collaborative product development: the effect of project complexity on the use of information...

Collaborative Product Development: The Effect ofProject Complexity on the Use of Information

Technology Tools and New Product DevelopmentPractices

David Xiaosong Peng, Gregory R. HeimDepartment of Information & Operations Management, Mays Business School at Texas A&M University, College Station,

Texas 77843-4217, USA,[email protected], [email protected]

Debasish N. MallickDecision Sciences Department, Opus College of Business, University of St. Thomas, Minneapolis, Minnesota 55403, USA,

[email protected]

C ollaboration is an essential element of new product development (NPD). This research examines the associationsbetween four types of information technology (IT) tools and NPD collaboration. The relationships between NPD

practices and NPD collaboration are also examined. Drawing on organizational information processing theory, we proposethat the relationships between IT tools and NPD collaboration will be moderated differently by three project complexitydimensions, namely, product size, project novelty, and task interdependence, due to the differing nature of informationprocessing necessitated by each project complexity dimension. Likewise, the moderation effects of the project complexitydimensions on the relationship between NPD practices and NPD collaboration will also be different. We test our hypothe-ses using data from a sample of NPD projects in three manufacturing industries. We find that IT tools are associated withcollaboration to a greater extent when product size is relatively large. In contrast, IT tools exhibit a smaller associationwith collaboration when project novelty or task interdependence is relatively high. NPD practices are found to be moresignificantly associated with NPD collaboration under the contingency of high project novelty or high task interdepen-dence. The findings provide insights about circumstances where several popular IT tools are more likely to facilitatecollaboration, thus informing an NPD team’s IT adoption and use decisions.

Key words: collaboration; product development; information technology; NPD practices; project complexityHistory: Received: September 2010; Accepted: April 2012 by Stylianos Kavadias, after 3 revisions.

1. Introduction

Collaboration is an essential driver of new productdevelopment (NPD) success. Effective collaborationrequires active involvement of stakeholders (e.g.,NPD team members, suppliers, and customers) indeveloping product concepts and executing designtasks. Whereas NPD teams traditionally have usedNPD practices oriented toward integrated productdevelopment to interpret, organize, and packageinformation, many NPD teams increasingly use infor-mation technology tools (IT tools for short) to facili-tate information sharing, enhance communicationand collaboration among stakeholders, and speed upproduct development processes. Although an NPDteam is likely to use both IT tools and NPD practicesfor collaboration, an important decision for the NPDteam is to what extent the team should use IT tools

and NPD practices in a specific project environment.Given the growing list of IT tools available to a NPDteam, it is also important to understand the extent towhich specific types of IT tools can help collaborationin different project environments.The existing literature does not provide detailed

insights that may help an NPD team to select and usethe appropriate IT tools to facilitate collaboration inspecific project environments. Few studies haveexamined the relationship between the extent towhich IT tools are used and the level of NPD collabo-ration (Banker et al. 2006). The limited research gener-ally treats IT tools as a high level, aggregate construct.Even fewer studies have examined the effect of theNPD project environment on the relationship betweenthe use of IT tools and NPD collaboration. Infor-mation systems literature suggests that IT shouldbe aligned with its context to achieve beneficial

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Vol. 23, No. 8, August 2014, pp. 1421–1438 DOI 10.1111/j.1937-5956.2012.01383.xISSN 1059-1478|EISSN 1937-5956|14|2308|1421 © 2012 Production and Operations Management Society

outcomes (Premkumar et al. 2005), implying that theproject environment is a relevant factor to considerwhen using IT tools. Prior research has found empiri-cal evidence about the context-dependent nature of ITat the firm level (Choe 2003) and at the individualuser level (Goodhue and Thompson 1995), but empir-ical evidence at the NPD project level is scant.Drawing on organizational information processing

theory, we propose that the relationship between ITtools and collaboration will vary across project envi-ronments with different complexity characteristics.Likewise, the relationship between NPD practicesand collaboration should also vary across projectenvironments. This is because the varying degreeand nature of project complexity will create differentinformation processing needs that should require IT-enabled or non-IT-enabled collaboration to differingextents. As opposed to the existing related literaturethat typically operationalizes IT tools as a singleaggregate construct (e.g., Barczak et al. 2008,Durmusoglu et al. 2006), we identify and measurefour types of IT tools based on a synthesis of ITtypologies in the existing literature: communicationIT tools, product design IT tools, project manage-ment IT tools, and product data and knowledgemanagement IT tools (e.g., Nambisan 2003,Sambamurthy et al. 2003). Furthermore, we examinethe moderation effect of multiple project complexitydimensions, including product size (the number ofparts in the product design), project novelty (the new-ness of product design, product markets, and tech-nology), and task interdependence (the influence of oneNPD task on other NPD tasks), on the IT tools-collaboration relationship. By disaggregating IT toolsand disaggregating project complexity dimensions,our study can potentially provide more specific man-agerial insights regarding the use of NPD IT tools.We test our hypotheses using survey data collected

from over 200 NPD projects in machinery, electronics,and transportation component industries. Our resultsindicate that product design IT tools and project man-agement IT tools have a significant association withcollaboration that is moderated by many of the projectenvironments we examine, whereas communicationIT tools and data and knowledge management ITtools are seldom associated with collaboration signifi-cantly. Overall, IT tools exhibit stronger associationswith collaboration for NPD projects with large productsize, low project novelty, or low task interdepen-dence, whereas NPD practices are more significantlyassociated with collaboration when task interdepen-dence or project novelty is high.Our results suggest that more NPD IT is not

necessarily better. Instead, our findings point to acontingency approach to the use of IT tools and NPDpractices. In particular, because IT tools represent

a cost to an NPD team and specific types of IT toolsfacilitate collaboration only in certain project environ-ments, managers should thoroughly assess variousproject complexity dimensions before adopting IT toolsas a means for project collaboration. When IT tools willonly have a limited effect on collaboration, managersshould provide incentives for team members to collab-orate through mechanisms such as NPD practices thatcan facilitate collaboration through non-IT-enabledinteraction and communication.The article is organized as follows. Section 2

presents the conceptual framework and constructsused in this study. Section 3 reviews relevant litera-ture and develops hypotheses. Section 4 describesthe data and the measurements that we use to testour hypotheses. Section 5 presents the analysis andthe results. Section 6 discusses theoretical implica-tions and managerial insights and suggests futureresearch directions.

2. Conceptual Framework

Before presenting the conceptual framework, it isimportant to differentiate between NPD practices andIT tools. Many of the NPD practices related to inte-grated product development became popular in the1970s and 1980s (Loch and Terwiesch 2000, Nambisan2003). As such, these practices initially were imple-mented without a major presence of IT. Today, NPDpractices are increasingly implemented with IT basedplatforms. Consequently, a growing number of NPDpractices have become embedded in IT tools. How-ever, NPD practices and NPD IT tools are conceptu-ally different. NPD practices typically refer toprinciples, frameworks, and methodologies for orga-nizing and coordinating NPD activities. NPD IT toolsare software applications for automating NPD designtasks, managing work flows, and facilitating informa-tion sharing and exchange. Although IT tools areincreasingly used in NPD activities, an NPD team cancollaborate without using IT tools by following theprinciples, frameworks, and methodologies as speci-fied in integrated NPD practices, especially whenNPD team members are co-located (Barczak et al.2009). NPD practices and IT tools are modeled as sep-arate constructs in a number of existing studies (Hullet al. 1996, Moffat 1998). Consistent with these stud-ies, we treat NPD practices and IT tools as separatetheoretical constructs and suggest that each canimpact collaboration independently.Information technology tools and NPD practices

each provide useful but different mechanisms forcollaboration. IT tools can be used to improve effi-ciency of information processing that involves clearlydefined, explicit information. For example, productdesign tools, such as computer-aided design (CAD)

Peng, Heim, and Mallick: Collaborative Product Development1422 Production and Operations Management 23(8), pp. 1421–1438, © 2012 Production and Operations Management Society

and simulation tools, can be used to support 2D and3D design modeling visualization and simulation,facilitating the exchange of technical data betweendesign engineers, manufacturing customers, and sup-pliers (Yassine et al. 2004). Email groupware providesan NPD team with environments in which toexchange ideas, share files, collaborate, and commu-nicate. Project management tools facilitate coordina-tion of activities among team members to share andcontrol project schedules, timelines, resources, andtasks. Shared parts databases are important for theexchange of technical information.However, when information is highly ambiguous,

using IT tools alone may not be sufficient for effectivecollaboration. Although the NPD team can still use ITtools to organize, process, and present informationwhich can subsequently be used in non-IT-enabledcollaboration (such as face-to-face meetings facilitatedby NPD practices), the NPD team may need to usemore direct means of communication and interaction,such as formal design review meetings, supplier orcustomer site visits, and design engineers workingside-by-side with experienced mentors. These formsof communication and interaction tend to be used to agreater extent when project managers strongly advo-cate integrated NPD practices (Swink 1998).Although IT tools can improve efficiency of infor-

mation processing, NPD practices can contribute tothe effectiveness of collaboration by improving infor-mation content clarity. Thus, NPD practices shouldbe particularly helpful for collaboration in a projectenvironment with a high degree of information ambi-guity. NPD practices, such as design for manufactura-bility (DFM), quality function deployment (QFD),and rapid prototyping facilitate real-time, multi-partycommunication with subtle cues and tailored mes-sages for intended recipients. Thus, these practicesshould enable an NPD team to clarify and make senseof customer demand information and its implicationon product and process designs and integrate andimprove communication between customers, design-ers, marketing, and manufacturing operations.We develop our conceptual framework based on

the above distinction between IT tools and NPD prac-tices. Our conceptual framework is presented inFigure 1. We propose that the extent to which NPDpractices and various IT tools are used should be posi-tively related to NPD collaboration. Furthermore, theassociations between IT tools and collaboration andbetween NPD practices and collaboration should bemoderated by the three project complexity dimen-sions. We draw on organizational information pro-cessing theory (OIPT) to articulate these theoreticalrelationships.According to OIPT, an organization must design

appropriate structural mechanisms and adopt the

right technologies and practices to provide the infor-mation processing capabilities that meet theorganization’s information processing needs (Bensaouand Venkatraman 1996, Galbraith 1974, MacCormackand Verganti 2003). This fit between informationprocessing needs and information processing capabil-ities can apply to the inter-organizational context, theintra-organizational context, and the project context.Product size, project novelty, and task interdepen-dence each create information processing needsof a different nature. Thus, each should requiredifferent means for NPD teams to communicate andcollaborate.Prior literature suggests two information contin-

gencies that can affect the choice of communicationand collaboration mechanisms: (i) the absence ofinformation and (ii) the equivocality (ambiguity) ofinformation (Daft and Lengel 1986, Weick 1979). Inthe former case, an organization needs to gather addi-tional information to solve problems. However, in thiscase information itself has little ambiguity and can beeasily codified, stored, and transferred. In the lattercase, equivocality presumes “a messy, unclear fieldand information stimulus that may have several inter-pretations” (Daft and Lengel 1986, p. 554). Whenfaced with a high degree of information equivocality,design engineers are likely to make decisions basedupon their own critical judgment. Project team mem-bers often must undertake intense discussion, debate,and negotiation to reach a consensus on project goals,schedules, and means to execute project tasks. In thiscircumstance, it is crucial to clarify ambiguous infor-mation rather than simply obtain more information.In the remainder of this section, we describe the

theoretical constructs in detail. We then develop ourresearch hypotheses in the following section.

2.1. New Product Development CollaborationNew product development involves complex andinterdependent activities. Successful NPD requires anNPD team to collaborate within the internal cross-functional team and with customers and suppliers.

H1+

H2+

H3a+NPD practices

Projectnovelty

Task inter-dependence

NPDcollaboration

Product size

NPD ITtools

H3b-

H4a- H4b+ H5a- H5b+

Figure 1 Conceptual Model

Peng, Heim, and Mallick: Collaborative Product DevelopmentProduction and Operations Management 23(8), pp. 1421–1438, © 2012 Production and Operations Management Society 1423

Collaboration involves intense cross-functional andinter-firm processes that use formal and informalmechanisms to develop a shared vision and mutualunderstanding among stakeholders and participantsof the NPD project (Jassawalla and Sashittal 2003). Wedefine NPD collaboration (“collaboration” hereinafter)as the extent to which an NPD project involves keystakeholders in defining project goals and executingproduct development tasks (Mishra and Shah 2009).With increasing pressure on NPD teams to develop

products better and faster, the need to collaborateeffectively with key stakeholders inside and outsideof the firm has grown significantly. During productdevelopment processes, the focal firm, customers, andsuppliers often must make joint decisions withrespect to product features, design specifications,product manufacturability, and process design.Therefore, NPD teams typically need to collaboratenot only with internal functions but also with the cus-tomer and the supplier organizations.NPD collaboration activities and processes enable

internal and external stakeholders to share data, infor-mation, and knowledge. An NPD team’s ability tointegrate knowledge sources across functional andorganizational boundaries is important for productdevelopment success (Rosenkopf and Nerkar 2001).Collaboration enables intra- and inter-firm knowledgesharing and improves problem-solving capabilities ofan NPD team. Joint involvement of internal functions,customers, and suppliers leads to collaboration syner-gies that generate more value than the sum totalvalue from the involvement of each individual stake-holder (Mishra and Shah 2009). We conceptualizeNPD collaboration as a higher order construct thatcaptures collaboration within the cross-functionalNPD team and between the NPD team and employ-ees from customer and supplier organizations.Because many IT tools can be used to facilitate collab-oration both within the NPD team and with outsidestakeholders, conceptualizing NPD collaboration as abroad, higher order construct is consistent with ourobjective of examining the relationships between the

use of various IT tools and collaboration that tran-scends functional and organizational boundaries.This conceptualization of collaboration has been usedin the literature (Mishra and Shah 2009).

2.2. NPD IT ToolsNPD IT tools are information technology applicationsan NPD team uses to accomplish development tasks.Our study captures IT tool usage because it is theactual use of IT tools instead of IT ownership thatleads to an organizational performance impact(Barczak et al. 2009). IT tool usage is defined as theapplication of IT tools within the NPD project’s strate-gic and operational activities. In an NPD environ-ment, IT tools can serve as exchange and sharingmedia to facilitate collaboration. Our study examinessix widely used IT tools (Barczak et al. 2009): CAD,computer-aided process planning (CAPP), simulationmodeling, shared parts databases, email groupware,and project management software. These IT tools canbe used to perform routine NPD tasks accurately andefficiently. Furthermore, these IT tools enablereal-time collaboration and extend visibility of parts,components, and vendors to the NPD team anytime,anywhere. The existing literature has classified NPDIT tools in different ways. Some representative classi-fication schemes are presented in Table 1. On thebasis of this literature, we classify the six IT tools intofour types: (i) communication IT tools (email group-ware), (ii) product design IT tools (CAD, CAPP, simu-lation modeling), (iii) project management IT tools(project management software), and (iv) product dataand knowledge management IT tools (shared partsdatabases).

2.3. NPD PracticesNPD teams use various NPD practices for more effec-tive collaboration and task execution. NPD practicescan be considered as rules, methodologies, andframeworks for organizing and packaging NPD infor-mation. A subset of NPD practices often referred to as“integrated product development practices” (IPDP)

Table 1 Types of NPD IT

StudyTypes of ITfor NPD

Nambisan 2003 Collaboration andcommunication

Information and knowledge Project management Processmanagement

Sambamurthyet al. 2003

Communication Knowledge management Processmanagement

Pavlou andEl Sawy 2006

Cooperative worksystems

Knowledge management Project and resourcemanagement

Gordon andTarafdar 2007

Collaboration andcommunication

Information and knowledgemanagement

Project management

Song andSong 2010

Communication Decision aiding/Product design


represents a significant contemporary trend in themanagement of new product development (Gerwinand Barrowman 2002). IPDP is a managerial approachfor improving new product development effective-ness. IPDP occurs in part by overlapping NPD activ-ities (e.g., partially or completely parallel execution).Some representative IPDPs are design for manufac-turability, concurrent engineering, and early manu-facturing involvement (Barczak et al. 2009, Gerwinand Barrowman 2002, Swink 1998). NPD teams useDFM methods to ensure that the product beingdesigned can be manufactured cost effectivelywithin the constraints of the manufacturing plant(Sanchez and Perez 2003). QFD is a design method-ology that employs interaction matrices to translatecustomer needs into design and process specifica-tions (Swink 1998). QFD is considered a method forimproving cross-functional integration and collabo-ration. As part of QFD, House of Quality (HoQ) is agraphic tool for defining relationships between cus-tomer desires and the firm’s engineering and manu-facturing capabilities (Hauser and Clausing 1988).Finally, rapid prototyping is the practice of quicklyproducing physical product models to support tool-ing and process design (Swink 1998). Rapid proto-typing is considered a part of the “concurrentengineering” approach to new product developmentand is believed to improve the quality of cross-func-tional decision making (Swink 1998).

2.4. Project ComplexityNPD projects are inherently complex because theytypically involve developing products that carrysome degree of uncertainty and novelty. Project com-plexity develops as a result of newness of producttechnology and markets, the size or scale of theproduct design, or the product structure (e.g., looselycoupled vs. tightly coupled product design). Novakand Eppinger (2001) summarize three sources ofNPD project complexity: number of components inthe product design, product novelty, and componentinteraction (interdependence of components). Build-ing on their research, we examine three NPD projectcomplexity dimensions: product size, project novelty,and task interdependence.Product size refers to the number of parts in the

product design. Its relevance to project complexityhas been documented in the literature. For instance,Clark and Fujimoto (1991) operationalize productcomplexity as the number of body styles in the newcar model. Murmann (1994) suggests that a means toreduce product complexity is to reduce the number ofparts in the product. Project novelty arises fromsources such as novelty of product or process technol-ogy (Tatikonda and Montoya-Weiss 2001, Tatikondaand Rosenthal 2000), lack of information about the

potential markets and target customers (Adler et al.1995, Anderson and Joglekar 2005, Tatikonda andMontoya-Weiss 2001), and ambiguity of project goals(Tatikonda and Rosenthal 2000). Prior literaturedefines project novelty as newness of product design,technology, and markets (Tidd and Bodley 2002). Ourresearch captures project novelty with respect to thedeviation of the product design from existing prod-ucts, newness of the target market, and newness ofproduct and process technologies. Task interdependencecharacterizes the influence of any given task on othertasks within an NPD project (Sobrero and Roberts2001). Task interdependence often results from tightlycoupled components in a product design (Novak andEppinger 2001). Tatikonda and Rosenthal (2000) sug-gest that interdependence or connectivity betweencomponents increases project complexity.

3. Hypotheses

3.1. The Relationship Between IT Tools and NPDCollaborationThe need for collaboration should stimulate an NPDteam to use various IT tools and NPD practices thatcan enhance collaboration. The use of these IT toolsand NPD practices, in turn, should lead to improvedNPD collaboration. Thus, discussion of collaborationcan relate either to requirements for collaboration orto the actual state of collaboration. The subsequentdiscussion focuses on the relationship between theuse of IT tools and the actual state of collaboration.IT tools can be used to enhance information sharing

and knowledge creation during the NPD process. ITtools “permit transmission of complex or tacit knowl-edge, or both, and support extensive vs. routine prob-lem solving” (Banker et al. 2006, p. 355). Priorresearch suggests that NPD teams can use IT tools tosupport a broad range of system-to-system collabora-tion capabilities for processing structured productdesign data (Nambisan 2003). IT tools enable productdesign teams to collaborate across functional andorganizational boundaries to gather and share designrequirements, conduct design iterations, verify andtest designs, and provide the final design handoff toother departments (Adler and Mandelbaum 1995,Banker et al. 2006, McGrath and Iansiti 1998).Various types of IT tools can impact collaboration

through different mechanisms. Email groupware cre-ates electronic communication channels among NPDteam members and other stakeholders. Email group-ware can transform the way documents are shared tofacilitate effective team collaboration (Boutellier et al.1998). Product design tools such as CAD can be usednot only for engineering design but also for cross-functional and cross-organizational information shar-ing (Tan and Vonderembse 2006). CAD can act as a


common language that facilitates communication andcollaboration among internal functions (Eisenhardtand Tabrizi 1995, Tan and Vonderembse 2006) andwith suppliers (Li et al. 2005), and facilitates customerco-design and collaboration (Piller et al. 2005). Projectmanagement software can be used to coordinate andschedule tasks and manage project resources effi-ciently. Sophisticated project management softwarecan provide complex real-time workflow manage-ment capabilities to coordinate the activities of NPDteam members (Nambisan 2003). Finally, modernNPD projects generate an extensive amount of infor-mation and knowledge. Often implemented as a partof a product data management (PDM) system, sharedparts databases provide a dual synchronous/asyn-chronous collaboration environment for anyoneinvolved in an NPD project to access, review, pro-duce, and store feedback on part design information.An NPD team can use shared parts databases as thegateway to access parts information under discussion,thus avoiding the need to copy and distribute largeamounts of paper documents. The above discussionleads to the following hypotheses:

H1: The extent to which NPD IT tools are usedis positively associated with the level of NPDcollaboration.

H1a: The extent to which communication ITtools are used is positively associated with thelevel of NPD collaboration.

H1b: The extent to which product design ITtools are used is positively associated with thelevel of NPD collaboration.

H1c: The extent to which project managementIT tools are used is positively associated withthe level of NPD collaboration.

H1d: The extent to which product data andknowledge management IT tools are used ispositively associated with the level of NPDcollaboration.

3.2. The Relationship Between NPD Practices andNPD CollaborationNPD practices oriented toward integrated productdevelopment can enhance NPD collaboration throughmechanisms, such as overlapping NPD projectphases, creating a context for cross-functional com-munication, and making product prototypes availableto relevant stakeholders early in the NPD life cycle.

These NPD practices enable simultaneous processingof the information needed to design, manufacture,sell, and service a product (McGrath 1992, p. 91).Design for manufacturability, for instance, requiresdesign engineers and manufacturing engineers towork together to design and rationalize both theproduct design and the manufacturing processes.Typically, product designer consideration of manu-facturability, cost, reliability, and maintainability pro-vides the starting point for cross-functional productdevelopment. QFD is widely regarded as a useful toolfor translating customer needs into technical targets.Essentially, QFD requires a cross-functional team towork collaboratively to generate and evaluate cus-tomer attributes and the requisite engineering specifi-cations (Swink 1998). Rapid prototyping enablesdesign engineers to quickly create product prototypesfor visual inspection, ergonomic evaluation, andform-fit analysis, thus enabling various internal func-tions and external stakeholders to provide their feed-back on the product prototypes (Choi andSamavedam 2001). By rapidly constructing productprototypes, accurate assessments of manufacturabilityand customer acceptance can better inform productdesigners (Tsenget et al. 1998).

H2: The extent to which NPD practices orientedtoward integrated product development areused is positively associated with the level ofNPD collaboration.

3.3. The Moderation Effects of Project ComplexityDimensionsNew product development projects vary considerablyin their levels of complexity. Project tasks with differ-ing natures and degrees of complexity need to bematched with different information processing mech-anisms. There is considerable empirical evidenceabout the contingency nature of information process-ing requirements for tasks with varying natures ofcomplexity (Tatikonda and Montoya-Weiss 2001).Due to the different information processing mecha-nisms associated with IT tools and NPD practices,their effects on NPD collaboration should be differentacross project environments with differing naturesand degrees of complexity. We discuss the modera-tion effect of each of the project complexity dimen-sions below.

3.3.1. The Moderation Effect of Product Size. Asproduct size increases, the number of product compo-nents and their interfaces can increase quickly, lead-ing to an increased amount of design information thatneeds to be processed. However, this informationis likely to be structured information, such as


engineering drawings, product specifications, testreports, and engineering change orders. This struc-tured information can be processed effectively usingIT tools. Prior literature suggests that the value of ITtools tends to increase when a product design hasmany components (Rodrıguez-Toro et al. 2005). If theinformation contingency facing an NPD team is toprocess a large amount of mostly structured informa-tion, then the nature of NPD collaboration shouldfocus on distributing and sharing a large amount ofinformation rather than clarifying ambiguity of theinformation. The NPD team can use IT tools toachieve a high level of collaboration of this nature.For instance, CAD can be used to create product visu-als, produce neat blueprints to display product speci-fications, and quickly prepare documentation for theproduction processes. A shared parts database pro-vides the NPD team with well-organized, complete,real-time data about components and parts, includingdesign notes, part alternatives, and bills of materials(BOM). Email groupware provides a convenient, cost-effective means of communication and documentsharing. Email groupware can be quite effective whenit is used to distribute large amounts of structuredinformation to multiple recipients. Finally, projectmanagement tools can facilitate collaboration andcommunication to control project schedules, time-lines, and resources that can become a daunting taskas the size of the project increases.Admittedly, as the product size becomes larger,

both IT-enabled collaboration and non-IT-enabledcollaboration should increase. However, due to theeffectiveness of IT tools for processing large amountsof structured information, the need for IT-enabledcollaboration should increase more than the need fornon-IT-enabled collaboration.

H3a: The association between the use of IT tools(e.g., communication IT tools, product design ITtools, project management IT tools, and productdata and knowledge management IT tools) andNPD collaboration will be greater for NPD pro-jects that develop products of larger size.

H3b: The association between the use of NPDpractices and NPD collaboration will be smallerfor NPD projects that develop products of largersize.

3.3.2. The Moderation Effect of ProjectNovelty. An NPD team developing novel productstypically faces high information equivocality (Daftand Lengel 1986). The NPD team has no establishedprocedures to follow. A large number of exceptions

could occur during task execution. NPD teammembers may have different and sometimes conflict-ing interpretations of the equivocal information. Pro-viding more information processing capacity willlikely but not necessarily yield positive outcomes.Although the NPD team still needs to use various ITtools to process and share structured information, theNPD team frequently has to “think about, create, orfind satisfactory solutions to problems outside of thedomain of facts, rules, or procedures” (Rice 1992,p. 479). Thus, it is important for the NPD team toimplement information processing mechanisms thatenable team debate, clarification, and enactment toreduce information equivocality. The NPD team islikely to collaborate using the most direct and richmedia (e.g., group meetings and working side-by-sideto solve problems) to a relatively greater extent (Mon-toya et al. 2009, Van de Ven et al. 1976). Koufteroset al. (2002) observe that in a low platform (i.e., highproject novelty) environment, personal interaction,and processing of rich information were more criticalthan IT tools for NPD success. Brown and Eisenhardt(1995) suggest that IT tools may be more effective forstable products in mature settings.Differences in information richness arise from the

capacity of communication media for immediate feed-back, the number of cues and channels, the degree ofpersonalization, and language variety (Daft andWiginton 1979). Although modern IT tools can enablecommunication through a variety of channels (e.g.,verbal, visual, and written) and relatively rich media(e.g., video conferencing), face-to-face meeting is stillthe richest communication media that is particularlyeffective for reducing information equivocality(Boutellier et al. 1998, Daft and Lengel 1986, Montoyaet al. 2009). When project novelty is high, the NPDteam can still share and exchange information usingIT tools. However, NPD team members likely willhave questions about information exchanged throughemail groupware, engineering design files shared byCAD software, or activities planned using projectmanagement tools. A novel project also implies thatteam members may rely to a lesser extent on the exist-ing parts database to design new parts. Prior researchsuggests that while email applications, CAD, andshared parts databases facilitate information exchange,they are relatively weak in facilitating informal con-versation and promoting creativity (Boutellier et al.1998). Although project management tools providestrong coordination support, they do not adequatelysupport collaboration for idea generation and ad hoccommunication (Gassmann and von Zedtwitz 1996).Collaboration enabled by NPD practices allows

NPD team members to brainstorm, debate, and clarifyinformation ambiguity, as well as follow up on infor-mation exchanged using IT tools. For instance,


integrated product development practices such asQFD and DFM enable an NPD team to work inter-actively and simultaneously to transform customerrequirement information into product designs thatcan be manufactured cost efficiently and facilitatejoint problem solving. When the product concept isnot clearly defined, rapid prototyping enables theNPD team to quickly turn a product concept into aproduct prototype, present it to the customer for feed-back, and incorporate the customer feedback into sub-sequent iterations. In contrast, when project novelty islow, an NPD team tends to have established rules andprocedures to follow in executing unambiguous andanalyzable tasks. Collaboration often involves com-municating and exchanging explicit, clearly definedinformation and knowledge. IT tools such as emailgroupware, CAD software, shared parts databases,and project management software can be used tofacilitate such information exchange processes effec-tively and therefore may be used to a relativelygreater extent.

H4a: The association between the use of IT tools(e.g., communication IT tools, product design ITtools, project management IT tools, and productdata and knowledge management IT tools) andNPD collaboration will be smaller for NPDprojects with a higher degree of novelty.

H4b: The association between the use of NPDpractices and NPD collaboration will be greaterfor NPD projects with a higher degree of novelty.

3.3.3. The Moderation Effect of Task Interde-pendence. When task interdependence is high, NPDteam members often have to share vague preliminarydesign information. Furthermore, with high interde-pendence among the product components, makingchanges to one component is likely to induce furthercomponent changes. Thus, whenever a change is initi-ated to a component, it is important for the designengineers involved in the design of the coupled com-ponents to coordinate design changes and associatedschedule changes. As the level of task interdepen-dence increases, the number of mutual adjustmentscan increase dramatically. To reduce informationequivocality (ambiguity) regarding design specifica-tions and project schedule, design engineers oftenhave to coordinate interdependent tasks “in an infor-mal, ad hoc manner” (Terwiesch et al. 2002), suggest-ing that intense brainstorming and debate are oftenneeded for design engineers to develop a clear under-standing of the interdependent tasks. Although anNPD team can still share design data using product

design tools and communicate preliminary designinformation using email groupware, high task inter-dependence should lead design engineers to commu-nicate face-to-face to a great extent to solve problemsquickly. Likewise, the project manager may prefer totalk to team members personally before schedulingthe project tasks using project management tools.Finally, high task interdependence implies tightlycoupled parts and components, which should lead anNPD team to use existing parts to a lesser extent (Ger-shenson et al. 2003).Prior research suggests that when task interdepen-

dence is high, the more effective teams exhibit ahigher frequency of communication between teammembers and utilize more complex decision-makingprocesses that require highly rich communicationmedia (Van de Ven et al. 1976). Design for manufac-turability enables continuous updating of preliminaryinformation from design engineers to manufacturingengineers, and vice versa, helping design engineers toanticipate problems in the manufacturing processes.QFD enables design engineers to work interactivelyto identify the design trade-offs and choose an appro-priate design that meets customer requirementswithin the project time and budget constraints. Rapidprototyping allows design engineers to anticipate andeliminate uncertainty and therefore enables bettercommunication in a project environment with hightask interdependence.In summary, although team members will still use

multiple forms of collaboration, the NPD practices forintegrated product development should stimulateteam members to use informal and ad hoc collabora-tion to a relatively greater extent, likely resulting in arelatively lower extent of IT tool use for collaboration.

H5a: The association between the use of IT tools(e.g., communication IT tools, product design ITtools, project management IT tools, and productdata and knowledge management IT tools) andNPD collaboration will be smaller for NPD projectswith a higher degree of task interdependence.

H5b: The association between the use of NPDpractices and NPD collaboration will be greaterfor NPD projects with a higher degree of taskinterdependence.

4. Data and Measures

4.1. DataThe empirical analysis is based on relevant datacollected as a part of a large-scale survey on highperformance manufacturing (Peng et al. 2008). The


survey collected data in 2006 from manufacturingplants in nine countries (Finland, Sweden, Germany,Austria, Italy, Spain, Japan, Korea, and the UnitedStates) and three industries (machinery, electronics,and transportation components) as defined by 4-digitStandard Industrial Classification (SIC) codes. A fewpublished studies have used the portion of the surveyrelated to NPD, but focused on completely differentresearch questions (Mishra and Shah 2009). We directthe interested readers to these studies and Roth et al.(2008) for more details about the survey.A team of researchers at universities in each of the

countries facilitated data collection. The questionnairescales were developed based on relevant literatureand underwent pilot testing and revision. Becausedata collection involved multiple countries, the ques-tionnaires were translated into the native language ofeach country before distribution. The questionnaireswere also translated back to English by a differentperson to check for translation accuracy.The plants were randomly selected from a master

list of manufacturing plants in each country. Manag-ers of the selected plants were contacted by phone torequest permission for the plant to participate in thestudy. Upon agreement, survey instruments andinstructions for administering the survey weremailed to a survey coordinator at each participatingplant. The survey coordinator distributed each ques-tionnaire to the designated respondents, collectedcompleted questionnaires, and mailed them back tothe research team. Among the plants contacted bythe research team, 65% returned the survey question-naires. This high response rate was achieved by call-ing each plant manager and by providing eachparticipating plant with a comprehensive reportcomparing its profile with competitors in its indus-try. We compared plants that provided responses tothe portion of the survey related to NPD and theplants in the master list. There were no statisticallysignificant differences between the samples and thetarget list of plants in terms of plant size and indus-try composition.The target population of our study consists of the

product development projects in the targeted manu-facturing industries in the countries where the surveywas conducted. For the portion of the survey relatedto NPD, an NPD team member in each manufacturingplant responded to a survey questionnaire regardinga recent product development project in which he orshe was involved. The research data include oneNPD project from each participating plant. The dataset includes 212 projects. We compared respondingand non-responding groups for differences in plantsize, team experience, and project priority. The resultsdid not indicate a significant difference between thetwo groups. We also compared the NPD performance

(technical performance, time-to-market, and manufac-turing costs) between the response group and thenon-response group. Again, we did not find signifi-cant differences between the two groups.

4.2. Measurement ItemsAppendix A presents measurement items. We measureNPD collaboration through three multi-item scales:cross-functional collaboration, customer collabora-tion, and supplier collaboration. Each collaborationscale evaluates the extent and timing of collabora-tion between internal functions, with customers orwith suppliers (Brown and Eisenhardt 1995, Gerwinand Barrowman 2002, Ittner and Larcker 1997).Items measuring IT tools capture the extent to whichNPD teams use six popular IT tools: CAD, CAPP,simulation modeling, shared parts databases, emailgroupware, and project management software. Wecreate four IT tool constructs, each measuring theuse of one of the four types of NPD IT tools. TheNPD practice scale uses three items. Each item mea-sures the extent of use of one of the three NPD prac-tices: DFM, QFD, and rapid prototyping.With respect to project complexity variables, prod-

uct size is operationalized as the number of parts inthe product design. Project novelty is constructed asan additive index aggregating five aspects of projectnovelty, including the extent to which product designdiffers from the existing products, newness of theproduct design, newness of the product market, new-ness of product technology, and newness of processtechnology (Mallick 2000). Each aspect of projectnovelty is captured by summing up the three itemsmeasuring that project novelty aspect. Task inter-dependence is evaluated by an item asking therespondent to indicate the extent to which projecttasks depend upon each other.The survey also collected data on relevant control

variables that may affect NPD collaboration: projectpriority, the average team member experience, thenumber of individuals involved in the NPD project,and country and industry of the participating plants.High priority projects motivate NPD team membersto collaborate to a greater extent to develop productswith the appropriate features and to meet the projectdeadline. Projects with more individuals involvedtypically require a higher degree of collaboration astasks are divided among more individuals, and teamssubsequently need more collaboration to integrateand coordinate tasks. A more experienced NPD teamtends to have a better capability to leverage the collec-tive knowledge of the team and, therefore, should bemore likely to rely on collaborative efforts to solveproblems during the development processes. Finally,as our project samples were drawn from plants indifferent geographical regions and industries, it is


necessary to control for potential cross-region andcross-industry differences. To maintain model parsi-mony, the final empirical models exclude the controlvariables that do not exhibit significant effects onNPD collaboration. These variables are team experi-ence and geographical regions.As the relevant data were self-reported by a single

member of the product development team, weemploy two tests to check for common method vari-ance (CMV): (i) Harman’s one-factor test and (ii) mar-ker variable test. In Harman’s one-factor test, all themeasurement scales were subjected to an exploratoryfactor analysis to determine whether a single factoraccounts for the majority of the covariance in themeasures. No single dominant factor emerged. Thelargest factor explains only 22% of the total variance.The marker variable test involves correcting item cor-relations that may have been inflated by CMV andassessing the extent to which the corrected item corre-lations deviate from the uncorrected ones (Lindelland Whitney 2001). We used the second lowest posi-tive correlation between the manifest items as a con-servative proxy for the correlation between a markervariable and the variables assumed to be theoreticallyunrelated to the marker variable in the researchmodel (Lindell and Whitney 2001). The CMV-adjusted item correlations are quite close to the itemcorrelations uncorrected for CMV. For our data, thepercentage difference in p-value between each CMV-adjusted correlation and the corresponding unad-justed correlation ranges from 0 to 3%. After adjustingfor CMV, 98% of the significant uncorrected correla-tions (p < 0.10) are still significant. The above resultssuggest that CMV is not evident in our data.

4.3. Construct Validity and ReliabilityWe examine the reliability and validity of the scalemeasures using Partial Least Square (PLS). PLS is acomponent-based structural equation modeling tech-nique that has less strict distributional assumptionsand can be used for relatively small samples (Chin1998). The appropriateness of PLS for our study is dis-cussed in section 5.1. For our data, the standardizeditem factor loadings for each multi-item scale are allabove 0.50, with only one exception (0.38).1 Each itemhas the highest item factor loading on the factor it isexpected to load upon. Composite reliability is greaterthan 0.70 for each measurement scale. Finally, Aver-age Variance Extracted (AVE), the percentage of over-all variance in the indicators explained by the latentconstructs, is above 0.50 for each measurement scale,with product design IT tools as the only exception,which has an AVE just below 0.50 (i.e., 0.49).Discriminant validity was assessed using the Chi-square (v2) difference test (Bagozzi and Phillips 1982).A significant v2 difference indicates the uniqueness of

the two scales being tested. Each pair-wise v2 differ-ence test is significant (p < 0.01), providing evidenceof discriminant validity. Overall, measurement valid-ity and reliability appear satisfactory.Because we conceptualize collaboration as a higher

order construct encompassing cross-functional collab-oration, customer collaboration, and supplier collabo-ration, we tested a second-order factor model ofcollaboration that has cross-functional collaboration,customer collaboration, and supplier collaboration asthe three first-order factors. We followed the guidanceprovided by Yi and Davis (2003) and Pavlou and ElSawy (2006) for examining second-order factor mod-els using PLS, in which factor scores of the first-orderfactor were computed, which were then used as theindicators of the second-order factor. The second-order factor loading is 0.70 for cross-functional collab-oration, 0.79 for customer collaboration, and 0.77 forsupplier collaboration. Each factor loading is signifi-cant (p < 0.01). The high second-order factor loadingssuggest that NPD teams tend to collaborate on allthree aspects.Construct level descriptive statistics and correlation

matrix are reported in Table 2.

5. Analysis and Results

5.1. Analysis MethodsOur hypotheses state that the IT tools and NPD prac-tices are associated with collaboration to a differentextent depending upon the level of project complex-ity, suggesting fit as moderation. A fit as moderationhypothesis specifies “the effect of a predictor variableon a criterion (dependent) variable is dependent on athird variable” (Venkatraman 1989). Prior literaturehas suggested several methods for testing fit as mod-eration, each with a different theoretical underpin-ning. Moderated regression is recommended ifresearchers specify that the criterion variable is jointlydetermined by the predictor and the moderator(Arnold 1982), whereas multiple-group analysis isrecommended when researchers propose that theimpact of the predictor variable on the criterion vari-able differs across different levels of the moderator(Arnold 1982). Because our moderation hypothesesstate that IT tools and NPD practices will be associ-ated with collaboration to a different extent acrossdifferent levels of project complexity variables, thesehypotheses can be appropriately tested using multi-ple-group analysis. This analysis strategy has beenused by researchers to study product developmentacross different levels of environmental uncertainty(Eisenhardt and Tabrizi 1995).Given the multiple hypothesized paths from NPD

practices and from the four types of IT tools to collabo-ration, it is appropriate to test these relationships


simultaneously using structural equation modeling(SEM). We used PLS graph 3.0 to perform the SEManalysis for three reasons. First, the sample size forthe subgroup analysis is relatively small. As PLS isregression based, researchers can use PLS to estimateresearch models using a relatively smaller sample(Chin 1998). PLS is also preferred for testing modera-tion effects using subgroup analysis (Qureshi andCompeau 2009). Second, our research seeks to exam-ine the contingency relationships between varioustypes of IT tools and NPD collaboration. As these rela-tionships have not been tested in prior studies, theprediction-oriented PLS method should be appropri-ate (Chin 1998). Third, PLS is appropriate for estimat-ing research models with single-item constructs. Ourresearch model includes a number of single-item con-structs and therefore using PLS is reasonable (Chinet al. 2003).Prior to the analysis, we examined the distribution

of each variable with respect to skewness and kurto-sis. We also visually checked the distribution of eachvariable. None of the variables exhibits significantskewness or kurtosis, and each variable has anapproximately bell-shaped distribution.

5.1.1. Structural Equation Modeling with theComplete Sample. Figure 2 summarizes the resultsof the model based on the complete sample. For con-ciseness and clarity of presentation, item factor load-ings and path coefficients of the control variables arenot shown in the figure.

5.1.2. Structural Equation Modeling by ProjectComplexity Groups. To create groups based on pro-ject complexity, we ranked the sample NPD projectsalong each of the three project complexity dimen-sions. We then median split the sample projects byproduct size, project novelty, and task interdepen-dence, respectively. For each project complexitydimension, projects with a score above the medianvalue of that dimension belong to the “higher” group,and projects with a score at or below the medianvalue were assigned to the “lower” group. Within the“higher” group and the “lower” group of each projectcomplexity dimension, the research model was tested.The results of SEM by groups are presented inFigure 3. To examine model robustness, we also testedthe model using different splits of the sample whenpossible, including 40–60%, 45–55%, 55–45%, and 60–40%, and the results are consistent with the mediansplit.To further check the robustness of our results, we

examined alternative models that include interactioneffects between NPD practices and each of the fourtypes of IT tools. We also tested models that includethe squared terms of NPD practices and each of theTa

ble2

Descriptive

StatisticsandCorrelation

Matrix

Mean

Min

Max

SD

12

34

56

78

910

11

1Em

ailgrou

pware

4.65

17

2.03

2Product

design

ITtools

5.22

1.32

9.24

1.87

0.28

*

3Project

Mgm

tIT

tools

3.95

17

1.93

0.32

*0.47

*

4Sharedpartsdatabases

4.60

17

1.66

0.27

*0.26

*0.20

*

5New

prod

uct

developm

ent

practices

5.46

1.42

9.94

1.74

0.22

*0.32

*0.34

*0.04

6NPDcollaboration

8.43

3.99

11.75

1.48

0.26

*0.39

*0.32

*0.14

**

0.37

*

7Product

size

(num

ber

ofparts)

773

212

,000

1,845

0.07

�0.01

�0.01

0.31

*0.07

0.05

8Project

novelty

85

142.21

0.14

**

0.03

0.12

***

�0.04

0.10

0.08

�0.10

9Task

interdependence

5.38

27

1.06

0.20

*0.26

*0.25

*0.11

0.33

*0.18

*0.13

***

0.15

*

10Project

priority

5.23

27

1.02

0.10

0.24

*0.14

**

0.01

0.19

*0.05

0.12

***

0.11

0.25

*

11Num

berof

individu

als

involved

29.86

250

063

.58

0.17

**

0.20

*0.13

***

0.21

*0.22

*0.13

***

0.42

*0.01

0.21

*0.30

*

12Average

team

experience

(year)

9.67

035

5.04

�0.10

�0.02

�0.21*

�0.06

�0.05

0.03

0.18

*�0

.18*

�0.07

0.00

�0.05

*p<0.01

,**

p<0.05,**

*p<0.10

;factor

scores

ofprod

uctdesign

ITtools,

NPDpractices,andNPDcollabo

rationareshow

nin

theabovetable.


IT tools. None of the interaction effects or squaredterms is significant at the 0.05 level. These resultsindicate that the hypothesized relationships arerobust. Furthermore, the lack of significant interactioneffects between NPD practices and IT tools indicatesthat NPD practices and IT tools can impact NPDcollaboration independently. This result is consistentwith our view that NPD practices and IT tools areconceptually different and may affect collaborationindependently.

5.2. Analysis ResultsOur results are summarized in Table 3. H1a throughH1d predict that the four types of IT tools will be pos-itively associated with collaboration. Among the fourtypes of IT tools, product design IT tools have a sig-nificant positive relationship with collaboration (p <0.05). This positive association is also evident for pro-ject management IT tools, although the significancelevel is somewhat weak (p < 0.10). Thus, H1b andH1c are supported but not H1a or H1d. NPD prac-tices exhibit a highly significant positive associationwith collaboration (p < 0.01). This result supports H2.H3a states that IT tools will be more closely related

with collaboration for NPD projects that developproducts of larger product size, whereas H3b statesthe opposite holds for NPD practices. For the higherproduct size group, product design IT tools have asignificant association (p < 0.05) with collaboration,and email groupware and project management toolseach have a marginally significant relationship(p < 0.10) with collaboration, whereas for the lower

product size group, only project management IT toolsare marginally related with collaboration (p < 0.10).Thus, there is some evidence supporting H3a. NPDpractices have a fairly consistent association with col-laboration between the higher and the lower productsize group. This result does not lend support to H3b.H4a suggests that IT tools should have a smaller

association with collaboration for NPD projects with ahigher degree of novelty, whereas H4b states thatNPD practices will have a greater association withcollaboration under the same circumstance. Again,we found some evidence supporting H4a. For thehigher project novelty group, NPD practices arehighly significantly related with collaboration. Withrespect to the IT tools, only product design IT toolsexhibit a positive and marginally significant associa-tion with collaboration (p < 0.10). For the lower pro-ject novelty group, NPD practices have no significantrelationship with collaboration. However, productdesign IT tools have a more significant associationwith collaboration (p < 0.05). Furthermore, projectmanagement IT tools also exhibit a marginally signifi-cant association with collaboration (p < 0.10). Thus,there is some evidence supporting H4a and strongevidence supporting H4b.Finally, H5a states that for projects with higher task

interdependence, IT tools will have a smaller associa-tion with collaboration, whereas H5b suggests theopposite holds for NPD practices. For projects with ahigher task interdependence, none of the IT tools hasa significant association with collaboration. For pro-jects with a lower task interdependence, productdesign IT tools and project management IT tools arepositively associated with collaboration (p < 0.05).Thus, there is evidence supporting H5a. NPD prac-tices exhibit a strong positive association with collabo-ration when task interdependence is higher, whereasthey are not significantly related with collaborationwhen task interdependence is lower. These resultssupport H5b.

6. Discussion and Conclusion

6.1. Implications for TheoryThis study examines the associations between fourtypes of IT tools and NPD collaboration and betweenNPD practices and NPD collaboration under theproject complexity contingencies of product size, pro-ject novelty, and task interdependence. Little researchhas explored the role of IT tools in enhancing NPDcollaboration. Even less is known about the contin-gency effect of IT tools on NPD collaboration givenspecific characteristics of project complexity. To thebest of our knowledge, our study is one of the firstthat develops and tests a contingency frameworkexamining the relationships between specific IT tools

NPD practices

Product design IT tools

CAD, CAPP, Simulationmodeling

NPD collaboration

Comm. IT toolsEmail

Groupware

Project mgmt.IT tools

Project mgmt. software

Product data and knowledge mgmt. IT tools Shared parts

databases

0.26**

0.14 †

ns

ns

0.17*

R2=0.26

Figure 2 Structural Equation Modeling Using the Full Sample

Control Variables: Team Size, Project Priority, Team Experience, and

Industry Sectors. †p < 0.10, *p < 0.05, **p < 0.01, ns denotes

“Not Significant”


and NPD collaboration and between NPD practicesand NPD collaboration.The contributions of our study are fourfold. First,

our research provides empirical evidence that theassociations between certain types of IT tools and

collaboration are moderated differently by the threedimensions of project complexity. Our researchextends the contingency view of the impact of IT to anNPD project context, whereas previously this line ofresearch has largely focused on the firm level or theindividual user level. Second, our research findingscan potentially provide insights about the relation-ships between the four types of IT tools we examineand NPD collaboration. In contrast, the existing litera-ture tends to use aggregated IT constructs. Third, ourstudy contrasts the association between IT tools andcollaboration and between NPD practices and collab-oration, allowing us to delineate different collabora-tion strategies (i.e., an NPD team’s relative emphasison IT tools or NPD practices as means for collabora-tion) available to an NPD team for coping with infor-mation contingencies due to differing projectcomplexity. Finally, we conceptualize and operation-alize NPD collaboration as a broad construct tran-scending cross-functional collaboration, customercollaboration, and supplier collaboration. In contrast,previous NPD literature has mostly examined colla-boration or integration between internal functions(e.g., Song and Song 2010). Krishnan and Loch (2005)suggest that collaboration with suppliers and partnersis an understudied research topic. As customers and

Table 3 Summary of Results

H1a: Communication IT tools ?collaboration

Not supported

H1b: Product design IT tools ?collaboration

Supported

H1c: Project management IT tools ?collaboration

Supported

H1d: Product data and knowledgemanagement IT tools ? collaboration

Not supported

H2: NPD practices ? collaboration SupportedH3a: NPD IT tools ? collaborationmoderated by product size

Supported

H3b: NPD Practices ? collaborationmoderated by product size

Not supported

H4a: NPD IT tools ? collaborationmoderated by project novelty

Supported

H4b: NPD Practices ? collaborationmoderated by project novelty

Supported

H5a: NPD IT tools ? collaborationmoderated by task interdependence

Supported

H5b: NPD Practices ? collaborationmoderated by task interdependence

Supported

Control variables: team size, project priority, team experience, industry sectors† p < 0.10, * p < 0.05, ** p < 0.01, ns denotes “not significant”

NPD Practices

Product Design IT tools

NPD Collaboration

Email Groupware

Project Mgmt. IT tools

Shared Parts DB

0.30**

0.14†

ns

0.13†

0.19*

R2=0.34

Subgroup with a higher product size

NPD Practices


NPD Collaboration

Email Groupware

Project Mgmt.IT tools

Shared Parts DB

0.42**

ns

ns

ns

0.18*

R2=0.35

Subgroup with a higher project novelty

NPD Practices


NPD Collaboration

Email Groupware


Shared Parts DB

0.40**

ns

ns

ns

ns

R2=0.27

Subgroup with a higher degree of task interdependence

NPD Practices


NPD Collaboration

Email Groupware


Shared Parts DB

0.33**

0.13†

ns

ns

ns

R2=0.23

Subgroup with a lower product size

NPD Practices


NPD Collaboration

Email Groupware


Shared Parts DB

0.15†

ns

ns

0.20*

R2=0.21

Subgroup with a lower project novelty

ns

NPD Practices


NPD Collaboration

Email Groupware


Shared Parts DB

ns

0.20*

ns

ns

0.30*

R2=0.25

Subgroup with a lower degree of task interdependence

Figure 3 Structural Equation Modeling Using Subgroups of Project Complexity


suppliers are increasingly involved in the focal firm’sNPD efforts, it is necessary to consider customercollaboration and supplier collaboration as constitu-ents of NPD collaboration.Overall, many of the relationships between IT tools

and collaboration and between NPD practices andcollaboration are moderated by project complexityvariables. In particular, task interdependence andproject novelty exhibit quite evident moderationeffects. These findings resonate with prior researchsuch as Eisenhardt and Tabrizi (1995), who found thateffective practices and tools for accelerating productdevelopment can vary considerably between projectswith a high or low degree of uncertainty. In general,our findings are consistent with the theoretical predic-tion that when causal ambiguity is resolved andknowledge is sufficiently well codified to become“embeddable” into IT tools, using these tools shouldhelp improve task execution and collaboration(Barczak et al. 2009). Among the four types of IT toolsexamined, product design IT tools and project man-agement IT tools appear to have a stronger associationwith collaboration. The lack of significant associationbetween email groupware and collaboration mayarise from the fact that our research does not focusspecifically on distributed product development.Prior research suggests email groupware can play amore important role in a distributed product devel-opment environment (Boutellier et al. 1998, Montoyaet al. 2009). It may also be that email groupware hasbeen used so extensively by the majority of theNPD teams in our sample that there is no systematicvariation to explain the relationship between emailgroupware and collaboration. Next, the finding thatshared parts databases have no association with col-laboration in any of the project environments issomewhat counterintuitive. Prior research alludes tothe possibility that the limited scope of shared partsdatabases can adversely affect the impact of thesedatabases (Boutellier et al. 1998). For some sharedparts databases, the inadequate accessibility andlack of inter-operability with other IT tools can alsolimit their impact (Liu and Xu 2001). Future research isneeded to shed light on this seemingly counterintui-tive finding.

6.2. Managerial ImplicationsNPD projects inherently involve some degree of com-plexity and uncertainty. To cope with the complexityof NPD projects, project teams often adopt formaldesign methodologies and information organizingframeworks in the form of various NPD practices.Such practices expect team members to interact fre-quently, often face-to-face, to resolve informationambiguity. However, this form of collaboration, ifused excessively, can slow down an NPD project by

distracting team members from executing theirassigned tasks. Our findings suggest that projectteams may be able to accomplish collaborationthrough a balanced use of NPD practices and IT toolswhen project goals and tasks can be clearly defined.Project managers should develop a collaboration

strategy that balances the need to process informationeffectively (i.e., reduce information ambiguity) andefficiently (i.e., increase information processingvolume and speed). For projects with higher informationambiguity, more emphasis should be placed uponNPD practices that provide an effective way forinterpreting, clarifying, and organizing information.IT tools can subsequently be used to distribute andexchange the organized information. However, for aproject with lower information ambiguity, theamount of effort needed to reduce informationambiguity is greatly reduced. The project teamshould focus on efficiently executing design tasks. Inthis situation, IT tools should be adopted to a highdegree to automate information sharing and distri-bution between team members. For instance, if anNPD team is designing a product that is largelybased on an existing platform and can reuse ormodify many existing components and parts, thenthe project manager should reduce the time-consum-ing coordinating activities, such as frequent projectstatus meetings, and instead provide IT tools forteam members to coordinate and access information.To help project managers devise an appropriate col-laboration strategy, our results provide some exam-ple project environments where NPD practices or ITtools should be used to a relatively greater extent.Our research also offers useful managerial implica-

tions regarding the adoption and use of specific ITtools in product development. Technology account-ability has become a significant issue in corporations(Coleman 1993). A managerial challenge is to use theright technology in the right place at the right time(Durmusoglu et al. 2006). Because adopting IT toolspresents a cost to a project team, when IT tools alonedo not meet the need for project collaboration, NPDteams should explore alternative means for collabora-tion. As we capture various types of actual IT toolsused by product development teams, our findings canpotentially provide actionable insights regardingwhat types of IT tools should be used to a greaterextent in specific project environments.

6.3. Limitations and Future ResearchThis study exhibits several limitations. First, theresearch design employed a single respondent.Although many existing studies have adopted asingle respondent strategy for data collection, usingmultiple respondents may help reduce potential com-mon method variance and enhance the richness of


data. Second, we use a single item to capture taskinterdependence. As task interdependence is mea-sured based on the respondent’s perception, using amulti-item measure for task interdependence mayenhance the construct validity and reliability. Also,while our research examines several types of IT tools,these IT tools tend to be used more heavily for collab-oration internally and with suppliers. There are manyother IT tools, including newer forms of collaborationtools such as wikis and blogs that can be used in prod-uct development but are not examined in ourresearch. The current study is limited by the dataavailable to us. Future research should employ a morerigorous research design and develop improved mea-surement instruments to reexamine the hypotheses ofthis study. Finally, with a cross-sectional researchdesign, we cannot draw a causal conclusion that ITtool use leads to a higher level of collaboration.Although it is widely proposed that IT tool use can

enhance project collaboration and ultimately projectsuccess, empirical research examining the contin-gency factors that may affect the impact of IT tools isstill at the preliminary stage. We hope the currentresearch can stimulate future studies in this directionas there are perhaps many interesting findings yet tobe discovered.

Acknowledgments

We appreciate helpful comments from the departmenteditor, an associate editor, two referees, the past departmenteditor Christian Terwiesch, and Anant Mishra.

Appendix A: Measurement Items

ConstructsStd. factorloading T-value

New product development collaborationCross-functional collaboration 0.82*, 0.53†

New product design teams have frequentinteraction with the manufacturing function.

0.81 16.93

Manufacturing is involved in the earlystages of new product development.

0.73 8.94

The manufacturing function is involved inthe creation of new product concepts.

0.65 7.03

New product concepts are developed as aresult of the involvement of various functions.

0.72 8.64

Supplier collaboration 0.89*, 0.67†

Suppliers were involved early in thedesign efforts in this project.

0.87 32.10

We partnered with suppliers for thedesign of this product.

0.81 22.48

Suppliers were frequently consultedabout the design of this product.

0.83 22.51

Suppliers were an integral part of thedesign effort.

0.76 11.53

(continued)

Appendix continued


Customer collaboration 0.88*, 0.61†

We consulted customers early in thedesign efforts for this product.

0.80 20.80

We partnered with customers for thedesign of this product.

0.82 21.06

Customers were frequently consultedabout the design of this product.

0.66 9.03

Customers became involved in thisproject only after the design wascompleted.

0.77 16.71

Customers were an integral part of thedesign effort for this project

0.86 28.27

NPD IT toolsProduct design IT tools 0.74*, 0.50†

Computer-aided design 0.49 3.90Computer-aided process planning 0.83 13.25Simulation modeling 0.76 9.13

Email groupware, such as Lotus Notes - -Project management software(e.g., Microsoft Project)

- -

Shared parts database - -NPD practices 0.73*, 0.49†

Design for manufacturability 0.65 6.45Rapid prototyping 0.71 8.90House of quality or quality functiondeployment

0.79 16.90

Project noveltyNewness of product designThis product was: 0.51

1. A derivative product basedon modifications to existing products.

2. A platform product for startinga new product line.

3. A breakthrough product withnew technology.

Similarity to existing productsThis product was: 0.56

1. Similar to our existing products.2. Different from what we have

manufactured, but similar to productsoffered by our competitors.

3. Different from what we havemanufactured, and no similarproducts were offered by our competitors.

Newness of product marketThe market for the product was: 0.38

1. An existing market that weserved.

2. An existing market, but newto this company.

3. The market did not exist prior todevelopment of this product.

Newness of product technologyThe product technology for thisproduct was:

0.66

1. Available within the company.2. New to the company, butavailable from outside.

3. New to the world.

(continued)


Appendix continued


Newness of process technologyThe process technology used toproduce this product was:

0.58

1. Similar to technology we hadused before.

2. Required major changes inexisting manufacturing.

3. Completely new.Task interdependenceThe tasks in this project werehighly interdependent

- -

Product sizeWhat is the number of parts thatare required to make one unit?

- -

Project priorityThis project was a high priorityto our organization

0.74 11.74

Other projects took a back seatto this project because of itsimportance.

0.86 15.37

This was a low priority project(Reversed coded).

0.51 5.75

Average team experienceWhat are the approximate averageyears of experience of the projectteam members?

Project team sizeWhat is the total number of individualsinvolved in the project

*Composite reliability,†Average Variance Extracted.

Appendix B: Item-Level DescriptiveStatistics

Items Min Max Mean SD

New product developmentcollaborationNew product design teamshave frequent interaction withthe manufacturing function.

2 7 5.58 1.17

Manufacturing is involved inthe early stages of new productdevelopment.

1 7 5.31 1.31

The manufacturing function isinvolved in the creation of newproduct concepts.

1 7 5.04 1.31

New product concepts aredeveloped as a result of theinvolvement of various functions.

1 7 4.64 1.33

Suppliers were involved early inthe design efforts in this project.

1 7 4.85 1.45

We partnered with suppliers forthe design of this product.

1 7 4.84 1.41

(continued)

Appendix continued

Items Min Max Mean SD

Suppliers were frequentlyconsulted about the design ofthis product.

1 7 4.90 1.49

Suppliers were an integral part ofthe design effort.

1 7 4.64 1.59

We consulted customers early inthe design efforts for this product.

1 7 5.11 1.46

We partnered with customers forthe design of this product.

1 7 4.81 1.66

Customers were frequentlyconsulted about the design ofthis product.

1 7 4.78 1.50

Customers became involved in thisproject only after the design wascompleted.

1 7 5.24 1.53

Customers were an integral part ofthe design effort for this project

1 7 4.83 1.53

NPD IT toolsComputer-aided design 1 7 6.19 1.29Computer-aided processplanning

1 7 3.25 1.87

Simulation modeling 1 7 4.04 2.00Email groupware, such asLotus Notes

1 7 4.65 2.03

Project management software(e.g., Microsoft Project)

1 7 3.95 1.93

Shared or common partsdatabase

1 7 4.6 1.66

NPD practicesDesign for manufacturability 2 7 5.54 1.23Rapid prototyping 1 7 4.20 1.46House of quality or qualityfunction deployment

2 7 5.96 1.14

Project noveltyNewness of product design 1 3 1.74 0.76Similarity to existing products 1 3 1.76 0.82Newness of product market 1 3 1.32 0.58Newness of product technology 1 3 1.45 0.66Newness of process technology 1 3 1.36 0.57

Task interdependenceThe tasks in this project werehighly interdependent

2 7 5.38 1.06

Product sizeWhat is the number of parts thatare required to make one unit?

2 12,000 773 1845

Project priorityThis project was a high priority toour organization

2 7 5.54 1.23

Other projects took a back seatto this project because of itsimportance.

1 7 4.20 1.46

This was a low priority project(Reversed coded).

2 7 5.96 1.14

Average team experienceWhat are the approximate averageyears of experience of the projectteam members?

0 35 9.67 5.04

Project team sizeWhat is the total number ofindividuals involved in the project

2 500 29.86 63.58


Note1We tested models with and without the item with lowloading and the results are consistent.

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