17.752 70.290
4 0.585 9.746 87.780 0.585 9.746 87.780 1.049 17.490 87.780
5 0.396 6.598 94.378
6 0.337 5.622 100.000
Table 10. Matrix of rotated components of internal influencing elements.
Component
Influencing element 1 2 3 4
Degree of effect of attention attached by senior executives 0.279 0.101 0.097 0.928
Degree of effect of quality of logistics risk management staffs 0.886 0.142 0.128 0.178
Degree of effect of logistics management level 0.817 0.290 0.084 0.207
Degree of effect of improvement of logistics risk management institutions 0.224 0.851 0.068 0.295
Degree of effect of advancement of logistics risk management technology 0.220 0.785 0.365 −0.121
Degree of effect of logistics development phase 0.130 0.227 0.946 0.109

Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning:
Based on Manufacturing Industries in Beijing Area
388
technology equipment to reach its risk management goal.
In terms of phase of logistics development, this factor
links closely with macroscopic environment within a
country, thus any attempt to change should consider in
the prospect of industry as a whole. As for attention at-
tached by senior executives, it refers to enhancement of
senior executives’ understanding of logistics risk early
warning and cementing of their attention attached on it,
which can be realized by dissecting successful cases of
enterprise logistics risk early warning, through which
management can perceive the interests brought by enter-
prise logistics risk early warning.
6. Conclusions and Suggestions
Based on questionnaire survey, this research analyzes
fundamental status and influencing elements of enter-
prise logistics risk early warning of manufacturing in-
dustry in Beijing area. Concluded from above discus-
sions, 1) present status of enterprise logistics risk early
warning of manufacturing industry in Beijing area is not
ideal, because of insufficient attention paid and lack of
professional knowledge, which haven’t drawn much at-
tentions from whatever first line staffs or management; 2)
the external influencing elements of enterprise logistics
risk early warning includes political-legal environment
factor, natural environment factor and economic envi-
ronment factor, and internal influencing elements are
consist of logistics management soft technology, logistics
management hard technology, phase of logistics devel-
opment and attention attached by senior executives. The
effect of internal influencing elements outweighs that of
external counterparts.
Suggestions according to above conclusions are
proposed as follows. 1) To radically shift the adverse
situation of enterprise logistics risk early warning, firstly,
understanding what enterprise logistics risk management
is should be put onto an agenda, which is the basis. And
secondly, trainings on fundamental knowledge and skills
of enterprise logistics risk early warning should be
enforced to make that working process understood by
related staffs, who can identify and evaluate enterprise
logistics risk and early warning indexes; 2) during the
enterprise logistics risk early warning working process,
management’s perception of risk should be enhanced as
well. As for external influencing elements, mends of
related political-legal items should be put on more
emphasis. To internal ones, more importance should be
attached to improvement of logistics management level.
Although manufacturing industry in Beijing area is
selected as research object in this research, to some ex-
tent, the conclusions and suggestions are valuable to the
ractice of enterprise logistics risk early warning of
China’s manufacturing industry, even other industries as
well.
p
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