Technological Forecasting & Social Changegeza.kzoo.edu/~erdi/patent/cikkek/yang-weng.pdfof NCPA....

Technological Forecasting & Social Change xxx (2011) xxx–xxx

TFS-17388; No of Pages 17

Contents lists available at ScienceDirect

Technological Forecasting & Social Change

A New Comprehensive Patent Analysis Approach for New Product Design inMechanical Engineering

Kuang OuYang a, Calvin S. Weng b,⁎a Department of Business Administration, National Yunlin University of Science and Technology, Yunlin, Taiwanb Department of Banking and Finance, Takming University of Science and Technology, Taipei, Taiwan

a r t i c l e i n f o

⁎ Corresponding author.E-mail addresses: [email protected] (K. O

0040-1625/$ – see front matter © 2011 Elsevier Inc.doi:10.1016/j.techfore.2011.02.012

Please cite this article as: K. OuYang, C.S.Mechanical Engineering, Technol. Forecas

a b s t r a c t

Article history:Received 15 December 2009Received in revised form 19 February 2011Accepted 23 February 2011Available online xxxx

This study proposes a five-phase procedure for a new product design process. Based on theconcept of “focus first, then extend”, this study presents a new approach called the NewComprehensive Patent Analysis model (NCPA) which combines the patent family with patentcitation analysis in a new product design process. The procedure includes the followingfeatures: (1) integrating the perspective of management-based and technology-based designfor patent searching, (2) building a patent family based on industry basic patents, (3) filteringthe patent family to obtain key patents, (4) utilizing patent citations to gain necessarytechnology information in product development design, and (5) combining TRIZ theory toconstruct patent technology performance maps, and to discover product niches. This NCPAmodel is empirically applied in a real case. The results show that the NCPA improves the overallefficiency of new product designs, but also involves higher cost than other approaches.

© 2011 Elsevier Inc. All rights reserved.

Keywords:Patent analysisPatent familyPatent citationNew product design

1. Introduction

Prior researchers have proposed several different approaches for New Product Development (NPD) [1–4]. Many studies havealso suggested that in order to meet customer needs, Quality Functional Development (QFD) should be applied during the productplanning stage to ensure awareness of the voice of the customer [5]. However, QFD should be adjusted according to the differencesamong the various industry fields and their product characteristics [6]. Because of TRIZ is capable of analyzing engineeringtechnical issues, resolving contradictions and producing systematic innovation, Kim and Cochran recommended that TRIZ is apowerful and efficient tool for the phase of NPD concept design [7]. Therefore, Yamashina et al. further proposed the model ofInnovative Product Development Process (IPDP) to be systematically integrated with QFD and TRIZ, so as to enhance theperformance of technical innovation [8].

Management of patent rights is the key to business intellectual property, and has a highly positive correlation between patentsand enterprise market value [9–13]. However, the IPDP model does not include the procedure of patent analysis. Without patentanalysis and a proper patent portfolio, the following issues may occur: (1) failure to translate intellectual property into marketvalue, (2) failure to utilize intellectual property capital and convert it into financial capital, (3) lack of offensive capability, and(4) lack of bargaining power in patent authorization.

The patent analysis procedure is a complex and time-consuming task in R&D management [14–17]. Especially, when thevolume of patents is huge, it may cause analysis problems of inaccurately targeting and failing to lock-on to the right subjectsduring the design-around. Therefore, how to focus on some key patents will become an ever more important issue. Moreover,insufficient patent information prevents designers from utilizing the results of analysis in NPD process. As patent analysistechniques are developed, the patent family and patent citations can provide important information for business intelligence and

uYang), [email protected] (C.S. Weng).

All rights reserved.

Weng, A New Comprehensive Patent Analysis Approach for New Product Design int. Soc. Change (2011), doi:10.1016/j.techfore.2011.02.012

http://dx.doi.org/10.1016/j.techfore.2011.02.012

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2 K. OuYang, C.S. Weng / Technological Forecasting & Social Change xxx (2011) xxx–xxx

for technology management and strategy formation reference. For example, a patent family is formed on the basis of priority, andpatent intelligence is acquired through patent citations. How to implement the above into NPD in order to enhance productperformance, to protect innovation and to construct patent portfolio is becoming an important issue today.

In sum, using a patent family and patent citation analysis can help to enhance new product design, whichwas neglected in pastresearch. This study proposes a patent analysis model called the New Comprehensive Patent Analysis process (NCPA) to integratea patent family and patent citations within the phase of NPD, and to complement the procedure of the IPDP model. This paper isstructured as follows: Section 2 is the literature review of the patent family and patent citations. Section 3 introduces themodelingof NCPA. Section 4 is the empirical study of a real case, and the final section includes conclusions and discussions.

2. Literature review

According to Berkowitz's study, patent analysis helps to discover not only technical niches but also uncovered areas [18]. Chenand Chen conducted technical clusters by using a patent map, and further developed a design strategy through observing thedistribution of 96 patents of bicycle parts in the period of 1992 to 2003 [17]. There are some defects in Chen and Chens' study: first,the research neglected the heterogeneousness of patents. In other words, not every patent is of the same value [19]. This causedbiases and inaccurate information making it difficult to create a design-around strategy. Second, the research failed to recognizethe importance of “Claim” and “Drawing” in patent documents. Third, the value of prior art was not utilized, and the possibleapplicable fields of patents were not analyzed.Without accurate information, in such circumstances, engineers rely on nothing buttheir profession and limited creativity. In sum, the concepts proposed by the aforementioned research did not necessarily help tosolve the engineering problems in the phase of detail design.

2.1. Patent family

A patent family, which is derived from the concept of priority, is a group of related patent publications (including applicationsand granted patents) describing the same invention. The first application filed is the priority application, and subsequent filingswithin 12 months after the priority application will list this number [20]. The World Intellectual Property Organization (WIPO)even extends the priority to 30 months after first application. In a narrow sense of theword, a patent family is a set of patents takenin various countries to protect a single invention. On the other hand, a patent family can also be a series of patent applicationsderived from the same core technology and its relevant patent portfolios in other countries [21]. On the contrary, a patent familycan be broadly defined as a company's highly similar or related patent portfolio. Based on this definition, a competitor's mostrepresentative patent can be specified and identified for design-round during the NPD process through patent family analysis.

Fig. 1 illustrates an example of a patent family. According to the definition of a patent family by the Europe Patent Office, PatentIV is a Continuations in Part (CIP) of Patents I, II and III. Patents I, II and III are applied for in countries C, B and A, respectively. PatentIV, IV′, and IV″ are also applied for in country B. In the case, the Patent IV″ is a Divisional Applications (DIV) of Patent IV′, and is alsothe Continuations Application (CA) of Patent IV. The Patent Family is then formed as Fig. 1. Patents I, II, III, and Patents IV and IV′are the priority to Patent IV″ as well. Looking at the application process of each patent within the patent family, it is obvious thatthe priority of prior art lead to changes of claims, including identical claims, partially identical claims, new claims, or divisionalclaims to prior art. These changes not only show a company's efforts on claiming the validity of novelty but also demonstrate itsdeployment of a patent portfolio [22].

The International Patent Documentation Center database (INPADOC) of the Europe Patent Office (EPO) is currently the mostcomplete extended patent family database. INPADOC currently integrates patent data from 42 Patent Offices across 80 countries,which includes priority application numbers, application numbers, publication numbers, and legal status database additionalinformation. Therefore, patent family information for a certain patent can be rapidly obtained through INPADOC, and the legal

Patent I

Patent II

Patent III

Patent IV Patent IV’ Patent IV”

Country A

Country B

Country CCIP

CIP

CIP

CA DIV

Fig. 1. Patent family.

Please cite this article as: K. OuYang, C.S. Weng, A New Comprehensive Patent Analysis Approach for New Product Design inMechanical Engineering, Technol. Forecast. Soc. Change (2011), doi:10.1016/j.techfore.2011.02.012


3K. OuYang, C.S. Weng / Technological Forecasting & Social Change xxx (2011) xxx–xxx

status of its claims in various countries can be determined. Thus, considering the information of a patent family will bring thefollowing benefits for new product development: (1) obtain reader-friendly versions of patent descriptions, e.g. an Englishdescription of a French Patent, (2) aid in assessing the core values of patents, and (3) filter out patents for design-around [23,24].

In practice, due to various assessment criteria from different countries, language translation problems, and poor expositions ofpatent claims, many patents did not deserve their own equivalent protection for a Claim, which weakens the real value ofimportant patents [21]. Thus, in order to determine the coverage of a patent claim and screen for the most valuable patents, asystematic expert analysis procedure should be conducted while utilizing patent family information. In sum, in order to enhancethe effectiveness of patent analysis, a competitor's patents must be effectively identified for design-around during the process ofNPD. Patent families created by using INPADOC can help to deploy the corporative patent strategy as well as to explore the mostrepresentative and competing patents.

2.2. Patent citation

Patent citation analysis is gaining more popularity in technology and corporate management [25]. Technological developmentis cumulative in nature because inventions and research are on the basis of existing technologies [26,27]. Patents are the outcomesof R&D, which declare their right to protect and the claim not to be infringed upon [29]. In patent documents, prior art informationclearly recorded the path of knowledge accumulation [28]. And patent citations build technological relationships by linking thegranted patents to its prior art. Patent citations therefore serve as an information exchange between sciences and technologies[30]. The spillover effects resulting from patent citations illustrate that patent citations are one of the knowledge sources fortechnological breakthroughs and product designs [12,31,32]. Thus, design-around in NPD requires vast knowledge of prior art, andthe tracing of linkages among technological innovations through patent citation analysis. Therefore, patent citation analysis is notonly a resolution for insufficient data during new product design, but also a source for innovation.

There are different ways to analyze patent citations, but Wartburg et al. concluded that single-stage citation analysis cannotreveal technological paths or lineages. Therefore, one should also make use of indirect citations and bibliographical coupling, andtwo-stage citation can obtain more complete and appropriate information of prior art for the new product design process [33].Fig. 2 illustrates the two-stage patent citation process proposed by Wartburg et al. [33].

On the other hand, patent citations facilitate the discovery of evolution of technological development, and the frequency ofpatents that are cited will reveal the technological importance [25,34]. Previous studies proposed that patent citations aresignificantly correlated with its market value [38–41]. The higher the frequency is, the higher the value of innovations and profit is[35,36]. Besides, Park and Park used patent citations to measure the amount of technological knowledge [37]. Therefore, thefrequency of patent citations not only determines the market value of technology, and but also may be a measurement index forassessing patent quality [13,42–44]. Accordingly, Lee et al. [45] and Hu [41] measured patent quality and knowledge flow withfrequency of patent citations. In sum, from the above review of the literature (section 2), patent citation analysis can help to screenprior art information and efficiently facilitate the design-around [1,8,46,47]. Integrating patent families and citations, togetherwith expert analysis, will assist the evaluation of real value of patents.

3. New Comprehensive Patent Analysis approach (NCPA) for NPD

In order to introduce patent information into the design phase of NPD, this research proposes the New Comprehensive PatentAnalysis (NCPA) which creates a patent analysis procedure on the basis of a patent family and patent citations. This procedureincludes five phases as follows:

(a) Phase I selects an appropriate patent database after carrying out an industry analysis and expert interviews. Phase I consistsof step 1 and step 2.

(b) Phase II selects industrial basic patents and creates a patent family. Phase II consists of steps 3 to 5.(c) Phase III filters the members of a patent family to obtain the most representative patents, and focuses product design on

these key patents. Phase III consists of steps 6 to 8.

Core sample Cited step one Cited step two

Fig. 2. Stepwise development of the citation network [33].




(d) Phase IV employs a patent citation to trace back to the relevant technical information of “key patents” for the purpose ofproduct development design. Phase IV consists of steps 9 to 11.

(e) Phase V uses the TRIZ theory to analyze technological performance of patents and constructs technological performancemaps of patents for product development design. Phase V consists of steps 12 to 14.

Fig. 7 illustrates the five-phase NCPA approach with its 14 steps. Descriptions of each phase of the NCPA are as follows.

3.1. Phase I: industrial analysis and patent search strategy

Fig. 3 illustrates the procedure. The purpose of conducting industrial analysis and expert interviews is to ascertain the researchscope and to set the patent search strategy. This step addresses three issues: market trends, technological evolution and competingfirms [18].

3.1.1. Step 1: industrial analysis and expert interviewA. Industrial analysis:

The task descriptions are as follows:(a) Understanding market trends. To identify a target market and its market position, it is necessary to analyze product

classification and its circulation, the system structure and possible future development.(b) Grasping technological evolution. To satisfy customer demand, it is necessary to conduct expert analysis to explore the key

technology structures, features, and evolution for the product or subsystem. Technological evolution serves as a guide forthe development of NPD. In this stage, Quality Function Deployment (QFD) will be used to facilitate the translation of theclient's demands into the design parameters [5].

(c) Identifying competingfirms. In order to knowmore about competingfirms, it is important to enhance patent search efficiencyfrom the perspective of business managers [48].

B. Expert interview:Experts include enterprise management and R&D personnel. The patent search is based on a combination of commercial andtechnical information.

3.1.2. Step 2: patent search strategyThe patent search strategy is made on the basis of the following information: market results, industry and technological

structure analysis, expert interviews, confirmation of technology keywords and International Patent Classification (IPC). Anappropriate patent database needs to be selected as well.

3.2. Phase II: selecting industry basic patent and building patent family

After a patent search strategy is formed, the next phase is to conduct an industry basic patent search and to create a patent family.

Industrial Analysis Expert Interview

TechnologicalEvolution

Market Trend Competiting Firms

TechnologicalKeywords

Confirm IPC

Select Patent Database

Fig. 3. The process of phase I in NCPA.




3.2.1. Step 3: industrial basic patent setA patent search strategy is created to obtain competitors' patents which are required by the NDP. The result of patent search is

known as the industry basic patent set. Let Ci represent Industrial competitors and Pj represent the patents relevant to NPD,respectively. The intersection of competitor's patents and patents related to NPD are classified as industrial basic patents. Andrelationship between CiandPj can be shown as matrix [εij]M×N, where:

PleasMec

εij =1 Pj is affliated with Ci; i = 1;2;…;M0 Otherwise; j = 1;2;…;N

�ð1Þ

Industrial basic patents are the source for design-around. The relationship between competitors and industry basic patents isshown as Fig. 4.

Patent family information is further filtered by experts' assessments and patent citation analysis among the industry basic patents.

3.2.2. Step 4: candidates of patent familyNot every patent is of the same value [19]. The primary objective of selecting candidates of a patent family is to provide a basis

for constructing a patent family. Criteria for selecting candidate patents are the frequency of citation and expert assessment. Fig. 5shows the process of obtaining candidates for a patent family.

[δij]m×n, mbM, nbN, where:

δij =10

Pj is affliated with Ci; i = 1;2;…;mOtherwise; j = 1;2;…;n

�ð2Þ

The final selection of industrial basic patents is the candidates of the patent family and they will serve as the basis forconstructing the patent family.

3.2.3. Step 5: constructing patent familyA patent family is constructed by the final selection of step 4. The patent family will help with the well understanding of a

competitor's patent portfolio of a specific technology. The details are as follows:(a) Compute the total of the patent family selection:

∑i ∑j δij = s, s≧1, where the cutoff value “s” depends on the expert opinion.

PatNoCA2321056AACA2321056CEP1056607A4US7273117 ……….WO9942311A2…………

DelphionDatabase

IPC code

Industry basic patent set

PatNo TitleAT192386E HOEHENAT260183E HYDROPNEUAT304469E MIT HILFECA2321056C ADJUSTABLEEP1056607A4 ADJUSTABLE

……….

PatNoAT243126EAT304469EAT91779EDE68907657C0EP1137560B1………..

Firm A

PatNoAT192386EAT260183ECA2214971AADE19949152C2EP1224088B1……….

Firm B

Firm C

.

.

Fig. 4. The relationship of competitors and industrial basic patents.

e cite this article as: K. OuYang, C.S. Weng, A New Comprehensive Patent Analysis Approach for New Product Design inhanical Engineering, Technol. Forecast. Soc. Change (2011), doi:10.1016/j.techfore.2011.02.012


Industry basic patent set

Firm PatNo TitleA …… ....B …… ….C …… ….D …… ….E ……. ……

Reject

Finally Candidateof patent family

YES

Firm PatNo TitleA ……. ….D ……. ….… …… ….…

Firm PatNo TitleB …… ….C …… ….E ……. …..… …… ….…

Candidate of patent family

Firm PatNo TitleA ……. ….B ……. …..C …….. …..D ……. ….… ……

YES

NONO

Decision by citation analysis

Decision by experts

…… ....…… ….…… ….…… ….……. ……

……. ….……. ….

… …… ….…

…… ….…… ….

……. …..… …… ….…

……. ….……. …..…….. …..……. ….

… ……

…… ....…… ….…… ….…… ….……. ……

……. ….……. ….

… …… ….…

…… ….…… ….

……. …..… …… ….…

……. ….……. …..…….. …..……. ….

… ……

Fig. 5. The process of obtaining candidates of patent family. The new relationship of competitors and industrial basic patents is a matrix.



(b) In order to collect the complete set of competitors' patent information, data is selected from the Delphion commercialdatabase. TheDelphion commercial databasewas built on the base of INPADOC. The patent familymatrix is as follows:

PFcijh i

kc×lc; C = 1;2;3;…; s ð3Þ

Where, kc represents the number of candidates of patent family, and lc represents the number of patent of the largest patentfamily.

3.3. Phase III: selecting key patent

3.3.1. Step 6: computing key patent priority number (KPPNmc

c )After constructing a patent family, the KPPNmc

c of each key patent is computed.We select the largest number of KPPNmc

c among apatent family to serve as representative patent. We treat this patent as candidate of the key patent. The key patent must bedetermined by calculating the key patent priority number KPPNmc

c . A detailed description is as follows:

A. Let kc× lc=mc, KPPNmc

c represents the key patent priority numberThe KPPNmc

c is calculated from three dimensions of a patent, which are

(a) Technological value added (Tmc

c );(b) Application potential (Amc

c ); and(c) Other (Omc

c ).The results of KPPNmc

c are the criteria for selecting representative patents in each family. To increase flexibility of patentvalue assessment, letWA,WB,WC represent the weight of Tmc

c , Amc

c , Omc

c , respectively. The values ofWA,WB,WC is decided byexpert opinions and decision makers. Therefore,

KPPNcmc

= f Tcmc;Ac

mc;Oc

mc

� �= Tc

mc× WA

� �× Ac

mc× WB

� �× Oc

mc× WC

� �ð4Þ

, WA+WB+WC=1.
whereB. The dimensional definition of Tmc
c , Amc

c and Omc

c

The dimensional definitions and the criteria are described as follows:

(a) Tmc

c represents the innovativeness of technology patents. The criteria indices include the following: (1) Functionality, and(2) Variability.

(b) Amc

c represents the innovativeness of technology patents when applied to mechanical engineering. The criteria indicesinclude the following: (1) Development effort, (2) Space, (3) Construction effort, (4) Information, (5) Cost, (6) Production,(7) Control, (8) Maintenance effort, and (9) Time.

(c) Omc

c represents other innovativeness. The criteria indices include the following: (1) Energy efficiency, (2) Security, and(3) Environment.Index evaluation standard: Use the following quantification standard to quantify the three dimensions of KPPNmc

c .

(a) Tmc

c : The scale is 1–10, of which 1 represents the lowest value of patent technology innovativeness, or, low effectiveness intechnology production, while 10 represents the highest value of patent technology innovativeness, or, high effectivenessin technology production.



(b) Amc

c : The scale is 1–10, of which 1 represents the lowest value of technology application, and difficulty in integration withmechanical engineering and in commercialization, while 10 represent the highest value in technology application, andease in integration with mechanical engineering and in commercialization.

(c) Omc

c : The scale is 1–10. 1 represents the lowest value in other aspects of patent technology while 10 represents the highestvalue in other aspects of patent technology.

C. Selection of representative patents in a patent family. Calculate the key patent priority number KPPNmc

c in each patent family,and choose the largest key patent priority number KPPNmc

c in each patent family as the representative patent (KPPNc)*, whichare the candidates of the key patent. Where select,

PleasMec

MAX KPPNcmc

h i= KPPNc� ��

; c = 1;2;…; s ð5Þ

After identifying candidates of key patents from a patent family, the next step is to compare and screen the KPPNmc

c of allkey patent candidates.

3.3.2. Step 7: Scree testThe Scree test developed by Cattell is a statistical method that gives greater weight to more important variables and less weight

to less important ones [49]. Scree is a graphical method of judgment. The principles of the Scree test are identical to those ofPrinciple Component Analysis (PCA). Therefore, the variables are almost with the same weight and should be discarded when thegraph shows flat curves. KPPNmc

c for the representative patents (KPPNc)* in each patent family are depicted along with the abovethree dimensions. The Scree is shown in Fig. 6.

3.3.3. Step 8: key patentIn addition, key patents can be selected after the Scree is presented. The results of the Scree indicate the most representative

patents in all patent families, whichmay be assumed to be the competitive objects for a new product. A description is given below:

A. Integrate the Scree and the expert interviews to select the representative patent (KPPNc)* and determine the critical value (C⁎)of key patent quantity. And C⁎, where 1≦C⁎≦s.

B. After C⁎ is determined, key patents can be obtained, and

KPPN�� n; n = 1;2;…;C�

er the key patents are identified, the next step is to employ patent citation analysis to trace their prior arts for the primary
Aftreference of the new product design-around.
3.4. Phase IV: key patent citation

3.4.1. Step 9: two-step patent citationAn appropriate patent database is selected for new product design. Here, we chose the Delphion commercial database.

A. Key patents (KPPN*)n are searched in the Delphion commercial database.

Fig. 6. The Scree of key patent priority numbers in patent family.




B. A two-step citation process is employed to ensure the quality of the citation information [33]. A new matrix is thus formed asfollows:

PleaMec

αnij

h irn×sn

; n = 1;2;…; c�; i = 1;2;…; rn; j = 1;2;…; sn ð6Þ

C. To obtain more complete patent citation information, both commercial databases, Delphion and Aureka, can be mutually used.Prior arts are identified by the two-step citation process, but irrelevant data for new product design may still remain. Next is toidentify candidates of key technology patents.

3.4.2. Step 10: candidates of key technology patentKey technologies are the core technologies of the company. However, these key technologies often exist in patent documents

and need to be explored by experts. Irrelevant patent data for new product design will be produced after the two-step citationprocess. Therefore experts must further analyze the “title” and “abstract” of patents to filter candidates of key technology patentsand to obtain the best combinations of candidates. A new matrix is developed accordingly:

βnij

h ir0n

×s0n; n = 1;2;…; c�; i = 1;2;…; rn

0; j = 1;2;…; sn0; rn

0≦rn; sn0≦sn: ð7Þ

After candidates of key technology patents are determined, experts will judge the importance and value of patents to select thefinal key technology patents.

3.4.3. Step 11: key technology patentKey technology patents must be patents containing key technology with high quality of patent documentation. High quality of

patent documentation means that information of patent technology is directly related to new product designs. Once thecombination of candidates of key technology patents are obtained, experts then judge the “drawings” and “claims” in patentdocuments and decide which are necessary for new product designs. The combination of key technology patents is then obtained.A new matrix is developed accordingly:

γnij

h ir00n

×s00n; n = 1;2;…; c�; i = 1;2;…; rn

00; j = 1;2;…; sn00; rn

00≦rn0; sn00≦sn0: ð8Þ

Next, patent technology performance analysis is conducted. A graph distribution is created to explore the following: (1) thetechnological development, (2) deployment in the industry, and (3) technological performance niches for new product development.

3.5. Phase V: technology performance analysis

3.5.1. Step 12: analysis of patent technology performanceTechnology performance is performed after key technology patents are finalized. Information of patent technology

performance mainly comes from the “drawings”, “claims” and “summary of innovation” in patent documents. To enhance theefficiency of technology performance analysis, categorization of patents is conducted beforehand based on “title”, “abstract”, and“drawings” of patents. The relationship between performance Pi and technology Tj produces a technology performance matrix[TPij]j*× l* as shown below:

TPij =1 Tj is affiliated with Pi; i = 1;2;…; j� and j = 1;2;…; l�

0 otherwise

�ð9Þ

Various definitions have been given due to different aspects of product performance [1,50,51]. Ambiguous definitions oftencause problems for product designers of how to correctly interpret the technological performance. Therefore, this paper utilizesTRIZ to clarify this ambiguity.

3.5.2. Step 13: transformation by TRIZ 39 parametersTRIZ theory originated in patent analysis (primarily from the field of mechanical engineering) [46,47]. 39 functional

parameters of TRIZ are used to address the fuzzy definition of technology performance and consolidate the consensus betweendevelopment personnel. Group decisions among the development teammay be employed to translate standard patent technologyperformance. This step is a supplementary of the step 12. TRIZ is helpful to produce technology performance maps, providecomplete product design information and offer an innovative solution to the engineering conflicts in the phase of detailing designs.

3.5.3. Step 14: implementation of technology performance mapPatent technology performance maps may help to obtain information such as technology niches and uncovered areas. Patent

technology performance maps are then visually presented to R&D managers and product design engineers. They use them toconduct design-around, assess market development, and deploy patent portfolios.

se cite this article as: K. OuYang, C.S. Weng, A New Comprehensive Patent Analysis Approach for New Product Design inhanical Engineering, Technol. Forecast. Soc. Change (2011), doi:10.1016/j.techfore.2011.02.012


Fig. 7. Five-phases of the NCPA approach.


Fig. 7 illustrates the five-phase NCPA approach with its 14 steps. To enhance the efficiency of patent searches, commercialdatabases including Delphion, INPADOC, and Aureka are mutually employed, respectively.

4. A real case study

In this section, a case study is conducted to verify the NCPA model. Company A, a leading R&D and manufacturing institute ofspecialized vehicles, had applied theNPDprocedure for its new specialized vehicles (8×8). Therewas no similar product in themarket atthat time. The results of the industrial survey indicated the following: (1) the specialized vehicle (8×8) has a worldwide market, (2)patents for specialized vehicle (8×8) were applied for worldwide, such as in Europe (EP), the United States (US), Japan (JP) andinternational organizations (IO), (3) the newproduct could have significant potential in themarket, and (4) the suspension systemof thespecialized vehicles is not only the company A's core technology but also the key to fulfill the market's demand. In addition, customerneeds are investigated and confirmed. Now, NCPA is applied to the NPD of the suspension system of the specialized vehicle (8×8).

4.1. Phase I: industrial analysis and patent search strategy

4.1.1. Step 1Patents in databases are searched for by keywords, such as “Armored Vehicle”, “Wheeled Armored Vehicle”, etc. Industry structure

analysis indicates that there were twenty-five manufacturers worldwide producing these kinds of specialized vehicles like “MowagMotorwagenfabrik AG” of Switzerland, and etc. The specialized vehicles have global market with the greatest demand in Euro-American



Table 1List of experts.

No. Department Position Name Years of experience Degree

1 R&D Product engineer Chen. 5 Master2 R&D Product engineer Wang. 5 Master3 R&D Senior product engineer Huang. 10 Master4 R&D Manager Yin. 20 Master5 Operation Vice president Wu. 25 PhD6 Intellectual property Patent engineer Su. 10 Master7 Intellectual property Patent engineer Liu. 10 Master8 Intellectual property Manager Ou. 30 PhD

Table 2Important IPC codes for patents.

B01D 53/047 B01D 53/053 B60B 1/ B60B 11/ B60B 21/ B60B 23/B60B 25/ B60B 27/ B60B 3/ B60B 5/ B60B 7/ B60B 9/B60G B60Q 1/44 B60T 13/ B60T 15/ B60T 17/ B60T 7/B60T 8/ B60W 40/12 F15B 21/ F16F F16N 7/



markets. Although themarket share in Asia is still low, it indicates that there is a high demand for specialized vehicles. Themarket surveyhas also shown an annual growing tendency. In otherwords, there is a high potential for NPD for specialized vehicles in Asia. Technologystructure analysis of specialized vehicles indicates that the suspension system is the key technology and essential for entering newmarkets. In addition, technology development analysis suggests that it is very important to design a customized controllable hydro-pneumatic base suspension to meet the demand of the Asian market. Experts have been chosen for this study based on the position,experience andacademicdegree. Theexperts includepatent analysis experts andpatent searchexperts as show inTable 1. Patent analysisexperts spread across all levels of R&Ddepartment and are in charge of patent content analysis and assessment. Patent search experts arein charge of patent data searching, filtering, and patent document downloading.

4.1.2. Step 2We analyzed industry conditions and conducted expert interviews to understand suspension system technology structure,

development and technological categories to confirm important distinctions of key technologies in NPD. Three technologicalcategories have been organized with technological keywords as follows:

A. Actuating method: Mechanical spring, Fluid spring, Hydraulic dampers, Hydropneumatic suspension, Mechanical brakes,Hydraulic brakes, Pneumatic brakes, Compound brakes, Electric brakes, Air-over-hydraulic brakes.

B. Controlling method: Automatic control devices, Sensors, Control units.C. Structure form: Suspension arms, Axle supports, Stabilizer bars, Mounting bushings, Stoppers.

Searching the EPO database and cross comparing with keywords, the experts further confirmed the following important IPCcodes for suspension system patents as follows in Table 2.

IPC codeswereused as searching criteria in theDelphiondatabase andpatents from25 suspension systemmanufacturerswere found.

4.2. Phase II: selecting industry basic patent and building patent family

4.2.1. Step 3The searching results indicated that there were a total of 162 industry basic patents for suspension systems. Assignees were

spreadworldwide, and the top five assigneeswere located in Europe, America and Asia. In Table 3, only 16 of 25 suspension systemmanufacturers own suspension system patents. This means that the other 9 suspension system manufacturers did not even havetheir core technologies. They might produce suspension systems through purchase patent rights or by other means, and thensubsequently integrate themwithin their own systems. After being analyzed, the industry basic patent matrix is as follows:

εijh i

M×N; M = 16; N = 46

4.2.2. Step 4Utilizing “frequency of patent citation”, “patent title” and “abstract” as the judging criteria, 162 industry basic patents were

filtered by product engineers and then further confirmed by R&D department managers. 24 candidate patents of suspensionsystem patent family are listed in Table 4, and the matrix of candidate patents of patent family was as follows:

δijh i

m×n; m = 8; n = 7


Table 3The statistics of industry basic patents for suspension systems.

Item Assignee Amount Location

1 Giat Industries 46 France2 Mowag Motorwagenfabrik AG 27 Switzerland3 Komatsu 26 Japan4 Doosan 18 South Korea5 General Dynamics Land Systems 14 Canada6 Krauss 8 Germany7 Steyr Daimler Puch 7 Australia8 Reunert Mechanical Systems Limited 5 France9 Samsung Techwin 3 South Korea10 Recherche Et 2 Europe11 Magna Steyr 1 Austria12 Nextersystems 1 France13 Patria Vammas OY 1 Finland14 Singapore Technologies 1 Singapore15 Volkswagen AG 1 Germany16 Wegmann & Co. 1 GermanyTotal 162



4.2.3. Step 524 candidate patents of the patent family were linked to INPADOC through the Delphion database. The patent family data

was:

∑i∑jδij = s; where s = 179

And the patent family was:

PFcijh i

kc×lc; kc = 24; lc = 16

Next, selection of key patents was carried out based on 179 patents in 24 candidate patents.

4.3. Phase III: selecting key patents

4.3.1. Step 6The calculation of key patent priority number KPPNmc

c is listed as follows:

[KPPN(1)c ]={45, 36, 32, 18, 6, 8, 12, 30, 9, 24, 12, 48, 8, 6, 18, 8}

[KPPN(2)c ]={72, 45, 9, 60, 8, 18, 8, 24, 90, 9, 36, 27, 9, 1, 6, 8}

[KPPN(3)c ]={150, 240, 64, 80, 49, 180, 336, 56, 12, 72, 8, 90, 9, 81}

[KPPN(4)c ]={56, 280, 95, 310, 350, 580, 81, 648, 450, 90, 125, 210, 49}

[KPPN(5)c ]={285, 240, 160, 480, 576, 250, 380, 420, 280, 125, 81, 25}

[KPPN(6)c ]={60, 64, 28, 48, 20, 48, 8, 36, 35, 72, 48}

[KPPN(7)c ]={81, 240, 125, 312, 120, 78, 81, 72, 95, 16}

[KPPN(8)c ]={150, 240, 9, 8, 21, 68, 300, 120, 15, 49}

[KPPN(9)c ]={10, 64, 8, 72, 35, 12, 8, 52, 21}

[KPPN(10)c ]={90, 60, 49, 8, 36, 18, 10, 60}

[KPPN(11)c ]={15, 75, 54, 48, 9, 16, 18}

[KPPN(12)c ]={28, 42, 45, 18, 48, 60}

[KPPN(13)c ]={8, 8, 5, 18, 16, 8}

[KPPN(14)c ]={285, 480, 250, 512, 360}

[KPPN(15)c ]={8, 36, 45, 27, 18}

[KPPN(16)c ]={30, 24, 2, 9, 18}

[KPPN(17)c ]={120, 81, 196, 108}

[KPPN(18)c ]={30, 16, 9, 18}

[KPPN(19)c ]={2, 18, 16, 8}

[KPPN(20)c ]={6, 15, 24, 8}

[KPPN(21)c ]={95, 116, 126}

[KPPN(22)c ]={8, 6, 8}

[KPPN(23)c ]={105, 120, 324}

[KPPN(24)c ]={196, 124}

After filtering and selecting the 24 candidates of the key patents, they are listed as follows:

(KPPNc)*={648, 576, 512, 336, 324, 312, 300, 196, 196, 126, 90, 90, 75, 72, 72, 60, 48, 45, 30, 30, 24, 18, 18, 8}


Table 4Candidate patents of suspension system patent family.

EP1493985A1 EP1547891B1 EP1657470A1 CA2423222AA EP1676765A2 CN1796199AEP1757472A1 US3941061 EP351277B1 US5957046 US6017023 US6036201DE59809649C0 US6497262 US6662702 EP1222411B1 DE102004011113A1 EP1577580A2EP1493942A1 FR2720448A1 EP1786639A1 EP908346A1 US6848692 US7273117


The detailed information of the 24 candidates of the key patent is shown in Table 5.

4.3.2. Step 7The Scree of the suspension systems in different patent families KPPNmc

c is shown as Fig. 8. Fig. 8 clearly shows that the curves ofthe graph begin to flatten when KPPNmc

c ≦100. These patents were supposed to be disregarded.

4.3.3. Step 8Table 5 shows the information of the 24 candidates of the key patents. We conducted an expert interview to filter

representative patents, and determine key patent quantity from the Scree, and set the critical value C*=3. Key patents (KPPN*)n

were obtained upon determining the critical value C*, where:

Table 524 cand

Item

123456789101112131415161718192021222324

Symbol

PleaMec

KPPN�� n; n = 1;2;3: KPPN�� n = 648;576;512f g:

Three key patents were chosen, which were US6017023, US6036201 and US2003196433A1, respectively. These three patentsrepresented the hypothetical competitive patents for NPD. The results of patent analysis indicated that the patents were also thedominate technologies in recent years. US6017023 and US6036201 are owned by European and US companies, respectively. Thisimplies that these companies were not only the primary competitors in the specialized vehicle (8×8) market, but also that theseproducts are the mainstream products in the market. US2003196433A1 is owned by a Japanese firm named Komatsu. It is worthknowing that Komatsu applied for this patent from USPTO and has not introduced new products recently. It is more likely thatKomatsu might attempt to profit from patent authorization, or establish technological barriers to its competitors, or even increaseits bargaining power by owning this patent. Once key patents have been targeted, next is to trace their situation of citation throughsearching for their prior arts.

idates of key patents data.

Patent no. Patentfamily

Representativepatent

Assignee Degree of importance

US6662702 16 US6662702 GIAT IndustriesEP1222411B1 15 US6854358 Magna Steyr Powertrain AG & amp; Co KGUS6848692 14 US6848692B1 Mowag Motorwagenfabrik AG ⊚US6017023 13 US6017023 Mowag Motorwagenfabrik AG ☆US6036201 12 US6036201 GDLS, Inc. ☆US3941061 11 US3941061 Wegmann & Co.DE59809649C0 10 US6400135B1 Steyr-Daimler-Puch Spezialfahrzeug AG & Co.KG/Volkswagen AG ⊚US6497262 10 US6497262B1 Steyr-Daimler-Puch Spezialfahrzeug AG & Co.KG/Volkswagen AG ⊚EP351277B1 9 US4957033 GIAT IndustriesEP1547891B1 8 EP1547891B1 GIAT IndustriesEP1493985A1 7 EP1493985A1 GIAT IndustriesUS5957046 6 US5957046 Komatsu Ltd./Komatsu Industries CorporationEP908346A1 6 EP908346A1 GIAT IndustriesCA2423222AA 5 US2003196433A1 Komatsu Mining Germany GmbH ☆EP1757472A1 5 US2007044881A1 Steyr-Daimler-Puch Spezialfahrzeug GmbHDE102004011113A1 5 US7097021 Komatsu Forklift Co., Ltd./Komatsu Ltd.EP1657470A1 4 EP1657470A1 Krauss-Maffei Wegmann GmbH & amp; Co. KG △EP1676765A2 4 US2006137345A1 Doosan Infracore Co., Ltd.CN1796199A 4 US2006157028A1 Doosan Infracore Co., LtdEP1786639A1 4 EP1786639A1 Krauss-Maffei Wegmann GmbH & amp; Co. KGEP1577580A2 3 EP1577580A2 Krauss-Maffei Wegmann GmbH & amp; Co. KG △EP1493942A1 3 EP1493942A1 GIAT IndustriesUS7273117 3 US2005/0051990A1 GDLS, Inc. ⊚FR2720448A1 2 FR2720448A1 GIAT Industries △

s: (☆): Very important; (⊚): Important; (△): Less important.

se cite this article as: K. OuYang, C.S. Weng, A New Comprehensive Patent Analysis Approach for New Product Design inhanical Engineering, Technol. Forecast. Soc. Change (2011), doi:10.1016/j.techfore.2011.02.012


0

400

600

1Patent

11 13 15 17 19 21 233 5 7 9

Key Patent Priority Number

200

800

Fig. 8. The Scree of key patents of suspension systems.


4.4. Phase IV: key patent citation

4.4.1. Step 9This step conducted two stepwise patent citations to search prior arts of key patents by using the Delphion database. After two

stepwise citations, there were a total of 507 prior arts for 3 key patents. However, the Delphion database only contains fulldocumentation of 424 patents. Therefore, the Aureka database was used for cross comparing and 47 patents with fulldocumentationwere obtained. The remaining 36 patents only had the information about the “issue dates”, “titles”, and “abstracts”.Experts had identified that these 36 patents were old technologies without any reference value for new product design. These 36patents were eliminated by the experts' opinions. Finally, these 471 patents belonged to 78 companies and one company owned 9patents, which was the most. Therefore,

PleasMec

rn = 78; sn = 9:

4.4.2. Step 10Based on the technological keywords (Hydro-pneumatic, Height Adjustment, Automatic, Parallelogram) and the contents of

patent documents (such as “titles” and “abstracts”), experts further selected 60 potential basic technology patents out of 471 keypatents. And these 60 patents belong to 32 companies and the company with the most patents had seven. Therefore,

rn′ = 32; sn′ = 7

This step has effectively converged patent data from 471 patents into 60 patents and from 78 companies to 32 companies.

4.4.3. Step 11R&D managers engaged in a detail investigation focused on the “Drawing” and “Claims” in full patent documents. 17 key

technology patents were selected out of 60 candidates of key technology patents. And these 17 patents belonged to 14 companiesand the company with the most patents had four. Therefore, rn″ =14, sn″ =4.

These 17 patents were the most important prior arts that were relevant to the 3 competitive objects for a new product. Andthese 17 patents were also the primary reference of new product design-around.

Table 6Technological categories of suspension system.

Technology category Characterization Technology code

1 Actuating method T1

1.1 Hydropneumatic T111.2 Hydraulic T121.3 Pneumatic T13

2 Controlling method T2

2.1 Signal control T212.2 Detect and sensor T222.3 Valve and circuit T23

3 Structure form T3

3.1 Upper and lower control arm T313.2 Ball joint T32



Table 7Technological performance of suspension system.

Performancecode

Characterization Parameter of TRIZ

F1 Inexpensive No.32 (manufacturability)F2 With a minimum of lateral movement No.13 (stability of object)F3 Improved cushioning No.31 (harmful side effects)F4 With a limit stop for the bottom surface of the sensor No.28 (accuracy of measurement)F5 Rise length No.3 (length of moving object)F6 Helpful adjustable track tension No.30 (harmful factors acting on object)

No.33 (convenience of use)F7 The distance can be altered independently for the front,

rear, and sides of the vehicleNo.37 (complexity of control)

F8 Ensured safety No.14 (strength)F9 A fully interchangeable suspension assembly No.35 (adaptability)F10 Automatic control No.38 (level of automation)F11 Repair-friendly No.34 (repair ability)F12 Continuously variable adjustable vehicle ground clearance

and variable wheel-track width respectivelyNo.33 (convenience of use)No.37 (complexity of control)

Table 8Technological performance matrix.

T T1 T2 T3

F T11 T12 T13 T21 T22 T23 T31 32

F1 1 1 1F2 1 2 2 2 1 1F3 1 2 2 2F4 2 2 1F5 3 6 6 14 11 12F6 3 3 3F7 2 2 2F8 2 2 1F9 1 1F10 1 2 3F11 1 1F12 1



4.5. Phase V: technology performance analysis

4.5.1. Step 12We conducted technology performance analysis on these 17 patents. Expert analysis obtained 8 technology items of 3

categories which were “Actuating method”, “Controlling method”, and “Structure form”, as shown in Table 6. Where: j⁎=8.Next, experts defined technological performance of each key technology patent based on their “drawing”, “Claims” and

“Inventive summary”. Experts finally categorized 12 items of technological performance which are listed in Table 7. Where:l⁎=12.

4.5.2. Step 13These 12 technological performances had one-to-one correspondence with the parameters of TRIZ as assessed by expert

analysis and group decision as shown in Table 7.Next, we combined the technological performance with TRIZ parameters into the technological performance matrix as shown

in Table 8.

4.5.3. Step 14Finally, we converted the technological performance matrix into a technological performance map as shown in Fig. 9. Fig. 9

gives the whole overview of performance distribution for related technology patents, and the size of circles/ellipses depicts thetechnological performance and the numbers associated with the eclipses accordingly. For the results of analysis, the technologicaldevelopment of suspension systems is concentrated in the “controllingmethod” and the “actuatingmethod”, while performance isfocused on enhancing of “No.3: Length of moving object”. The technologies of the “Controlling method” and “Actuating method”are distributed among the American and Japanese markets. Japanese have the greatest advanced development in “Controllingmethods”, while their development in “Actuating methods” is relatively weaker. The technologies of “Structure form” are mainlydeveloped by South Korean firms. These technologies have no portfolio value because of they are least important in quantity andwith different models in different products. From the technology performancemaps, it can be seen that technology performance isconcentrated in the intersection of “Controllingmethod” and “No.3: Length of moving object”. Furthermore, experts' opinions also


Hydropneumatic

Hy-draulic

Pneu-matic

SignalControl

Detect &Sensor

Valve &Circuit

Upper and LowerControl Arm

Ball Joint

T11 T12 T13 T21 T22 T23 T32 T33

No. 32 F11 1 1

No. 13 F21 2 2 2 1 1

No. 31 F31 2 2 2

No. 28 F42 2 1

No. 3 F53 6 6

No. 30, 33 F63 3 3

No. 37 F72 2 2

No. 14 F82 2 1

No. 35 F91 1

No. 38 F101 2 3

No. 36 F111 1

No. 33, 37 F121

Actuating Method Controlling Method Structure form

14 11 12

Performance

TechnologyHydro

pneumaticHy-

draulicPneu-matic

SignalControl

Detect &Sensor

Valve &Circuit

Upper and LowerControl Arm

Ball Joint

T11 T12 T13 T21 T22 T23 T32 T33

No. 32 F11 1 1

No. 13 F21 2 2 2 1 1

No. 31 F31 2 2 2

No. 28 F42 2 1

No. 3 F53 6 6

No. 30, 33 F63 3 3

No. 37 F72 2 2

No. 14 F82 2 1

No. 35 F91 1

No. 38 F101 2 3

No. 36 F111 1

No. 33, 37 F121

Actuating Method Controlling Method Structure form

14 11 12

Technology

Fig. 9. The technological suspension system performance map.

Table 9NCPA overall efficiency of new product design.

Item Product characteristics Number or labor Expert limit Patent database Search speed Cost

A model Complex 8 Low 80 High HighB model Simple 11 High 1 Slow LowBetter model A A A A A B

Note: A model: NCPA; B model: Chen and Chen [17].



suggest that this is the easiest area to conduct a new product design-around. In other words, this is the core technology of vehiclesuspension system development that requires technological concentration. This area is also an intensely competitive area fortechnology digging and patent portfolio planning in NPD design.

5. Conclusion and discussion

5.1. Conclusion

Chen and Chen proposed an approach which includes three stages and seven steps for converting patent data into designstrategies [17]. This research compares with a similar patent analysis model from Chen and Chen. Chen and Chen devoted 11human resources (examiners of patent design) to design a less complicated mechanical element-bicycle frame [17]. On thecontrary, this research only devoted 8 human resources (related industry labor) to complete a more complicated patent analysisfor a mobile suspension system. The model proposed by this research is more efficient. Moreover, in Chen and Chen's study, theyfocused merely on the database information from the Taiwan Property Office, but this research covers in wider range ofinternational Intellectual Property Office databases. The quantity of intellectual property is rather more on scale. Therefore, theresults of research are more complete and accurate. Besides, Chen and Chen used manpower to download database information



one-by-one [17], but this research combined two commercial databases, which are Delphion and Aureka, for obtaininginformation quickly. The information for analysis is systematically arranged, and patent titles and summaries are selected inadvance, before downloading the full text. In this way, of course, the cost will indeed increase, but the time spent for analyzinginformation is significantly decreased. In sum, the approach proposed by this research increases overall efficiency of new productdesign, but also involves higher cost than other approaches. The two researches are compared in Table 9.

The results of analysis allow the following:

(1) Rapid extraction of patent intelligence required for research.(2) Discovery of important key patents in new product design.(3) Creation of a complete technological performance map of patents.(4) Strategy for patent portfolio.(5) Ability to obtain technological niche for performance.(6) Ability to closely connect with TRIZ to allow better fit of IPDP.(7) Enhanced efficiency of new product design.

The findings of the paper are as follows:

A. Patent information is an important resource in product development. To quickly obtain complete and accurate technologicalperformance information, the analysis process must be subject to both qualitative and quantitative analysis. First, focus on thepatent family is meant to eliminate the “noise effect” and quickly obtain key patents. But without structured and qualitativeexpert analysis, unrelated patents will still remain. For example, in phase IV of NCPA, after filtering by frequency of patentcitations and inspecting by “Title” and “Abstract” of patents, experts still found that patent US04568101 was not relevant to thepurpose of study.

B. Patent citations help to identify intelligence relevant to key patents. Nevertheless, core values in mechanical engineering areoften represented in “Drawings” of patent documents. If technology performance analysis only focuses on the “Title” and“Abstract” of a patent, the information discovered is extremely limited, and therefore requires the additional cross-referencingof “Claims”, “Summaries of invention” and “Drawings” for completeness. Moreover, product function definitions must bedetermined through collaboration of the entire team for greater consensus to facilitate detailed design of new products.

C. This research defines product performance through TRIZ. Therefore, 40 principles of the TRIZ contradiction function matrixmay be combined to solve engineering technology contradictions during the product detail design stage. This allows productdesigners to convert technological contradictions into physical contradictions to assist the patent design-around.

5.2. Discussion

In this paper, the Scree test is used for selection of the most representative patents. The 8th step of the NCPA may lead to thediscarding of some covered niche applications. However, it is very likely that a lot of unnecessary patents still remain after patentsearching without effective filtering which may affect the effective application of patent intelligence.

Therefore, the purpose of acquiring adequate patent information is to better predict technology performance niches for thedesign-round in NPD. This research adopts the criteria for patent value assessment developed by Wartburg et al., which includesthree indicators and fourteen indices [33]. In addition, we invited experts specializing in mechanics with significant workingexperience in vehicle suspension system design to assess the patent values in different patent families. Finally, we provided themost representative patents through patent family filtering with the Scree test. That is the goal of the design-around in NPD.

Nevertheless, we made use of technological specialists with practice experiences the filtered the results of the Scree test toselect the most representative of the key patents and to avoid deleting important patents. But in the end we still needed theappraisement of senior management to decide what the most representative key patents were in the patent family through thereviewing of technology and administration for new product design.

The results of patent value assessment may be different due to the differences between the characteristics of technology andindustry on various NPD cases. The Scree test provides quantitative analysis. The senior management will assess the integralrequirements for R&D, which decreases the inaccuracy of step 8 in NCPA.

In conclusion, NPD of other mechanic systems is suggested for future research to ensure the external validity of NCPA. Inaddition, the criteria of patent value assessment is another important issue for future research, such as indices like patent royalties.

References

[1] K.T. Ulrich, S.D. Eppinger, Product Design and Development, 4th Ed.., McGraw-Hill, Singapore, 2007, pp. 15–17.[2] M.E. McGrath, Setting the PACE in Product Development: A Guide to Product and Cycle-time Excellence, Rev. Ed.Butterworth-Heinemann, Massachusetts,

1996.[3] G. Pahl, W. Beitz (Eds.), Engineering Design — A Systematic Approach, 3rd Ed., Springer, London, 2007.[4] R.G. Cooper 3 rd (Ed.), Winning at New Products: Accelerating the Process from Idea to Launch, Basic Books, New York, 2001.[5] Y. Akao, G.H. Mazur, The leading edge in QFD: past, present and future, Int. J. Qual. Reliab. Manage. 20 (1) (2003) 20–35.[6] T. Lager, The industrial usability of quality function deployment: a literature review and synthesis on a meta-level, R&D Manage. 35 (4) (2005) 409–426.[7] Y.S. Kim, D.S. Cochran, Reviewing TRIZ from the perspective of axiomatic design, J. Eng. Des. 11 (1) (2000) 79–94.[8] H. Ito, T. Yamashina, H. Kawada, Innovative product development process by integrating QFD and TRIZ, Int. J. Prod. Res. 40 (5) (2002) 1031–1050.




[9] Z. Griliches, B.H. Hall, A. Pakes, R&D, patents, andmarket value revisited: is there a second (technological opportunity) factor? Econ. Innov. NewTechnol. 1 (3)(1991) 183–201.

[10] F. Narin, Patents as indicators for the evaluation of industrial research output, Scientometrics 34 (3) (1995) 489–496.[11] H. Grupp, U. Schmoch, Patent statistics in The Age of Globalization: new legal procedures, new analytical methods, new economic interpretation, Res. Policy

28 (4) (1999) 377–396.[12] A.B. Jaffe, M. Trajtenberg, M.S. Fogarty, Knowledge spillovers and patent citations: evidence from a survey of inventors, Am. Econ. Rev. 90 (2) (2000)

215–218.[13] B.H. Hall, A. Jaffe, M. Trajtenberg, Market value and patent citations, Rand J. Econ. 36 (1) (2005) 16–38.[14] J.W. Robert, L.P. Alan, C. Cherie, Functional analysis deriving systems knowledge from bibliographic information resources, Inf. Knowl. Syst. Manag. 1 (1)

(1999) 45–61.[15] B.U. Yoon, C.B. Yoon, Y.T. Park, On the development and application of self-organizing feature map-based patent map, R&D Manage. 32 (4) (2002) 291–300.[16] M.G. Moehrle, L. Walter, A. Geritz, M.I. Sandra, Patent-based inventor profiles as a basis for human resource decisions in research and development, R&D

Manage. 35 (5) (2005) 513–524.[17] A. Chen, R. Chen, Design patent map: an innovative measure for corporative design strategies, Eng. Manage. J. 19 (3) (2007) 14–29.[18] L. Berkowitz, Getting the most from your patents, Res. Technol. Manage. 36 (2) (1993) 26–31.[19] H. Ernst, B. Fabry, J.H. Soll, Enhancing market-oriented R&D planning by integrated market and patent portfolios, J. Bus. Chem. 1 (1) (2004) 2–13.[20] R. Haupt, M. Kloyer, M. Lange, Patent indicators for the technology life cycle development, Res. Policy 36 (3) (2007) 387–398.[21] E.S. Simmons, “Black sheep” in the patent family, World Patent Inf. 31 (1) (2009) 11–18.[22] C. Robinson, P. Boyle, S. Al-Jurf, Court finds patent creates resumption of market power in antirust tying actions, Wash. Leg. Found. 15 (6) (2005) 1–2.[23] D. Harhoff, F.M. Scherer, K. Vopel, Citations, family size, opposition and the value of patent rights, Res. Policy 32 (8) (2003) 1343–1363.[24] van P. Bruno, van Z. Nicolas, A brief history of space and time: the scope-year index as a patent value indicator based on families and renewals, Scientometrics

75 (2) (2008) 319–338.[25] A.F. Breitzman, M.E. Mogee, The many applications of patent analysis, J. Inf. Sci. 28 (3) (2002) 187–205.[26] J.M. Podolny, T.E. Stuart, A role-based ecology of technological change, Am. J. Sociol. 100 (5) (1995) 1224–1260.[27] T.E. Stuart, J.M. Podolny, Local search and the evolution of technological capabilities, Strateg. Manage. J. 17 (7) (1996) 21–38.[28] M. Reitzig, What determine patent value? Insights from the semiconductor industry, Res. Policy 32 (1) (2003) 13–26.[29] K.K. Lai, S.J. Wu, S.B. Chang, Establishing an industry classification system—from the viewpoint of patent co-citation, J. Manage. 22 (2) (2005) 261–277.[30] F. Narin, E. Noma, R. Perry, Patents as indicators of corporate technological strength, Res. Policy 16 (2) (1987) 143–155.[31] A.B. Jaffe, Technological opportunity and spillovers of R&D: evidence from firms' patents, profits, and market values, Am. Econ. Rev. 76 (6) (1986) 984–1001.[32] E. Duguet, M. MacGarvie, How well do patent citations measure flows of technology? Evidence from French innovation survey, Econ. Innov. New Technol. 14

(5) (2005) 375–393.[33] I.V. Wartburg, T. Teichert, K. Rost, Inventive progress measured by multi-stage patent citation analysis, Res. Policy 34 (10) (2005) 1591–1607.[34] A. Breitzman, P. Thomas, Using patent citation analysis to target/value M&A candidates, Res. Technol. Manag. 45 (5) (2002) 28.[35] M. Trajtenberg, A penny for your quotes: patent citations and the value of innovations, J. Econ. 21 (1) (1990) 172–187.[36] D. Harhoff, F. Narin, F.M. Scherer, K. Vopel, Citation frequency and the value of patented inventions, Rev. Econ. Stat. 81 (3) (1999) 511–515.[37] G. Park, Y. Park, On the measurement of patent stock as knowledge indicators, Technol. Forecast. Soc. Change 73 (7) (2006) 793–812.[38] M. Hirschey, V.J. Richardson, Are scientific indicators of patent quality useful to investors? J. Empir. Finance 11 (1) (2004) 91–107.[39] S. Nagaoka, Determinants of high-royalty contracts and the impact of stronger protection of intellectual property rights in Japan, J. Jpn. Int. Econ. 19 (2)

(2005) 233–254.[40] Z. Deng, B. Lev, F. Narin, Science and technology as predictors of stock performance, Financ. Anal. J. 55 (3) (1999) 20–32.[41] M.-C. Hu, Knowledge flows and innovation capability: the patenting trajectory of Taiwan's thin film transistor-liquid crystal display industry, Technol.

Forecast. Soc. Change 75 (9) (2008) 1423–1438.[42] Y.-S. Chen, K.-C. Chang, The relationship between a firm's patent quality and its market value— the case of US pharmaceutical industry, Technol. Forecast. Soc.

Change (2009), doi:10.1016/j.techfore.2009.06.003.[43] H. Ernst, Patent information for strategic technology management, World Patent Inf. 25 (3) (2003) 233–242.[44] A.K. Chakrabarti, Industry characteristics influencing the technical output: a case of small and medium size firms in the US, R&D Manage. 21 (2) (1991)

139–152.[45] Y.G. Lee, J.D. Lee, Y.I. Song, S.J. Lee, An in-depth empirical analysis of patent citation counts using zero-inflated count data model: the case of KIST,

Scientometrics 70 (1) (2007) 27–39.[46] G.S. Altshuller, Creativity as an Exact Science: the Theory of Inventive Problem Solving, Gordon and Breach, New York, 1988.[47] M.G. Moehrle, How combinations of TRIZ tools are used in companies — results of a cluster analysis, R&D Manage. 35 (3) (2005) 285–296.[48] A.L. Porter, S.W. Cunningham, Tech Mining: Exploiting New Technologies for Competitive Advantage, John Wiley & Sons, New York, 2004.[49] R.B. Cattell, The scree test for the number of factors, Multivariate Behav. Res. 1 (1) (1966) 245–276.[50] T. Osteras, D.N.P. Murthy, M. Rausand, Product performance and specification in new product development, J. Eng. Des. 17 (2) (2006) 177–192.[51] D.G. Ullman, The Mechanical Design Process, 4th Ed..McGraw-Hill, New York, 2009.

Dr. OuYang is an associate professor in Department of Business Administration in National Yunlin University of Science and Technology. His research focused ontechnology management, innovation management, and patent analysis.

Dr. Weng is an associate professor in Takming University of Science and Technology. His research focuses on social network, technology management, strategicmanagement and patent analysis.




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