organizational integration for product development

Decision SciencesVolume 41 Number 1February 2010

C© 2010, The AuthorJournal compilation C© 2010, Decision Sciences Institute

Organizational Integration for ProductDevelopment: The Effects on Glitches,On-Time Execution of Engineering ChangeOrders, and Market Success

Xenophon A. Koufteros†Mays Business School, Texas A & M University, 320 Wehner Building, 4217, College Station,TX 77843-4217, e-mail: [email protected]

Greg E. Rawski1800 Lincoln Avenue, Room 122, Schroeder Family School of Business AdministrationBuilding, University of Evansville, Evansville, IN 47722, e-mail: [email protected]

Rauniar RupakDepartment of Management and Marketing, Cameron School of Business, University of St.Thomas, 3800 Montrose Blvd, Houston, TX 77006, e-mail: [email protected]

ABSTRACT

Deviations from requirements during the product development process can be consid-ered as glitches. Fixing glitches, or problems, during the product development processconsumes valuable resources, which may adversely affect product development timeand hamper the firm’s goal to pursue a first-mover advantage. It is posited that an in-tegrated organizational response can diminish incidences of glitches and improve theability of the firm to respond to engineering changes, subsequently leading to improvedmarket success. This organizational response frequently includes heavyweight prod-uct development managers who are seen as essential catalysts for internal integration.Though internal integration is vital, it is equally important to integrate with customersand suppliers alike because such network partners can provide access to information,knowledge, and unique and complementary resources that are otherwise unavailable tothe firm. Findings, which are based on a sample of 191 product development projects inthe automotive industry, suggest that some integration routines have a positive impacton product development outcomes and market success, while other routines can in facthamper the collective effort.

Subject Areas: Customer Integration, Market Success, Organizational Inte-gration, Product Development, Product Glitches, Structural Equation Mod-eling, and Supplier Integration.

†Corresponding author.

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50 Organizational Integration for Product Development

INTRODUCTION

Customers demand powerful products that are simple and easy to use. Designingand building such products is not an easy task. Consider the new Boeing 787Dreamliner, which largely relies on composite materials (Manning, 2007; West,2007). The challenge is not only to design the product, but also to develop newprocesses to fabricate it. Realizing the uncertainty and complexity of such anundertaking, Boeing has outsourced 70% of the 787 work to almost 50 partnersand top-tier suppliers (Manning, 2007). These suppliers are located at 135 sites onfour continents. Some suppliers participate in product development by taking on theproduct engineering of parts or whole subassemblies. Such suppliers are assuminga sizable risk as they are solely responsible for designing and building entiresections or components for the plane. Boeing also relies on its customers for ideasand input. Though the integration of suppliers and customers had been promising,the experience of Boeing with this project has not been very encouraging.

Several glitches, including fuselage sections not fitting together, have sur-faced and are spelling disaster for Boeing. Glitches and subsequent engineeringchange orders (ECOs) are causing expensive delays, further damaging Boeing’sreputation and credibility. Boeing expected a $2.5 billion hit in 2008 to covercustomer late fees and increased costs to keep its suppliers on track (West, 2007).Glitches and ECOs can impact market success and potentially affect firm perfor-mance. Thus, identifying organizational routines that can both reduce the numberof glitches and improve responsiveness when they do occur is critical.

Hoopes and Postrel (1999) argue that glitches and inefficient execution ofECOs are directly caused by a lack of shared interfunctional or interspecialtyknowledge. Dealing with complex tasks requires the efficient acquisition, pro-cessing, and sharing of information and tacit knowledge and the mobilization ofcomplementary resources afforded through relationships with network partners.Organizational integration can prove to be invaluable in this respect. The prac-titioner literature and anecdotal evidence suggest that integration, internal andexternal, can be quite effective in reducing the number of glitches and in improv-ing responsiveness to ECOs. There is a gap, however, in the empirical literaturedemonstrating such effects. The literature describing relationships between prod-uct development routines and glitches is rather scant but the importance of studyingorganizational routines and their effect on glitches cannot be underestimated. Afterall, people and firms appear to learn more from their mistakes and failures thanfrom their successes and triumphs (Popper, 1963). The need to empirically testwhether organizational integration can affect incidences of glitches and timelinessin executing ECOs is urgent.

This article makes several significant and unique contributions to theory de-velopment and testing. Although the front portion of the proposed research frame-work relies on a prior model (i.e., Koufteros, Vonderembse, & Jayaram, 2005), theend portion is very different. The front portion in Koufteros et al. (2005) describesrelationships between internal and external integration practices or routines whilethe end portion relates these integration practices/routines to product innovation,quality, and, ultimately, profitability. In contrast, the end portion in this articleincludes variables such as glitches and on-time execution of engineering changes.

Koufteros, Rawski, and Rupak 51

These latter product development outcomes are more proximal to integration prac-tices and thus reflect a more immediate impact of integration practices/routines.Moreover, Koufteros et al. (2005) and Koufteros, Cheng, and Lai (2007) relatedproduct development integration routines and practices to outcomes that connotesuccess (i.e., product innovation and quality). On the other hand, this article relatesintegration practices to outcomes that primarily signify failure: glitches and ECOs.It is well established in the literature that the factors that lead to success maynot always be the same factors that lead to failure. This is an empirical questionthat is addressed here. Also, building a sound theoretical framework requires thatresearchers test and retest a given framework. The front portion of the Koufteroset al. (2005) model is essentially retested here with a new sample where the unitof analysis is the project rather than the firm.

A sizable portion of the academic and practitioner literature is examining andaddressing the more visible product development practices and routines of fairlylarge final assemblers such as name brand auto manufacturers (e.g., General Mo-tors, Ford, Toyota, BMW). Little is known about how the suppliers of these finalassemblers cope with the task of developing parts or subassemblies. Do they inte-grate their suppliers in product development through supplier product or processintegration? How about integrating with their customers? How is the integrationof suppliers or customers working out in terms of reducing the number of glitchesor being able to execute ECOs on time? What has been the effect on market suc-cess? These are important research questions that this study addresses. The focusis on suppliers in the automotive industry and their respective relationships withcustomers and lower-tier suppliers.

Some of the most salient integration routines reported in the literature (Clark,Chew, & Fujimoto, 1987; Brown & Eisenhardt, 1995) and their effects are exam-ined in this article. Routines such as the use of heavyweight product developmentmanagers, internal integration, supplier product integration, supplier process inte-gration, and customer integration are posited to affect incidences of glitches andthe on-time execution of ECOs. In turn, the latter are hypothesized to affect marketsuccess. The next section of the article begins with a brief discussion of the con-cept of integration and is followed by the presentation of the research hypothesesrelating organizational routines with product development process outcomes andsubsequently with market success. A section on research design and methods ap-pears next, followed by the presentation of the research findings. The last sectionprovides a summary of the findings along with a discussion and directions forfuture research and implications for practitioners.

LITERATURE REVIEW AND THEORY DEVELOPMENT

Eisenhardt and Martin (2000) posit that each resource, no matter how valuableit may be, can rarely stand on its own. It is rather the integration of resourcesthat can lead to sustained advantage. As Schreyogg and Kliesch-Eberl (2007)put it, capabilities can be “conceptualized in the context of collective organi-zational problem-solving” (p. 915). In the strategy literature, the roots of inte-gration can be traced to Fayol’s (1949) notions of cooperation and coordinationand to Lawrence and Lorsch’s (1967) concept of unity of effort among systems.


Historically, integration meant the coordination of activities or the managementof their dependencies (Glouberman & Mintzberg, 2001). However, the concept ofintegration was reserved for internal cooperation and coordination as firms used tobe vastly more vertically integrated than they are today. The reality of integrationnowadays is very different as firms depend on external network partners for ideas,information, knowledge, complementary resources, or even complete design andmanufacturing solutions. Barki and Pinsonneault (2005) state that organizationalintegration “essentially represents a structural and relational characteristic of agiven organization or between organizations” (p. 167). As illustrated by the workof Clark et al. (1987), such a network can include suppliers, manufacturers, andcustomers. Coinciding with Barki and Pinsonneault’s (2005) perspective, Bagchiand Skjoett-Larsen (2002) suggest that organizational integration paves the wayfor distinct actors in the network to behave like a unified entity.

Integration in Product Development

While the body of literature in product development is quite diverse, Brown andEisenhardt (1995) impart a rather useful review of the vast literature and pro-vide directions for future research. They also identify three streams of researchthat adequately cover the domain of product development routines: (i) productdevelopment as a rational plan, (ii) communication web, and (iii) disciplined prob-lem solving. While not diminishing the importance of the communication stream,Brown and Eisenhardt advance a model that includes primarily elements from therational and disciplined problem-solving streams. They articulate a model depict-ing internal and external factors as important contributors to product developmentperformance. Specifically, the model includes internal factors such as those relatedto a cross-functional team with its composition (various functional specializations)and organization of teamwork (i.e., early involvement, planning, and overlapping)as well as project leadership exemplified through the appointment of heavyweightproduct development managers. Relying on the earlier findings of Clark et al.(1987), Brown and Eisenhardt’s model also includes external factors that are vitalfor organizational integration to come to full fruition. Integrating with both cus-tomers and suppliers goes beyond just maintaining good relationships with externalconstituents.

While the Brown and Eisenhardt (1995) model is useful in identifying someof the most salient routines that can impact product development outcomes, it doesnot account for all the interrelationships between product development routines.The literature has moved forward and specified and tested more complex modelsthat relate such routines. For example, Koufteros et al. (2005) examine the re-lationships between internal and external integration constructs while Koufteros,Vonderembse, and Doll (2002) and Koufteros and Marcoulides (2006) examinethe impact of heavyweight product development managers on internal integration.Such advancements in the literature ought to be considered in positing a morecomprehensive framework that relates product development routines and relevantoutcomes.

Figure 1 shows a framework that describes the relationships between organi-zational routines and outcomes. This framework first relates heavyweight product


Figure 1: Research framework.

HeavyweightProduct

DevelopmentManager

H2a

H1 InternalIntegration

CustomerIntegration

Supplier ProductIntegration

Supplier ProcessIntegration

Glitches

On-timeExecution

of EngineeringChanges

MarketSuccess

H2b

H2c

H3a

H3b

H3c

H 4b

H4a

H4b

H5a

H5b

H7

H6

development managers with internal integration (cross-functional integration) andis consistent with Koufteros et al. (2002) who found empirical support for sucha relationship. Internal integration is subsequently related to external integra-tion, operationalized through both supplier integration and customer integration(Koufteros et al., 2002). Supplier integration is further split into two constructs,namely supplier product integration and supplier process integration, adhering toprior research such as Petersen, Handfield, and Ragatz (2003), Koufteros et al.(2005), and Koufteros et al. (2007). Supplier product integration refers to an or-ganizational routine that charges suppliers with the responsibility of developingcomponents or even entire subassemblies for their customers. On the other hand,supplier process integration can be described as a routine that involves suppli-ers during the product development process undertaken by their customers. Priorresearch also postulated and found support for a relationship between supplierproduct integration and supplier process integration. Thus, a path that relates thetwo constructs is specified. Supplier product integration along with supplier pro-cess integration and customer integration are then hypothesized to impact glitchesand on-time execution of ECOs. Finally, the latter are posited to affect market suc-cess. A discussion of each variable in the model along with theoretical argumentsdescribing each hypothesis follows.

Heavyweight product development managers

Clark and Fujimoto (1992) pioneered the concept of the “heavyweight manager”and “heavyweight teams” through their numerous articles but also launched thedebate regarding the virtues of external integration. Cross-functional teams areled by a product development manager who is typically a senior manager withinthe organization and who has the expertise but also the organizational clout tochampion the product development effort. Clark and Fujimoto (1992) highlight five


roles that typify heavyweight managers. Heavyweight managers directly interactwith the market and customers and interpret the environment. They also speakmultiple languages, those of customers, suppliers, engineers, marketers, and stylistsso they can translate requirements between various constituents. They assume therole of chief engineer, translating top management vision into tangible blueprints.Beyond being direct engineering managers, heavyweight managers are programmanagers that constantly communicate with others and act as conflict-resolutionmanagers. Finally, they coordinate the details and attempt to create harmony.Collectively, heavyweight managers are agents of integration (Daft & Lengel,1986). A heavyweight manager is the glue that makes organizational integrationfor product development a reality.

Heavyweight product development managers can help the team members ac-quire environmental information, exchange views, interpret the task environment,resolve cross-functional conflicts, and reach a mutual understanding of the productdevelopment tasks (Koufteros, Vonderembse, & Doll, 2001, 2002). Recent empir-ical evidence (Koufteros et al., 2002; Koufteros & Marcoulides, 2006) suggeststhat heavyweight product development managers are instrumental for integrationto materialize.

H1: The presence of heavyweight product development managers is positivelyassociated with internal integration.

Internal integration

Integration, whether internal or external, does not materialize by accident. It isa rather purposeful activity that requires constant maintenance and commitment.Hoopes and Postrel (1999) believe that organizational integration generates muchof its beneficial effect by reducing the incidence and severity of knowledge prob-lems, which are magnified in the presence of environmental uncertainty and equiv-ocality (Koufteros et al., 2005). Integration enables patterns of shared knowledgeto develop across the various specialties and constituencies when developing newproducts. The shared aspect of knowledge is critical because “any purely individualcapability can be bid away by rivals, dissipating most of the rents generated bythe individual’s know how, and because joint problem-solving activities requireindividuals to understand the effect of their choices on others’ tasks” (Hoopes &Postrel, 1999, p. 838). This can be immensely useful in reducing incidences ofglitches and the time to process engineering changes. Integrating mechanisms suchas the formation of cross-functional teams that work jointly on product develop-ment projects from the onset may also improve product development performance,and reduce incidences of glitches in particular, by improving cooperation andcoordination of activities.

Early release of information allows engineers to begin working on differentphases of the problem while final designs are evolving. The early release of infor-mation reduces uncertainty and promotes the early detection of potential glitches,which enables firms to avoid time-consuming changes later. Cross-functional teamsprovide an avenue for constituents to express concerns, a mechanism for captur-ing learning, and an opportunity to reduce equivocality. A cross-functional teambrings together a carefully selected array of specialists who share information


and knowledge and make product, process, and manufacturing decisions jointlyand simultaneously. Early involvement empowers downstream participants in thesense that they have a say before decisions are finalized. This helps to achievecommitment and clarify product requirements before too much time and moneyhave been invested and opinions have been formed (Gupta & Wilemon, 1990).

Just as internal integration may be abundantly useful for product developmentsuccess, external integration may prove to be a more critical asset as more and morefirms are outsourcing product development activities to suppliers and customers areincreasingly demanding higher-quality products. Faems, Van Looy, and Debackere(2005) state that interorganizational collaboration might stimulate the transfer ofcodified and tacit knowledge (Eisenhardt & Schoonhoven, 1996; Ahuja, 2000) butalso marshal the mobilization of assets that are otherwise unavailable to a firm. AsHagedoorn (2002) notes, collaboration and coordination can reduce the risks whilecosts are spread among a variety of constituents (Knudsen, 2007). Knudsen (2007)suggests that one strong motivation for interfirm relationships is the internal needfor renewing the knowledge base through knowledge creation and learning (Child& Faulner, 1998).

Koufteros et al. (2007) explain the motivation for external integration inproduct development through the social network theory lenses. Based on Burt’s(1992) work, they state that the efficacy of network partners to absorb, sift through,and classify new developments is unmatched by the capabilities of a single firm.Kijkuit (2007) also notes that relationships between network members can leadto more accurate and reliable information, the development of shared language,increased absorptive capacity, and a higher speed of information transfer. Networkactors can cross-validate information from multiple sources by consulting thirdparties and this may result in more accurate and reliable information. This leads toa reduction of glitches and their severity and to a more efficient response to ECOsthat emerge on the aftermath of glitches. Relying on the multiple-lens hypothesis,receiving diverse criticism can allow actors to anticipate a variety of contingencies.In addition, network actors can pull the absorptive capacity of other members inorder to better understand the environment and the challenges it presents. Networkactors also develop shared language and routines, which enables the recognitionand transfer of knowledge. Because of direct contacts with other actors, the averagepath length is shortened, leading to higher speeds of information transfer andbetter timing, which is especially critical for reducing the number of glitches andimproving response time (Kijkuit, 2007).

Based on the discussion above, internal constituents stand to benefit fromintegrating with customers and suppliers. They recognize that the logic that drivesinternal integration is equally relevant for external integration. Koufteros et al.(2005) posited and subsequently tested a hypothesis that relates internal and ex-ternal integration in product development. Based on responses from 244 manu-facturing firms, they show that internal integration can drive external integration.Results indicate that internal integration had a strong impact on customer inte-gration, supplier product integration, and supplier process integration, though theeffects on customer integration were the strongest. Given the strong motivation toengage customers and suppliers in the product development effort, it is assertedhere that internal integration will drive higher levels of external integration.


H2a: Internal integration is positively associated with customer integration.

H2b: Internal integration is positively associated with supplier product inte-gration.

H2c: Internal integration is positively associated with supplier process integra-tion.

Customer integration

The integration of customers emerged as an important factor in the tradition of arational plan while the integration of suppliers appears to be a significant factor inboth the rational as well as disciplined problem-solving streams (Brown & Eisen-hardt, 1995). Developing a product that does not match customer requirementscan be problematic at best. Given the resources and time that are expended towarda new product development project, presenting the product to customers in thelatter phases of the effort can be devastating. Stump, Athaide, and Joshi (2002)suggest that customer involvement includes obtaining reactions to the product de-sign and securing “ . . . feedback on desirable product modifications and alternativeapplications . . . ” (p. 443). Customers can evaluate the product’s interface with ex-isting operations and feedback can benefit supplying firms because such feedback“ . . . alerts sellers to buyers’ perceptions of salient product attributes and reducesmarket uncertainty . . . ” (p. 444).

Customers have a vested interest in product development. Being integratedwith their suppliers ensures that their voice will be heard and their recommenda-tions and suggestions will be incorporated in the design of new products. Integrativeactivities can generate shared knowledge, a firsthand understanding of customerrequirements, cooperation in solving potential problems, and coordination of ac-tivities that are expected to reduce instances of glitches. Customers can addresspotential failures in meeting requirements because of the early and direct releaseof information during the upstream, midstream, and downstream product devel-opment processes. Information about product attributes, product quality, productcosting, and lead time can be shared. Joint problem-solving routines can expeditethe processing of ECOs when they emerge. As noted earlier, direct contact enablesmore accurate and timely information transfer. Thus, it is expected that integrationwith customers will reduce incidences of glitches, improve the capability of theorganization to respond to ECOs, and ultimately impact market success.

H3a: Customer integration is negatively associated with incidences of glitches.

H3b: Customer integration is positively associated with on-time execution ofECOs.

H3c: Customer integration is positively associated with market success.

Supplier integration

Supplier integration in product development may be manifested via three basicmodes, which are commensurable with the degree of supplier participation inengineering work. Some parts (i.e., “white-box” parts) are detail-controlled partsand are developed entirely by customers (i.e., firms higher in the chain), from


basic to detail engineering. White-box parts are characterized by the absence ofsupplier participation. Essentially, the first mode of supplier integration in productdevelopment is in fact supplier nonintegration. Given that less than a handful offirms in our sample reported using a white-box approach to product design, thefocus is turned to the other two basic approaches to supplier integration, namely,supplier product integration and supplier process integration.

Supplier product integration suggests that the supplier assumes full respon-sibility for developing a given component, part, or subassembly. This is analogousto developing “black-box” parts. In other words, the supplier is solely responsiblefor the product engineering. The customer may provide performance specificationsand input, but the basic and detailed engineering is undertaken by the supplier. Thesupplier is held accountable for cost control, quality, and performance. The moti-vation behind this practice is to capitalize on the know-how of the supplier, but alsoto gain engineering capacity and talent that is not available within the company.Tasks can also be processed in parallel (and thus the overall processing time willbe faster) instead of sequentially, as distinct suppliers can work on different taskssimultaneously.

If a customer is integrating suppliers in order to have them develop parts orsubassemblies on a black-box basis, it is reasonable to assume that product devel-opment competency ought to be weighted heavily during supplier selection delib-erations. Under the assumption that suppliers are selected based on their expertise,technical know-how, and product development capability at large (Narasimhan& Das, 1999; Petersen et al., 2003; Koufteros et al., 2007), instances of glitchesshould be minimized. Such suppliers should be able to minimize deviations fromexpectations and be able to rectify glitches effectively once they occur.

In between supplier nonintegration and supplier product integration standssupplier process integration. Essentially, with supplier process integration the sup-plier participates in product development activities alongside its customer. Thesupplier is providing input and expertise, often starting at the early stages of theproduct development process. This may be necessary for several reasons. Sup-pliers may possess unique technical knowledge that is vital for the integrity ofa new product development project. Suppliers may participate in this effort inorder to understand how the part they manufacture may interact or fit with otherparts being developed by other relevant constituents. Suppliers may also providecost information that may be invaluable in determining whether the project willbe profitable or not. As the design of any given product undergoes several itera-tions and alterations, internal and external partners need to be informed of all thechanges in order to assure constancy of purpose among all constituents. Productattributes such as specifications, durability, costing, lead time and market introduc-tion, manufacturability, and ease of assembly can be discussed and resolved withsuppliers. This direct communication and participation can lead to a reduction inthe number of glitches and the development of the requisite competency to handleECOs efficiently.

Though supplier product integration and supplier process integration canstand on their own, some suppliers end up getting assimilated via both integra-tion modes and this occurs for two important reasons. Suppliers and customers


that integrate through supplier product integration need to reduce uncertainty andequivocality and might find solace through supplier process integration.

Supplier product integration implies an unparallel level of trust of the sup-plier product development capabilities. The supplier is trusted to develop a partor a subassembly by relying on minimal specifications, which are often based oncustomer performance parameters. Under such circumstances, suppliers may beexperiencing intense levels of uncertainty and equivocality. Frequently, the sup-plier, and even the customer, does not know exactly what the part should look likeor what changes may be forthcoming. Galbraith (1977) defines uncertainty as thedifference between the amount of information required to perform a task and theamount of information possessed by the organization. Firms react to the perceivedlevel of environmental uncertainty by gathering or seeking more information tohandle environmental permutations. Tatikonda and Rosenthal (2000) suggest that,overall, “tasks having higher uncertainty require greater information processingduring the execution of the task than tasks having lower uncertainty” (p. 408). Daftand Lengel (1986) suggest that specific organizational routines can provide addi-tional data gathering that can be used to cope with uncertainty. One such routineincludes the participation of suppliers in product development teams assembledby customers to help them carry out product development projects. Such partici-pation affords obtaining firsthand and timely information about the project and itsdirection. Such participation can commence early in order to avoid expensive andtime-consuming ECOs.

Equivocality means ambiguity, the existence of multiple and conflicting inter-pretations about an organization’s situation. High equivocality implies confusionand lack of understanding. Equivocality is portrayed as being similar to uncertaintybut equivocality “presumes a messy, unclear field where an information stimulusmay have several interpretations” (Daft & Lengel, 1986, p. 554). Even with infor-mation at their disposal, constituents find it difficult to cope with ambiguity dueto the complex nature of the task at hand. With respect to reducing equivocality,structural mechanisms have to enable debate, clarification, and enactment ratherthan simply providing large amounts of data (Daft & Lengel, 1986). Daft andLengel indicate, “ . . . the key factor in equivocality reduction is the extent to whichstructural mechanisms facilitate the processing of rich information” (p. 559). Richmedia are typically personal and involve face-to-face contact. Such media includethe use of teams where members can converse on the meaning of equivocal cues. Inaddition, a team approach enables rich communication, which can be used for dif-ficult and equivocal issues. Suppliers will find it useful to participate in the productdevelopment team assembled by the customer in order to seek clarifications andascertain the meaning of different information stimuli, thus reducing equivocality.

Because supplier product integration is frequently accompanied by sub-stantive uncertainty and equivocality, it is expected that suppliers and respectivecustomers will seek approaches to deal with these environmental challenges. Oneconstructive approach is for such suppliers to become involved early in the prod-uct development process where they can receive timely information that can helpthem reduce uncertainty. In addition, their involvement in the product developmentprocess presents them with the opportunity to engage in rich discussions and de-bates with other constituents in order to explicate the meaning of information and


cope with complexity. Although supplier product integration and supplier processintegration can stand alone, it is posited that supplier product integration may bemore rewarding if it is followed up by supplier process integration practices.

H4a: Supplier product integration is positively associated with supplier processintegration.

H4b: Supplier product integration is negatively associated with glitches.

H4c: Supplier product integration is positively associated with on-time execu-tion of ECOs.

H5a: Supplier process integration is negatively associated with glitches.

H5b: Supplier process integration is positively associated with on-time execu-tion of ECOs.

Glitches and ECOs

Early visibility of potential changes is necessary in order to create products thatmeet customer requirements. Well-designed products that are free from glitchesare easier and more economical to produce. The negative consequences of glitchesin overlapped stages are amplified when glitches go undetected until a later stageof the project. In order to fix the glitch, the product development team has to revisitvarious interdependent product development phases to investigate the plausiblecause(s) and respective effect(s). This leads to rework among several stages whilethe successive stages have to wait until the issues are addressed. From a perfor-mance perspective, a glitch translates into rework, wastage, project delays, andinefficient usage of resources including valuable engineering hours. Glitches, ifnot detected internally during product development, can also lead to poor qualityor defective products. Such glitches can propagate into losses in sales and marketshare (Hendricks & Singhal, 2003).

A product that is glitch free translates into delivering a high value to cus-tomers (Clark & Fujimoto, 1991; Clark & Wheelwright, 1993) and creates theperception of high-quality products (Clark & Wheelwright, 1992) and a percep-tion of uniqueness (Zirger & Maidique, 1990). Products designed and developedwithout glitches can improve customer satisfaction and market performance. Sat-isfied customers means lower handling cost in managing customer complaints,lower warranty costs, customer loyalty, and subsequent expansion of market share(Slater & Narver, 1995).

H6: Higher incidences of glitches are associated with lower market success.

ECO time is the time required to make changes due to glitches that may occurduring any of the stages of the product development process (Terwiesch & Loch,1999). In the presence of a glitch, the project may suffer delays in and across themultiple stages, which ultimately can impede the pursuit of first-mover advantage.In a typical business-to-business product development environment, customersmay ask for engineering changes because of unexpected glitches or componentincompatibility. Similarly, the suppliers may demand changes to improve manu-facturability or cost. Designers may also call for changes across various stages ofthe product development process in order to assure that designs are compatible


with customer requirements and with existing or newly acquired manufacturingprocess technology. Executing ECOs on time is vital as timing is of the essence inproduct development. Introducing the product in the market late is costly and canhave other serious consequences as competitors can build loyalty and switchingbarriers.

H7: On-time execution of ECOs is associated with higher market success.

RESEARCH DESIGN AND METHODS

In order to test the hypotheses, data were collected from the automotive industrybased on a survey. To gain such empirical evidence, the survey instrument wasassembled based on an extensive literature review. The instrument was assessedfor content and face validity by a group of practitioners and academics alikeand was refined through a pilot study that included responses pertaining to 34projects. Finally, measurement properties and hypotheses testing were examinedvia a sample of 191 projects and firms, respectively.

Instrument Development

To develop the measurement instrument, the extant literature on product devel-opment routines (e.g., Clark, 1989; Clark & Fujimoto, 1991; Millson, Raj, &Wilemon, 1992; Donnellon, 1993; Cooper & Kleinschmidt, 1994; Brown &Eisenhardt, 1995; Koufteros et al., 2001, 2002, 2005, 2007) was reviewed. Theitems for heavyweight product development managers, internal integration, cus-tomer integration, and supplier integration are largely adapted from the work ofKoufteros et al. (2001), (2002), and (2005). Items for product design glitches arederived from the work of Hoopes and Postrel (1999) who expended a consid-erable effort describing organizational routines that can affect glitches. Glitcheswere defined as costly mistakes; they are mistakes in the sense that requirementsfor a particular constituent group(s) are not met or satisfied. Such constituentsmay include internal as well as external actors. The items for glitches appear inRupak, Doll, Rawski, and Hong (2008) who operationalize glitches as the differ-ence between the requirements of customers, suppliers, manufacturing/assembly,and actual deliverables. The items for on-time execution of ECOs were first re-ported in Syamil, Doll, and Apigian (2004) and were based on prior literature ofECOs such as Terwiesch and Loch (1999) and Terwiesch, Loch, and de Meyer(2002). The items reflect the ability of the organization to process ECOs on time.Items for market success are adopted from a customer satisfaction scale developedin Syamil et al. (2004). This scale reflects whether customers and the market atlarge are positive about the new product. Structured interviews with two prod-uct development managers, three product development team members, and threeacademics followed the construction and assembly of the survey instrument. Thisfacilitated refinement before the instrument was subjected to a pilot study. Basedon suggestions from practitioners, two of the items from the market success scale(adopted from Syamil et al., 2004) were subsequently dropped as one of the itemsappeared confusing while the other was characterized as redundant. Item responses


were based on a five-point Likert-type scale where 1 = strongly disagree and5 = strongly agree.

The survey was then administered to members of the Society of AutomotiveEngineers (SAE). The SAE provided a mailing list of 3,200 professional memberswho are involved in product development projects and can be considered as keyinformants in this research (Kumar, Stern, & Anderson, 1993). A list of 200individuals from this SAE mailing list was generated for the purpose of a pilot study.These individuals were randomly selected based on certain key parameters suchas position title, functional affiliation, product complexity, and industry position(i.e., suppliers). Firms that responded to the pilot study were excluded from thelarge-scale study. The respondents were asked to reply to the survey based on theirexperience from the last completed product development project.

A total of 34 usable responses (17.7% response rate, 8 surveys were unde-liverable) were obtained for the pilot study. Each of the seven constructs with itsblock of items was first factor analyzed separately. Only one factor emerged foreach block of items and the loadings appeared to be reasonable. Factor extractionwas based on principal axis factoring and was accompanied by direct obliminrotations. For each construct, one clear factor emerged and the loadings were fairlysubstantive. One item from supplier process integration was dropped due to ex-tremely low loading with its respective factor. Internal consistency of the constructswas assessed through an evaluation of Cronbach’s (1951) alpha. All Cronbach’salpha values exceeded .80. Based on these findings, a large-scale administration tomembers of the SAE commenced.

Description of Sample

The survey was administered to product development professionals in two waves,placed 2 weeks apart. Out of 3,000 surveys mailed, 220 were completed andreturned. However, only 191 were usable (Table 1). Most discarded surveys wereattributed to excessive missing data. Respondents were asked to report on theirlast product development project (successful or unsuccessful) that was completedand they have actively managed. Respondents were prompted to specify the exactnature of the focal project. In other words, they had to indicate the specific system(e.g., chassis, powertrain, electronics, etc.) the project involved. To assure thatrespondents deliberated only in reference to the focal project, a reminder wasprinted on the top of every page of the survey. One response from each firm wasreceived but each respondent was specifically targeted as he/she would be a keyinformant about product development activities. It is acknowledged here that biasin data collection may stem from the use of a single informant. However, a keyinformant may be a more reliable source of information and helps to ensure thatthe respondent has the necessary knowledge to respond to the questionnaire items(Phillips & Bagozzi, 1986). To examine whether there was a response bias, themean score of each construct was compared (through t tests) between early (firstwave) and late respondents (second wave). At an alpha level of .05 there wereno statistical differences between the mean scores of early and late respondents.To assess response/nonresponse bias, a χ2 test of differences between observedand expected (population) frequencies along firm size was carried out. The χ2


Table 1: Demographics.

Number of Up to 500– 1,000– 5,000– OverEmployees: 499 999 4,999 9,999 10,000

Frequency 54 15 46 23 53Valid percent 28% 8% 24% 12% 28%

Electrical/Focal product Body Body Body ElectronicManufactured: Exterior Interior Powertrain Component Chassis Component Other

Frequency 8 27 48 17 52 17 22Valid percent 4% 14% 25% 9% 27% 9% 12%

Supplier First Second ThirdLevel Tier Tier Tier Other

Frequency 146 19 4 22Valid percent 76.4% 9.9% 2.1% 11.5%

test showed that the distribution of firm size in the sample fits very well with thedistribution of firm size in the population (p value = .17).

In order to assess whether common-method bias is present, researchers haveemployed Harmon’s one-factor test (Podsakoff & Organ, 1986). Eight factors wereextracted from all the measures in this study and in total accounted for 68.62%of the variance. The first factor accounted for 26.14% of the variance. Becausemultiple factors did emerge and the first factor did not account for most of thevariance, this suggests that common-method bias may not be an issue of greatconcern.

Respondents represented supplier firms that developed and produced diverseproducts for the automotive industry. About 28% of the respondents worked forcompanies with up to 499 employees, 8% for companies that employed 500 to999 employees, 24% for companies that had 1,000 to 4,999 employees, 12% forcompanies with 5,000 to 9,999 employees, and 27% for companies having over10,000 employees.

The great majority of projects involve first-tier suppliers of the auto industry,though some suppliers are classified as second or third tier. Some suppliers didnot report their respective tier. Responses from separate firms were solicited andthus the projects concern primarily activities of different focal suppliers of the autoindustry. Some rather large suppliers produced multiple responses (11 instances)through their various divisions. Each response was for a different project, however.Responses pertain to the last product development project that the focal supplierhas undertaken. The focal supplier may integrate its customers and/or its suppliersduring its product development effort. The customer is the firm one level abovethe focal company in the chain and a supplier refers to the firm one level belowthem in the chain. If a given focal firm that responded to this survey is a first-tiersupplier, their customer would probably be the final assembler of the automobilewhile their supplier would be a second-tier supplier.


To ascertain whether the focal company actually engaged in product develop-ment projects, a series of questions was posited pertaining to the typical nature oftheir involvement in product development. Out of 191 responding firms, only three(1.6%) indicated that “customer provides complete design, we are not involved.”Twenty nine (about 15%) of the firms reported that “customer provides concept, wedo the rest.” Seventy firms (about 37%) indicated that “customer provides criticalspecifications, we do the rest” while 41 firms (about 22%) reported that “we workwith the customer to codevelop the design.” In essence, these frequencies illustratethat the focal firms did play a significant role in product development efforts.

Research Methods—Measurement Model

Anderson and Gerbing’s (1988) two-step approach for structural equation model-ing was closely followed, which suggests that researchers should first obtain anadequate measurement model and then test the structural model in a second step. Togain an initial understanding of the data, the entire set of items across all constructswas subjected to an exploratory factor analysis using principal axis factoring andoblimin rotation, as it is expected that the factors would be correlated. Overall,there was comforting evidence for both convergent and discriminant validity.

The measurement model was then examined via confirmatory factor analytictechniques. This included the specification of a measurement model consisting ofall eight latent variables concurrently and the assessment of unidimensionality,convergent, and discriminant validity as well as composite reliability. The mea-surement model was examined via LISREL 8.51 using a covariance matrix as inputand maximum likelihood estimation. To assess convergent validity, the individualitem loadings and their respective t tests can be examined (Koufteros, 1999). Inessence, the relationship between latent and observed variables is evaluated throught tests. The hypothesized measurement model fit is assessed here through someof the most commonly used goodness-of-fit indices (Koufteros & Marcoulides,2006). In summary, to support model fit it is desirable to exhibit χ2/df <2; anAkaike’s Information Criterio (AIC) value closer to the saturated model than theindependence model; an nonnormed fit index (NNF) ≥.90 and a confirmatory fitindex (CF) ≥.90; and an root mean square error of approximation (RMSEA) below0.05 or the left endpoint of its 90% confidence interval to be markedly smallerthan 0.05 (with this interval not excessively wide) (Raykov & Marcoulides, 2000).Discriminant validity can be assessed by comparing the average variance extracted(AVE) to the squared correlation between constructs (Fornell & Larcker, 1981).Discriminant validity is supported when the AVE for each latent variable is higherthan the squared correlation between any two latent variables under consideration.Discriminant validity can also be assessed by developing a confidence interval of� ± 2σe (Marcoulides, 1998) for each pair of constructs and examining whetherthe value 1.00 is included. In other words, the confidence interval is constructedby the correlation between two constructs plus or minus twice the standard error.If 1.00 is not included, there is evidence of discriminant validity. Reliability of agiven construct within the context of structural equation modeling can be evaluatedthrough the composite reliability estimate (Koufteros, 1999).


Research Methods—Structural Model

Once a measurement model is secured, the next step is to test the substantivehypotheses. A structural model is evaluated and if the model fits the data adequately,the t values of the structural coefficients (i.e., γ and β) can be used to test theresearch hypotheses. The magnitudes of the structural coefficients as well as thestatistical significance associated with such coefficients are useful in the assessmentof potential relationships between latent variables.

RESULTS

This section begins with the assessment of the measurement model followed bythe results of testing the substantive hypotheses.

Measurement Model

The measurement model appears to be supported by various fit indices. Using max-imum likelihood estimation on the entire set of items in the model, the fit indicesalong with the t values provide evidence of convergent, as well as discriminantvalidity (Table 2). The NNFI was 0.91 and CFI was 0.92, while the χ2 per degreeof freedom was 1.44. The RMSEA was 0.048 and its 90% confidence intervalwas fairly narrow (i.e., 0.039–0.057). The model AIC (718.98) was significantlysmaller than the saturated AIC (930.00). These fit indices are indicative of a goodmodel-to-data fit. All of the items have statistically significant relationships withtheir latent factors. All factor loadings were above 0.57 and the great majority wasabove 0.70. The significance of the t values (Table 2) associated with factor-to-itemloadings exceeds the critical value at the .001 significance level (lowest t value =7.75). These results attest to the strong relationships between respective observedand latent variables and thus provide evidence of convergent validity.

Table 3 provides descriptive statistics, composite reliabilities, and correla-tions among the constructs. It turns out that internal integration and customerintegration are the two top practices while supplier product integration is the leastused practice. Table 3 also presents evidence suggestive of discriminant validity.First, none of the squared correlations exceeds the AVE of a latent variable inany comparison. The highest squared correlation was evidenced between supplierproduct integration and supplier process integration and stood at 0.35. The re-spective AVEs are 0.64 and 0.54, far exceeding the squared correlation measure.Alternatively, none of the � ± 2σe confidence intervals contained the value of1.00. The highest upper bound of a confidence interval was observed when corre-lating supplier product integration and supplier process integration. This providesfurther evidence of discriminant validity. All composite reliabilities were above.70 and coincide with the pilot study reliability assessments through Cronbach’salpha. The posited measurement model appears to be supported when scrutinizedfor model fit, unidimensionality, convergent and discriminant validity, and latentvariable composite reliability.

Structural Model

A structural model (Figure 2) was postulated here relating product developmentpractices and outcomes such as glitches, on-time execution of ECOs, and market


Table 2: Overall measurement model—exogenous and endogenous variables (n =191).

CompletelyStd. Coefficient,

Variable (t value)

Heavyweight Product Dvpl. ManagersHW1 Product development managers are given real authority

over personnel.81∗

HW2 Product development managers have enough influence tomake things happen

.78, (10.98)

HW3 Product development managers have a final say in budgetdecisions

.62, (8.49)

HW4 Product development managers have a final say inproduct design decisions

.69, (9.65)

HW5 Product development managers have a broad influenceacross the organization

.69, (9.56)

Internal IntegrationCF1 Product development team members represented a variety

of disciplines.82∗

CF2 Various disciplines were involved in product developmentfrom the early stages

.73, (10.31)

CF3 The team consisted of cross-functional members of theorganization

.78, (11.19)

CF4 The team simultaneously planned the product, process,and manufacturing activities of the project

.57, (7.75)

CF5 All necessary functions of the organization wererepresented in the project team

.70, (9.90)

Customer IntegrationCI1 We involved customers in the early stages of product

development.69∗

CI2 During the requirements definition, potential customersare involved continuously and interactively

.72, (8.50)

CI3 We visit our customers to discuss product developmentissues

.79, (9.02)

CI4 Our product development team met with customers .78, (9.06)Supplier Product Integration

SPI1 Our suppliers did the product engineering of componentparts for us

.77∗

SPI2 Our suppliers developed component parts for us .87, (11.69)SPI3 Our suppliers develop whole subassemblies for us .75, (10.32)

Supplier Process IntegrationSCI1 Our suppliers were involved in the early stages of product

development.63∗

SCI2 We made use of suppliers’ expertise in the developmentof our projects

.83, (7.91)

GlitchesDG1 The product design did not meet customer requirement(s) .71∗DG2 The product design did not meet supplier requirement(s) .75, (9.13)DG3 The product design did not meet manufacturing

requirement(s).83, (9.78)

DG4 The product did not meet assembly requirements .69, (8.48)

Continued


Table 2: (Continued)

CompletelyStd. Coefficient,

Variable (t value)

On-time Execution of Engineering Change Orders (this product development team)EC1 Finished engineering change orders on time .88∗EC2 Delivered engineering change notices on time .91, (17.84)EC3 Met engineering change deadlines regularly .90, (17.57)

Market Success (compared to the average in the industry, our product)CS1 Fit target customers better .66∗CS2 Has more loyal customers .77, (8.91)CS3 Generated more new customers .74, (8.65)CS4 Was more successful in the marketplace .85, (9.50)

Fit indices: χ2 (df) = 541.98 (377); χ2/df = 1.44; CFI = .92; NNFI/TLI = .91; RMSEA =.048; model AIC = 718.98; saturated model AIC = 930. ECO = Engineering change order.

success. Before the structural coefficients are assessed, the fit of the structuralmodel ought to be examined in order to ascertain whether the model can representthe data. The χ2 per degree of freedom was 1.61 and both NNFI and CFI are0.90 while RMSEA and its 90% confidence interval were 0.057 and 0.048–0.065,respectively. The model AIC (777.73) was significantly lower than the saturatedAIC (930.00). Overall, these fit indices are suggestive of good model fit (Table 4)thus an examination of structural coefficients and hypotheses commences.

The first hypothesis describes the relationship between heavyweight productdevelopment managers and internal integration. The t value describing the respec-tive relationship (γ = 0.29) is 4.98 and it is statistically significant. This indicatesthat organizations characterized by a solid presence of heavyweight product de-velopment managers will exhibit a high level of internal integration. The findingshere render more support to the work of Koufteros et al. (2002) and Koufterosand Marcoulides (2006) who concluded that heavyweight managers are instru-mental for achieving cross-functional integration. While Koufteros et al. (2002)and Koufteros and Marcoulides (2006) used the firm as the unit of analysis, theanalysis here is, however, at the project level.

Consistent with prior literature and empirical studies, it was hypothesizedthat internal integration is a precursor to external integration. Koufteros et al.(2005) provide theoretical support for the internal-external integration link andusing a sample of 244 firms they show strong relationships among the constructs.Similarly here, Hypothesis 2 is fully supported. Internal integration had strongeffects on customer integration (H2a), supplier product integration (H2b), andsupplier process integration (H2c). Coinciding with Koufteros et al. (2005), theeffects on customer integration appear to be the most potent (t = 4.78, β = 0.48).However, the effects on supplier process integration (t = 2.81, β = 0.18) do notappear to be as strong as those reported in Koufteros et al. (2005). Nevertheless,internal integration maybe quite useful in coordinating and enabling the integrationof external parties during the product development process.


Tabl

e3:

Des

crip

tives

,cor

rela

tions

,com

posi

tere

liabi

lity,

and

aver

age

vari

ance

extr

acte

d(n

=19

1).

Mea

nH

eavy

wei

ght

Supp

lier

Supp

lier

On-

time

Con

stru

ctpe

rPr

oduc

tDvl

pIn

tern

alC

usto

mer

Prod

uct

Proc

ess

Exe

cutio

nM

arke

t(N

o.of

Item

s)It

emM

anag

ers

Inte

grat

ion

Inte

grat

ion

Inte

grat

ion

Inte

grat

ion

Glit

ches

ofE

CO

sSu

cces

s

Hea

vyw

eigh

tpr

oduc

tdvl

pm

anag

ers

(5)

3.65

1.00

(.52

d.8

4e )

Inte

rnal

3.93

.26a ,.

07b

1.00

(.52

,.84

)in

tegr

atio

n(5

)[.

14,.

38]c

Cus

tom

er3.

84.3

2,.1

0.2

1,.0

41.

00(.

55,.

83)

inte

grat

ion

(4)

[.12

,.40

][.

11,.

31]

Supp

lier

prod

uct

2.56

.38,

.14

.18,

.03

.13,

.02

1.00

inte

grat

ion

(3)

[.18

,.58

][.

06,.

30]

[−.0

1,.2

7](.

64,.

84)

Supp

lier

proc

ess

3.34

.27,

.07

.18,

.03

.08,

.01

.59,

.35

1.00

inte

grat

ion

(2)

[.13

,.41

][.

08,.

28]

[−.0

2,.1

8][.

54,.

70]

(.54

,.70

)

Glit

ches

(4)

2.06

−.24

,.06

−.17

,.03

−.06

,.00

−.05

,.02

−.14

,.02

1.00

[−.3

8,−.

10]

[−.2

7,−.

07]

[−.1

6,.0

4][−

.19,

.09]

[−.2

4,−.

04]

(.56

,.83

)

On-

time

3.52

.40,

.16

.14,

.02

.11,

.01

.26,

.07

.23,

.05

−.25

,.06

1.00

(.81

,.93

)ex

ecut

ion

of[.

24,.

56]

[.04

,.24

][−

.01,

.23]

[.10

,.42

][.

11,.

35]

[−.3

7,−.

13]

EC

Os

(3)

Mar

kets

ucce

ss(4

)3.

65.2

5,.0

6.1

6,.0

3.1

1,.0

1.2

0,.0

4.1

4,.0

2−.

15,.

02.1

4,.0

21.

00(.

58,.

84)

[13,

.37]

[.08

,.24

][.

03,.

19]

[.10

,.30

][.

06,.

22]

[−.2

3,−.

07]

[.06

,.22

]

a Cor

rela

tions

,bSq

uare

dco

rrel

atio

ns,c C

onfid

ence

inte

rval

ofco

rrel

atio

nco

effic

ient

,dA

vera

geva

rian

ceex

trac

ted

onth

edi

agon

alin

pare

nthe

ses,

e Com

posi

tere

liabi

lity

onth

edi

agon

alin

pare

nthe

ses.

EC

O=

Eng

inee

ring

chan

geor

der.


Figure 2: Research framework.

HeavyweightProduct

DevelopmentManager

H2at=4.78

H1t=4.98 Internal

Integration

CustomerIntegration

Supplier ProductIntegration

Supplier ProcessIntegration

Glitches

On-timeExecution

of EngineeringChanges

MarketSuccess

H2bt=3.36

H2c

t=2.81

H3at=-.48

H3bt=.87

H3ct=2.86

H4bt=2.86

H 4a

t=7.25

H 4c

t=-2.25

H 5a

t=-3.07

H5bT=3.12

H7t=1.94

H6t=-3.08

Customer integration has received quite the attention as a prospective contrib-utor to the product development effort. The logic is rather simple. As customersultimately buy the products under consideration, they should participate in theproduct development effort in order to avoid costly delays and glitches that canhave adverse effects on their financial health of the supply chain. The results hereare interesting as only hypothesis H3c is supported (t = 2.86, β = 0.18). In otherwords, customer integration has a direct effect on market success but does notappear to have a direct impact on reducing glitches (H3a) nor does it impact theability of the firm to execute ECOs on time (H3b). The effects and accompany-ing t values were negligible (i.e., t = −.07, β = −0.48 and t = .11, β = 0.87,respectively).

Supplier product integration was projected to have an effect on supplier pro-cess integration (H4a), glitches (H4b), and the ability of the organization to executeECOs in a timely fashion (H4c). All effects were found to be statistically signifi-cant but two of the effects appear to be contrary to expectations. It was expectedthat supplier product integration will lead firms to adopt more process integrationpractices and the findings here are consistent with prior research (Koufteros et al.,2005; Koufteros et al., 2007) and support the hypothesis (t = 7.25, β = 0.57). Itwas anticipated that supplier product integration would enable the firm to reduceinstances of glitches and thus a negative relationship was posited. It was also an-ticipated that supplier product integration would be an accelerant force during theexecution and management of ECOs. Instead, the data suggest that supplier prod-uct integration is contributing to increasing incidences of glitches (t = 2.86, β =1.14) and it adversely affects the ability of the firm to manage ECOs efficiently (t =−2.25, β = −0.67). Such results should not be a total surprise. Prior research has


Tabl

e4:

Sum

mar

yof

stru

ctur

alm

odel

para

met

eres

timat

es—

dire

ct,i

ndir

ect,

and

tota

leff

ects

(n=

191)

.

Hea

vyw

eigh

tSu

pplie

rSu

pplie

rO

n-T

ime

Prod

uctD

vlp

Inte

rnal

Cus

tom

erPr

oduc

tPr

oces

sE

xecu

tion

Path

Man

ager

sIn

tegr

atio

nIn

tegr

atio

nIn

tegr

atio

nIn

tegr

atio

nG

litch

esof

EC

Os

Inte

rnal

inte

grat

ion

H1:

.29a ,4

.98b

–—.2

9,4.

98d

Cus

tom

erin

tegr

atio

n–—

H2a

:.4

8,4.

78.1

4c ,3.6

1–—

.14,

3.61

.48,

4.78

Supp

lier

prod

ucti

nteg

ratio

n–—

H2b

:.4

3,3.

36.1

2,2.

87–—

.12,

2.87

.43,

3.36

Supp

lier

proc

ess

inte

grat

ion

–—H

2c:

.18,

2.81

H4a

:.5

7,7.

25.1

2,3.

44.2

4,3.

18–—

.12,

3.44

.42,

4.41

.57,

7.25

Glit

ches

–—–—

H3a

:−.

07,−

.48

H4b

:1.

14,2

.86

H5a

:−1

.98,

−3.0

7−.

11,−

3.19

−.38

,−3.

91–—

−1.1

2,−2

.86

–—−.

11,−

3.19

−.38

,−3.

91−.

07,−

.48

.02,

.31

−1.9

8,−3

.07

On-

time

exec

utio

nof

EC

Os

–—–—

H3b

:.1

1,.8

7H

4c:−.

67,−

2.25

H5b

:1.

50,3

.12

.11,

3.36

.40,

4.23

–—.8

5,2.

95–—

.11,

3.36

.40,

4.23

.11,

.87

.18,

2.47

1.50

,3.1

2

Mar

kets

ucce

ss–—

–—H

3c:

.18,

2.86

–—–—

H6:

−.20

,−3.

08H

7:.1

0,1.

94.0

6,3.

34.2

0,4.

19.0

2,.6

6.0

1,.7

3.5

4,2.

74–—

–—.0

6,3.

34.2

0,4.

19.2

0,2.

84.0

1,.7

3.5

4,2.

74−.

20,−

3.08

.10,

1.94

a Dir

ecte

ffec

tcoe

ffici

ent,

btv

alue

,c Indi

rect

effe

ctco

effic

ient

,dTo

tale

ffec

tcoe

ffici

ent.

Fit

indi

ces:

χ2(d

f)=

625.

73(3

89);

χ2/d

f=

1.61

;C

FI=

.90;

NN

FI/T

LI=

.90;

RM

SEA

=.0

57;

mod

elA

IC=

777.

73;

satu

rate

dm

odel

AIC

=93

0.E

CO

=E

ngin

eeri

ngch

ange

orde

r.


documented the nonconsequential or even potential detrimental effects of supplierproduct integration on product development outcomes such as product innova-tion, quality, and time to market (Koufteros et al., 2005, 2007; Ettlie & Pavlou,2006).

Supplier process integration was expected to be a significant factor in re-ducing incidences of glitches (H5a) and enhancing on-time execution of ECOs(H5b). The data analysis suggests that supplier process integration is indeed astatistically significant explanatory variable of both glitches and on-time executionof ECOs. The effect on glitches was negative (t = −3.07, β = −1.98), suggestingthat higher levels of supplier process integration are associated with fewer glitches.On the other hand, supplier process integration contributed favorably to the timelyexecution of ECOs (t = 3.12, β = 1.50).

It was hypothesized that glitches (H6) and on-time execution of ECOs (H7)would have a determining impact on market success. Glitches and ECOs are costlyand can have adverse effects on the ability of the firm to introduce the productto market on time. The effect of glitches on market success was statisticallysignificant and negative (t = −3.08, β = −0.20). Lower levels of glitches areassociated with higher market success. The effects of on-time execution of ECOson market success were positive (t = 1.94, β = 0.10) and statistically significantat the .03 level. Thus, reducing incidences of glitches and managing the executionof ECOs on time contribute beneficially to market success.

DISCUSSION

Glitches are costly in many respects and demand close attention. Glitches can delayproduct introduction and/or can result in poor quality and unsatisfied customers(Hoopes & Postrel, 1999). Glitches can also be expensive to remedy as differ-ent phases of product development may have to be revisited. This may consumevaluable engineering time and talent along with taxing suppliers and customerswith added duties. Many firms have discovered that organizational integration isconducive both to eliminating glitches and mitigating their impact when they dooccur (Hoopes & Postrel, 1999). An internal integration approach, coupled withthe presence of a heavyweight product development manager, provides an avenueto integrate with suppliers and customers alike. The integration of suppliers andcustomers in the product development effort can improve the early identification ofpotential glitches and thus a metastasis of a glitch from one product developmentphase to another can be avoided. Based on prior literature and theoretical argumen-tation, a nomological network of product development routines and outcomes wasput forward and tested via a sample of 191 projects in the automotive industry. Fiveorganizational routines were examined and include the use of heavyweight productdevelopment managers as leaders of the project, internal integration, customer in-tegration, and supplier product and process integration. Outcomes examined hereinclude glitches, on-time execution of ECOs, and market success.

The practice of appointing a heavyweight product development managerappears to be not only catalytic but also instrumental for integration and sub-sequent product development outcomes. Heavyweight managers appear to havea strong positive effect on internal integration, which is manifested via a


cross-functional team that begins work from the early stages of product devel-opment and works concurrently on multiple phases of the project. As Table 4shows, however, the effects of heavyweight product development managers canbe felt along the nomological network of variables. Such indirect effects appearto be statistically significant and positive for customer integration, supplier in-tegration, on-time executions of ECOs, and market success while the effect onincidences of glitches is negative, showing the far reaching favorable implicationsof heavyweight product development managers.

Internal integration for product development is perhaps one of the most pop-ular routines that researchers employ to empirically study antecedents of productdevelopment outcomes. Integration is useful as it can assist the organization todevelop a shared universe of knowledge, and it can encourage higher levels of co-operation and coordination among and between internal and external constituents.The effects of internal integration on customer integration, supplier product inte-gration, and supplier process integration were positive and statistically significant(Table 4), attesting to the strong links that bind internal and external actors. Al-though direct effects between internal integration and product development out-comes (such as incidences of glitches and on-time execution of ECOs) were notspecified, the indirect effects that appear on Table 4 stand as testament to theimportance of internal integration.

In order to examine whether internal integration may be directly related toproduct development outcomes, an alternative structural model (i.e., nested model)is examined where internal integration along with external integration constructsare both posited to impact outcomes directly. Results indicate that the additionof direct effects resulted in insignificant improvement in χ2 (�χ2 = 4.41, 2 df,p value = .11) and the direct path coefficients that relate internal integration toboth glitches and on-time execution of ECOs alike (i.e., t = −.02, t = −.72,respectively) are statistically nonsignificant. This suggests that in the presence ofexternal integration routines, the direct effects of internal integration assume lessimportance. Since more and more product development activities are outsourcedand external constituents are assuming an increasingly important role in productdevelopment, the argument above appears to be a potential explanation.

Given the utility, motivation, and logic of integrating customers in the productdevelopment process, it was expected that customer integration would play a sig-nificant role in impacting glitches and in resolving ECOs expeditiously. Althoughboth path coefficients bare the hypothesized sign, Table 4 shows that neither ofthem is statistically significant. On the other hand, Table 4 indicates that the directeffect of customer integration on market success is statistically significant. Perhapsthe direct involvement of customers during the product development process re-sults in a sense of ownership and satisfaction, analogous to the feelings of personalsatisfaction reported by end-users who are involved in new software development.The direct effect of user input on process performance may be negligible, yet theusers may be satisfied with the end product due to their intimate participation indeveloping the new product (Cavaye, 1995).

Although supplier product integration appears to be an attractive approachto capitalize on the resources and capabilities of suppliers, its effects have notbeen examined in depth in the literature. The results here indicate that supplier


product integration is found to be a strong predictor of supplier process integra-tion, confirming earlier findings (i.e., Koufteros et al., 2005). To keep abreast ofproject activities and changes, suppliers that integrate through a supplier productintegration may also be integrated through a supplier process mode. The effects ofsupplier product integration on product development outcomes were not encour-aging, however. The adverse effects on glitches and on-time execution of ECOscoincide with prior work that showed (i.e., Koufteros et al., 2005) that supplierproduct integration may have statistically significant negative effects on productinnovation. Another research study (i.e., Koufteros et al., 2007) found that supplierproduct integration has no statistically significant impact on product innovation.Although the present manuscript does not employ product innovation as a de-pendent variable, the findings are relatively consistent in that supplier productintegration does not contribute productively and directly to product developmentoutcomes. Whether the unit of analysis was the firm or a particular project, thefindings are similar.

There are many possible explanations. First, the concept of supplier productintegration and the respective black-box parts suppliers develop are relative new-comers to the United States. Historically, the concept originated in Japan by Toyotaand one of its suppliers, Nippondenso, around 1949 (Fujimoto, 1994). The needfor supplier product integration emerged when Toyota’s engineers for electricalcomponents ended up with Nippondenso (when Nippondenso was separated fromToyota). As a matter of necessity, Toyota relied on Nippondenso engineers to do allthe basic and detailed engineering of electrical components (Fujimoto, 1994). Thispractice prevailed swiftly during the era of rapid growth of the auto industry in the1960s and the diffusion was complete within Japan by the 1980s (Fujimoto, 1994).The diffusion of this mode of supplier integration in product development beganin the United States in the 1980s and continues today. Compared to six decades ofpractice in Japan, the phenomenon is fairly recent in the United States and may ex-plain some of the findings. It takes time for the supplier base to mature and be ableto undertake the responsibility to develop black-box parts, components, or sub-assemblies. U.S. suppliers have not always been entrusted with the development ofcomponents, let alone subassemblies. U.S. auto manufacturers in particular havebeen operating under a white-box design approach where all product engineeringwas performed in-house with very little, if any, participation from suppliers. Thefact that U.S. suppliers were played against each other in order to minimize costdid not help to build a supplier base that is capable of engaging in supplier productintegration. Supplier selection is often based on lowest cost. Suppliers with thelowest cost do not always exhibit the best product development capabilities. Also,over the last few years, many U.S. firms have depleted their engineering staff andmade the assumption that suppliers can undertake the responsibility to do the prod-uct engineering of parts and subassemblies with minimal supervision/oversight orfeedback. This assumption is untenable. Firms put too much faith in their indus-trial suppliers and their respective capabilities without verifying them. Supplierselection is vital, but supplier monitoring and management is equally critical.

The data analysis suggests here that companies that involved their suppliersthough supplier product integration did experience higher levels of glitches andpoor on-time execution of ECOs. However, companies that proceeded to augment


supplier product integration with supplier process integration reported fruitfulindirect effects. In other words, the indirect effects of supplier product integra-tion on glitches and on-time execution of ECOs were statistically significant andrewarding.

Contrary to the adverse direct effects of supplier product integration, theeffects of supplier process integration were rather constructive. Lower levels ofglitches and more timely response to ECOs can be attributed to higher usageof supplier process integration. Since supplier process integration has been inexistence in the United States far longer than supplier product integration, it ispossible that both suppliers and manufacturers are well versed on this type ofintegration.

Terwiesch and Loch (1999), Hoopes and Postrel (1999), and Rouibah andCaskey (2003) report on the consequential effects of glitches and ECO response.While the use of descriptive statistics can illustrate the financial importance ofglitches and ECOs, the data analyses, however, do demonstrate that lower inci-dences of glitches and efficient management of ECOs does lead to higher levels ofmarket success. Reducing incidences of glitches appears to be a stronger predictorof market success than managing ECOs on time. This should not come as a sur-prise; ECOs owe their existence to glitches. In the absence of glitches, managingECOs is a moot issue.

The model advanced here essentially posits that customer integration and sup-plier integration mediate the effects of internal integration on product developmentoutcomes. Future research should assess perhaps whether customer integrationand supplier integration could instead moderate the relationship between internalintegration and product development outcomes. The limited empirical evidencegathered so far is not very encouraging, however. A recent empirical study findsno statistical support for moderation effects, though the study was not specific toproduct development. Flynn, Huo, and Zhao (2009), relying on the contingencytheory of the firm, hypothesized and tested for two-way and three-way interac-tions between internal integration, customer integration, and supplier integrationas a means to explain operating performance. Given a relatively large sample ofover 600 firms, there was very little empirical evidence to support the moderatinghypothesis.

Future research could also examine whether internal integration, customerintegration, and supplier integration can be conceptualized as dimensions of asecond-order construct. One may argue that it is the confluence or convergenceof effort that makes integration useful. Subsequently, the second-order constructcan be directly related to product development outcomes. Mishra and Shah (2009)provide some evidence in support of a second-order model via a sample of 189projects across several industries and countries. They coin the second-order con-struct as “collaborative competence” but they fail to properly examine the modelfit of the second-order measurement model. They specify three first-order fac-tors but for identification purposes there has to be a minimum of four first-orderfactors. Thus the model is just identified and the second-order measurement struc-ture is not truly tested. Nevertheless, they find that “collaborative competence” isstatistically related to project performance. Future research can potentially spec-ify a second-order factor model using the four first-order factors (i.e., internal


integration, customer integration, supplier product integration, and supplier pro-cess integration) employed in this study as indicators.

Implications for Decision Making

Product development is perhaps one of the most critical activities that organizationsengage in. Many product attributes that can engender competitive advantage rely onproduct development. How a product looks, functions, and performs; how currentit is; how attractive it is; how reliable and durable it is; how manufacturable it is;and how costly it is all depend immensely on the product development process.Moreover, the timing of market launch depends arguably on the effective andefficient execution of product development activities. Glitches and mismanagementof ECOs hamper the ability of the organization to compete in the market across theaforementioned product attributes. Thus, organizations employ an array of routinesand technologies to avoid glitches, speed up processing of ECOs, and thus assurea more successful product launch. This article focuses on many organizationalroutines that can reduce glitches, execute ECOs on time, and ultimately lead tomarket success.

What are the implications from this empirical study? Terwiesch and Loch(1999) classified prior work on glitches and ECOs into “Four Principles of ECOManagement.” The first one calls for decision makers to avoid unnecessarychanges. This can be achieved if the different constituents spend more time onthe first release of the component. Efforts should be expended by internal andexternal constituents to anticipate information from downstream phases so thatearly phases can account for potential constraints and opportunities. The role ofheavyweight product development managers along with internal integration andsupplier process integration is vital in this respect. More deliberations and sharingof information and knowledge should occur in upstream stages to avoid unnec-essary ECOs later. The liberal use of supplier product integration without beingaccompanied by supplier process integration can spell disaster. The direct effectsof supplier product integration on glitches can be detrimental. As Table 4 shows,however, the indirect effects flowing through supplier process integration can bebeneficial as suppliers can be kept up to date with project constraints and re-quirements. Customer integration may not have a substantial effect on glitches butdirect customer involvement is more likely to lead to customer satisfaction andthus market success. In general, individuals display higher levels of satisfactionwhen they participate in a development process. They are likely to rate productattributes more favorably, conceivably because they would like to accredit theirown contributions.

The second principle suggests that decision makers should reduce the nega-tive impact of an ECO or glitch. The impact of ECOs is a function of the magnitudeof the change, its timing, and the number of components and tools that are to beaffected by the change (Terwiesch & Loch, 1999). Due consideration must begiven to all constituents in order to minimize the total impact across stakeholders.The discussions center on mitigating the negative impact of ECOs. Better under-standing of each others’ concerns and constraints is necessary. This can be facili-tated through the leadership exhibited by heavyweight managers who can martial


resources to deal with a glitch once it happens. Close cooperation and coordina-tion achieved by means of internal integration and supplier process integration areneeded.

The third principle recommends that decision makers detect ECOs (glitches)early. Glitches become more expensive and more difficult to implement as theproject moves downstream. Similar to the first principle, this frontloading activityis made possible by internal integration and supplier process integration. Finally,the fourth principle emphasizes reaction (Verganti, 1999). Decision makers shouldspeed up the ECO process. Because ECO lead time affects ECO cost and can haveadverse effects on the market launch date, an organization has every incentiveto manage ECOs efficiently. Moreover, having long-lived ECO problems impliesthat multiple problems will probably be open simultaneously, stressing limitedresources that can be employed toward ECOs (Terwiesch & Loch, 1999). Heavy-weight product development managers have the organizational clout and positionalauthority to allocate resources when glitches do occur. The occurrence of glitchesis a fertile ground for disagreements and blame games to arise. Heavyweight man-agers can assure that the team stays focused on the task. The integration of suppliersin the product development process (supplier process integration) implies betterknowledge sharing and faster transmission of information. Moreover, individualshave a cognitive bias trusting information that is provided first hand.

Limitations

Like all empirical research, this article has limitations. The use of a single re-spondent and a single method to collect data for each project can be considered alimitation. While key informants were carefully targeted and while there is signif-icant variance in responses, the possibility of bias is real. Also, the response rateis relatively low but not uncommon for large-scale empirical studies. The surveyinstrument was six pages long and possibly contributed to the low response rate.A low response rate may be interpreted from different angles. The respondentsperhaps found the survey to be too long or not very interesting or relevant. It couldalso be argued that some of the targeted respondents considered the questions tobe too intrusive.

The study did not use objective measures of glitches. However, gaining accessto such data may be logistically difficult. Reporting the number of glitches relatedto a particular project may be a thorny issue. While one project may experience fewglitches, those may be severe. On the other hand, another project may experiencemany glitches but those may be quite amendable to quick fixes. Perhaps reportingthe number along with the type of glitch may be conducive for further empiricalresearch. Furthermore, the timing of a glitch is equally important as glitches thatoccur closer to market launch are costly and more challenging to accommodate.[Received: February 2008. Accepted: October 2009.]

REFERENCES

Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: Alongitudinal study. Administrative Science Quarterly, 45(3), 425–455.


Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in prac-tice: A review and recommended two-step approach. Psychological Bulletin,103(3), 453–460.

Bagchi, P. K., & Skjoett-Larsen, T. (2002). Organizational integration in supplychains: A contingency approach. Global Journal of Flexible Systems Man-agement, 3(1), 1–10.

Barki, H., & Pinsonneault, A. (2005). A model of organizational integration,implementation effort, and performance. Organization Science, 16(2), 165–179.

Brown, W., & Eisenhardt, K. M. (1995). Product development: Past research,present findings and future directions. Academy of Management Review,20(2), 343–378.

Burt, R. S. (1992). Structural holes: The social structure of competition. Cam-bridge, MA: Harvard University Press.

Cavaye, A. L. M. (1995). User participation in system development revisited.Information & Management, 28(5), 311–323.

Child, J., & Faulner, D. (1998). Strategies of cooperation: Managing alliances,networks, and joint ventures. New York: Oxford University Press.

Clark, K. (1989). Project scope and project performance: The effects of partsstrategy and supplier involvement on product development. ManagementScience, 35(10), 1247–1263.

Clark, K., Chew, B., & Fujimoto, T. (1987). Product development in the worldauto industry. Brookings Papers on Economic Activity, 3, 729–781.

Clark, K. B., & Fujimoto, T. (1991). Product development performance. Boston:Harvard Business School Press.

Clark, K., & Fujimoto, S. (1992). Product development and competitiveness. Jour-nal of the Japanese and International Economies, 6(June), 101–143.

Clark, K. B., & Wheelwright, S. C. (1992). Organizing and leading “heavyweight”development teams. California Management Review, 34(3), 9–28.

Clark, K., & Wheelwright, S. C. (1993). Managing new product and processdevelopment. New York: Free Press.

Cooper, R. G., & Kleinschmidt, E. J. (1994). Determinants of timeliness in productdevelopment. Journal of Product Innovation Management, 11(5), 169–184.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psy-chometrika, 16(3), 297–334.

Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements,media richness and structural design. Management Science, 32(5), 554–571.

Donnellon, A. (1993). Cross-functional teams in product development: Accom-modating the structure to the process. Journal of Product Innovation Man-agement, 10(5), 377–392.

Eisenhardt, K., & Martin, J. (2000). Dynamic capabilities: What are they? StrategicManagement Journal, 21(10/11), 1105–1121.


Eisenhardt, K. M., & Schoonhoven, C. B. (1996). Resource-based view of strate-gic alliance formation: Strategic and social effects in entrepreneurial firms.Organization Science, 7(2), 136–150.

Ettlie, J., & Pavlou, P. (2006). Technology-based new product development part-nerships. Decision Sciences, 37(2), 117–147.

Faems, D., Van Looy, B., & Debackere, K. (2005). Interorganizational collab-oration and innovation: Toward a portfolio approach. Journal of ProductInnovation Management, 22(3), 238–250.

Fayol, H. (1949). General and industrial management. London: Pittman.

Flynn, B. B., Huo, B., & Zhao, X. (2009). The impact of supply chain integra-tion on performance: A contingency and configuration approach. Journal ofOperations Management, 28, 58–71.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equations models withunobservable variables and measurement error. Journal of Marketing Re-search, 18(1), 39–50.

Fujimoto, T. (1994). The origin and evolution of the “black box parts” practice inthe Japanese auto industry. 94-F1, Fuji Conference-January, The Universityof Tokyo.

Galbraith, J. (1977). Organizational design. Reading, MA: Addison-Wesley.

Glouberman, S., & Mintzberg, H. (2001). Managing the care of health and the cureof disease—part II: Integration. Health Care Management Review, 26(1),70–84.

Gupta, A. K., & Wilemon, D. L. (1990). Accelerating the development oftechnology-based new products. California Management Review, 32(2), 24–44.

Hagedoorn, J. (2002). Inter-firm R&D partnerships: An overview of major trendsand patterns since 1960. Research Policy, 31(4), 477–492.

Hendricks, K. B., & Singhal, V. R. (2003). The effect of supply chain glitches onshareholder wealth. Journal of Operations Management, 21(5), 501–522.

Hoopes, D. G., & Postrel, S. (1999). Shared knowledge, “glitches,” and productdevelopment performance. Strategic Management Journal, 20(9), 837–865.

Kijkuit, B. (2007). Social networks in the front end: The organizational life ofan idea. Doctoral dissertation, Erasmus University, Rotterdam, The Nether-lands.

Knudsen, M. P. (2007). The relative importance of interfirm relationships andknowledge transfer for new product development success. Journal of ProductInnovation Management, 24(2), 117–138.

Koufteros, X. A. (1999). Testing a model of pull production: A paradigm for manu-facturing research using structural equation modeling. Journal of OperationsManagement, 17(4), 467–488.

Koufteros, X. A., Cheng, T. C. E., & Lai, K. H. (2007). “Black-box” and “gray-box”supplier integration in product development: Antecedents, consequences and


the moderating role of firm size. Journal of Operations Management, 25(4),847–870.

Koufteros, X. A., & Marcoulides, M. A. (2006). Product development practices andperformance: A structural equation modeling-based multi-group analysis.International Journal of Production Economics, 103(1), 286–307.

Koufteros, X. A., Vonderembse, M. A., & Doll, W. J. (2001). Concurrent engi-neering and its consequences. Journal of Operations Management, 19(1),97–115.

Koufteros, X. A., Vonderembse, M. A., & Doll, W. J. (2002). Integrated productdevelopment practices and competitive capabilities: The effects of uncer-tainty, equivocality, and platform strategy. Journal of Operations Manage-ment, 20(4), 331–355.

Koufteros, X. A., Vonderembse, M. A., & Jayaram, J. (2005). Internal and externalintegration for product development: The contingency effects of uncertainty,equivocality, and platform strategy. Decision Sciences, 36(1), 97–133.

Kumar, N., Stern, L., & Anderson, J. C. (1993). Conducting interorganizationalresearch using key informatings. Academy of Management Journal, 36(6),1633–1651.

Lawrence, P. R., & Lorsch, J. W. (1967). Organization and environment. Boston:Harvard University Press.

Manning, M. (2007 August). Boeing talks 787 Dreamliner. Airways, 16–23.

Marcoulides, G. A. (1998). Modern methods for business research. Marwah, NJ:Earlbaum.

Millson, M. R., Raj, S. P., & Wilemon, D. (1992). A survey of major approachesfor accelerating new product development. Journal of Product InnovationManagement, 9(1), 53–69.

Mishra, A. A., & Shah, R. (2009). In union lies strength: Collaborative compe-tence in new product development and its performance effects. Journal ofOperations Management, 27(4), 324–338.

Narasimhan, R., & Das, A. (1999). An empirical investigation of the contribution ofstrategic sourcing to manufacturing flexibilities and performance. DecisionSciences, 30(3), 683–718.

Petersen, K., Handfield, R., & Ragatz, G. (2003). A model of supplier integrationinto new product development. Journal of Product Innovation Management,20(4), 284–299.

Phillips, L. W., & Bagozzi, R. P. (1986). On measuring the organizational propertiesof distribution channels: Methodological issues in the use of key informants.Research in Marketing, 8, 313–369.

Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research:Problems and prospects. Journal of Management, 12(4), 69–82.

Popper, K. (1963). Conjectures and refutations. London: Routledge and KeaganPaul.


Raykov, T., & Marcoulides, G. A. (2000). A first course in structural equationmodeling. Marwah, NJ: Earlbaum.

Rouibah, K., & Caskey, K. R. (2003). Change management in concurrent engi-neering from a parameter perspective. Computers in Industry, 50(1), 15–34.

Rupak, R., Doll, W., Rawski, G., & Hong, P. (2008). Shared knowledge and productdesign glitches in integrated product development. International Journal ofProduction Economics, 114(2), 723–736.

Schreyogg, G., & Kliesch-Eberl, M. (2007). How dynamic can organizationalcapabilities be? Toward a dual-process model of capability dynamization.Strategic Management Journal, 28(9), 913–933.

Slater, S. C., & Narver, J. C. (1995). Market orientation and the learning organi-zation. Journal of Marketing, 59(3), 63–74.

Stump, R. L., Athaide, G. A., & Joshi, A. W. (2002). Managing seller-buyer newproduct development relationships for customized products: A contingencymodel based on transaction cost analysis and empirical test. Journal of Prod-uct Innovation Management, 19(6), 439–454.

Syamil, A., Doll, W. J., & Apigian, C. H. (2004). Process performance in prod-uct development: Measures and impacts. European Journal of InnovationManagement, 7(3), 205–217.

Tatikonda, M., & Rosenthal, S. R. (2000). Successful execution of product devel-opment projects: Balancing firmness and flexibility in the innovation process.Journal of Operations Management, 18(4), 401–425.

Terwiesch, C., & Loch, A. (1999). Measuring the effectiveness of overlappingdevelopment activities. Management Science, 45(4), 455–465.

Terwiesch, C., Loch, C., & de Meyer, A. (2002). Exchanging preliminary infor-mation in concurrent engineering: Alternative coordination strategies. Orga-nization Science, 13(4), 402–419.

Verganti, R. (1999). Planned flexibility: Linking anticipation and reaction in prod-uct development projects. Journal of Product Innovation Management, 16(4),363–376.

West, K. (2007). Boeing 787 designed for passenger comfort, accessed October 3,2009, available at http://www.msnbc.msn.com/id/19421451/.

Zirger, B. J., & Maidique, M. A. (1990). A model of new product development:An empirical test. Management Science, 36(7), 867–883.

Xenophon A. Koufteros is an associate professor of supply chain managementat the Mays Business School at Texas A&M University. He received his PhD inmanufacturing management from the University of Toledo in 1995. He has anMBA and a BSBA degree in operations management from Bowling Green StateUniversity. He has published widely in journals such as Journal of OperationsManagement, International Journal of Production Research, International Journalof Production Economics, Structural Equations Modeling Journal, InternationalJournal of Operations and Production Management, and others. He is an associate


editor of Decision Sciences, Journal of Operations Management, and Journal ofSupply Chain Management and serves on the editorial board of Structural EquationModeling Journal. He is also the feature editor for Doctoral Student Affairs forDecision Line.

Greg Rawski is an assistant professor of management at the Schroeder Fam-ily School of Business at the University of Evansville. He received his PhD inmanufacturing management from the University of Toledo in 2005. He has anMBA from the University of Toledo in 2000 in international business and a BAdegree in business administration from Bluffton University. He has published injournals such as the International Journal of Operations and Production Manage-ment, International Journal of Production Economics, Journal of Information andKnowledge Management, and others. In 2006, he was one of 12 recipients of theIndiana Governor’s Award for Tomorrow’s Leaders.

Rupak Rauniar is an assistant professor of strategic management at the Universityof St. Thomas. He received his PhD in manufacturing management from the Uni-versity of Toledo in 2005. His research area includes new product development,knowledge management, and e-commerce. He has publications in the Interna-tional Journal of Production Economics, International Journal of Production andOperation Management, Journal of e-commerce Research, International Journalof E-business, Journal of Information and Knowledge Management, Journal ofBusiness and Behavioral Science, and others.

organizational integration for product development

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