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Research Policy 40 (2011) 391–402

Contents lists available at ScienceDirect

Research Policy

journa l homepage: www.e lsev ier .com/ locate / respol

nalysis of sources of innovation, technological innovation capabilities, anderformance: An empirical study of Hong Kong manufacturing industries

ichard C.M. Yam ∗, William Lo, Esther P.Y. Tang, Antonio K.W. Lauhe Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong

r t i c l e i n f o

rticle history:eceived 27 October 2009eceived in revised form 27 August 2010ccepted 15 October 2010vailable online 24 November 2010

eywords:egional innovation systemirm innovation system

a b s t r a c t

The concept of the regional innovation system (RIS) has been developed into an important framework forevaluating innovation performance. The study reported in this paper explores the relationship betweenthe RIS and the firm’s innovation system (FIS) according to the basic premise that firms that betterutilize sources of information (SI) available within their regional innovation system (RIS) perform betterdue effect this has in enhancing the firm’s technological innovation capabilities (TICs). The differentinnovation capabilities of a firm are regarded as the key components of the firm’s innovation system.The sources of information available within an RIS include external sources (EXT) and external expertorganizations, the latter of which are referred to as knowledge-intensive business services (KIBS). Thisstudy also explores the dual role of KIBS as both sources of and bridges for innovation in the RIS. Data

tilization of innovation sources

nowledge-intensive business servicesechnological innovation capabilities

were obtained through a mailed survey using a self-administered questionnaire. The utilization conceptand the dual role of KIBS were verified. The results show that externally available information affectsall innovation capabilities of the firm, while external expert organizations affect only the firm’s R&Dand resources allocation capabilities. This study contributes to the RIS literature by providing empirical

n int

evidence on how firms cacompetitiveness.

. Introduction

.1. The national innovation system (NIS)

The OECD (National Innovation Systems, OECD, 1997) defines aational innovation system as the flows of technology and infor-ation among people, enterprises, and institutions that are the

ey to the innovation process at the national level. Many influen-ial studies have been carried out in this area in recent decades,ncluding those of Freeman (1987), Porter (1990), Lundvall (1992),elson et al. (1993), OECD (1997), Edquist et al. (1997), and Carlssont al. (2002). These investigations have described the link betweennnovation and competitive and economic outcomes at the nationalevel (Porter, 1990; Nelson et al., 1993) and their results have been

idely adopted in the national science & technology policy researchomain. Moreover, they have collectively formulated an analyti-

al framework for NIS and provided a research background for thetudy of regional innovation systems (RISs) and firm innovationystems (FISs).

∗ Corresponding author at: City University of Hong Kong, Tai Chee Avenue,owloon Tong, Hong Kong. Tel.: +852 2788 8417; fax: +852 2788 8423..

E-mail addresses: mery@cityu.edu.hk (R.C.M. Yam), lowailam@hkpc.org (W. Lo),sesther@polyu.edu.hk (E.P.Y. Tang), antonio lau2000@hotmail.com (A.K.W. Lau).

048-7333/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.respol.2010.10.013

eract with the RIS by utilizing SI to enhance their TICs and achieve global

© 2010 Elsevier B.V. All rights reserved.

1.2. The regional innovation system

Braczyk et al. (1996) first delineated the concept of the RIS.Within a short time, various researchers came to apply the NISconcept in studying RIS (Braczyk et al., 1996; Cooke et al., 1997;Morgan and Nauwelaers, 1999; Koschatzky et al., 2000; Cooke,2001; Doloreux, 2002). Studies adopting the RIS approach examineinnovating firms in the context of the external institutions, gov-ernment policies, competitors, suppliers, customers, value system,and social and cultural practices that affect their innovation activi-ties (Kumaresan and Miyazaki, 1999; OECD, 1999). The focus is onthe generation and diffusion of knowledge among RIS actors thattakes place outside the boundary of the firm. However, most studiesin the extant literature have concentrated on theoretical discus-sions on the composition of innovation actors. Acs et al. (2002)insisted that the problem of measuring innovation effectivenessat the regional level had not yet been completely resolved. Noactive discussion has yet taken place on how a firm can interactwith the RIS to enhance its capacity to innovate and achieve globalcompetitiveness.

1.3. The firm innovation system

The firm innovation system can be defined as an interactiveprocess that involves the generation, adoption, implementation,

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nd incorporation of new ideas and practices within the firm (Vane Ven et al., 1989; Carlsson et al., 2002). The main feature ofhis system is the ability of the actors to generate, diffuse, andtilize innovations that have economic value, collectively knowns the firm’s technological innovation capabilities (TICs). Innova-ion activity within a firm is an interactive process characterizedy technological interrelatedness between various sub-systems orub-processes (Teece, 1996). These sub-processes include those ofoncept generation, product development, production, technologycquisition, leadership, resource provision, and system and toolrovision (). TICs can be enhanced by developing the firm’s abil-

ty in each sub-process. Various studies have sought to identify theIC components that are important to firms (Adler and Shenbar,990; Christensen, 1995; Yam et al., 2004). It is recognized that arm with greater TICs is able to achieve higher levels of organiza-ional performance and effectiveness. Hence, the TICs of a firm arerucial in sustaining its global competitiveness. However, there isittle empirical evidence on how firms harness the benefits of theIS to improve their technological innovation capabilities (Romijnnd Albaladejo, 2002).

. The link between regional innovation systems and firmnnovation systems

In recent years, some researchers have started to investigatehe possibility of integrating the RIS and FIS approaches. Galendend Fuente (2003) proposed the idea of considering both externalnd internal factors in studying the innovation process. Romijn andlbaladejo (2002) identified a range of internal and external factorselated to innovation performance among electronics and softwareevelopment firms in the UK. Caloghirou et al. (2004) showed thatoth firm innovation capabilities and openness towards knowledgeharing are important in bolstering innovation performance. Thistream of the innovation literature demonstrates a growing interestn integrating the RIS and FIS approaches.

.1. Organizational learning

Technological innovation can be conceptualized as a learningrocess (Cohen and Levinthal, 1989; Garvin, 1993; Dodgson, 1993;itt et al., 2000). Learning results in enhancement of the knowl-dge and skills firms need to choose, install, operate, maintain,dapt, improve, and develop their technology (Hamel and Prahalad,990), i.e. the TICs of a firm. In a world of increasing competitionnd technological change, the generation and diffusion of innova-ions increasingly rely on new technological knowledge generatedot only through internal R&D departments, but also by the firm’s

nteraction with external sources of innovation (SI), particularly inhe region in which the firm operates (Romijn and Albaladejo, 2002;aloghirou et al., 2004). Hence, a critical component of successfulechnological innovation is the ability of a firm to exploit and utilizexternal knowledge in the RIS (Lin et al., 2002).

On the other hand, organizational learning theory suggests thatfirm’s innovation performance is an outcome of increases in its

nowledge base (Henderson and Cockburn, 1996a,b). In additiono the contribution made by knowledge-enhancing investmentsver time, firms can grow their knowledge by acquiring exter-al knowledge bases (Cohen and Levinthal, 1989; Huber, 1991).lthough the relationship between firms’ investments in knowl-dge and their technological innovation performance has been

tudied intensively (Griliches, 1990), relatively few studies haveocused on the role of acquisitions in growing the firm’s knowledgease (Huber, 1991). This indicates that the relationship betweenbtaining technological know-how and developing technologicalnnovation capabilities is becoming an important area of study in

licy 40 (2011) 391–402

the technological innovation arena. Many studies have consideredthe impact of external knowledge bases or SI on the technologicalinnovation performance of a firm (Uzun, 2001; Todtling and Trippl,2005). However, few prior investigations have found that the firm’sTICs are enhanced by utilizing SIs within the RIS (i.e. the utilizationconcept).

2.2. Knowledge-intensive business services (KIBS)

In addition to highlighting the key role played in technolog-ical development by fostering the firm’s TICs, researchers havealso pinpointed the importance of effective intermediaries betweenfirms and knowledge providers (Dodgson and Bessant, 1996).When there is a wide gap between suppliers and users of tech-nology, intermediary agencies help to facilitate the absorption ofknowledge. This is particularly true for small and medium-sizedenterprises (SMEs) (Rothwell and Dodgson, 1991). Muller (2001)defined intermediary agencies as KIBS, or organizations such asconsultancy firms, research institutes, and universities that provideservices adding a high level of intellectual value to other firms. KIBSnot only have a direct impact on the innovation activities of SMEs,but also have an indirect influence on such activities by paving theway for the absorption of knowledge from other sources of innova-tion (Muller and Zenker, 2001). The role of KIBS therefore appearsto be twofold in that they act as both a “source of innovation” and a“bridge for innovation”. The study reported in this paper exploredthis dual role of KIBS in integrating the RIS and the FIS.

3. The regional innovation system in the Hong Kong/PearlRiver Delta Region

3.1. The RIS in Hong Kong

In the 1960s–1970s, Hong Kong’s wider manufacturing industrysuccessfully developed a reputation as a low-cost, labor-intensiveoriginal equipment manufacturing (OEM) center by producinggoods for export to Western countries. The Hong Kong govern-ment adopted a “positive non-intervention” policy in the areasof technological development by providing funding for infrastruc-ture development instead of directly subsidizing sub-industrieswith minimal institutional support. The technological and market-ing support given to the industry was very limited. Technologicaladvances in Hong Kong trailed those made in the three other “littleAsian dragons”: South Korea, Singapore, and Taiwan.

Ever-increasing wages and land prices in the late 1970s seri-ously threatened the OEM manufacturing strategy adopted by mostmanufacturing firms in Hong Kong. With the introduction of theopen door policy in China at about the same time, Hong Kong’slabor-intensive industries were substantially relocated to the PearlRiver Delta (PRD) in the province of Guangdong, adjacent to HongKong. This relocation helped Hong Kong manufacturers to developa highly competitive low-cost manufacturing base in the PRD dueto the vast supply of cheap labor and the low cost of land in China.However, this transition also delayed technological innovation inHong Kong (Lo et al., 2001).

Britain handed the sovereignty of Hong Kong over to China in1997. The Hong Kong Special Administration Region (HKSAR) gov-ernment revisited its technology policies and took a number ofmeasures to facilitate technology transfer and foster a culture ofinnovation in the community. For example, the Innovation and

Technology Fund (ITF) was set up to finance innovation and tech-nology programs relevant to industry, and the Applied ResearchFund (ARF), a government-owned venture capital fund, was setup to support local technology ventures with commercial poten-tial. The establishment of the Hong Kong Science and Technology

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arks Corporation (HKSTPC) offered one-stop support servicesor technology-based companies and activities. Other commis-ions and institutes were also formed to encourage investmentn technology. Most of these measures were principally designed

ith the manufacturing sector in mind. Manufacturing firms werencouraged to apply for the abovementioned forms of support inonjunction with their own industrial associations, universities, oronsulting firms.

.2. The RIS in the PRD

Due to the strong presence of Hong Kong manufacturers in theRD, their success in low-cost manufacturing and their reluctanceo pursue technological advances affected technological develop-

ent in this region of China. In addition, the scarcity of naturalesources in the PRD limited its ability to contribute to the devel-pment of heavy industry, the focal point of China’s five-year plansn the 1950s, 1960s, and 1970s. Hence, the PRD became a technol-gy laggard in comparison with other parts of China. This situationad not changed significantly until recently. China’s reform pro-ram initiated in 1979 facilitated a very successful low-cost HK/PRDanufacturing collaboration that substantially improved economic

rowth in the PRD but hindered its technological development.lthough China has started to re-establish its national innovationystem since the 1990s (Zhou, 2005), the scope of the measuresaken in this regard only recently included technological devel-pment of the PRD. Given the isolation of the PRD from China’sndustrial and technological heartland, the support it received fromhe central government was minimal. As a result, the innovationystem of the PRD was very immature during the period cov-red by this study. Most HK manufacturers still relied on the HKnnovation system rather than the PRD RIS for technological devel-pment.

. Research model

In exploring the relationship between the RIS/FIS, this studyocused on two components of the RIS only—external sources ofnnovation (EXT) and KIBS—to supplement the knowledge gap inhe extant literature. Because most manufacturers in the Hongong/PRD region function in a largely homogenous context of tech-ological lags and institutional support, factors influencing the

ndustrial structure and the institutional environment were notpecifically analyzed.

.1. Technological innovation capabilities

TICs are defined as a comprehensive set of firm characteris-ics that facilitate and support the firm’s technological innovationtrategies (Burgelman et al., 2004). Various researchers have devel-ped their own approaches to assessing a firm’s TICs, such ashe asset approach (Christensen, 1995), the process approachChiesa et al., 1996; Burgelman et al., 2004), and the functionalpproach (Yam et al., 2004). These approaches and the elementsxamined in assessing the TICs of a firm are summarized inable 1.

Among these approaches, the asset and process approachesre somewhat more difficult to comprehend than the functionalpproach. The latter approach not only has the advantage of beingasier to understand, but also facilitates adoption of the multi-

nformants approach employed in the survey conducted for thistudy. It has also been used to assess the TICs of Chinese companiesYam et al., 2004), enterprises that have a culture similar to thatf Hong Kong manufacturers. Hence, the functional approach wasdopted in this study as it seemed to be more suitable for Hong

licy 40 (2011) 391–402 393

Kong manufacturers.

4.2. Utilization of sources of innovation and technologicalinnovation capabilities

Studies of technological innovation have traditionally focusedon firm-specific determinants such as R&D activities and firm size.Recent studies have tended to incorporate determinants externalto firms, especially with respect to external sources of innovationfirms use to develop or improve their products or processes. Thesource of innovation is important because it determines the capa-bilities a firm must possess to adopt the necessary innovationsin time to achieve success in the marketplace. They commentedthat innovations are not only determined by factors internal tofirms, but also by an interactive process involving relationshipsbetween firms and different actors in the RIS. Firms cannot inno-vate in isolation; they tend to complement their ability to createknowledge in-house by utilizing knowledge from external sourcesof innovation. This can be achieved by learning by using, learningby doing, and learning by sharing through formal or informal net-works within the RIS (Lengrand and Chatrie, 1999; Foray, 2000).Interaction with external sources of innovation can provide miss-ing external inputs into the learning process that the firm cannotprovide itself (Romijn and Albaladejo, 2002) and improve firm per-formance (Caloghirou et al., 2004). Hence, technological innovationcan be conceptualized as a learning and utilization process (Cohenand Levinthal, 1989; Dodgson, 1993; Garvin, 1993; Hitt et al., 2000).Firms can reinforce their technological innovation capability byimporting technologies and then diffusing, assimilating, commu-nicating, and absorbing them into their organizations (Hamel andPrahalad, 1990). Teece et al. (1997) also ascertained that the abil-ity of a firm to acquire, utilize, and develop valuable resources andcapabilities is largely related to its acquisition of knowledge exter-nal to the firm and its integration of such knowledge with the firm’sown.

Proponents of the systems of innovation approach argue thatinnovation should be seen as an evolutionary, non-linear, and inter-active process requiring intensive interaction with different actorsin the RIS such as suppliers, customers, and even competitors, aswell as with other organizations (Todtling and Trippl, 2005) suchas universities, research centers, educational institutions, financ-ing institutions, standard-setting bodies, and industry associations.The generation and utilization of knowledge depend on the fre-quency and density of the firm’s interactions with external sourcesof innovation and its openness to external knowledge (Caloghirouet al., 2004).

4.2.1. Sources of innovation—external information (EXT)Souitaris (2001) distinguished efforts firms make to establish

knowledge flow channels and linkages into two categories: (1)those involving the scanning of external information; and (2) thoseinvolving cooperation with external organizations. SI is includedin the first knowledge acquisition category and includes techni-cal reports, the use of patent databases, attendance at conferences,and scientific publications. Patents are considered a useful sourceof knowledge on the technical characteristics of protected inven-tions. The use of patent databases may provide valuable knowledgeon potentially profitable research areas or on how to invent arounda patent (Arundel, 2001). Journals provide are a more conven-tional means of acquiring codified knowledge. The use of patentsand journals reflects an interlay between basic/applied scientific

research and technological development in the context of corpo-rate R&D efforts. The same is true of conferences: Caloghirou et al.(2004) classified them as the “external source of knowledge”. Hisstudy proved that scanning external knowledge via scientific orbusiness journals is beneficial to the firm and that firms regularly

394 R.C.M. Yam et al. / Research Policy 40 (2011) 391–402

Table 1Different approach and elements in assessing TICs.

Proposed by Study approach TIC elements

Christensen (1995) Asset approach • Science research asset• Product innovation asset• Esthetics design asset

Burgelman et al. (2004) Process approach • Capabilities of a firm in• Resources availability and allocation• Understanding competitor innovative strategy and market• Understanding technological developments relevant to firm• Structural and cultural affecting internal innovative activities• Strategic management capability to deal with internal innovative activities

Chiesa et al. (1996) Process approach • Concept generation capability• Process innovation capability• Product development capability• Technology acquisition capability• Leadership capability• Resources deployment capability• Capability in effective use of system and tools

Yam et al. (2004) Functional approach • Learning capability• R&D capability• Resources allocation capability

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se this method to find new ideas for innovation. Thus, we pro-osed that EXT provide market knowledge in the form of patents,

ournals, equipment, etc., and formulated the first set of hypothe-es as follows.H1a: EXT has a positive relationship with learningapability.H1b: EXT has a positive relationship with R&D capabil-ty.H1c: EXT has a positive relationship with resource allocationapability.H1d: EXT has a positive relationship with manufactur-ng capability.H1e: EXT has a positive relationship with marketingapability.H1f: EXT has a positive relationship with organizationalapability.H1g: EXT has a positive relationship with strategic plan-ing capability.

.2.2. Sources of innovation—external organizations (KIBS)The second category of sources of innovation is cooperation with

xternal organizations (KIBS). The external knowledge to whichrms may seek to gain access in the course of their technologyourcing activities may be categorized by type of institution intonowledge from research institutions, knowledge from universi-ies, and knowledge from consultancy firms (i.e. KIBS). There is clearmpirical evidence that external knowledge from research institu-ions plays a particularly important role in some industries. Thus,he second set of hypotheses was stated as follows.H2a: KIBS havepositive relationship with learning capability.H2b: KIBS have a

ositive relationship with R&D capability.H2c: KIBS have a positiveelationship with resource allocation capability.H2d: KIBS have aositive relationship with manufacturing capability.H2e: KIBS havepositive relationship with marketing capability.H2f: KIBS have aositive relationship with organizational capability.H2g: KIBS havepositive relationship with strategic planning capability.

Due to the complexity and variability of technologies and mar-ets, individual firms, especially SMEs, find it most beneficial tonnovate in cooperation with other firms or institutions in a mannerhat enables all partners to use their own competencies to the opti-

al extent and to combine them with the specific competencies of

heir partners. Because the knowledge involved in innovation activ-ties can be tacit or codified and can be generated within the firmr acquired from external organizations, innovation can be under-tood as a cycle involving interactions between tacit and codifiednowledge.

• Manufacturing capability• Marketing capability• Organization capability• Strategic planning capability

KIBS play a specific role in innovation by facilitating the uti-lization of knowledge gained from SIs. KIBS play a twofold role ininnovation systems (Czarnitzki and Spielkamp, 2000; Muller andZenker, 2001). Not only do they have a direct impact on innovationactivities among manufacturing SMEs, but they also have an indi-rect influence by “paving the way” for the absorption of knowledgefrom other sources of innovation. KIBS are potential co-innovatorsfor SMEs and can be considered “bridges for innovation” giventheir functions of purchasing knowledge, equipment, and invest-ment goods from the manufacturing industry, providing servicesor knowledge for companies in the manufacturing industry/servicesector, and delivering knowledge or services that are complimen-tary to the manufacturing industry’s products or to other services(Muller and Zenker, 2001). Hence, it was proposed that KIBS helpto improve the utilization of SI to enhance technological innova-tion by playing a dual role as bridges for and sources of innovation.The third hypothesis predicted as follows.H3: KIBS have a positiverelationship with EXT.

4.3. Relationship between TICs and technology innovationperformance (TIP)

A firm’s competitive advantage could come from the effi-ciency and capabilities derived from new product developments(Lawless and Fisher, 1990; Guan, 2002). An increase in prod-uct innovation is attributable to the accumulation of capabilitiesand contributes to innovation outputs. In most circumstances,high-performance firms have stronger capabilities than low-performance firms. Improving TICs can be beneficial to the firm andlead to enhanced competitiveness (Yam et al., 2004). Evangelistaet al. (1997) regarded R&D activities as a central component offirms’ technological innovation activities and as the most importantintangible form of innovation expenditure. A firm’s heterogeneousresource portfolios (including its human, capital, and technol-ogy resources) are responsible for the variability observed in its

financial returns. These are the firm’s specific competencies thatcontribute substantially to its sales growth and competitive advan-tage. There is a causal connection between a firm’s resources andits technological innovation performance. The OLSO Manual (1997)proposed that TIP can be measured by the proportion of sales

R.C.M. Yam et al. / Research Policy 40 (2011) 391–402 395

Innovation Capabilities

R & D

Capability

Resource Allocation

Capability

Manufacturing

Capability

Learning

Capability

Organization

Capability

Marketing

Capability

Strategic Planning

Capability

Sales

Performance

Technological

(TICs)

Technological

Innovation Performances

(TIPs)

H4a-gExternal

Source (EXT)

KIBS

H1a-g

H2a-g

Sources

of Innovation (SI)

H3

Regional Perspective Firm Perspective

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ue to technologically new or improved products, i.e. sales per-ormance. This indicator has also been widely adopted in recentnnovation studies (Evangelista et al., 2001; Yam et al., 2004).hus, the fourth set of hypotheses made the following predic-ions.H4a: Learning capability has a positive relationship withales performance.H4b: R&D capability has a positive relationshipith sales performance.H4c: Resource allocation capability has aositive relationship with sales performance.H4d: Manufacturingapability has a positive relationship with sales performance.H4e:arketing capability has a positive relationship with sales perfor-ance.H4f: Organizational capability has a positive relationshipith sales performance.H4g: Strategic planning capability has aositive relationship with sales performance.

The overall research model is depicted in Fig. 1.

. Research methodology

.1. Measures

.1.1. Sources of innovationThe OSLO manual (OECD, 1997) proposed a list of SIs that has

een widely adopted by researchers in RIS studies over the pastecade or more. In this study, after considering the circumstancesf the HK manufacturing industry and feedback gathered in a pilottudy, relevant items were employed to measure the utilization ofIs (EXT and KIBS). Respondents were asked to give their views onhe degree to which these items were utilized. With reference toimilar previous studies (Yam et al., 2004), a 7-point Likert scale wassed for all applicable items to ensure a higher degree of statisticalariability among the survey responses. A higher score denoted aigher degree of utilization of the type of innovation source con-erned.

.1.2. Technological innovation capabilities

A review of the prior TIC literature (Christensen, 1995; Chiesa

t al., 1996; Yam et al., 2004) suggested that the scales employedy Yam et al. (2004) should be used in this study. As noted earlier,he functional approach used in these prior studies has the advan-age of being easy to understand. A pilot study conducted to verify

earch model.

the scales examined seven TICs: learning capability, R&D capability,resource allocation capability, manufacturing capability, marketingcapability, organizational capability, and strategic planning capa-bility. The definition of each capability is given in Appendix A. Incommon with the SI measure, a 7-point Likert scale was used forall applicable items. A higher score denoted greater strength in thecapability concerned.

5.1.3. Technological innovation performanceThe performance of any innovation is always best measured

in financial terms. Financial indices show whether the innovationhas had an impact on the market or has been financially success-fully. Sales performance was measured as the amount of sales due totechnologically new or improved products as a percentage of totalsales over the last three years. This indicator is widely adopted ininnovation studies (Yam et al., 2004).

5.1.4. Control variableCompany size was used as a control variable in this study.

Previous investigations have indicated there could be a positiverelationship between company size and technological innovationperformance. Size can affect a firm’s innovation and performance(Rothwell, 1983; Pavitt et al., 1987). Large companies tend to havemore resources with which to enhance their innovation capabil-ity and performance. They are usually more powerful than smallcompanies and have some advantages in gaining the support ofheadquarters for their business operations and innovation activ-ities (Tsai, 2001). On the other hand, other studies have showndifferent conclusions: those of Wan et al. (2003) and Caloghirouet al. (2004) revealed that company size has no direct influence ontechnological innovation performance.

Given that this study included data from five industries, we con-trolled for the possibility of industry effects in our analysis by usingdummy variables for the type of industry. This approach was takenbecause firms from different industries may have differing levels ofperformance in innovation capability and efficiency.

396 R.C.M. Yam et al. / Research Po

Table 2Demographic characteristics of the sampled firms (N = 200).

N Percentage

Type of industryElectronics 41 20.5Electrical appliance 83 41.5Toys 26 13.0Watch and clock 39 19.5Machinery 11 5.5

Company size1–100 21 10.6101–500 53 26.8

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for testing overall model fit with a lower degree of measurementerror.1 In the model analysis, maximum likelihood estimation(ML) and standardized regression weighting were used for inter-pretation. Multiple indices of fit including IFI, CFI, and cmin/df

1 As the sample examined in this study was relatively small, partial least squaresmodeling (PLS-SEM) could have been used (Falk and Miller, 1992). However, stud-ies in the prior literature have continued to question the use of PLS-SEM and it isa method that is not commonly used in the field of general management (Rouseand Corbitt, 2008). PLS analysis also requires a relatively large sample (Marcoulidesand Saunders, 2006; Goodhue et al., 2006). In view of this, we preferred to adopt

501–1000 14 7.11001–3000 58 29.3>3000 52 26.2

.2. Pilot study

We consulted a researcher interested in technological innova-ion and four industry executives primarily to improve the surveynstrument and ensure a high level of content validity. A pre-test

as then carried out with a convenience sample of 30 managersorking in the manufacturing industries included in the study.

hey were asked to complete the questionnaire and to comment onhe clarity and appropriateness of the items included. Simple sta-istical analyses were undertaken to test the reliability of the scalesdopted. The revised questionnaire was then sent to the sampledrms by mail.

.3. Sample

Hong Kong manufacturers from the electronics, electri-al appliance, toy, machinery, and watch & clock industriesere selected as the sample frame in the survey conducted

or this study. These industries were chosen for two rea-ons. First, they develop relatively complex and advancedroducts involving active participation in technological prod-ct and process innovations to maintain their competitivenessHKTDC, 2000). Second, these industries combined made a 40.1%ontribution to the total value of exports among all manufac-uring industries in 1999. Studying technological product androcess innovations in these industries is thus of great signifi-ance.

The sample for the mail survey used to collect the data wasrawn from firms listed in the Directory of Hong Kong Industriesublished by the Hong Kong Productivity Council. The targetedespondent in each firm was the president, general manager,irector of engineering, R&D manager, or engineering manager.ollow-up telephone interviews were conducted to ensure datauality. The survey questionnaires were mailed to the 1200 selectedrms. Of these, 1153 reached the targeted firms, of which 12 wereot in the targeted industries. Of the 1153 successfully contactedrms, 202 responded to the survey for a response rate of 17.7%.fter the data cleaning process, 200 questionnaires were found toe useful. The sample profile is shown in Table 2.

.4. Follow-up case interviews

Eleven follow-up case interviews were conducted to verifyhe survey findings. The companies interviewed in these casesere selected from respondents with more than 5 years of pro-

ess/product innovation experience. The interviewees were seniorompany representatives with good knowledge of the company,articularly in the area of product/process innovation. The surveyndings, the utilization concept, and the dual role of KIBS werepecifically discussed during each 2-h structured interview.

licy 40 (2011) 391–402

6. Data analysis

6.1. Non-response bias

To detect any non-response bias, a test was conducted to deter-mine whether any significant differences existed between the laterespondents and early respondents in terms of variables relevantto the research hypotheses (Armstrong and Overton, 1977). Theaverage values of the measurement items for the first 10% ofrespondents were compared with those for the last 10% of respon-dents using t-tests. The results showed no statistically significantdifference between the means for the items across the two groups,indicating that non-response bias was not a problem in this study.

6.2. Validation of instrument

Before conducting the hypothesis testing, a thorough mea-surement analysis was carried out on the instrument to reducemeasurement error (Churchill, 1979). The analysis included assess-ments of the scale reliability, convergent validity, discriminantvalidity, and unidimensionality of the research constructs. Cron-bach’s alpha was used to assess the scale reliability of each constructin the research model. Cronbach’s alpha for every factor (shownin Appendix B) was greater than the suggested threshold valueof 0.7 for an acceptable level of reliability (Kline, 1998). The con-vergent validity of the research constructs was assessed usingexploratory factor analysis (EFA). The EFA results showed that allthe constructs had eigenvalues exceeding 1.0 and that all the factorloadings exceeded 0.3 (see Appendix B). The convergent validityof the research constructs was therefore confirmed. Discriminantvalidity and unidimensionality were assessed using confirma-tory factor analysis (CFA) and the results are shown Appendix C.The measurement model constructed for CFA had a relative chi-square value (cmin/df) of 2.665 < 3, an incremental fit index (IFI)of 0.926 > 0.9, and a comparative fit index (CFI) of 0.926 > 0.9. Thestandardized loadings (�) for all constructs were high (i.e. � > 0.5)and the corresponding t-values were statistically significant. Theseresults indicated unidimensionality among the research constructs.A check of the modification indices for the measurement modelconducted during the CFA process revealed no significant cross-loadings among the variables (e.g. � > 0.85), which indicated gooddiscriminant validity (Kline, 1998). The scores for valid variableitems in each construct were then averaged as a single score tobe used in the model analysis.

6.3. Hypothesis testing

The hypotheses were tested by way of structural equationmodeling (SEM). SEM enables us to test several multiple regressionequations at the same time and is therefore a very useful tool

the well-established and widely used ML-SEM methodology (Rouse and Corbitt,2008). The survey data for this study were acceptable for ML-SEM as the sample metthe minimum size requirement of 200 (Kelloway, 1998) and the study adopted fitindexes (e.g. CFI and RMSEA) that are least affected by sample size (Fan et al., 1999).It is acknowledged, however, that the small sample examined here represents alimitation of this study.

R.C.M. Yam et al. / Research Policy 40 (2011) 391–402 397

Table 3Descriptive statistics and correlations.

Mean SD 1 2 3 4 5 6 7 8 9 10

1. EXT 3.597 1.537 12. KIBS 2.843 1.299 0.450** 13. Learning capability 4.888 1.099 0.220** 0.024 14. R&D capability 4.257 1.141 0.315** 0.245** 0.436** 15. Resources allocation

capability4.320 1.097 0.347** 0.209** 0.505** 0.618** 1

6. Manufacturing capability 4.507 1.158 0.259** 0.113* 0.432** 0.721** 0.624** 17. Marketing capability 4.808 1.023 0.172* 0.082 0.484** 0.556** 0.549** 0.483** 18. Organizing capability 4.320 1.060 0.488** 0.250** 0.554** 0.704** 0.612** 0.644** 0.580** 19. Strategic planning

capability4.520 1.121 0.283** 0.123+ 0.474** 0.630** 0.683** 0.672** 0.665** 0.707** 1

0.081

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7

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7

T

TH

n

10. Sales performance 2.990 1.725 0.141+ 0.168*

+ p-value < 0.10.* p-value < 0.05.

** p-value < 0.01.

ere used to specify the overall model fit. The IFI and CFI valuesere over 0.9 and that of cmin/df was below 3, indicating a goodegree of model fit (Bentler, 1990). An RMSEA value of less than.7 indicates an adequate degree of model fit (Bollen, 1989). Theesearch hypotheses were tested according to the significance ofhe t-test result in each path, with parameter estimates (p < 1.0)eing made in the SEM process.

. Results and discussion

Table 3 reports the means, standard deviations, and intercorre-ations of SIs, TICs, and TIP. The SEM results are presented in Fig. 2.he unidirectional arrows represent the regression relationship ofhe two connected variables. A note is added to describe the sig-ificant correlations among the TICs. The overall fit indices for thisodel indicated a good degree of model fit. The model yielded a

min/df of 1.395 < 3, a CFI of 0.984 > 0.9, an IFI of 0.985 > 0.9, and anMSEA of 0.045 < 0.07. The results generally supported the mainoncept on which this study was based: that the utilization of SInhances multiple TICs and thus affects the TIP of the firm.

.1. Impact of utilizing SI on TICs

The results of hypothesis testing are summarized in Table 4.hey reveal that although all TICs can be enhanced through the

able 4ypothesis testing and results.

Hypothesis testing

H1a: EXT has positive relationship with learning capabilityH1b: EXT has positive relationship with R&D capabilityH1c: EXT has positive relationship with resources allocation capabilityH1d: EXT has positive relationship with manufacturing capabilityH1e: EXT has positive relationship with marketing capabilityH1f: EXT has positive relationship with organization capabilityH1g: EXT has positive relationship with strategic planning capabilityH2a: KIBS has positive relationship with learning capabilityH2b: KIBS has positive relationship with R&D capabilityH2c: KIBS has positive relationship with resources allocation capabilityH2d: KIBS has positive relationship with manufacturing capabilityH2e: KIBS has positive relationship with marketing capabilityH2f: KIBS has positive relationship with organization capabilityH2g: KIBS has positive relationship with strategic planning capabilityH3: KIBS has a positive relationship with EXTH4a: Learning capability has a positive relationship with sales performanceH4b: R&D capability has a positive relationship with sales performanceH4c: Resources allocation capability has a positive relationship with sale performanceH4d: Manufacturing capability has a positive relationship with sales performanceH4e: Marketing capability has a positive relationship with sales performanceH4f: Organization capability has a positive relationship with sales performanceH4g: Strategic planning capability has a positive relationship with sales performance

.s.: the hypotheses is insignificant and is deleted in the model re-specification of the stru

0.302** 0.310** 0.346** 0.150* 0.386** 0.263** 1

utilization of EXT, this will not happen unless KIBS are also uti-lized. The unidirectional arrow from KIBS to EXT in Fig. 2 indicatesa positive relationship between the two. This reflects the fact thatEXT will be utilized to a greater extent if KIBS are better utilized.Hong Kong is a region in which basic industrial research is lack-ing. Technologically innovative products are normally developedby modifying existing products. Hence, technology transfer andpatent disclosure are major sources of innovation for Hong Kongmanufacturers. However, the effectiveness of the transfer dependslargely on the competence of the people involved and the busi-ness strategy of the firm (Teece, 1996). The success of technologytransfer really depends on how much the firm can learn frompatent information and use its knowledge to develop new prod-ucts. Another barrier to the acquisition of knowledge to enhance thefirm’s capabilities is the tacitness of new knowledge (Storper andHarrison, 1991). It is often difficult to transfer knowledge withouttransferring key individuals (Teece, 1996). Hence, the alternativesolution is to utilize intermediary agencies. KIBS can act as a bridgeenabling the firm to improve the effectiveness of its knowledgetransfer activities. For example, in the electronics and softwaresector of southern England, a dense network of regional business

link centers has been set up to provide single points of easy accessto a range of innovation support services (Romijn and Albaladejo,2002). In Hong Kong, similar institutions such as the Hong KongProductivity Council and the Applied Science and Technology

r Result

0.229 Accepted0.260 Accepted0.293 Accepted0.258 Accepted0.183 Accepted0.483 Accepted0.281 Acceptedn.s. Rejected0.117 Accepted0.109 Acceptedn.s. Rejectedn.s. Rejectedn.s. Rejectedn.s. Rejected0.442 Accepted−0.263 Rejectedn.s. Rejected0.194 Accepted0.177 Acceptedn.s. Rejected0.433 Accepted−0.191 Rejected

ctural equation modeling.

398 R.C.M. Yam et al. / Research Policy 40 (2011) 391–402

Notes:

• Overall Model Fit Indices: cmin/df = 2.591; CFI = 0.900; IFI = 0.923; RMSEA = 0.09

• Strength of significance: at 0.01 at 0.05

at 0.10

• The 7 TICs are highly correlated with each other.

• 4 dummy variables were created for controlling the type of industry.

Regression correlation between control variable and research constructs Standardized regression weights (r)

Company size *780.0ytilibapacgnirutcafunaMType of industry (electrical appliances & house-ware) KIBS 0.221** Type of industry (electrical appliances & house-ware) Sales performance 0.149* Type of industry (electrical appliances & house-ware) Marketing capability -0.106* Type of industry (electronic goods & component) Learning capability 0.119* Type of industry (watch and clock) Resource allocation capability 0.141** Type of industry (toys) 711.0-ecnamrofrepselas +

.01

External

Source (EXT)

KIBS

R & D

Capability

Resource Allocation

Capability

Manufacturing

Capability

Learning

Capability

Organization

Capability

Marketing

Capability

Strategic Planning

Capability

SalesPerformance

TechnologicalInnovation Capabilities

(TICs)

Technological

(TIP)

Utilization of

Innovation Sources

(SI)

Innovation Performance

uatio

Rp

acvHjctspi

otodIiHfO

+P-value < 0.1, * P-value < 0.05, ** P-value < 0

Fig. 2. Structural eq

esearch Institute have been established to serve analogousurposes.

As shown in Fig. 2, KIBS are positively related to R&D capabilitynd resource allocation capability. The R&D and resource allocationapabilities of a firm will be enhanced by utilizing services pro-ided by consultancy firms and universities (i.e. utilizing KIBS). Inong Kong, collaborations with universities normally focus on the

oint development of new products, whereas collaborations withonsultancy firms generally center on transferring knowledge andechniques enabling the firm to better utilize its existing resourcesuch as total quality management practices and enterprise resourcelanning skills. Hence, it is well understood that these two capabil-

ties can be improved through the utilization of KIBS.On the other hand, KIBS has no direct impact on capabilities

ther than the two mentioned above. As most Hong Kong manufac-urers are OEM or ODM manufacturers for which the major sourcesf marketing knowledge are their customers or suppliers, they sel-om acquire marketing knowledge from other sources such as KIBS.

n addition, the short-term mindset of Hong Kong manufacturerss another barrier to utilizing KIBS to enhance these capabilities.ong Kong manufacturers normally employ KIBS to fix problems

or them rather than to learn about new problem-solving methods.ne of the interviewees (the owner of a precision plastics part man-

n modeling results.

ufacturer) complained that the firm was normally unable to obtainimmediate practical solutions from consultancy firms or universi-ties to resolve the problems it identified. Nevertheless, the majorfunction of KIBS should be to act as knowledge transfer agenciesrather than as problem solvers. This anecdotal evidence reflects amisunderstanding among Hong Kong manufacturers over the func-tion of KIBS.

7.2. The dual role of KIBS

The results for hypothesis 2 reveal the role of KIBS as a sourceof innovation. KIBS act as a source of new knowledge that can beused to enhance the firm’s R&D and resource allocation capabilities.The unidirectional arrow from KIBS to EXT in Fig. 2 indicates thatKIBS are positively related to EXT. That is, the utilization of KIBS isrelated to the utilization of EXT in that the latter can be improvedby the former.

Muller and Zenker (2001) commented that KIBS not only have a

direct impact on innovation activities among manufacturing SMEs,but also have an indirect impact on such activities by paving theway for the absorption of knowledge from other external sourcesof innovation. Based on the results of the analysis of hypotheses2 and 3, KIBS play a dual role as both sources of and bridges for

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R.C.M. Yam et al. / Resea

nnovation in Hong Kong’s manufacturing industries. Successfulechnology transfer requires that firms develop a capacity to recog-ize opportunities and to search for, modify, and adapt technology.

Furthermore, where there is a wide knowledge gap betweenuppliers and users of technology, there have to be appropri-te intermediary agencies that connect them (Izushi, 2003). Theridging role of KIBS is especially important for SMEs (Chang andhih, 2004; Izushi, 2003; Muller and Zenker, 2001). In technologyransfer policy supporting SMEs, the last two decades saw a shiftf emphasis towards the development of innovation capabilitiesithin firms and the creation of effective intermediaries betweensers and providers of knowledge (Dodgson and Bessant, 1996).xamples of this trend include the kosetsushi centers in Japan andhe US modernization program (Izushi, 2003).

.3. Effect of TICs on TIP

Among all TICs, resource allocation, manufacturing, and organi-ation capabilities were positively related to the sales performancef a firm. Organizational capability refers to the ability of a firmo coordinate various departments such as the R&D, marketing,nd manufacturing departments to handle innovation projects inarallel with each other. For resource allocation capability, we mea-ured how well a firm managed its human and capital investmentsade to support innovation activities. For manufacturing capabil-

ty, we measured how well a firm employs manufacturing methodsnd personnel to transform R&D output into production. As saleserformance measured the percentage of sales generated by tech-ologically new or improved products in the past three years, itoncerned not only the design and manufacture of new or improvedroducts, but also the production of new or improved productshat are marketable. Firms therefore need to develop a strong abil-ty to transform an innovative idea into a product, organize theesources required to make it happen, and ultimately manufacturehe product. These three steps are core processes in the develop-

ent and manufacture of a successful new product. Firms thereforeeed strong organizational, resource allocation, and manufacturingapabilities to achieve outstanding sales performance.

Our results also show that learning capability is not directlyelated to TIP. However, Table 3 indicates that learning capabil-ty is highly correlated with the other six TICs. Despite the absencef a direct nexus between learning and TIP, the former is neededo enhance the firm’s performance in the other six TICs. Cohen andevinthal (1990) found that an organizational unit’s internal learn-ng capability determines the extent to which it can absorb newnowledge from other units.

. Conclusions

This study contributes to the growing interest in integrating theIS and FIS approaches in studying firm innovation performance,subject that has not been fully investigated in empirical studies

n the prior literature. Lin et al. (2002) have pointed out that thebility of a firm to exploit external knowledge is a critical com-onent of successful innovation. As noted earlier, in addition toonducting internal R&D activities, firms can reinforce their tech-ology competence by importing technologies and then diffusing,ssimilating, communicating, and absorbing them into their orga-izations (Hamel and Prahalad, 1990). This study confirms the

ediating role played by TICs between SIs and TIP. The technologi-

al innovation performance (TIP) of a firm is determined by its TICs,hich can themselves be enhanced by utilizing appropriate SI. Werovide empirical evidence that TICs can act as a bridge betweenhe RIS and the FIS.

licy 40 (2011) 391–402 399

When supported by KIBS, EXT was found to have a positiverelationship with all TICs. This provides empirical evidence on thebridging function of KIBS in facilitating the utilization of SIs forTIC enhancement. These findings on the interrelationships betweenTICs and EXT contribute to the RIS literature by showing how firmscan interact with the RIS to enhance their technological innovationcapabilities and achieve global competitiveness. They also provide areference for firms considering how to arrange their resources mosteffectively to enhance the TICs they need and thereby improve theirtechnological innovation performance.

This study also found that KIBS have a positive relationship withEXT. This implies that better utilization of KIBS will assist firms inbetter utilizing external sources of innovation. At the same time,KIBS have a positive relationship with R&D and resource allocationcapabilities. These results demonstrate that KIBS have two roles:the first is as a “source of innovation” and the second is as a “bridgefor innovation”. This finding provides empirical evidence on the co-innovator role or “bridge for innovation” proposed by Muller andZenker (2001). The role KIBS play as “bridges for innovation” is par-ticularly important for industries dominated by SMEs such as thosethat form the manufacturing sector of Hong Kong. KIBS act as inter-mediaries between technology suppliers and users, select specifictechnologies suitable for development in Hong Kong, and transferinnovative technologies to firms within Hong Kong’s innovationsystem.

This study is subject to several limitations that provide scopefor future research. First, the data were gathered from a single keyinformant in each sample firm. The underlying assumption behindthis method is that senior managers, by virtue of their position inthe company, are capable of providing opinions and perceptionsthat reflect the company’s behavior. Although all the reliability andvalidity tests conducted in this study indicated that respondentbias may not be a serious problem, a multiple informant approachcould be adopted in future research. However, the complications ofconducting a large-scale empirical study using multiple informantsshould not be underestimated.

Second, the cross-sectional data used in the present study maynot be adequate for identifying fundamental relationships amongthe variables. To improve on our study, future researchers couldconduct multiple cross-sectional analyses in different timeframesto generalize the findings reported here.

A final limitation is that in constructing the model, the struc-tural equation modeling approach adopted involved the testing of10 research constructs, five control variables, and 10 error termssimultaneously. Although the size of the sample employed in thisstudy reached the acceptable threshold of 200 (Kelloway, 1998) andthe overall model fit indices used (e.g. CFI and RMSEA) are amongthe measures least affected by sample size (Fan et al., 1999), a big-ger sample may have produced more accurate statistical results inthe model testing process.

Appendix A. Definitions of technological innovationcapabilities

Learning capability is the firm’s ability to identify, assimilate, andexploit knowledge from the environment.

R&D capability refers to the firm’s ability to integrate R&D strat-egy, project implementation, project portfolio management, andR&D expenditure.

Resources allocation capability ensures that the firm possesses

enough capital, professionals and technology in the innovation pro-cess.

Manufacturing capability refers to the firm’s ability to transformR&D results into products, which meet market needs, accord withdesign request and can be manufactured in batches.

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Marketing capability is the firm’s ability to publicize and sellhe products on the basis of understanding consumer needs, com-

etition situation, costs and benefits, and the acceptance of the

nnovation.Organizing capability refers to the firm’s ability in secur-

ng organizational mechanism and harmony, cultivating

Appendix B. Results of exploratory factor analysis

Factors/constructs Reliability (alpha) Eigen- valu

Utilization of innovation sourcesExternal source 0.7484 1.599Knowledge intensive business service 0.8236 2.232

Technological innovation capabilitiesLearning capability 0.7815 1.652R&D capability 0.8255 2.224Resources allocation capability 0.8612 2.827Manufacturing capability 0.8234 2.218Marketing capability 0.8542 2.787Organization capability 0.8503 2.322Strategic planning capability 0.9204 3.799

Assessment criteria: Eigen value > 1, factor loading > 0.3 and reliability > 0.7.

Appendix C. Results of confirmatory factor analysis

Construct and items

External source (EXT)• Acquisition of embodied technology (such as patent, license, trade mark, design, tech• Patent disclosure

Knowledge-intensive business services (KIBS)• Consultancy firms• University and research institution in Pearl River Delta• University and research institution outside Pearl River Delta

Learning capability• Your company encourages work teams to identify opportunities for improvement• Your company adopts accessed knowledge into your daily activities

R&D capability• Your company has high quality and quick feedbacks from manufacturing to design an• Your company has good mechanisms for transferring technology from research to pro• Your company has great extent of market and customer feedback into technological i

Resources allocation capability• Your company attaches importance to human resource• Your company programs human resource in phase• Your company selects key personnel in each functional department into the innovatio• Your company provides steady capital supplement in innovation activity

Manufacturing capability• Your company’s manufacturing department has ability in transforming R&D output in• Your company effectively applies advanced manufacturing methods• Your company has capable manufacturing personnelMarketing capability• Your company has close relationship management with major customers• Your company has good knowledge of different market segments• Your company has highly efficient sales-force• Your company provides excellent after-sale services

Organization capability• Your company can handle multiple innovation projects in parallel• Your company has good coordination and cooperation of R&D, marketing and manufa• Your company has high-level integration and control of the major functions with the

Strategic planning capability• Your company has high capability in identifying internal strengths and weaknesses• Your company has high capability in identifying external opportunities and threats• Your company has clear goals.• Your company has a clear plan—a road map of new product and process with measur• Your company is highly adapted and responsive to external environment

licy 40 (2011) 391–402

organization culture, and adopting good managementpractices.

Strategic planning capability is the firm’s ability to identify inter-nal strengths and weaknesses and external opportunities andthreats, formulate plans in accordance with corporate vision andmissions, and acclimatize the plans to implementation.

es Factor loading for items

#1 #2 #3 #4 #5

0.894 0.8940.817 0.881 0.888

0.909 0.9090.908 0.878 0.7930.834 0.884 0.841 0.8030.880 0.876 0.8230.830 0.912 0.840 0.7490.875 0.868 0.8960.883 0.890 0.885 0.850 0.849

Standardized Loading (�) Error Term t-value**

nical services) 0.730.79 0.16 9.22

0.690.83 0.09 10.380.87 0.11 10.60

0.770.79 0.12 10.47

d engineering 0.88duct development 0.76 0.03 13.22

nnovation process 0.69 0.06 11.31

0.600.70 0.12 11.62

n process 0.83 0.10 8.880.75 0.13 8.39

to production 0.810.80 0.19 12.730.68 0.09 10.12

0.770.88 0.16 13.510.77 0.13 11.520.64 0.11 9.35

0.79cturing department 0.75 0.05 11.61company 0.84 0.06 13.47

0.850.86 0.16 16.000.82 0.12 14.53

able milestones 0.76 0.31 12.930.79 0.17 13.68

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area of marketing and manufacturing interface.

02 R.C.M. Yam et al. / Resea

ichard C.M. Yam is associate professor in the Department of Manufacturing Engi-eering and Engineering Management, City University of Hong Kong. His currentesearch interests are in the areas of product innovation and technology manage-

ent.

illiam Lo is a PhD graduate in Department of Manufacturing Engineering and Engi-eering Management, City University of Hong Kong. His current research interestsre in the areas of technology management and advanced manufacturing practicesn Hong Kong and Pearl River Delta region.

licy 40 (2011) 391–402

Esther P.Y. Tang is associate professor in the Department of Management and Mar-keting, Hong Kong Polytechnic University. Her current research interest is in the

Antonio, K.W. Lau is a former teaching staff of the Department of Manufactur-ing Engineering and Engineering Management at the City University of Hong Kong.His current research interests are in the areas of new product development andinnovation management.