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Under the environment of supply chain, enterprises not only put forward higher request to the product itself, but also focus more on the supplier selection criteria. In the early stage of the supply chain construction enterprises, we will find that there are many outstanding suppliers to choose from; facing a large number of suppliers, an effective way of supplier evaluation is very important. In this paper, the principal component analysis method is applied in supplier evaluation index, by extracting the principal components of the multi index comprehensive evaluation, and quantitatively provides guidance and reference for the selection of suppliers for the enterprises in the supply chain.

With the advent of the era of economic globalization, the management of modern enterprise has changed; the supply chain management mode has become more and more popular. Supply chain is composed of suppliers, manufacturers and distributors, in which the three suppliers in the main position are to enhance the efficiency of the supply chain, an important way to improve the operational efficiency of the supply chain. An ideal supplier will not only help enterprises to reduce production costs, and improve product quality, but also determine the supply chain to run the degree of stability and operational efficiency. Screening reasonable supplier has become a strategic weight to enhance the core competitiveness of enterprises. The principal component analysis is applied to the supplier evaluation system, and the principal component analysis method is applied to the evaluation of the supplier under the multi index system. The weight is determined by the variance contribution rate, which overcomes the defect of artificial weight. The weight contains the amount of information of the original data, so it is objective and reasonable.

In the current supply chain management, there are many suppliers of the evaluation criteria, which makes the companies have chosen to become more complex. Huang- Yao Guo believed that the four main indicators of quality, price, technical capability, and transmission reliability can be a better measure of supplier [

The principal component method is applied to the reduction of dimension in the method of transforming several variables into a few synthetic variables. Each of the main components is a linear combination of the original variables. Each of the main components of the information does not overlap with each other, but can reflect the vast majority of information variables. The basic process of analysis is as follows.

Standardized evaluation process: in indicators due to the selection of third-party suppliers, packaging, storage, transportation, handling and other indicators belong reverse indicators need to be translated into positive indicators, commonly used logarithmic or the reciprocal method for processing.

Obtaining standardized data correlation matrix: A high degree of correlation between the various indicators, indicating indicators has great repeatability for the Principal Component Analysis.

Find the eigenvalues of the correlation matrix, eigenvalue contribution rate, the cumulative contribution rate and weight to calculate the score of each index and the total score of the vendor evaluation.

Taking Liaoning Province as an example, After screening, there are four suppliers to choose from Now wants to conduct a comprehensive assessment of the four suppliers,

This paper mainly uses the SPSS21.0 statistical software to analyze the main components of the evaluation index. Because of the index of evaluation, we need to transform it into a positive indicator, and this paper mainly adopts the method of taking the reciprocal. And then the index is standardized (graph omission). Finally the total variance explained is shown in

In SPSS output, there are three main components of eigenvalues greater than 1, the three main components extracted from the initial solution, the cumulative variance contribution rate of 100%, indicating that with these three main components repre- senting the original 16 indicators comprehensive evaluation of logistics enterprises have sufficient grasp.

According to

In the first component, Z_{SCORE} (X4), Z_{SCORE} (X5), Z_{SCORE} (X6) coefficient is larger. The first principal component is a comprehensive index of annual income, annual profit and cash flow, which reflects the financial situation of the supplier. The financial situation is an important index to evaluate the production and operation of an enterprise, which indirectly reflects the management level of the enterprise and the management strategy. It is reasonable to use the financial situation as the first principal component.

Supplier name | Transport (million) | Handling (million) | Package (million) |
---|---|---|---|

1 | 80 | 3 | 2.5 |

2 | 100 | 4 | 3.5 |

3 | 60 | 3.5 | 4 |

4 | 105 | 2.5 | 3.2 |

Supplier name | Income (million) | Profit (million) | Cash flow (million) |

1 | 300 | 2000 | 200 |

2 | 1600 | 20000 | 600 |

3 | 200 | 600 | 200 |

4 | 2600 | 30000 | 700 |

Supplier name | Main business (million) | Advertising expenditures (million) | Outbound time rate (%) |

1 | 2 | 1 | 80 |

2 | 1.8 | 0.8 | 60 |

3 | 1.5 | 1 | 80 |

4 | 2 | 0.5 | 100 |

Supplier name | Documents accuracy (%) | Transportation safety factor (%) | Transportation accuracy rate (%) |

1 | 100 | 99 | 99 |

2 | 99 | 98 | 98 |

3 | 100 | 99 | 99 |

4 | 99 | 100 | 100 |

Supplier name | Goods broken rate (%) | Quality of personnel (10-point) | Customer reviews (10-point) |

1 | 1 | 8 | 10 |

2 | 0.1 | 6 | 8 |

3 | 0.5 | 8 | 8 |

4 | 2 | 8 | 6 |

Supplier name | Transport records (10-point) | Storage security (10-point) | Storage timeliness (10-point) |

1 | 8 | 8 | 8 |

2 | 10 | 9 | 10 |

3 | 5 | 8 | 8 |

4 | 8 | 6 | 4 |

The second component is Z_{SCORE} (X9), Z_{SCORE} (X13), Z_{SCORE} (X11) coefficient larger, the second principal component is by the library and timely rate, cargo damage rate and transportation safety rate characterizations of comprehensive index, which reflects the suppliers transport and storage quality. Transport and warehousing is an important part of is supply chain management, having certain transportation and storage capacity of the suppliers can not only ensure the successful completion of the transaction tasks but also can bring more customers for the enterprise, the position is second only to financial status. The last principal component is a comprehensive service index, which is

Ingredient | Initial eigenvalues | Extracting square and load | ||||
---|---|---|---|---|---|---|

Total | Variance % | Accumulation % | Total | Variance % | Accumulation % | |

1 | 9.624 | 53.465 | 53.465 | 9.624 | 53.465 | 53.465 |

2 | 5.904 | 32.803 | 86.267 | 5.904 | 32.803 | 86.267 |

3 | 2.472 | 13.733 | 100.000 | 2.472 | 13.733 | 100.000 |

4 | 1.009E−013 | 1.048E−013 | 100.000 | |||

5 | 1.004E−013 | 1.022E−013 | 100.000 | |||

6 | 1.003E−013 | 1.019E−013 | 100.000 | |||

7 | 1.002E−013 | 1.011E−013 | 100.000 | |||

8 | 1.001E−013 | 1.007E−013 | 100.000 | |||

9 | 1.001E−013 | 1.005E−013 | 100.000 | |||

10 | 1.000E−013 | 1.002E−013 | 100.000 | |||

11 | 1.000E−013 | 1.000E−013 | 100.000 | |||

12 | 1.000E−013 | 1.000E−013 | 100.000 | |||

13 | −1.001E−013 | −1.004E−013 | 100.000 | |||

14 | −1.001E−013 | −1.007E−013 | 100.000 | |||

15 | −1.002E−013 | −1.009E−013 | 100.000 | |||

16 | −1.003E−013 | −1.016E−013 | 100.000 | |||

17 | −1.003E−013 | −1.019E−013 | 100.000 | |||

18 | −1.005E−013 | −1.028E−013 | 100.000 |

Extraction method: principal component analysis; extract three principal components.

Ingredient | |||
---|---|---|---|

1 | 2 | 3 | |

Z_{SCORE} (X_{I}) | 0.810 | −0.531 | 0.248 |

Z_{SCORE} (X_{2}) | −0.671 | −0.710 | −0.214 |

Z_{SCORE} (X_{3}) | −0.231 | −0.189 | −0.954 |

Z_{SCORE} (X_{4}) | 0.929 | −0.344 | −0.137 |

Z_{SCORE} (X_{5}) | 0.901 | −0.413 | −0.129 |

Z_{SCORE} (X_{6}) | 0.832 | −0.531 | −0.160 |

Z_{SCORE} (X_{7}) | 0.648 | 0.004 | 0.761 |

Z_{SCORE} (X_{8}) | −0.969 | 0.170 | 0.178 |

Z_{SCORE} (X_{9}) | 0.648 | 0.955 | −0.102 |

Z_{SCORE} (X_{10}) | −0.741 | 0.656 | 0.146 |

Z_{SCORE} (X_{11}) | 0.648 | 0.855 | −0.102 |

Z_{SCORE} (X_{12}) | 0.648 | 0.755 | −0.102 |

Z_{SCORE} (X_{13}) | 0.813 | 0.870 | 0.118 |

Z_{SCORE} (X_{14}) | 0.102 | 0.695 | 0.501 |

Z_{SCORE} (X_{15}) | −0.759 | 0.077 | 0.646 |

Z_{SCORE} (X_{16}) | 0.367 | −0.769 | 0.523 |

Z_{SCORE} (X_{17}) | −0.930 | 0.357 | 0.091 |

Z_{SCORE} (X_{18}) | −0.940 | 0.350 | 0.091 |

Extraction method: principal component analysis; extract three principal components.

composed of personnel quality, customer evaluation, and transport record. With good service ability is an important guarantee for enterprises to open up the market, as the third main components of supplier evaluation is an indispensable indicator.

According to

The first principal component is the main measure of the financial situation of each supplier. Score ranking are the supplier 4, supplier 2, supplier 1, supplier 3. In the second principal component, the transportation and storage quality advantages are supplier 3, supplier 1, supplier 4, supplier 2. In the third principal component, the comprehensive service ability of the supplier 1 is superior to other suppliers. In the third principal component, the comprehensive service ability of the supplier 1 is superior to other suppliers. Enterprises can be based on each index score to pick out in a certain area has the advantage of suppliers for enterprise profit.

The three main components of the variance contribution rate were 0.505, 0.34202, 0.19298.With three principal components variance contribution rate as weights, get each index of the comprehensive score in the above

Supplier | Z_{1} | Z_{2} | Z_{3} |
---|---|---|---|

1 | −3.80284 | 3.010255 | 3.54424522 |

2 | −3.08909 | −7.669 | −0.57220002 |

3 | −7.30337 | 3.08135712 | −2.35426568 |

4 | 14.1953 | 1.57738807 | −0.61777823 |