Collaborative Innovation with Customers: A Review of the Literature and Suggestions for Future Research

Collaborative Innovation with Customers:A Review of the Literature and

Suggestions for Future Research*ijmr_310 63..84

Charles R. Greer and David Lei1

Neeley School of Business, Department of Management, Texas Christian University, Fort Worth, TX 76129, USA,and 1Cox School of Business, Department of Strategy and Entrepreneurship, Southern Methodist University, Dallas,

TX 75275, USACorresponding author email: [email protected]; [email protected]

Collaborative innovation with customers or users is increasingly important for thedevelopment of new products and services. In this paper we provide a review of theliterature, placing emphasis on how firms engage in collaborative innovation withindividual and business customers. Our review develops a synthesized conceptualframework from three existing models, and other streams of research, to organize thisdiverse body of literature. We review studies from several disciplines including innov-ation, strategy, management, marketing and information technology.Although much ofthe literature assumes net positive benefits from such collaboration, we also discusscontrary perspectives. We highlight areas in which research is needed for greaterunderstanding of the strategic issues and for managing the collaborative process, andprovide suggestions for future studies.

Introduction

The importance of collaborating with customers inthe development of innovative products and serviceshas been recognized for many years. As a result, suchcollaboration has become a major component ofmany organizations’ developmental efforts and therehas been a steady proliferation of studies on thissubject. In the product design literature, for example,Elofson and Robinson (2007), Franke et al. (2006)and Franke and Piller (2004) have investigated theimpact of customer knowledge and capabilities onnew product design. The implications of collabora-

tive innovation with customers (CIC) are substantialas there has been a paradigm shift. Firms now learnfrom their customers and new technologies pushtoward collaboration and more open forms of innov-ation (Chesbrough 2003; Chesbrough and Appleyard2007; Lichtenthaler 2008; Prandelli et al. 2006).

Firms are working closely with customers andsuppliers and are obtaining new insights and know-ledge from these sources (Prahalad and Ramaswamy2000; Skaggs and Youndt 2004). Declining econo-mies of scale in research and development areprompting some of these collaborations (Chesbrough2006; van der Meer 2007) and the growth ofextended relationships among firms is even trans-forming the nature of competition and cooperation(Lichtenthaler 2008). In several industries, such asathletic footwear (Fuller et al. 2007), equipment forextreme sports (Hienerth 2006; Raasch et al. 2008),surgical equipment (Lettl et al. 2006) and videogames (Jeppesen and Molin 2003), customers areserving as sources of product and service innovations

*A free Teaching and Learning Guide to accompany thisarticle is available at: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1468-2370/homepage/teaching___learning_guides.htm

The authors would like to acknowledge the assistance ofBart Shirley, Lisa O’Brien, Satish Nambisan, Ville Ojanen,David Cravens, Sunny Cui and Ray Smilor.

International Journal of Management Reviews, Vol. 14, 63–84 (2012)DOI: 10.1111/j.1468-2370.2011.00310.x

© 2011 The AuthorsInternational Journal of Management Reviews © 2011 British Academy of Management and Blackwell Publishing Ltd.Published by Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA02148, USA

or ideas for future development. A few examplesinclude Snap-on’s collaboration with automotivetechnicians who create the logic for their computer-ized diagnostic systems on an after-hours basis,Lego’s collaboration with customers on the develop-ment of its Mindstorms NXT Robot, and the BBC’scollaboration with customers who provide pro-gramme content (Seybold 2006).

In this paper we provide an interdisciplinaryreview of the CIC literature that involves collabora-tion between (1) producers or suppliers and (2) cus-tomers or users, either as individual consumers orbusiness customers.1 We use the CIC acronym to referto the process of engaging in the creation of newproducts or services in collaboration with customersor users. CIC falls within one of the major streams ofopen innovation (OI) (Gianiodis et al. 2010), whichhas been defined as ‘systematically performingknowledge exploration, retention, and exploitationinside and outside an organization’s boundariesthroughout the innovation process (Lichtenthaler2011, p. 77). Although there has been debate aboutthe value of OI as a framework (Linstone 2010; Trottand Hartmann 2009), the concept generally includesinbound, outbound and combined processes or know-ledge flows (Gianiodis et al. 2010; Lichtenthaler2011). OI presents a perspective that describes thedegree to which an organization’s boundaries arepermeable to knowledge flows (Chesbrough andCrowther 2006).

Inbound processes utilize the discoveries of others(e.g. acquisitions), outbound processes involvepassing on internally developed technologies (e.g.licensing), and combinations involve processes suchas alliances and cross-licensing (Chesbrough andCrowther 2006; Gianiodis et al. 2010; Lichtenthaler2011). Another dimension of OI is whether suchprocesses are of a pecuniary or non-pecuniary nature(Dahlander and Gann 2009). OI has been furtherdefined as involving four research streams: (1) tech-nology transactions, (2) user innovation, (3) businessmodels (e.g. appropriability), and (4) innovationmarkets (e.g. intermediaries and auctions) (Lich-tenthaler 2011). This review falls within the secondstream, but our focus on customers goes beyond

previous work in this area, which has often concen-trated on lead users.

CIC is less comprehensive as it involves the pro-cesses by which firms and customers engage inmutual innovation, instead of the broader OI issuesof acquisition or divestiture. Although we refer to OIconcepts at times for comparison, clarification orextrapolation, much of the vast literature on OI,which can occur without interaction with customers,is beyond the scope of our review.2 Also beyond thefocus of our review are studies concerning customerswho innovate by themselves, only with other users invirtual communities, or as lead users who formuser-led companies, but never engage in collabora-tion with manufacturers, producers or suppliers(Baldwin et al. 2006; von Hippel 2005).

The first objective of our paper is to provide aninterdisciplinary review that encompasses workfrom the innovation, strategy, management, market-ing and information technology (IT) literatures.We pursue this objective by (1) reviewing studiesthat convey insights into how firms engage in CICand (2) providing summaries of the approaches,samples, types of collaboration and key findings ofpapers that directly address CIC. The second objec-tive is to review perspectives that are critical ofthe approach. The literature has often assumed netpositive benefits, although there are several chal-lenges with CIC that are receiving more attention(Brockhoff 2003; Ojanen and Hallikas 2009;Schultze et al. 2007). Our third objective is toprovide suggestions for future research on this topic.

We note that a recent review by Bogers et al.(2010) has addressed innovation by users (particu-larly lead users), with emphasis on why users innov-ate. While we include work on lead users, whichbegan with the path-breaking work of Eric vonHippel (von Hippel 1978, 1986, 1988), our reviewfocuses on how firms and customers collaboratein innovation, such as through participatory design,empathy, trust and modularization. Our reviewplaces greater emphasis on strategic managementissues, such as the effects of CIC on in-house innov-ators, the selection of innovation partners, the role of

1Where needed for clarity, we identify whether the customeris an individual or business customer and provide separatediscussions in the sections on motivation and indicators ofcollaborative potential, where such distinctions are mostcritical. The supplementary material also provides informa-tion on the level of analysis.

2We note that there are differences between the focus of ourreview and the concept of mass collaboration. Mass collabo-ration or peer production, such as seen in the examples ofWikipedia and Linux, involve innovations that are developedand maintained by thousands of contributors (Tapscott andWilliams 2008). However, these initiatives do not necessar-ily involve collaborations between producers or suppliersand customers or users.

64 C.R. Greer and D. Lei

© 2011 The AuthorsInternational Journal of Management Reviews © 2011 British Academy of Management and Blackwell Publishing Ltd.

networks, and customer motivation. Our approach ismore interdisciplinary as we review a substantialnumber of marketing papers on co-production andco-development, as well as IT papers. We alsoprovide a synthesis of existing conceptual frame-works for CIC.

Approach to the review

We used the electronic database EBSCO BusinessSource Complete to search academic journal papers.Because several terms may potentially refer to CIC,we used a number of words or phrases in titlesor as key words: co-creation, co-development, co-innovation, co-production, collaborative innovation,customer new product development, joint devel-opment, lead users, participatory innovation anduser-centric innovation.3 In addition, we conductedBoolean searches on several combinations of these askey words. We also conducted text searches usingsome of these key words. We retained papers by theirrelevance as indicated by their title or abstract, or byexamination of the paper. Also, we limited the searchto journals dealing with innovation, strategy, manage-ment, marketing and information technology and topapers written in English. In addition, in order toidentify papers potentially missed in such searches,we conducted targeted searches of journals withheavier focus on these topics in the EBSCO database,as well as the Emerald database. We also conductedmanual searches of numerous reference lists to iden-tify additional relevant papers and books and searchedan electronic library catalogue for relevant books.

Conceptual framework

The lack of a comprehensive theory for CIC, particu-larly from a managerial perspective, has been cited asan important shortcoming in the literature (Bogerset al. 2010). There has been substantial reliance onSchumpeterian concepts (Schumpeter 1934), withinnovation being motivated by the prospect of

economic rents (von Hippel 1988). For example,Schumpeterian theory explains market displacementof entrenched incumbent firms by entrepreneurialfirms (Chesbrough and Crowther 2006; Ojanen andHallikas 2009). Agency theory, which can provideinsights into decisions about innovating in-house orpurchasing innovations, has been used for guidance(Athaide et al. 2003; von Hippel 2005). Transactioncost economics, which can explain fidelity andperformance in CIC relationships, has been used astheory (Athaide et al. 2003). For example, suchtheory helps to explain decisions about engaging ininnovation activities outside the firm (Ojanen andHallikas 2009).

However, none of these theories provides compre-hensive guidance for understanding the process ofCIC (Athaide et al. 2003). While these theoriesprovide insights on why firms might pursue CIC,they provide little guidance to how such innovationcan be performed. As a result of these deficienciesthere has been a call for more applicable, relevantand integrated theory (Bogers et al. 2010; Gianiodiset al. 2010; Ojanen and Hallikas 2009; Tzeng 2009).The need for such theory, to explain such phenomenaas co-creation of value and co-production, hasresulted in the development of service-dominantlogic, which emphasizes relationships and the cen-trality of customer integration in active exchangesof knowledge and skills (Vargo and Lusch 2004).Integrative theory is also reflected in a recentapproach to firm-hosted virtual forums (for productinnovation), which has found evidence for thesuperiority of the interaction of multiple theories,relative to single theories, as explanations of cus-tomer involvement. The approach involves the inter-action of social capital theory (sense of obligation),social exchange theory (social reward expectations),involvement (sense of partnership with the firm)and social identity (identification with the group)(Nambisan and Baron 2009). An OI framework alsoprovides guidance for innovation decisions, such aswhether to ‘make or buy’, ‘integrate or relate’ (inter-firm innovation options) and ‘keep or sell’. Theframework views the firm’s ability to innovate as afunction of its capacities to invent, transform andinnovate along with its external capacities to absorb,connect and transfer knowledge to external entities(Lichtenthaler and Lichtenthaler 2009).

Table 1 presents three conceptual frameworks thatreflect more comprehensive and integrative explan-ations of CIC. These frameworks, which provide theorganization for our review, include the Ojanen and

3The literature uses several terms in reference to such col-laboration, although some terms, such as co-development,can often have a very different meaning. In addition to CICrelated processes, co-production has also been used to referto customer production or self-service activities, e.g. scan-ning purchases in a store or cropping photos in a camerashop (Bendapudi and Leone 2003), and studies that have thisconnotation are not the focus of our review.

Collaborative Innovation with Customers 65


Hallikas (2009) CIC framework, the Etgar (2008)model of co-production and the Payne et al. (2008)framework for co-creation of value. The Ojanen andHallikas (2009) model, which focuses on organ-izational routines or processes that facilitate collabo-ration, was developed from an examination of CIC inknowledge-intensive engineering consulting. Suchknowledge-intensive business services industries(KIBS) have been the subject of numerous studiesof collaboration and innovation (Bettencourt et al.2002; den Hertog 2000; Miozzo and Grimshaw2005; Skjolsvik et al. 2007).

The Etgar (2008) five-stage co-production model,which is directed toward the joint creation of value,such as initiatives directed at innovation,4 providesthe second framework in Table 1. This model incor-porates the integrative concepts of dominant logictheory at its second stage, which includes customiz-ation, psychological motivations and social ben-efits.5 Components for consumption, distributionand logistics, and assembly, which apply to differentconnotations of co-production, are not included. Thethird framework in Table 1 is the Payne et al. (2008)framework for co-creation of value, which envisionscustomers as equal contributors with firms increation. This framework highlights the recursivenature of the processes involved with supplier andcustomer encounters, relationships and organ-izational learning (Payne et al. 2008). Such recur-sive and related interactions are also characteristicof fourth and fifth generation innovation models(Tidd and Bessant 2009).

While all three models address CIC, they providedifferent perspectives, which should be considered inview of any tensions or contradictions. The Ojanenand Hallikas (2009) model perhaps most closelyreflects the notion of CIC, although at a greater levelof abstraction. Its perspective is different from theother two as it views CIC through the lens of supplierand customer firm interactions, while the Etgar(2008) and Payne et al. (2008) models view theprocess between firms and individual customers. The

4Etgar has confirmed that his theoretical model ofco-production can also apply to CIC, since the logic of themodel is directed toward the joint creation of value, whichinnovation can provide (M. Etgar, personal communication,2 September 2010).5We occasionally refer to different terms, such as co-production or co-creation of value, where verbatim corre-spondence with a source provides greater clarity or whendrawing on studies in which the terms are clearly notsynonymous with CIC.

Table 1. Conceptual frameworks for CIC

Ojanen and Hallikas (2009) CIC model

Driving and restricting forcesOrganizational forcesStrategic/structural forcesCommunication-related forcesIndividual-level forcesTechnology-related forcesExternal forces

Interactiona

Developmental phases of relationshipFirst phase: feasibilitySecond phase: implementationThird phase: further development

Interactionb

Measurement and feedbackObjectivesChallengesNeeded operationsNeeded knowledge

Etgar (2008) Consumer co-production model

First stage: antecedent conditionsMacroenvironmental conditions

Cultural predispositionsTechnological changes

Consumer linked factorsProduct linked factorsSituational factors

Second stage: dominant logic and motivationLevel of customizationPsychological motivations

Intrinsic valuesExtrinsic values

Social benefitsThird stage: cost–benefit analysisFourth stage: activationc

Design phaseInitiating phase

Fifth stage: evaluation

Payne et al. (2008) Co-creation of value model

Customer value-creating processesRelationship experienceCustomer learning

Interactiond

The encounter processEncounter typesCo-creating by encounter design

Interactiond

Supplier value-creating processesCo-creation opportunities

Technological breakthroughsIndustry logisticsChanges in customer preferences

Planning, implementation and metricsOrganizational learning

aIndicates driving and restraining force impact on the developmentalphases of relationships.dIndicates measurement and feedback interaction with feasibility,implementation and further development processes.cConsumption, distribution and logistics, and assembly phases whichapply to more traditional co-production are not included.dIndicates reciprocal interactions with customer and supplier value-creating processes.



Ojanen and Hallikas (2009) model also reflects moreof a managerial approach by introducing objectives,challenges and operational requirements, while theother two models reflect greater consideration ofmicro-level implementation, such as cultural predis-positions in the Etgar (2008) model and experiencesin the Payne et al. (2008) model.

Also, the Ojanen and Hallikas (2009) and theEtgar (2008) models begin at the inception of theCIC process, with driving and restraining forces orantecedent conditions. In contrast, the Payne et al.(2008) model begins at the mid-point of the other twomodels. It focuses on encounter processes involvingfirms and customers that produce new product orservice ideas, as well as learning opportunities forboth parties. If one were to rely solely on the Payneet al. (2008) model, there would be less guidance forthe prerequisite processes that are needed for produc-tive encounters. Also, the Etgar (2008) model doesnot provide as much guidance on the processesinvolved in firm and customer interactions, althoughit provides guidance to decision-makers as to thecircumstances in which CIC is more likely to occur.

Finally, individual motivation is not as relevant tothe Ojanen and Hallikas (2009) model as it is to theEtgar (2008) model. If decision-makers rely only onthe former, there would be little guidance as to thepsychological considerations that motivate membersof a company-sponsored online community to con-tribute design ideas, such as for a new motor cycleor athletic shoe. In contrast, there is little guidancein the Etgar (2008) model about the managerial andorganizational processes that will be needed tosupport such CIC activities. Thus, the three modelsprovide different lenses through which to view CIC,and all three are needed for more comprehensiveunderstanding.

We have compiled a conceptual framework(Table 2) from a synthesis of the three existingconceptual frameworks to provide structure for ourreview. Our inclusion of specific components reflectsrelevance to CIC, focus in the literature and economyof presentation. We also include components notspecified by the three frameworks in Table 1 butwhich are reflective of focus in the literature, such asproduct modularity, indicators of collaborativepotential, lead user collaboration and participativedesign. (Their different sources are indicated inTable 2.) For each component in Table 2, which wasderived from the models in Table 1, we cite thespecific models that serve as the sources. For thosecomponents not contained in these models but which

were suggested by the literature, such as lead users orparticipative design, we provide citations to rep-resentative papers in these streams of literature anddiscussion and citations for related papers in thecorresponding sections that follow.

Table 2. Synthesis of conceptual frameworks for CIC

Driving and restraining forcesa,b

Demand for customization (Etgar 2008)Technology related (Etgar 2008; Ojanen and Hallikas 2009; Payne

et al. 2008)Technological change (Etgar 2008; Ojanen and Hallikas 2009)Product modularity (Baldwin and Clark 1999; Salvador 2007)

Individual, consumer or customer level (Etgar 2008; Ojanen andHallikas 2009)Expertise and depth of knowledge (Etgar 2008)Motivation for collaboration (Etgar 2008; Ojanen and Hallikas2009)

Strategic and structural (Ojanen and Hallikas 2009)Strategy (Ojanen and Hallikas 2009)Networks (Etgar 2008)

Organizational (Ojanen and Hallikas 2009)Cultural views of collaboration (Etgar 2008; Ojanen andHallikas 2009)Availability of time (Etgar 2008; Ojanen and Hallikas 2009)Presence or absence of trust (Etgar 2008; Ojanen and Hallikas2009)Presence or absence of empathy (Etgar, 2008)

Feasibilitya

Assessment of costs and benefits (Etgar 2008)Processes for customer integration (Ojanen and Hallikas 2009)

Implementationc

Indicators of collaborative potential (Bilgram et al. 2008; Fulleret al. 2007)

Learning and knowledge transfer (Ojanen and Hallikas 2009;Payne et al. 2008)Lead user collaboration (von Hippel 2005; von Krogh 2006;Lettl et al. 2006)Participative design (Buur and Matthews 2008; Pals et al.2008)

Further developmenta

Mutual learning (Ojanen and Hallikas 2009; Payne et al. 2008)Mutual innovation processes (Ojanen and Hallikas 2009; Payne

et al. 2008)

Measurement and feedbacka

aDriving and restraining forces, feasibility, further development,and measurement and feedback are components from Ojanen andHallikas (2009).bEtgar’s (2008) major component of antecedent conditions is verysimilar to the Ojanen and Hallikas (2009) driving and restrainingforces.cImplementation is from both Ojanen and Hallikas (2009) andPayne et al. (2008).Note: Some components from the Etgar (2008), Ojanen andHallikas (2009) and Payne et al. (2008) frameworks were notpresented at the level of headings or subheadings, although theywere discussed in these papers. We have included them at theheading or subheading level because they are also wellrepresented in the broader literature.



Table 2, which reflects the general sequence of themodels from Table 1, begins with the notion ofdriving and restraining forces. Such forces are notunique to the Ojanen and Hallikas (2009) frameworkand are similar to the antecedent conditions from theEtgar (2008) model. Indeed, Kurt Lewin’s early workon force field analysis (Lewin 1936) has been widelyused in organizational diagnosis and developmentsince the 1950s (Cronshaw and McCulloch 2008).The major categories of driving and restrainingcomponents include the following forces: (1)demand for customization; (2) technology-related;(3) individual, consumer or customer level; (4) learn-ing and knowledge transfer; (5) strategic andstructural; and (6) organizational.

The next major components include the develop-mental stages of feasibility, implementation andfurther development (Ojanen and Hallikas 2009;Payne et al. 2008). The universality of the feasibilityassessment phase, in which we include assessment ofcosts and benefits and processes for customer inte-gration, has been emphasized in a study of essentialactivities in new product development. Feasibilityanalysis was identified as one of seven activities (outof a set of 54 possible activities) in all 11 companiesstudied (Buijs 2008). Under implementation (Ojanenand Hallikas 2009; Payne et al. 2008) we includeindicators of collaborative potential and knowledgetransfer processes. In the further development phasewe include mutual learning and mutual innovationprocesses. The final component is measurement andfeedback (Ojanen and Hallikas 2009). Recursive andinteractive processes are not incorporated as a separ-ate component in Table 2 as they are implicit in CIC,have been noted in the previous discussion, and arereflected in two of the models in Table 1. In sectionsthat follow, we review the literature for each of thecomponents from Table 2.

Research methods, samples and streams of research

The papers summarized in Table S1 are a subsetinvolving some degree of CIC between producers orsuppliers and customers or users. They are organizedby their correspondence with the major categories ofthe synthesized framework in Table 2.6 With theapplication of this criterion and the use of the proce-dures described earlier, we identified 47 papers, from26 different journals. When the customer is another

business (Magnusson 2009), we accordingly addresssuch businesses from a customer-oriented or end-user perspective. Table S1 provides a summary of (1)research methods, either qualitative or quantitative,(2) samples (including level of analysis), (3) type ofcollaboration, and (4) key contributions and descrip-tive information.

Examination of the papers listed in Table S1reveals that 23 were empirical, 21 were qualitativeand three used combined qualitative and empiricalapproaches. Of the qualitative studies, 75% involvedcase studies, which are represented throughout thechronology of papers. While empirical studies reflecttraditional approaches, recent studies of CIC inonline communities have often relied on netno-graphic techniques, which involve the analysis of thecontent of ideas posted in online discussions and thecharacteristics of contributors (Fuller et al. 2006,2007). Over 80% of the papers provide insights intohow firms can improve innovation with CIC, such asthrough the role of customer knowledge, selection ofpartners, benefits for customers, and processes suchas participative design. The framework in Table 2,and the sections that follow, reflect these streams ofresearch. The remaining papers, which deal withsuch issues as problems encountered, criticisms ofCIC and characteristics of firms engaging in CIC, areintegrated in discussions throughout the review.

Driving and restraining forces

Demand for customization

Research indicates that demand for customized prod-ucts has been stimulated by the heterogeneity ofcustomer needs (von Hippel 2005) and product con-figurations made possible by networked organ-izations (Schilling and Steensma 2001). Possibilitiesfor changes in product design have expanded withflexible manufacturing processes that make it possibleto capture the benefits of economies of scope withoutincurring significant declines in efficiencies (Pine1993).The ability to offer precise customization at thelevel of the individual is also linked with strongerbonding and customer lock-in (Vandermerwe 2000).The literature indicates that firms are using customi-zation and CIC to shape product ideas and reducedevelopment risks. For example, viewers of an onlineseries, which is sponsored by Sprint and Unilever,submit ideas for story plots and vote on the submis-sions of the viewer community (Cook 2008).

6Papers may fit multiple categories, but for economy ofpresentation are shown in only one.



Technology-related forces

Technological change. Recent studies have high-lighted the role of the internet in facilitating CIC, byproviding access to the knowledge of customers orvirtual communities of customers who have commoninterests (Fuller et al. 2007; Prandelli et al. 2008).More entities are sharing ideas and product conceptsthrough internet-based tools that facilitate CIC in allphases of the new product or service developmentprocess (Sawhney et al. 2005). For example, at thefeasibility stage complaints and survey data stimu-late ideas, while customers designate features neededin the product design. Subsequently, customers mayevaluate the product through online animation(Prandelli et al. 2006). However, key customeractivities appear to vary by developmental phase(Kim et al. 2008).

The Lego Ambassadors outreach program, inwhich hobbyists collaborate in the developmentof new product features, provides an example ofsuch networked connectedness (Hamel 2002;Vandermerwe 2000). Similarly, video game design-ers look to their customers as potential co-developers of new gaming ideas and encouragehigh customer interaction during the developmentand testing process (Jeppesen and Molin 2003). Asthe literature has noted, firms now perform aspectsof product development on a virtual basis, suchas by placing product prototypes on the internetfor comment and critique by future customers(Choi and Cheung 2008).

Product modularity. Modularity has been a subjectof substantial interest as firms have sought ways toaccelerate product development and the ability to‘interface’ with other firms (e.g. Sanchez andMahoney 1996; Schilling 2000; Worren et al. 2002).In brief, modularity is generally viewed as involvingthe standardization of interfaces between differentcomponents that connect with one another (Baldwinand Clark 1999). Such standard interfaces provide‘embedded coordination’ between different com-ponents, thereby facilitating product customization(Sanchez and Mahoney 1996).

Modularization also allows firms to create differ-entiated products at lower costs by utilizing differentcombinations of core modules (Pil and Cohen 2006).For example, modularity in design has also beencredited as the most important driver of change in thecomputer and electronics-related industries by facili-tating networked innovation through sharing under-

lying product architectures. The growing use ofUSB-compatible devices, which plug into computersand other devices, exemplifies how an enhanced,shared interface or protocol (‘plug compatibility’)has streamlined and eased product developmentefforts. With modularity, product components can bedeveloped concurrently and then integrated with thecomplete product (Prandelli et al. 2008). In addition,modularity in IT has been observed to facilitateinnovation in information services because it pro-vides greater flexibility and speed in changingsystems (Ordanini and Pasini 2008).

Although the literature has described many ben-efits of modularity, the evidence of its contributionsto CIC remains unclear and its strategic implicationshave been the subject of debate. On one hand, arecent study found that modularity contributes toCIC involving suppliers and users (Kim et al. 2008).On the other hand, a case study of modularity inservices found that the emphasis of client organ-izations on cost savings, which motivates the out-sourcing of IT to KIBS firms, tends to limit theflexibility needed for innovation. Moreover, as KIBSfirms attempt to provide more standardized IT toclients, in order to distribute costs over multiplecontracts, there is less innovation (Miozzo and Grim-shaw 2005). Furthermore, it is possible that learningbetween firms decreases with high levels of com-ponent modularity. When modules are commoditiesthat can be purchased off-the-shelf, there is littleinterdependence between suppliers and buyers, andlittle inter-firm learning. On the other hand, whencomponent modularity is low, there is high inter-dependence between suppliers and buyers and highco-development (Mikkola 2003). A complicatingfactor is that there is no common definition of modu-larity (Campagnolo and Camuffo 2010; Salvador2007), as a recent review of 100 publications foundover 40 different definitions (Salvador 2007).

Individual, consumer or customer-level forces

Expertise and depth of knowledge. The importanceof in-depth knowledge as a contributing factor to CICis indicated in several studies. For example, radicalinnovation in surgical equipment has been attributed,in part, to the in-depth knowledge of surgeons andtheir strong personal motivation to find solutions tospecific surgical problems (Lettl et al. 2006). More-over, sellers who perceive that their customer collabo-rators are knowledgeable are more satisfied with theCIC relationship (Athaide et al. 2003). In-depth



knowledge is also evident in the innovations of onlineuser communities for digital products and computergames (Arakji and Lang 2007; Jeppesen and Molin2003; Kim et al. 2008) and among individual leadusers (Schreier and Prugl 2008). The importance ofclient knowledge is reflected in the innovations ofclient firms and KIBS firms, which serve as know-ledge brokers (Bettencourt et al. 2002; den Hertog2000; Skjolsvik et al. 2007).

Differences in knowledge intensity explainthe extent to which CIC varies across industries(Prahalad and Ramaswamy 2000). For example, theproportion of innovations credited to users is morethan 90% in pultrusion (similar to extrusion), 75% inscientific instruments and 67% in semiconductorsand printed circuit boards. CIC is also more exten-sive with software products when customers areknowledgeable and experienced (Nambisan 2002).In contrast, only one-tenth of the innovations inengineering plastics and even fewer in plastics addi-tives come from users (von Hippel 1988). Percep-tions by in-house developers that lead users lack theirlevel of technical sophistication have also beenlinked to the discontinuation of CIC in high technol-ogy (Olson and Bakke 2001).

Individual customers frequently have the expertiseto improve future product designs by highlightingparticular features they prefer or to point out designflaws (Nonaka and Konno 1998). They can also be animportant source of tacit knowledge, particularly as itrelates to the product’s use and design (Dahlsten2004; Prahalad and Ramaswamy 2004; Selden andMacMillan 2006), which may supplement the know-ledge of in-house experts (Magnusson 2009). A la-boratory study has demonstrated that ordinary userscan provide valuable ideas for new product develo-pment (Kristensson et al. 2004) while another studyhas found that the originality of new ideas for cellulartelephone service is inversely related to users’ know-ledge of the underlying technology (Magnusson2009). Unsurprisingly, there is a negative relationshipbetween the originality of individual user ideas forservice innovations and their feasibility. As a result,consultation with professionals having diverse aca-demic backgrounds is needed to improve feasibility(Magnusson 2003; Magnusson et al. 2003).

The literature indicates that the relationshipbetween knowledge and CIC is complex. While depthof knowledge is generally a contributing factor, giventhe social and collective nature of the process, a largeknowledge base does not necessarily result in innov-ation (Schienstock and Hamalainen 2001). A study of

CIC with the clients of KIBS firms also indicated thatknowledge is not sufficient for success, as it recom-mended screening clients on characteristics such ascommunication openness, tolerance, accommoda-tion, taking initiative, advocacy and personal dedica-tion (Bettencourt et al. 2002). Another study hasquestioned the value of CIC for technical innov-ations, finding that successful collaborations arelikely to focus on less innovative products and thatcollaborations with customers on highly innovativeproducts ‘may be more trouble than they are worth’(Campbell and Cooper 1999, p. 516).

Motivation for collaboration

Individual customers. The sustainability of col-laborative efforts with customers is a critical issue, asit has been argued that such efforts are probablyviable for only a limited amount of time (Amabileand Khaire 2008; Sawhney and Prandelli 2000) andthat incentives are needed to ensure continuedcollaboration as a quid pro quo. Indeed, perceivedbenefits have been found to predict the continuedinvolvement of individual customers in CIC (Nam-bisan and Baron 2007). A wide range of incentivesmay be appropriate, such as payments, expectationsof future services (Vargo and Lusch 2004) and earlyaccess, such as with Microsoft’s beta testers (Praha-lad and Ramaswamy 2000). When there are strongand ongoing collaborative relationships, customersor users may also share knowledge with the expec-tation of future flows of more valuable services(Lusch et al. 2006).

Although financial or extrinsic rewards are impor-tant, they can undermine creativity when individualsare more motivated by intrinsic rewards (Kohn1993). Such non-monetary incentives may includediscretion over product designs, increased control,and greater opportunity for choice (von Hippel 2005;Kaiser and Muller-Seitz 2008; Lettl et al. 2006).Active engagement of the customer in product designactivities may also promote self-actualization. Otherpotential rewards include learning and hedonicbenefits, such as enjoyment, excitement and fun,which have been found to be strongly associated withparticipation in online CIC (Fuller et al. 2006, 2007;Nambisan and Baron 2007, 2009). Because customersatisfaction with collaboration depends on both thenature of the process and the product or serviceoutcome, psychic benefits, whether in the form ofenjoyment, accomplishment, self-confidence orcontrol, may be critical (Bendapudi and Leone



2003). For online CIC, customer empowerment andenjoyment is also positively related to the designtools furnished for interaction (Fuller et al. 2009).

The actual creative process, including the inter-action experience, the challenge of the problem andthe potential for cognitive stimulation, also hasreward implications (Fuller 2010; Fuller et al. 2007;Nambisan and Baron 2007, 2009). For example,Ducati provides recognition for customers who makeonline contributions to designs and uses design com-petitions as incentives (Sawhney et al. 2005).Another example is peer recognition in user commu-nities of computer gamers, who develop new featuresfor games, or for participants in online productforums (Jeppesen and Frederiksen 2006; Jeppesenand Molin 2003; Nambisan and Baron 2009).

Business customers. The literature has alsoaddressed motivation for business customers, andseveral incentives have been identified, such as pricereductions, exclusive rights to the product for a periodof time (Brockhoff 2003; Prandelli et al. 2008), extraservice and warranties (Brockhoff 2003). When thecosts of CIC are high, such as when the informationis sticky or tacit (von Hippel 2005), additional incen-tives may also be needed to encourage participation.Also, when several customers are involved, jointrewards may be appropriate. However, the magnitudeof incentives must offset the dilution of benefits thatoccurs when several collaborators, along with com-petitors, are involved in the same innovation net-works. Moreover, the value of the customer’sinput may be difficult to determine, and when theirsuggestions are not adopted it may be difficult tomaintain their loyalty. Customer innovations may alsobe sidelined for perverse reasons, such as when aproduct is expected to cannibalize sales of existinglines with higher margins (Brockhoff 2003).

Strategic and structural forces

Strategy. The pursuit of CIC can provide a chal-lenge for strategists, as there may be conflicts withfundamental tenets of strategy, such as ownership orappropriation rights (Chesbrough and Appleyard2007; Schultze et al. 2007). There are also problemswith maintaining confidentiality with more radicalinnovation (Brockhoff 2003) and, from the perspec-tive of users, there have been instances in which theinnovations of user communities have been hijackedby manufacturers (Raasch et al. 2008). Anotherimportant strategic issue involves the risk that the

customer will eventually compete with the supplier(Schultze et al. 2007). A survey of collaboration,which was not restricted to customer or user collabo-rators, found that 11% of respondents identified col-laborators becoming future competitors as a majorrisk (Littler et al. 1995). In a worst case scenario, inthe absence of contractual agreement, the customercould license jointly developed intellectual propertyto a competitor (Mehlman et al. 2010).

There is also the potential threat to suppliers ofbeing led by representatives of competing suppliers,posing as customers, toward areas in which productdevelopment is unlikely to be successful (Brockhoff2003). Suppliers or customers could also be at adisadvantage if, in the absence of contractual pro-tections, their innovation is disseminated throughfacilitating intermediaries or knowledge brokers. Forexample, Deloitte conducts an innovation tournamentin which its employees submit ideas for innovationsthey have observed at their client organizations. Thebest ideas are then developed and refined and used toprovide additional or improved services to clients(Terwiesch and Ulrich 2009). The following heuristicfor suppliers summarizes the downside of CIC:

As a simple rule of thumb, if the firm can achieve itsmarketplace objectives with internal resources, orwith a combination of internal resources and assetspurchased through normal procurement channels,the firm typically should not enter a collaborativeeffort. (Mehlman et al. 2010, p. 56)

Networks. Studies have cited a number of benefitsfor networking, such as early and greater customerinteraction in product development (Corso et al.2001), pooling complementary skills, accessingexternal knowledge and accelerating product devel-opment (Pittaway et al. 2004). Positive performanceand productivity effects have also been found withnetworking and greater heterogeneity of partners(Faems et al. 2005; Kristensson et al. 2008; Pittawayet al. 2004). Researchers have highlighted linkagesamong customers and other entities, which involvedesign, prototyping and testing, as significant ben-efits of networked innovation (Jeppesen and Molin2003; Lei and Slocum 2002).

Studies have also noted that the integration of cus-tomer knowledge requires supportive organizationaldesigns (Lei and Slocum 2002) and other mecha-nisms for assimilating customer insights (Prahaladand Ramaswamy 2000). Virtual knowledge brokers(VKBs) or intermediaries now act to foster innov-ation by recombining and transferring knowledge



(Schultze et al. 2007). By providing a forum thatenables idea exchange across multiple entities, theseVKBs facilitate two-way interactions between firmsand customers (and virtual communities). Commoncognitive reference frames and ‘strategic lenses’ alsoaccelerate information flows between firms and cus-tomers (Hitt and Tyler 1991). However, a critique ofOI has pointed out that a counterintuitive effect ofgreater information flows between organizations maybe a decrease in interdepartmental flows in the sameorganization (Trott and Hartmann 2009).

Manufacturers have also sponsored online infor-mation exchanges, supplemented with inputs fromexperts, which enable them to scan user ideas forinnovations (Tietz et al. 2005). Networked innov-ation, which is occurring in online customer commu-nities and social networks (Etgar 2008), may alsorepresent weak ties (Granovetter 1973; Hansen 1999)which have a positive relationship with innovation(Kang and Kang 2009). However, there is evidencethat innovation networks having both weak and strongties are needed, with the complementary functions ofweak ties for exploration and strong ties for exploit-ation, where the focus shifts to implementation-driventasks (Harryson et al. 2008). While there is extensiveresearch on the positive contribution of networks toinnovation (Burt 2005; Perks and Jeffery 2006), anexamination of this work, which involves more thanCIC, is beyond the scope of this review.

Organizational forces

Cultural views of collaboration. While engineeringand science are often emphasized in innovation,some researchers have characterized the process as asocial or collective undertaking involving actors whohave different skills (Schienstock and Hamalainen2001). The literature reflects a growing recognitionthat the social fabric of embedded knowledge inorganizations, the dominant logics, and the strategiclenses of decision-makers limit the ability of organ-izations to absorb information necessary for innov-ation (Florida and Goodnight 2005; Hitt and Tyler1991; Vargo and Lusch 2004). Collaborating withcustomers provides a means for increasing the flowof new knowledge, but firms must first have a com-prehensive understanding of how its offerings fit thecustomer’s overall needs (Lester and Piore 2004).Such understanding of the broader context of thecustomer’s emotions and experiences can providevaluable insight that transcends raw data from marketresearch or focus groups (Visser et al. 2007). Indeed,

raw user data alone do not facilitate the kind ofinsightful interpretations needed for demand articu-lation, which involves the translation and synthesisof market data, and abstract desires about a product,into workable product concepts (Nonaka and Konno1998; Xu et al. 2006).

Incremental, sustaining innovations are usuallywell received by existing business customers, sincethey reduce risk and avoid the costs of significantproduct changes. Also, customer involvement ispotentially biased toward incremental innovation(van der Panne et al. 2003). However, there is alsoresistance to ideas that have been developed in col-laboration with customers. For example, a study ofcollaboration with lead users found problems relatedto the organizational fit of ideas, prospects forinternal funding, difficulties in patenting ideas andtime required for idea generation (Lilien et al. 2002).On the other hand, radical or ‘disruptive’ innovations,which often lead to ‘game-changing’ products andtechnologies, may face resistance from establishedbuyers and customers, particularly industrial orcommercial buyers (Christensen 1997).

Presence or absence of trust. Trust is another likelycontributor to CIC, as it has been highlightedas being critical for innovation with customers(Bettencourt et al. 2002; Brockhoff 2003; Ritter andWalter 2003). Much has been written in the strategicalliance literature about the importance of trust infostering and sustaining collaborative relationshipsamong firms. Firms often find themselves engagingin ‘co-opetition’ whereby they simultaneouslycompete and cooperate with each other to share thecosts, risks and uncertainties of product development(Brandenburger and Nalebuff 1996). Working withcustomers who can be trusted, such as those withwhom a long-term relationship exists, provides anapproach for managing the risks of CIC (Enkel et al.2005a). Furthermore, when radical innovation isinvolved, the implications are more strategic becauseof the need to keep the innovation secret for a longertime period. In such cases, trust and contractualrights become critical (Brockhoff 2003). An investi-gation of product development, which was not con-fined to CIC, also found trust to be a critical factorfor successful collaboration (Littler et al. 1995).

Presence or absence of empathy. Empathy, asreflected in organizational values of caring and help-fulness, has been identified as a key contributor tosustainable, collaborative efforts with customers



(Etgar 2008; Kelly et al. 1990). At the organizationallevel, highly personal relationships that are focusedon identifying and satisfying customers’ individualneeds reflect such empathy (Lei and Greer 2003).Insights into how customers feel and empathy alsofacilitate deeper understanding and enable organ-izations to gain knowledge about customers’ experi-ences, such as with a product or service (Sanders2002; Visser et al. 2007). Ongoing customer involve-ment in developing product ideas may satisfy emo-tional or psychic needs, which create stronger bonds(Prahalad and Ramaswamy 2004). Empathy has alsobeen found in virtual teams involved in CIC and hasbeen linked with effective leadership of culturallydiverse teams (Kayworth and Leidner 2001).

Availability of time. There is evidence from casestudies that new products can be developed withcustomers in less time and at lower cost (Lettl et al.2006). However, the discretionary time of customershas been cited as an issue in collaborative efforts(Etgar 2008). In general, time demands for customersappear to be greater during the earlier phases of CIC,although customer involvement throughout all stagesof innovation appears to facilitate the development ofsuccessful products (Brockhoff 2003). It is interestingto note that suppliers have offered time pressures as arationale for their discontinued involvement in CIC.However, the underlying reason may be inadequatelearning on the part of suppliers (Olson and Bakke2001). Time-based competition, in which firms seekto engage in ever faster product development, canlimit learning from customers as the exploitation of anexisting design trumps the exploration of new cus-tomer needs. However, CIC can speed up innovationwhere developmental processes are more independent(Fang 2008). Time can also become an issue whenCIC requires a comprehensive understanding of thecontext of the customer’s use and tacit knowledge ofthe product. Although CIC can speed up innovation,firms employing collaborative approaches shouldnot expect to immediately produce workable prod-uct designs, and short-term commercial gains areunlikely (Buur and Matthews 2008).

Feasibility

Assessing costs and benefits

Some observers have argued that the ability to designor innovate with customers can become a core

competency (Seybold 2006). The firm’s absorptivecapacity is critical (Tsai 2009) for such competenciesand the value of learning from external sources orcustomers has been well established (Broring et al.2006; Trott and Hartmann 2009). The benefits ofcollaboration with external partners are particularlyimportant for complex or radical innovation (Pitta-way et al. 2004). In contrast, a firm’s pursuit ofdevelopment from only internal sources may result inthe creation of ‘core rigidities’ (Leonard-Barton1992) and ‘cognitive inertia’ (Bond and Houston2003), and the weaknesses of sole reliance on intern-al sources have been well established (Trott and Hart-mann 2009).

While much of the literature assumes positivebenefits for CIC, at some point there may be declin-ing returns, as there is evidence that CIC has aninverted U-shaped relationship with innovationperformance (Kang and Kang 2009). A few studieshave also questioned the effectiveness of CIC orraised questions about the associated costs. Forexample, a survey of manufacturers found no evi-dence that partnering with customers producesmore successful new products than in-house devel-opment (Campbell and Cooper 1999). Similarly, areview of studies of user involvement in the devel-opment of management information systems foundno convincing demonstration of their contributionto system success, although limitations in researchmethods may have prevented more conclusive find-ings (Ives and Olson 1984). Furthermore, althoughcollaboration is often espoused, a study of Dutchfirms found that in larger innovative firms there wasan overwhelming reversion to closed innovation‘when things really start to matter’ (van der Meer2007, p. 201).

Costs can also be substantial, particularly withgreater involvement (Brockhoff 2003), and thedecision to become involved in CIC involves anumber of strategic tradeoffs for both suppliers andcustomers. A survey of firms where collaborationdid not necessarily involve customers or usersfound that 51% of respondents reported higherproduct development costs with collaboration andthat 58% disagreed that it accelerates productdevelopment (Littler et al. 1995). Another risk isthat customers may suddenly discontinue collabora-tion, thereby severely disrupting product devel-opment (Nambisan 2002). Customers for industrialproducts may also be interested in a slower pace ofinnovation, such as when they operate numerousmachines of the same model and keep maintenance



costs low by servicing only one instead of multiplemodels (Brockhoff 2003). Moreover, customerswho believe they have contributed considerableeffort to the innovation may demand greater eco-nomic rewards (Brockhoff 2003).

From the customer’s perspective, one of thedifficult decisions to be made concerns the numberof suppliers with whom they will collaborate. Forcustomers who have committed to CIC, a dis-advantage is that their choice of suppliers will berestricted (Brockhoff 2003). This creates potentialsupplier lock-in and limits the customer’s bargain-ing power. However, there is strong indication thatmany customers perceive the benefits to be greaterthan the costs, as customers are increasing theirCIC activities and in many cases have taken thelead in generating new product ideas (Prahaladand Ramaswamy 2000; Selden and MacMillan2006; Seybold 2006). Indeed, manufacturers mayfacilitate CIC with lead users by providing fundingin later phases of development (Hienerth 2006).High expectations of benefits from innovationare descriptive of lead users (Franke et al. 2006)and researchers have found that, when such expec-tations are not present, customers decline opportu-nities to become involved in CIC (Enkel et al.2005b).

Processes for customer integration

The literature notes that processes are needed forthe integration of customers in CIC. Informationacquisition processes are needed to overcome limi-tations, such as customers’ inability to communi-cate what they need, an inability to recall problemsencountered with a product and the limiting effectsof their real-world experience (Bilgram et al. 2008;Franke et al. 2006; von Hippel 1988; Lilien et al.2002). In addition, lack of foresight (Lettl et al.2006), and lack of experience with a new productor service (Leonard-Barton 1995) can limit thevalue of their inputs. Also, the latent preferences ofcustomers may be difficult to capture unless theyhave experience with a new product (Lengnick-Hall1992). Along this line, a case study of a failed CICinitiative has cited the need for better approachesfor integrating customers into the CIC process(Enkel et al. 2005b). Participatory design, whichhas the potential to overcome some of the chal-lenges and limitations described, is discussed in afollowing section.

Implementation

Indicators of collaborative potential

Individual customers. Several factors have beenfound to be predictive of participation in CIC. Afactor of particular importance with lead users isvery high stakes, such as in equipment for surgery ormountaineering, where there is relatively high userinvolvement in innovative modifications of products(von Hippel 2005; Lettl et al. 2006). Such a factor isrevealed in GE’s pursuit of CIC in its medical equip-ment units (von Krogh 2006). Recent studies havealso been guided by such rationales in their attemptsto identify lead users in online communities(Bilgram et al. 2008; Fuller et al. 2007). Research onlead users has also found such users to be character-ized by the proactive trait of internal locus of control(Schreier and Prugl 2008).

Business customers. Although industry is notstrongly related to OI (Lichtenthaler 2008), thenature of the industry may be a driving or restrain-ing force for CIC as vast differences were citedearlier (von Hippel 1988; Nambisan 2002). Forexample, CIC may be less frequent in service indus-tries because it is easier for lead users to innovatewithout collaborating with existing service provid-ers (Skiba and Herstatt 2009). Also, the stability ofCIC relationships appears to differ by industry, withthose in consumer goods being less stable than thosein industrial goods (Brockhoff 2003). The issue offirm size and innovation is the subject of ongoingdebate (Faems et al. 2005) and whether firm size islinked with CIC remains an unresolved issue. Onone hand, larger firms have been found to be morelikely to engage in online CIC (Prandelli et al.2006) and in OI (Lichtenthaler 2008). On the otherhand, a study by Faems et al. (2005) of CIC atthe firm level found a negative relationshipbetween firm size and innovation. When the mostinnovative firms are considered separately, size isinversely related to collaboration and OI (van derMeer 2007).

Because innovation frequently occurs at thefringes, at a distance from the research core or focaldiscipline (Kanter et al. 1997), diversity of experi-ence is important for innovation. This is particularlytrue if the product design represents a significantbreakthrough or departure from existing designs orsupporting organizational routines. Interdisciplinaryknowledge can also be advantageous because of the



cumulative insights that cut across the different func-tional mindsets that exist in many large firms (Alveset al. 2007; Leonard and Rayport 1997). Networkresearch highlights the generally positive impact ofdiverse disciplines (Burt 2005), and access to inter-disciplinary knowledge has been found to be criticalfor CIC (Lettl et al. 2006).

Differences in customer expertise may lead tovarying levels of involvement at the various stages ofdevelopment. Such differences in involvement havebeen identified as a potential source of conflict,which suppliers need to address (Brockhoff 2003).There is also evidence that the best partners for col-laborative efforts may not be those who are the mosttechnically attractive, in terms of innovativeness and‘know-how’, because their needs may not match wellwith the larger market (Gruner and Homburg 2000).Similarly, the creativity of the customer may not bethe most important criterion for selecting CIC part-ners or the most important criterion for eventualsuccess. Instead, customers’ knowledge or innov-ativeness may be less critical to success than theirpurchasing power (Brockhoff 2003). Indeed, Camp-bell and Cooper (1999) have found CIC to be morelikely where markets are more concentrated andwhere the collaborating partners have access tocustomers.

Learning and knowledge transfer processes

Lead user collaboration. As mentioned earlier, thelead user approach, which originated with Eric vonHippel, constitutes a major stream of programmaticresearch that has established its value in innovation(von Hippel 1978, 1986, 1988; von Hippel andKatz 2002; Urban and von Hippel 1988). Withthis approach, many of the limitations of customerinnovation have been overcome (von Hippel 1988).Moreover, examinations of its effectiveness havebeen the subject of numerous studies, e.g. vonHippel (2005), Lilien et al. (2002), Olson andBakke (2001), Urban and von Hippel (1988). In thelead user approach, the emphasis is on lead custom-ers, who provide early insights into needs and solu-tions for satisfying such needs (Lilien et al. 2002).Such users typically face more extreme conditionsand have greater needs for breakthrough solutionsor products (Lilien et al. 2002). Being ahead ofmarket trends is predictive of innovation (Frankeet al. 2006), and a major advantage of the approachis that lead users can provide early insights intousers’ needs for new products, which the other

players in the market will face months or years later(von Hippel 1986, 1988).

Because of their extreme needs, such users maycustomize or modify the product and are oftenwilling to collaborate on its development (Seybold2006). Accordingly, it has been suggested thatmanufacturers should proactively initiate contactwith lead users (Luthje 2004). The literature oninnovation with lead users has been supplemented byfindings that such users, who are often completelyoutside a target market, are a frequent source ofbreakthrough innovations (Franke et al. 2006; Lilienet al. 2002). Such innovations also often emerge inresponse to firms’ inabilities to meet needs insmaller or neglected markets (Christensen andRaynor 2003).

Participatory design. A few recent studies haveaddressed participatory design which, along withthe term co-design, refers to approaches for buildingin customer or user involvement in CIC, with thegoal of incorporating their tacit knowledge intodesigns (Pals et al. 2008). Papers on participatorydesign typically provide examples, often from Scan-dinavia, about the procedures by which theseapproaches are implemented (Buur and Matthews2008; Pals et al. 2008). In participatory design,which usually occurs in the initial phases of productdevelopment (Pals et al. 2008), users of productsmay be asked to perform their work while beingshadowed by engineering, design and other person-nel, who have little knowledge about the actualwork of such employees. These specialists mayinterview product users and organize data throughsuch means as video recordings of the work. Theparticipants may then engage in team processes inwhich improvements are envisioned with productand organizational changes (Buur and Matthews2008). Personalization of input from individualusers also helps design teams interpret their experi-ences (Visser et al. 2007).

Participatory design has been proposed as analternative for overcoming the limitations of tradi-tional marketing research, which asks customers, ata distance and with very limited contact (includingfocus groups), to validate or improve existingproduct designs (Visser et al. 2007). A relatedapproach to participatory design, called designanthropology (Buur and Matthews 2008), involvesan immersion approach in which developers maywork and live with the customers being studied(Pals et al. 2008).



Further development

Mutual learning

The ability for manufacturers or suppliers to learnfrom their customers and to engage in CIC isdependent on the quality of customer relationships(Payne et al. 2008). Such relationships require aninvestment, and as a result decision-makers havebeen advised to consider the time and expense ofdeveloping relationships before committing to CIC(Campbell and Cooper 1999). Customer and sup-plier learning have been depicted as reciprocal inter-actions, which involve relationships that potentiallyaffect future CIC. An application of theory devel-oped by Thompson (1967) would suggest that higherlevels of reciprocal interdependence increase theneed for mutual adjustment, as firms steadilyincrease their dependence on customers for productinsights. With even higher reciprocal interdepend-ence, firms may regard their customers as key con-tributors to their overall R&D strategy. As the partieslearn more from each other, they can upgrade theirrelationship experience and enhance future col-laborative initiatives (Payne et al. 2008). Anotherbenefit of strong relationships between suppliers andcustomers is that dysfunctional consequences areless likely (Bendapudi and Leone 2003).

Mutual innovation processes

Relationship management has been found to be posi-tively related to the extent of customer involvementin CIC (Ritter and Walter 2003), and training incustomer relationship management has also beensuggested for those involved (Comer and Zirger1997). The level of relationship management shouldbe matched with the circumstances (Lagrosen 2005).Early customer involvement and a ‘clean slate’ per-spective have been recommended (Ciccantelli andMagidson 1993), along with attention to the compo-sition of developmental teams (Luthje and Herstatt2004) and the inclusion of multiple disciplines(Skjolsvik et al. 2007). It appears that customers whoare involved in collaborative efforts need moreexperience when complex products are involved(Brockhoff 2003). Adequacy of experience may bean issue, because it is sometimes challenging to iden-tify manufacturing personnel who feel comfortablein CIC activities (Swink 2006).

Pre-existing product development routines mayhave shaped a more internally focused ‘strategic

lens’ (Hitt and Tyler 1991), at the expense of externalfocus. Likewise, less experienced customers andusers may regard joint idea sharing with firms as atemporary expedient for immediate product needs,rather than a long-standing, emerging practice.Practices for managing intellectual assets in CICinitiatives also have implications for relationships.These include clarifying the parties’ strategiesregarding intellectual property, specifying the condi-tions under which intellectual property should beprotected or licensed, making decisions on dis-closure, and the use of long-term contracts (Hipp andBouncken 2009; Mehlman et al. 2010).

Interestingly, because customers rely on existingproducts as a point of reference in expressing theirdevelopmental preferences, their extensive participa-tion can undermine the creativity of in-house innov-ators and encourage imitative innovation (van derPanne et al. 2003). Some researchers have pointed tothe risk of CIC, which can result from customers’‘natural myopia’, and have recommended that firmsbe more imaginative when pursuing break-throughinnovations. In short, some studies have argued thatfirms may be better served by ignoring or not listen-ing to their customers (Tzeng 2009), since sugges-tions from customers may be overly conservative(Brockhoff 2003). Furthermore, although mass col-laboration is beyond the focus of this review, someobservers have offered similar criticisms, referringto this process as mass mediocrity (Tapscott andWilliams 2008).

Measurement and feedback

The final component of the framework involvesmeasurement or evaluation and feedback (Ojanenand Hallikas 2009). One criterion is whether thefirm’s initiatives with customers cause it to missopportunities for radical innovation, because of adesire to avoid disruption in existing markets (Chris-tensen 1997). In the case of lead users, von Hippel’s(2005) response is that lead users involve a broaderset of entities or people who are not constrained bythoughts of whether their innovations will disruptexisting markets. However, the issue remains forfirms working with customers in their own existingmarkets. Also, the alternative for evaluative com-parisons should probably not be the ‘straw manargument’ for closed innovation, which has beenthoroughly refuted (Trott and Hartmann 2009).However, the impact on the performance of in-house



innovators should be an important criterion for evalu-ation, given the potential for CIC to undermine theirinnovative capabilities (van der Panne et al. 2003).

Researchers have called attention to the potentialuse of ‘return on relationships’ as a metric for evalu-ating customer relationships (Payne et al. 2008). Theconcept, which is a variation of the balanced score-card approach, emphasizes several considerations,such as the importance of high customer retentionand the resulting benefits of better partnerships forCIC (Gummesson 2004). Finally, comprehensiveevaluations are needed so that firms can addressperceptions that collaboration with customers whichinvolves technical innovation may not be worth thetrouble (Campbell and Cooper 1999) or suggestionsthat such collaboration should generally be theexception rather than the norm (Mehlman et al.2010).

Suggestions for future research

Strategic considerations

Technological change and turbulence. From thebroader OI literature, it may be inferred that thefirm’s knowledge management capacities, such asthe ability to integrate knowledge from outside itsboundaries, will also partially determine its successwith CIC initiatives. Such capabilities typicallyrequire structural and cultural changes to createopenness to external knowledge, which along withinternal knowledge is needed for the pursuit ofgrowth strategies (Lichtenthaler and Lichtenthaler2009). Since absorptive capacity, or learning fromexternal sources, is positively associated with firmperformance (Lichtenthaler 2009), a question forfuture research is how such changes can be accom-plished quickly enough to meet the needs of growthstrategies or turbulent environments. Schilling andSteensma’s (2001) work on evolving ‘modular’organizational forms also raises interesting questionsabout the kinds of organizational structure and capa-bilities firms will need in rapidly changing environ-ments. In a related vein, connective capacity, whichinvolves the ability to manage multiple inter-firmrelationships and access knowledge from such net-works, has been proposed as a critical requirementfor OI (Lichtenthaler and Lichtenthaler 2009). Canfirms cultivate a ‘quick-connect’ (Sanchez andMahoney 1996) capability to work with customerfirms in rapidly changing network configurations?

Can they easily adapt and coordinate their productdevelopment routines with those of customerfirms so that they can internalize new sources ofknowledge?

Effect on in-house innovators. The question hasbeen raised whether collaboration with customershas the potential to undermine the creativity ofin-house innovators. More specifically, it has beensuggested that customer involvement may causetechnology-driven ideas to be neglected, because thefirm is discouraged by input from customers who donot envision the future (van der Panne et al. 2003).While this suggestion resulted from a general reviewof innovation success, and not specifically with CIC,the biasing effect would be similar. Future researchalso needs to determine whether emphasis onabsorptive capacity comes at the expense of keyin-house innovation capabilities (Lichtenthaler2009). As firms seek to capture more product designand technical insight from outside the firm, thenature of in-house researchers and teams may changeas well. In-house researchers will increasingly serveas liaisons or linking pins with external entities, andit is likely that their own job designs and requiredskill sets will correspondingly shift.

Collaborators as future competitors. As notedearlier, CIC initiatives, by their very nature, may alsoinvolve the issue of strategic ‘co-opetition’ (Branden-burger and Nalebuff 1996), whereby customers canpotentially become important competitors in defin-ing technical standards, setting product expectations,and even capturing the economic rents generatedfrom more open approaches to product development.The balance of bargaining power also shifts over timeduring collaborative initiatives, such as toward thetechnology supplier when feasibility of the technol-ogy has been established (Mehlman et al. 2010).While CIC increasingly encourages customers toprovide more input to product design, organizationsmust continue to rethink the boundaries of the firm(Chesbrough and Appleyard 2007).

There are open questions about intellectual prop-erty, licensing and partnering which make disclosureand the timing of disclosure fruitful areas forresearch. While some disclosure of proprietary infor-mation is needed for the other party to make thedecision to collaborate, the legal issues involved withdisclosure are complex, particularly in the USA(Mehlman et al. 2010). Companies do not share their‘crown jewels’ of intellectual property (van der Meer



2007; Tapscott and Williams 2008) for good reasons.At the same time, firms may choose to share theirmost advanced product concepts and technologies ifthey can capture a first-mover advantage, or to shapethe future evolution of the industry to their benefit.

Managing the process

Broader implications of modularity. The relation-ship between modularity and CIC appears to becomplex. On one hand, modularity is positively asso-ciated with innovation and the mass customization ofa variety of products and services that meet uniquecustomer needs (Voss and Hsuan 2009). Becausemodularity provides a high degree of embeddedcoordination (Sanchez and Mahoney 1996), it seemsthat standardized interfaces, which enable the devel-opment of new products by combining a variety ofcomponents (Voss and Hsuan 2009), will lead tomore CIC in network interactions. On the other hand,as noted earlier, when modular components becomecommodities, they can be purchased off-the-shelfwith little interaction or inter-firm learning betweensuppliers and customers (Mikkola 2003). Yet,Mikkola (2003) surprisingly found that difficultieswith modular compatibility increased collaboration.This raises the question of whether modularity ispositively associated with CIC when designs andproduct specifications are more fluid in the earlierstages of development.

Managing customer interaction and costs. A fewstudies have found that the quality of individual cus-tomer contributions in CIC is greatly determined byhow interactions are managed, such as through con-sultation with experts. However, the results havesometimes been surprising (Magnusson 2003; Mag-nusson et al. 2003), and more research into thedetailed operational aspects of CIC is needed. Morework on processes for acquiring information fromcustomers or users is also needed, such as on partici-patory design or empathic design, as reflected in thework of Leonard-Barton (1995) and Leonard andRayport (1997).

Cost control is an issue since customers may per-ceive that quicker innovation, which results fromtheir involvement in CIC, comes at a high cost(Brockhoff 2003). Conversely, individual customersmay view CIC as more economical in view of theiropportunity costs, such as surgeons who developmedical devices. Surgeon lead users have evendevoted time to manage innovation networks before

linking up with producers (Lettl et al. 2008). In addi-tion, there should be interest in any cost savings thatare possible with modularity (Pil and Cohen 2006),in the context of CIC. The outcomes of CIC alsoappear to be affected by a number of other factors,such as the industry involved and the level of cus-tomer sophistication (Brockhoff 2003). Knowledgeof such differences across industries and customersshould be important for a better understanding ofcosts.

Selection of partners. As we have noted, suppliersmay not choose the most knowledgeable or inno-vative business customers for CIC partnershipsbecause their needs may not match the greatermarket, or their demand for products may be small(Brockhoff 2003; Gruner and Homburg 2000).Moreover, there is evidence that selection of partnersis affected by their access to markets (Campbell andCooper 1999). In addition, Fuller et al. (2009) haveconcluded that CIC initiatives may sometimes besymbolic. Also, research by Bettencourt et al. (2002)is relevant to partner selection and they have notedthe importance of organizational citizenship behav-iours such as helping behaviours and individualinitiative. However, organizational citizenshipbehaviours have not been identified for selectinginter-firm partners. Partner selection criteria shouldprovide interesting questions for further research.

Conclusions

This paper makes a contribution by providing areview of the literature, which was drawn fromseveral disciplines. In order to provide a logicalstructure for the review, we synthesized three exis-ting frameworks of CIC and incorporated othercomponents that reflect important insights fromdifferent research streams in the literature. Usingthis synthesized conceptual framework, we thenprovided summaries of the critical findings ofstudies that contribute to our understanding of howfirms pursue CIC. Our summaries and interpreta-tions have highlighted key findings and intercon-nections for each of the major components andprocesses involved in these collaborative efforts. Inaddition, we discussed implications for managingthe CIC process and offered suggestions for futureresearch. We also included discussions of contraryperspectives, which have implications for both prac-titioners and researchers.



Another contribution is the review’s breadth ofcoverage of this rapidly expanding literature. Lessthan 12% of our references appear in the recentBogers et al. (2010) review, which focused heavilyon innovation involving lead users.7 The timelinessof our review is also evident in the inclusion of 73papers from the five-year period from 2006 through2010. In contrast, the Bogers et al. (2010) reviewincludes only 24 papers from this period, which infairness to the authors may reflect the earlier originsof the lead user literature going back to the 1970s.The comparative breadth of our review is alsoevident in the inclusion of 21 papers from marketingand management information systems/IT journals,while Bogers et al. (2010) included only two. Finally,our review makes a unique contribution by pre-senting the methods, samples, type of CIC and keycontributions of papers that specifically examinedcustomer involvement.

Limitations

The framework in Table 2 represents a synthesis ofthe three models and reflects coverage by the existingliterature. However, because it is not a compilation,some components from the models were not includedor addressed in this review. For example, we did notaddress macroeconomic conditions, product linkedfactors or situational factors (Etgar 2008) whichmake CIC more likely. Our review has placed greateremphasis on the process of CIC rather than itsdeterminants. However, questions about the typesof products and situations that are most conducivefor CIC should be addressed in future research. Inaddition, our synthesized model does not includeencounter processes from the Payne et al. (2008)model that are involved in services innovation. Wehave not addressed techniques such as process andactivity mapping, business process engineering andcustomer–firm touch point analysis, which Payneet al. (2008) suggest for use in encounter design.These areas should provide intriguing topics forfuture researchers. Finally, our synthesized modeldoes not address different types of customer encoun-ters, such action-supporting (e.g. product usage),cognition-supporting (e.g. functionality) andemotion-supporting (e.g. design), which vary in theirrelevance to CIC (Payne et al. 2008). The role of

emotion and bonding in CIC, which are mentioned inLei and Greer (2003), may provide an interestingarea for future researchers.

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Supporting information

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Table S1. Articles on collaborative innovation withcustomers.

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Collaborative Innovation with Customers: A Review of the Literature and Suggestions for Future Research