Inbound Open Innovation Activities in High-Tech SMEs: The Impact on Innovation Performance

Inbound Open Innovation Activitiesin High-Tech SMEs: The Impact onInnovation Performancejsbm_354 283..309

by Vinit Parida, Mats Westerberg, and Johan Frishammar

Prior studies suggest that open innovation activities positively influence innova-tion outcomes in large firms. However, few studies have investigated the implicationsof small and medium-sized enterprises’ (SMEs) adoption of open innovation. Weaddress this research gap by investigating the effects of four inbound open innovationactivities on innovation performance of SMEs. In doing so, we draw on data from 252high-tech SMEs. Our results reveal that different open innovation activities are ben-eficial for different innovation outcomes. For instance, technology sourcing is linkedto radical innovation performance, whereas technology scouting is linked to incre-mental innovation performance. These findings hold several important theoreticaland practical implications.

IntroductionMany small and medium-sized enter-

prises (SMEs) depend on their ability tobe innovative for achieving and sustain-ing competitive advantage. However, theaverage success rate of innovative effortstends to be much lower than desirable,mainly due to the high level of risk,

complexity, and uncertainty inherent inthe innovation process (Cooper, Edgett,and Kleinschmidt 2003; Griffiths-Hemansand Grover 2006; Koufteros, Vonder-embse, and Jayaram 2005). In addition,innovative development is usually chal-lenging for SMEs because they are subjectto the “liability of smallness,” that is, SMEsgenerally have limited financial resources

Vinit Parida is assistant professor at Entrepreneurship and Innovation, Luleå University ofTechnology.

Mats Westerberg is associate professor at Entrepreneurship and Innovation, Luleå Universityof Technology.

Johan Frishammar is professor at Entrepreneurship and Innovation, Luleå University ofTechnology.

Address correspondence to: Vinit Parida, Department of Business Administration, Technol-ogy and Social Science (ETS), Entrepreneurship and Innovation, Luleå University of Technol-ogy, SE-971 87, Luleå, Sweden. Tel: +46 920 492469. E-mail: [email protected].

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(Freel 1999; Grando and Belvedere 2006),often lack a multidisciplinary competencebase (Bianchi et al. 2010), and tend to useless structured approaches to innovation(De Toni and Nassimbeni 2003; Vossen1998). Altogether, these factors mayrestrict their ability to innovate andachieve competitiveness.

To this background, recent studiesin the innovation and technology man-agement domain have proposed severalpotential benefits of opening up theinnovation process. In the literature, thisis described as a shift from the traditionalor “closed” innovation model, with a mainfocus on internal research and develop-ment (R&D), toward an “open innova-tion” approach (Chesbrough 2003;Gassmann 2006; Lichtenthaler 2011). Inessence, firms engaging in open innova-tion actively utilize and exploit inwardand outward transfer of knowledge andtechnologies (Chesbrough, Vanhaver-beke, and West 2006). The notion thatfirms in general and SMEs in particularmay benefit from tapping into externalresource bases is not novel (Jarillo 1989),but specific knowledge about the effect ofdifferent open innovation activities islimited. Therefore, in this study, we shedlight on which open innovation activitiesSMEs can engage in to spawn their owninnovation efforts.

Although most scholars would agreethat open innovation activities couldbe beneficial for SMEs and large firmsalike (Chesbrough 2003; Chesbrough,Vanhaverbeke, and West 2006;Lichtenthaler 2008a), to date, the major-ity of prior research has focused on largeor multinational firms (Bianchi et al.2010; Christensen, Olesen, and Kjær2005; Lecocq and Demil 2006; Van DeVrande et al. 2009). SMEs are clearly dif-ferent from larger firms with respect tohow they can utilize open innovationactivities for innovation outcomes. Forexample, compared with large firms,SMEs have several inherited limitations,such as lack of resources for R&D,

unstructured innovation processes, andunderdeveloped internal capabilities;(Chesbrough and Crowther 2006;Lichtenthaler 2008a; Madrid-Guijarro,Garcia, and Van Auken 2009). On theother hand, SMEs are usually less bureau-cratic, more inclined to take risks,possess more specialized knowledge,and are faster in reacting to changingmarket demands, which all togetherenables them to be better at gaining fromopen innovation activities comparedwith larger firms (Christensen, Olesen,and Kjær 2005; Stam and Elfring 2008;Vossen 1998). Therefore, given theunderlining differences between largerand small firms, we argue for specificallyfocusing on the topic of SMEs and openinnovation.

If SMEs become proficient in applyingopen innovation by collaborating withnetwork partners, they can compensatefor the scarcity of internal resources andcompetences (Christensen, Olesen, andKjær 2005; Kogut 2000; Lichtenthaler2008a). Through access to network part-ners’ external resources, SMEs candevelop new technological combina-tions, and thus address or take advantageof a wider range of market opportunities(Baum, Calabrese, and Silverman 2000;Dyer and Singh 1998). Another exampleis utilizing technology developed else-where (Grönlund, Rönnberg-Sjödin, andFrishammar 2010; Lichtenthaler 2008b).This would facilitate SMEs to fill in theirinternal technological gaps, which arelikely to exist due to their focus on spe-cialized technological development.Moreover, as the acquired technologywill be tested and proven, it can increaseboth the speed and quality of innovativeactivities (Tao and Magnotta 2006; VanDe Vrande et al. 2009).

Thus, open innovation activities canhold a wide spectrum of potential oppor-tunities for significantly improving SMEsinnovative performance. However, fewprior studies have explored this interest-ing research avenue, and the studies that

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do exist have mainly been case studiesand/or conceptual analyses, which makethe generalizability of prior findingssomewhat limited.

In prior literature, we find examplesof open innovation and SMEs studiesfocusing on the implication of opensource strategies (Henkel 2006; Lecocqand Demil 2006), industrial dynamics(Christensen, Olesen, and Kjær 2005),methodologies for technology out-licensing (Bianchi et al. 2010), andeffects of intermediate organizations (Leeet al. 2010). To the best of our knowl-edge, Van De Vrande et al. (2009),Lichtenthaler (2008a), and Laursen andSalter (2006) have published the threeprominent studies encompassing abroader set of open innovation activitiesin SMEs by drawing on larger quantita-tive data sets. However, one study hasexcluded small firms (Lichtenthaler2008a) and another has excluded micro-firms (SMEs having less than 10 employ-ees) from the analysis (Van De Vrandeet al. 2009), making the results valid onlyfor larger SMEs.

Therefore, even though prior studieshave made important contributions tothe literature and management practicealike, by addressing open innovationactivities in the SME context, there isclearly a need for more quantitativestudies that can advance our understand-ing regarding the effects of open innova-tion activities in SMEs.

To this background, our study willfocus on four distinct inbound open inno-vation activities, namely technologyscouting, horizontal technology collabo-ration, vertical technology collaboration,and technology sourcing, and investigatetheir effects on innovation performancein SMEs (Chesbrough, Vanhaverbeke,and West 2006; Lichtenthaler 2008a; VanDe Vrande et al. 2009). In line with thestudy of Laursen and Salter (2006), we useperceptual measures of radical innovationand incremental innovation to measureSMEs innovation performance. In

essence, radical innovation represents afirm’s ability to develop products that arenew to the world or industry, whereasincremental innovation refers to theability to develop products that are new tothe firm. Certain open innovation activi-ties may have stronger positive influenceon radical rather than incremental inno-vative performance and vice versa(Faems, Van Looy, and Debackere 2005;Pittaway et al. 2004; Ragatz, Handfield,and Scannell 1997). Capturing differencesrelated to these two dimensions has notbeen widely explored (Lane, Koka, andPathak 2006), and by investigating thetwo innovation performance dimensions,we were able to provide a more fine-grained understating of open innovationactivities in SMEs. Therefore, we takethese differential effects into account, andcommence our arguments about theseissues in the sections to come.

Our study contributes to the techno-logy and innovation management litera-ture by providing new insights on howdifferent open innovation activities couldenhance innovation performance (Ches-brough 2003; Lichtenthaler 2008a; VanDe Vrande et al. 2009). Additionally, wealso contribute to the small businessmanagement literature by adding to thebody on knowledge on how SMEs canbenefit from adapting and utilizing openinnovation activities. From a managerialperspective, our study provides newinsights to owners, managers, and chiefexecutive officers (CEOs) of SMEs abouthow they can use their limited resourcesfor practicing open innovation to achieveand sustain incremental and/or radicalinnovation.

The rest of the article is organized asfollows. Next, we will present priorresearch on the topic of open innovationand SMEs, open innovation and innova-tion performance, and subsequentlypresent eight hypotheses for empiricaltesting. In the third section, the methodsemployed in this research are described,including operationalization of con-


structs and data analysis. We subse-quently present the results before wediscuss these, and offer conclusions,limitations, and suggestions for futurestudies in the final section.

Conceptual Backgroundand Literature ReviewOpen innovation and SMEs

SMEs depend on their ability to beinnovative for sustaining competitive-ness. However, due to increased compe-tition and rapidly advancingtechnologies in many industries, SMEsare often forced to develop new productsfaster and more effectively. This require-ment is challenging for SMEs not onlybecause of their limited size, but alsobecause they have less internal resourcesand a more restricted competence base,which affect their ability to engagein innovative efforts (Cooper, Edgett,and Kleinschmidt 2003; De Toni andNassimbeni 2003; Pittaway et al. 2004;Powell, Koput, and Smith-Doerr 1996).One way to address these challengingdemands is by opening up the innovationprocess to facilitate increased rents fromthe interaction with external actors. Priorstudies support the idea that utilizing openinnovation activities can render SMEs stra-tegic benefits (Chesbrough and Crowther2006; Chesbrough, Vanhaverbeke, andWest 2006; Gassmann 2006; Laursen andSalter 2006; Lee et al. 2010).

Bianchi et al. (2010) make the case foran increasing role of open innovation inSMEs, as they argue that both technologyand products are becoming morecomplex, and it is thus becoming lessfeasible to engage in product and tech-nology development for a small firmpurely by itself. Because the competenceand knowledge needed for such deve-lopment are scattered across firms andinstitutions (universities), it makes senseto form collaborations with external part-ners (Frishammar, Lichtenthaler, andRundquist 2011). In line with the earlierarguments, Van De Vrande et al. (2009)

suggest that open innovation activitiescan provide access to missing knowl-edge, reduce the costs of development,provide possibilities for risk sharing, andimprove the product developmentprocess. For example, through the use ofan open source development approach,SMEs can gain from the competence ofenthusiastic and skilled programmersfrom around the globe, and compensatefor the lack of limited in-house resources(Henkel 2006). Therefore, in accordancewith prior literature, we assume that ifSMEs are able to integrate and utilizeopen innovation activities, they canreduce the challenges related to “liabilityof smallness” and finite resources inthe context of innovation (Chesbrough,Vanhaverbeke, and West 2006).

Although the idea that SMEs can reapbenefits from open innovation activitiesis rather intriguing (Bianchi et al. 2010;Chesbrough 2003; Chesbrough, Vanha-verbeke, and West 2006), only a limitednumber of prior studies have addressedthe role of open innovation in SMEs (foran overview and summary, see Table 1).These studies have, indeed, made signifi-cant contributions to our understandingof open innovation in the SME context,but they lack generalizable empiricalexaminations about how different openinnovation activities relate to innovationperformance. For example, Christensen,Olesen, and Kjær (2005) examined therole of small firms over the technologylife cycle and provided a basis for under-standing how small firms can benefitfrom forming collaboration with differentpartners. Lecocq and Demil (2006)focused on the open innovation strategyof the firm and explained its effects onthe industry with respect to new entrantsand related aspects. Furthermore,Henkel (2006) provided motives forSMEs to adapt an open source develop-ment strategy, and Bianchi et al. (2010)provided a quick and easy-to-use meth-odology for identification of viableopportunities for out-licensing techno-


Table 1Studies on Open Innovation and Small and Medium-Sized

Enterprises (SMEs)

Authors Year Key Focus Type ofStudy

Key Insights

Christensen,Olesen, andKjaer

2005 Innovationstrategy andmanagement

Qualitativestudy

SMEs manage open innovation with respectto emerging technologies based on theirposition within the innovation system andtheir stage of maturity of the technology.For example, SMEs may explorecommercial opportunities with smallerestablished players in the early stage ofthe technology cycle while they may optfor collaboration with large incumbentsas technology becomes matured.

Lecocq andDemil

2006 Open innovationstrategy

Quantitativestudy

The study finds that introduction of opensystem strategy leads to an increasednumber of new entrants into the industryas they adopt open systems more readilythan incumbents. Moreover, the diffusionof open systems into the low-techindustry leads to decrease in the averagesize of the firms in that industry.

Henkel 2006 Informaldevelopmentcollaboration(Open sourcesoftwaredevelopment)

Quantitativestudy

It was found that smaller firms are likely tobenefit from open source softwaredevelopment as they usually needexternal development support. Also, firmswith long experience of open sourcedevelopment are more willing to revealthan protect software codes.

Laursen andSalter

2006 Search strategyfor externalknowledge

Quantitativestudy

The study suggests that firms that are opento external sources and search channelsare likely to have a higher level ofinnovative performance. However,oversearch would result in negative effecton innovative performance. Firms shouldbe careful with the temptation ofopenness and consider the cost of thesearch efforts.

Lichtenthaler 2008a Externaltechnologyacquisition andexternaltechnologyexploitation

Quantitativestudy

The study found that open innovation wasmainly practiced by large firms, as theyare not able to rely only on internalactivities due to the diversification of thetechnology knowledge that they use.They are also likely to have largeresource pool to build up dedicated openinnovation organizational functions.

Van deVrande, DeJong,Vanhaverbeke,and DeRochemont

2009 Technologyexploitationand technologyexploration

Quantitativestudy

Medium-sized and large firms were found toembrace open innovation to a largerextent. However, SMEs were increasinglyopening their innovation process to copewith lack of internal resources. Withrespect to open innovation practices,utilization of non-R&D workers’knowledge was a prominent technologyexploitation activity, and involvement ofcustomer was a prominent technologyexploitation activity.


logy. Finally, Lee et al. (2010) proposedifferent models of open innovationwithin SMEs and highlight the role of anintermediate organization in supportingSMEs’ innovation ambitions.

As mentioned earlier, we have onlyfound three prominent studies thatprovide empirically generalizable resultsabout the relationship between openinnovation and innovation outcomesfor SMEs (Laursen and Salter 2006;Lichtenthaler 2008a; Van De Vrande et al.2009). Laursen and Salter (2006) make astrong case for how open innovationsearch strategy and search channels influ-ence the innovative performance of SMEs.The other two studies found that largefirms embrace and utilize open innova-tion activities to a larger extent than SMEs(Lichtenthaler 2008a; Van de Vrande et al.2009). A possible explanation for thisoutcome could be that CEOs and man-agers in SMEs have too little knowledgeregarding the effects of open innova-tion, and specifically the potential ben-efits associated with employing it. Inaddition, it might be difficult for SMEsto experiment with open innovationactivities as the resources they caninvest in R&D activities are limited.Thus, we argue that it is practically and

theoretically relevant to investigate howdifferent open innovation activities mayinfluence innovation performance in thecontext of SMEs.

In the literature, open innovation hasbeen associated with a wide spectrum ofactivities. Generally, open innovationactivities fall into two distinct categories.Inbound open innovation refers to thepractice of exploring and integratingexternal knowledge for technologydevelopment and technology exploita-tion. Outbound open innovation is thepractice of exploiting technology capa-bilities by utilizing not only internal butalso external paths of commercialization(Chesbrough 2003; Chesbrough andCrowther 2006). On the one hand,inbound open innovation includes net-working or collaborating with otherfirms or universities for product develop-ment, involving customers or end usersin product development activities, andlicensing-in of intellectual property (IP)from other organizations. On the otherhand, outbound open innovationincludes the spin-off of new venturesbased on prior product or technologydevelopment and external involvementin product development and licensing-out technologies to other organizations

Table 1Continued

Bianchi, Orto,Frattini, andVercesi

2010 Outbound openinnovation(out-licensing)

Qualitativestudy

The study provides an overview on a quickand easy-to-use methodology foridentification of viable opportunities forlicensing out alternative technologyapplication. This methodology is basedon the TRIZ instruments, which combinenonfinancial weights, ranking techniques,and portfolio management tools.

Lee, Park,Yoon, andPark

2010 Technologyexploitationand technologyexploration

Quantitativeandqualitativestudies

The study presents different models of openinnovation within SMEs. In particular, anintermediate network models is furtherinvestigated, and the important role ofintermediate organization in supportingSMEs in searching for appropriatepartners and contributing in building trustbetween network members is highlighted.


(Chesbrough, Vanhaverbeke, and West2006; Gassmann 2006; Henkel 2006;Lichtenthaler 2008b, 2011; Van DeVrande et al. 2009).

Prior research show that most firmsare inclined toward inbound or technol-ogy exploration aspects of open innova-tion (Bianchi et al. 2010; Chesbroughand Crowther 2006; Grönlund,Rönnberg-Sjödin, and Frishammar 2010).A possible reason can be that outboundopen innovation activities imposes ahigher level of managerial challenge dueto the imperfections in the marketsfor technologies (Lichtenthaler andErnst 2007) and lack of systematicinternal process to drive such initiatives(Lichtenthaler, Lichtenthaler, andFrishammar 2009). Though we do realizethat much more research is needed on theoutbound dimension of open innovationin SMEs, the current study focuses on theinbound dimension. Our reason fordoing so is that many SMEs still strugglewith inbound activities due to strategicchallenges, such as technology pricing,IP disclosure, and partner negotiations.Thus, by investigating this dimension,we also assure a sufficient sample size ofSMEs with reasonable levels of experi-ence in these activities. Specifically, westudy four inbound open innovationactivities: technology scouting, verticaltechnology collaboration, horizontaltechnology collaboration, and technol-ogy sourcing, and their effect onradical and incremental innovationperformance.

Innovation performance outcomesof open innovation

The seminal book by Chesbrough(2003) makes a strong case for integra-tion and utilization of open innovationactivities as a way to drive innovationoutcomes and sustain competitiveness indynamic environments. However, due toa lack of quantitative studies on thistopic, the proposed effects of open inno-vation have not been sufficiently investi-

gated in the context of SMEs(Lichtenthaler 2008a; Van De Vrandeet al. 2009). Chesbrough and Crowther(2006) propose growth and revenue asthe main motive for conducting inboundopen innovation, whereas Lichtenthaler,Lichtenthaler, and Frishammar (2009)support the use of more nonmonetaryoutcomes, such as increased customersatisfaction or the acquisition of newknowledge. However, in line withLaursen and Salter (2006), we proposethat the relationship between open inno-vation activities and innovation perfor-mance is central.

Although we realize that firms engagein open innovation activities for differentreasons, we empirically study the linkbetween the inbound open innovationactivities and innovation performance.Innovative performance may vary alonga newness continuum, ranging fromradical to incremental (Ettlie, Bridges,and O’Keefe 1984; Laursen and Salter2006; Sher and Yang 2005). Radical inno-vations are ground-breaking develop-ment that requires significant resourcesto materialize. Many times, such innova-tion has longer time lags to profitabilitycompared with incremental innovations(Chaney, Devinney, and Winer 1991;Veryzer 1998). Although radical innova-tion could enable existing SMEs to estab-lish a dominant position in a marketniche and provide new firms with anopportunity to gain a dominant positionin the market, it could also expose firmsto an increased level of risk.

Incremental innovation, on the otherhand, are development and improve-ments of products and services that donot fit into the first category. It can rangefrom development of new products (thatare known to the market) to minorimprovements in existing products andservices (Atuahene-Gima 2005; Laursenand Salter 2006). The intention of incre-mental innovation is to use the insightsfrom customers or others to developbetter solutions that are attractive and


would add to the profits from the exist-ing products (Pavitt 1998; Xin, Yeung,and Cheng 2008). In theory, firms adapt-ing open innovation activities should beable to support both innovation out-comes. However, it appears that certainopen innovation activities might be morefavorable for incremental innovation,whereas others are better settled tospawn radical innovation.

According to Veryzer (1998), themethods and approaches employed byfirms to develop radical or discontinuousinnovations are largely different fromincremental innovation. The reason forthis is rooted in the genetics of these twoinnovation types which often differenti-ate on the degree of technological uncer-tainty, development time, andcomplexity of the development pro-cesses. Several prior studies exemplifythese different outcomes. For example,according to Faems, Van Looy, andDebackere (2005), collaboration withpartners from the value chain (customersand suppliers) provides a strong base forincremental development of existingproducts and services, whereas collabo-ration with academic institutionsincrease the ability of firms to driveradical development due to access tonew technologies. Similarly, Miotti andSachwald (2003) support the view thatopening the innovation process to inputsfrom research institutions could enablefirms to conduct research at the techno-logical frontier and develop patents fornew-to-the-world products. Moreover,forming innovation cooperation withcompetitors may also have a more posi-tive effect on the incremental dimensionof innovation performance (Belderbos,Carree, and Lokshin 2004). To conclude,we propose that two types of innovationperformance will be related to the openinnovation activities in different ways.

Hypotheses DevelopmentTechnology scouting represents an

internal search or scanning function

related to systematically assessing andobserving technology trends in order todetect opportunities and encounterthreats in a timely manner (Bianchi et al.2010; Katila 2002; Laursen and Salter2006; Lichtenthaler 2007). The purpose oftechnology scouting is not to gather largesets of detailed information, but rather tocreate insights or awareness regardingsignificant patterns of change in the exter-nal environment (Van Wyk 1997).However, due to the complexity anddynamism of technological develop-ments, it is challenging for most firms togenerate an appropriate information baseabout the technological trends (Licht-enthaler 2003). Still, the scouting compo-nent has been highlighted in priorseminar work on absorptive capacity(Cohen and Levinthal 1990), and sug-gested to be a key cornerstone for thetheoretical framework of open innovation(Lichtenthaler and Lichtenthaler 2010).

A recent study by Lichtenthaler,Lichtenthaler, and Frishammar (2009)shows the importance of analyzing afirm’s technological environment to gatherideas, information, and knowledge usefulto support its internal innovation process,although this study was performedoutside the SME context. Thus, firmswith advanced scouting mechanismswould be able to identify opportunitygaps in the market and undertake sounddecisions regarding which innovativeproducts ideas to develop. Moreover, byintroducing such innovative productsbefore their competitors, they would beable to realize a “first mover advantage”(Cohen and Levinthal 1990). This func-tion can become particularly importantfor SMEs with limited internal resourcesand by having a clear direction for inno-vative product development so that theycan utilize their resources effectively.

However, technology scouting canhave negative effects on innovation per-formance of SMEs as it can result in theidentification of too many potential ideas(Frishammar and Hörte 2005). In such


cases, SMEs might struggle to allocatesufficient internal resources to manageand prioritize ideas. In addition, SMEsmay also lack the ability to balance“attention allocation,” leading to negativeconsequences (Koput 1997). However,as suggested by Laursen and Salter(2006, p. 146), “firms who are more opento external sources or search channelsare more likely to have higher level ofinnovative performance. Openness toexternal sources allows firms to draw inideas from outside to deepen the pool oftechnological opportunities available tothem.” Therefore, we propose that tech-nology scouting represents an importantinbound open innovation activity, whichhas the potential to drive innovation per-formance of SMEs.

H1a: Technology scouting is positivelyrelated to innovation performance inSMEs.

Even if technology scouting seemsbeneficial for radical innovation perfor-mance as a way to acquire novel ideas thatcan lead to development of breakthroughproducts, we argue that techno-logy scouting is more likely to enhanceincremental innovation as it may help thefocal firm to hone its present innovationprocess. This is because in comparison tolarger firms, SMEs possess specializedand deep knowledge (Gans and Stern2003; Giarratana 2004). Moreover, SMEsusually have a focused business portfolio,which represents their strength (Vossen1998) but also limits their ability to scanand search for technological opportuni-ties outside their own industry (Bianchiet al. 2010; Zahra and George 2002).Thus, they are normally better at conduct-ing local search or scouting activities thansearching for diverse and novel knowl-edge. This is due to the fact that firmslargely depend on preexisting knowledgebases for scouting activities which, in thecase of SMEs, often are limited. SMEs canovercome this limitation by employing a

broader and deeper search or scanningstrategy of their external environment(Laursen and Salter 2006), but this ischallenged by resource constrains. Con-siderable resources may be needed interms of recruiting specialized employeesand develop dedicated technology scout-ing units, which are costly and seldomfeasible for SMEs (Rothwell and Dodgson1991). Thus, we propose that SMEs nor-mally would prefer to scout within theirknown industrial boundaries, whichmakes them more likely to achieve incre-mental innovation as compared withradical innovation. Therefore, we suggestthe following hypothesis:

H1b: Technology scouting is morestrongly related to incremental asopposed to radical innovation perfor-mance in SMEs.

Vertical technology collaborationcaptures collaborative relationshipswith customers (i.e., vertical down-stream collaboration) or supplier (i.e.,vertical upstream collaboration) (Baum,Calabrese, and Silverman 2000).However, in the context of open innova-tion, multiple studies regard verticaltechnology collaboration with presentcustomers, potential customers, and endusers as one of the key alternatives for animproved internal innovation process(Chesbrough, Vanhaverbeke, and West2006; Gassmann 2006; Henkel 2006; VonHippel 2005). Thus, in this study, wespecifically focus on the vertical down-stream technology collaboration.

According to Gemünden, Heydebreck,and Herden (1992), approximately75 percent of firms are integrating cus-tomers into their innovation process.However, the intensity of collaborationmay differ widely. In the context of openinnovation, vertical technology collabora-tion could represent a more activeinvolvement of customers and users asthey become key stakeholders in thedevelopment process, and in certain


cases, codevelop technologies together(Chesbrough 2003; Enkel, Kausch, andGassmann 2005). SMEs usually considercollaboration with larger customer firmsas they hold strong resources to convertideas and inventions into commerciallyviable innovative products. Therefore, itis not surprising that SMEs in severalindustries, such as in the biotech industry,have long been associated with initiatingcollaboration joint projects where theyprovide the specialized knowledge fordevelopment of the innovative product,whereas large firms provide the neededinfrastructure and resources for manufac-turing, marketing, and commercialization(Kleinknecht and Reijnen 1992; Oliver2001). SMEs can also struggle to tap intotheir present and potential customersneed and requirements. This challenge isincreasingly becoming obsolete due tothe increased use of information and com-munication technology, which facilitatesSMEs to access customer insights in acost-effective manner (Dahan and Hauser2002).

According to Dyer and Singh (1998),vertical technology collaboration couldincrease the ability of a firm to innovateand create value because it becomesmore aware of customers’ needs andexpectations. Moreover, involving cus-tomers in the early phases of innovationsignificantly reduces risks in develop-ment and improve the likelihood of inno-vation success (Ragatz, Handfield, andPetersen 2002). Customer collaborationin the innovation process could also havea positive influence on idea generation,product concept development, prototypetesting, and market launch, leadingto innovation success (Gruner andHomburg 2000).

Another aspect of vertical technologycollaboration concerns collaboratingwith qualified customers, that is, leadusers. This group of users are usuallyforerunners regarding the products theyuse, and could thus provide uniqueinsights critical to the internal innovation

process (Von Hippel 2005). In addition,there are cases when users have devel-oped their own products that producershave later imitated successfully. Thus,assuring customer and user inputs helpsfirms produce customized and commer-cially viable products. Firms might alsocodevelop products with certain custom-ers and users such as in the case of opensource software development (Henkel2006). Still, there are drawbacks withvertical technology collaboration too. Forexample, firms that follow their custom-ers too closely may loose their competi-tive advantage (Christensen and Bower1996). Still, it appears that the gains out-weigh the drawbacks, and we proposethe following hypothesis.

H2a: Vertical technology collaborationis positively associated to innovationperformance in SMEs.

With respect to vertical technologycollaboration, perhaps most clearly, leadusers may be critical to achieve radicalinnovation by informing the firm aboutentirely new product and service options(Von Hippel 2005), but customerinvolvement generally appears linked toincremental innovation. For example,using customer feedback and customerinteraction for improving the currentproducts and services (Belderbos,Carree, and Lokshin 2004; Christensenand Bower 1996; Enkel, Perez-Freije, andGassmann 2005; Faems, Van Looy, andDebackere 2005). This could beexplained by understanding the risksassociated with vertical technology col-laboration. According to Enkel, Kausch,and Gassmann (2005), quite often, partsof customers’ insights are lost in the inte-gration process, which means that a firmmay not actually understand those needscorrectly, blindly depending on custom-ers’ demands, personality, and viewsmay also limit the level of innovative-ness, and end up developing productsfor a niche market. Moreover, as custom-


ers who are involved in the innovationprocess largely rely on their experience,they could only be able to reflect uponhow to improve the products they arefamiliar with, rather than trying toprovide inputs for developing radicalproducts (Von Hippel 2005). Therefore,we suggest the following hypothesis:

H2b: Vertical technology collaboration ismore strongly related to incrementalas opposed to radical innovation per-formance in SMEs.

Horizontal technology collaborationrefers to collaborating with partnersthat are not part of the value chain of aparticular SME. These linkages couldinclude partners from similar or otherindustries, such as competitors or non-competitors, and they can be largefirms or other SMEs. Forming R&D col-laboration with noncompetitor firms istypically easier due to the possibility ofdeveloping win–win collaboration asboth actors could see the advantage ofcombing resources and competences todevelop innovative products (Pittawayet al. 2004). SMEs may find it attractiveto initiate a risk and revenue-sharingagreement with partners across indus-tries as the cost of innovative develop-ment usually tends to be prohibitivelyhigh for SMEs compared with theirlarger counterparts that can sustainlarge R&D units (Baum, Calabrese, andSilverman 2000). In comparison, tech-nological collaboration with competingfirms can be complex and risky, but ifcollaborating firms can identify commongoals, the likelihood of leveraging tech-nological development through externalsupport can increase significantly (Leeet al. 2010; Lichtenthaler 2005). More-over, when a competing partner firm isfrom the same or similar industry,it could facilitate the access to andinterpretation of uncodified knowledgeleading to innovation success (Liebe-skind et al. 1996).

In addition, due to the ever-increasingcomplex nature of technological prod-ucts, SMEs may find it overwhelming tohandle R&D activities by themselves.Thus, forming collaboration with com-petitors and/or noncompeting firms toacquire and leverage from their techno-logy capabilities could be a beneficialstrategy (Hagedoorn, Roijakkersand, andVan Kranenburg 2006). SMEs couldbenefit from exploring innovative deve-lopment and commercialization opportu-nities with other small established firmsas they can jointly enter new markets andsubstantially improve their chancesagainst larger competitors (Christensen,Olesen, and Kjær 2005; Lee et al. 2010). Inaddition, horizontal technological col-laboration can have a “spillover effect” forSMEs as they may benefit from the expe-riences of their partner firms, which couldlead to learning effects for future innova-tive developments (Argote and Ingram2000).

Although compelling, the open inno-vation activity of horizontal technologi-cal collaboration can also have negativeeffects for SMEs’ innovative perfor-mance. For example, forming strategicalliances with partners outside the valuechain could result in higher transactioncosts as collaborating partners may free-ride by restricting contribution to the col-laboration or act opportunistically(Bessant, Kaplinsky, and Lamming 2003;Bradley, Meyer, and Gao 2006; Hameland Prahalad 1994). In either case, SMEscould suffer major losses due to the lackof resources and negotiation power tomeet such unpredictable partner behav-ior. However, in light of the significantpotential benefits associated with theinbound open innovation activity of hori-zontal technology collaboration, wehypothesize a positive effect on innova-tion performance of SMEs.

H3a: Horizontal technology collabora-tion is positively associated to innova-tion performance in SMEs.


Technology collaboration outside thevalue chain can be useful for incrementalinnovation performance as SMEs canbenefit from the expertise and experi-ence of collaborating firms to makeimprovements to their products.However, as technology collaborationinvolves greater risks, it can be expectedthat SMEs will engage in such collabora-tion when they foresee a clear potentialfor more radical development. Moreover,as SMEs expand collaboration with part-ners across industry, they develop non-redundant network relationships, whichcan have a positive influence on SMEsability to access more diverse informa-tion and resources (Burt 2004). Throughsuch collaborations, SMEs can createnew and highly innovative technologicalcombinations (Katila 2002; Katila andAhuja 2002), leading to positively influ-encing the radical dimension of innova-tion performance. This also links to adiscussion in social network research,which suggests that radical innovation ismuch more contingent on “weak ties,” asthrough such links, SMEs can gain accessto new and distant knowledge and infor-mation (Burt 2004; Kim and Aldrich2005).

SMEs may also utilize horizontal col-laborations for ensuring successful com-mercialization and marketing of radicalinnovations in new markets (Pittawayet al. 2004). In addition, the competitorand noncompetitor partners may providethe legitimacy and recognition toSMEs for enhancing radical innovationperformance. Thus, we propose thathorizontal technology collaboration withdifferent actors is an important openinnovation activity for SMEs and wouldbe strongly linked to radical innovationperformance.

H3b: Horizontal technology collabora-tion is more strongly related toradical as opposed to incre-mental innovation performance inSMEs.

Technology sourcing represents anopen innovation activity for buying orusing external technology through IPagreements. Many SMEs can benefit fromthis activity because they are faced withthe challenge of shortened product lifecycles, rapid changes in technologies,and shortage of capital. According to VanDe Vrande et al. (2009), SMEs canaddress these challenges by licensingin technology from external sourcesas it can fuel and accelerate theirinternal innovation process. Chesbrough,Vanhaverbeke, and West (2006) suggestthat such inward technology sourcing ispractically important for firms operatingin an R&D-intensive (high-tech) industryas there is usually high demand on themto be innovative. Although external acqui-sition of technological know-how couldbe a strategic innovation activity, firmsmay struggle with this transfer due to thehigh level of tacit knowledge associatedwith the technologies (Vanhaverbeke,Duysters, and Noorderhaven 2002). Nev-ertheless, many SMEs aim to capitalizeon external knowledge by technologysourcing from different actors, such asother firms, research institutions, anduniversities for three reasons. First,focusing on internal R&D requires largeinvestments of capital, time, and person-nel. These investment costs could be sig-nificantly reduced when SMEs opt fortechnology sourcing as they would focusonly on search, evaluation, adaptation,and royalty costs (Atuahene-Gima 1993).Second, if firms focus on internal inno-vation processes, they would limit theirability to be flexible to the emergingopportunities as a development cyclerequires long lead times (Håkansson andLaage-Hellman 1984). Thus, throughtechnology sourcing, SMEs can advancetheir internal innovation process as theycan integrate almost-ready technologiesfrom external sources and use it toaddress the emerging gaps in the market(Anokhin, Wincent, and Frishammar2011; Chesbrough, Vanhaverbeke, and


West 2006). According to Teece (1989, p.38), technology sourcing and similaractivities enable firms to “preserve anopen window on science and technologyand to alert to changing opportunitiesand threats.” Finally, technology sourc-ing can improve innovation performancebecause it allows SMEs to developcomplex product through integration oftested and proven technologies(Atuahene-Gima 1992; Tao and Magnotta2006). However, there are clear draw-backs to extensive sourcing as well. First,too much sourcing may lead to limitedinternal development of critical techno-logical knowledge, and thus reducedpossibilities to develop technologicalcore competencies (Lichtenthaler 2010).In addition, SMEs may experience pro-blems with the “not invented here” syn-drome (Katz and Allen 1982), whichcould make it difficult to exploit techno-logy developed elsewhere. Again,however, the potential upsides seem tooutweigh the risks, and we propose thefollowing hypothesis.

H4a: Technology scouring is positivelyassociated with innovation perfor-mance in SMEs.

As most SMEs operate in a nichemarket and offer their product to specificcustomer segments, they are usually wellinformed about customers’ needs andrequirements (Pittaway et al. 2004).Thus, by combining their market knowl-edge with technology scouring activities,they can make incremental innovationand continue to generate revenues. Suchinitiatives would require low investmenton the part of the SMEs and still makethem innovative in their current market(Atuahene-Gima 1993). However, weargue that inward technology scouringmay have a stronger role for radical inno-vation. As development of new-to-the-world type of innovations required SMEsto access and gain from diverse knowl-edge bases and competences, they can

fill these gaps through licensing in tech-nologies from external actors. The role ofuniversities and research institutionscould be pivotal because several innova-tions would not have been achievedwithout their influence (Fontana, Geuna,and Matt 2006). University and researchinstitutions are well known sources ofoffering such specialized technologiesand knowledge, which SMEs can benefitfrom and use as a base for the develop-ment of radical innovation (Mohnen andHoareau 2003). Moreover, as the tech-nologies are mature and pretested, therisk of product failure is reduced evenwhen developing radically new products.Therefore, we propose the followinghypothesis.

H4b: Technology sourcing is morestrongly related to radical as opposedto incremental innovation perfor-mance in SMEs.

The eight hypotheses discussed in thissection form the basis of Figure 1. Theunderlying logic in this model is that allfour inbound open innovation activitiespositively influence both types of inno-vation performance but to differentdegrees. A thick arrow indicates a strong-(er) relationship, whereas a thin arrowindicates a weak(er) relationship.

MethodsSample and data collection

To test the hypotheses, a survey tar-geting technology-based SMEs in theinformation and technology (IT) sector inSweden was conducted between Marchand May of 2009. Technology-basedSMEs were selected because these firmsoperate in a dynamic environment whereinnovative abilities are necessary forgrowth and survival. Moreover, welimited the survey to a single industry toavoid unnecessary “noise” due to indus-try factors (Westerberg, Singh, andHäckner 1997).


A Swedish business database (Affärs-data) containing all active firms inSweden was used to obtain the sample,where we included firms classifiedaccording to SIC 62010 and 62020,representing firms involved withconsultancy-related computer systemsor computer software production.1 Weemployed two sampling constraints.First, the targeted firms should be SMEsaccording to the European Union defi-nition, and thus have fewer than 250employees. Second, the firms shouldhave a turnover of at least USD150,0002 to ensure an active firm. Asthe vast majority of firms only have afew employees, we sample only a smallportion of firms up to seven employees(300 out of a total 1,500). For firmswith eight employees and up, all firmswere included in the sampling frame.This means that the results mainlyreflect firms with more than eightemployees. This resulted in the identi-fication of 1,500 firms, which was con-sidered as the total population for thesurvey.

A self-administrated questionnairewas subsequently developed. Toenhance external validity, the question-naire was checked for any problems orirregularities, and was pretested on fiveCEOs of SMEs and five academics. Thesurvey was addressed to the CEO of eachSME, with a cover letter explaining thepurpose of the study. After a reminder, atotal of 252 usable and complete ques-tionnaires were received, a response rateof 16 percent. As the study targeted theCEOs of SMEs, it is expected to be quitelow (Baruch 1999; Baruch and Holtom2008), and the study’s response rate mayhave been exacerbated by the negativeeconomic climate and an increasedresearch focus on SMEs, especially in theinformation and communications tech-nology sector. Still, a nonresponse analy-sis including the variables of age (year ofestablishment), size (number of employ-ees), profitability, sales, sales peremployees, and solidity (the degree ofinternally funded capital) showed no sig-nificant differences between respondentsand nonrespondents.

1Since the Swedish industry code system is not fully compatible with US SIC, it is not possibleto find a perfect matching. However, the sampled firms are all part of industries with the USSIC starting with 737.2Based on a currency rate where 1 USD = 6.67 SEK.

Figure 1Illustration of the Proposed Hypotheses

H3

H2

H1

Technology Scouting

Vertical Technology Collaboration

Horizontal Technology Collaboration

Technology Sourcing

Incremental Innovation Performance

Radical Innovation Performance H4


MeasuresBased on and inspired by the study by

Van De Vrande et al. (2009), we mea-sured four inbound open innovationactivities. First, technology scouting(three items) refers to the process ofobserving technology trends, viewingexternal sources for ideas and knowl-edge, and collecting informationabout the technological environment(a = 0.82). Second, horizontal technologycollaboration refers to opening theproduct development process for extend-ing the collaboration with actors or part-ners outside the value chain of an SME.Three items were used for this con-struct, all of which address the practiceof cooperating with other firms (com-petitors and/or noncompetitors), net-working to exchange experiences/knowledge with partners, and benefitingfrom important inputs from partners(a = 0.83). Third, vertical technology col-laboration (three items) refers to theprocess of integrating inputs frompresent and potential customers, andend users (a = 0.82). Finally, technologysourcing (two items) is the process ofaccessing, using, and buying technolo-gies from other firms and institutions fordriving the product developmentprocess. In the open innovation context,it can also be regarded as the process ofinward IP licensing of technologies(a = 0.67). For details on the factor load-ings, see appendix A.

Innovative performance was thedependent variable, which we measuredby employing the scales developed byLaursen and Salter (2006), and Atuahene-Gima (2005). Radical innovation indi-cated the ability of the firms to produceinnovations that were “new to theworld.” Incremental innovation is thefirms’ ability to produce product innova-tions that were “new to the firm.” Basedon these dimensions, the respondentswere asked to report the frequency ofsuch innovations in the last three yearsand the amount of such innovations

launched in comparison to their competi-tors in the last three years (two items).The innovative performance dimensionof radical innovation (a = 0.93) andincremental innovation (a = 0.85) scalesboth showed acceptable reliability. Thetwo dimensions were considered impor-tant to capture the differences in terms ofinnovative outcomes, which have beenlacking in many prior studies (Lane,Koka, and Pathak 2006).

Several control variables were used.Firm age was calculated by the log of thenumber of years since establishment, andwas included because younger firmstend to be more innovative even whenthey possess less-developed capabilitiesand resources (Huergo and Jaumandreu2004). Another control variable was firmsize, which was calculated by taking thelog of the total number of employees.Size was considered important becauselarger firms might be able to innovatefaster than small firms due to their pos-session of greater resources (Dewar andDutton 1986). Possible influences of theenvironment were based on Miller andFriesen (1982) and capture hostility (fouritems), heterogeneity (three items),product dynamism (two items), andmarket dynamism (two items). Finally,we also controlled for the degree ofinternationalization (percentage of saleson international market) as SMEs that aremore internationally oriented tend tobe more innovative (Frishammar andAndersson 2009).

Analytical proceduresWe used conventional hierarchical

regression analysis to test the relation-ships between the four inbound openinnovation activities and the two dimen-sions of innovative performance. Col-linearity tests were performed to analyzeto what extent each of the individualconstruct scores were dependent on theother construct scores. All variance infla-tion factor values were less than 1.7,which suggested multicollinearity was


not a major problem (Hair et al. 2006).To test for common method bias, wefollowed the guidelines set by Podsakoffet al. (2003) and Podsakoff and Organ(1986). We thus used a Harmon factoranalysis by entering all the self-reportedvariables used in the analysis into afactor analysis. Four factors with eigen-values > 1.0 were extracted, accountingfor 60.59 percent of the variance. Thefirst factor accounted for 22.86 percent ofthe variance. Because more than onefactor was identified, and individualfactors accounted for the majority of thevariance explained, common methodbias was not judged as a major issue,although we cannot fully rule out theexistence of a common method bias.

ResultsThe correlations and descriptive statis-

tics are listed in Table 2, whereas Table 3displays the results of the regressionanalysis. In short, all four a-hypothesesreceived support as all inbound openinnovation activities have a positive andsignificant effect on either incremental orradical innovation performance, whereasonly two of the b-hypotheses receivedsupport.

Turning to the individual hypotheses,H1a receives strong support as techno-logy scanning is significantly related toboth incremental (b = 0.17, p < .01) andradical (b = 0.11, p < .10) innovation.H1b is weakly supported as the coeffi-cient for incremental is higher than thatof radical innovation. However, the coef-ficients are not significantly differentfrom each other. H2a received mixedsupport as vertical technology collabora-tion is significantly related to radical(b = 0.15, p < .05) but not to incremental(b = 0.08, n.s.) innovation. H2b wasrejected as the only significant result isfound for the link to radical innovation.Similar to H2a, H3a received mixedsupport, where horizontal technologycollaboration is significantly linked toincremental (b = 0.14, p < .05) but not to

radical (b = 0.00, n.s.) innovation. H3bwas rejected as the significant result isevidenced for incremental innovation.Finally, H4 received strong support forboth the a and b hypotheses. For H4a,technology sourcing was significantlylinked to both incremental (b = 0.16,p < .05) and radical (b = 0.37, p < .01)innovation. For H4b, the strongest effectwas found for radical innovation, and itis also significantly stronger than theeffect on incremental innovation.

Discussion andConclusions

In this study, we explored the theo-retical concept of inbound open inno-vation in the SME context. Morespecifically, we have empirically inves-tigated the effect of four inbound openinnovation activities on innovation per-formance of SMEs. Our empirical resultshave provided strong support for theimportance of open innovation in thecontext of SMEs. Despite activelyaddressing these inbound activities,many SMEs still experience major diffi-culties in performing open innovationactivities, which constitutes key mana-gerial challenges for SMEs opting for amore open approach to innovation. Thepositive effects of the inbound activi-ties, thus, highlight the link betweensuch activities and innovative perfor-mance in the context of increasinglyopen innovation processes amongSMEs. Altogether, these results deepenour understanding of previouslyreported discrepancies between success-ful and less successful SMEs involvedwith open innovation (Bianchi et al.2010; Henkel 2006; Laursen and Salter2006; Lichtenthaler 2008a; Van DeVrande et al. 2009). The findings areparticularly relevant in light of agrowing interest of both academics andmanagers of SMEs to understand theenablers of and barriers to successfulinbound open innovation activities.


Tab

le2

Mea

n,

Sta

ndar

dD

evia

tion,

and

Corr

elat

ion

Mat

rix

Lat

ent

Const

ruct

Mea

nS.

D.

Cro

nbac

h’s

Alp

ha

12

34

56

78

910

11

12

13

1.Rad

ical

Innova

tion

Per

form

ance

-0.2

02.

000.

93

2.In

crem

enta

lIn

nova

tion

Per

form

ance

0.85

1.62

0.85

0.5

1

3.Si

ze(l

og)

2.85

1.22

NA

0.1

50.2

44.

Age

(log)

2.5

0.84

NA

0.06

0.08

0.10

5.D

ynam

ism

Pro

duct

-0.5

21.

360.

680.

080.

02-0

.03

-0.0

36.

Dyn

amis

mM

arket

-0.3

01.

170.

610.2

10

.15

0.03

0.07

-0.0

27.

Het

eroge

nei

ty0.

351.

570.

820.

050

.15

0.1

90.

030.

010.2

08.

Host

ility

0.31

1.12

0.69

-0.0

6-0

.09

0.1

50.

02-0

.11

0.2

90.2

39.

Inte

rnat

ional

izat

ion

19.4

30.6

NA

0.2

60

.13

0.2

3-0

.01

0.11

0.1

30.

090.

0610

.Tec

hnolo

gySc

outing

1.47

1.05

0.82

0.3

30.3

60

.16

0.1

3-0

.03

0.08

0.03

-0.0

40.

0911

.H

ori

zonta

lTec

hnolo

gyCollab

ora

tion

2.43

1.61

0.83

0.2

30.3

30

.15

0.11

-0.0

2-0

.01

0.11

-0.0

80.

060.3

6

12.

Ver

tica

lTec

hnolo

gyCollab

ora

tion

2.97

1.71

0.82

0.3

20.3

50.1

90.

12-0

.02

0.04

0.1

5-0

.13

0.1

30.4

20.5

7

13.

Tec

hnolo

gySo

urc

ing

-0.4

11.

520.

670.4

90.3

30.1

80

.15

0.05

0.1

50.

01-0

.02

0.11

0.3

50.2

60.2

51

N=

252.

Corr

elat

ions

are

sign

ifica

nt

atth

e0.0

1le

vel

and

atth

e0

.05

leve

l.Pea

rson

(2-tai

led).


Theoretical implicationsThe empirical findings have high-

lighted that the adoption and utilizationof open innovation activities can posi-tively influence innovative performanceof SMEs. This notion is strongly sup-ported as all four inbound activities arelinked positively to at least one aspect ofinnovation performance and there is nonegative links present. The few priorstudies on the topic agree on this impor-tance of SMEs opening their innovationprocess to external influences (Bianchi

et al. 2010; Henkel 2006; Lee et al. 2010),although there has been a lack of quan-titative empirical support prior to ourstudy. Moreover, the survey studiesby Van De Vrande et al. (2009) andLichtenthaler (2008a) have found thatopen innovation is mainly driven bylarger companies than SMEs due to theassociated challenges. We build on theirfindings and argue that if SMEs canperform technology scouting, verticaland horizontal technology collaboration,as well as technology sourcing, they can

Table 3Regression Analysis for Open Innovation Practices in

Small and Medium-Sized Enterprises

Radical InnovationPerformance New

to the World

Incremental InnovationPerformance New

to the Firm

Size (log) 0.110* 0.006 0.228*** 0.143**Age (log) 0.040 -0.033 0.047 -0.013Dynamism Product 0.045 0.041 -0.005 0.004Dynamism Market 0.224*** 0.144** 0.172*** 0.126**Heterogeneity 0.000 -0.005 0.113* 0.092Hostility -0.1542 -0.076 -0.211 -0.140Internationalization 0.217*** 0.173*** 0.059 0.027Technology Scouting 0.114* 0.173***Horizontal Technology

Collaboration-0.002 0.138**

Vertical Technology Collaboration 0.152** 0.088Technology Sourcing 0.375*** 0.158**F-ratio 5.54 12.0 5.22 8.29R2 0.137 0.355 0.13 0.274R2(adj) 0.112 0.325 0.105 0.241Sign <0.001 <0.001 <0.001 <0.001R2 Change 0.218 0.145F (R2 Change) 20.3 12.0Sign (R2 Change) <0.001 <0.001

N = 252. *p < .10; **p < .05; ***p < .01.Regression coefficients shown are beta coefficients.


partly overcome their liability of small-ness and drive their innovation perfor-mance better than if all innovativeactivities are done in-house.

In general, most of the research onopen innovation in SMEs have been con-ceptual or qualitative, which has resultedin a lack of understanding of more gen-eralized findings and effects. We closethis gap in the technology and innova-tion management literature by not onlyidentifying innovation performance as asuitable dependent variable for futurestudies on the topic of open innovationbut also by distinguishing radical fromincremental dimensions (Atuahene-Gima2005; Laursen and Salter 2006). Ourresults provide credence for this as wefind that inbound open innovation activi-ties have different influence patterns onthe two aspects of innovation perfor-mance. This could be of specific impor-tance for SMEs because the contingencyfor both dimensions of innovation per-formance are significantly varied basedon the level of risk, investment, anddevelopment time (Chaney, Devinney,and Winer 1991; Ettlie, Bridges, andO’Keefe 1984; Sher and Yang 2005).

For example, our analysis shows arather strong support for how techno-logy scouting and technology sourcingaffect the different aspects of innovationperformance. Scanning tends to be moreimportant for incremental innovation,whereas sourcing is more important forradical innovation, which is fully in linewith the stated hypotheses. Moreover, itis important to note that technologyscouting and sourcing are two inboundopen innovation activities that are linkedto both incremental and radical innova-tion performance. Therefore, and inline with the prior studies in techno-logy and innovation management(Bianchi et al. 2010; Chesbrough, Vanha-verbeke, and West 2006; Van De Vrandeet al. 2009), we support the view that anemphasis on these activities by SMEswould fuel their innovation process.

Regarding the technology collabora-tion hypotheses, the pattern we antici-pated is completely reversed as verticaltechnology collaboration was found tohave an influence on radical innovationperformance and horizontal technologycollaboration instead of incrementalinnovation performance. This counterin-tuitive result may reside in the particularcircumstances of the empirical domain ofour study. Several studies have held theview that vertical (customer and enduser) collaboration mainly drives incre-mental innovation (Belderbos, Carree,and Lokshin 2004; Faems, Van Looy, andDebackere 2005; Pittaway et al. 2004),but in the high technology-based indus-try, customers tend to be larger firms(e.g., IBM and Siemens) that are moreaware and informed about their currentand future requirements. Thus, they mayactually drive radical development intechnologically specialized SMEs to meettheir emerging needs. Moreover, recentstudies in the field of open source canalso provide some explanation as in thatcontext of end users and lead usersdriving radical development (Henkel2006). In line with the earlier argument,Von Hippel and Katz (2002) propose thatwithin the high-tech industry, severalfirms are using an entirely new approach(user innovation) to product develop-ment, where users are given the tools tobe innovative. Thus, SMEs in high-techindustries may actually gain inputs fromcustomers and end users about develop-ing new-to-the-world innovations, com-pared with developing significantimprovement to existing products. Thus,contrary to the view within the technol-ogy and innovation management litera-ture, our study provides an alternativeexplanation on how SMEs can benefitfrom vertical technology collaboration.

Contrary to our hypothesis, horizontaltechnology collaboration was found tohave a positive influence on incrementalinnovation performance. SMEs in thetechnology sector (e.g., biotech) form


horizontal collaborations with competi-tor and noncompetitor firms for shar-ing risks and cost of development(Kleinknecht and Reijnen 1992; Oliver2001). However, such collaborations areknown to suffer from high transactioncosts and opportunistic behavior on thepart of large firms (Christensen, Olesen,and Kjær 2005). Therefore, it can beexpected that SMEs may opt for a moreconservative collaboration strategy,where they focus on using horizontalcollaboration for market diversificationor creating new to industry productbundling.

In conclusion, SMEs can greatlybenefit from these key inbound openinnovation activities to advance theirinnovation performance. However, whenmaking the choice as to which activitythey should invest their limitedresources, the present study provides aslightly more complex picture than thefindings reported in prior literature.

Managerial implicationsBased on our study, it seems clear that

managers of SMEs in high-tech industriesstriving to increase their innovation per-formance should consider a more openapproach to innovation. As technologyscouting is fairly easy to implement andalso has strong positive effects on inno-vation performance, it seems appropriateto start with this activity. Doing so, theSME probably can reap significant ben-efits for a rather limited cost, and tech-nology scouting also seems to be a goodstart regardless of the innovation ambi-tions in the firm.

The next step toward adoption ofopen innovation largely depends onwhether incremental or radical innova-tion is the main focus of the firm. If thefocal SME is inclined toward new-to-the-industry types of innovation (incrementalinnovation), which usually involveslower levels of investment, then ourresults indicate that much can be gainedby collaborating with partners outside

the value chain. Such horizontal techno-logy collaboration with other firms canbe beneficial for sharing developmentcosts and sharing information. However,due to the risks associated with it, asnoted by Christensen, Olesen, and Kjær(2005), it may be worthwhile to initiatecollaboration with smaller firms ratherthan larger firms during the initial stagesof innovation development.

If radical innovation is targeted bySME managers, then it will be advisableto team up with strong customer firms inthe value chain and become a specializedsupplier for them in the area where thefirm has its competence base. An alter-native is to set up and organize interac-tions with end users and lead users thatcan provide insights about future marketneeds. Technology sourcing is also aviable alternative to achieve radical inno-vation. Acquiring licenses or other formsof technology, or tapping into universityknowledge that can help the company tocommercialize new-to-the-world prod-ucts (including services) or processes canprovide a relatively safe shortcut toradical innovation (Chesbrough, Vanha-verbeke, and West 2006; Mohnen andHoareau 2003). Thus, we would like toencourage SME managers to open theirinnovation process to more fully capturethe value from technology, and to utilizethe four suggested inbound open inno-vation activities to drive radical orincremental innovation performance,respectively.

Limitations and OutlookThis study has made an effort at con-

tributing to the literature in technologyand innovation management, and smallbusiness management by advancing ourknowledge regarding effects of openinnovation activities in the context ofSMEs. Although our study has attemptedto fill this gap, it has several limitations.First, the focus of this study has beensolely on inbound open innovationactivities. We understand that this repre-


sents an incomplete view on open inno-vation as the dimensions of outboundactivities were not included. The studyby Van De Vrande et al. (2009), forexample, highlights venturing or spin-offs, outward IP licensing, and employeeinvolvement as three key outboundactivities. Second, we have focused on asample of Swedish high technology-based SMEs. This limits generalizabilityoutside this context. However, doing sohas provided us with the possibility toreduce uncontrolled noise in our sample,and future studies could benefit frombuilding on our findings and testing thestated hypothesis in a larger sample frommultiple industries and countries. More-over, we have only examined the effectsof open innovation activities, but theantecedents to these are still unexplored.We can also expect that the relationshipbetween open innovation actives andinnovative performance can be moder-ated by certain variables, such as tech-nology strategy or external environmentconditions. Finally, there may be interac-tion effects. Although not specificallyfocused in the present study, there is aprobability that the proposed open inno-vation activities may substitute or com-pliment the effects on innovationperformance dimensions of radical inno-vation and incremental innovation. Thus,future studies can explore the suggestedresearch directions and build on thelimited body of knowledge on openinnovation and SMEs.

Another limitation is the reliance onperceptual measures and possible prob-lems with common method variance, andwe thus encourage future studies withobjective measures, especially concern-ing the dependent variables. Altogether,we find that the role and effects of openinnovation activities in the context ofSMEs is an underresearched topic thatneeds further attention from researchersin technology and innovation manage-ment, and we hope that our studyhas provided an initial step toward

understanding the complexities aroundthis relationship.

ReferencesAnokhin, S., J. Wincent, and J.

Frishammar (2011). “A ConceptualFramework for Misfit TechnologyCommercialization,” TechnologicalForecasting and Social Change 78(6),1060–1071.

Argote, L., and P. Ingram (2000).“Knowledge Transfer: A Basis forCompetitive Advantage in Firms,”Organizational Behavior and HumanDecision Processes 82(1), 150–169.

Atuahene-Gima, K. (1992). “InwardTechnology Licensing as an Alterna-tive to Internal R&D in New ProductDevelopment: A Conceptual Frame-work,” Journal of Product InnovationManagement 9(2), 156–167.

——— (1993). “Buying Technology forProduct Development in SmallerFirms,” Industrial Marketing Manage-ment 22(3), 223–232.

——— (2005). “Resolving the Capability:Rigidity Paradox in New ProductInnovation,” Journal of Marketing69(4), 61–83.

Baruch, Y. (1999). “Response Rate inAcademic Studies—A ComparativeAnalysis,” Human Relations 52(4),421–438.

Baruch, Y., and B. C. Holtom (2008).“Survey Response Rate Levels andTrends in Organizational Research,”Human Relations 61(8), 1139–1160.

Baum, J. A. C., T. Calabrese, and B. S.Silverman (2000). “Don’t Go It Alone:Alliance Network Composition andStartups’ Performance in CanadianBiotechnology,” Strategic Manage-ment Journal 21(3), 267–294.

Belderbos, R., M. Carree, and B. Lokshin(2004). “Cooperative R&D and FirmPerformance,” Research Policy 33(10),1477–1492.

Bessant, J., R. Kaplinsky, and R.Lamming (2003). “Putting SupplyChain Learning into Practice,” Inter-


national Journal of Operations andProduction Management 23(2), 167–184.

Bianchi, M., S. C. Orto, F. Frattini, and P.Vercesi (2010). “Enabling Open Inno-vation in Small- and Medium-SizedEnterprises: How to Find AlternativeApplications for Your Technologies,”R and D Management 40(4), 414–430.

Bradley, F., R. Meyer, and Y. Gao (2006).“Use of Supplier-Customer Relation-ships by SMEs to Enter ForeignMarkets,” Industrial Marketing Man-agement 35(6), 652–665.

Burt, R. S. (2004). “Structural Holes andGood Ideas,” The American Journal ofSociology 110(2), 349–399.

Chaney, P. K., T. M. Devinney, and R. S.Winer (1991). “The Impact of NewProduct Introductions on the MarketValue of Firms,” Journal of Business64(4), 573–610.

Chesbrough, H. (2003). Open Innova-tion: The New Imperative for Creatingand Profiting from Technology.Boston, MA: Harvard Business SchoolPublishing Corporation.

Chesbrough, H., and A. K. Crowther(2006). “Beyond High Tech: EarlyAdopters of Open Innovation in OtherIndustries,” R and D Management36(3), 229–236.

Chesbrough, H., W. Vanhaverbeke, andJ. West, Eds. (2006). Open Innovation:Researching a New Paradigm. NewYork: Oxford University Press.

Christensen, C. M., and J. L. Bower(1996). “Customer Power, StrategicInvestment, and the Failure of LeadingFirms,” Strategic Management Journal17(3), 197–218.

Christensen, J. F., M. H. Olesen, and J. S.Kjær (2005). “The Industrial Dynamicsof Open Innovation: Evidence fromthe Transformation of Consumer Elec-tronics,” Research Policy 34(10),1553–1549.

Cohen, W. M., and D. A. Levinthal(1990). “Absorptive Capacity: A NewPerspective on Learning and In-

novation,” Administrative ScienceQuarterly 35(1), 128–152.

Cooper, R. G., S. J. Edgett, and E. J.Kleinschmidt (2003). Best Practices inProduct Innovation: What Distin-guishes Top Performers. Ancaster, ON:Product Development Institute.

Dahan, E., and J. R. Hauser (2002). “TheVirtual Customer,” Journal of ProductInnovation Management 19(5), 332–353.

De Toni, A., and G. Nassimbeni (2003).“Small and Medium District Enter-prises and the New ProductDevelopment Challenge,” Interna-tional Journal of Operations andProduction Management 23(6), 678–697.

Dewar, R. D., and J. E. Dutton (1986).“The Adoption of Radical and Incre-mental Innovations: An EmpiricalAnalysis,” Management Science32(11), 1422–1433.

Dyer, J. H., and H. Singh (1998). “TheRelational View: Cooperative Strategyand Sources of InterorganizationalCompetitive Advantage,” TheAcademy of Management Review23(4), 660–679.

Enkel, E., C. Kausch, and O. Gassmann(2005). “Managing the Risk ofCustomer Integration,” EuropeanManagement Journal 23(2), 203–213.

Enkel, E., J. Perez-Freije, and O.Gassmann (2005). “Minimizing MarketRisks Through Customer Integrationin New Product Development: Learn-ing from Bad Practice,” Creativity andInnovation Management 14(4), 425–437.

Ettlie, J. E., W. P. Bridges, and R. D.O’Keefe (1984). “Organization Strat-egy and Structural Differences forRadical versus Incremental Innova-tion,” Management Science 30(6),682–695.

Faems, D., B. Van Looy, and K.Debackere (2005). “Interorganiza-tional Collaboration and Innovation:Toward a Portfolio Approach,”


Journal of Product Innovation Man-agement 22(3), 238–250.

Fontana, R., A. Geuna, and M. Matt(2006). “Factors Affecting University-Industry R&D Projects: The Impor-tance of Searching, Screening andSignaling,” Research Policy 35(2),309–323.

Freel, M. S. (1999). “Where Are the SkillsGaps in Innovative Small Firms?”International Journal of Entrepre-neurial Behaviour and Research 5(3),144–154.

Frishammar, J., and S. Andersson (2009).“The Overestimated Role of StrategicOrientations for International Perfor-mance in Smaller Firms,” Journal ofInternational Entrepreneurship 7(1),57–77.

Frishammar, J., and Å. S. Hörte (2005).“Managing External Information inManufacturing Firms: The Impact onInnovation Performance,” Journal ofProduct Innovation Management22(3), 251–266.

Frishammar, J., U. Lichtenthaler, and J.Rundquist (2011). “Identifying Tech-nology Commercialization Opportuni-ties: The Importance of IntegratingProduct Development Knowledge,”Journal of Product Innovation Man-agement (in press).

Gans, J. S., and S. Stern (2003). “TheProduct Market and the Market for‘Ideas’: Commercialization Strategiesfor Technology Entrepreneurs,”Research Policy 32(2), 333–350.

Gassmann, O. (2006). “Opening Up theInnovation Process: Towards anAgenda,” R and D Management 36(3),22–228.

Gemünden, H. G., P. Heydebreck, andR. Herden (1992). “TechnologicalInterweavement: A Means ofAchieving Innovation Success,”R and D Management 22(4), 359–376.

Giarratana, M. S. (2004). “The Birth of aNew Industry: Entry by Start-Ups andthe Drivers of Firm Growth: The Case

of Encryption Software,” ResearchPolicy 33(5), 787–806.

Grando, A., and V. Belvedere (2006).“District’s Manufacturing Perfor-mances: A Comparison among Large,Small-to-Medium-Sized and DistrictEnterprises,” International Journal ofProduction Economics 104(1), 85–99.

Griffiths-Hemans, J., and R. Grover(2006). “Setting the Stage for CreativeNew Products: Investigating the IdeaFruition Process,” Journal of theAcademy of Marketing Science 34(1),27–39.

Grönlund, J., D. Rönnberg-Sjödin, and J.Frishammar (2010). “Open Innovationand the Stage-Gate Process: A RevisedModel for New Product Develop-ment,” California ManagementReview 52(3), 106–131.

Gruner, K. E., and C. Homburg (2000).“Does Customer Interaction EnhanceNew Product Success?,” Journal ofBusiness Research 49(1), 1–14.

Hagedoorn, J., N. Roijakkersand, and H.Van Kranenburg (2006). “Inter-FirmR&D Networks: The Importance ofStrategic Network Capabilities forHigh-Tech Partnership Formation,”British Journal of Management 17(1),39–53.

Hair, J. F., W. C. Black, B. J. Babin, R. E.Anderson, and R. L. Tatham (2006).Multivariate Data Analysis. UpperSaddle River, NJ: Pearson PrenticeHall.

Håkansson, H., and J. Laage-Hellman(1984). “Developing a Network R&DStrategy,” Journal of Product Innova-tion Management 1(4), 224–237.

Hamel, G., and C. K. Prahalad (1994).“Competing for the Future,” HarvardBusiness Review 72(4), 122–128.

Henkel, J. (2006). “Selective Revealing inOpen Innovation Processes: The Caseof Embedded Linux,” Research Policy35(7), 953–969.

Huergo, E., and J. Jaumandreu (2004).“How Does Probability of Innovation


Change with Firm Age?,” SmallBusiness Economics 22(3–4), 193–207.

Jarillo, J. C. (1989). “Entrepreneurshipand Growth: The Strategic Use ofExternal Resources,” Journal of Busi-ness Venturing 4(2), 133–147.

Katila, R. (2002). “New Product Searchover Time: Past Ideas in Their Prime?”The Academy of Management Journal45(5), 995–1010.

Katila, R., and G. Ahuja (2002). “Some-thing Old, Something New: A Longi-tudinal Study of Search Behavior andNew Product Introduction,” TheAcademy of Management Journal45(6), 1183–1194.

Katz, R., and T. J. Allen (1982). Investi-gating the Not Invented Here (NIH)Syndrome: A Look at the Perfor-mance, Tenure, and CommunicationPatterns of 50 R & D Project Groups,”R and D Management 12(1), 7–20.

Kim, P., and H. Aldrich (2005). SocialCapital and Entrepreneurship. Delft,The Netherlands: Publishers Inc.

Kleinknecht, A., and J. O. N. Reijnen(1992). “Why Do Firms Cooperate onR&D? An Empirical Study,” ResearchPolicy 21(4), 347–360.

Kogut, B. (2000). “The Network asKnowledge: Generative Rules and theEmergence of Structure,” StrategicManagement Journal 21(3), 405–425.

Koput, K. W. (1997). “A Chaotic Model ofInnovative Search: Some Answers,Many Questions,” OrganizationScience 8(5), 528–542.

Koufteros, X., M. Vonderembse, and J.Jayaram (2005). “Internal and ExternalIntegration for Product Development:The Contingency, Effects of Uncer-tainty, Equivocality, and PlatformStrategy,” Decision Science 36(1),97–133.

Lane, P. J., B. R. Koka, and S. Pathak(2006). “The Reification of AbsorptiveCapacity: A Critical Review and Reju-venation of the Construct,” The

Academy of Management Review31(4), 833–863.

Laursen, K., and A. Salter (2006). “Openfor Innovation: The Role of Opennessin Explaining Innovation Performanceamong U.K. Manufacturing Firms,”Strategic Management Journal 27(2),131–150.

Lecocq, X., and B. Demil (2006). “Strat-egizing Industry Structure: The Caseof Open Systems in a Low-Tech Indus-try,” Strategic Management Journal27(9), 891–898.

Lee, S., G. Park, B. Yoon, and J. Park(2010). “Open Innovation inSMEs—An Intermediated NetworkModel,” Research Policy 39(2), 290–300.

Lichtenthaler, E. (2003). “Third Genera-tion Management of Technology Intel-ligence Processes,” R and DManagement 33(4), 361–375.

——— (2007). “Managing TechnologyIntelligence Processes in Situations ofRadical Technological Change,” Tech-nological Forecasting and SocialChange 74(8), 1109–1136.

Lichtenthaler, U. (2005). “External Com-mercialization of Knowledge: Reviewand Research Agenda,” InternationalJournal of Management Reviews 7(4),231–255.

——— (2008a). “Open Innovation inPractice: An Analysis of StrategicApproaches to Technology Transac-tions,” IEEE Transaction 55(1), 148–157.

——— (2008b). “Opening Up StrategicTechnology Planning: Extended Road-maps and Functional Markets,” Man-agement Decision 46(1), 77–91.

——— (2010). “Open Innovation: Poten-tial Risks and Managerial Countermea-sures,” paper presented at the R&DManagement Conference, Manchester,Great Britain, June.

——— (2011). “Open Innovation: PastResearch, Current Debates, andFuture Directions,” Academy of Man-agement Perspectives 25(1), 75–93.


Lichtenthaler, U., and H. Ernst (2007).“Developing Reputation to Overcomethe Imperfections in the Markets forKnowledge,” Research Policy 36(1),37–55.

Lichtenthaler, U., and E. Lichtenthaler(2010). “A Capability-Based Frame-work for Open Innovation: Comple-menting Absorptive Capacity,”Journal of Management Studies 46(3),1315–1337.

Lichtenthaler, U., E. Lichtenthaler, and J.Frishammar (2009). “TechnologyCommercialization Intelligence: Orga-nizational Antecedents and Perfor-mance Consequences,” TechnologicalForecasting and Social Change 76(3),301–315.

Liebeskind, J. P., A. L. Oliver, L. Zucker,and M. Brewer (1996). “Social Net-works, Learning, and Flexibility:Sourcing Scientific Knowledge in NewBiotechnology Firms,” OrganizationScience 7(4), 428–443.

Madrid-Guijarro, A., D. Garcia, and H.Van Auken (2009). “Barriers to Inno-vation among Spanish ManufacturingSMEs,” Journal of Small BusinessManagement 47(4), 465–488.

Miller, D. H., and P. H. Friesen (1982).“Innovation in Conservative andEntrepreneurial Firms: Two Modelsfor Strategic Momentum,” StrategicManagement Journal 3(1), 1–25.

Miotti, L., and F. Sachwald (2003). “Co-Operative R&D: Why and withWhom?: An Integrated Framework ofAnalysis,” Research Policy 32(8),1481–1499.

Mohnen, P., and C. Hoareau (2003).“What Type of Enterprise Forges CloseLinks with Universities and Govern-ment Labs? Evidence from CIS 2,”Managerial and Decision Economics24(2–3), 133–145.

Oliver, A. L. (2001). “Strategic Alliancesand the Learning Life-Cycle of Bio-technology Firms,” OrganizationStudies 22(3), 467–489.

Pavitt, K. (1998). “Technologies, Pro-ducts and Organization in the Inno-vating Firm: What Adam Smith TellsUs and Joseph Schumpeter Doesn’t,”Industrial and Corporate Change7(3), 433–452.

Pittaway, L., M. Robertson, K. Munir, D.Denyer, and A. Neely (2004). “Net-working and Innovation: A SystematicReview of the Evidence,” Interna-tional Journal of ManagementReviews 5–6(3–4), 137–168.

Podsakoff, P. M., S. B. MacKenzie, J. Y.Lee, and N. P. Podsakoff (2003).“Common Method Biases in Beha-vioral Research: A Critical Review ofthe Literature and RecommendedRemedies,” Journal of Applied Psy-chology 88(5), 879–903.

Podsakoff, P. M., and D. W. Organ(1986). “Self-Reports in Organiza-tional Research: Problems and Pros-pects,” Journal of Management 12(4),531–544.

Powell, W. W., K. W. Koput, and L.Smith-Doerr (1996). “Interorganiza-tional Collaboration and the Locus ofInnovation: Networks of Learning inBiotechnology,” AdministrativeScience Quarterly 41(1), 116–145.

Ragatz, G. L., R. B. Handfield, and K. J.Petersen (2002). “Benefits Associatedwith Supplier Integration into NewProduct Development under Condi-tions of Technology Uncertainty,”Journal of Business Research 55(5),389–400.

Ragatz, G. L., R. B. Handfield, and T. V.Scannell (1997). “Success Factors forIntegrating Suppliers into NewProduct Development,” Journal ofProduct Innovation Management14(3), 190–202.

Rothwell, R., and M. Dodgson (1991).“External Linkages and Innovation inSmall and Medium-Sized Enterprises,”R and D Management 21(2), 125–138.

Sher, P. J., and P. Y. Yang (2005). “TheEffects of Innovative Capabilities andR&D Clustering on Firm Performance:


The Evidence of Taiwan’s Semicon-ductor Industry,” Technovation 25(1),33–43.

Stam, W., and T. Elfring (2008). “Entre-preneurial Orientation and NewVenture Performance: The ModeratingRole of Intra- and Extraindustry SocialCapital,” Academy of ManagementJournal 51(1), 97–111.

Tao, J., and V. Magnotta (2006). “HowAir Products and Chemicals ‘Identifiesand Accelerates’,” Research Technol-ogy Management 49(5), 12–18.

Teece, D. J. (1989). “Inter-OrganizationalRequirements of the InnovationProcess,” Managerial and DecisionEconomics 10(Special Issue), 35–42.

Van De Vrande, V., J. P. J. De Jong, W.Vanhaverbeke, and M. De Rochemont(2009). “Open Innovation in SMEs:Trends, Motives and ManagementChallenges,” Technovation 29(6–7),423–437.

Van Wyk, R. J. (1997). “Strategic Tech-nology Scanning,” Technological Fore-casting and Social Change 55(1),21–38.

Vanhaverbeke, W., G. Duysters, and N.Noorderhaven (2002). “External Tech-nology Sourcing through Alliances orAcquisitions: An Analysis of theApplication-Specific Integrated Cir-cuits Industry,” Organization Science13(6), 714–733.

Veryzer, R. W. (1998). “DiscontinuousInnovation and the New ProductDevelopment Process,” Journal ofProduct Innovation Management15(4), 304–321.

——— (2005). Democratizing Innova-tion. Cambridge, MA: MIT Press.

Von Hippel, E., and R. Katz (2002).“Shifting Innovation to Users via Tool-kits,” Management Science 48(7),821–833.

Vossen, R. W. (1998). “Research Note-Relative Strengths and Weakness ofSmall Firms in Innovation,” Interna-tional Small Business Journal 16(3),88–94.

Westerberg, M., J. Singh, and E. Häckner(1997). “Does the CEO Matter? AnEmpirical Study of Small SwedishFirms Operating in Turbulent Environ-ments,” Scandinavian Journal ofManagement 13(3), 251–270.

Xin, J., A. Yeung, and T. Cheng (2008).“Radical Innovations in New ProductDevelopment and Their Financial Per-formance Implications: An EventStudy of US Manufacturing Firms,”Operations Management Research1(2), 119–128.

Zahra, S. A., and G. George (2002).“Absorptive Capacity: A Review,Reconceptualization, and Extension,”Academy of Management Review27(2), 185–203.


Appendix AConstruct Details and Factor Loading

Construct Items Factor Loading

1 2 3 4

Technology Scouting 1 Observe technology trends 0.893Technology Scouting 2 View external sources for ideas, knowledge

as important0.903

Technology Scouting 3 Collect deep information about our industry 0.710Technology Sourcing 1 Regularly contact R&D institutes and

universities to access new technology0.867

Technology Sourcing 2 Often buy and use new technology (IPRs)from other firms and institutions

0.823

Horizontal TechnologyCollaboration 1

Cooperate and co-develop with other firms(e.g., competitors and/or non-competitors)

0.745


Regularly network to exchange experiences/knowledge with partners

0.858


Our network partners contribute withimportant input

0.886

Vertical TechnologyCollaboration 1

Involve present customers 0.796


Involve future potential customers 0.696


Involve end-users 0.937


Documents

Inbound Open Innovation Activities in High-Tech SMEs: The Impact on Innovation Performance