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2015 (9th) Top 10 Competitiveness Enterprises in the Optical Communications Industry of China & Global Market Contests                                                                                                                                                                              26 The competitiveness report on "the Top 10 competitiveness enterprises in the optical communications industry of China & Global market in 2015” (Abstract Edition)

3. Ranking of Top 10 competitiveness enterprises in the optical components and auxiliary equipment field of Global market during 2014-2015

Rankings of Top 10 competitiveness enterprises in the optical components and auxiliary equipment field of Global market during 2014-2015

                                               Standard value weighted of the financial data(70% weight)                                            Standard value weighted of the survey data(30% weight)

Company                 Sales Net       Net    Return    Return     Sales The ratio of The average        The average       Total       Technology  Customer        Brand    Management   Corporation  Total standard  Comprehensive                      Source of financial data  Country
             Ranking revenues assets   profit  on total  on net   revenues international growth rate of   growth rate     standard      innovation  satisfaction  awareness     level of    culture    value weighted      index of Comprehensive
                                               assets    assets  contribution revenue sales revenues      of net profit                                                       enterprise                of the survey
                        weight weight  weight                                                              for the last     value                                                                                      competitiveness score of
                         18% 13%        13%    weight                per to total sales for the last      three years    weighted of                                                                                                     competitiveness
                                                 8%              employee revenues three years                           the financial                                                                      data $
%


                                                         weight weight weight  weight                     weight         data weight                weight weight weight                  weight            %

                                                         8% 5%   6%            14%                        15% $ 34%                               18% 12% 11%                           25%

Finisar      1 2.1591 0.0636 0.1452 0.0451 0.0155 -0.0283 0.0185               -0.0920                    0.1500         2.4767 0.7385 0.4257 0.3903 0.3045                               0.6063            2.4653     2.4733   1000 Annual report of listed company USA

Avago        2 0.9832 0.0519 0.0899 0.0101 0.0141 0.0583 0.0293                0.1400                     -0.0793        1.2975 0.7294 0.3905 0.3890 0.2842                               0.6554            2.4485     1.6428   977 Annual report of listed company USA

Viavi(JDSU)  3 1.0758 0.0778 -0.0314 -0.0221 -0.0100 0.0239 0.0076             -0.1400                    -0.1334        0.8482 0.7298 0.4184 0.3847 0.2816                               0.6426            2.4571     1.3309   968 Annual report of listed company USA

Sumitomo Electric 4 0.6804 0.0377 0.0336 0.0297 0.0210 -0.0226 0.0110          -0.0386                    0.0929         0.8451 0.5772 0.5094 0.3796 0.2181                               0.6593            2.3436     1.2947   967 Annual report of listed company Japan

Accelink     5 0.4547 0.0111 0.0211 0.0179 0.0058 -0.0260 -0.0080              -0.1168                    -0.0384        0.3214 0.5717 0.3628 0.3794 0.2928                               0.6079            2.2146     0.8894   955 Annual report of listed company China

Fujikura     6 0.4500 0.0285 0.0190 0.0033 0.0069 -0.0245 0.0085               -0.1289                    -0.0353        0.3275 0.7129 0.3736 0.3629 0.2136                               0.5244            2.1874     0.8855   954 Annual report of listed company Japan

Furukawa Electric 7 0.3510 0.0334 0.0410 0.0034 0.0103 -0.0025 -0.0107         -0.1400                    -0.1087        0.1772 0.4367 0.4579 0.4495 0.3370                               0.4025            2.0836     0.7491   948 Annual report of listed company Japan

Oclaro       8 0.4506 -0.0035 0.0173 -0.2599 -0.1142 0.0157 0.0298             0.0214                     -0.0403        0.1169 0.5925 0.3527 0.3523 0.1785                               0.6225            2.0985     0.7114   946 Annual report of listed company USA

Fujitsu      9 0.0978 0.0658 0.0394 0.0082 0.0195 0.0121 -0.0020               -0.1400                    -0.1500        -0.0492 0.5878             0.2931 0.2952 0.3449                  0.5860            2.1070     0.5977   941 Annual report of listed company Japan

NeoPhotonics 10 0.2617 -0.0075 -0.0340 -0.0641 -0.0286 -0.0218 0.0250          0.0167                     -0.0936        0.0538 0.4408 0.2410 0.2268 0.2106                               0.5721            1.6913     0.5451   939 Annual report of listed company USA

Note 1: For the financial data of sales revenues indicator, due to enterprises’ sales revenues derived from diversified products, the data we collect is based on the revenues of relevant products in each sub-sectors of optical communications division. Net profit data is collected from
the relevant products in the optical communications division of the enterprise; Net assets data is collected from the optical communications division of the enterprise.
Note 2: The calculation data of return on net assets and return on total assets are collected from the net profit, net assetsand total assets of the communication division of the selected enterprises. If the enterprise listed does not reveal relevant data in its annual report, they will be
calculated according to the contribution rate of the enterprise’s total profit rate, net assets and total assets.
Note 3: As for the four indicators of sales revenues contribution per employee, the ratio of international revenue to total sales revenues, the average growth rate of sales revenues for the last three years and the average growth rate of net profit for the last three years, we refer to
the released annual reports of the enterprises listed in the rankings, and make no more in subdivision.
Note 4: “Return on net assets” can be defined in different formula. To avoid the incomparable problem of net profit caused by the different corporate income tax rate in listed companies and unlisted companies, we define the molecular in the formula as net profit before tax instead
of net profits. The formula of calculating “return on net assets” is: Return on net assets=net profit before tax/ net assets; Return on total assets=Net profits before tax/ total assets.
Note 5: From the monitoring data, it is found that if the enterprise competitiveness comes mainly from the increase indicators (that is, the average growth rate of revenues for the last three years & the average growth rate of net profit for the last three years), the monitoring data of
the enterprise competitiveness is usually unstable. The main reason for the enterprise competitiveness instability is that the original sales revenues base in these enterprises was small and the increasing sales revenues of recent 2 years make the averag e growth rate of the past
3 years far higher than the industry average level. The extremely high standard value of a certain indicator in the company may cause the standard value of financial data competitiveness index over high on the whole. But in the second or third years, when the growth rate of sales
revenues drops to the normal average level and instead there is no higher growth in the other indicators, the monitoring index of the enterprise competitiveness will decline significantly. To avoid the impact of abnormal change in financial indicators on the objectivity of the enterprise
competitiveness evaluation, we find a practical way to improve it. That is, we set the upper and low limit of standard value in the increase indicators (the average growth rate of revenues for the last three years & the average growth rate of net profit for the last three years) within
[-1,1]. With the consistency of statistical test, the overdone impact on overall standard value of financial data by the abnormal data of growth index can be eliminated.
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