The Mixed Blessings of Technological Innovativeness for theCommercial Success of New ProductsAlexander Kock, Hans Georg Gemünden, Søren Salomo, and Carsten Schultz

This study addresses the contradiction that, although technological innovativeness of new products is often seen as amajor driver of competitive advantage and commercial success, empirical research is not always able to show asignificant performance influence. In order to find an explanation, the effects of technological innovativeness aredecomposed as its influence on the market, the innovating firm, and the firm’s environment is considered. The proposedmodel is tested on a sample of new product development projects. In order to avoid systematic biases, this paper usesa longitudinal survey design with two informants and a sample that includes both incremental and highly innovativeprojects.

The results show that technological innovativeness has both positive and negative effects on the commercial successof new products. On the one hand, technological innovativeness can increase customer value, which in turn has apositive effect on success. On the other hand, incorporating new technologies into new products also implies changesin the innovating firm and potentially in its environment. These changes have a negative impact on commercial success.The positive and negative effects compensate for each other, so that the total effect of technological innovativeness oncommercial success is close to zero.

The findings imply that firms developing new products through incorporating radically new technologies often seemto underestimate the inherent complexities with respect to both internal and external changes. Developing andintroducing new products with a radically changed technology also implies anticipating the need for new competences,processes, structures, and network partners. Social and political resistance against technological changes, largeinvestments in new infrastructures, and the long duration of these changes additionally become frequent features ofsuch innovation endeavors. Hence, firms embarking on a path of exploiting radically new technologies should considerthose complexities very carefully when making their new product development decisions.

Introduction

T echnology-driven innovation activity and invest-ment in R&D is considered to be important forthe future performance of firms (Kafouros,

2008). Accordingly, new products based on technologicaladvances are frequently described as being essential to acompany’s future competitiveness and long-term viabil-ity (Chandy and Tellis, 2000; Kim and Mauborgne, 2005;Leifer et al., 2000; McDermott and O’Connor, 2002).Technological innovativeness—the degree of newness oftechnologies embodied in a new product—is assumed tobe a driver of new product success because new technolo-gies promise higher technical performance, and offeradditional functionality and increased benefits to custom-ers (Garcia and Calantone, 2002; Hill and Rothaermel,2003; Zhou, Yim, and Tse, 2005). However, such benefits

of technological advances are often matched by severalsacrifices and barriers such as high levels of risk anduncertainty associated with these endeavors (O’Connorand Ayers, 2005; Schmidt and Calantone, 1998). Manag-ers have to decide which level of technological newnessto incorporate in their new product development efforts.A better understanding of the influence of technologicalinnovativeness on innovation outcomes is therefore a pre-requisite for improved decision making in technology-based new product development.

Quite a few empirical studies in the new productdevelopment literature have analyzed the performanceimpact of technological innovativeness of new products.While some authors find that products are more success-ful with increasing novelty of their underlying technol-ogy (Gatignon and Xuereb, 1997; Talke, Salomo,Wieringa, and Lutz, 2009; Zhou et al., 2005), manyauthors report a negative or nonsignificant influence oftechnological newness on success (e.g., Danneels andKleinschmidt, 2001; Lynn and Akgün, 2001; Salomo,Weise, and Gemünden, 2007; Storey and Easingwood,

Address correspondence to: Alexander Kock, Chair for Technology andInnovation Management, Berlin Institute of Technology, 10623 Berlin,Germany. E-mail: alexander.kock@tim.tu-berlin.de.

J PROD INNOV MANAG 2011;28(S1):28–43© 2011 Product Development & Management Association

1996; Tatikonda and Rosenthal, 2000). In sum, empiricalresearch does not provide an unambiguous picture on theimpact of technological innovativeness on new productsuccess.

The present paper mainly contributes to new productdevelopment literature by examining more closely the rela-tionship between technological innovativeness and com-mercial success of new products in order to gain a deeperunderstanding of the underlying effects. Drawing on theresource-based view of the firm, the study develops andempirically tests a framework of hypotheses which offers anexplanation for the ambiguous findings of previousresearch. We differentiate the effects of technological inno-vativeness on other dimensions of product innovativeness toseparately account for its influence on the market, theorganization, and the firm environment. The model shows

that the relationship between technological innovativenessand commercial success is mediated by market and byorganizational and environmental innovativeness. Sincedifferent dimensions of innovativeness account for differentperformance effects that compensate for each other, themodel offers an explanation as to why previous studies havefailed to find significant relationships. From a managementperspective, the findings offer a basis from which toimprove technology-based new product development deci-sions.Acknowledging both performance-enhancing effectsand complexity-related challenges from strong technologynewness could help firms to design adequate levels ofnewness for technology-based new products.

On the methodological side this paper heeds the callfor more longitudinal and multi-informant researchdesigns in new product development research (Page andSchirr, 2008). Nearly all of the studies on innovativenessand success are cross-sectional and use single informants(e.g., Calantone, Chan, and Cui, 2006; Danneels andKleinschmidt, 2001; Gatignon and Xuereb, 1997; Zhouet al., 2005), which might seriously bias results (Marchand Sutton, 1997; Podsakoff, MacKenzie, Lee, and Pod-sakoff, 2003). Danneels and Kleinschmidt (2001) notethat only a longitudinal study could avoid such distortionswhen analyzing the effects of innovativeness on projectperformance. Consequently, this study avoids hindsightbias by measuring in two points in time and commonmethod bias by using two informants from different func-tional backgrounds.

The remainder of this paper is organized as follows:The next section provides the theoretical background forthe proposed research framework and reviews previousempirical work. Then hypotheses for the differentiatedimpact of technological innovativeness on the commer-cial success of new products are derived. The model isempirically tested on a sample of 62 new product devel-opment projects using partial least squares (PLS) struc-tural equation modeling. Finally, implications for futureresearch and management practice are discussed.

Conceptual Background

Product innovations are the result of a creative processinvolving different actors from one or more organiza-tions, which leads to a qualitatively new means-end com-bination that is introduced to the market. The extent ofchange in the means as compared to the status quo can bereferred to as technological innovativeness. Earlier con-ceptualizations of technological innovativeness catego-rize products dichotomously as being either radical orincremental (e.g., Ettlie, Bridges, and O’Keefe, 1984).

BIOGRAPHICAL SKETCHES

Dr. Alexander Kock is a postdoctoral researcher at the Berlin Institute ofTechnology. He received his doctorate and a diploma of business admin-istration and engineering from Berlin Institute of Technology, and aM.Sc. in technology management from Stevens Institute of Technology.His main research interests are the management of highly innovativenew product development projects and the management of project port-folios.

Dr. Hans Georg Gemünden is professor of technology and innovationmanagement at Berlin Institute of Technology. He holds a diploma anda doctorate in business administration from Saarbrücken University anda habilitation degree from the University of Kiel. He has publishedseveral books and numerous articles in the fields of innovation andtechnology management, marketing, business policy and strategy,project management, entrepreneurship, human information behaviorand decision making, and accounting. He has received several Awards ofExcellence for his research, which has been published in journals suchas Journal of Engineering and Technology Management, R&D Manage-ment, IEEE Transactions on Engineering Management, InternationalJournal of Research in Marketing, Organization Science, ResearchPolicy, and Journal of Product Innovation Management.

Dr. Søren Salomo is professor of innovation management at the DanishTechnical University and director of DTU Executive School of Businessin Copenhagen. He holds a diploma and a doctorate in business admin-istration from Kiel University. His research interests entail corporateinnovation management with a special focus on process and organiza-tional system mechanisms for supporting highly innovative ventures.His work has been published in journals such as Journal of Engineeringand Technology Management, Entrepreneurship Theory and Practice,and Journal of Product Innovation Management.

Dr. Carsten Schultz is assistant professor of innovation management atBerlin Institute of Technology. He holds a diploma in business engineer-ing and a doctorate in business administration from Berlin Institute ofTechnology. His research interests cover organizational issues of inno-vation management on individual, corporate, and network levels, with aspecial focus on service innovations and radical innovations. He isleading a work group that deals with management problems within thehealth care sector.

29 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

However, more recent studies regard technological inno-vativeness as a continuous construct that relates to thedegree of newness of technologies embodied in newproducts with incremental and radical as the extremes ofthe scale (Gatignon, Tushman, Smith, and Anderson,2002; Green, Gavin, and Aiman-Smith, 1995). Very newtechnologies are often not well understood by anycompany or scientific community and thus implicateunpredictability and uncertainty (Green et al., 1995). Inextreme cases they are capable of causing a paradigmshift concerning technology or science (Garcia andCalantone, 2002) and can fundamentally alter the tech-nological trajectory in relevant fields, which leads tosupersession of existing technologies (Dosi, 1982). Tech-nological innovativeness of a new product is high if it isbased on completely new technological principles thatrequire a new knowledge base, if the architecture of atechnological system is changed fundamentally (Hender-son and Clark, 1990), or if completely new componentsand materials are used (Gemünden, Salomo, and Krieger,2005).

In order to explain the impact of technological inno-vativeness on commercial success of new products, weresort to the resource-based view (RBV) of the firm.According to RBV firms can be conceptualized asbundles of resources and competences, which are hetero-geneously distributed across firms (Barney, 1991; Wer-nerfelt, 1984). Because the resource configuration isidiosyncratic and difficult to modify, RBV states that afirm’s competitive advantage stems from strategies thatexploit these resources. The static approach of RBV hasbeen extended by the concept of dynamic capabilities,which states that in situations of rapid and unpredictablechange, competitive advantage arises from capabilities bywhich managers adapt, integrate, and reconfigureresources to meet the requirements of the changing envi-ronment (Teece, Pisano, and Shuen, 1997). Productdevelopment can be understood as a dynamic capabilitybecause it encompasses routines that reconfigure andrecombine resources to pursue market opportunities(Eisenhardt and Martin, 2000; Verona, 1999).

By developing new products, firms change theirresource base and generate new knowledge. High tech-nological innovativeness corresponds with high newnessof knowledge embodied in products. New knowledgeallows the creation of customer value, differentiationpotential, and consequently the appropriation of tempo-rary monopoly rents. Because in case of high technologi-cal newness the required underlying capabilities are oftentacit, complex, and unobservable, the new knowledge isdifficult to imitate, which makes the competitive advan-

tage sustainable (McEvily and Chakravarthy, 2002).Development of unique and technologically novel prod-ucts should therefore lead to competitive advantage(Gatignon and Xuereb, 1997).

However, acquisition and building of new capabilitiesare connected with additional efforts. Firms that developproducts with only incremental changes in technologycan profit from experience by exploiting existingresources and capabilities (Danneels and Kleinschmidt,2001). Additionally, in order to successfully commercial-ize a new technology, firms must own or gain access tocomplementary resources (Teece, 1986, 2006). If thechange in technology is only moderate in comparison toprevious products, complementary resources may alreadybe in place or need only minor adjustments. In case ofhigh technological innovativeness, however, existingcapabilities may be cannibalized and complementaryresources may lose their value because they cannot beused in the new context (Hill and Rothaermel, 2003). Themore the required resource configuration for a newproduct differs from the existing one in the firm, the moreorganizational costs are incurred, which can reduce thelikelihood of commercial success (Danneels and Klein-schmidt, 2001). This notion of resource fit can also beapplied to resources outside the boundaries of the firm(Teece, 2006). Since products are often embedded in aninfrastructure or closely linked to complementary prod-ucts, profound changes in the underlying technology willalso affect the resource structure of the firm environment.Products that fit to the existing resource configurationwill be more likely to succeed.

Therefore, from a resource perspective technologicalinnovativeness has both positive and negative effects.This notion is mirrored in the ambiguous results ofempirical studies on the relationship between technologi-cal innovativeness and success. Recent meta-analysesshow that the average correlation between technology-related innovativeness and new product success is only0.07 (Szymanski, Kroff, and Troy, 2007) and 0.05 (Kock,2007) respectively. Yet some studies support the notionthat products with a more innovative technology are moresuccessful. Zhou et al. (2005) find that highly innovativeproducts that incorporate radically new technologicalknowledge offer higher product quality and customervalue. Accordingly, Gatignon and Xuereb (1997) showthat technologically newer products have a higher newproduct performance. However, many other studiescannot find a significant impact of technological noveltyon success. For example Tatikonda and Rosenthal (2000),as well as Larson and Gobeli (1989), do not find aninfluence of technological novelty on project outcomes.

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 302011;28(S1):28–43

Storey and Easingwood (1996) report that innovativenessand the use of new technology have no relationship withthe profitability of new services. Other studies cannot finda significant impact of newness of technologies onsuccess either (Danneels and Kleinschmidt, 2001;Gemünden et al., 2005; Lynn and Akgün, 2001; Salomoet al., 2007).

However, these findings must also be assessed withcaution, since they are prone to some methodologicallimitations. In a recent review, Page and Schirr (2008)report that most research in new product developmentuses single informants and cross-sectional surveydesigns, which also applies to the majority of studies ontechnological innovativeness and success. Relying ononly one informant can lead to systematic bias due tocommon method variance (Podsakoff et al., 2003).Cross-sectional data, meaning that all variables areassessed at the same point in time, does not allow forconfident causal inference (March and Sutton, 1997).This is especially troublesome when assessing a subjec-tive and latent construct like technological innovative-ness, which will inevitably lead to ex post rationalizationand hindsight bias (Fischhoff and Beyth, 1975; Golden,1992). Another methodological limitation might be tradi-tional sample selection procedures. Really innovativeprojects are quite rare in general and of strategic impor-tance for the innovating firm. Managers might feel reluc-tant to share information on these projects and prefer toreport on more incremental projects. As a consequence, apotential bias towards samples of moderate and incre-mental innovations, which leads to censored samples,cannot be ruled out. When the central variable is thedegree of innovativeness, this constitutes a problem ofpopulation validity (Cook and Campbell, 1979). As aconsequence, further empirical investigation demands alongitudinal, multi-informant approach and carefulsample selection.

Possible methodological limitations set aside, theoverall empirical findings do not seem to show a signifi-cant positive performance impact of technological inno-vativeness. In light of these nonsignificant findings, itcould be suggested that a high degree of technologicalinnovativeness is not worth the trouble and firms shouldconcentrate on incremental technological changes ratherthan on technological breakthroughs (Banbury andMitchell, 1995). This assertion is premature because it israther necessary to understand the mechanisms by whichtechnological innovativeness influences performance.Based on the previous discussion it is suggested thattechnological innovativeness has predominantly an indi-rect effect on product success that should be decomposed

in order to understand its total impact. Pursuing highdegrees of technological innovativeness has positive andnegative consequences for the firm. In order to profit fromtechnological advantages, innovation management has toaccount for the barriers within the organization and theenvironment. In the next section a conceptual frameworkis built that substantiates this notion.

Research Framework and Hypotheses

In order to model the different effects of technologicalinnovativeness on the market, the organization, and thefirm environment, the concept of product innovativeness isused that has been associated with RBV in several previ-ous studies (Danneels and Kleinschmidt, 2001; Garcia andCalantone, 2002; Molina-Castillo and Munuera-Aleman,2008). Recent research conceptualizes product innova-tiveness as a multidimensional and continuous phenom-enon relating not only to technological, but also tomarket, organizational, and environmental innovativeness(Avlonitis, Papastathopoulou, and Gounaris, 2001; Dan-neels and Kleinschmidt, 2001; Garcia and Calantone,2002; Salomo et al., 2007).

Market innovativeness of new products is high if theinnovation encompasses a significant increase in cus-tomer value in comparison to prior products (Chandy andTellis, 1998; Jordan and Segelod, 2006). This can be thefirst fulfillment of previously unsatisfied needs and/or thecreation of entirely new benefits, which will addressmany new customers. In an extreme case the new productrepresents the first of its kind and establishes a newproduct category or creates a totally new market. Orga-nizational innovativeness relates to the internal changesof the innovating unit that are induced by the innovation(Avlonitis et al., 2001). Organizational innovativenesstherefore covers the degree to which existing resourcesare appropriate for the development of an innovation(Danneels and Kleinschmidt, 2001) and relates tochanges in strategy, structure, processes, competences, orincentive systems (Avlonitis et al., 2001; Jordan andSegelod, 2006). Environmental innovativeness relates tothe potential impact an innovation has on the externalenvironment of a firm beyond the customer (Gemünden,Salomo, and Hölzle, 2007; Salomo et al., 2007). Similarto organizational innovativeness, this dimension is con-cerned with the degree to which existing resourcesoutside the firm are appropriate for the development of aninnovation. New products that are highly innovative onthis dimension may call for an entirely new infrastructure(such as a network of gasoline stations for hydrogen-fueled cars), alterations in regulations and industry

31 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

norms, or even adjustments in social values and norms(e.g., in the case of genetically engineered food).

In order to understand its overall impact, technologicalinnovativeness is suggested to impact the other threedimensions of product innovativeness, which in turnaffect innovation success. The research framework, asdepicted in Figure 1, therefore suggests an indirect effectof technological innovativeness on the commercialsuccess of a new product. Technological developmentsimpact product architecture and components. Hence, forthose products, which rely on technology to generatefunctionality relevant to customers, technological inno-vation will impact market innovativeness. With its directlink to commercial success (Gatignon and Xuereb, 1997;Veldhuizen, Hultink, and Griffin, 2006), market innova-tiveness is argued to mediate the performance effect oftechnological innovativeness. At the same time techno-logical innovativeness is suggested to increase organiza-tional innovativeness and environmental innovativeness,which both potentially impact new product success nega-tively.

Interplay of Innovativeness Dimensions

Innovations are often driven by application of new tech-nologies (Bower and Christensen, 1995; Sood and Tellis,2005). Innovative technologies can turn the competitivebalance in a market upside down. Consequently, hightechnological innovativeness offers enormous opportuni-ties for a firm’s long-term success (Chandy and Tellis,2000). Examples of significant product innovations

which implemented completely new technologies includecolor television, cellular telephones, and the global posi-tioning system (GPS). These technologies may offer dis-tinct price-performance enhancements over presenttechnologies, as their technical advance is so substantialthat no upgrade in scale, efficiency, or design can renderolder technologies competitive with the new one(Tushman and Anderson, 1986). Accordingly, use ofhighly new technologies may foster differentiation,provide the customers with considerably greater benefitsfor their money, and lead to competitive advantages.Sometimes, technological change can induce a new valueproposition that has not existed before. Even if old cus-tomers might not appreciate this new functionality, thiscan open up opportunities for fringe and new customers(Christensen, 1997). Therefore, higher technologicalinnovativeness will induce higher market innovativeness:

H1: Technological innovativeness has a positive impacton market innovativeness.

In general, new product development can be under-stood as a vehicle to leverage existing capabilities or tobuild new capabilities regarding technologies and cus-tomers (Danneels, 2002). The pursuit of highly new tech-nologies will inevitably confront a company withunexplored fields of research, in which existing knowl-edge has become obsolete. Therefore the firm is com-pelled to expand and reconfigure its knowledge base andto acquire new capabilities, for example by hiring of newqualified employees. Apart from that, technologically

TechnologicalInnovativeness

H4 (+)H1 (+)

H6 (−)

H5 (−)H2 (+)

H3 (+)Environmental Innovativeness

Organizational Innovativeness

Market Innovativeness Commercial

Success

H7 (+)

Figure 1. Research Framework

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 322011;28(S1):28–43

innovative development projects may need to be orga-nized as clearly identified entities to escape the need ofconforming to the mainstream business (Hill and Roth-aermel, 2003; O’Connor, 2008).

With increasing technological newness, organizationalchanges are also driven by the need to cooperate withexternal partners in order to increase learning and to getaccess to new resources (Ireland, Hitt, and Vaidyanath,2002; Kale, Singh, and Perlmutter, 2000). In particular,the network of relationships will consist not only of morebut also of different suppliers and technology partnersthan in the case of incremental technological change (Bir-kinshaw, Bessant, and Delbridge, 2007). As a conse-quence, an organization has to alter its processes andcompetences to manage these networks (Ritter andGemünden, 2004).

Technological advances might also have an impact onfirm strategy, which is consistent with the notion thatstrategies can emerge from the grassroots of an organiza-tion in absence of prior strategic planning (Mintzberg andMcHugh, 1985). Highly innovative development projectsmay lead to new technological platforms, which willaffect the technology strategy. In the context of largersystems, a profound change in components has to bereflected in the interfaces between components or theywill alter the system architecture as a whole (Murmannand Frenken, 2006). With respect to the market strategy,the limited fit of the developed product with the existingproduct portfolio will require different approaches formarket launch. With increasing technological innovative-ness it is also likely that the product will require a differ-ent business model than existing products (Christensen,1997).

It is therefore suggested that the higher the technologi-cal innovativeness of an innovation project, the morelikely it will result in several types of changes within theorganization regarding structure, processes, competencesor strategy:

H2: Technological innovativeness has a positive impacton organizational innovativeness.

A similar argument can be made for alterations in theexternal environment of the firm. Products based on com-pletely new technological principles are more likely to beincompatible with existing infrastructure. Besides physi-cal network infrastructures, products often depend oninteroperability with other products in order to functionas a bigger modularized system. In this case, a change inthe technological basis will cause changing interfaceswith complementary products. Hence, the technologies

and products of these system partners have to be adapted(de Vries, 2006).

Even legislation may have to be changed in order tointroduce the innovation. Further, the application ofhighly new technologies in new contexts may also oftenpart with socially approved practices and values. Such acombination of necessary changes in infrastructure, leg-islation, and social norms, as well as interfaces withexternal stakeholders driven by technological innovative-ness, can for example be observed in the case of telemedi-cine. The introduction of advanced information andcommunication technology within health care demands acommunication infrastructure, cooperation with externalpartners like physicians and complementary system part-ners, changing regulation in order to allow for telemetricdiagnosis and treatment, and even a break with traditionalnorms in the context of physician-patient interaction(Field, 1996). Therefore technological innovativenesscomes along with a higher probability of environmentalchanges:

H3: Technological innovativeness has a positive impacton environmental innovativeness.

Performance Impact of Innovativeness Dimensions

A new product has a high degree of market innovative-ness if it constitutes a significant increase in customervalue (Chandy and Tellis, 2000). A highly innovativeproduct is connected with higher relative advantage(Veryzer, 1998), which has been found to be the strongestinfluencing factor of product adoption (Rogers, 2003).Also, customers might perceive introduction of novelattributes as a signal for additional value (Mukherjee andHoyer, 2001). In an extreme case, it is possible that anentirely new benefit dimension is introduced (Zhou et al.,2005). A firm designing and commercializing such aunique product has the position of a market pioneer andmight be able to enjoy temporary monopoly rents.

On the other hand, high market innovativeness canalso cause adoption barriers for customers (Rogers,2003). In addition, firms have to face significant costs tobuild new markets or introduce new products into exist-ing markets (Song and Montoya-Weiss, 1998). For thesereasons, the positive effect of market innovativeness oncompetitive advantage might be diminished in cases ofextremely high market innovativeness. However, manyempirical studies have shown that the overall effect ofmarket innovativeness on new product success is positive(Avlonitis and Salavou, 2007; Gatignon and Xuereb,1997; Veldhuizen et al., 2006). In addition, some adop-

33 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

tion barriers, e.g., whether the innovation fits to the valuesystem, are already considered in the construct environ-mental innovativeness. The proposed model thereforecontrols for these influences. For these reasons it isargued that the value potential gained through marketinnovativeness is stronger than possible negative effectsdue to adoption barriers:

H4: Market innovativeness has a positive impact on thecommercial success of new products.

The extent to which a new product developmentproject requires new capabilities and a change in theresource base of the company is reflected in the organi-zational innovativeness. Moving away from its estab-lished knowledge and experience base entails an arduouspath for a firm, because learning and successful productdevelopment becomes increasingly difficult (Kogut andZander, 1992; McGrath, Tsai, Venkataraman, and Mac-Millan, 1996). Therefore the applicability of existingresources to the respective development project is ofimportance. Cooper and Kleinschmidt (1995) argue that,ideally, a good fit must exist between the resources andcapabilities at hand and the requirements of the project.This will place the firm in a position of strength andshould improve the development process and project out-comes (Keller, 2004; Verona, 1999). For instance, syner-gies with existing marketing skills and resources are saidto improve the development team’s aptitude to acquireand to interpret relevant market and competitive informa-tion, which leads to better proficiency in developmentactivities (Song and Parry, 1997). Following this logic,product development projects with a high degree of orga-nizational innovativeness have on average a worse fit andcan profit less from synergies (Danneels and Klein-schmidt, 2001).

In addition, organizational changes are associated withbarriers. Individuals resist changes because of theirlimited willingness and ability to accumulate new knowl-edge, which is needed to deal with new processes andstructures (Amabile et al., 1996; Baldwin and Lin, 2002).Furthermore, organizations have difficulties with changesas they are locked into historical paths that constituteself-reinforced processes (Schreyögg and Kliesch-Eberl,2007). Deviating from existing core capabilities may thusinduce severe organizational resistance against successfulinnovative activity (Leonard-Barton, 1992). Overcomingthese barriers is costly and time-consuming.

Despite these negative effects, organizational changescan ultimately be beneficial for the firm in the long run.Organizational renewal and the creation of new capabili-

ties will enable future innovation activities and mightlead to future profits (Danneels, 2002). However, thescope of this research only encompasses the commercialsuccess of the single development project that initiateschanges in structure, processes, or strategy. Even if thesechanges are induced to facilitate development, launch,and marketing of this new product, the likelihood ofdirect commercial success is ceteris paribus higher if theproduct already fits to the existing resources and compe-tences (Danneels and Kleinschmidt, 2001; Zirger, 1997):

H5: Organizational innovativeness has a negativeimpact on the commercial success of new products.

The environmental dimension of product innovative-ness captures the most exogenous aspects of innovative-ness from the firm’s perspective. If environmentalinnovativeness of a new product is high, the firm isextremely dependent on actions of other actors, on whomthe company can exert influence only in a limited way.This leads to comparatively high uncertainty. In addition,the establishment of a new infrastructure or the introduc-tion of new legislation necessary for a new product willaffect many other stakeholders besides the firm (Hall andMartin, 2005). With varying stakeholder objectives, alter-ations in external resources can to a lesser extent beindividually tailored to the needs of the innovating firm.This may limit the commercial success of innovativeproducts dependent on environmental change. As anadditional complication, environmental change processesare usually lengthy and complex due to the divergence ofinterest and the multitude of involved stakeholders. Thebarriers rooted in required changes of values, infrastruc-ture, and environment in the broader societal and politicalissues will imply additional efforts for the firm. And ifthese barriers are not recognized early enough, they willnegatively affect effectiveness and efficiency of the devel-opment project (Talke and Salomo, 2009). Although envi-ronmental changes might be beneficial for the firm, suchas a change in legislation that favors the innovation, thechanges are either outside the control of the innovatingfirm or very difficult to achieve. Ceteris paribus it isexpected that innovations requiring these changes arecommercially less successful than innovations that do notface environmental barriers:

H6: Environmental innovativeness has a negative impacton the commercial success of new products.

Technological innovativeness may still have directeffects on commercial success that are not accounted for

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 342011;28(S1):28–43

when controlling for the effects of market, organizational,and environmental innovativeness. The development ofhighly innovative technologies is very knowledge-intensive and resource-demanding. In particular, tacitknowledge is needed in order to create new technologies(Mascitelli, 2000). This knowledge is built up in the longrun and cannot be easily transferred to other firms. Addi-tionally, new technologies can often be protected bypatents. Hence, more innovative technology will lead tohigher imitation barriers, which results in a protection ofcompetitive advantage and a decrease of competitiveintensity (Lieberman and Montgomery, 1988). Productsbased on highly innovative technology can therefore bemarketed for higher prices and can accumulate largermarket shares. Apart from that, a technology-orientedfirm may gain a reputation as an innovation leader withpositive side effects on sales. Both arguments lead to thelast hypothesis:

H7: Technological innovativeness has a direct positiveimpact on the commercial success of new products.

Empirical Analysis

Sample

In order to test the hypotheses, a cross-industry data set ofnew product development projects is used. Each project issurveyed in two points in time (T1 and T2) that had a timelag of approximately 18 months. In the first survey,special care was taken to also include highly innovativedevelopment projects in order to have a large variance ofproduct innovativeness in the sample. As outlined above,traditional survey approaches might lead to biasedsamples of more incremental or moderately innovativeprojects neglecting highly innovative developmentprojects. Therefore a stepwise approach was chosen.First, over 20 experts from different technologicaldomains were contacted to define different specific tech-nological areas of strong research and advanced develop-ment activity with potential for radical innovations. Thiswas done in cooperation with technology experts fromthe Association of German Engineers (VDI), which enter-tains “professional communities” in many different tech-nological domains, each chaired by a technologyspecialist. The study concentrated on the mechanicalengineering, automotive, electronics, software, and bio-technology industries. Within these industries, a total of45 promising technological areas was identified. Thesame experts were then asked to identify companies thatwere very active in pursuing technological development.

These firms were approached and asked to participate inthe study with their most innovative new product devel-opment project in their respective technological areas thatwas already in the development phase but not yet intro-duced into the market. Additionally, following a more“traditional” approach, large mature industrial corpora-tions drawn from different industry directories (e.g., Hop-penstedt) were contacted without specifically asking forhighly innovative NPD projects. The first approachyielded 104 participating firms and the second an addi-tional 40, which results in a total sample of 144 firms inT1.

In each of the participating firms the project leader ofthe designated innovation project was the key informant.The survey method was a questionnaire administered in astructured interview. By combining personal interviewswith standardized questions, it was possible to directlyaddress confidentiality concerns of the informants and tocreate a common understanding of the central constructsof the study.

In T2 a second survey was undertaken, in which all ofthe companies were contacted again to report once moreon the same innovation project as in T1. Of the 144 firms,75 agreed to participate again. Additionally, companiesthat entered an innovation competition organized by theGerman chambers of commerce were contacted by phoneand asked to participate in the survey. The present study,however, uses this additional data only for purposes ofmeasurement validation and not for further analysis. Onlyprojects with complete data from both surveys in T1 andT2 are used to test the hypotheses. In T2 questionnaireswere sent by mail to the project manager and a projectteam member responsible for marketing. Thirteenprojects had to be removed from analysis because theyhad missing values, resulting in a usable data set of 62new product development projects (46 from the first sam-pling approach and 16 from the second) in T1. At T2 allof the products had been introduced to the market. Thefinal sample includes firms from the automotive (14%),mechanical engineering (42%), electronics (21%), soft-ware (18%), and biotechnology (5%) industries. Of thesefirms, 29% have fewer than 200 employees, 38% havebetween 200 and 2000 employees, and 33% more than2000 employees.

Since not all firms from the first survey participated inT2, there might be reason to believe that poorly perform-ing projects were abandoned due to competitive selec-tion, eliminating the less successful projects from thesample. This bias due to “undersampling of failure” isparticularly problematic when risky practices are investi-gated (Denrell, 2003). Highly innovative development

35 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

projects are accompanied by high uncertainty and risk(Leifer et al., 2000), which might increase the chances offailure. On the other hand, there is also evidence showingthat managers feel more committed to innovative prod-ucts and are reluctant to terminate poorly performingdevelopment projects with a high degree of innovative-ness (Schmidt and Calantone, 1998). To account for non-response bias between the two surveys, firms from thecross-survey sample were compared with those firms par-ticipating in only one of the two surveys. Answers to allitems used in this study did not significantly differ in theirmeans (p < 0.05). Therefore it can be assumed that under-sampling of failure is not a concern in this study.

Method and Measures

PLS structural equation modeling (Chin, 1998; Fornelland Cha, 1994; Wold, 1982) is used to test the hypothesessuggested by the framework. Results for the measurementand path model are calculated with SmartPLS (Ringle,Wende, and Will, 2005). The significance of path coeffi-cients and loadings is determined using a Bootstrap pro-cedure with 500 repetitions and sample sizes equal to theoriginal sample (Efron and Tibshirani, 1993). The reasonfor choosing PLS over covariance-based methods is itsless stringent demand regarding sample size. In a modelwith exclusively reflective constructs, the minimumsample size is ten times the number of the incoming pathson a construct (Chin, Marcolin, and Newsted, 2003). Thestudy’s sample fulfills this requirement.

Measures for each construct were developed usingmultiple items and Likert-type scales from 1 (stronglydisagree) to 7 (strongly agree) (see the Appendix for themeasurement model and Table 1 for descriptive statistics).An extensive literature review on product innovativenessand success helped to identify relevant concepts and pre-viously operationalized scale items. Following prior con-ceptual and empirical research, measures for thedimensions of product innovativeness were applied thatcover aspects of product technology newness, market

newness, as well as organizational and environmentalchanges (Danneels and Kleinschmidt, 2001; Garcia andCalantone, 2002; Gatignon et al., 2002; Green et al., 1995;Salomo et al., 2007). This study takes a differentiatedapproach to measuring innovativeness by using two infor-mants and two points in time. The project leader was askedto assess the technological innovativeness at time T1,when the project was still ongoing. At T2 the marketingmanager of the project was asked to evaluate the externallyoriented innovativeness constructs market innovativenessand environmental innovativeness. In order to excludecommon method variance for all hypothesized relation-ships, the marketing manager was chosen as informant fororganizational innovativeness. Apart from this methodicalreason, marketing managers might be better suited toassess the impact of the project in the wider organizationalcontext, since they are not necessarily committed full timeto the project and also occupy a line position. The projectleader, being responsible for and most knowledgeableabout project outcomes, was asked to evaluate the com-mercial success at T2 using measures previouslyemployed by Griffin and Page (1993).

It can be argued that one and a half years might not beenough time to fully evaluate the commercial success ofa new product. Especially in the case of technologicalbreakthroughs, it may take several cycles of probing andlearning from failures (Lynn, Morone, and Paulson,1996) before a new product is successful. However, themajority of probing and testing usually takes place duringthe development phase. In addition, studies on the diffu-sion of new products show that the overall success of newproducts can be predicted to a certain degree using thesales performance of the first months after market intro-duction (Garber, Goldenberg, Libai, and Muller, 2004;Sood, James, and Tellis, 2009). Further, since informantswere asked to assess success compared to objectives, ameaningful evaluation is feasible despite the limited timeframe. Therefore, the assessment of commercial successsome time after market introduction can be considered acrucial measure of new product performance.

Table 1. Descriptive Statistics and Correlations

Mean Std. Dev. Min Max 1 2 3 4 5

1. Commercial Success (T2) 4.32 1.29 1.60 6.60 0.762. Technological Innovativeness (T1) 5.26 1.26 1.67 7.00 0.11 0.753. Market Innovativeness (T2) 4.37 1.08 1.33 7.00 0.12 0.45 0.744. Organizational Innovativeness (T2) 3.23 1.49 1.00 6.25 -0.18 0.23 0.42 0.805. Environmental Innovativeness (T2) 2.00 1.29 1.00 5.67 -0.23 0.41 0.38 0.37 0.85

All items were measured on a 7-point scale from 1 to 7; means, standard deviations and min/max are calculated from the simple average of construct items.Numbers on the diagonal (shown in italics) are the square root of the average variance extracted.

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 362011;28(S1):28–43

Since all constructs are conceptualized as being of areflective nature, the measurement model is validated bychecking for indicator and construct reliability, as well asfor discriminant validity. Indicator reliability is deter-mined by the factor loadings, which should ideallyexceed 0.7 (Chin, 1998) but can be acceptable when theyare larger than 0.4 (Hulland, 1999). Indicator loadings arehigher than 0.6 for all constructs and higher than 0.7 formost of the constructs. Construct reliability is confirmedby the composite reliability, which should exceed 0.7 forall constructs (Tenenhaus, Vinzi, Chatelin, and Lauro,2005). In the case of PLS this measure is better suitedthan Cronbach’s alpha, because it does not assume equalweights of indicators (Chin, 1998). Composite reliabilityis higher than 0.78 for all constructs. Finally, for eachconstruct only the first eigenvalue is greater than one in aprincipal component analysis, providing support for theunidimensionality of the constructs (Ahire and Devaraj,2001).

Discriminant validity is examined by comparing thesquare root of the average variance extracted for eachconstruct with the correlation to other constructs (Fornelland Larcker, 1981). Since the average variance extractedexceeds 0.5 for all constructs and the highest correlationbetween constructs is 0.45, the criterion is fulfilled.

Due to the small sample size a confirmatory factoranalysis (CFA) to further support the measurement modelis not possible. However, for the four constructs mea-sured in T2 it is possible to use the complete second

survey (including the additional projects that did not par-ticipate in T1) of 108 projects. The loadings derived fromthe CFA largely correspond to the loadings derived fromthe PLS algorithm and the model shows an acceptable fit(Chi-Square = 133.57 (df = 84); CFI = 0.93; SRMR =0.077; RMSEA = 0.074). Altogether the measurementmodel is deemed satisfactory.

Technological innovativeness has a mean value of5.26, which indicates that the sample has a tendencytowards technologically more innovative products, but astandard deviation of 1.26, which indicates that thesample still covers a range of different degrees of inno-vativeness. There might be reason to believe that the levelof technological innovativeness is influenced by firm sizeor industry. An analysis of variance shows, however, thatmean values of technological innovativeness are not sig-nificantly different across industries (F(4;57) = 0.97,p < 0.43) and the correlation between technological inno-vativeness and number of employees is not significant(r = 0.17, p < 0.17).

Results

The results of the path analysis are illustrated in Figure 2and Table 2, indicating the path coefficients with two-sided significance tests from the bootstrap. The model isable to explain 17% of the variance of the dependentvariable commercial success. Considering the empiricalapproach with two different informants and a longitudi-

0.30**0.46***

–0.25**

–0.31*0.23**

0.41***

Technological nnovativeness

Environmental Innovativeness

I

Organizational Innovativeness

Market Innovativeness Commercial

Success

0.17 (n.s.)

T1

PL

T2

MKT

T2

MKT

T2

MKT

T2

PLR2 = 0.17

R2 = .17

R2 = .21

R2 = .06

T1, T2 = Time 1, 2PL = Project Leader;MKT = Marketing Manager

Figure 2. Results

37 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

nal measurement of innovativeness, avoiding the bias ofcommon method variance, hindsight, and halo effects,these results are very satisfying.

As hypothesized, higher technological innovativenessleads to higher market innovativeness (b = 0.46;t = 4.31), supporting H1, which stated that market inno-vativeness is driven by the employment of new techno-logical principles. Technological innovativeness alsoincreases organizational innovativeness (b = 0.23;t = 2.00) and environmental innovativeness (b = 0.41;t = 4.85) lending support to H2 and H3. Market innova-tiveness has a significant positive impact on the commer-cial success of new products (b = 0.30; t = 2.25). Thissupports H4, which states that products addressing newcustomers and new customer benefits are commerciallymore successful. H5 and H6 expressed that changeswithin the firm or in the environment due to a newproduct will negatively affect its success. Organizationaland environmental innovativeness both have negativeimpacts (b = -0.31; t = 1.67 and b = -0.25; t = 2.24) oncommercial success. The direct effect of technologicalinnovativeness on commercial success is positive but notsignificant (b = .17; t = 1.26), and therefore H7 cannot besupported. The sum of all indirect effects of technologicalinnovativeness on commercial success is 0.11.

In order to investigate whether industry or firm sizemight affect results, additional OLS regressions for eachendogenous variable were calculated using dummy codesfor industry and the number of employees as controlvariables. The influence of industry and firm size was notsignificant.

Discussion

A major finding of this study is that different dimensionsof product innovativeness have distinct impacts on thecommercial success of a new product. Therefore, theresults of this study not only confirm previous researchstating that product innovativeness has multiple dimen-

sions (Avlonitis et al., 2001; Garcia and Calantone, 2002;Gatignon et al., 2002). They also stress the importance ofdistinguishing between these different facets because oftheir distinct performance impacts.

Market innovativeness exerts a positive influence oncommercial success. This supports the notion thataddressing new customer benefits is commercially attrac-tive (Gatignon and Xuereb, 1997; Veldhuizen et al.,2006). However, organizational innovativeness has anegative impact on success, and the direct influence oftechnological innovativeness on commercial success isnot significant. These findings are consistent with theresults of Danneels and Kleinschmidt (2001), who showthat technological newness does not impact performance,while the fit of the product with existing resources andcapabilities is positively related to success. The presentstudy extends their findings by analyzing these effects ina longitudinal setting and by also considering theinnovation-relevant social and political environmentdimension of innovativeness. Products that requirechanges in the resource configuration of the firm or thefirm environment have—at least in the short run—lowerchances of success. More importantly, this study showsthat the dimensions of product innovativeness are notindependent from each other, because technological inno-vativeness is an antecedent for market, organizational,and environmental innovativeness. Danneels and Klein-schmidt (2001) suggest that managers should not be dis-couraged by products that incorporate new technologiesas long as they can draw on existing competences of thefirm. The results imply however that such a strategy ofdecoupling technological innovativeness from organiza-tional change may be difficult to achieve as these inno-vativeness dimensions are related to each other.

Another major finding is that the total effect of tech-nological innovativeness on commercial success is closeto zero. The positive indirect effect through market inno-vativeness is compensated by the negative indirect effectthrough organizational and environmental innovative-

Table 2. Results of the Path Model

Effect of On Hypothesis Path coefficient (t-Value)

Technological Innovativeness Market Innovativeness H1 0.46*** (4.31)Technological Innovativeness Organizational Innovativeness H2 0.23** (2.00)Technological Innovativeness Environmental Innovativeness H3 0.41*** (4.85)Market Innovativeness Commercial Success H4 0.30** (2.25)Organizational Innovativeness Commercial Success H5 -0.31* (1.67)Environmental Innovativeness Commercial Success H6 -0.25** (2.24)Technological Innovativeness Commercial Success H7 0.17(n.s.) (1.26)

n = 62; Bootstrap with 500 repetitions; * p < 0.1; ** p < 0.05; *** p < 0.01; n.s. = not significant.

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 382011;28(S1):28–43

ness. This study therefore provides a deeper insight intothe indirect effects of technological innovativeness andoffers an explanation to why the empirical literaturecannot show a significant impact on success. In this waythe study complements the results of Calantone et al.(2006). They show that product innovativeness from acustomer’s perspective positively affects product advan-tage and negatively affects customer familiarity, whichleads to counteracting effects on profitability. This studyfinds a similar effect from the firm’s perspective. Whiletechnological innovativeness offers the ability to gaincompetitive advantage, it also leads to changes in the firmand its environment, which has negative effects for thecommercial success of the new product. It seems thatfirms underestimate the inherent complexities of theseinternal and external changes. Technological innovative-ness is apparently a two-edged sword because it has posi-tive and negative consequences. However, this resultshould not lead to the conclusion that technological inno-vativeness should be avoided or kept to a minimum. Onthe contrary, the analysis shows that technological inno-vativeness is a driver of market innovativeness and there-fore increases the potential for commercial success.Yet atthe same time the need for organizational changes andalterations in the environment increases, which raisesimplementations barriers.

Limitations and Implications for Research

The results of this study have several implications forfuture research. First, it is necessary to broaden ourunderstanding of product innovativeness. Since the dif-ferent dimensions have specific performance effects, it isimportant that future studies take these differences intoaccount. Beside the traditional approach of differentiat-ing market and technology newness (Garcia and Calan-tone, 2002), organizational and related environmentalchanges should be considered as well.

Second, while this study offers a possible explanationfor the nonsignificant impact of technological innovative-ness on commercial performance as found by previousstudies (Danneels and Kleinschmidt, 2001; Lynn andAkgün, 2001; Salomo et al., 2007; Storey and Easing-wood, 1996; Tatikonda and Rosenthal, 2000), there areother possible explanations. The NPD literature suggestsa variety of management practices that may moderate theperformance impact of technological innovativeness,e.g., the existence of product champions (Lee and Na,1994), top management support (Swink, 2000), commu-nication strategies (Lee and O’Connor, 2003), orautonomy (McGrath, 2001). Testing for all of these mod-

erating effects is beyond the scope of this research, whichis not mainly to identify best practice but to demonstratethe underlying effects of technological innovativeness.However, the general effect of the different dimensions ofproduct innovativeness analyzed in this study can behelpful to focus attention on specific implementation bar-riers in order to identify suited management instrumentsto overcome them. Hence, the results from this study mayguide future research to separately test moderating effectsfor individual innovativeness dimensions. This will notonly increase the explanatory power of statistical modelsbut will also allow better insights in the actual barrier-reducing effects of specific management instruments.

Third, a worthwhile avenue for future research could bea closer investigation of the shape of the relationships. Inthis study a linear model is assumed, but it is possible thatwith increasing technological innovativeness its positiveeffect on market innovativeness diminishes, because themore the new product differs from existing ones the moreit will require changes in the attitude and behaviors ofprospective new users. On the other hand, the costs forchanges in the organization and the environment mayincrease disproportionally. The result would be an optimaldegree of technological innovativeness that enables suffi-cient differentiation potential without inducing severeimplementation barriers. Since these barriers are definedby the required changes in comparison to the status quo ofa firm and within its environment, additional control andmoderating variables like the ability to change have to beconsidered (Danneels, 2008). Relevant characteristics likethe firm’s corporate mindset (Talke, 2007) or the level ofregulation in the industry would cause different optimaldegrees of innovativeness for different types of firms.

Fourth, the comprehensive empirical approach followsthe suggestions of Page and Schirr (2008). Of course,noble aspirations for methodological rigor are immedi-ately confronted with the harsh reality of data collection.Practical difficulties such as the motivation of firms toprovide several informants on more than one occasionwill inevitably lead to smaller sample sizes with reducedstatistical power. But there is no alternative to the sug-gestions of Page and Schirr. The results of this studyunderline that a multi-informant, longitudinal empiricaldesign is worth the effort. It allows uncovering the indi-rect effects of technological innovativeness, nearly free ofsystematic bias.

Finally, future studies could expand the investigationof technological innovativeness and its consequencesbeyond the initial product. While the present study con-centrated on the immediate commercial success of indi-vidual new product development projects, it could be

39 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

worthwhile to examine the effects on later projects.Highly innovative projects can have a long-lasting andbroad impact on the firm. In particular, knowledge andcompetences built into innovation projects can be benefi-cial for future generations of products (Ahn, Lee, andLee, 2006; Danneels, 2002). Therefore, even failures caneventually be valuable for a firm (Maidique and Zirger,1985). However, the analysis of emanating effects fromsingle projects on the new product development programcauses practical and methodological challenges. First, therequired long time horizon will lead to increased samplemortality, which necessitates large initial samples.Second, long-term effects on the program level are onlyto a limited extent related to technological advances ofsingle projects. Many additional factors related to firm-internal as well as external developments come into playthat have to be controlled for.

Management Implications

Some implications for the management of innovation canbe derived from the improved understanding of the per-formance effects and interdependencies of product inno-vativeness dimensions. A thorough assessment of aproduct’s innovativeness enables a more systematicselection of potential innovation projects, which is a pre-requisite for a balanced new product portfolio manage-ment (Meyer and Roberts, 1986; Salomo, Talke, andStrecker, 2008). It is necessary for managers to determinehow much newness they should aim for when developingnew products. The results show that in their selection ofinnovation projects managers should not only considermarket- and technology-related opportunities and risksbut also organizational and environmental consequences.Changes in the innovating organizations, which mayaffect changes in competences, processes, power distri-butions, and acceptance among managers and employees,are often not taken fully into account. Changes of values,infrastructure, and the broader societal and political envi-ronment yield additional challenges. If the costs of theserequired changes become too high, an innovation projectmay be slowed down or even stopped. Therefore, in theirevaluation of project proposals managers should alsoassess the organizational and environmental innovative-ness of a new product in order to anticipate potentialimplementation barriers.

Having transparency of the consequences of an inno-vation project is not only important for the decisionwhether to execute it or not. It is also the basis for theproblem-specific application of management instru-ments. The results of this study stress the central role of

innovation management, because its key purpose is over-coming barriers related to the invention and exploitationof new technological functionalities. Technological inno-vativeness might be created by an increase of R&Dbudgets alone but that is not sufficient for innovationsuccess. Managers have to lay open and address risks andbarriers of technological advances. The described scalesof innovativeness can be used as a score card to detectpossible barriers at different stages of the innovationprocess and can guide managers in dealing with them.For example, only if the likelihood of high environmentalinnovativeness is identified early on can managersinvolve relevant external stakeholders in a timely fashionin order to overcome possible barriers. This transparencyallows for an effective and efficient use of limited man-agement capacities.

References

Ahire, S. L., and S. Devaraj. 2001. An empirical comparison of statisticalconstruct validation approaches. IEEE Transactions on EngineeringManagement 48 (3): 319–29.

Ahn, J. H., D. J. Lee, and S. Y. Lee. 2006. Balancing business performanceand knowledge performance of new product development. Long RangePlanning 39 (5): 525–42.

Amabile, T. M., R. Conti, H. Coon, J. Lazenby, and M. Herron. 1996.Assessing the work environment for creativity. Academy of Manage-ment Journal 39 (5): 1154–84.

Avlonitis, G. J., P. G. Papastathopoulou, and S. P. Gounaris. 2001. Anempirically-based typology of product innovativeness for new financialservices: Success and failure scenarios. Journal of Product InnovationManagement 18 (5): 324–42.

Avlonitis, G. J., and H. E. Salavou. 2007. Entrepreneurial orientation ofSMEs, product innovativeness, and performance. Journal of BusinessResearch 60 (5): 566–75.

Baldwin, J., and Z. Lin. 2002. Impediments to advanced technology adop-tion for Canadian manufacturers. Research Policy 31 (1): 1–18.

Banbury, C. M., and W. Mitchell. 1995. The effect of introducing importantincremental innovations on market share and business survival. Strate-gic Management Journal 16: 161–82.

Barney, J. 1991. Firm resources and sustained competitive advantage.Journal of Management 17 (1): 99–120.

Birkinshaw, J., J. Bessant, and R. Delbridge. 2007. Finding, forming, andperforming: Creating networks for discontinuous innovation. Califor-nia Management Review 49 (3): 67–84.

Bower, J. L., and C. M. Christensen. 1995. Disruptive technologies: Catch-ing the wave. Harvard Business Review 73 (1): 43–53.

Calantone, R. J., K. Chan, and A. S. Cui. 2006. Decomposing productinnovativeness and its effects on new product success. Journal ofProduct Innovation Management 23 (5): 408–21.

Chandy, R. K., and G. J. Tellis. 1998. Organizing for radical productinnovation: The overlooked role of willingness to cannibalize. Journalof Marketing Research 35 (4): 474–87.

Chandy, R. K., and G. J. Tellis. 2000. The incumbent’s curse? Incumbency,size, and radical product innovation. Journal of Marketing 64 (3): 1–17.

Chin, W. W. 1998. The partial least squares approach to structural equationmodeling. In Modern methods for business research, ed. G. A. Mar-coulides, 295–336. Mahwah, NJ: Lawrence Erlbaum.

Chin, W. W., B. L. Marcolin, and P. R. Newsted. 2003. A partial leastsquares latent variable modeling approach for measuring interaction

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 402011;28(S1):28–43

effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research 14 (2):189–217.

Christensen, C. M. 1997. The innovator’s dilemma: When new technologiescause great firms to fail. Boston: Harvard Business School Press.

Cook, T. D., and D. T. Campbell. 1979. Quasi-experimentation: Design andanalysis issues for field settings. Chicago: Rand McNally.

Cooper, R. G., and E. J. Kleinschmidt. 1995. New product performance:Keys to success, profitability and cycle time reduction. Journal ofMarketing Management 11 (4): 315–37.

Danneels, E. 2002. The dynamics of product innovation and firm compe-tences. Strategic Management Journal 23 (12): 1095–1121.

Danneels, E. 2008. Organizational antecedents of second-order compe-tences. Strategic Management Journal 29 (5): 519–43.

Danneels, E., and E. J. Kleinschmidt. 2001. Product innovativeness fromthe firm’s perspective: Its dimensions and their relation with projectselection and performance. Journal of Product Innovation Manage-ment 18 (6): 357–73.

Denrell, J. 2003. Vicarious learning, undersampling of failure, and themyths of management. Organization Science 14 (3): 227–43.

de Vries, E. J. 2006. Innovation in services in networks of organizations andin the distribution of services. Research Policy 35 (7): 1037–51.

Dosi, G. 1982. Technological paradigms and technological trajectories: Asuggested interpretation of the determinants and directions of technicalchange. Research Policy 11 (3): 147–62.

Efron, B., and R. Tibshirani. 1993. An introduction to the bootstrap. NewYork: Chapman & Hall.

Eisenhardt, K. M., and J. A. Martin. 2000. Dynamic capabilities: What arethey? Strategic Management Journal 21 (10–11): 1105–21.

Ettlie, J. E., W. P. Bridges, and R. D. O’Keefe. 1984. Organization strategyand structural differences for radical versus incremental innovation.Management Science 30 (6): 682–95.

Field, M. J. 1996. Telemedicine: A guide to assessing telecommunicationsin health care. Washington, DC: National Academy Press.

Fischhoff, B., and R. Beyth. 1975. I knew it would happen: Rememberedprobabilities of once-future things. Organizational Behavior andHuman Performance 13 (1): 1–16.

Fornell, C., and J. Cha. 1994. Partial least squares. In Advanced methods ofmarketing research, ed. R. P. Bagozzi, 52–78. Cambridge, MA: Wiley.

Fornell, C., and D. F. Larcker. 1981. Evaluating structural equation modelswith unobservable variables and measurement error. Journal of Mar-keting Research 18 (1): 39–50.

Garber, T., J. Goldenberg, B. Libai, and E. Muller. 2004. From density todestiny: Using spatial dimension of sales data for early prediction ofnew product success. Marketing Science 23 (3): 419–28.

Garcia, R., and R. Calantone. 2002. A critical look at technological inno-vation typology and innovativeness terminology: A literature review.Journal of Product Innovation Management 19 (2): 110–32.

Gatignon, H., M. L. Tushman, W. Smith, and P. Anderson. 2002. A struc-tural approach to assessing innovation: Construct development of inno-vation locus, type, and characteristics. Management Science 48 (9):1103–22.

Gatignon, H., and J.-M. Xuereb. 1997. Strategic orientation of the firm andnew product performance. Journal of Marketing Research 34 (1):77–90.

Gemünden, H. G., S. Salomo, and K. Hölzle. 2007. Role models for radicalinnovations in times of open innovation. Creativity and InnovationManagement 16 (4): 408–21.

Gemünden, H. G., S. Salomo, and A. Krieger. 2005. The influence ofproject autonomy on project success. International Journal of ProjectManagement 23 (5): 366–73.

Golden, B. R. 1992. The past is the past—or is it? The use of retrospectiveaccounts as indicators of past strategy. Academy of ManagementJournal 35 (4): 848–60.

Green, S. G., M. B. Gavin, and L. Aiman-Smith. 1995. Assessing a multi-dimensional measure of radical technological innovation. IEEE Trans-actions on Engineering Management 42 (3): 203–14.

Griffin, A., and A. L. Page. 1993. An interim report on measuring productdevelopment success and failure. Journal of Product Innovation Man-agement 10 (4): 291–308.

Hall, J. K., and M. J. C. Martin. 2005. Disruptive technologies, stakeholdersand the innovation value-added chain: A framework for evaluatingradical technology development. R&D Management 35 (3): 273–84.

Henderson, R. M., and K. B. Clark. 1990. Architectural innovation: Thereconfiguration of existing product technologies and the failure ofestablished firms. Administrative Science Quarterly 35 (1): 9–30.

Hill, C. W. L., and F. T. Rothaermel. 2003. The performance of incumbentfirms in the face of radical technological innovation. Academy of Man-agement Review 28 (2): 257–74.

Hulland, J. 1999. Use of partial least squares (PLS) in strategic manage-ment research: A review of four recent studies. Strategic ManagementJournal 20 (2): 195–204.

Ireland, R. D., M. A. Hitt, and D. Vaidyanath. 2002. Alliance managementas a source of competitive advantage. Journal of Management 28 (3):413–46.

Jordan, G., and E. Segelod. 2006. Software innovativeness: Outcomes onproject performance, knowledge enhancement, and external linkages.R&D Management 36 (2): 127–42.

Kafouros, M. I. 2008. Economic returns to industrial research. Journal ofBusiness Research 61 (8): 868–76.

Kale, P., H. Singh, and H. Perlmutter. 2000. Learning and protection ofproprietary assets in strategic alliances: Building relational capital.Strategic Management Journal 21 (3): 217–37.

Keller, R. T. 2004. A resource-based study of new product development:Predicting five-year later commercial success and speed to market.International Journal of Innovation Management 8 (3): 243–60.

Kim, W. C., and R. Mauborgne. 2005). Blue ocean strategy: From theory topractice. California Management Review 47 (3): 105–21.

Kock, A. 2007. Innovativeness and innovation success: A meta-analysis.Zeitschrift für Betriebswirtschaft (Special Issue 2): 1–21.

Kogut, B., and U. Zander. 1992. Knowledge of the firm, combinativecapabilities, and the replication of technology. Organization Science 3(3): 383–97.

Larson, E. W., and D. H. Gobeli. 1989. Significance of project managementstructure on development success. IEEE Transactions on EngineeringManagement 36 (2): 119–25.

Lee, M., and D. Y. Na. 1994. Determinants of technical success in productdevelopment when innovative radicalness is considered. Journal ofProduct Innovation Management 11 (1): 62–68.

Lee, Y., and G. C. O’Connor. 2003. The impact of communication strategyon launching new products: The moderating role of product innovative-ness. Journal of Product Innovation Management 20 (1): 4–21.

Leifer, R., C. M. McDermott, G. C. O’Connor, L. S. Peters, M. P. Rice, andR. W. Veryzer. 2000. Radical innovation: How mature companies canoutsmart upstarts. Boston: Harvard Business School Press.

Leonard-Barton, D. 1992. Core capabilities and core rigidities: A paradoxin managing new product development. Strategic Management Journal13: 111–25.

Lieberman, M. B., and D. B. Montgomery. 1988. First-mover advantages.Strategic Management Journal 9 (Special Issue): 41–58.

Lynn, G. S., and A. E. Akgün. 2001. Project visioning: Its components andimpact on new product success. Journal of Product Innovation Man-agement 18 (6): 374–87.

Lynn, G. S., J. G. Morone, and A. S. Paulson. 1996. Marketing and discon-tinuous innovation: The probe and learn process. California Manage-ment Review 38 (3): 8–37.

Maidique, M. A., and B. J. Zirger. 1985. The new product learning cycle.Research Policy 14 (6): 299–313.

41 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43

March, J. G., and R. I. Sutton. 1997. Organizational performance as adependent variable. Organization Science 8 (6): 698–706.

Mascitelli, R. 2000. From experience: Harnessing tacit knowledge toachieve breakthrough innovation. Journal of Product Innovation Man-agement 17 (3): 179–93.

McDermott, C. M., and G. C. O’Connor. 2002. Managing radical innova-tion: An overview of emergent strategy issues. Journal of ProductInnovation Management 19 (6): 424–38.

McEvily, S. K., and B. Chakravarthy. 2002. The persistence of knowledge-based advantage: An empirical test for product performance and tech-nological knowledge. Strategic Management Journal 23 (4): 285–305.

McGrath, R. G. 2001. Exploratory learning, innovative capacity, and mana-gerial oversight. Academy of Management Journal 44 (1): 118–31.

McGrath, R. G., M.-H. Tsai, S. Venkataraman, and I. C. MacMillan. 1996.Innovation, competitive advantage and rent: A model and test. Man-agement Science 42 (3): 389–403.

Meyer, M. H., and E. B. Roberts. 1986. New product strategy in smalltechnology-based firms: A pilot study. Management Science 32 (7):806–21.

Mintzberg, H., and A. McHugh. 1985. Strategy formation in an adhocracy.Administrative Science Quarterly 30 (2): 160–98.

Molina-Castillo, F.-J., and J.-L. Munuera-Aleman. 2008. The joint impactof quality and innovativeness on short-term new product performance.Industrial Marketing Management 36 (8): 984–93.

Mukherjee, A., and W. D. Hoyer. 2001. The effect of novel attributes onproduct evaluation. Journal of Consumer Research 28 (3): 462–72.

Murmann, J. P., and K. Frenken. 2006. Toward a systematic framework forresearch on dominant designs, technological innovations, and industrialchange. Research Policy 35 (7): 925–52.

O’Connor, G. C. 2008. Major innovation as a dynamic capability: Asystems approach. Journal of Product Innovation Management 25 (4):313–30.

O’Connor, G. C., and A. D. Ayers. 2005. Building a radical innovationcompetency. Research Technology Management 48 (1): 23–31.

Page, A. L., and G. R. Schirr. 2008. Growth and development of a body ofknowledge: Sixteen years of new product development research, 1989–2004. Journal of Product Innovation Management 25 (3): 233–48.

Podsakoff, P. M., S. B. MacKenzie, J.-Y. Lee, and N. P. Podsakoff. 2003.Common method biases in behavioral research: A critical review of theliterature and recommended remedies. Journal of Applied Psychology88 (5): 879–903.

Ringle, C. M., C. Wende, and A. Will. 2005. SmartPLS 2.0 (Beta) [Com-puter software]. www.smartpls.de.

Ritter, T., and H. G. Gemünden. 2004. The impact of a company’s businessstrategy on its technological competence, network competence andinnovation success. Journal of Business Research 57 (5): 548–56.

Rogers, E. M. 2003. Diffusion of innovations. New York: Free Press.

Salomo, S., K. Talke, and N. Strecker. 2008. Innovation field orientationand its effect on innovativeness and firm performance. Journal ofProduct Innovation Management 25 (6): 560–76.

Salomo, S., J. Weise, and H. G. Gemünden. 2007. NPD planning activitiesand innovation performance: The mediating role of process manage-ment and the moderating effect of product innovativeness. Journal ofProduct Innovation Management 24 (4): 285–302.

Schmidt, J. B., and R. J. Calantone. 1998. Are really new product develop-ment projects harder to shut down? Journal of Product InnovationManagement 15 (2): 111–23.

Schreyögg, G., and M. Kliesch-Eberl. 2007. How dynamic can organiza-tional capabilities be? Towards a dual-process model of capabilitydynamization. Strategic Management Journal 28 (9): 913–33.

Song, X. M., and M. M. Montoya-Weiss. 1998. Critical development activi-ties for really new versus incremental products. Journal of ProductInnovation Management 15 (2): 124–35.

Song, X. M., and M. E. Parry. 1997. A cross national comparative study ofnew product development processes: Japan and the United States.Journal of Marketing 61 (2): 1–18.

Sood, A., and G. J. Tellis. 2005. Technological evolution and radical inno-vation. Journal of Marketing 69 (3): 152–68.

Sood, A., G. M. James, and G. J. Tellis. 2009. Functional regression: A newmodel for predicting market penetration of new products. MarketingScience 28 (1): 36–51.

Storey, C. D., and C. J. Easingwood. 1996. Determinants of new productperformance: A study in the financial services sector. InternationalJournal of Service Industry Management 7 (1): 32–55.

Storey, C., and C. J. Easingwood. 1999. Types of new product performance:Evidence from the consumer financial services sector. Journal of Busi-ness Research 46 (2): 193–203.

Swink, M. 2000. Technological innovativeness as a moderator of newproduct design integration and top management support. Journal ofProduct Innovation Management 17 (3): 208–20.

Szymanski, D. M., M. W. Kroff, and L. C. Troy. 2007. Innovativeness andnew product success: Insights from the cumulative evidence. Journal ofthe Academy of Marketing Science 35 (1): 35–52.

Talke, K. 2007. Corporate mindset of innovating firms: Influences on newproduct performance. Journal of Engineering and Technology Manage-ment 24 (1–2): 76–91.

Talke, K., and S. Salomo. 2009. Launching technological innovations: Therelevance of a stakeholder perspective. International Journal of Tech-nology Marketing 4 (2): 248–74.

Talke, K., S. Salomo, J. Wieringa, and A. Lutz. 2009. What about designnewness? Investigating the relevance of a neglected dimension ofproduct innovativeness. Journal of Product Innovation Management 26(6): 601–15.

Tatikonda, M. V., and S. R. Rosenthal. 2000. Technology novelty, projectcomplexity, and product development project execution success: Adeeper look at task uncertainty in product innovation. IEEE Transac-tions on Engineering Management 47 (1): 74–87.

Teece, D. J. 1986. Profiting from technological innovation: Implications forintegration, collaboration, licensing and public policy. Research Policy15 (6): 285–305.

Teece, D. J. 2006. Reflections on “Profiting from innovation.” ResearchPolicy 35 (8): 1131–46.

Teece, D. J., G. Pisano, and A. Shuen. 1997. Dynamic capabilities andstrategic management. Strategic Management Journal 18 (7): 509–33.

Tenenhaus, M., V. E. Vinzi, Y.-M. Chatelin, and C. Lauro. 2005. PLS pathmodeling. Computational Statistics & Data Analysis 48 (1): 159–205.

Tushman, M. L., and P. Anderson. 1986. Technological discontinuities andorganizational environments. Administrative Science Quarterly 31 (3):439–65.

Veldhuizen, E., E. J. Hultink, and A. Griffin. 2006. Modeling market infor-mation processing in new product development: An empirical analysis.Journal of Engineering and Technology Management 23 (4): 353–73.

Verona, G. 1999. A resource-based view of product development. Academyof Management Review 24 (1): 132–42.

Veryzer, R. W. 1998. Discontinuous innovation and the new product devel-opment process. Journal of Product Innovation Management 15 (4):304–21.

Wernerfelt, B. 1984. A resource-based view of the firm. Strategic Manage-ment Journal 5 (2): 171–80.

Wold, H. O. A. 1982. Soft modeling: The basic design and some extensions.In Systems under indirect observation, ed. K. G. Jöreskog and H. O. A.Wold, 1–54. Amsterdam: North-Holland.

Zhou, K. Z., C. K. B. Yim, and D. K. Tse. 2005. The effects of strategicorientations on technology- and market-based breakthrough innova-tions. Journal of Marketing 69 (2): 42–60.

Zirger, B. J. 1997. The influence of development experience and productinnovativeness on product outcome. Technology Analysis & StrategicManagement 9 (3): 287–97.

THE MIXED BLESSINGS OF TECHNOLOGICAL INNOVATIVENESS J PROD INNOV MANAG 422011;28(S1):28–43

Appendix. Measurement Items and Construct Characteristics

Constructs and Items Based on Loadings t-Value CR AVE

Commercial Success(T2, Project Leader)

Griffin and Page (1993), Storey and Easingwood (1999),Ahn et al. (2006), Cooper and Kleinschmidt (1995)

0.88 0.59

Achievement of sales goals 0.88 (8.91)Achievement of market share goals 0.81 (6.36)Achievement of time-to-break-even goals 0.80 (6.55)Achievement of net-present-value goals 0.68 (4.14)Achievement of return-on-investment goals 0.67 (4.56)

Technological Innovativeness(T1, Project Leader)

Gatignon et al. (2002), Chandy and Tellis (2000),Green et al. (1995), Talke et al. (2009)

0.79 0.56

In this project a completely new technologicalprinciple is applied

0.77 (7.04)

The technology enables a leap in technicalperformance

0.80 (8.48)

Existing technologies will be superseded by theinnovation (e.g., DVD vs. Video)

0.67 (5.04)

Market Innovativeness(T2, Marketing Manager)

Chandy and Tellis (2000), Jordan and Segelod(2006)

0.78 0.55

The innovation addresses a completely newcustomer benefit

0.74 (4.57)

The innovation addresses many new customers 0.87 (7.68)Steps in the value chain become obsolete or are

being fundamentally changed by thisinnovation (e.g. B2B-market places vs.classical sales)

0.60 (3.41)

Organizational Innovativeness(T2, Marketing Manager)

Gatignon et al. (2002), Avlonitis et al. (2001) 0.88 0.64

The implementation required a reorientation ofthe firm’s strategy

0.73 (4.37)

The implementation required a completely neworganizational structure

0.90 (6.91)

The implementation required the build-up ofcompletely new qualifications

0.69 (2.96)

The company’s processes had to befundamentally changed for the implementation

0.87 (5.85)

Environmental Innovativeness(T2, Marketing Manager)

Salomo et al. (2007), Gemünden et al. (2007) 0.88 0.72

A new infrastructure had to be built for theimplementation of the innovation

0.79 (8.75)

Regulatory frameworks had to be adjusted/created for the innovation

0.94 (28.49)

The innovation meets with criticism in society 0.81 (14.46)

CR = Composite Reliability; AVE = Average Variance Extracted; T1 = Time 1; T2 = Time 2.

43 J PROD INNOV MANAG A. KOCK ET AL.2011;28(S1):28–43