Appraisal of Logistics Enterprise Competitiveness on the Basis of Fuzzy Analysis Algorithm

Transcription

1 Appaisal of Logistics Entepise Competitiveness on the Basis of Fuzzy Analysis Algoithm Yan Zhao, Fengge Yao, Minming She Habin Univesity of Commece, Habin, Heilongjiang , China, Abstact: In the pape, we set up an appaisal index system of entepise competitiveness integated with entepise eality in China. Whethe a cetain entepise s concete index by using fuzzy analysis algoithm is weak o stong can be deived fom sending out questionnaies to expets fo them to investigate and mak scoes. In the pape a compehensive fuzzy appaisal model on competitiveness is set up. The fundamental model and thinking of two-level compehensive fuzzy appaisal of competitiveness is given by using fuzzy mathematical method on the basis of the index system of competitiveness and the identification of competitiveness. We take a logistics entepise in Heilongjiang (Entepise A) fo empiical analysis. The outcome agees with the eality, which veifies the model s validity. [The Jounal of Ameican Science. 2005;1(2):82-89]. Key wods: fuzzy analysis; logistics entepises; competitiveness 1 Foewod Unde the situation of the tend of pesent economic globalization enhancing day by day and China s enty to WTO, the competition envionment logistics entepises facing has changed a lot in China. Domestic and egional competition tuns into global competition; common cost and scale competition into ability-acquisition and ceativity competition. That equies logistics entepises in China to impove thei sevice quality, exploe management innovations, impove management level and stengthen the competitive powe, to paallel intenational maket and become pat of the wold economy maket. Fuzzy analysis is a kind of semi-quantitative analysis method applying to a multi-facto incident, which is not appopiate to quantitative analysis. It can expess some kind of qualitative desciption and people s judgment in quantitative fom by the way of membeship to detemine the isk level of system in fuzzy figuing. The method can check and educe people s subjective influence to some extent, and thus the analysis gets moe scientific. Appaisal on entepise s competitiveness is a typical compehensive multi-index and multi-level poblem, which is affected by many factos, most of which ae uncetain. The index detemining has qualitative and subjective colo, namely fuzzy. Theefoe it s appopiate to apply fuzzy algoithm theoy to such kind of questions by quantitative desciption. In the pape we adopt multi-level fuzzy analysis algoithm to appaise logistics entepise competitiveness. 2 Setting up Model of Fuzzy Algoithm Appaisal 2.1 Setting up Appaisal Index System To make the appaisal of logistics entepise competitiveness coect and effective, we set up multi-facto appaisal index system by dividing factos, which affect the designing plan of logistics cente into two levels accoding to thei attibutes. The appaisal index is as follows: 82

2 Maket competitiveness Kenel business abilityx 11 Kenel poduct ability X Logistics entepise kenel competitieness Technical competitiveness U 2 Kenel leadeship X 21 New absoption X 22 Kenel applicationx 2 Kenel extending X 24 Stategic management ability X 1 Management competitiveness U Management of human esouce X 2 Entepise cultue X Figue 1. Appaisal Index of Logistics Entepise Competitiveness 2.2 Setting up Appaisal Model We can set up the compehensive model of entepise competitiveness appaisal. The concete pocedue is as follows: (1) Suppose U is facto set U={U 1,U 2,U }, whee U 1 ={X 11,X } U 2 ={X 21,X 22,X 2,X 24 } U ={X 1,X 2,X } V is appaisal set. V={Y 1,Y 2,Y,Y 4 }={stong,semi-stong, aveage,weak}. (2) Weight numbe We can get the weight numbe vecto of X ij to U i, N(i=1,2,) i by expet s compehensive appaisal and AHP method, whee N 1 = [N 11 N ] N 2 = [N 21 N 22 N 2 N 24 ] N = [N 1 N 2 N ]. Additional, we can get ijt which stands fo the degee of X ij subjective to Y t by fuzzy statistics and we fom a vecto set R i (i=1,2,) R =

3 R 2 = R = Consideing main factos of competitiveness being emphasized, we take opeato as M(*,v),then t t t [ i1 i2 i i4] B = N R = b b b b () Second level appaisal Like the above, we get the weight numbe of C to A by expet s making and AHP method. = [ 1 2 ] C C C C Besides, we can also get b ij which stands fo the degee of U t subjective to Y t and we fom a judgment matix B b b b b R = B2= b21 b22 b2 b24 B b1 b2 b b4 Then we get second level appaisal vecto B = C R = [ b1 b2 b b4] bt= c. b t c. b t c. bt whee. (4) Appaisal judgment [ [ 4] ' ' ' ' ' We get by educing B= b1 b2 b b4 B = b1 b2 b b ] to unity. Then we can judge the entepise competitiveness accoding to the maximum membeship pinciple. Empiical Analysis The above analysis founds the theoy basis fo empiical analysis of logistics entepise competitiveness appaisal. Now we analyze the competitiveness appaisal of a logistics entepise in Heilongjiang povince empiically by applying fuzzy analysis algoithm..1 Competitiveness Identification.1.1 Investigation and Calculation of Index Weight Numbe Accoding to the above, we should make sue competitiveness index weight numbe befoe appaising a cetain entepise in setting up an appaisal model. Fo this sake, we invite specialists including senio executives in industy, expets in academic cicle and othe people to appaise the impotance among indexes by AHP method associating with intenal attibutes of competitiveness. (1) Calculating on the weight numbe of maket competitiveness, management competitiveness and competitiveness to entepise competitiveness. Accoding to the investigation, the appaisal outcome of 5 expets in Goup A and 7 in Goup B is shown by Table 1. Table 1. Table of Index Weight Numbe Appaisal of AHP Method Maket competitiveness Technical competitiveness Management competitiveness Maket Technical Management competitiveness competitiveness competitiveness vecto A B A B A B A B The sequencing vecto in Table 1 is deived fom judgment matix of AHP method by the way of squae oot law. Its concete pocedue is as follows. 1 Numbes multiplied in evey line one by one, then above 84

4 2 Reduction to unity of the above outcome as vecto to get the estimated sequencing vecto Othe index sequencing vecto s calculating is the same, so we leave out the concete pocedues. The pocedue of estimating judgment matix consistency in Table 1 is as follows. 1 The tansposed matix of judgment matix is ight multiplied by sequencing vecto to get a new vecto [ ] [ = ] 2 Evey numbe in the new vecto is divided by evey accoding numbe in sequencing vecto to get anothe vecto = [ ] The total by summing evey numbe in the vecto divided by the numbe of to get an appoximate value fo the maximum chaacte oot λ max. ( ) λ = + + = max 4 Calculating the compatibility index C.I. C.I. = ( λ n ) max ( ) = n 1 1 = 0 5 Calculating the andom compatibility atio C.R C.R. = CI.. RI.. = = 0 Finally, we judge the matix compatibility. The judgment matix has satisfactoy consistency because of C.R.= The weight numbe consistencies of othe judgment matixes ae done as the above pocedue. Though they ae not given, the calculating outcomes show that judgment matixes ae of compaatively satisfactoy consistency. Out of expets, 5 get the judgment outcome as Table 1 and 7 as Table 2. We can wok out the accoding index weight numbe 0.:0.:0.4 i.e., the weight numbes of maket competitiveness, competitiveness and management competitiveness to entepise competitiveness ae 0.,0.,0.4 espectively. Then we get C =[ ]. (2) Calculating weight numbes of kenel business capability and kenel poduct capability to maket competitiveness. Accoding to the investigating outcome, the appaisal outcome of 2 expets in Goup A, 8 in Goup B and 2 in Goup C is shown by Table 2. Table 2. Table of Index Weight Numbe Appaisal of AHP Method Kenel business ability Kenel poduct ability Vecto A B C A B C A B C Kenel business ability Kenel poduct ability We can calculate the accoding index weight numbes as follows: = = 05. namely, weight numbes of kenel business capability and kenel poduct capability to maket competitiveness ae espectively. Then we get N 1 =[ ]. () Calculating weight numbes of the degee of kenel leadeship, new absoption ability, kenel application ability and kenel extending ability to competitiveness. Accoding to the investigation, the appaisal outcome of expets is shown by Table, i.e. the weight numbes ae espectively. Thus we get N 2 =[ ]. 85

5 (4) Calculating weight numbes of stategic management ability, human esouce management ability and entepise cultue to management competitiveness Accoding to the investigation, the appaisal outcome of 6 expets in Goup A and 6 in Goup B is shown by Table 4. Table. Table of Index Weight Numbe Appaisal of AHP Method Kenel leadeship New absoption Kenel application Kenel extending Kenel leadeship New absoption Kenel application Kenel extending vecto Table 4. Table of Index Weight Numbe Appaisal of AHP Method Stategic management ability Management of human esouce vecto Stategic management ability Management of human esouce Entepise cultue Vecto A B A B A B A B Accodingly we get the weight numbes as follows: i.e. weight numbes of stategic management ability, human esouce management ability and entepise cultue to management competitiveness ae espectively. Thus we get N =[ ]..1.2 Identification of Concete Index fo Logistics Entepise A s Competitiveness Expets ae invited to appaise entepise competitiveness identification to get the maximum scoes of identification, besides they have appaised index weight numbes. Accoding to the investigation, the appaisal outcome of 8 expets in Goup A and 4 in Goup B is shown by Table

6 Table 5. Table of Appaised Maximum Scoes of Competitiveness Identification of AHP Method advance malleability histoical dependence value vecto A B A B A B A B A B advance malleability histoical dependence value The accoding index weight numbes ae i.e. the identifications of competitiveness ae that the maximum scoes of advance, malleability, histoical dependence and value ae =0, = 15, =25 and =0 espectively. On the basis of the above, we combine evey expet s advice to detemine the popotion attibuted to appaisal stong, semi-stong, aveage, weak in each identification and compehensive appaisal, which is shown by Table 6. Thus, we can identify the competitiveness of the logistics entepise concetely though the identification of competitiveness. If an expet s appaisal of advance, malleability, histoical dependence and value ae 20,, 18 and 24 espectively, the total scoe is 64, which is included in semi-stong ange. So the competitiveness of the entepise is appaised as semi-stong. If 100 expets ae invited, of whom appaise the competitiveness index as stong, 60 semi-stong, 20 aveage and 8 weak, the membeship of the appaisal set of the entepise maket competitiveness is R={0.,0.60,0.20,0.08}. Table 6. Table of Index Appaisal Based on Identification identification advance malleability histoical dependence value Compehensive appaisal appaisal stong semi-stong aveage weak Obvious leadeship in industy 25-0 Geat influence in many fields 1-15 Most difficult to imitate Obvious pofit advantage 24-0 Infeio to leadeship Influence in some fields 9- Moe difficult to imitate Faily good pofit 18-2 Middle level in industy -17 Middle level in industy 6-8 Imitate at geat cost Middle level in industy -17 Obvious behind othes 0-11 No influence 0-5 Imitate easily 0-10 Pofit disadvantage

7 4 Example fo Calculating and Analysis On the basis of the above analysis of the investigation, we appaise the competitiveness of the entepise though appaisal model we have set up. The concete pocedue is as follows. We get the weight numbe vecto of X to U N 1 =[N 11 N ]=[ ] N 2 =[N 21 N 22 N 2 N 24 ]=[ ] N =[N 1 N 2 N ]=[ ] and the weight numbe vecto of U to A C=[C 1 C 2 C ]=[ ]fom Figue 1. We get the appaisal membeship matix of the index facto X ij to the appaisal set V R = R = R = Then B= 1 N 1 R= 1 [ ] = = [ ] B N R B N R =[ ] [... ] = = =[ ] Then the single-facto appaisal matix of U is R = N R = [ ].. =[ ] The multi-facto appaisal matix of U is R= B B B 1 2 =

8 B= [ b b b b ] C R [ ] = = =[ ] Though eduction to unity and assuming b t = bt 4 b t = 1 t, we get [ ] [ ] B ' b ' b ' b ' b ' = = We can daw the conclusion accoding to B. The membeship numbes of the competitiveness of the entepise to Y 1 (stong), Y 2, Y and Y 4 ae.4%, 18.7 %, 24.8 % and 44.1 % espectively. Accoding to the pinciple of maximum membeship, we appaise the competitiveness of the entepise as weak. 5 Conclusion Finally we can wok out the competitiveness of an entepise by appaising though the compehensive fuzzy appaisal method, which poves to be a easonable one. The method takes vaious kinds of factos into consideation and eflects the eality objectively. The appaisal outcome is accuate and easy to wok out. So it has ealistically instuctive significance. Coespondence to: Yan Zhao, Fengge Yao, Minming She Habin Univesity of Commece Habin, Heilongjiang , China zhaoyan2000@yahoo.com.cn Refeences [1] Wu Wangming. Method of Applied Fuzzy Set Beijing: Beijing Nomal Univesity Pess 1985: [2] Wang Zhitai. Moden Logistics Management. Beijing: Pess China Laboe Pess [] Wang Cheng. Pactice and Cases of Moden Logistics Management. Beijing: Entepise Management Publishing House [4] Song Weigang. Logistics Engineeing and Application. Beijing: China Machine Pess. 200:20-2. [5] Wang Zhitai. Moden Logistics. Beijing: China Logistics Publishing House. 1995: