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Research on Risk Evaluation in Supply Chain ... - ResearchGate

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30 JOURNAL OF COMPUTERS, VOL. 3, NO. 10, OCTOBER 2008<br />

disrupti<strong>on</strong> of the whole supply cha<strong>in</strong>. In a geographical<br />

area where natural disasters are comm<strong>on</strong>, most of<br />

companies c<strong>on</strong>fessed that if a natural disaster occurred<br />

they probably can not ma<strong>in</strong>ta<strong>in</strong> bus<strong>in</strong>ess operati<strong>on</strong>s and<br />

supply obligati<strong>on</strong>s.<br />

Cooperative risk(C 6 ): Cooperative risk means the loss<br />

result from the cooperati<strong>on</strong> breakdown or changes am<strong>on</strong>g<br />

the participants <strong>in</strong> the supply cha<strong>in</strong>. This may lead to bad<br />

results, such as supply cha<strong>in</strong> disrupti<strong>on</strong> or failure. And<br />

the distrust between the copartners <strong>in</strong> the supply cha<strong>in</strong> is<br />

supported to be the most important factor to br<strong>in</strong>g about<br />

such results.<br />

Management decisi<strong>on</strong> risk(C 7 ): As the bus<strong>in</strong>ess world<br />

becomes more complex, the decisi<strong>on</strong> envir<strong>on</strong>ment turn to<br />

be vague and uncerta<strong>in</strong>. So to make a right decisi<strong>on</strong> more<br />

depend <strong>on</strong> the understand<strong>in</strong>g of decisi<strong>on</strong> <strong>in</strong>formati<strong>on</strong> and<br />

the decisi<strong>on</strong> experience <strong>in</strong> the same circumstance. And<br />

for those who have a bad sense and are <strong>in</strong>experienced,<br />

this would be a missi<strong>on</strong> impossible.<br />

Informati<strong>on</strong> shar<strong>in</strong>g risk(C 8 ): The central purpose of<br />

<strong>in</strong>formati<strong>on</strong> shar<strong>in</strong>g is to assist <strong>in</strong> m<strong>in</strong>imiz<strong>in</strong>g the risk of<br />

harm to supply cha<strong>in</strong>. But the fact is <strong>in</strong>formati<strong>on</strong> shar<strong>in</strong>g<br />

accompanies greater risk. Sensitive <strong>in</strong>formati<strong>on</strong> revealed<br />

might result <strong>in</strong> loss of an advantage or level of security<br />

and may lead to the disrupti<strong>on</strong> of supply cha<strong>in</strong>. So to be<br />

clear with what <strong>in</strong>formati<strong>on</strong> can be shared and what can<br />

not will help the companies ma<strong>in</strong>ta<strong>in</strong> an efficient but<br />

secure supply cha<strong>in</strong>.<br />

Operati<strong>on</strong> schedule risk(C 9 ): Operati<strong>on</strong> schedule risk<br />

is the danger of loss <strong>in</strong> fail<strong>in</strong>g to meet schedule plans.<br />

S<strong>in</strong>ce uncerta<strong>in</strong>ly exists <strong>in</strong> every schedule. So it is<br />

impossible to predict, with complete c<strong>on</strong>fidence, the<br />

length of time necessary to produce the product, to<br />

deliver the product etc. And Schedule delay often results<br />

<strong>in</strong> loss of revenue, costs <strong>in</strong>creas<strong>in</strong>g and reputati<strong>on</strong><br />

damage.<br />

F<strong>in</strong>ancial risk(C 10 ): F<strong>in</strong>ancial risk is normally any risk<br />

associated with any form of f<strong>in</strong>anc<strong>in</strong>g. Fac<strong>in</strong>g f<strong>in</strong>ancial<br />

risk, the company <strong>in</strong> today’s bus<strong>in</strong>ess world need take<br />

TABLE I.<br />

INDICATOR SYSTEM FOR SUPPLY CHAIN RISK EVALUATION<br />

<strong>Risk</strong> category<br />

External risk<br />

Internal risk<br />

Political risk(C 1 )<br />

Ec<strong>on</strong>omic risk(C 2 )<br />

Technology risk(C 3 )<br />

Market risk(C 4 )<br />

Nature hazard(C 5 )<br />

Cooperative risk(C 6 )<br />

Criteria<br />

Management decisi<strong>on</strong> risk(C 7 )<br />

Informati<strong>on</strong> shar<strong>in</strong>g risk(C 8 )<br />

Operati<strong>on</strong> schedule risk(C 9 )<br />

F<strong>in</strong>ancial risk(C 10 )<br />

Human resource risk(C 11 )<br />

acti<strong>on</strong>s to mitigate the risk and create ec<strong>on</strong>omic value by<br />

us<strong>in</strong>g f<strong>in</strong>ancial <strong>in</strong>struments to manage exposure to risk.<br />

Human resource risk(C 11 ): Human resource risks are<br />

events that prevent employees from fulfill<strong>in</strong>g their<br />

resp<strong>on</strong>sibilities and thus keep the supply cha<strong>in</strong> from<br />

operat<strong>in</strong>g at full efficiency. Human resource risks<br />

<strong>in</strong>cludes death, disability, divorce, employee turnover etc.<br />

The ideal way to deal with human resource risk is to keep<br />

a c<strong>on</strong>t<strong>in</strong>gency plan <strong>in</strong> case of the available of key<br />

pers<strong>on</strong>nel.<br />

III. THE PROPOSED MODEL<br />

Suppose D is the decisi<strong>on</strong> matrix, A 1 , A 2 , … , A m are<br />

the alternatives to be chosen, C 1 , C 2 , …, C n denote the<br />

evaluati<strong>on</strong> criteria, x ij represents the rat<strong>in</strong>g of alternative<br />

A i with respect to criteri<strong>on</strong> C j .<br />

So a typical fuzzy multi-criteria decisi<strong>on</strong>-mak<strong>in</strong>g<br />

problem can be expressed <strong>in</strong> matrix format as<br />

C1<br />

C2<br />

L Cn<br />

A1<br />

⎡ x11<br />

x12<br />

L x1n<br />

⎤<br />

⎢<br />

⎥<br />

D = A2<br />

⎢<br />

x21<br />

x22<br />

L x2n<br />

⎥ ,<br />

M ⎢ M M M M ⎥<br />

⎢<br />

⎥<br />

Am<br />

⎣xm1<br />

xm2<br />

L xmn<br />

⎦<br />

where, i =1, 2, …, m, j=1, 2, …, n, x ij is denoted by<br />

l<strong>in</strong>guistic term.<br />

T<br />

Let ϖ = w , w , ) be weight vector, w j be<br />

(<br />

1 2<br />

Lw n<br />

n<br />

∑ i = 1<br />

the weight of criteri<strong>on</strong> C j , and w = 1 .<br />

Ow<strong>in</strong>g to the complexity of evaluati<strong>on</strong> object, the<br />

evaluators usually just give partial weight <strong>in</strong>formati<strong>on</strong>.<br />

And there are 6 forms of partial weight <strong>in</strong>formati<strong>on</strong><br />

usually given by evaluators:<br />

wi ≥ w j<br />

,<br />

wi<br />

≥ ∂ijw<br />

j<br />

,<br />

wi − w j<br />

≥ βij<br />

,<br />

γ<br />

j<br />

≤ w<br />

j<br />

≤ η<br />

j<br />

,<br />

σ<br />

ij<br />

≤ wi<br />

/ w<br />

j<br />

≤ ζ<br />

ij<br />

,<br />

w + w ≤ 2w<br />

( i ≠ j ≠ k)<br />

,<br />

where<br />

ij<br />

i<br />

j<br />

j<br />

j<br />

∂ β , γ , η , σ , ζ are n<strong>on</strong>negative<br />

,<br />

ij<br />

c<strong>on</strong>stant numbers. For dem<strong>on</strong>strat<strong>in</strong>g the steps of the<br />

method, let Q be the set of above 6 forms.<br />

A. Normalize the Decisi<strong>on</strong> Matrix<br />

x ij is represented by l<strong>in</strong>guistic term, and x<br />

ij<br />

∈ S , S =<br />

{S1=EL, S2=VL, S3=L, S4=M, S5=H, S6=VH, S7=EH}.<br />

The exact mean<strong>in</strong>g of the elements <strong>in</strong> S is given <strong>in</strong><br />

Table II.<br />

Generally criteria can be classified <strong>in</strong>to two types:<br />

benefit criteria and cost criteria.<br />

For benefit criteria, the normalized formula is:<br />

ij<br />

ij<br />

k<br />

j<br />

© 2008 ACADEMY PUBLISHER

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