Analysis on Influencing Elements of Enterprise Logistics Risk Early Warning: Based on Manufacturing Industries in Beijing Area

doi:10.4236/ajibm.2013.34045

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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.

Email: [email protected]om, [email protected]

Received May 26th, 2013; revised June 26th, 2013; accepted July 16th, 2013

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.

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