The Effectiveness of Customer Participation in New Product Development: A Meta-Analysis

See discussions stats and author profiles for this publication at httpswwwresearchgatenetpublication283767890 The Effectiveness of Customer Participation in New Product Development A MetaAnalysis Article in Journal of Marketing October 2015 DOI 101509jm140057 CITATIONS 55 READS 3334 2 authors Woojung Chang University of Seoul 13 PUBLICATIONS 256 CITATIONS SEE PROFILE Steve Taylor Illinois State University 38 PUBLICATIONS 10818 CITATIONS SEE PROFILE All content following this page was uploaded by Woojung Chang on 01 February 2016 The user has requested enhancement of the downloaded file Woojung Chang Steven A Taylor The Effectiveness of Customer Participation in New Product Development A MetaAnalysis Although the returns of customer participation on new product development NPD performance can vary substantially the current literature lacks a systematic conceptual and empirical integration showing when customer participation is valuable in enhancing NPD performance Building on knowledge management theory the authors present a conceptual framework that synthesizes a variety of contingency factors A metaanalysis empirically examines the moderating effects of contextual factors between customer participation and NPD performance The analysis reveals that involving customers in the ideation and launch stages of NPD improves new product financial performance directly as well as indirectly through acceleration of time to market whereas customer participation in the development phase slows down time to market deteriorating new product financial performance Furthermore the benefits of customer participation on NPD performance are greater in technologically turbulent NPD projects in emerging countries in lowtech industries for business customers and for small firms The authors discuss several theoretical and managerial implications about when to engage customers in the innovation process Keywords customer participation new product development new product development performance knowledge management metaanalysis Online Supplement httpdxdoiorg101509jm140057 T he notion that firms can improve their innovation performance by tapping into customers knowledge around needs and solutions has led firms to increas ingly involve customers at various phases of new product development NPD Fang 2008 Gruner and Homburg 2000 In the ideation stage eg idea generation concept testing firms engage customers to obtain their needs related knowledge evaluate the potential of new product ideas and refine and often select promising ideas for further consideration eg LEGO Ideas In the product develop ment stage eg product design and engineering customers can provide solutionrelated knowledge such as technical advice or design skills eg Threadlesscom In the launch stage eg prototype testing and market launch customers are frequently invited to test prototypes in a realuse setting eg Nokias betatesting community and to help launch new products Some firms benefit from engaging customers in NPD Muji a Japanese consumer goods brand reported that the threeyear aggregate sales of products from users ideas were five times higher than the sales of products built from pro fessional designers ideas Nishikawa Schreier and Ogawa 2013 Yet customer participation sometimes leads to inef ficient NPD processes and poor NPD performance For example in 2006 Netflix invited customers to design a new algorithm to improve the accuracy of its DVD movie rec ommendation engine It took three years for Netflix to develop a new algorithm with customers and even then it could not be implemented because customer preferences had shifted from mailed DVDs to video streaming Lakhani et al 2014 Indeed many firms have found it difficult to leverage customer participation toward NPD success One reason for this is that customers can sometimes be limited sources of innovation because of their lack of valuable creative ideas Christensen 1997 Christensen and Bower 1996 or inability to clearly articulate their latent needs Franke Keinz and Steger 2009 It can also be difficult for firms to manage customer participation because of their diminished mana gerial discretion Boyd Chandy and Cunha 2010 and the increased complexity that comes of reconciling firms objectives and customers interests Hoyer et al 2010 However a dearth of knowledge about the various factors that affect the impact of customer participation on NPD performance precludes guidance about when customer participation either can viably improve NPD performance or should be avoided Chatterji and Fabrizio 2014 These factors are the focus of this article Woojung Chang is Assistant Professor of Marketing Department of Marketing College of Business Illinois State University email wchang3 ilstuedu Steven A Taylor is Professor of Marketing Department of Marketing College of Business Illinois State University email staylor ilstuedu The authors are grateful to the JM review team for their con structive comments Robert Palmatier served as area editor for this article 2016 American Marketing Association Journal of Marketing ISSN 00222429 print Vol 80 January 2016 4764 15477185 electronic DOI 101509jm140057 47 To provide initial insights into when firms can utilize customer participation as a more effective strategy we conceptually integrate a variety of factors that influence the effectiveness of customer participation in NPD and empiri cally examine the moderating effects of contextual factors between customer participation and NPD performance through a metaanalysis of 123 correlations from 39 inde pendent samples This study substantially contributes to the literature on customer participation in the innovation process First drawing on a knowledge management perspective we provide a comprehensive conceptual synthesis of contingency factors in the customer participationNPD performance link From an extensive literature review we identify four critical contingency factorscontextual factors customer partic ipation design factors relationship factors and organizational factors see Theme 1 of the Web Appendixthat can independently or jointly influence the effectiveness of cus tomer participation Aside from a few conceptual integrations about the drivers and outcomes of customer participation eg Etgar 2008 Hoyer et al 2010 there is a surprising lack of synthesis about contingency factors in the customer participationNPD performance relationship Thus our conceptual integration advances a more complete under standing of customer participation by addressing the current lack of knowledge on the contingency factors Second we describe the first systematic empirical syn thesis a metaanalysis of the contextual moderating factors1 of NPD projects industry offerings and country in the customer participationNPD performance association We find that customer participation improves NPD per formance more in technologically turbulent NPD projects in emerging countries in lowtech industries for business customers and for small firms Notably and contrary to previous literature emphasizing the relevancy of customer participation in hightech industries the effect of customer participation on NPD performance is significantly lower in hightech industries In emerging countries and for business customers the correlation between customer participation and new product financial performance is 81 and 65 higher than that found in developed countries and for con sumers respectively These results offer guidance about the contexts in which firms should more actively engage cus tomers for successful NPD Finally we present evidence that in some situations customer participation actually damages or generates non significant impacts on NPD performance which calls for a reassessment of the oftdominant assumption that customer participation always leads to new product success The findings of metaanalytic path analysis indicate that involving customers in the early ideation stage total effect 27 p 01 or later launch stage total effect 20 p 01 enhances new product financial performance directly as well as indi rectly through acceleration of time to market whereas customer participation in the development stage slows down time to market which hurts new product financial per formance total effect 12 p 05 The findings of scenario analyses also support the notion that involving customers in NPD may not always be an effective strategy by revealing that consumers unlike business customers do not facilitate speed to market furthermore engaging customers in emerging countries does not help develop an innovative new product Overall our conceptual and empirical inte grations 1 highlight the idea that failing to examine con tingency factors leads to an incomplete understanding of the effects of customer participation on NPD performance and 2 form valuable groundwork for further research in this domain Conceptual Framework Definitions of Customer Participation and NPD Performance Customer participation refers to a customers involvement in the firms NPD process Fang 2008 Customers have long been believed to be able to provide needs and solution related knowledge that the firm may lack internally Nambisan 2002 Poetz and Schreier 2012 Whereas customers needs related knowledge refers to customers input about their needs and preferences ie What is the problem customers solutionrelated knowledge refers to customers input about potential ways to solve problems Poetz and Schreier 2012 Thus we view customer participation herein as the customer knowledge provision phenomenon whereby customers share their needs and solutionrelated inputs in the firms NPD process We include open innovation with customers Chesbrough 2003 innovation through the leaduser approach Lilien et al 2002 and crowdsourcing Franke Keinz and Klausberger 2013 as customer participation because they also are characterized by integrating external knowledge from customers in the innovation process New product development performance refers to the success of new product development efforts Troy Hirunyawipada and Paswan 2008 p 136 This concept captures the performance of the NPD process and the new product and includes three aspects of success operational financial and marketing performance New product opera tional performance reflects how effectively and efficiently the new product is developed eg new product innova tiveness speed to market whereas new product financial performance describes how much economic return the new product realizes eg sales and profits of the new product New product marketing performance emphasizes marketingoriented aspects such as satisfaction and loyalty within the customerfirm relationship Because the three measures are interrelated we expect similar patterns in the effects of customer participation on each Thus we test the effect of customer participation on NPD performance that combines all aspects of NPD success and further examine the possible effects of differences across the aspects of NPD performance as studyspecific moderators 1For this metaanalysis we focused only on contextual factors among the four contingency factors in the customer participation NPD performance link identified in Theme 1 of the Web Appendix because available studies in this domain are mainly related to con textual factors 48 Journal of Marketing January 2016 Customer Participation in the Firms Knowledge Management Process Figure 1 presents our conceptual framework which emphasizes contextual factors that affect the efficacy of customer par ticipation in NPD The framework is based on the notion that three factors shape the efficacy of the firms knowledge management process involving customer participation 1 the potential value of customer knowledge 2 the difficulty ie stickiness of knowledge management and 3 the characteristics of actors in the knowledge manage ment process These factors rely on contexts ie NPD project industry offering and country thus the returns from involving customers can differ across contexts Bogers Afuah and Bastian 2010 Specifically the effect of customer participation on NPD performance can be enlarged in contexts in which 1 the firm as knowledge seeker acquires valuable knowledge from customers as knowledge providers Mahr Lievens and Blazevic 2014 2 the difficulty of transferring integrating and applying knowledge from customers in the firms NPD process diminishes Szulanski 1996 Von Hippel 1994 and 3 the motivation and abilities of actors ie customers and the firm related to knowledge exchange and integration are maximized Szulanski 1996 Hypothesis Development Potential Value of Customer Knowledge Stage of NPD process The differences in necessary tasks and skills at each NPD phase may make customer participation more valuable in one phase than in others Gruner and Homburg 2000 In the early ideation stage customers provide a variety of needsrelated input comment on other customers new product ideas and often participate in selecting promising ideas for further consideration It is wellestablished that such needsrelated inputs from cus tomers can reduce the risk of new product failure by increasing the productmarket fit Carbonell Rodrıguez Escudero and Pujari 2009 Engaging customers in this phase also helps the firm avoid wasting resources on lowvalue NPD projects that customers do not actually perceive as unique selling propositions Ernst Hoyer and Rubsaamen 2010 Research has also recognized customers diverse perspectives and wealth of information as critical ingredients in the early ideation phase Troy Szymanski and Varadarajan 2001 despite the complexity inherent in a wide range of diverse ideas Arnold Fang and Palmatier 2011 In the product development stage customers can offer useful solutionrelated knowledge in designing and engi neering actual products Coviello and Joseph 2012 Yet extant literature has implied that the value of customer input in this stage may be less than in other stages because of the inherent nature of the development work and development personnels reluctance to accept customer input Katz and Allen 1985 Un and Asakawa 2015 All tasks and knowledge in this stage are highly interdependent and contextual such that changing one component of new products on the basis of customers solutionrelated input may accidentally affect other functions negatively or may not be appropriate in the firms current production situation Un and Asakawa 2015 FIGURE 1 Conceptual Framework of Current MetaAnalysis The Difficulty of Knowledge Management H Hightech industries Lowtech industries 5 StudySpecific Moderators Operational vs other NPD performance measure Financial vs other NPD performance measure Marketing vs other NPD performance measure Objective vs subjective NPD performance measure Binary vs continuous NPD performance measure Binary vs continuous customer participation measure Experiment vs other study design Secondary vs other study design Year of publication Customer Participation Potential Value of Customer Knowledge H1a Ideation stage Development stage H1b Launch stage Development stage H2 Turbulent NPD project Stable NPD project H3 Emerging countries Developed countries H4 Physical goods Services Characteristics of Actors in NPD Knowledge Management H6 Consumer Business customer H7 Large firms Small firms H7alt Large firms Small firms NPD Performance Customer Participation in New Product Development 49 Moreover concerns about 1 the spillover of the firms intellectual property eg technical and engineering know how to customers and 2 researchanddevelopment per sonnels deeprooted notinventedhere syndrome Katz and Allen 1985 which shuns solutions from external sources are often intensified in the development phase Enkel Kausch and Gassmann 2005 The firms engineers may try to protect their conventional leading role in inno vation by being reluctant both to acquire customer input and to allow customers to take charge of the codevelopment process Hoyer et al 2010 Thus even valuable customer knowledge in the development phase may be less likely to be acquired and leveraged in such a way as to maximize its value for successful NPD Finally in the late launch stage which includes activ ities such as prototype testing market testing and market launch customers provide their firsthand feedback on product usability product performance potential problems specific to the prototype and the positioning and marketing mix of the new product These customers reactions help the firm in making the new product error free positioning the product better and coming up with appropriate marketing mix tactics Henard and Szymanski 2001 With a specific prototype customers are better able to provide detailed and precise solutionrelated inputs regarding problems in usage situations and marketing mix of the new product Gruner and Homburg 2000 Gruner and Homburgs 2000 empirical finding and Brockhoffs 2003 claim also support the notion that the level of customer contributions in NPD follows a Ushape from ideation to development and launch stages Taken together we posit H1 The relationship between customer participation and NPD performance is weaker in the development stage than a in the ideation stage and b in the launch stage Degree of technological turbulence of NPD project Technological turbulence2 of an NPD project refers to the rate and uncertainty of technological change in the NPD project Souder Sherman and DaviesCooper 1998 This is an NPD projectspecific variable and it can vary among different projects even in the same industry Souder Sherman and DaviesCooper 1998 First rapid change in technologies in a turbulent NPD project can quickly render the firms existing technologies less useful Danneels and Sethi 2011 It can be a costly and slow process for the firms NPD personnel to catch up with the changing technologies and develop new products internally In such situations engaging customers with solutionrelated knowledge consistent with emerging technologies can be a cost and timeefficient strategy to secure prompt access to critical knowledge and help the firm overcome the constraints of the existing stock of techno logical knowledge Danneels and Sethi 2011 Eggers Kraus and Covin 2014 Second customers input about their uncertain needs caused by rapid technological change can facilitate the quick launch of a new product which is a key success factor for turbulent projects Rapid technological change leads to expeditious product obsolescence and short windows of new product opportunity highlighting the importance of the timeliness of new products Eggers Kraus and Covin 2014 Customer participation enables a firm to obtain accurate knowledge about customers changing needs and to avoid delays resulting from a mismatch between ideas and needs consequently speeding up time to market and helping the firm realize new innovation opportunities within the short time window Carbonell RodrıguezEscudero and Pujari 2009 The pressure of timely NPD in technologically turbulent projects requires the firm to get immediate access to customers need and solutionrelated knowledge Thus we posit H2 The relationship between customer participation and NPD performance is stronger in a more technologically turbulent project than in a project that is less technologically turbulent Degree of economic development emerging versus developed countries Whereas developed countries are already at the forefront of technology and experience stable trends emerging countries undergo rapid economic growth and dramatic change in market and technology development leading to a high level of uncertainty Gaining customer input could be more valuable to firms in emerging countries because customer knowledge can increase responsiveness to rapidly changing trends in technology and markets and can help firms cope with the market uncertainty caused by rapid change Narver and Slater 1990 Moreover firms in developed countries tend to have accumulated a richer stock of resources and knowledge about their products and market using stateoftheart information systems Hitt et al 2000 In contrast many of the firms in emerging countries are relatively young or recently privatized and may not have the sophisticated information hardware and software possessed by most developed market firms leading to limited knowledge resources Hitt et al 2000 p 452 According to the marginal information value argument if knowledge resources increase the probability of diminishing returns of knowledge exchange and knowledge sharing grows Li and Hsieh 2009 p 427 Thus firms in developed countries may find the knowledge they gain from customer participation to be redundant Although firms in emerging countries tend to have limited experience or organizational support systems for customer participation Etgar 2008 previous research has consistently implied greater benefits of customer participation in emerging countries on the basis of the rapidity of change there and the marginal information value argument Thus we propose H3 The relationship between customer participation and NPD performance is stronger in emerging countries than in developed countries The nature of developed products goods versus services Although research on customer participation in service innovation is relatively scarce Carbonell Rodrıguez Escudero and Pujari 2009 service firms also seek customer participation in new service development For example the US Postal Service allows customers to post new service ideas 2Despite the potential moderating effect of market turbulence Jaworski and Kohli 1993 we could not include it because of the scarcity of related correlations 50 Journal of Marketing January 2016 about shipping and mail on its website and uses their ideas to improve and create new postal services The unique charac teristics of service imply that the effect of involving customers on NPD performance could vary between the new physical products and service development contexts Witell Gustafsson and Johnson 2014 First the more intimate interaction between a customer and a service provider which results from services inseparability of production and consumption sug gests that greater opportunities exist for customizing services to customers specific needs and contexts Schleimer and Shulman 2011 The possibility of a high degree of customization and easy adaptability relative to tangible products may make obtaining accurate knowledge about customers specific needs more valuable to service firms Second customer participation particularly in the later phases of the NPD process for services has greater potential to reduce the risk of new product failure Witell Gustafsson and Johnson 2014 The success of new physical goods is relatively dependent on productspecific factors eg product quality product advantage but in services a customers perceived evaluation of the interaction between a customer and a service provider or service technology plays a more critical role Ottenbacher and Harrington 2010 Thus new service success cannot be accomplished without customer feedback on the effectiveness of the service delivery process that is based on the interaction between a customer and a service provider Thus we propose H4 The relationship between customer participation and NPD performance is stronger for developing services than for developing goods Despite these arguments however some scholars have claimed that the possibility of a high level of customization in services may lead the firm to appeal only to smaller customer segments thereby constraining the firms opportunities to gain greater financial returns from the new services Kirca Jayachandran and Bearden 2005 Moreover because the intangibility of services may make it difficult for customers to evaluate the new services before actual utilization Szymanski Kroff and Troy 2007 customers may provide only unspecified or uncreative ideas in service innovation thereby limiting the benefits of customer participation The Difficulty of Knowledge Management in NPD Hightech versus lowtech industry Hightech refers to an industry whose offerings are based on significant amounts of scientific and technical knowledge Rubera and Kirca 2012 As the prevalence of leaduser methods in hightech industries has shown Herstatt and Von Hippel 1992 customers have the potential to offer valuable needs and solutionrelated knowl edge in hightech industries eg Coviello and Joseph 2012 However the challenge is that the knowledge in hightech industries is characterized by high degrees of complexity and tacitness that increase the difficulty of knowledge management in NPD De Luca Verona and Vicari 2010 Knowledge stickiness theory3 suggests that all else being equal customer knowledge in hightech vs lowtech industries may yield lower returns on NPD performance because of knowledge stickiness or the difficulty of transferring and applying knowledge from the knowledge provider to the knowledge seeker in a usable form Szulanski 1996 Von Hippel 1994 Specifically even though customers have valuable knowledge it is often difficult for them to transfer such complex and tacit knowledge to the firms NPD team in hightech industries De Luca and AtuaheneGima 2007 Szulanski 1996 A high level of knowledge complexity in hightech industries also hinders the firms knowledge integration because integrating complex knowledge from customers with the firms prior stock of knowledge is more complicated and challenging De Luca Verona and Vicari 2010 The consequence is a lower probability that cus tomer inputs in hightech industries are transferred to the firms NPD employees integrated and finally utilized in the NPD project Thus we predict H5 The relationship between customer participation and NPD performance is weaker in hightech industries than in low tech industries Characteristics of Actors in NPD Knowledge Management Knowledge provider consumers versus business customers As knowledge providers customers motiva tion to actively share their knowledge in the innovation process and their ability to possess reliable and relevant knowledge can vary between businesstobusiness B2B and businesstocustomer B2C contexts Bogers Afuah and Bastian 2010 Business customers in B2B markets are more motivated to share their knowledge because they can expect more explicit benefits from participation in NPD than consumers in the B2C market such as development of customized products for themselves improvement of the products they sell and exclusive rights to the customized product for a period of time Brockhoff 2003 Fur thermore relative to consumers business customers are believed to possess more reliable and relevant knowledge about the NPD projects goals and needs because they tend to have a high level of mutual understanding of needs and expertise as well as a shared language Mahr Lievens and Blazevic 2014 Consequently business customers can produce more relevant and feasible ideas to solve the problem at hand in the NPD process though there is the potential disadvantage that they may not provide diverse and authentic information Gargiulo and Benassi 2000 In summary business customers reliable and relevant knowledge and their higher motivation to share this knowledge compared with consumers can lead to greater returns from customer participation Thus we propose the following H6 The relationship between customer participation and NPD performance is weaker for collaboration with consumers than for collaboration with business customers Knowledge seeker firm size As knowledge seekers in the innovation process firms may have differing levels of 3We appreciate an anonymous reviewers suggestion about using the concept of stickiness Customer Participation in New Product Development 51 motivations and abilities to acquire and leverage external knowledge from customers according to firm size Lee 2011 Von Hippel 1994 Large firms are likely to possess more internal resources including existing knowledge about their established customer base and product category as well as technical skills This large stock of prior knowledge enhances large firms absorptive capacity or ability to recognize the value of new information assimilate it and apply it to commercial ends Cohen and Levinthal 1990 p 128 As a result large firms are expected to find it easier to evaluate the potential value of knowledge obtained from customers in the NPD process leverage the knowledge effectively and apply it to new products Brockman and Morgan 2003 Furthermore large firms with more internal resources are likely to have resource slack enabling them to better manage the knowledge creation and appropriation process in NPD Joshi and Sharma 2004 Following this reasoning we expect H7 The relationship between customer participation and NPD performance is stronger for large firms than for small firms In contrast motivationally large firms can have dis advantages in effectively acquiring and leveraging external knowledge Bettis and Prahalad 1995 Scholars have pointed out that a stock of existing knowledge may serve as a core rigidity holding firms back from acquiring new external knowledge LeonardBarton 1992 A large firms inertia and large stock of extant knowledge may inhibit new learning processes to acquire knowledge from customers for NPD whereas small firms are highly motivated to complement their lack of internal knowledge through customer partic ipation Moreover because large firms tend to have estab lished NPD processes it would be more challenging for them to integrate customers into a settled system Schaarschmidt and Kilian 2014 Given the wellsupported stream of research about the lack of motivation of some large firms to process external knowledge we propose the following alternative hypothesis H7alt The relationship between customer participation and NPD performance is weaker for large firms than for small firms StudySpecific Moderators We also examine the moderating effects of studyspecific variables on the customer participationNPD performance link First we enter study variables related to measures of key variables including measures of customer participation ie whether customer participation is assessed as a binary or continuous variable measures of NPD performance ie objective vs subjective performance measure and binary vs continuous performance measure and dimen sions of NPD performance ie operational financial and marketing NPD performance Second we consider the type of research design ie whether the correlation comes from survey research an experiment or secondary data research Finally we enter the year of publication to test whether the magnitude of the correlation of interest changes over time Methods Database Development and Level of Analysis We first identified relevant studies as of May 2014 through searches of electronic databases using ABIINFORM Global Business Source Complete ProQuest Digital Dis sertations and Google Scholar As search terms we used customer participation customer involvement co creation coproduction and crowdsourcing as well as combinations of these key terms with new products new services and performance Second we supple mented the electronic searches with manual searches of abstracts of articles published in Academy of Management Journal Administrative Science Quarterly Industrial Marketing Management Journal of Business Research Journal of Marketing Journal of Marketing Research Journal of Product Innovation Management Journal of the Academy of Marketing Science Management Science Organization Science and Strategic Management Journal Finally we examined the references to find overlooked studies In terms of inclusion criteria we first limited our dis cussion to studies that measure customer participation and performance at the new product project level making our unit of analysis an NPD project Second we retained only articles about collaborating with customers rather than with suppliers or frontline employees Third the zeroorder cor relation4 of the relationship of interest or other statistical information that could be converted into correlations was required Finally multiple studies using the same sample were treated as a single study and several independent samples from a single study were regarded as different observations Variable Coding After reaching consensus on the definitions and coding criteria for the variables of interest the two authors independently coded all the studies The specific coding criteria for key variables appear in Theme 2 of the Web Appendix For each variable the initial independent coding between the two authors yielded greater than 82 inter coder reliability which indicates a good level of interrater agreement see Theme 2 After initial coding we resolved discrepancies in coding results by discussion We further checked coding quality by getting an independent coder who is knowledgeable about this topic but not involved in 4Our metaanalysis is based on zeroorder correlations that do not account for the effects of other variables that may influence the relationship However because a metaanalysis combines the cor relations from many studies conducted in various contexts a meta analytic estimate is perceived to be closest to the unknown true relationship For that reason most of the metaanalyses in marketing have successfully used zeroorder correlations as the effect size Eisend 2015 In addition with correlations we cannot exclude the possibility of reverse causality such that high performance leads to more customer participation However because it is unusual that higher NPD performance of a particular new product project would lead customers to be more involved in the new product project the issue of reverse causality is of less concern 52 Journal of Marketing January 2016 this study to code the moderators of all the studies The agreement level between the coding of the two authors and the coding of the independent coder is greater than 96 for each moderator confirming high coding quality We resolved the few differences by discussion As a result we coded 123 correlations between customer participation and NPD performance from 39 independent samples reported in 35 empirical studies We present a list of studies in this metaanalysis and detailed information in Theme 3 of the Web Appendix The numbers of studies and effects in cluded in this metaanalysis are comparable to those from metaanalyses in new product success contexts eg 95 effects from 32 studies in Szymanski Kroff and Troy 2007 146 effects from 25 studies in Troy Hirunyawipada and Paswan 2008 Furthermore the maximum number of correlations in a single study is 20 which accounts for approximately 16 20 out of 123 of the total effects Compared with Troy Hirunyawipada and Paswans 2008 21 the 16 of our metaanalysis indicates that a single study does not provide an excessive number of correlations Data Analysis Metaanalysis approach We began with a preliminary analysis that provides initial insights into the central ten dency and distribution of the effects Troy Hirunyawipada and Paswan 2008 As we show in Theme 4 in the Web Appendix the 123 correlations between customer partic ipation and NPD performance range from 290 to 589 with one correlation being zero and 17 correlations being negative M 196 SD 187 SE 017 The correlation frequency is normally distributed Zskewness 009 p 05 Zkurtosis 785 p 05 We first calculated the mean correlation between cus tomer participation and NPD performance to provide overall insights on the relationship We adjusted the effects from each study for measurement error by dividing the correlation coefficients by the product of the square root of the reliabilities of the two constructs Hunter and Schmidt 19905 We then transformed the reliabilitycorrected correlations into Fishers zcoefficients and weighted these coefficients by the inverse of their variance to give greater weight to more precise estimates with greater sample sizes Borenstein et al 2009 Finally we computed the mean effect size by dividing the sum of the weighted coefficients by the sum of the weights and converting it from the Fishers z metric back to correlation Table 1 shows the calculated mean correlations between customer participation and NPD performance For completeness we report the mean correlations between customer partic ipation and discrete dimensions of NPD performance in Table 1 but our moderating analysis is based on the relationship between customer participation and NPD performance that combines all dimensions TABLE 1 Overview of Customer ParticipationNPD Performance Relationships Relationships Number of Samples Number of Effects Number of Observations Mean Correlationa 95 Confidence Interval QValue I2 Fail Safe Nd NPD performance combined 39 123 18002 26 29b 22 30 28 30b 113573 8926 37362 New product operational performance 31 73 10853 28 18b 21 33 16 19b 81993 9115 14471 New product financial performance 26 37 5683 26 34b 19 32 32 37b 24110 8507 3837 New product marketing performance 5 7 923 14 17b 1 28 12 23b 2708 7784 19 New product performance otherc 3 6 543 22 07 36 1607 6888 37 p 01 p 001 aRandom model point estimates bValues in brackets represent adjusted fixedeffects estimates for potential publication bias using Duval and Tweedies 2000 trimandfill method cThis category includes measures that assess new product performance using a mix of different performance dimensions that cannot be classified into one of the three discrete dimensions dThe number of nonsignificant unpublished or missing studies that would need to be added to a metaanalysis to reduce an overall statistically significant observed result to nonsignificance 5Researchers have recognized that dividing the effect size by the product of the square root of the reliabilities inflates the effect size and influences the standard errors Lipsey and Wilson 2000 Following Hoxs 2010 suggested remedy to add reliabilities as covariates we checked the impact of the corrections for measure ment errors The findings indicate that our results are consistent in terms of the hypothesis testing except that firm size is no longer a significant moderator Customer Participation in New Product Development 53 TABLE 2 Correlations Between Moderators 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 Customer participation in 1 ideation vs development stage 2 Customer participation in 29 1 launch vs development stage 3 Technological turbulence 16 11 1 4 Emerging vs developed 13 26 02 1 country 5 Product vs service 22 04 04 01 1 6 Hightech vs lowtech 07 10 06 17 68 1 industry 7 Consumers vs business 09 11 21 49 07 27 1 customers 8 Small vs large firms 18 11 03 03 00 31 01 1 9 Operational vs other 02 02 04 04 02 10 06 05 1 performance measure 10 Financial vs other 01 01 08 00 01 11 09 04 79 1 performance measure 11 Marketing vs other 02 01 04 01 12 19 05 07 30 16 1 performance measure 12 Objective vs subjective 08 02 00 12 16 02 21 03 00 06 07 1 performance measure 13 Binary vs continuous 08 08 00 06 09 06 16 00 16 06 03 04 1 performance measure 14 Experiment vs other study 16 14 00 07 11 21 19 28 08 01 04 05 02 1 15 Secondary vs other study 23 004 00 10 15 05 27 04 04 10 06 49 03 04 1 16 Binary vs continuous 08 15 00 17 22 00 32 26 10 08 23 53 15 42 26 1 customer participation measure 17 Year of publication 12 20 01 45 36 28 31 11 03 04 10 01 40 13 15 26 Notes All correlations whose absolute values are greater than 18 26 are significant at p 05 p 01 Moderator analysis To examine the potential moderat Xj are matrices of the moderators u is the studylevel ing effects we ran hierarchical linear modeling by accounting residual error term and e is the measurementlevel residual for withinstudy error correlation between effect sizes and error term regressing the Fishers ztransformed correlations on the oo o hypothesized moderating variables and studyspecific mod Check for multicollinear ily Before estimating the erators We estimate the specific model as follows model we examined potential multicollinearity among Its variables In Table 2 the correlations between product vs 7 service and hightech vs lowtech variables and between Yij Oo oe Xi uj ej operational and financial performance measures are 68 and I 79 respectively which indicates potential collinearity where Yj are ztransformed correlations in study j Oo is a issues However regressing the ztransformed correlations constant Ox are the parameter estimates of the moderators on all 17 variables reveals that the variance inflation factors ee are less than 10 implying that multicollinearity does not In line with previous metaanalyses g Rubera and Kirca 2012 seriously distort our findings The model that dropped the Troy Hirunyawipada and Paswan 2008 we estimated the model operational performance measure and product vs service using the maximum likelihood method after replacing the missing iable that were not significant in our original model values for the moderating variables with the sample mean of each varla 8 Lo 8 moderator Although most moderators have more than 100 out of 123 showed consistent results with the original model with all valid effect sizes three moderators ie technological turbulence moderators Thus we kept all the variables in this model consumers vs business customers and small vs large firms have a large number of missing values with 33 83 and 33 valid effects respectively According to the simulation results of LopezLopez et al Resu Its 2014 it is acceptable to include moderators with more than 30 effect sizes However to analyze the potential impact of replacing many The Effect of Customer Participation on NPD missing values we employed bivariate regressions for each moderator Performance with a large number of missing values using available data without replacement The results are similar to our results with the replaced Table 1 reports the mean correlations between customer values except that firm size is no longer significant participation and NPD performance At the aggregate 54 Journal of Marketing January 2016 level we found that customer participation is significantly positively related to all types of NPD performance except new product marketing performance Although the small sample size five samples prevents us from making a clear conclusion the results imply that the mean corre lation with new product marketing performance is equal to approximately half of the correlations with the other per formance measures An investigation of the five samples that involve new product marketing performance reveals that the prior relationship eg prior trust interaction between the firm and the customers who engaged in NPD could be a cause of the low correlation The effects of customer participation on new product marketing per formance were very small or even negative when the samples included varying levels of prior relationship between the firm and customers whereas the effect was strongly positive for those with good prior history These findings are notable in that they may suggest effect polarization Customer participation can maximize the firms good relationship with customers but may not affect or may even damage the relationship with cus tomers who have not had a special prior connection with the firm Results of Moderator Analyses Both Qstatistic and I2 values in Table 1 suggest substantial heterogeneity Qvalue 113573 p 001 I2 value 8926 confirming the need for moderator analyses Borenstein et al 2009 Table 3 presents the results of our moderator analyses using hierarchical linear regression The effect of customer participation in the launch stage on NPD performance is significantly greater than that in the devel opment stage b 10 p 05 but the effect of customer participation in the ideation stage does not significantly differ from the effect in the development stage b 02 p 05 Thus we found partial support for H1 In addition H2 is supported as technological turbulence of the NPD project increases the impact of customer participation on NPD performance also increases b 43 p 01 As we expected in H3 involving customers in NPD yields greater returns for NPD performance in emerging countries than in developed countries b 22 p 01 However in terms of H4 we did not find evidence that the relationship between customer participation and NPD performance is stronger in service innovation than for developing goods b 01 p 05 One explanation for this finding may be related to Vargo and TABLE 3 Moderators of the Impact of Customer Participation on NPD Performance Robustness Analyses Model with Full Data Model Without One Outlier Model Without Three Outliers Constant 1535 1157 1432 1144 1110 1098 Customer participation in the ideation vs development stage H1a 02 05 03 05 02 05 Customer participation in the launch vs development stage H1b 10 05 10 05 10 05 Degree of technical turbulence in the NPD project H2 43 12 42 12 44 12 Emerging vs developed country H3 22 07 22 07 19 07 Product vs service industry H4 01 07 02 07 05 07 Hightech vs lowtech industries H5 17 08 16 08 22 08 Consumers vs business customers H6 23 07 21 07 24 07 Small vs large firms H7 19 09 21 09 19 09 StudySpecific Variables Operational vs other new product performance measure 08 10 08 10 09 09 Financial vs other new product performance measure 05 10 03 10 03 10 Marketing vs other new product performance measure 12 13 10 13 09 12 Objective vs subjective performance measures 27 10 20 11 22 10 Binary vs continuous performance measures 27 20 22 20 22 19 Experiment vs other study design 03 16 12 17 06 16 Secondary vs other study design 35 12 42 12 39 12 Binary vs continuous customer participation measure 14 10 07 11 07 10 Year of publication 01 01 01 01 01 01 Number of effects 123 122 120 Number of samples 39 39 39 Wald c2 df 5710 17 5995 17 6597 17 p 05 p 01 Notes In the leftmost column the variables in parentheses are coded as 0 whereas the variables outside parentheses are coded as 1 The values in parentheses are standard errors Customer Participation in New Product Development 55 Luschs 2004 argument that because the traditional dis tinction between services versus manufacturing contexts has been built on a legacy of manufacturingbased theory tra ditional industry categorization schemes may be decreasing in value Further research that examines innovation from the servicedominant logic perspective is needed Skalen et al 2015 The results show that the effect of customer partic ipation in hightech industries is significantly smaller than in lowtech industries b 17 p 05 lending support for H5 In support of H6 involving consumers in the NPD process produces lower NPD performance than involving business customers b 23 p 01 Finally the results provide support for H7alts prediction that small firms utilize customer participation more effectively and generate a greater return on NPD performance than large firms b 19 p 05 Results of studyspecific moderators Studyspecific moderator analyses indicate that the effect of customer participation is smaller when NPD performance is assessed by objective measures eg documented sales and profits than by subjective measures eg managers perceptions of the NPD performance b 27 p 01 Given that objective measures are regarded as relatively free of respondents perception bias Ford Smith and Swasy 1990 these results imply that the actual gains of customer participation reported in extant studies may be inflated by samples based on subjective NPD measures We also find greater impact of customer participation in secondary study design eg online crowdsourcing b 35 p 01 We need to interpret the results with caution because a small number of studies in our metaanalysis are based on secondary study design However a common theme in these studies is that they used longterm NPD performance vs snapshot performance by aggregating NPD performance over the course of a sub stantial time period after product launch eg Nishikawa Schreier and Ogawa 2013 Because the full effects of new products are likely to become evident long after product introduction Henard and Szymanski 2001 such longterm NPD performance7 in secondary study design may capture more of the potential effects Robustness analysis outlier bias We conducted various analyses to check the robustness of our findings The scree plot based on Huffcutt and Arthurs 1995 sampleadjusted metaanalytic deviancy statistic suggests one obvious outlier and two potential outliers in our data set Thus following Geyskens et al 2009 we compare the results of the full data set with the results of the reduced data sets that exclude the one apparent outlier and the three outliers ie one apparent outlier plus two potential outliers and report the results in the Robustness Analyses columns in Table 3 The findings for the reduced data sets that excluded the outliers consistently provide the same conclusions as those for the full data set with outliers Thus we conclude that outliers have negligible effects on our results Robustness analysis availability bias We assessed potential availability bias using a recommended set of tri angulation methods including 1 trim and fill 2 cumulative metaanalysis and 3 selection models Harrison et al 2014 First Table 1 presents the mean correlations of the customer participationdimensions of NPD performance relationships and their adjusted estimates based on Duval and Tweedies 2000 trimandfill method The smaller adjusted estimate for new product operational performance suggests that the available studies may be biased toward large positive impacts which could be interpreted as a form of publication bias The larger adjusted correlations in new product financial and marketing performance could indicate another type of availability biasthat is that smaller effects tend to be published more often for new product financial and marketing performance However further investigation using funnel plots reveals that the observed skew toward smaller effects is not likely to be a result of studies with smaller effect sizes being published more often but rather a result of our having included unpublished sources eg dis sertations that reported smaller effects Second we conduct a cumulative metaanalysis that assesses the drift in effect sizes when studies in the data set are added one at a time according to their precision calculated by the inverse of the standard error The results identify drift in effect sizes implying the possibility of availability bias in our data set Finally a selection model that calculates the adjusted meta analytic effect size estimate by considering the statistical significance of the effect size in certain samples Vevea and Woods 2005 shows that the availability bias in our metadata set is not likely to be a serious issue in moderate asymmetry situations The large failsafe sample size in Table 1 and a nonsignificant Eggers test result p 193 consistently suggest that availability bias may not be a serious issue Overall caution is warranted about the pos sibility of availability bias in new product operational performance but we do not expect availability bias to seriously distort our results in general Robustness analysis sample selection bias Samples from particular industries may be overrepresented in our metaanalysis because customer participation has been prevalent in some industries but not in others Etgar 2008 To evaluate the possibility we compared the distribution of industries in our US sample data set with the overall dis tribution of these industries in the United States The com parison shows that 528 and 332 of firms in our US sample come from manufacturing North American Industry Classification System NAICS codes 3133 and infor mation industries NAICS code 51 respectively compared with 4 and 18 respectively of firms in the United States Specifically most of our samples from information industries are from the software development NAICS code 511 and telecommunications NAICS code 517 sectors while computer and electronic product manufacturing NAICS code 334 and general machinery and transportation equipment NAICS code 333 dominate the samples in our 7To explicitly analyze whether the correlation between customer participation and NPD performance depends on the performance measure longterm vs shortterm that assesses NPD performance we coded a separate moderator of a longterm performance measure other than secondary study design However because of the mul ticollinearity problem we could not include a longterm perform ance measure as a separate studyspecific moderator in our model 56 Journal of Marketing January 2016 manufacturing sectors Thus our data set does not rep resent all industries and the generalizability of our find ings is limited to these industries Further Analyses Scenario analysis A substantial number of effects in our database reported negative correlations between cus tomer participation and NPD performance Post hoc inquiry shows that the negative correlations tend to be with new product operational performance eg new product inno vativeness speed to market in developed countries in hightech industries or in a combination of hightech and consumer contexts We conducted a scenario analysis to explore combinations of situations in which customer participation hurts NPD performance and creates a tradeoff among the types of NPD performance We divided the studies according to NPD stages type of knowledge pro vider consumer vs business customer economic devel opment emerging vs developed countries and type of performance ie new product innovativeness speed to market new product financial performance8 Figure 2 displays the metaanalytic mean correlations in the cus tomer participationcorresponding NPD performance link in each scenario Notably engaging business customers in the NPD process contributes to speeding up the new products time to market and enhancing its financial performance but does not help develop creative new products thus demonstrating business customers tendency toward strategic consideration and convergent thinking style see Figure 2 Panel A In contrast consumers with divergent thinking styles can help firms introduce novel ideas but do not contribute to speed to market In addition business customers contribution to improving new product financial performance is 65 higher than consumers contribution p 01 Although we rec ommend some caution in interpretation because of the small sample sizes we find that customer participation in emerging countries could be a significantly more productive strategy in accelerating time to market than in developed countries p 01 see Figure 2 Panel B In emerging countries the return of customer participation on new product financial per formance is also 81 higher than that of customer partic ipation in developed countries p 01 However involving customers in emerging countries may damage the intro duction of an innovative new product Structural path analysis for NPD stages Contrary to the literature our moderating analysis does not support a sig nificant difference in the effects of customer participation between the ideation and development stages One possi bility for the nonsignificant result is that the aggregation of distinct types of NPD performance may cancel out con trasting effects of customer participation between the two stages As we show in Figure 2 Panel C involving cus tomers in ideation has greater effects on speed to market and FIGURE 2 Scenario Analyses A Customer Type B Country Type C NPD Stage 071 346 374 373 078 227 200 100 000 100 200 300 400 500 Speed to Market Business customer 8a 10b 4a 6b 9a 14b Innovativeness New Product Financial Performance New Product Consumer MetaAnalytic Mean Correlation with Customer Participation 145 506 412 291 198 228 300 200 100 000 100 200 300 400 500 600 Emerging Developed 24b 2a 14b 5a 28b 2a Speed to Market Innovativeness New Product Financial Performance New Product MetaAnalytic Mean Correlation with Customer Participation 248 154 304 276 084 252 373 193 291 200 100 000 100 200 300 400 500 Ideation Development Launch 14a 10a 10b 7ab 6a 8b 17a 10b 13ab Speed to Market Innovativeness New Product Financial Performance New Product MetaAnalytic Mean Correlation with Customer Participation p 01 Notes The numbers above the bars are the mean correlations between customer participation and NPD performance The entries below the bars are the number of effect sizes for each scenario For each comparison the same superscript represents that the correlations are not significantly different whereas different superscripts refer to a significant p 05 difference between the correlations 8We could not include a combination of hightech vs lowtech industries with types of NPD performance in this scenario analysis because of the scarcity of related correlations Customer Participation in New Product Development 57 new product financial performance than involving cus tomers in the development stage but the former has a smaller effect on new product innovativeness than the latter To elaborate more on this issue we conducted a meta analytic path analysis for the structural model in Figure 3 We first constructed a metaanalytic correlation matrix in Table 4 by computing mean correlations for each pair of constructs in the model We then fixed error terms at zero and used the harmonic mean N 728 of the correlations total sample sizes as the sample size for model estimation Rubera and Kirca 2012 Overall the proposed metaanalytic model9 in Figure 3 provides a good fit to the data c2 239 df 1 p 10 comparative fit index 100 TuckerLewis index 96 root mean square error of approximation 04 Notably involving customers in the early ideation stage enhances new product financial performance directly g 20 p 01 and indirectly through acceleration of speed to market indirect effect 08 p 01 Yet as the mixed arguments about customer contribution to new product innovativeness dem onstrate engaging customers in ideation does not improve new product innovativeness g 01 p 10 The total effect of customer participation in ideation on new product financial performance is 27 p 01 In sharp contrast customer participation in the devel opment stage slows down speed to market g 11 p 05 and in turn damages new product financial performance as a result of the delayed cycle time indirect effect 04 p 05 Involving customers in this phase also hurts new product financial performance directly at the 10 significance level FIGURE 3 MetaAnalytic Path Analysis for NPD Stages Customer Participation in the Ideation Stage Customer Participation in the Development Stage Customer Participation in the Launch Stage New Product Innovativeness Speed to Market New Product Financial Performance 20 08 10 33 02 01 23 11 03 37 28 R2 128 R2 137 R2 206 p 1 p 05 p 01 Notes c2 239 df 1 p 10 comparative fit index 100 TuckerLewis index 96 root mean square error of approximation 04 The figure reports standardized estimates and Rsquares for each dependent variable 9We compared the model fits of several alternative models with ours The comparison results confirm that our proposed model indicates better fit 58 Journal of Marketing January 2016 g 08 p 10 and does not contribute to new product innovativeness g 03 p 10 The total effect of cus tomer participation in the development stage on new product financial performance is negative total effect 12 p 05 Finally customer input in the launch phase enhances new product financial performance directly g 10 p 05 and indirectly through speed to market indirect effect 09 p 01 The total effect of customer participation in the launch stage is 20 p 01 Discussion and Implications Theoretical Implications Table 5 provides an overview of our key findings and implications First we provide a systematic conceptual and empirical integration on when customer participation generates more or less NPD performance using a knowl edge management perspective Our study directly addresses Chatterji and Fabrizios 2014 p 1428 observation that we lack theory and systematic empirical evidence about the conditions under which sourcing external knowledge from users will be most beneficial for a firm As the first comprehensive investigation we identify four potential contingency factors in the customer participationNPD performance link and empirically validate the moderating effects of contextual factors through a metaanalysis These advance our understanding of the conditions under which customer participation can be a viable strategy and form a foundation for further research Second our metaanalytic path analysis clarifies both the distinct value of customer participation across NPD stages and the mechanism by which customer participation in each stage leads to new product financial performance The differential effect in each stage that we identified is in line with Gruner and Homburgs 2000 finding thereby reinforcing the importance of NPD stagespecific analysis Beyond their finding however we shed new light on the mechanisms by which customer participation in each stage enhances or deteriorates new product financial performance In particular the discovery of a critical mediating role of speed to market is noteworthy In light of the increased rate at which technology and consumer tastes are evolving delayed time to market with the consequent missed opportunities is the top risk to current NPD managers Product Development Man agement Association 2013 Thus our finding of the mediating route suggests that firms can use customer participation in the ideation and launch stages as an effective way to expedite the NPD process which in turn leads to NPD success However our results did not provide support for the mediating role of product innovativeness in the customer participationnew product financial performance association which has been long debated in the innovation literature Christensen 1997 Poetz and Schreier 2012 The absence of a mediating mechanism through product innovativeness pre vents us from arriving at a conclusion about Christensens 1997 claim that listening carefully to customers leads suc cessful firms to put too much emphasis on current customers needs in existing markets which makes the firms more likely to develop incremental innovations and eventually lose new opportunities in emerging markets The nonsignificant finding may suggest that while Christensens argument is still relevant in certain contexts as Figure 2 Panel B shows in other situations customers may become better knowledge providers of their current and future needs and help expand the scope of information search beyond a firms existing markets Rubera Chandrasekaran and Ordanini 2015 Finally our metaanalysis adds unique insights to extant literature that has emphasized the role of customer partic ipation in hightech industries Von Hippels 1986 lead user methods and use of open innovation as a general term for obtaining external knowledge have been regarded as relevant primarily to hightech industries Chesbrough and Crowther 2006 Herstatt and Von Hippel 1992 However our finding supports the notion that customer participation in lowtech industries yields greater returns on NPD per formance than in hightech industries The key logic behind advocating the leaduser method in hightech industries is that firms knowledge acquisition of novel and diverse technical inputs from lead users helps the firms broaden TABLE 4 MetaAnalytic Correlations for NPD Stages 1 2 3 4 5 1 Customer participation in the ideation stage 1 2 Customer participation in the development stage 700 6 806 1 3 Customer participation in the launch stage 518 4 484 603 4 484 1 4 Product innovativeness 178 10 1578 197 6 900 357 6 1041 1 5 Speed to market 296 4 511 217 3 297 333 5 590 169 5 600 1 6 NPD financial performance 290 13 1895 189 6 917 268 9 1173 132 9 1282 409 8 1715 p 05 p 01 Notes The first entry in each cell is the mean correlation for that pair of variables Entries in parentheses are the number of estimates and observations total sample sizes from which the mean correlations were derived Because these correlations are based on specific subsets combinations of our meta database the number of estimates and the total sample sizes are relatively small Customer Participation in New Product Development 59 their knowledge base and develop innovative radical products that are crucial to the success of hightech industries Von Hippel 1986 In contrast our ratio nale for greater benefits in lowtech industries places more emphasis on knowledge integration and utilization than on knowledge acquisition Even though customers provide novel and valuable knowledge the difficulty of transferring integrating and utilizing the knowledge in hightech industries inhibits firms from fully capturing the value of customer knowledge Thus contrary to prior research our results do not negate the value of acquiring novel customer knowledge in hightech industries but highlight the efficacy of knowledge integration and the utilization process in these industries TABLE 5 Key Findings and Implications from Analyses Contingency Variables Key Results Implications NPD stage Customer participation in the ideation and launch stages improves new product financial performance directly as well as indirectly through acceleration of time to market whereas involving customers in the development phase delays time to market and in turn deteriorates new product financial performance We advise managers and academics alike to consider the NPD stage when implementing a customer participation strategy in NPD In particular in contexts in which the market is rapidly changing and interdependency among a products parts is critical engaging customers in the development stage should be avoided because it can significantly delay time to market and cause firms to miss market opportunities Technological turbulence of NPD projects As technological turbulence of an NPD project increases customer participation is more strongly related to NPD performance Degree of technological turbulence can vary across NPD projects within a firm Thus a firm may be better off by solving its technologically turbulent NPD projects using an open approach with customers and managing its technologically stable NPD projects using a closed traditional innovation approach Hightech versus lowtech industries The returns of customer participation on NPD performance are greater in lowtech industries than in hightech industries Extant literature has emphasized the relevancy of involving customers primarily in hightech industries because such industries gain the benefits of new knowledge acquisition from customers However our findings imply that on average customer participation could be a more effective strategy in lowtech industries because of the ease of knowledge integration and utilization in lowtech industries Emerging versus developed countries In emerging countries customer participation is more strongly associated with combined NPD performance than in developed countries In relation to different types of NPD performance the benefits of customer participation in emerging countries on speed to market and new product financial performance are significantly greater than those in developed markets In contrast involving customers in emerging countries produces a significantly smaller effect on new product innovativeness Customer participation in emerging countries may be an underutilized opportunity that can work as a source of competitive advantage rather than as a cost of competing However managers need to recognize tradeoffs among different types of NPD performance when involving customers in emerging countries Business customers versus consumers Overall involvement of business customers yields notably greater benefits than engaging consumers in NPD With regard to different types of NPD performance business customers generate significantly greater impact on speed to market and new product financial performance than consumers whereas the effect of business customers on new product innovativeness is significantly smaller than that of consumers The findings support the notion that business customers with more relevant knowledge and high motivation to share that knowledge could contribute more to NPD performance than consumers However managers should be attentive to business customers disadvantage in bringing novel ideas into NPD as a result of their strategic consideration and convergent thinking style Small versus large firms The effect of customer participation for small firms is significantly greater than for large firms Small firms with high motivation to acquire and apply knowledge from customers can utilize customer participation in NPD as a complementary strategy to make up for their lack of resources relative to large firms 60 Journal of Marketing January 2016 Managerial Implications First our empirical synthesis helps firms assess whether customer participation is a viable strategy for them Our findings suggest that small firms in lowtech B2B industries and in emerging countries should actively consider involving customers in NPD As customer participation gains popu larity Cui and Wu 2015 many firms may jump on the bandwagon without assessing whether engaging customers is suitable for them Our results offer initial advice to firms that face the decision of whether to adopt customer participation Despite the value of customer input customer participation may not be an imperative for every firm in every industry In practice industry differences in adoption rates of customer participation are manifest Etgar 2008 For example users develop 77 of innovations in the field of scientific instruments and 67 of innovations in semi conductors and printed circuit board processing whereas only 10 of innovations in engineering plastics are co developed with customers Von Hippel 1988 It is not clear whether the low adoption rate in some industries means that the value of engaging customers is small or just that customer participation is in its infancy in these industries Our meta analysis helps firms in industries with low adoption rates to evaluate whether they have the potential to effectively utilize customer participation and therefore should embrace it quickly Second the metaanalytic path analysis provides specific guidance as to which NPD stage firms should consider engaging or avoiding customer participation According to our findings NPD managers are well advised to actively engage customers in the early or late NPD stages to accelerate the project and improve productmarket fit However firms in the industries examined in our meta analysis and in contexts in which the interdependency among the parts of a product is critical should be wary about the practice of engaging customers in the devel opment phase This is an imperative implication because in practice customers are frequently involved in the development stages of those industries In contrast to the industry routine NPD managers need to acknowledge the danger of delaying the project through customer par ticipation in the development stage Third these results inform NPD managers of how to obtain greater benefits from customer participation in technologically turbulent NPD projects in contrast with previous conflicting arguments and nonsignificant empirical effects eg Souder Sherman and DaviesCooper 1998 This NPD projectspecific exploration suggests that a firm may be better off by strategically selecting which of the firms NPD projects should be solved using an open approach with customers and which should be managed using a more closed traditional innovation approach We advise NPD managers who have repetitively applied the same approach to all projects to first gauge the characteristics of the NPD project at hand including technological turbulence and decide whether to adopt customer participation for the given project Fourth the result that small firms and business customers with high motivation to acquire or transfer knowledge gain more benefits implies that firms toplevel managers should pay more attention to how to motivate customers and NPD employees for fruitful customer participation Researchers have recently emphasized how challenging it is to encourage NPD employees to proactively utilize customer participation given their skepticism substantial level of stress and dis satisfaction from involving customers in the NPD process Chan Yim and Lam 2010 Finally our results also imply that customer partic ipation in emerging countries may be an underutilized opportunity This is in line with Zou Chen and Ghauris 2010 finding that in China partnering with external knowledge sources plays a more critical role in generating a firms competitive advantage than does an internal inno vation strategy In emerging countries customer partic ipation is less common even in the promising industries in which customer participation could be a valuable strategy Thus for firms in emerging countries it is unlikely that cus tomer participation will become simply the cost of competing rather than a source of competitive advantage Consequently involving customers in emerging countries is more likely to improve the shortterm outcomes of an NPD project and create a longterm competitive advantage Limitations and Future Research Directions This article has some limitations that future researchers can address First our study focuses on the moderating effects of contextual factors in the customer participationNPD per formance link Although our findings offer initial insights about the industries and NPD projects in which customer participation could be better suited future researchers should thoroughly examine how other contingency factors identified in Theme 1 of the Web Appendix independently or jointly influence the effectiveness of customer partic ipation Future inquiry on the individual and combined effects of these contingency factors would help give a more complete understanding of the conditions under which customer participation is a beneficial strategy In particular it would be worth investigating the combined moderating effects of contextual and customer participation design factors to guide firms on how best to design platforms for customer participation in a given context Theme 5 of the Web Appendix lists some example questions related to the joint impact of contextual and customer participation design factors Second despite an extensive literature search the studies in our data set predominantly come from specific industries such as software development and computer and electronic product manufacturing which makes it difficult to apply our results directly to other industries More research is needed to test the moderating effects of contextual factors in the customer participationNPD performance relationship in other contexts 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