Page 12 - Market Analysis Report of Optical Communications Field in China & Global market 2015

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Rankings of Top 10 competitiveness enterprises in the optical components and auxiliary equipment & raw material field of China during 2014-2015

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

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

%
weight weight weight weight weight weight weight data weight weight weight weight weight
15% $ 34% 18% 12% 11% 25%
13% 8% 8% 5% 6% 14%

Accelink 1 1.8157 0.6756 0.0916 -0.0014 -0.0072 0.0657 0.2732 -0.1400 -0.0789 2.6943 0.7254 0.4166 0.3032 0.3465 0.5038 2.2955 2.5747 1000 Annual report of listed company

O-net 2 0.5461 0.1722 0.0110 0.0081 -0.0080 0.4262 0.6192 -0.1400 0.0111 1.6459 0.5329 0.2896 0.2265 0.2420 0.4281 1.7191 1.6679 938 Annual report of listed company
HG Genuine 3 0.8242 0.1395 -0.0081 -0.0176 -0.0175 0.0355 0.1165 0.1400 -0.1500 1.0625 0.3575 0.2656 0.2854 0.2280 0.2596 1.3961 1.1626 919 Annual report of listed
JONHON 4 0.6272 0.1411 0.0379 0.0134 0.0174 0.0276 0.0041 0.0224 -0.0251 0.8660 0.3635 0.3533 0.0871 0.2872 0.2510 1.3421 1.0088
parent company
911 Annual report of listed company

Sunsea 5 0.4274 0.5433 -0.0191 -0.0170 -0.0165 0.0330 0.0018 0.0168 -0.1500 0.8197 0.3823 0.2775 0.2919 0.2455 0.2353 1.4325 1.0035 910 Annual report of listed company
0.7629
Sunstar 6 0.2976 0.0115 -0.0047 0.0060 0.0152 0.0455 0.3040 -0.1400 -0.0694 0.4657 0.3863 0.3762 0.1099 0.3100 0.2738 1.4562 0.5833 902 Annual report of listed
parent company

HONGHUI 7 0.2360 0.0501 0.0116 0.0269 0.0179 0.3474 -0.0480 -0.1400 -0.0389 0.4630 0.2610 0.1972 0.1358 0.1482 0.1217 0.8639 889 Annual report of listed company

NSU 8 0.0933 0.2305 -0.0011 0.0007 0.0007 0.0149 -0.0480 0.0459 -0.0117 0.3252 0.3707 0.2714 0.1979 0.1446 0.1636 1.1482 0.5721 887 Annual report of listed company

Haiso 9 0.1512 0.0529 -0.0078 0.0379 0.0502 0.0634 -0.0240 -0.1400 -0.0643 0.1195 0.2600 0.2034 0.0912 0.0821 0.0833 0.7200 0.2997 Taxationǃresearch ˂ survey
TIANYI 10 0.0743 0.0510 0.0092 0.0200 0.0163 -0.0009 0.0215 -0.1055 -0.0382 0.0477 0.2340 0.2138 0.1284 0.1296 0.1212 0.8270 0.2815 868 information˗self-reported figures

and operators' tender results

866 IPO annual report of
listed company

Note 1: Enterprises qualified for the competitiveness selection in the optical communications field of China shall have 2 or more items of relevant products as core businesses. FiberHome Technologies is the only company with 3 types of products that participates in the selection.
Note 2: What makes the list of comprehensive competitiveness enterprises in the optical communications field different from the other lists of 3 sub-sectors is the data resource of the sales revenues indicator. The data of the former list comes from the total revenues in the optical communications
business, while the data of the other 3 lists is the sales revenues of the related products in the sub-sectors of the optical communications industry.
Note 3: “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.
Note 4: 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 average 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 co nsistency of statistical test, the overdone impact
on overall standard value of financial data by the abnormal data of growth index can be eliminated.