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This is to certify that the

dissertation entitled
ENHANCING FIRM INNOVATION PERFORMANCE

THROUGH STRATEGIC MANAGEMENT
OF NEW PRODUCT DEVELOPMENT

presented by

Yushan Zhao

has been accepted towards fulﬁllment
of the requirements for

Ph.D. degree in Business Administration

 

 

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2/05 (:EIRC/Dataoueindd-p. 15

ENHANCING FIRM INNOVATION PERFORMANCE THROUGH STRATEGIC
MANAGEMENT OF NEW PRODUCT DEVELOPMENT
By

Yushan Zhao

AN ABSTRACT OF A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Marketing and Supply Chain Management
The Eli Broad Graduate School of Management

2001

Professor Roger Calantone

ABSTRACT

ENHANCING FIRM INNOVATION PERFORMANCE THROUGH STRATEGIC
MANAGEMENT OF NEW PRODUCT DEVELOPMENT

By

Yushan Zhao

This dissertation addresses the important issue of “how not to make things” in
new product development (NPD). As increasing competitive pressure forces the firm to
greatly reduce costs, improve quality, and shorten development time, making the best use
of internal resources and capabilities is not sufficient for NPD program success.
Mobilizing resources and capabilities beyond ﬁrm boundaries becomes a necessity for
the full implementation of new product strategies.

A “barbell-shaped” conceptualization of NPD, in contrast to the traditional
“football-shaped” NPD, is proposed for the incorporation of other ﬁrms’ resources and
capabilities in the ﬁrm’s NPD. “Football-shaped” NPD represents the traditional “do-it-
all” paradigm, while “barbell-shaped” NPD allows other ﬁrms to “share the burden.”

"Barbell-shaped" NPD is based on the integration of internalization theory and the
resource-based view of the ﬁrm. The two theories stress, from different perspectives, the
importance of mobilizing other ﬁrms’ resources and capabilities in NPD. Internalization
theory emphasizes using other ﬁrms’ resources and capabilities to minimize total NPD
costs, to increase speed, and to improve quality. The resource-based view of the ﬁrm
concentrates on protecting ﬁrm core competencies and accessing other firms’ valuable
resources and capabilities. The two theories converge on the premise of this dissertation:

i.e., that the ﬁrm should internalize NPD tasks that are closely related to its core

competencies and extemalize complex and less important ones to improve NPD
efficiency.

Two models are proposed in this dissertation. The first model aims at
investigating which tasks should be internalized and which should be given to other
ﬁrms. The bottom line is that the ﬁrm should protect and strengthen its core
competencies in NPD. Therefore, it can concentrate on the tasks that affect firm core
competencies. Less important and complex tasks, which require resources that are not
available internally or capabilities not easily developed internally, can be given to other
ﬁrms thus accessing their “best-in—world” resources and capabilities.

The second model explores how to enhance NPD capability through interactions
with other ﬁrms. It illustrates how the ﬁrm can enhance NPD capability by acquiring tacit
knowledge from strong relationships and novel knowledge from weak relationships and
from firms that are unique in relationships.

A large portion of this study is driven by the major concerns of NPD managers.
This study provides managerial guidelines on how to use external resources and
capabilities to the greatest extent. This dissertation also assists NPD managers in
developing a strategy for managing different kinds of relationships. Both strong and weak
relationships can be equally valuable for NPD program success. Tacit or uncoded
knowledge is likely from strong relationships and novel knowledge is likely from weak

relationships or ﬁrms that are unique in the relationships.

Copyright © by
Yushan Zhao

200 l

ACKNOWLEDGEMENTS

I would like to thank the members of my doctoral committee. In particular, I
would like to extend special gratitude to Dr. Roger J. Calantone for his support and
guidance. Without his direction, this dissertation would have been impossible. I remain
deeply indebted to Dr. Michael Song, Dr. S. Tamer Cavusgil, Dr. Cornelia Droge, and Dr.
Joseph Bonner for the valuable contributions they made to this work, as well as their
guidance during the doctoral program.

This dissertation is also dedicated to my wife Liping, my son Xiaoyu, and my

daughter Linda.

TABLE OF CONTENTS

Item Page
LIST OF TABLES ........................................................................ vii
LIST OF FIGURES ....................................................................... viii
LIST OF ABBREVIATIONS ........................................................... ix
CHAPTERI
INTRODUCTION ........................................................................ 1
CHAPTER 2
MODEL l—ENHANCING FIRM NPD PROGRAM PERFORMANCE
THROUGH EXTERNALIZATION ................................................... 24
CHAPTER 3
MODEL 2—ENHANCING FIRM NPD CAPABILITY THROUGH
KNOWLEDGE TRANSFER ........................................................... 40
CHAPTER 4
METHODOLOGY ........................................................................ 52
CHAPTER 5
FIRST MODEL TESTING AND ANALYSIS ........................................ 64
CHAPTER 6
SECOND MODEL TESTING AND ANALYSIS .................................... 89
CHAPTER 7
DISCUSSION AND CONCLUSION .................................................. 104
REFERENCES ............................................................................ 118

vi

Table

1.1

4.1

4.2

4.3

4.4

4.5

5.1

5.2

5.3

5.4

5.5

5.6

5.7

5.8

6.1

6.2

6.3

6.4

6.5

LIST OF TABLES
Caption

Externalization Decision Based on Internalization Theory and
Resource-Based View of the Firm ...................................

Distribution of Sample by Industry ..................................
Distribution of Sample by Firm Size .................................
Respondent Characteristics ............................................
Results of Non-response Bias Testing ...............................
Comparison of Sample to Population ................................
Results of Conﬁrrnatoty Factor Analysis ............................
Ten Four-Factor Models ...............................................
Comparison of Five-Factor Model with Ten Four-Factor Models
Interfactor Correlation .................................................
Correlation Matrix of Factors (not mean-centered variables). . ..
Correlation Matrix of Mean-Centered Factors ......................
R2 Difference Test of Interaction Term ..............................
Results of Seemingly Unrelated Regression Analysis ..............
Relationship Strength Second-Order Measurement Modei. . . . .
Results of Conﬁrmatory Factor Analysis ............................
Interfactor Correlation .................................................
Results of Path Analysis ................................................

Results of Two—Group Comparison ...................................

vii

Page

16

59

60

60

62

63

66

7O

72

73

75

76

78

8O

91

94

97

98

102

LIST OF FIGURES

Figure Caption Page

1.1 Paradigm Shift of NPD in the PC Industry ........................... 8

1.2 Paradigm Shift of NPD—The Firm A Case .......................... 9

1.3 Paradigm Shift of NPD—The Firm B Case .......................... 10
1.4 New Paradigm of NPD in Heavy Machinery Industry .............. 11
1.5 Metaphorical Description of the Paradigm Shift in NPD .......... 12
1.6 The Conceptual Framework ............................................ 15
2.1 Enhancing Firm NPD Performance Through Extemalization. . 24

3.1 Enhancing Firm NPD Capability Through Knowledge Transfer 41
5.1 Measurement Model ................................................... 68
5.2 Complexity—Externalization Relationship ......................... 82

5.3 Moderating Effect of Importance on Extemalization—NPD

Capability Relationship ................................................ 84
5.4 Extemalization—NPID Capability Relationship .................... 85
5.5 Moderating Effect of Importance on Extemalization—NPD

Program Performance Relationship ................................... 86
5.6 Extemalization—NPD Program Performance Relationship. . 87
6.1 Path Model ............................................................. 99
7.1 Three Types of Barbell Design ....................................... 109

viii

LIST OF ABBREVIATIONS

CFA ................................................................ CONFIRMATORY FACTOR ANALYSIS

CFI ................................................................. COMPARATIVE FIT INDEX

IFI ................................................................... INCREMENTAL FIT INDEX

MCI ................................................................ MAXIMUM CONDITION INDEX

NF I ................................................................. NORMED FIT INDEX

NPD ................................................................ NEW PRODUCT DEVELOPMENT

R&D ............................................................... RESEARCH AND DEVELOPMENT

RMSEA .......................................................... ROOT-MEAN-SQUARE ERROR
APPROXIMATION

VIF ................................................................. VARIANCE INFLATION FACTOR

ix

CHAPTER 1

INTRODUCTION

Firms need to learn how not to make things.

— Venkatesan (I 992)

New product development (NPD) is the set of activities beginning with the
perception of a market opportunity and ending in the production, sales, and delivery of a
new product (Ulrich and Eppinger 1995; Rogers 1995). Perhaps the most compelling
justiﬁcation for studying NPD is that organizations are less likely to survive without the
lifeblood of new products (Montoya-Weiss and Calantone 1994; Rogers 1995; Brown and
Eisenhardt 1995). Traditionally, NPD study typically emphasized the best utilization of
ﬁrm internal resources and capabilities. In recent years, the ﬁrm has begun to learn “how
not to make things” (Venkatesan 1992, p. 98)—how to give some tasks to other ﬁrms
which could accomplish them more efﬁciently, i.e., how to use resources and capabilities

beyond ﬁrm boundaries (Veugelers and Cassiman 1999).

The Need for Using Other Firms’ Resources and Capabilities
The ﬁrm is still not clear about how to prevail in NPD (Damanpour 1991b;
Montoya-Weiss and Calantone 1994; Rogers 1995; Brown and Eisenhardt 1995; Wind
and Mahajan 1997). Fast shifting consumer preferences, high rate of technical
obsolescence, short product life cycle, and increasing NPD cost force the ﬁrm to greatly

reduce cost, improve quality, and shorten development time (Monczka and Trent 1991;

Grifﬁn 1997a, 1997b; Fine 1998). Xerox, for example, is pressed by brutal competition
from Japanese competitors and faces a painful choice: either slash its traditional product
development cycle, or be overtaken by more nimble competitors (Wysocki, Jr. 1999).

Evidence from a variety of industries shows that making the best use of internal

resources and capabilities is not sufﬁcient for NPD success in today’s highly competitive
environment (Kurokawa 1997; Venkatesan 1992; Millson, Raj, and Wilemon 1996;
Hansen 1999; Lowe and Taylor 1998; Monczka, et a1. 2000; Krause, Scannell, and
Calantone 2000). The ﬁrm ﬁnds that giving some tasks to other ﬁrms is a necessity for
the full implementation of new product strategies (Quinn and Hilmer 1994; Goes and
Park 1997; Veugelers and Cassiman 1999; Rubenstein 1994). The ﬁrm can thus focus its
limited resources on important tasks and fulﬁll them with great quality and high speed. At
the same time, this strategy allows other ﬁrms to “share the burden” of NPD; other ﬁrms’
expertise is incorporated into the NPD process (Quinn 1999). The following examples
from industry highlight this trend.

0 Japanese car companies provide general speciﬁcations to suppliers and then
expect them to design the parts as the car is being developed, a process called
"design-in" (Dutton 1992).

0 Chrysler has stopped writing detailed speciﬁcations for many parts. Instead, it
relies on suppliers to design and build the right parts and to ﬁnd ways to lower
prices. Chrysler and the supplier split the savings (Minahan 1998).

0 Whirlpool, McDonnell Douglas, and Boeing have shifted many of their design

activities to other ﬁrms (Proctor 1999).

0 Apple let Sony, the Japanese company specialized in miniaturization, to
design the structure of the PowerBook. The PowerBook's size was reduced
and the development time was shortened (Magee 1992).

The problem of resource limitations in NPD and the tapping of outside resources
has been noted in reviews by Damanpour (1991b), Rogers (1995), Montoya-Weiss and
Calantone (1994), and Brown and Eisenhardt (1995). They all recognize that internal
resources and capabilities are not sufﬁcient for the full implementation of new product
strategy and call for the mobilization of resources outside of the ﬁrm. Rogers (1995)
noted the necessity to explore inter-ﬁrm relationships in R&D. Brown and Eisenhardt
(1995) put suppliers and customers in their comprehensive framework of NPD and stress
the importance of supply chain partners for new product performance. Montoya-Weiss

and Calantone (1994) also noticed the need to explore factors outside of the ﬁrm.

Internalization and Externalization of NPD Tasks

In this study, the unit of analysis is the ﬁrm’s NPD program. At the lowest level of
detail, a new product development program is divisible into a number (usually large) of
individual tasks that collectively deﬁne the new product development program (Yassine
and Falkenburg 1999). NPD tasks, therefore, are the basic activities of the NPD program.
They are unique and yet related. The accomplishment of a certain NPD task requires
employing and allocating speciﬁc resources and capabilities. Because the ﬁrm is unlikely
to possess all of the required resources and capabilities for all the NPD tasks of a NPD
Program, strategically managing different NPD tasks in a NPD program becomes an

Important issue.

Internalization of a NPD task means that the ﬁrm does the NPD task in-house
(Veugelers and Cassiman 1999; Kurokawa 1997; Robertson and Gatignon 1998). If the
ﬁrm performs a NPD task itself, it is internalizing the task. Externalization, in contrast,
refers to the performance, by outside parties, of NPD tasks that would otherwise be
performed in-house (Venkatesan 1992). Externalization of an NPD task means that the
ﬁrm lets other ﬁrms perform the task (Quinn 2000). Currently some writers refer to this
as an outsourcing (Quinn 2000, 1999; Quinn and Hilmer 1994). The ﬁrm may provide
speciﬁcations of NPD tasks to other ﬁrms and allow them to develop the tasks to meet
the requirements of a NPD program (externalization of NPD tasks). The ﬁrm may absorb
knowledge from other ﬁrms to enhance its NPD capability and undertake a NPD task
relying on its own (the issue of acquiring knowledge from other ﬁrms to enhance NPD
capability is discussed extensively in Chapter 3).

The distinction between internalization and extemalization of NPD tasks lies in
who is responsible for the tasks being performed (Venkatesan 1992). Firms may jointly
work on a NPD program or part of the program, but are responsible for different tasks.
An example of internalization of NPD tasks is Coca-Cola’s internal development and
manufacture of its secret syrup. Vickers’ development of hydraulic systems for Natsteel’s
NPD program is a case of externalizing NPD tasks.

Tatikonda and Rosenthal (2000) identiﬁed two dimensions of a NPD task—
importance of the task and complexity of the task. The two dimensions capture the
Overall execution challenge posed by those tasks to the developing organizations (this
Will be discussed in detail in Chapter 2). First, if a task is important for the ﬁrm’s

Competitive strategies, it tends to be internalized. Second, if a task is so complex that the

ﬁrm does not possess the required resources and capabilities, or if a task is so complex

that the ﬁrm cannot develop it efﬁciently, extemalization of the task is suggested. This is

based on the fact that ﬁrms are complementary in nature, i.e., one ﬁrm’s weakness is

likely to be another ﬁrm’s strength (Quinn 2000).

The Research Questions

To identify important problems in NPD, relevant literatures were reviewed and

case studies were conducted in several ﬁrms. The results indicate that ﬁrm NPD

strategies are seriously affected by ﬁrm resource limitations. These problems can be

categorized into three classes.

1.

The ﬁrm recognized market opportunities, but lacked the requisite capabilities
to develop new products. The ﬁrm abandoned NPD plans because it was not
aware of the importance of using the resources of partner ﬁrms such as
suppliers, customers, and other ﬁrms. Valuable opportunities were missed.
The ﬁrm recognized the new product opportunity and developed new products
internally. But it developed new products poorly because either it did not
possess the requisite skills to achieve a high level of quality in certain NPD
tasks, or else it did not develop them fast enough and thus missed
opportunities. In either case, the ﬁrm jeopardized its new product success due
to its limited resources and capabilities.

The ﬁrm recognized the importance of using partner ﬁrms’ resources and
capabilities in NPD but poorly utilized these partner ﬁrms. There were two

scenarios. First, the ﬁrm ignored protection of its core competency, gave

 

crucial tasks to partner ﬁrms, and thus lost its competitive advantage in the
long run. Second, the ﬁrm did not fully understand how to strengthen its NPD
capability in interactions with other ﬁrms (similar scenarios can be found in
Millson, Raj, and Wilemon 1996).

The literature on extemalization in ﬁrm NPD is "imprecise" (Brown and
Eisenhardt 1995, p. 372). With the ﬁrm moving some tasks to partner ﬁrms, the literature
does not provide sufﬁcient guidance as to what kinds of tasks can be internalized and
what kinds of tasks can be extemalized. With some NPD tasks being closely related to
core competencies, the challenge for both practitioners and academicians is how to
protect ﬁrm core competencies while incorporating other ﬁrms' expertise in NPD. With
the ﬁrm needing knowledge from outside the ﬁrm, the literature is not clear about where
and how to get the required knowledge to improve ﬁrm NPD capability.

Questions thus arise about which NPD tasks should' be developed internally and
which tasks should be given to other ﬁrms to improve NPD efﬁciency and effectiveness.
Another closely related question would be how to enhance ﬁrm NPD capability through
interactions with other ﬁrms so that the ﬁrm can fully implement its new product
strategies. These are summarized into three research questions of this dissertation.

1. Which tasks should be developed by the ﬁrm itself so that ﬁrm core
competencies are protected and strengthened and NPD is performed more
effectively and efﬁciently?

2. Which tasks could be given to other ﬁrms so that other ﬁrms’ expertise is
incorporated into the NPD process and NPD program performance is

improved?

3. How to enhance ﬁrm NPD capability by interacting with other ﬁrms?

Two studies are conducted to address the above issues. The ﬁrst study aims at
investigating which tasks should be internalized and which should be given to other
ﬁrms. The second study explores how to enhance NPD capability through interactions

with other ﬁrms.

Paradigm Shift in NPD

In this dissertation, a “barbell-shaped” conceptualization of NPD, in contrast to
the traditional “football-shaped” NPD, is proposed for the incorporation of other ﬁrms’
resources and capabilities in the ﬁrm’s NPD. Case studies in the PC, heavy machinery,
and steel industries show a paradigm shift from “do it all” to “share the burden” in NPD.
Case Studies in Several Industries

The PC industry. Over the last ﬁfteen years, the ﬁrm in the PC industry has
experienced a fundamental paradigm shift in NPD. As shown in Figure 1.1, before 1985,
the ﬁrm was likely to internally develop most of the tasks. After the middle of 19805, the
ﬁrm has begun to focus on the development of the key tasks, assembled hardware, and let
other ﬁrms to perform the other tasks such as microprocessor, operating systems,
peripherals, application software, network services, etc., which are not closely related to

its core competencies (Fine 1998).

Microprocessors, Operating Systems,

Peripherals, Applications Software.
Network Services, Assembled Hardware

 

Before 1985

 

 

 

Microprocessors

Application
Software

 

 

 

 

Operating Systems

 

Network Services

 

 

 

 

 

Peripherals

   

/

Standard Parts

 

 

 

 

 

Note: Shaded areas represent internalized tasks

Adopted from

Fine (1998)

Figure 1.1: Paradigm Shift of N PD in the PC Industry

......... After 1985

 

Firm A, for example, developed most of the NPD tasks in-house before 1985.
After 1985, however, it has begun to focus on the assembled hardware and to externalize
application software and operating system to Microsoft, microprocessor to Intel, network
services to DEC, peripherals to Epson, etc. (see Figure 1.2). As one highly respected
senior R&D vice president stated: “You externalize when other companies can perform
the activity better than you.” Another said that companies should ask, “What is it we will

never be experts at or should not spend time doing?”

Microprocessors, Operating Systems.

 

Peripherals, Applications Software, Before 1985
Network Services, Assembled Hardware

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Intel Microsoft
(Microprocessors) (Application Software)
Microsoft DEC
(OperatingSystems‘l (Network Services) After 1985
Epson / Others
(Peripherals) (Standard Parts)

 

 

Note: Shaded areas represent internalized tasks

Figure 1.2: Paradigm Shift of NPD— The Firm A Case

The steel industry. Similarly in the steel industry, time-based pressure has forced
Firm B to undergo a fundamental change in NPD. Before 1980, Firm B internally
designed most NPD tasks. After 1980, it has begun to concentrate on the key technology,
the mainframe design, and to let Siemens (the expert ﬁrm on electric system) to design
the electric system, RAM (a ﬁrm that specializes in control) to design control systems,
Vickers (a ﬁrm experienced at hydraulic system) to design hydraulic systems, and CRD to
design grasp systems, thus incorporating other ﬁrms’ expertise in its own new product
development (see Figure 1.3).

Mr. Andrew Wang, Vice President of Engineering, made the following remarks in
the interview:

No one company acting alone can compete successfully with competitors

in NPD. Strategically externalizing some of NPD tasks can put a company

in a sustainable leadership position. It is the most powerful tool in NPD
management.

Main Frame, Control, Hydraulic, Before 1980

 

Grasp, Electric Systems

 

 

 

Electric Systems Hydrolic Systems

(Siemens) (Vickers)

Note: Shaded areas represent internalized tasks

 

   

 

 

.................. After 1980

 

 

Control Systems
(RAM)

Grasp Systems
(CRD)

 

 

 

 

 

 

Figure 1.3: Paradigm Shift of NPD — The Firm B Case

10

The heavy machinery industry. In the heavy machinery industry, ﬁrms like
Mannesmann, Kawasaki Heavy Industries, Ltd., and AIDA Corporation have
concentrated on the key technology of mainframe and given feeding speed control, pump
design, temperature control, and mold design to other ﬁrms to speed up new product
development (see Figure 1.4). One executive mentioned that externalizing NPD tasks
allowed the ﬁrm to do more without additional employees or with fewer employees. Even

companies with highly developed NPD capabilities have extemalized many NPD tasks.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Feeding Speed Pump
Control \ Design
Electrical Temperature
Devices Control
Mold Standard
Design Design

 

 

 

 

 

Note: Shaded area represents internalized tasks

Figure 1.4: Paradigm Shift of NPD in Heavy Machinery Industry

11

Paradigm Shift in NPD

Figure 1.5 provides a metaphorical description of the paradigm shift in NPD.
Traditionally, the ﬁrm tended to develop most of the tasks internally (“football-shaped”
NPD). The “barbell-shaped” NPD allows the ﬁrm to give (externalize) some NPD tasks

to other ﬁrms in order to use outside resources and capabilities to the greatest extent and

still keeps its core competencies.

Paradigm Shift in NPD: Football => Barbell

Traditional
Pattern

 

Externalized New

Externalized ...........................
Pattern

Designs

Designs

 

Internalized Designs (Key Tasks)

Figure 1.5: Metaphorical Description of the
Paradigm Shift in NPD

The “barbell—shaped” NPD allows the ﬁrm to focus on critical tasks and

externalize the others. The bar of the “barbell” represents the internalized tasks, i.e., tasks

12

that are performed by the ﬁrm itself. The internalized tasks are those that are closely
related to the ﬁrm’s core competencies or those that are critical for customer value
creation. The weights of the “barbell” denote the extemalized tasks, i.e., tasks that are
given to other ﬁrms. Those are tasks for which the ﬁrm has neither critical strategic needs
nor special capabilities.

There are several advantages associated with the “barbell-shaped” NPD. First, the
“barbell-shaped” NPD allows the ﬁrm to concentrate its “best-in-world” (Quinn 1999, p.
11) resources and capabilities on a few core tasks and thus provide unique and superior
value for customers (Quinn 1999; Howells 1999).

Second, this strategy enables the ﬁrm to protect and strengthen its core
competencies and competitive advantages in the market place. Focusing on the
development of core technologies may improve the ﬁrm’s capability to stay current and
provide formidable barriers against present and future competitors (Quinn and Hilmer
1994). Honda, for example, mainly focuses on the design and manufacture of clean,
efﬁcient, and small engines and captures a considerable share of the market.

Third, the “barbell-shaped” NPD gives the ﬁrm opportunities to use resources that
are not available internally or to access capabilities not easily developed internally. Each
ﬁrm has its own “best-in-world” core competencies. Duplicating them would be
prohibitively expensive or even impossible. Giving complicated tasks to other ﬁrms is a
way of incorporating other ﬁrms’ expertise into NPD. NPD program performance can
thus be greatly enhanced (Prahalad and Hamel 1990; Venkatesan 1992).

Fourth, “barbell-shaped” NPD greatly broadens the windows of opportunities

(Quinn 1999; Quinn and Hilmer 1994). Traditionally, many NPD programs are

13

abandoned or fail and valuable market opportunities are missed because the ﬁrm relies
mostly on internal NPD capabilities. By incorporating other ﬁrms’ resources and
capabilities, the ﬁrm can fully implement NPD strategies and enhance competitive
positions. One R&D vice president pointed out that the R&D department often lacks a
clear strategic focus because they are preoccupied with operational activities.
Extemalizing non-strategic NPD tasks permits the R&D department to move away from
routine administration toward a more strategic role.

It has to be noted that the “barbell-shaped” NPD not only stresses “giving” tasks
to other ﬁrms and utilizing outside resources and capabilities beyond the boundaries of
the ﬁrm, it also emphasizes “taking” knowledge from other ﬁrms to strengthen NPD

capability, which is another important research issue in this dissertation.

A Theoretical Explanation of the “Barbell-Shaped” NPD

Figure 1.6 presents a conceptual framework of this dissertation to justify the
“barbell-shaped’ NPD from a theoretical point of view. It links the ﬁrm’s strategic NPD
management to NPD program performance, both directly and indirectly through its
inﬂuence on ﬁrm NPD capability. The direct relationship between strategic NPD
management and NPD program performance symbolizes the extemalization principle,
i.e., to leverage external resources and capabilities. The indirect link between strategic
NPD management and NPD program performance indicates the internalization function,

i.e., to leverage internal resources and capabilities.

l4

Externalization Principle:
.............. Leverage External Capabilities

 

V

 

 

 

Strategic NPD Firm NPD NPD Program
——> . , -——>
Management Capability Performance

 

 

 

 

 

 

 

 

 

TH

Internalization and Resource-Based View:
Leverage Internal Capabilities

Figure 1.6: Conceptual Framework

The underlying rationale is that ﬁrm NPD program performance could be
enhanced directly by incorporating other ﬁrms’ expertise (extemalization principle). At
the same time, the ﬁrm could assemble its limited resources and focus on the
development of one or severaI key technologies, making them the “best—in-world”
(internalization principle). The conceptual framework is based on the principles of
internalization theory (Buckley and Casson 1976, 1998; Casson 1984, 1994) and the
resource-based view of the ﬁrm (Wemerfelt 1984; Day and Wensley 1988; Collis 1994).
Following are the comparisons of the rationales of internalization theory and the resource-

based view of the ﬁrm. Table 1.1 is a summary of the two theories.

Table 1.1: Externalization Decision Based on Internalization Theory and Resource-
Based View of the Firm

 

 

 

 

 

 

 

Internalization Resource-Based View of the
TheorL Firm
Logic behind the Minimizing total NPD costs, Maximizing NPD program
Strategic NPD increasing speed, and performance by incorporating
Management improving quality. other ﬁrm resources and
capabilities.

Logic behind the Using other ﬁrm’s expertise. Gaining access to other ﬁrm
Externalization Lowering development cost. resources and capabilities.
Decision in NPD Letting the ﬁrm concentrate on Focusing limited resources on

the most successful work. key technology and developing
Increasing capacity. “best-in-world” core
competencies.
Logic behind the Intemalizing NPD tasks is If tasks are critical for ﬁrm core
Internalization efﬁcient. competencies, or
Decision in NPD Important tasks need to be extemalization would transfer
performed internally. ﬁrm core competencies, there
The danger of tremendous loss in is less incentive to externalize.
the future if externalizing Protecting core competencies.
certain tasks. Improving market competitive
position.
The Logic of If the design of the complex tasks Firms exist because of different
Extemalizing internally is prohibitively expertise. Giving complex

Complicated costly or impossible, it is better tasks to other ﬁrms is to use
Tasks. to give that to other ﬁrms with the best resources in the world.

more expertise.

Logic of Knowledge in certain areas is too Getting knowledge in critical
Improving NPD costly to develop internally. areas of NPD from other ﬁrms
Capability to strengthen core competence.
through
Knowledge from
Other Firms

 

 

 

16

 

Rationale of Internalization T heory

Internalization theory comes, in part, from Buckley and Casson (1976) and is
further developed by Casson (1984, 1994), Buckley (1983, 1988), and Buckley and
Casson (1998). These authors synthesize various critics of the neoclassical model of the
ﬁrm from the ﬁelds of economics, law, and theory of organizations. The main
contribution of internalization theory has been to operationalize Coase's (1937) seminal
work: he argued that there are conditions under which it is more efﬁcient for the ﬁrm to
perform certain tasks internally (ﬁrm-based solutions) rather than externally (market-
based solutions).

Under what conditions would the ﬁrm choose each of the two means—
intemalizing or extemalizing—necessary to NPD success? The internalization theory has
linked this type of decisions to two types of considerations. The earliest factors addressed
in the internalization theory focus on the efﬁciency of ﬁrm activities (Coase 1937;
Williamson 1975). Internalization theory proposes that market-based solutions are default
options for the ﬁrm; but when ﬁrm activities are seriously affected by market failure, the
ﬁrm tends to internalize these activities. The earliest factors addressed in the
internalization theory, therefore, focus on the efﬁciency of the ﬁrm’s operation. If the
ﬁrm cannot efﬁciently accomplish the task, extemalization would be considered.
Otherwise, internalization would be the choice (Krause, Scannell, and Calantone 2000).

Internalization theory is further advanced by Buckley and Casson (1976, 1998),
who have linked ﬁrm activities with ﬁrm internal factors, such as the ﬁrm’s core
competencies. They argued that efﬁciency may not be the only consideration that

determines the ﬁrm strategic choice. The ﬁrm intemalizes tasks that are critical for NPD

success and extemalizes the others. In other words, when ﬁrm activities become so
important that extemalization causes harmful consequences, the ﬁrm tends to internalize
these activities (Krause, Scannell, and Calantone 2000). In some situations, even if the
ﬁrm can perform a task efﬁciently, the ﬁrm still considers to strategically externalize it.
Thus, the ﬁrm can successfully move from one product line to another, or from one
market to another market. In the 19805, Apple internalized most NPD tasks because
Apple was the leading ﬁrm then and could perform the tasks efﬁciently. Apple ﬁnally lost
the dominant position in the market partially because it ignored the strategic side of NPD
management.

Internalization theory offers NPD managers a model for rethinking the
management of a portfolio of NPD tasks. Time pressure becomes an important concern in
NPD (Montoya-Weiss and Calantone 1994; Fine 1998). Internalization suggests that the
ﬁrm should externalize highly complex NPD tasks (Casson 1982; Rugmanl980, 1981;
Hennart 1982). This is based on the premise that the firm is unlikely to perform these
tasks efﬁciently. Externalization thus would be the choice (see Chapter 2 for detailed
discussion). Examples from industries include IBM’s extemalization of operating system,
Natsteel’s extemalization of hydraulic system, and Mannesmann’s extemalization of
pump design.

Another strategic consideration for NPD managers is that the ﬁrm should
internalize NPD tasks that are crucial for ﬁrm survival. In NPD, some tasks are very
important for the ﬁrm. If the ﬁrm extemalizes these tasks, it is subject to a tremendous
loss in the long run. In contrast, if the cost to perform tasks internally is extremely high

and these tasks do not affect core competencies, then they could be assigned to other

18

 

TESC

tap;

01115

'\ >
rim

ﬁrms with more expertise. For example, as Toyota builds its core competency in engine
parts, it always assigns tasks on transmissions and electrical systems to partners (Fine

1998). How to internalize or externalize NPD tasks is the central theme in Chapter 2.

Rationale of Resource-Based View of the Firm

Wemerfelt (1984), Day and Wensley (1988), Barney (1991), and Prahalad and
Hamel (1990) expanded the seminal work of Penrose (1959) and built resource-based
theory around the internal competencies of the ﬁrm. Firm competitive advantage is rooted
inside the ﬁrm, in assets that are valuable and inimitable according to the resource-based
view of the ﬁrm. The ﬁrrn's survival largely depends on how it builds, develops (or
strengthens), and protects its core competencies (Day and Wensley 1988).

Consistent with the principle of internalizing important and critical tasks, the
resource-based view of the ﬁrm emphasizes the protection of ﬁrm core competencies
(Penrose 1959; Wernerﬁeld 1984; Barney 1991; Day and Wensley 1988). The ﬁrm seeks
to perform certain NPD tasks internally because ﬁrm speciﬁc advantage needs to be
protected by its organizational structure. In other words, if NPD tasks are closely related
to ﬁrm core competencies and externalizing these tasks will undermine ﬁrm competitive
advantage, the ﬁrm should not externalize these tasks.

The resource-based view of the ﬁrm is not restricted solely to exploring internal
resources and capabilities. Researchers recognized that many of the resources and
capabilities essential to the fully implementation of the ﬁrm’s competitive advantage lie
outside the ﬁrm’s boundaries (D02 and Hamel 1998). Grant (1991), for example,

acknowledged the importance of resources and capabilities within other ﬁrms. He

19

asserted that when needed resources and capabilities are not available internally,
outsourcing should be considered. By using other ﬁrms’ resources and capabilities, the
ﬁrm can gain “otherwise unavailable competitive advantages and values for the ﬁrm”
(Das and Teng 2000, p. 36). Applying this perspective to NPD, when the ﬁrm does not
possess the resources and capabilities to perform certain NPD tasks, the ﬁrm can give
these tasks to other ﬁrms to use their “best-in—world” resources and capabilities.

The resource-based view of the ﬁrm explicitly recognizes the importance of
intangible assets such as organizational culture (Barney 1986) and knowledge (Teece
1981; Grant 1996, 1997). This offers a signiﬁcant opportunity for research on links
between ﬁrm NPD capability and the activities of getting knowledge from partner ﬁrms
(this is discussed extensively in Chapter 3).

The strategic choice perspective, as developed by internalization theory and
resource-based view of the ﬁrm, rests on the assumption that actors are economically
rational and strive to maximize ﬁnancial performance by enhancing their market positions
relative to competitors’ positions (Porter 1980, 1990). Internalization theory predicts that
the ﬁrm extemalizes or internalizes NPD tasks to enhance the NPD efﬁciency or
strengthen core competencies. The resource-based view of the ﬁrm complements
internalization theory and predicts that the ﬁrm can enhance the NPD efﬁciency by using
other ﬁrms’ resources and capability, i.e., by externalizing some NPD tasks. The
resource-base view of the ﬁrm also stresses that the ﬁrm extemalizes NPD tasks

unrelated to their core competencies.

20

Theoretical Contributions

The framework of this study incorporates concepts from internalization theory and
the resource-based view of the ﬁrm. The contributions of this dissertation to NPD theory
could be summarized as follows.
Internalizing and Extemalizing NPD Tasks

This dissertation attempts to provide a theoretical explanation for the
extemalization issue in NPD. In Chapter 2, I propose a framework based on
internalization theory (Buckley and Casson 1976, 1998) and the resource-based view of
the ﬁrm (Day and Wensley 1988). Considering the difﬁculties of the ﬁrm in developing
new products internally, I propose a solution of developing new products both internally
and externally. In particular, I propose that the ﬁrm could give part of its NPD tasks to
partner ﬁrms in order to use other ﬁrms’ resources and capabilities and accelerate NPD.
Internalization theory stresses that the ﬁrm should internalize tasks that are critical and
externalize unimportant tasks. The resource-based view of the ﬁrm also emphasizes the
importance of protecting ﬁrm core competency. I propose that the ﬁrm should not
externalize tasks that affect core competencies. In other words, the ﬁrm would beneﬁt if it
concentrates on new product tasks that are crucial and gives unimportant tasks to partner
ﬁrms.
Enhancing NPD Capability Through Obtaining Knowledge

The above theoretical study aims at “giving” some tasks of NPD to other ﬁrms to
improve NPD program performance. This dissertation also provides theoretical guidance

for “taking” knowledge from other ﬁrms to enhance NPD capability.

21

Based on the premise that the ﬁrm is likely to internalize tasks that are connected
to core competencies, a strong NPD capability is crucial for NPD program success.
Improving ﬁrm NPD capability is, therefore, critical in this respect. I propose that the
ﬁrm could improve its NPD capability through acquiring knowledge from other ﬁrms.

The theory of knowledge management stresses the importance of tacit knowledge
and novel knowledge for the ﬁrm. Based on the premise that obtaining tacit knowledge
requires repeated and intensive interaction between ﬁrms, I propose that the ﬁrm could
get tacit knowledge from close partners. The literature on inter-ﬁrm relationship also
stresses the role of weak relationships in getting new knowledge. I propose that the ﬁrm
is likely to get novel knowledge from "friends of friends", or partners that are unique (not

closely related to other ﬁrms) in the relationship.

Contributions to Managerial Practice

A large portion of this study is driven by the major concerns of NPD managers.
As many product managers turn their attention from primarily internal design issues to
the combination of internal and external designs, the study could provide some basic
managerial guidelines for strengthening NPD capability and using external resources and
capabilities to the greatest extent.

From a managerial standpoint, the results of this dissertation assist NPD managers
in developing a strategy for managing different kinds of relationships. This dissertation
provides speciﬁc guidance on how to acquire tacit or uncoded knowledge from close

relationships and how to get novel knowledge from weak relationships (or from ﬁrms that

22

are unique in the relationships). Close relationships are very valuable for NPD success,
but ﬁrms that are not close could be equally useful.

Two models are developed in this dissertation. Chapter 2 presents the ﬁrst
framework and hypotheses, which focus on extemalization strategy and NPD program
performance. Chapter 3 presents the second model, which deals with getting knowledge

from other ﬁrms to enhance ﬁrm NPD capability.

23

CHAPTER 2

MODEL l—ENHANCING FIRM NPD PROGRAM PERFORMANCE
THROUGH EXTERNALIZATION

Figure 2.1 presents the model for studying NPD program performance through
extemalization. The less the importance and greater the complexity of NPD tasks, the
more likely the ﬁrm is to externalize these tasks. The links from extemalization to both
NPD capability and NPD program performance are moderated by the importance of tasks.
Extemalizing less important tasks is beneﬁcial to NPD capability and NPD program
performance. Extemalizing important tasks are likely to jeopardize NPD capability and

NPD program performance.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Importance of NPD Tasks
H3 NPD Capability
Extent of a
Externalization H5
+
of NPD Tasks
- H4 , NPD Program
Performance
4..
Complexity of NPD
Tasks

 

 

 

FIGURE 2.1: ENHANCING FIRM NPD PERFORMANCE THROUGH
EXTERNALIZATION

24

Review of N PD Literature

Graham (1985) and Friar and Horwitch (1985) reported evidence of a paradigm
shift from internal to external sources of NPD since 1975. Robertson and Gatignon
(1998), Croisier (1999), and Kurokawa (1997) had brief reviews on in-house NPD versus
extemalization in their subsequent research.

Reasons for Externalization in NPD

Graham (1985) analyzed the strategic purpose for extemalization of NPD from
both long-term and short-term perspectives. He attributes short-term motivation for
extemalization to generic cost reduction (including cost spreading), redundancy
avoidance, obtaining knowledge from outside sources, and technological objective
evaluation. The long-term intention of extemalization is mainly opportunity generation. It
encompasses building the stock of usable technology, insulating researchers from day-to-
day operating pressures, and enhancing the quality of research. Subsequent researchers
have suggested several reasons why the ﬁrm extemalizes its NPD tasks; these encompass
cost reduction, NPD speed, and NPD quality.

Cost reduction. Cost reduction is often given as a main reason for extemalization
in NPD (Mohr and Spekman 1994; Bonaccorsi and Lipparini 1994; Ragatz, Handﬁeld,
and Scannell 1997). Cost of NPD is deﬁned as the total ﬁnancial requirements and
associated human resources needed to complete the NPD process (Kessler and
Chakrabarti 1996; Rosenthal 1992). The increasing complexity of the NPD process
increases the cost of research. Many NPD plans fail because of the expense of NPD.
Furthermore, because of rapid technological advances, the ﬁrm’s R&D department may

lack current technological expertise and equipment (Croisier 1999; Brockhoff 1992).

25

Many NPD programs may require several scientiﬁc and technical disciplines. It is
commonly believed that an outside partner can provide the same level of technology at a
lower cost than the internal R&D department when performing certain tasks. The often
cited rationale is that the partner typically has more focused expertise in a particular area
(Day and Wensley 1988; Collis 1994).

The expectation that extemalization will cut cost is consistent with the strategic
management view of competitive resource allocation (Kazanjian and Rao 1999). This
viewpoint holds that all activities unrelated strategic core competencies should be
extemalized since economies of scale allow specialized ﬁrms to perform the tasks at
lower costs. One interviewee observed that the fees charged by the partner ﬁrms had
decreased because of increasing economies of scale.

NPD speed. NPD speed is another factor driving the paradigm shift in NPD. NPD
speed is deﬁned as the time elapsed between the initial development (such as idea
generation and new product deﬁnition) and ultimate commercialization, which is the
introduction of the new product into the market place (Kessler and Chakrabarti 1996). An
increasing number of organizations have recognized the importance of speeding up NPD
to build a competitive advantage (Kessler and Chakrabarti 1996; Grifﬁn 1997b). NPD
cycle time is critical because product life cycles are shrinking (Grifﬁn 1997b). Grifﬁn
(1997b, p.25) reported that the NPD cycle time decreased by 25 - 50%. The growing
popularity of speeding up NPD is partly based on the belief that being a faster innovator
can give the ﬁrm either ﬁrst-mover or second-mover strategies.

Quality. Quality is also important in NPD (Li and Calantone 1998; Jacobson and

Aaker 1987). Quality has been deﬁned as the perceived superiority or excellence in a

26

product as compared with competing alternatives from the perspectives of the
marketplace (Sethi 2000; Garvin 1988). Many analysts who have studied the apparent
success of Japanese ﬁrms have hypothesized that a key strategic ingredient has been
product quality (Li and Calantone 1998; Song and Mark 1997). Many authors have
proposed that best utilizing internal resources and capabilities, such as through cross-
functional teams, is one way to enhance new product quality.

The main problem in NPD is that cost, speed, and quality goals are extremely
difﬁcult to be achieved simultaneously. Generally speaking, NPD speed has been
positively related to NPD cost and new product quality. NPD cost is also positively
correlated with new product quality. That is, speeding up development results in the ﬁrm
committing more person-hours, materials, or equipment to NPD. Also, because of
resource limitations, the ﬁrm speeding up NPD ﬁnds it hard to correct mistakes in NPD
and to make accurate projections about competitors’ movements and customers tastes and
expectations, resulting in lower new product quality.

The ﬁrm, therefore, could outsource NPD tasks to simplify the NPD agenda, to
focus on core competencies (Venkatesan 1992; Prahalad and Hamel 1990; Quinn and
Hilmer 1994), and to speed up the development process (Bonaccorsi and Lipparini 1994;
Robertson and Gatignon 1998). Technological reasons for extemalization, such as
improving the quality of the NPD process (Dyer and Ouchi 1993) and gaining access to
new talent and technology, as well as the easy availability of partners with expertise, have
also been proposed (Croisier 1999; D02, 01k, and Ring 2000; Moorrnan and Miner 1997).

One executive mentioned that strategically externalizing non-core and low skill

activities would offer existing staff more time to concentrate on core activities. Thus

27

extemalization relieves existing staff of mundane, repetitive, and basic work, allowing
them to focus on high value-added activities.
NPD Capability

NPD capability can be viewed as a subset of ﬁrm overall capability. It is deﬁned
as the comprehensive set of characteristics of the ﬁrm that facilitate and support NPD
strategies (Hurley and Hult 1998). Moorman and Slotegraaf (1999) referred the NPD
capability to the ﬁrm’s technological ability to formulate and develop new products and
related processes. Other researchers similarly have identiﬁed technical proﬁciency, R&D,
and engineering or technical resources and skills as important to new product and process
developments (Calantone and di Benedetto 1988; Cooper 1993; Roth and Jackson 1995).
Montoya-Weiss and Calantone's (1994) meta-analysis of more than 40 studies examining
new product success factors found that technical proﬁciency was important to new
product success (see also Rothwell 1972; Song and Parry 1997). NPD capabilities are
also important to the speed of product development, because greater R&D investments
have been found to inﬂuence time to market (Li and Calantone 1998).

The existence of NPD capability rests on an accumulated expertise and a set of
skills that support NPD. The firm with high NPD capability employs learning-by-doing,
which makes it very difﬁcult for competitors to buy this know-how in the market and also
makes it extremely difﬁcult for other ﬁrms to imitate. The difﬁculties of imitating this
know-how are further exacerbated by the large tacit component of NPD. These

characteristics of NPD capability enable the ﬁrm to succeed in NPD programs.

28

NPD Program Performance

Because of the high failure rate of new products, NPD program performance is an
area that has attracted great attention (Li and Calantone 1998; Cooper and Kleinschmidt
1987; Wind and Mahajan 1997). NPD program performance is the level of success
achieved by the NPD program in the market place (Song and Parry 1997). Traditionally,
NPD program performance is described in terms of its actual and perceived outcomes
(Calantone and Cooper 1979, 1981; Cooper 1979; Crawford 1977). Damanpour (1991a),
however, found that organizational members’ perceptions of innovation outcomes do not
coincide with the actual innovation outcomes. When innovation outcome is highly
effective, respondents are likely to overestimate the performance. When innovation
outcome is highly ineffective, respondents tend to underestimate the performance.

Another problem concerning NPD program performance is that the ﬁrm has
different perceptions about what constitutes NPD outcomes. Some studies, especially
studies in the US. and Canada, emphasizes sales growth, market share, and proﬁts. While
others, typically studies in Japan, focus on speed of new product development process, or
lead time and productivity (Song and Parry 1997; Clark and Fujimoto 1991).

As a result, both subjective and objective measures were used in this dissertation.
NPD program speed, lead-time, and ﬁnancial performance such as proﬁtability, sales

growth, market share, and return on investment are considered.

29

Hypotheses
The Importance of NPD Tasks and Externalization

Importance of a NPD task is deﬁned as the degree to which the NPD task is
related to the ﬁrm’s core competencies (Veugelers and Cassiman 1999). The resource-
based view of the ﬁrm emphasizes the critical role of ﬁrm core competencies. Core
competencies are not products or those things the ﬁrm does relatively well. They are
those activities—usually intellectually-based service activities or systems—that the ﬁrm
performs better than any other enterprises. They are the set of skills and systems that the
ﬁrm does at “best in the world” levels and through which the ﬁrm creates uniquely high
value for customers (Day and Wensley 1988; Collis 1994).

Researchers of NPD warn of the danger of losing core competencies through
extemalization (Kurokawa 1997; Robertson and Gatignon 1998; van den Bosch and
Elfferich 1993; Veugelers and Cassiman 1999; Rubenstein 1994). The simple way to
protect core competencies is not to give away much of the ﬁrm’s unique competence at
the outset. In other words, the ﬁrm does not share all the basic technology, but simply
performs these functions on its own. Coca-Cola, for example, develops its syrup, a secret
formula, in its own plants and then distributes this syrup to its franchising partners.

In a NPD program, one risk the ﬁrm is subjected to is that other ﬁrms may imitate
the technology and try to compete with the ﬁrm (Robertson and Gatignon 1998). Thus,
ﬁrms such as Natsteel, IBM, and Microsoft pursue internal R&D for core NPD tasks.
Core NPD tasks are usually associated with ﬁrm intangible assets. If the ﬁrm extemalizes
these tasks, it will leave the intangible assets unprotected (Teece 1996). Even if the ﬁrm

gives the core tasks to close partners, the difﬁculties with regulating the transaction with

30

incomplete contracts and the cost of protecting against opportunistic behavior favor
internal mode of NPD (Robertson and Gatignon 1998). Veugelers and Cassiman (1999)
studied NPD in Belgian manufacturing ﬁrms and ﬁnd that the ﬁrm seldom gives
important tasks to other ﬁrms.

Creating uniquely high value for customers is one important aspect of ﬁrm core
competencies (Woodruff 1997; Parasuraman 1997; Slater 1997; Prahalad and Hamel
1990). One executive stressed, “If we really provide satisfaction to customers through
new product development, we will be proﬁtable.” The central organizational challenge in
NPD is to maximize the effectiveness of the ﬁrm’s customer value creation activities.
Many ﬁrms responded that it is most effective to focus on developing and supporting core
NPD tasks that can create and maintain a real and meaningful long-term distinctiveness in
customers’ minds.

Despite all best efforts, the design process often leads to the introduction of
products that do not meet customer expectations. One possibility is that, when designing
products, designers are not always able to effectively incorporate information about the
customer. Veugelers and Cassiman (1999) have suggested to control key tasks that a vital
to customers’ satisfaction when designing a product. Incorporating the customer in the
key design allows the actual participation of a customer in the product design. This form
of design could involve customer as an "actor," using product prototypes and interacting
with speciﬁc aspects of a design. Customers’ voice could be effectively translated into
engineers’ language. The key design process thus remains centered on the customer.

One executive warned that ignoring customer input would lead to NPD failure. He

further mentioned that for some NPD tasks, it is critical to seek customers’ feedback

31

about designs. This feedback serves as the reality check and ensures that the superiority of
NPD design is considered meaningful by customers. In some situations, the ﬁrm might
proactively apply their own knowledge and expertise about the product and help
customers discover and articulate their requirements. If the ﬁrm extemalizes the tasks that
are crucial for customer value creation, the required interactions between the ﬁrm and
customers in NPD will be jeopardized. The resultant new products are less likely to be
considered meaningful by customers. Hence, I propose,

HI .' The greater the importance of tasks, the less the extent of extemalization.

The Complexity of Tasks and Externalization

Grifﬁn (1997b) uses the number of functions of a product to describe product
complexity. The overall complexity of tasks in a NPD program can be referred to as the
broadness of knowledge and technology required to fulﬁll these tasks relative to the
ﬁrm’s knowledge and technology base (Taggart 1997; Hobday 1998). Both
internalization theory and the resource-based view of the ﬁrm support the notion of
externalizing complex tasks, but from different perspectives. Internalization theory
emphasizes the “push” effect. If a task requires novel knowledge, or if a task covers a
variety of distinct knowledge bases, or if the task needs a variety of skills and engineering
inputs that the ﬁrm does not have or which are prohibitively costly to acquire, then
extemalization is preferred to internalization. In research on UK manufacturing
multinational corporations, Taggart (1997) posited that as complexity increases, an
extemalization decision becomes more likely.

Singh (1997) pointed out that the fundamental challenge the ﬁrm faces in

32

developing complex tasks is developing multiple competencies required by these designs.
As complex NPD task design requires different knowledge bases, the ﬁrm that internally
developing these tasks must possess the ability to design, manufacture, and coordinate
many dissimilar components. The ﬁrm, however, is unlikely to have the ability to develop
a broad set of competencies. Depending on limited knowledge base and competencies to
develop these complex NPD tasks runs a great risk. One executive indicated: “If other
companies could perform better than me, why should I do it myself?”

In the heavy machinery industry, for example, the design of a new product
includes feeding speed control, mold design, pump design, and temperature control, and
these designs cover several scientiﬁc and technical disciplines. Many companies simply
do not have all the necessary resources to cope with these problems. Furthermore, the
increasing complexity of NPD increases the cost of NPD. NPD may become less
attractive without other ﬁrms to “share the burden” (van den Bosch and Elfferich 1993).

The resource-based view of the ﬁrm emphasizes the “pull” effect. The
attractiveness of other ﬁrms’ expertise encourages extemalization (Quinn and Hilmer
1994). Other ﬁrms have the technology and knowledge to perform certain tasks in more
efﬁcient and effective ways than one ﬁrm can internally. For example, Natsteel let
Vickers, the expert ﬁrm in hydraulic systems, to design the hydraulic press system. Time
and costs were saved.

D02 and Hamel (1998) focused on the resources and capabilities within the
boundaries of other ﬁrms. They further propose that many valuable resources and
Capabilities lie outside of the ﬁrm’s boundaries. If the ﬁrm can use other ﬁrms’ resources

and capabilities, the ﬁrm could be in a superior competitive position in the marketplace.

33

Grand (1991), Das and Teng (2000), and Teece (1996) called for the utilization of other
ﬁrms’ “best-in-world” resources and capability. This perspective supports the notion of
externalizing complex NPD tasks.

The ﬁrm may be able to develop the broad set of competencies required for
complex NPD task design over a long period of time in a stable environment (Langlois
1992). However, environmental stability is uncommon in most industries, especially for
ﬁrms in high-tech industries. Instead, environmental turbulence is a major characteristic
that signiﬁcantly affect ﬁrm strategic decisions.

One threat of developing a broad knowledge base is “technology unrelatedness.”
In other words, the ﬁrm’s knowledge base will lack a “synergy” which is critical for NPD
success. Meyer and Roberts (1986), Roberts and Meyer (1991), and Kurokawa (1997)
found that the ﬁrm with more related technology performed better in NPD than those
with wider knowledge diversity. Rumelt (1974) also demonstrated that ﬁrms with related
technological activities outperformed those with diverse technological activities.
Extemalizing complex tasks affords the development of technological synergy or
relatedness.

One could also argue that the ﬁrm should internalize complex NPD tasks because
the ﬁrm may have the chance to develop technologies that are valuable. Singh (1997)
argued that developing complex tasks that are not related to ﬁrm core competencies is
extremely costly. Different knowledge bases are likely to reside in separate organizations.
The ﬁrm is constrained in its ability to rapidly learn and implement these competencies
and routines embodied in other ﬁrms.

Williamson (1991) suggested considering additional problems when analyzing

34

organizational forms in conjunction with the development of new products. When
concerned with the NPD program, two important dimensions have to be added: timeliness
and costs. In today’s technological environment, new products are introduced at a faster
pace and often combined with technological paradigm shifts (Robertson and Gatignon
1998)

The above discussion suggests that, in general, the ﬁrm tends to externalize
complex tasks to increase speed and to reduce costs of new product development. I
propose,

H2: The greater the complexity of tasks, the greater the extent of extemalization.

Externalization and NPD Capability

Externalization gives the ﬁrm the opportunity to access other ﬁrms’ core
competencies (Quinn 1999). Through frequent interactions during the NPD process,
partners’ useful technology and management skills are acquired and NPD capability is
strengthened.

Externalization increases the organization’s focus (Venkatesan 1992). By giving
certain tasks to other ﬁrms, the ﬁrm can concentrate its limited resources on core
competencies and develop “best-in-world” technologies (Kurokawa 1997). This
ultimately leads to high NPD capability. One approach to strategic NPD management is
the focused investment, i.e., to invest on high value-added NPD activities (Quinn 2000).
These investments further generate know—how related to core competencies. NPD
capability is enhanced (Nonaka 1994).

Many executives maintain that externalizing unimportant NPD tasks increases

35

R&D department focus. The R&D department could then put much emphasis on the
strategic side of NPD development. NPD capability thus is improved. Quinn (2000)
pointed out that because of its size and focus, the ﬁrm applying an extemalization
strategy is very active in the marketplace.

Pisano (1990) supported externalizing NPD tasks from the organizational learning
perspective. The interactions in externalizing NPD tasks facilitate knowledge transfer
among ﬁrms, which would ultimately enhance NPD capability. He supported this view by
citing examples from the pharmaceutical industry. The ﬁrm developing a speciﬁc
therapeutic compound may also “generate knowledge and build R&D capabilities that are
valuable for discovering other drugs for the same disease” (Pisano 1990, p. 159).

In contrast, externalizing important tasks discourages the ﬁrm ﬁ'om developing
key technology, thus jeopardizing NPD capability (Verona 1999). One principle of
“barbell-shaped” NPD is that the ﬁrm should strengthen internal capabilities by focusing
on several key technologies and developing them into the “best in the world.” The
building of NPD capability is a cumulative process that needs the continuous investment
in R&D (Robertson and Gatignon 1998). The ﬁrm giving critical tasks to other ﬁrms
tends to ignore necessary investments in R&D, leading to lower NPD capability (Pisano
1990)

The interviewees were unanimous in their advice not to externalize NPD tasks
related closely to ﬁrm core competencies. They stressed that externalizing core NPD
tasks would result in the loss of NPD capability and diminish NPD quality. Therefore, I
propose,

H3: The relationship between extemalization and NPD capability decreases from

36

positive to negative as the level of the importance ofNPD tasks increases.
Externalization and NPD Program Performance

The previous discussion summarized several advantages of extemalization, such
as reducing costs, gaining speed, improving quality, and sharing risks. Externalization,
therefore, directly contributes to NPD program performance. Quinn (1999) asserts that
extemalization strategy allows the ﬁrm to return to its most successful work and enjoy the
beneﬁts of utilizing other ﬁrms’ valuable resources and capabilities. In the analysis of
“make-or—buy” decisions in R&D, Kurokawa (1997) proposed that internalizing NPD
tasks that are not related to the ﬁrm’s core competencies would be costly and the
development period would be longer as compared to externalizing these tasks. The
subsequent empirical tests supported the above assertion. In other words, externalizing
less important NPD tasks is positively related to NPD program performance.

It has to be pointed out however that externalizing tasks critical to frnn core
competencies is harmful for NPD program performance because this gives other ﬁrms
opportunities to develop better products (Quinn 1999; Prahalad and Hamel 1990;
Robertson and Gatignon 1998). Robertson and Gatignon (1998) warned that other ﬁrms
may imitate the technology and compete with the ﬁrm if the ﬁrm exposes the core
competencies through externalizing key NPD tasks.

In the study of R&D boundaries in the pharmaceutical industry, Pisano (1990)
found that externalizing tasks that are strategically important to the corporation was
negatively related to R&D performance. He further explained that NPD tasks that are
closely related to ﬁrm core competencies are likely to be those that the ﬁrm has

experience with and can perform relatively better than other ﬁrms because technological

37

development is likely to be cumulative. Consequently, externalizing NPD tasks that the
ﬁrm can perform efﬁciently will jeopardize NPD program performance. Stated formally,

H4: The relationship between extemalization and NPD program performance

decreases from positive to negative as the level of the importance of NPD
tasks increases.
NPD Capability and NPD Program Performance

The positive relationship between NPD capability and NPD program performance
is uniformly supported by the NPD literature (Cooper 1984; Cooper and Kleinschmidt
1987; Hurley and Hult 1998; Han, Kim, and Srivastava 1998). The ﬁrm with great NPD
capability develops new products with greater quality, lower cost, and at higher speed,
leading to high NPD program performance (Li and Calantone 1998; Veugelers and
Cassiman 1999; Gatignon and Xuereb 1997).

The ﬁrm with high NPD capability is likely to develop products that are highly
valued by buyers. It synthesizes the knowledge of what is needed in the market and how
to create a product to meet the need. Such a ﬁrm places the highest priority on
continuously ﬁnding ways to provide superior customer value and thus can conceive of or
implement NPD strategies that are superior to competitors’ strategies (Han, Kim and
Srivastava 1998; Barney 1986), resulting in high NPD program performance. Many
studies suggest that the ﬁrm is able to improve NPD program performance only when its
products are valuable to buyers.

Dumaine (1989) reported that the speed at which the ﬁrm brings new products to
the market is crucial for NPD proﬁtability. Speedy product development enjoys the

pioneering advantage, such as earlier market segment and customer loyalty. It allows the

ﬁrm to develop second—generation models based on the feedback from its original product

38

launch. Through speedy NPD the ﬁrm can deal with volatile market changes and maintain
proﬁtability. Speedy NPD requires that the ﬁrm have superior NPD capability: it is high
NPD capability that allows the ﬁrm to develop new product at great speed and high
quality, resulting in high NPD program performance. So, the proposition is,

H5 .' The greater the NPD capability, the higher the NPD program performance.
Control Variables

Two control variables, ﬁrm size and age, were included in the study. Firm size
refers to the number of employees and annual sales. Firm age is the years the ﬁrm has
been in business. They were included to account for the possible inﬂuence on

extemalization of NPD tasks, NPD capability, and NPD program performance.

39

CHAPTER 3

MODEL 2—ENHANCING FIRM NPD CAPABILITY
THROUGH OBTAINING KNOWLEDGE

Figure 3.1 presents the model for studying how to enhance ﬁrm NPD capability
through acquiring knowledge from other ﬁrms. The key arguments are that ﬁrm NPD
program performance depends mostly on ﬁrm NPD capability, and that tacit knowledge
and novel knowledge are critical antecedents of the ﬁrm’s NPD capability. A high level of
tacit knowledge could be obtained though close interactions with partner ﬁrms, and novel

knowledge could be acquired from ﬁrms not closely related.

Knowledge

The importance of knowledge for the ﬁrm is reﬂected in internalization theory
and the resource-based view of the ﬁrm. Researchers in the resource-based view of the
ﬁrm consistently stress that knowledge is one of the important ﬁrm resources because it is
unique, inimitable, and valuable for the ﬁrm (Day and Wensley 1988; Collis 1994;
Barney 1986). Some scholars propose a knowledge-based view of the ﬁrm (Grant and
Baden-Fuller 1995; Grant 1997) to acknowledge the central role of knowledge in the
ﬁrm. In internalization theory, scholars recognize the importance of knowledge (Buckley
and Casson 1976) and postulate that some knowledge is too costly to develop internally.

Acquiring knowledge from other ﬁrms is more efﬁcient.

40

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Closely related to NPD are tacit knowledge and novel knowledge (Nonaka 1994;
Tidd 1995; Tatikonda and Rosenthal 2000). Tacit knowledge is uncoded knowledge and
resides in the ﬁlm’s system. Tacit knowledge is important but difﬁcult to interpret and
transfer from one ﬁrm to another. Due to difﬁculties related to interpretation and transfer,
previous studies are mostly descriptive in nature. Detailed research on it is lacking: in
particular, how to get tacit knowledge from other ﬁrms is a neglected issue (Howells
1999; Madhavan and Grover 1998).

Novelty is deﬁned as the newness, to the NPD ﬁrm, of the knowledge (Hansen
1999). It is an important concept for NPD but has received little attention (Tidd 1995;
Tatikonda and Rosenthal 2000). In the NPD literature and studies of knowledge
management, scholars often describe knowledge novelty on the basis of lack of
familiarity with the given knowledge. In the operationalization, existing measures of
technology newness and technology novelty were integrated and extended (Tatikonda and

Rosenthal 2000).

Relationship Strength
Relationship strength is one characteristic of inter-ﬁrm relationships. It is central
to relationship research (Morgan and Hunt 1994; Hansen 1999; Rindﬂeisch and
Moorman 2001). Four dimensions of relationship strength are identiﬁed, which are ( 1)
frequency of interactions, (2) conﬁdence on one another, (3) desire to maintain the

relationship, and (4) bidirectionality. Hansen (1999) proposed that close interﬁrm

42

relationships are characterized by (1) frequent interactions, (2) an extended history, and
(3) intimacy or mutual conﬁding (see also Kraatz 1998).

Mutual frequent information sharing in a close relationship includes the formal as
well as informal exchange of meaningful and timely information (Mohr and Nevin 1990).
This is critical for a close relationship because one party seeks a dialogue with the
partner, not only concerning the partner’s operations and strategies, but also with respect
to feedback on its own operations and strategies. This kind of give-and—take requires
open-mindedness and a non-defensive attitude. Information sharing has a substantive
effect when strategies and operations are modiﬁed and improved. The frequency and
quality of information sharing signal the importance of the relationship and the respect
that the parties have for each other (Mohr, Fisher, and Nevin 1996).

In marketing research on relationships, Morgan and Hunt (1994) emphasize that
the nature of close relationship lies in mutual trust, commitment, and the high quality and
frequency of communications. In a close relationship, compared with a weak relationship,
both ﬁrms treat the relationship as valuable and important (Moorman, Zaltman, and
Deshpande 1992). They desire that the relationship endure indeﬁnitely and are willing to
work together to maintain it. For example, when one party is in need of help, the other
party is readily available (Morgan and Hunt 1994).

The closeness of the relationship between ﬁrms determines the extent of
knowledge transfer. A close relationship allows for prolonged cohabitation of managerial
and technical personnel and facilitates the replication of organizational routines (Teece
1981). A direct interface among the partner ﬁrms permits direct observation of operations

and enables the gradual and experiential learning that is essential for successﬁrl transfer

43

of tacit knowledge (Davies 1977; Killing 1983; Osborn and Baughn 1990). For example,
a supplier may get knowledge of inter-functional integration during its participation in the
manufacturer's NPD. Furthermore, partnering relationships include a monitoring process
(Stump and Heide 1996). Monitoring is especially valuable where tacit knowledge is
concerned, since such knowledge is not readily codiﬁed, and hence cannot be transmitted
in the form of reports and balance statements.

Recent research indicates that weak relationships could be as important as strong
relationships (Hansen 1999; Rogers 1995; Kraatz 1998; Rindﬂeisch and Moorman 2001).
Compared with strong relationships, weak relationships tend to be infrequent and distant.
Firms with different values, interests, degrees of power, and ways of interacting often ﬁnd
it difﬁcult to identify common bonds that build trust (Rowley, Behrens, and Krackhardt
2000). However, weak relationships that connect otherwise isolated ﬁrms have been
noted for their capacity to bring new information and resources that would otherwise not
be accessible (Ashman, Brown, and Zwick 1998). They are especially efﬁcient for
knowledge sharing because they provide access to novel information by bridging
otherwise disconnected ﬁrms (Hansen 1999). Strong ties, in contrast, are likely to lead to
redundant information because they tend to occur among a small group of actors; these

actors tend to possess the same information and to hold similar opinions (Rogers 1995).

44

Hypotheses
Strength of Relationship and the Level of Tacit Knowledge Obtained

Strong ties are more likely to promote in-depth, two-way communication and to
facilitate the exchange of detailed information between organizations (Kraatz 1998). A
close relationship enhances the opportunities for people in both ﬁrms to share feelings,
emotions, collaborative experiences, and mental models through physical, face to face
contacts. A close relationship is therefore the base for tacit knowledge transfer (Nonaka
1994). Through frequent dialogue among the members of two ﬁrms, knowledge in one
ﬁrm is converted into terms and concepts shared with another ﬁrm. Thus, tacit knowledge
rooted in one ﬁrm is likely to be transferred into another ﬁrrn's knowledge.

In the study of the knowledge transfer among the sub-units of an organization,
Hansen (1999) found that units with strong ties have greater motivation to be of
assistance and are typically more easily available to each other than units with weak ties.
He highly valued the two-way interactions between the source and recipient in strong ties.
Tacit knowledge transfer is not likely to be completed the ﬁrst time due to the difﬁculty
of transfer. Repeated two-way interactions are necessary, for then the recipient ﬁrm can
"try, err, and seek instruction and feedback" from the source (Hansen 1999, p. 88). When
problems occur and questions arise, the source ﬁrm is immediately available. Uzzi (1996)
also noted that ﬁrms in strong relationships are likely to exchange “ﬁne-gained”
knowledge.

Examples from industry support the positive relationship between relationship
strength and the level of tacit knowledge obtained. IBM obtained the valuable knowledge

of image processing during a seven-year long cooperation with USAA (United States

45

Automobile Association), which had a strong capability in image processing. HP failed in
the ﬁrst four years in getting the knowledge necessary to deal with special conditions in
China because it did not ﬁnd the right partners and develop close relationships. Based on
the above arguments, I propose,

H6. The stronger the relationship between the ﬁrm and a partner ﬁrm, the higher

the level of tacit knowledge can be obtained from the partner ﬁrm.
The Relationship Strength and the Level of Novel Knowledge Obtained

Hansen (1999) observed that strong relationships are less likely to provide novel
knowledge because actors know each other very well. New information should be more
readily available from ﬁrms with whom the ﬁrm has weak relationships. By contacting
ﬁrms that are loosely coupled, diverse ideas are obtained. For example, the idea of a new
feeding system for press machines in Mannesmann was from a textile factory. Some of
Natsteel’s most innovative projects were copied from a beverage company.

Rowley, Behrens, and Krackhardt (2000) synthesized previous studies on weak
relationships and found that weak relationships are more likely to bridge distant others
possessing new knowledge. Weak relationships can be thought of as representatives of
remote networks. Through the weak relationships, new knowledge in remote networks is
accessed and transferred.

Hakansson (1999) also suggested searching weakly related relationships for new
ideas. On the one hand, weakly related ﬁrms are unlikely to be direct competitors in the
market place. They may be willing to share useful knowledge in their interactions because
there is less incentive to protect this knowledge (Constant, Sproull, and Kiesler 1996). On

the other hand, general knowledge in one industry can generate a highly innovative idea

46

for the ﬁrm in a different industry. For example, the mechanism to ﬁll the container in
production line is the basic design in a beverage company. Natsteel’s highly innovative
project of feeding system design is from that “basic design.” Therefore, it is more likely
that the ﬁrm can get novel knowledge when searching in weak relationships. Stated in
another way,

H7. The stronger the relationship between the ﬁrm and a partner ﬁrm, the lower
the level of novel knowledge can be obtained from the partner ﬁrm.

Partner Non-Redundancy and the Level of Novel Knowledge Obtained

The construct of non-redundancy is derived from studies of networks in NPD
(Bonner 1999; Gabbay and Zuckerman 1998; McEvily and Zaheer 1997). Non-
redundancy refers to the degree to which a partner is not directly nor indirectly related to
other ﬁrms in the relationship (Burt 1992). Burt (1983) pointed out that expertise offered
by members that are connected closely in the relationship tends to be redundant. Firms
that are unique in the relationship are sources of new knowledge (Nonaka 1994).

Contacting the ﬁrm that is not related either directly or indirectly to other ﬁrms in
the network relationships is to bridge a hole in the social structure (Constant, Sproull, and
Kiesler 1996). The structural hole is an opportunity to access to diverse information from
different clusters of ﬁrms. The probability of ﬁnding new knowledge is higher if
searching in these relationships. Gabbay and Zuckerrnan (1998) observed that R&D work
units with disconnected contacts have more chance to get novel knowledge than others
who do not enjoy the same degree of access to structural holes. Therefore, the more the
partner is not related to other ﬁrms in the relationship, the greater the probability the ﬁrm

will get novel knowledge from this partner. Stated formally,

47

H8. The greater the partner non-redundancy, the higher the level of novel
knowledge that can be obtained from the partner ﬁrm.

The Levels of Tacit Knowledge and Novel Knowledge Obtained and NPD Capability

The main premise of this study is that the more the tacit and novel knowledge are
transferred, the greater the NPD capability. Rooted in the resource-based perspective, the
reasoning behind this premise is that tacit—as opposed to explicit—knowledge is more
difﬁcult to transfer across borders, and hence more likely to be unique, rare, and difﬁcult
for rivals to replicate. Acquiring high explicit (or low tacit) knowledge is unlikely to be as
effective for improving NPD capability and NPD program performance as acquiring high
tacit knowledge through a close relationship. This is because explicit knowledge about
innovation is easily available to all competitors, while tacit knowledge about innovation
is not. At the same time, NPD is rooted in innovative ideas. Firms obtaining more novel
knowledge are likely to have stronger NPD capability.

In today’s highly dynamic environment, the ﬁrm searches for continuity to
improve the competitive position in the marketplace. One continuity can be found in
terms of the skills and knowledge used for product development. Several works in
industrial economics emphasize that the nature of NPD is cumulative, and the ﬁrm's
innovation capability is strongly related to the knowledge, tacit or novel, accumulated
over time (Liebeskind 1996; Hedlund 1994; Nonaka 1994). They also underline the role
of learning processes in improving technological competencies and continuously
deepening and broadening the knowledge domain. Knowledge accumulation over time
helps to make the NPD capability hard to imitate by competitors, and opens unique

innovative opportunities. Hence,

48

H9. The higher the level of tacit knowledge obtained, the higher the ﬁrm NPD
capability.

H10. The higher the level of novel knowledge obtained, the higher the ﬁrm NPD
capability.
Moderating Effect of Firm Collaborative Experience

Collaborative experience is the ﬁrm’s experience of collaboration (Simonin
1997), which correlates closely with the ﬁlm's collaborative history. The ﬁrm
accumulates experience from long, frequent collaborations and intense interactions with
different ﬁrms. The ﬁrm with rich collaborative experience, therefore, has strong
capabilities to develop different relationships and to manage conﬂicts in interactions with
other ﬁrms (Simonin 1997).

The relationships between (1) relationship strength and the level of tacit
knowledge obtained, (2) relationship strength and the level of novel knowledge obtained,
and (3) partner non-redundancy and level of novel knowledge obtained are all likely to be
moderated by collaborative experience. Simonin ( 1999) argued that experience at
collaborating is necessary to manage a diverse portfolio of collaborative ties and to deal
with any emerging conﬂicts in the relationship. As empirically shown by Simonin (1997,
1999), collaborative experience is fundamental to building collaborative know-how
which, in turn, translates into greater collaborative beneﬁts.

The ﬁrm that has more collaborative experience should have more knowledge of
how to manage, monitor, and acquire knowledge from its partners. Inkpen (1998) found
that in the collaboration, the ﬁrm develops experience of cooperation and a reputation as

a partner. The ﬁrm with more collaborative experience is likely to understand the learning

49

opportunities created in the relationship. Furthermore, as the ﬁrm’s collaborative
experience accumulates, the ﬁrm moves up the learning curve and the skills necessary for
knowledge acquisition are reﬁned.

For example, partner ﬁrms could protect their tacit knowledge instinctually.
Experienced partners may resolve the conﬂict smoothly and get the tacit knowledge
transferred to the greatest extent. Collaborative experience also affects the capability of
the ﬁrm to recognize and understand the proper mechanisms of information gathering,
interpretation, and diffusion. Familiarity with collaborative mechanisms and/or transfer
processes facilitates the transfer of knowledge more effectively and efﬁciently.

Collaborative experience also serves as a “ﬁlter” in the identiﬁcation of
knowledge sources. The ﬁrm with high collaborative experience can efﬁciently ﬁnd the
right partners to collaborate with and ﬁlter out those with less value for collaboration.
The ﬁrm also has the ability to convince potential candidate companies of the merits of
collaboration, and to develop ways of easing these organizations through the
collaboration “initiation” (for example, by assisting with hurdles such as contract
negotiation).

The ﬁrm with high collaborative experience can establish trust in the relationship
with little difﬁculty. Trust evolves relatively easily as partners develop mutual
understandings from prior collaborative experiences. Opportunistic risks, therefore, are
obviated by partners’ anticipation of repeated transactions in the future. Also, the ﬁrm
with high collaborative experience can quickly ﬁnd the partner’s strengths and
weaknesses; it can manage better coordination and minimize bureaucratic complexity in

the relationship.

50

I propose,

H1]. The relationship between relationship strength and the level of tacit
knowledge obtained is stronger for ﬁrms with more collaborative experience
than for ﬁrms with less collaborative experience.

H12. The relationship between relationship strength and the level of novel
knowledge obtained is stronger (in absolute value) for ﬁrms with less
collaborative experience than for ﬁrms with more collaborative experience.

H13. The relationship between partner non-redundancy and the level of novel

knowledge obtained is stronger for ﬁrms with more collaborative experience
than for ﬁrms with less collaborative experience.

51

CHAPTER 4

METHODOLOGY

In this chapter, methodology is described. This chapter is organized into three
sections. The ﬁrst section introduces how the survey instrument was developed. The
second section discusses measures for the constructs. The third section is about the data

collection.

Survey Instrument

A questionnaire was used to collect data to test the two models in this dissertation.
The questionnaire development followed the Churchill (1979) and DeVellis (1991)
paradigms of developing better measures. The questionnaire was developed in four
stages. In the ﬁrst stage, a draft of the questionnaire was developed. Previous research
and relevant literature were reviewed. Scales in previous studies were collected and
categorized based on the constructs in this study. The purpose was to use well-developed
scales from previous studies. New measures were generated if there were no existing
scales in the literature. Items were generated from discussions with industry and academic
experts in new product development. Based on these approaches, the ﬁrst draft of the
questionnaire was developed.

In the second stage, the questionnaire was evaluated by academic and industry
experts. Four problems were revealed in this stage:

1. The wording of the questions: for example, items from previous studies did

not ﬁt the content of this dissertation well.

52

2. Imprecise and ambiguous questions: some questions were too long and not
concrete.

3. The clarity of the instructions: there was confusion between the questions on
speciﬁc relationships with a speciﬁc partner and questions of relationships
with partners in general (the ﬁrst two parts of the questions were about the
relationships with one speciﬁc ﬁrm; the rest of the questions were about the
general relationships with all partner ﬁrms).

4. Some measurement scales were not appropriate.

Based on the feedback from experts, questions were reworded and re-designed to
be as short as possible. For example, multiple questions instead of a single question were
used to make questions short and speciﬁc. Bipolar scales were used to measure
knowledge novelty and a scale of thermometer was used to measure the extent of two-
way communication. Instructions about the questions on relationships with a speciﬁc
partner and the questions on relationships with partner ﬁrms in general were redesigned
and clariﬁed. The revised questionnaire was send back to these experts to let them review
the changes. The second draft of the questionnaire was thus developed.

In the third stage, the questionnaire was pre-tested with a sample of 5 NPD
programs. The objectives of the pre-test were (1) to identify unclear or difﬁcult aspects of
the questionnaire and (2) to test the reliability and validity of measures. Each manager
who participated in the pretest was given a questionnaire and was asked to ﬁll it out. They
were then asked to report on the difﬁculty/clarity of the questionnaire and its individual
items by ﬁlling out an additional form. After receiving the form, each respondent was

contacted over the phone for further discussion of problems and concerns.

53

The pretest revealed that (1) the questionnaire was too long (taking 50 minutes on
average), (2) the extent of extemalization was a difﬁcult concept to understand, and (3)
some of the items used to measure knowledge novelty, knowledge tacitness, and task
complexity were unclear. In response to these issues, items were removed from the
questionnaire in order to reduce the completion time to around 20 minutes, task
extemalization was clariﬁed, and measures of knowledge novelty, tacitness, and task
complexity were modiﬁed.

In the fourth stage, the questionnaire was pretested on 15 NPD programs. In this
stage, no major problems were revealed. In the next part, measures of the constructs are

discussed.

Measures

Overall, multiple items were used for each construct. All measurements
represented by the questions in the questionnaire were built on the existing literature and
based on ﬁeld research. When there was no existing measure, new scales were developed
either by modifying relevant measures or scales were generated by experienced
academicians or managers.

Relationship strength is the degree to which two ﬁrms are related to one another.
It has four dimensions: frequency of interactions, conﬁdence in one another, desire to
maintain the relationship, and bidirectionality. Frequency of interactions was measured
with three items examining how often the two ﬁrms communicated with each other. The
respondents were asked to report how often the ﬁrm and its partner ﬁrm communicate

with each other about work-related matters in the oral, written, and electronic forms on a

54

ﬁve-point scale: less than once per month, 1-3 times per month, once per week, several
times per week, daily. The scales were from Maltz and Kohli (1996) and modiﬁed by
ﬁeld research. Two measures of information sharing from Heide and John (1992) and Lin
and Germain (1999) were modiﬁed to capture the frequency of information sharing in
general.

Conﬁdence in one another was measured by four items, which were modiﬁed
from measures of trust (Morgan and Hunt 1994; Anderson and Narus 1990; Moorman,
Zaltman, and Deshpande 1992; Heide and John 1992; Dwyer, Shurr, and Oh 1987;
Garbarino and Johnson 1999).

Desire to maintain the relationship was measured by seven items, which were
modiﬁed from measures of commitment and expectation of continuity (Anderson and
Narus 1990; Morgan and Hunt 1994; Gundlach, Achrol, and Mentzer 1995; Lusch and
Brown 1996).

Bidirectionality was measured by four items that captured the degree to which
two-way communications occurred (these were from Fisher, Maltz, and Jaworski (1997)).

Partner non-redundancy is the degree to which one partner is not linked to other
ﬁrms in the ﬁrm’s network. It was measured by four items that tapped the similarities
between this partner ﬁrm and other ﬁrms in the network; these items were from McEvily
and Zaheer (1997) and Bonner (1999). Respondents were asked to indicate the degree of
similarities of this partner ﬁrm and other ﬁrms in the network in terms of technical
competencies, market served, industry events attended, and competitive strategies.

Tacit knowledge refers to uncoded knowledge. The level of tacit knowledge

obtained was the degree of tacitness of the knowledge that the ﬁrm got from the partner

55

ﬁrm. It was measured by six items that were from Hansen’s (1999) and Subramaniam
(1999) scales of non-codiﬁed knowledge. The level of novel knowledge obtained is the
degree of newness of the knowledge that the ﬁrm got from the partner ﬁrm. It was
measured by seven items, which were modiﬁed from scales of technology novelty
(Tatikonda and Rosenthal 2000).

Collaborative experience was measured by ﬁve items which were modiﬁed from
Robertson and Gatigonon (1998) scales of partnering experience.

Complexity of NPD tasks refers to the broadness of knowledge and technology
required to fulﬁll tasks relative to the ﬁrm’s knowledge and technology base (Taggart
1997; Hobday 1998). Six items were used to measure complexity of NPD tasks; these are
from Singh (1997), Eliashberg and Robertson 1988, McCabe 1987, McQuiston (1989),
Kozlowski and Hult (1986), and Jaworski, Stathakopoulos, and Krishnan (1993), and
address (1) the degree of technological novelty, (2) the variety of distinct knowledge
bases, or the variety of skills and engineering inputs of NPD tasks.

Importance of NPD tasks is the degree to which the tasks are related to ﬁrm core
competencies. It was measured by four items. Two were modiﬁed ﬁom McQuiston
(1989) and two were from ﬁeld research. These items reﬂected the importance of NPD
tasks for meeting customer needs and for ﬁrm core competencies.

Extent of extemalization of NPD tasks was measured by two items. These were
new items generated from ﬁeld research. Respondents were asked to indicate the overall
percentage of tasks that were performed by other ﬁrms (extemalized) in the new product
development program. Respondents were also asked to categorize tasks into three groups,

very important tasks, important tasks, and unimportant tasks. They were asked to indicate

56

the percentage of tasks in each category that were performed by other ﬁrms.

NPD capability was measured by 12 items. According to Moorman and Slotegraaf
(1999), there are two approaches to measure capability. The ﬁrst approach is to measure
directly the underlying knowledge and skills that are likely to constitute the capability.
The second approach is to measure observable outcomes associated with the presence of
capabilities. In this dissertation, both approaches were used. The ﬁrst set of questions was
to measure the knowledge and skills of innovation capabilities. The second set of
questions was to measure the outcomes associated with innovation capability, such as the
ability to enter into new markets and enter into multiple markets.

NPD program performance was measured by eight items. Both subjective and
objective measures were used. They were from Li and Calantone (1998) and Moorman
and Miner (1997). The ﬁrst set of items was objective measures. Respondents were asked
to report market share, pretax proﬁt margin, and length of development of new product
development programs. The second set of measures was subjective measures. The
respondents were asked to judge the new product development program’s performance on
sales, proﬁt margin, return on assets, and return on investment.

As for control variables, organizational size was operationalized as the number of
peOple in the organization and annual sales of the organization. Organizational age is

measured by the years the organization has been in business.

Data Collection
The sampling ﬁ'ame was drawn from a national mailing list of US high-tech ﬁrms.

A total of 1741 executives and their associated ﬁrms were selected randomly from the

57

mailing list. The ﬁrms represented a variety of industries, which included chemicals (SIC
codes begin with 28), machinery (SIC codes begin with 35), electronics (SIC codes begin
with 36), aircraft (SIC codes begin with 37), instruments (SIC codes begin with 38), and
computer software (SIC codes begin with 73).

The unit of analysis is NPD program. This is based on the following two
considerations. First, NPD capability development is the task of the whole organization
and should not be delegated to a technical team (Li and Calantone 1998). Second, the
study is interested in the overall extemalization of NPD tasks in the organization. Thus,
respondents were asked to evaluate the NPD program in the survey.

The executives targeted in these ﬁrms held the position of Vice President of R&D,
Vice President of Engineering, or technological manager (director). Of the 1741 surveys
initially mailed, a total of 127 were returned marked "moved/not forwardable,"
"forwarding order expired," or "employee no longer works here." This reduced the actual
sample frame to 1614 companies.

In order to get the largest response rate, following methods were used:

1. The survey packet contained a personalized cover letter that introduced the

study, its potential value, and the importance of the executive's participation.

2. Respondents who participated were offered a copy of the survey results and

research conclusions.

3. A reminder card was mailed ﬁve days after the initial mailing, reminding the

executives of the request for their participation. This followup card again
highlighted the relevance of the study to the executives and offered the survey

results. I also included the name and telephone number of a contact person

58

from whom they could receive a replacement survey if it was needed.
4. A second round of mailing was conducted four weeks after the initial mailing.
The target of the mailing was non-respondents.

Of these executives, 247 responded to the survey (a response rate of 15.3%). This
was a reasonable rate for this type of study. Of the 247 surveys received, 14 were
identiﬁed as unusable due to missing values. As a result, 233 usable questionnaires were
used in the data analysis. Firm and respondent characteristics are summarized in Tables

4.1 to 4.3.

Table 4.1: Distribution of Sample by Industry

 

 

Industry (SIG Code) Percent of the Sample
Chemical (28) 5.48
Mechanical (35) 14.61
Electronics (36) 48.33
Aircraft (37) 2.87
Instrument (38) 19.62
Computer software (73) 9.09
Total 100.00

 

59

Table 4.2: Distribution of Sample by Firm Size

 

Firm Size (# of Employees)

Percentage of the Sample

 

10,000+
5,000—9,999
LOGO—4,999
500—999
100—499
Less than 100

Total

Table 4.3: Respondents:

9.09

6.70

17.22

16.75

25.84

24.40

100.00

 

 

Respondent Title Percentage of the Sample
Vice President of R&D 52.15
Vice President of Engineering 37.32
Technology Manager (Director) 10.53
Total 1 00.00

 

60

Initial Data Analysis

Missing values were replaced following the procedure in Wilson and Collier
(2000). The measurement items were grouped based on the constructs in the ﬁrst model
and the second model. If a question was not answered, the average score of the answered
questions on the relevant scale would be used to replace the missing value. Missing
values in demographic variables were replaced by the relevant sample average.

The normality of the data was tested by examining kurtosis and skewness of all
measurement items. The kurtosis ranged from 0.06 to 1.28. They were below 2.00, a
point beyond which nonnorrnality becomes a concern. Skewness of all items ranged from
0.04 to 0.97, which were acceptable. Kolmogorov-Smirnov tests further conﬁrmed that
the nonnorrnality was not present.

To assess non-response bias, the data were divided into two groups based on the
date on which they were received. The ﬁrst group, which represents the early responses,
consisted of the data received from the ﬁrst mailing process. The second group, which
represents the later responses, was composed of the data received from the second
mailing process. The two groups were compared on all the measurement items and
constructs using t-tests (Armstrong and Overton 1977). The summary of the non-response
bias testing is presented in Table 4.4. The t-values ranged from 0.21 to 1.19; none of them
was signiﬁcant. Therefore, there was no signiﬁcant difference between the two groups on

all variables.

61

Table 4.4: Results of Testing for Non-response Bias

 

 

Constructs t-value p—value
Externalization .30 .76
Importance .21 .84
Complexity .32 .75
Relationship Strength .46 .65
Non-Redundancy .87 .39
Tacit Knowledge .41 .68
Novel Knowledge 1 .19 .24
NPD Capability .32 .76
NPD Program Performance .73 .47
Collaborative Experience .26 .79

 

Following Armstrong and Overton (1977) and Stump and Heide (1996), non-
response bias was also tested by comparing the sample statistics with the known
population values. If there was no signiﬁcant difference between the sample means and
the population values, response bias is not present. The sample means of sales and
employees were compared with population values of sales and employees through two-
tailed t-test. The results are shown in Table 4.5. It was found that that t-values were -0.02
and —1.42 for sales and employees respectively. They were not signiﬁcant. This further

provided evidence that non-response bias might not be a problem.

62

Table 4.5: Comparison of Sample with Population

 

 

 

 

Variable Sample” Population Results
Mean SD. Mean t-value p-value
Sales (S) 54314900 164110680 62269618 -.02 ns.
(n=179)
Employees 6389 15466 8041 -l .42 ms.
(n=177)

 

Note: 3: Missing values were not included in the test.
n.s.: not signiﬁcant.

63

CHAPTER 5

FIRST MODEL TESTING AND RESULTS

In this chapter, the method to test the ﬁrst model is described. Measurement issues
are examined. Construct reliability and validity are tested. The ﬁrst model is tested using

seemingly unrelated regression.

Measurement Validation

There are ﬁve constructs in the ﬁrst model: they are NPD program performance,
NPD capability, extemalization, importance of NPD tasks, and complexity of NPD tasks.
Churchill (1979), Gerbing and Anderson (1988), Anderson and Gerbing (1982), and
Durvasula et al. (1993) were followed in testing the reliability and validity of constructs.
First, exploratory factor and Chronbach Alpha testing were run on each construct
separately. Items with low item-to-total correlation and low loadings were discarded.
Second, all constructs were subject to exploratory factor analysis. Items with high cross
loadings were eliminated. It was assured that all the items loaded on their theoretically
relevant factors.

After the preliminary analysis, all measurements were subject to conﬁrmatory
factor analysis (CFA) using LISREL to verify unidimensionality. Generalized least square
estimation method was used for it is less sensitive to sample size (see Li and Calantone
1998). In the CFA testing, items with low item-to-construct and insigniﬁcant loadings

were discarded. Again, care was taken to ensure that items loaded on their theoretically

64

relevant constructs.

Thirteen items were dropped in the analysis. For the NPD program performance
construct, six of the eight items met the criterion of unidimensionality. Two items were
deleted because of low or cross loadings. Reliability of the construct was 0.83.

As to the NPD capability construct, ﬁve of the twelve items met the above
criteria. Seven items were removed from consideration. Reliability of the construct was
0.94.

Two items of extemalization met the criteria. The Pearson correlation of the two
items was 0.78.

Three of the four items of the importance of NPD tasks met the criteria. One item
was removed. Reliability of the construct was 0.72.

With respect to the complexity of NPD tasks, three of the six items survived after
the analysis. Three items were eliminated. Reliability of the construct was 0.90.

The CFA results are presented in Table 5.1. The measurement model is shown in
Figure 5.1. The CFA testing resulted in ﬁve constructs (F1 to F5) with 19 measurement
items (V1 to V19). It was found that the reliabilities of four constructs, measured by
Chronbach alpha, were between 0.72 to 0.94. These alphas were above the traditional
coefﬁcient alpha cutoff of 0.70. The reliability of extemalization, measured by Pearson

correlation, was 0.78, indicating acceptable inter-item consistency.

65

Table 5.1: Results of Confirmatory Factor Analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct Measurement Items Standardized Cronbach
Loadings" Alphab
V1: Pretax proﬁt margin .93
V2: Market share .76
F1: V3: Overall, how satisﬁed were you
NPD Program with this new product development
Performance program. .78 .83
V4: Sales, relative to objective .73
V5: ROA, relative to objective .55
V6: ROI, relative to objective .70
V7: The ﬁrst-to-market .97
V8: Our new product introductions have
increased over the last ﬁve years. .94
F2: V9: We have a strong capability in .94
NPD penetrating new markets. .89
Capability V10: We have a strong capability in
responding to unique requirements
of different markets. .88
V11: We have a strong capability in
introducing new products
simultaneously into several
markets. .79
F3: V12: Overall percentage .72 .78
Externalization V13: Average percentage .97
V14: These tasks are important for ‘
meeting customer regirements. .74
F4: V15: These tasks are critical for our .72
Importance ﬁrm’s long-term beneﬁt. .78
V16: These tasks are important for our
ﬁrm’s core competency. .71

 

 

 

 

66

 

Table 5.1 (Continued)

 

 

 

 

 

 

Construct Measurement Items Standardized Cronbach
Loadings' Alphab
V17: These tasks involve technology
never used in the industry before. .84
F5: V18: Because these tasks were so
Complexity complex, if we had performed them .90
ourselves, we would have involved
more engineers than usual. .96
V19: Overall complexity .88

 

 

 

Fit Indexes 12 =403.56 (d.f.=142); CFI=1.00; IFI=1.00; NFI=.99; RMSEA=.089

 

" All loadings are signiﬁcant at p<.01.
b‘ The reliability of extemalization is measured by Pearson correlation.

67

 

  

<

iiiiiiiilii
3:35:30 Chm-h

NPD Program
Performance

   

\l

   

OO

NPD Capability

Externalization

 

 

    

Importance of
NPD Tasks

] 1
Complexity of “j;
NPD Tasks

Figure 5.1: Measurement Model

   
  
 
 

<<
5;;

  
  

 

<
:3

 
    

<
'55

  

The overall measurement model ﬁt was judged to be satisfactory. Bentler and
Bonett's Normed Fit Index (NFI) and Bender's Comparative Fit Index (CFI) were both
above the desired minimum acceptable 0.90 level (Hair et a1. 1995; Byrne, 1994).

RMSEA indicated reasonable ﬁt (RMSEA=0.082). Examining item-to-construct

68

loadings, they ranged from 0.55 to 0.97. The loadings were all signiﬁcant at the 0.01
level, indicating convergent validity.

To test for discriminant validity, two approaches were adopted. The ﬁrst approach
was a series of chi-square difference tests of one, two, three, four, and ﬁve-factor models,
as suggested by Durvasula et al. (1993). The ﬁve-factor model represented the
hypothesized model in which NPD program performance, NPD capability,
extemalization, importance of NPD tasks, and complexity of NPD tasks were distinct
constructs. In each four-factor model, one pair of factors was combined into one factor.
The four-factor models, thus, were represented by 10 combinations of the measures as
shown in Table 5.2. The three-factor models, two-factor models, and one-factor model
were the combinations of three factors, four factors, and ﬁve factors into one factor

respectively.

69

Table 5.2: Ten Four-Factor Models

 

Model

Constructs

 

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Model 7

Model 8

Aurel-z: ADJNH ADJNH wwmv— humi— Roam—-

WNF‘

. NPD program performance and NPD capability as one factor
. Externalization

. Importance of NPD tasks

. Complexity of NPD Tasks

. NPD program performance and extemalization as one factor
. NPD capability

. Importance of NPD tasks

. Complexity of NPD Tasks

. NPD program performance and importance of NPD tasks as one factor
. NPD capability

. Externalization

. Complexity of NPD Tasks

. NPD program performance and complexity of NPD tasks as one factor
. NPD capability

. Externalization

. Importance of NPD tasks

. NPD Capability and extemalization as one factor
. NPD program Performance

. Importance of NPD tasks

. Complexity of NPD Tasks

. NPD capability and importance of NPD tasks as one factor
. NPD program performance
. Externalization

. Complexity of NPD Tasks

. NPD capability and complexity of NPD tasks as one factor
. NPD program performance

. Externalization

. Importance of NPD tasks

. Externalization and importance of NPD tasks as one factor
. NPD program performance

. NPD capability

4.

Complexity of NPD Tasks

 

70

Table 5.2 (continued)

 

Model Constructs

 

Model 9 1. Externalization and complexity of NPD tasks as one factor
2. NPD program performance
3. NPD capability
4. Importance of NPD Tasks

Model 10 1. Importance of NPD tasks and complexity of NPD tasks as one factor
2. NPD program performance
3. NPD capability
4. Externalization

 

Evidence of discriminant validity existed if the chi-square ﬁt of the ﬁve factor
model was better than that of the four-, three-, two-, and one-factor models. Table 5.3
shows the comparison of the ﬁve-factor model with the ten four—factor models. It was
seen that the difference between the ﬁve-factor model and any of the four-factor models
was signiﬁcant at 0.01 level. It was concluded that the ﬁve-factor model was better than
any of the four-factor models. In the same way, the ﬁve-factor model was compared with

the three-, two-, and one-factor models. The results supported discriminant validity.

71

Table 5.3: Comparison of Five-Factor Model with Ten Four-Factor Models

 

 

Model Chi-square Difference with the Significance
Five-Factor Model level
Five-F actor Model 403.56 (d.f.=142)
Four-Factor Model 1 455.60 (d.f.=l46) 52.04 (d.f.=4) .01
Four-Factor Model 2 454.95 (d.f.= 146) 51.39 (d.f.=4) .01
Four-Factor Model 3 427.48 (d.f.= 146) 23.92 (d.f.=4) .01
Four-Factor Model 4 466.61 (d.f.= 146) 63.05 (d.f.=4) .01
Four-Factor Model 5 440.88 (d.f.= 146) 37.32 (d.f.=4) .01
Four-Factor Model 6 425.90 (d.f.= 146) 22.34 (d.f.=4) .01
Four-Factor Model 7 460.38 (d.f.= 146) 56.82 (d.f.=4) .01
Four-Factor Model 8 427.54 (d.f.= 146) 23.98 (d.f.=4) .01
Four-Factor Model 9 460.17 (d.f.= 146) 56.61 (d.f.=4) .01
Four-Factor Model 10 433.31 (d.f.= 146) 29.75 (d.f.=4) .01

 

72

The second approach to test discriminant validity was to examine Phi values as

suggested by Anderson and Gerbing (1982) and Gerbing and Anderson (1988).

Discriminant validity is supported if intervals of inter-factor correlations (Phi values) did

not contain a value of one. Table 5.4 presented the inter-factor correlations. Absolute Phi

values ranged from 0.01 to 0.44, and none of the conﬁdence intervals of these estimates

contained a value of one (p<0.01). Thus, it was concluded that the measurements were

appropriate for the study.

Table 5.4: Inter-factor Correlation

 

 

F1 F2 F3 F4 F5
F1 1.00
F2 .19 1.00
F3 -.01 .24 1.00
F4 .44 -.15 -.35 1.00
F5 -.01 .06 -.03 -.13 1.00

 

Note:

F1: NPD Program Performance
F2: NPD Capability

F3: Externalization

F4: Importance of NPD Tasks
F5: Complexity of NPD Tasks

73

Hypothesis Testing

Moderated regression analysis was applied to test Hypotheses 1 to 5. The
interaction term was used to test the moderating effect of importance of NPD tasks on the
relationship between extemalization and NPD capability and the relationship between
extemalization and NPD program performance as suggested by Aiken and West (1991)
and Jaccard, Wan, and Turrisi (1990). Signiﬁcant interactions in the model were
examined through simple slope analysis, a technique that overcomes the need to create
subgroups from continuous independent variables’ (Aiken and West 1991).

An important concern in using this approach is the possible multicollinearity
between the interaction terms and their components (J accard, Turrisi, and Wan 1990). An
examination of correlations among independent variables showed that correlations ranged
from 0.01 to .79 (see Table 5.5). It was found that the correlation between importance of
NPD tasks and the interaction term was 0.79 (p<0.01). There was multicollinearity among

the independent variables.

 

’ It was predicted that externalizing unimportant tasks had a positive impact on NPD capability and NPD
program performance. Extemalizing very important tasks had a negative impact on NPD capability and
NPD program performance.

If using beta to represent the effect of extemalization on NPD capability and NPD program
performance, beta would decrease as the importance of NPD tasks increased. Beta would change from
positive to negative at certain level of the importance NPD tasks, indicating that externalizing very
important NPD tasks would be detrimental to NPD capability and NPD program Performance.

74

Table 5.5: Correlation Matrix of Factors (not mean-centered variables)

 

 

F1 F2 F3 F4 F3*F4 F5
F1 1.00
F2 .33 1.00
F3 .13 .40 1.00
F4 .27 -.16 -.29 1.00
F3*F4 .26 -.03 .31 .79 1.00
F5 -.05 -.06 .01 -.08 -.06 1.00

 

Note: F1: NPD Program Performance
F2: NPD Capability
F3: Externalization
F4: Importance of NPD Tasks
F 3*F4: Interaction Term
F5: Complexity of NPD Tasks

To minimize multicollinearity among the interaction term and its constituent
terms in the regression model, a technique suggested by Aiken and West (1991) and
J accard, Wan, and Turrisi (1990) was employed. The interaction term and its constituent
terms (importance of NPD tasks and extemalization of NPD tasks) were mean centered
(i.e., the mean of each scale was subtracted from each observation) (Aiken and West
1991). In other words, importance of NPD tasks and extemalization of NPD tasks were
mean-centered. Then the interaction term was created by multiplying the relevant mean-
centered scales (i.e., mean-centered importance of NPD tasks and extemalization of NPD

tasks). The resulting correlation matrix is shown in Table 5.6.

75

Table 5.6: Correlation Matrix of Mean-Centered Factors

 

 

F1 F2 F3M F 4M F3M*F4M F5
F1 1.00
F2 .33 1.00
F3M .13 .40 1.00
F4M .27 -.16 -.29 1.00
F3M*F4M -.19 -.42 .05 .19 1.00
F5 -.05 -.06 .01 -.08 .02 1.00

 

Note: F1: NPD Program Performance (not mean-centered)

F2: NPD Capability (not mean-centered)

F3M: Mean-Centered Externalization

F4M: Mean-Centered Importance of NPD Tasks

F 3M*F 4M: Interaction Term

F5: Complexity of NPD Tasks (not mean centered)

To check if this was successful, two widely used measures of multicollinearity

were employed. The maximum variance inﬂation factor (VIF) was 1.53, which was well
below the level of 10 that commonly signals detrimental multicollinearity. The maximum

condition index (MCI) was 2.17, which is below the cutoff of 30 (Mason and Perrault

1991). Multicollinearity thus was not presentz.

 

2 VIF and MCI for not mean-centered variables were 16.69 and 35.01 respectively. The mean-center
technique was successful

76

All hypotheses were tested by estimating three regression equations:

(1) Externalizationm = ,6 10 + ,6 11 Importancem + 5 12 Complexity + ,6 13 Employees
+ ,614 Sales +ﬂ 15 Years + e1

(2) Capability = ,8 20 + ,B 21 Externalizationm + ,6 22 Externalization,m * Importancem
+ ,6 23 Importancem + ,6 24 Employees + ,6 25 Sales + ﬂ 26 Years + e2

(3) Performance = ,6 30 + ,6 31 Externalizationm + ,6 32 Externalizationm * Importancem
+ ,8 33 Importancem + ,6 34 Capability + ,6 35 Employees
+ 16 36 Sales + )3 37 Years + e3

Where,

0 Externalizationlm is mean-centered extemalization of NPD tasks. Therefore,
Externalizationm = Externalization - mean of Externalization.

o Importancem is mean-centered importance of NPD tasks. Therefore,
Importancem = Importance — mean of Importance.

o Externalizationm * Importancem denotes the interaction term between mean-
centered Externalization of NPD tasks and mean-centered Importance of NPD
tasks.

0 Performance is NPD program performance (not mean-centered).

- Capability is the NPD capability (not mean-centered).

0 Importance is importance of NPD tasks (not mean-centered).

0 Complexity is complexity of NPD tasks (not mean-centered).

0 Employees is the number of employees in the organization (not mean-centered).

0 Sales is annual sales (not mean-centered).

0 Years is the years of organization in business (not mean-centered).

To test if including the interaction term in equations 2 and 3 was appropriate,

77

Cohen and Cohen (1983) procedure was followed. The independent variables were
entered into the model in three steps: (1) control variables, (2) main effects, and (3)
interaction term. R-square change in step 2 and step 3 was examined. If the change in R-
square was signiﬁcant, then a signiﬁcant moderating effect was present.

Table 5.7 shows the R—square changes for equations 2 and 3. It can be seen that in
equation 2, when there was no interaction term, R-square was 0.1832. When the
interaction term was added to the equation, R—square was 0.3788. F value for the R2
difference test was 71.16 (degrees of freedom were 1, 226), which was signiﬁcant at
p<0.01. In equation 3, when there was no interaction term, R-square was 0.2461. When
the interaction term was added to the equation, R-square was 0.2641. F value for the R2
difference test was 5.50 (degrees of freedom were 1, 225), which was signiﬁcant at
p<0.05. Thus, it was concluded that adding the interaction term in equations 2 and 3 was

appropriate.

Table 5.7: R2 Difference Test of Interaction Term

 

 

Equation R2 of Unmoderated R2 of Moderated F-Statistic p-value
Model" Model” (d.f.)
2 .1832 .3788 71.16 <01
(1, 226)
3 .2641 .2461 5.50 <05
(1, 229

 

a: The interaction term was not included in the regression.
b: The interaction term was included in the regression.

After the justiﬁcation of the interaction term in equations 2 and 3, seemingly

unrelated regression was used to test the three equations simultaneously. Since some

78

variables, such as importance and extemalization, were used in more than one equation,
statistical estimation of the equations one at a time may lead to biases. Furthermore,
extemalization was both a dependent and an independent variable in the equations. So
was NPD capability. Seemingly unrelated regression can estimate sets of equations that

were related theoretically, as are Equations 1-3 (Johnston 1984).

Results

The results of seemingly unrelated regression are presented in Table 5.8. System
weighted R-square is 0.2635. Most hypotheses are supported. Below, the test results for
each hypothesis are described. In brief, four hypotheses (H1, H3, H4, H5) are supported.
One hypothesis (H2) is not supported.

H1 posits that the sign of the relationship between importance of NPD tasks and
extemalization will be negative. The results in Table 5.8 show that there is a negative and
signiﬁcant effect of importance of NPD tasks on extemalization (regression coefﬁcient =
-0.21, t = -4.46, p<0.01). This indicates that the less the importance of NPD tasks, the

more the extemalization of NPD tasks.

79

Table 5.8: Results of Seemingly Unrelated Regression Analysis

 

Equation 1: Dependent Variable—Externalization!

 

 

Variables DF Parameter t-value p—value
Estimate

Intercept 1 .15 .39 n.s.
Importancem 1 -.21 -4.46 < .01
Complexity 1 -.01 -.30 n.s
Employees 1 .07 1.22 n.s
Sales 1 -.06 -.82 n.s
Years 1 . l 5 .86 n.s

 

Equation 2: Dependent Variable—NPD Capability

 

Intercept 1 3 .43 7.70 <.01
Externalizationm 1 .65 8.21 <.01
Externalizationm * 1 -.39 -8 .44 <.01
Importancem

Importancem 1 .05 .84 n.s.

Employees 1 -.03 —1 .98 <.05
Sales 1 -.03 -.29 n.s

Years 1 .03 1.73 <.10

 

80

Table 5.8 (continued)

 

Equation 3: Dependent Variable—NPD Program Performance

 

 

Variables DF Parameter t-value p-value
Estimate

Intercept 1 2.36 7.71 <.01
NPD Capability 1 .15 3.65 <.01
Externalizationm 1 .1 1 2.02 <.05
Externalizationm * 1 -.08 -2.35 <.01
Importance,m

Importancem 1 .23 6.33 <.01
Employees 1 .02 1 .45 n.s
Sales 1 .04 .62 n.s
Years 1 .03 2.38 <.01

 

System Weighted R-square=.2635.

 

Note: n.s.: not signiﬁcant.

Externalizationm and Importancem are mean-centered variables.

H2 predicts that the complexity of NPD tasks will be positively related to
extemalization of NPD tasks. The results in Table 5.8 indicate that there is not a

signiﬁcant relationship between complexity of NPD tasks and extemalization of NPD

tasks (regression coefﬁcient = -0.01, t = -0.30, not signiﬁcant).

To further explore the relationship between complexity of NPD tasks and
extemalization of NPD tasks, Figure 5.2 was analyzed. Complexity of NPD tasks was
rescaled into 1, 2, 3: 1 represents low complex NPD tasks; 2 represents complex tasks;
and 3 represents high complex tasks. A U-shape relationship between complexity of NPD

tasks and extemalization of NPD tasks was found. So, the ﬁrm extemalizes both low and

81

high complex NPD tasks. Low complex NPD tasks may be of little interest for the ﬁrm to
develop internally due to little added value to the ﬁrm. In the interview, most executives
listed unimportant tasks as the industrial standard parts designs and manufacture, which
were easily “ordered” from other ﬁrms. High complex NPD tasks add more uncertainty to
NPD and may be given to ﬁrms with more expertise. NPD tasks in between, because they
are doable within the ﬁrm, may be internalized to fertilize ﬁrm core competencies. This

interesting ﬁnding will be discussed in Chapter 7.

Externalization

 

       

3 Complexity
Figure 5.2: Complexity—Externalization Relationship

H3 states that the relationship between extemalization and NPD capability
decreases from positive to negative as the level of the importance of NPD tasks increases.
To examine the moderating effect of importance of NPD tasks on the relationship

between extemalization and NPD capability, a new coefﬁcient is deﬁned:

82

6c = 621 + 622 Importancem
Equation 2 thus can be rearranged as follows:

Capability = 6 20 + 6 21 Externalizationm + 6 22 Externalizationm * Importancem
+ 6 23 Importancem + 6 24 Employees + 6 25 Sales + 6 25 Years + e2
= 6 20 + (6 21 + 6 22 Importancem) Externalizationm + 6 23 Importancem
+ 6 24 Employees + 6 25 Sales + 6 25 Years + e2
= 6 20 + 6 c Externalizationm + 6 23 Importancem + 6 24 Employees
+ 625 Sales + 626 Years + e2

6 c thus is the effect of extemalization of NPD tasks on NPD capability. Pluging

in the results in Table 5.8 and substituting the original value of importance of NPD tasks

(not mean-centered value),
6 c = 6 21 + 6 22 Importancem = 0.65 — 0.39 Importancem
= 0.65 — 0.39 (Importance — Mean of Importance)
= 0.65 — 0.39 (Importance — 3.69)
= 2.09 — 0.39 Importance
A series of equations thus can be generated based on different levels of
importance of tasks (see also Sethi 2000 and Grifﬁn 1997b for similar reasoning). To
illustrate the moderating effect, Figure 5.3 was analyzed based on the above equation. It is
clear that the impact of extemalization of NPD tasks on NPD capability decreases as the
importance of NPD tasks increases. Also, when importance of NPD tasks is greater than
5.36, the impact of extemalization of NPD tasks on NPD capability is negative. When

importance of NPD tasks is less than 5.36, the impact of extemalization of NPD tasks on

NPD capability is positive.

83

ﬂ 0 (the Effect of Externalization on NPD Capability)

  

Importance

 

 

Figure 5.3: Moderating Effect of Importance on
Externalization—NPD Capability Relationship

To illustrate clearly the moderating effect of importance of NPD tasks on NPD
capability, Figure 5.4 was analyzed. When importance of NPD tasks equals two
(unimportant tasks), the relationship between extemalization of NPD tasks and NPD
capability is positive and signiﬁcant (regression coefﬁcient = 0.1.17, p<0.01). When
importance of NPD tasks equals 6.5 (very important tasks), the relationship between
extemalization of NPD tasks and NPD capability becomes negative and signiﬁcant
(regression coefﬁcient = -0.54, p<0.01). This further illustrates that NPD capability will
suffer if externalizing very important NPD tasks. However, externalizing unimportant

tasks is beneﬁcial to NPD capability.

84

10 “T NPD Capability

    
  

Importance=2

Externalization
l I

1 2 * 4 5 6 7

 

 

‘

Importance=6.5

 

Figure 5.4: Externalization—NPD Capability Relationship

Similarly, according to H4, the relationship between extemalization and NPD
program performance decreases from positive to negative as the level of the importance

of NPD tasks increases. Similar to the testing of H3, a new coefﬁcient is deﬁned:
6p = 631 + 632 Importancem
Equation 3 thus can be rearranged as follows:

Performance = 6 30 + 6 31 Externalizationm + 6 32 Externalizationm * Importancem
+ ,5 33 Importancem + 6 34 Complexity + 13 35 Employees
+ ,3 36 Sales + ,3 37 Years + e3
= 6 30 + 6 p Externalizationm + 6 33 Importancelm + 6 34 Complexity
+ 6 35 Employees + 6 36 Sales + ,6 37 Years + e3

6p thus is the effect of extemalization of NPD tasks on NPD program

performance. Pluging in the results of Table 5.8 and substituting the original value of

importance of NPD tasks (not mean-centered value), the equation is solved for 6p at

85

different levels of importance of NPD tasks.

6 p = 6 31 + 6 32 Importancem = 0.09 — 0.08 Importancem

= 0.11 — 0.08 (Importance — Mean of Importance)
= 0.11 - 0.08 (Importance — 3.69)
= 0.41 — 0.08 Importance

,6 p (the Effect of Externalization on NPD Program Performance)

0.5 ‘

 
    

Importance
l

 

 

7

 

-0.5 r

Figure 5.5: Moderating Effect of Importance on Externalization—NPD
Program Performance Relationship

This yields a series of equations reﬂecting the effects of the extemalization of
NPD tasks under different levels of importance of NPD tasks. To illustrate the
moderating effect of the importance of NPD tasks, Figure 5.5 was analyzed based on the
above equation. It can be seen that the impact of extemalization of NPD tasks on NPD
program performance decreases as the importance of NPD tasks increases. When the
importance of NPD tasks is greater than 5.13, the impact of extemalization of NPD tasks
on NPD program performance is negative. When the importance of NPD tasks is less
than 5.13, the impact of extemalization of NPD tasks on NPD program performance is

positive.

86

Figure 5.6 was created to illustrate clearly the moderating effect of the importance

of NPD tasks on NPD program performance. When the importance of NPD tasks equals

two (unimportant tasks), the relationship between extemalization of NPD tasks and NPD

program performance is positive and signiﬁcant (regression coefﬁcient=0.20, p<0.01).

When the importance of NPD tasks equals 6.5 (very important tasks), the relationship

between extemalization of NPD tasks and NPD program performance becomes negative

and signiﬁcant (regression coefﬁcient=-0.16, p<0.01). This further illustrates that

externalizing very important NPD tasks is detrimental to NPD program performance.

However, externalizing unimportant tasks is beneﬁcial to NPD program performance.

2m

 

Performance

    
 
 

Importance=2

 

 

Externalization
I l
6 7
Importance=6.5 ‘

Figure 5.6: Externalization—NPD Program Performance Relationship

87

 

Consistent with expectations, NPD capability and NPD program performance are
positively related (regression coefﬁcient = 0.15, t = 3.65, p<0.01). Thus, NPD capability
has a signiﬁcant and positive impact on NPD program performance. H5 is supported.

As for the control variables, in the ﬁrst equation, none of the control variables
were found to be statistically signiﬁcant. Firm size and age thus do not affect
extemalization of NPD tasks.

In the second equation, the number of employees was found to be negatively
related to NPD Capability (regression coefﬁcient = -0.03, t = -1.98, p<0.05). Thus, large
ﬁrms (with more employees) tend to have lower NPD capability than small ﬁrms (with
less employees). Years in business is positively related to NPD capability (regression
coefﬁcient = 0.03, t = 1.73, p<0.1). Old ﬁrms have greater NPD capability than young
ﬁrms.

In the third equation, years in business is positively related to NPD program
performance (regression coefﬁcient = 0.03, t = 2.38, p<0.01). Old ﬁrms tend to have

higher NPD program performance than young ﬁrms.

88

CHAPTER 6

SECOND MODEL TESTING AND RESULTS

In this chapter, the method to test the second model is described. Construct
reliability and validity were tested. The second model is tested using structural equation

modeling.

Measurement Validation

There were seven constructs in the second model. They were NPD program
performance, NPD capability, the level of tacit knowledge obtained, the level of novel
knowledge obtained, relationship strength, partner non-redundancy, and collaborative
experience.
The Relationship Strength Construct

Relationship strength had four dimensions: frequency of interactions, conﬁdence
in one another, desire to maintain the relationship, and bidirectionality. In the analysis,
relationship strength was designed as a higher-order construct with four dimensions. To
reduce the complexity of the model, the relationship strength scale was aggregated to
have four indicators by summing the measurement items of the ﬁrst-order construct.
Before the means were taken, reliability of each indicator was examined. They were
acceptable (the reliability for frequency of interactions, conﬁdence in one another, desire
to maintain the relationship, and bidirectionality were 0.83, 0.79, 0.69, and 0.75

respectively). CFA was performed to ensure the convergent and discriminant validity.

89

Table 6.1 displays the results of the second-order conﬁrmatory factor analysis of
relationship strength, which posit relationship strength as a latent higher-order construct
that is manifested by the four ﬁrst order factors. The ﬁt indexes were excellent
(CFI=1.00; RMSEA=0.01). The standardized loadings of the ﬁrst order factors on
relationship strength were from 0.57 to 0.93, and were all signiﬁcant at p<0.01. In
addition, the item loadings on the ﬁrst order factors were high and signiﬁcant. It was

concluded that second-order scale of relationship strength was adequate for the study.

90

Table 6.1: Relationship Strength Second-Order Measurement Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct* Measurement Items Standardized
Loadings**
A: First-Order Loadings
Frequency of Interaction frequency. .79
Interactions We frequently interact with each other in managing .83
(0.83) the relationship.
The information sharing between our ﬁrm and this .76
partner is prompt.
Confidence in In our relationship this partner cannot be trusted at .83
One Another times.***
(0.79) This partner often breaks promises it made to our .85
ﬁrm.***
In the relationship this partner can be counted on to .65
do what is right.
Desire to Maintaining a long-term relationship with this partner .64
Maintain the is important to our ﬁrm.
Relationship We would like to develop a long-term relationship .65
(0.69) with this partner.
This partner is crucial for our future performance. .70
We would consider more investment in our .49
relationship.
Bidirectionality The extent of two way communications .82
(0.75) There is a lot of two-way communication between .73
our ﬁrm and this partner.
Our ﬁrm always responds to communication from .61
this partner ﬁrm.
B: Second-Order Loadigs
Relationship Frequency of interactions .63
Strength Conﬁdence on one another .71
(0.75) Desire to maintain the relationship .57
Bidirectionality .93
Goodness of ﬁt: 12 =62.62 (d.f.=6l), p=0.42; CFI=1.00; IFI=1.00; NFI=.97;
RMSEA=0.01.
Note: * Reliability of the constructs are in parentheses.

"All loadings were signiﬁcant at p<.01.
*** Scale was reversed in the analysis.

91

 

The Second Model

Measurement validation follows a similar procedure to the ﬁrst model testing.
First, exploratory factor analysis and Chronbach Alpha testing were run on each construct
separately. Items with low item-to-total correlations and low loadings were discarded.
Second, all constructs were subject to exploratory factor analysis. Items with high cross
loadings were eliminated. It was assured that all the items loaded on their theoretically
relevant factors.

After the preliminary analyses, all measurements were subject to conﬁrmatory
factor analysis (CFA) analysis using LISREL to verify unidimensionality. The
generalized least square estimation method was used. In the CFA analysis, items with low
item-to-construct and insigniﬁcant loadings were discarded. Care was taken to ensure that
items loaded on their theoretically relevant constructs.

Fifteen items were dropped in the analysis. For NPD the program performance
construct, six of the eight items met the criterion of unidimensionality. Two items were
dropped from consideration. Construct reliability is 0.83.

As for NPD capability construct, ﬁve of the twelve items met the above criteria.
Seven items were deleted. Construct reliability is 0.94.

Five of the six items for the level of tacit knowledge obtained survived after the
test. One item was removed. Construct reliability is 0.89.

Four of the seven items for the level of novel knowledge obtained met the criteria.
Three items were eliminated. Construct reliability is 0.83.

For relationship strength construct, four items met the criteria. No item was

deleted. Construct reliability is 0.87.

92

 

Four items for the construct of partner non-redundancy met the criteria. No items
were deleted. Construct reliability is 0.85.

With respect to collaborative experience, three of the ﬁve items survived after the
analysis. Two items were removed. Construct reliability is 0.90.

The CFA results were presented in Table 6.2. The CFA testing resulted in seven
constructs (F1 to F7) with 31 measurement items (V1 to V31). It was found that the
reliability of ﬁve constructs, measured by Chronbach alpha, was from 0.83 to 0.94. These
measures were above the traditional coefﬁcient alpha cutoff of 0.70, indicating acceptable
inter-item consistency.

The overall measurement model ﬁt was judged to be satisfactory. Bentler and
Bonett's Normed Fit Index (NFI) and Bender's Comparative Fit Index (CFI) were all
above the desired minimum acceptable 0.90 level (Hair et al.1995; Byrne, 1994).
RMSEA is 0.049, indicating good ﬁt. Examining item-to-construct loadings, they ranged
from 0.51 to 0.95. The loadings were all signiﬁcant at p<0.01. Convergent validity was
supported.

Similar to the ﬁrst model testing, discriminant validity was tested by two
approaches. The ﬁrst approaches is to conduct a series of chi-square difference tests of
one-, two-, three-, four-, ﬁve-, six-, and seven-factor models. In each six-factor model,
one pair of factors was combined into one factor. Thus, there were 21 six-factor models
(represented by 21 combinations of the measures). The ﬁve-, four, three-, two-, and one-
factor models were the combinations of three factors, four factors, ﬁve factors, six

factors, and seven factors into one factor respectively.

93

 

Table 6.2: Results of Confirmatory Factor Analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct Measurement Items Standardized Cronbach
Loadings' Alpha
F1: V1: Pretax proﬁt margin .88
NPD V2: Market share .84
Program V3: Overall, how satisﬁed were you with .80
Performance this new product development .83
program.
V4: Sales, relative to objective .73
V5: ROA, relative to objective .68
V6: ROI, relative to objective .71
V7: In a new product or service .94
introduction, how often is your ﬁrm
the ﬁrst to market?
F2: V8: Our new product introductions have .93
NPD increased over the last ﬁve years. .94
Capability V9: We have a strong capability in .84
penetrating new markets.
V10: We have a strong capability in .82
responding to unique requirements
of different markets.
V11: We have a strong capability in .77
introducing new products
simultaneously into several
markets.
V12: A useful manual describing this .59
knowledge can be written.*
V13: Extensive documentation .95
describing critical parts of the
knowledge exists in our ﬁrm.*
F3: V14: The knowledge we received from .65 .89
Tacit this partner is quite complex.
Knowledge V15: The knowledge could be easily .76
understood from written
documents.*
V16: The knowledge could be easily .63

 

communicated through written
documents.*

 

 

 

94

 

Table 6.2 (Continued)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct Measurement Items Standardized Cronbach
Loadings' Alpha
F4: V17: Please rate the knowledge acquired .94 .83
Novel from this partner ﬁrm on
Knowledge “familiar—unfamiliar” (familiar is
1; unfamiliar is 7).
V18: Please rate the knowledge acquired .88
from this partner ﬁrm on “
Previously known—previously
unknown” (previously known is 1;
previously unknown is 7)
V19: The knowledge we acquired from .80
this partner was totally new to us.
V20: We had never used this kind of .51
knowledge before.
F5: V21: Frequency of interactions .90 .87
Relationship V22: Conﬁdence in one another .70
Strength V23: Desire to maintain the relationship .89
V24: Bidirectionality .86
F6: V25: Technical competencies .79 .85
Non- V26: Market served .87
Redundancy V27: Industry events attended .85
V28: Competitive strategies .85
V29: Overall, our collaboration with .80
other ﬁrms in new product
F7: development has been a success. .90
Collaborative V30: Firm sales and proﬁts have .92
Experience beneﬁted from collaborating with
other ﬁrms in new product
development
V31: Our track record on collaboration .74

 

has been poor.*

 

 

 

 

Fit Indexes: [2 =641.72 (d.f. = 413); CFI=1.00; IFI=1.00; NFI=.99; RMSEA=.049.

 

3‘ All loadings are signiﬁcant at p<.01.
* Scale was reversed in the analysis.

95

 

 

Chi-square difference tests showed that the seven-factor model was better than
six-, ﬁve-, four-, three-, two-, and one-factor models. The difference between the seven-
factor model and each of the six-, ﬁve-, four-, three-, two-, and one-factor models was
signiﬁcant at 0.01 level. It was concluded that the seven-factor model was better than any
of the six-, ﬁve-, four-, three-, two-, and one-factor models. Discriminant validity was
supported.

Discriminant validity is also supported if intervals of inter-factor correlations (Phi
values) do not contain a value of one. Table 6.3 presents the inter-factor correlations.
Absolute Phi values ranged from 0.01 to 0.57, and none of the conﬁdence intervals of
these estimates contained a value of one (p<0.01). Thus, it was concluded that the

measurements were adequate.

96

Table 6.3: Inter-Factor Correlation

 

 

 

F1 F2 F3 F4 F5 F6 F7

F1 1.00

F2 .34 1.00

F3 .11 .26 1.00

F4 -.12 .11 -.11 1.00

F5 -.02 -.04 .31 -.18 1.00

F6 -.01 -.13 -.12 .01 -.04 1.00

F7 .09 .57 .10 .13 -.17 .04 1.00
Note: F1: NPD program performance

F2: NPD capability
F 3: The level of tacit knowledge obtained
F4: The level of novell knowledge obtained

F5: Relationship strength

F6: Non-redundancy
F7: Collaborative experience

97

Hypothesis Testing
The model in Figure 3.1 was tested using structural equation modeling. The path
model is presented in Figure 6.1. The covariance matrix was as the input. The results of
structural analysis are presented in Table 6.4. Examination of the overall ﬁt measures
indicated a good ﬁt of the model to the data (CFI = 1.00; NFI = 0.99; chi-square =

570.36, d.f. = 343; RMSEA=0.053).

Table 6.4: Results of Path Analysis

 

 

Path Hypotheses Results
62: NPD Capability 9 NPD 6, >0 .23*
Program Performance (p<.01)
623 : Tacit Knowledge 9 NPD [623 >0 36*
Capability (p<.05)
62, : Novel Knowledge 9 NPD ’62, >0 ,11*
Capability (p<.10)
)3, : Relationship Strength 9 y“ >0 ,17*
Tacit Knowledge (P<-01)
y,“ : Relationship Strength 9 7," <0 -,22*
Novel Knowledge (p<.01)
742 : Non-Redundancy 9 Novel 742 >0 Not Signiﬁcant"

Knowledge

 

Fit Indexes: 12 =570.36 (d.f.=343); NFI=.99; CFI=1.00; IFI=1.00; RMSEA=.053.

 

*: Hypothesis is supported.
**: Hypothesis is not supported.

98

 

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99

H6 proposes that the stronger the relationship between the ﬁrm and a partner ﬁrm,
the higher the level of tacit knowledge obtained from the partner ﬁrm. In Table 6.4, the
parameter estimate is 0.17 (p<0.01). This hypothesis is, therefore, strongly supported.

H7 states that the stronger the relationship strength between the ﬁrm and a partner
ﬁrm, the lower the level of novel knowledge obtained from the partner ﬁrm. The
parameter estimate is -0.22 (p<0.01). There is a negative relationship between
relationship strength and the level of novel knowledge obtained. The hypothesis is
supported.

H8 asserts that the greater the partner non-redundancy, the higher the level of
novel knowledge obtained from the partner ﬁrm. The parameter estimate for the
hypothesis is not signiﬁcant. There is no relationship between partner non-redundancy
and the level of novel knowledge obtained. The hypothesis is not supported.

H9 suggests that the higher the level of tacit knowledge obtained, the higher the
ﬁrm NPD capability. The parameter estimate of the hypothesis is 0.36 (p<0.05). There is
a positive relationship between the levei of tacit knowledge obtained and NPD capability.
The hypothesis is supported.

H10 indicates that the higher the level of novel knowledge obtained, the higher
the ﬁrm NPD capability. The parameter estimate is 0.11 (p<0.10). The hypothesis is
supported. There is a positive relationship between the level of novel lcnowledge obtained
and the NPD capability.

Table 6.4 shows that there is a positive relationship between NPD capability and

NPD program performance (parameter estimate = 0.23, p<0.01). This is consistent with

100

the results of the ﬁrst model, in which the NPD capability is hypothesized to inﬂuence

NPD program performance positively.

Testing the Moderating Effect

To evaluate the moderating effect of collaborative experience, the sample was
split into two groups based on the mean of collaborative experience. The data above the
mean were classiﬁed as high collaborative experience, and data below the mean as low
collaborative experience. A two-group LISREL model was conducted to examine
whether or not there was any signiﬁcant difference in structural parameters between the
high collaborative experience and the low collaborative experience groups.

Before conducting the two-group comparison, the two data sets were examined
for metric unidimensionality following the same procedures as for the whole model.
Reliability, convergent validity, and discriminant validity were at acceptable levels.

For the ﬁrst analysis, the two-group model was estimated with all parameters
unconstrained (freed). This model was the base for all of the comparisons. A parameter
would be constrained to be equal when examining the moderating impact of collaborative
experience on the relevant relationship. A signiﬁcant chi-square difference between
constrained and unconstrained models indicated a difference in the relationships for the
high collaborative experience versus the low collaborative experience. In the testing, the
parameters of the relationship between relationship strength and the level of tacit
knowledge obtained, the relationship between relationship strength and the level of novel
knowledge obtained, and the relationship between partner non-redundancy and the level

of novel knowledge obtained were constrained to be equal, each in three separate models.

101

These models were compared with the unconstrained model. The results of the
comparisons are shown in Table 6.5.

Table 6.5: The Results of Two-Group Comparisons

 

 

Path Results of Multi-Group [2 Difference Conclusion
Comparison
High Low
Experience Experience

73, : Relationship .10 .23 34.01; d.f.=1 Hypothesis is
Strength 9 Tacit (P<-10) (p<.05) (p<.01) not supported
Knowledge

7,, : Relationship -.34 n.s. 50.37; d.f.=1 Hypothesis is
Strength 9 Novel (P<-10) (p<.01) supported
Knowledge

y” : Non-Redundancy .31 n.s. 1800.16; d.f.=1 Hypothesis is
9 Novel Knowledge (P<-10) (p<.01) SUpportcd

 

n.s.: not signiﬁcant.

For the relationship between relationship strength and the level of tacit knowledge
obtained, the constrained model produced chi-square = 889.40 (d.f. = 687). This model
was compared with the unconstrained model (chi-square = 855.39, d.f. =686). Table 6.5
shows that the difference of the two models is 34.01 with degrees of freedom of 1
(signiﬁcant at p<0.01). The value of the parameter estimate in the high collaborative
experience group is 0.10 (p<0.10) and the value of the low collaborative experience group
is 0.23 (p<0.05), which contradicts H11. The results suggest that the ﬁrm with low
collaborative experience gets more tacit knowledge than the ﬁrm with high collaborative
experience. This surprising ﬁnding will be discussed in Chapter 7.

When constraining the relationship between relationship strength and the level of

novel knowledge obtained, the model produced chi-square = 905.76, d.f. = 687. Table 6.5

102

 

denotes that the difference between constrained and unconstrained models is signiﬁcant
(chi-square difference = 50.37, d.f.=1; p<0.01), indicating that collaborative experience
moderates the relationship between relationship strength and the level of novel
knowledge obtained. The values of the parameter estimates are consistent with the
hypothesis (-0.34 for high collaborative experience, signiﬁcant at p<0.10; and not
signiﬁcant for low collaborative experience). This implies that ﬁrms with high
collaborative experience get more novel knowledge from weak relationships than ﬁrms
with low collaborative experience. Hypothesis 12 is supported.

For the relationship between partner non-redundancy and the level of novel
knowledge obtained, the constrained model generated chi-square of 2655.55 with degrees
of freedom 687. Table 6.5 shows that the chi-square difference is 1800.16 and d.f. = 1
(signiﬁcant at p<0.01). The parameter estimate for the high collaborative experience
group is 0.31 (p<0.10). The parameter estimate for the low experience group is not
signiﬁcant. Thus, hypothesis 13 is supported. It is noted that in the full model, the
relationship between non-redundancy and the level of novel knowledge obtained is not
signiﬁcant (see Table 6.4). The relationship is signiﬁcant for the ﬁrm with high

collaborative experience however. This interesting ﬁnding will be addressed in Chapter 7.

103

CHAPTER 7

DISCUSSION AND CONCLUSION

This chapter discusses the implications of the analyses presented in Chapter 5 and
Chapter 6. The chapter begins with a summary of the ﬁndings from the two studies. The
contribution to theory and research, as well as implications for managers, are then given.

Finally, limitations and ﬁrture research directions are discussed.

Summary

This dissertation addresses a paradigm shift in new product development, that is,
the paradigm shift from do-it-all (football shaped NPD) to share-the-burden (barbell
shaped NPD). Two models are tested. The ﬁrst model studies how to externalize NPD
tasks and how extemalization impacts both NPD capability and NPD program
performance. The second model focuses mainly on how to get knowledge (both tacit and
novel) from partner ﬁrms to enhance both NPD capability and NPD program
performance.
The First Model

The ﬁrst model is developed based on the principles of internalization theory and
the resource-based view of the ﬁrm, as well as on the NPD literature. It is hypothesized
that the ﬁrm will externalize unimportant and complex NPD tasks. These hypotheses are
based on the special requirements in NPD related to time, cost, and quality. It is also
hypothesized that externalizing unimportant NPD tasks is beneﬁcial to both NPD

capability and NPD program performance, while externalizing very important tasks is

104

 

detrimental to both NPD capability and NPD program performance. These arguments are
based on the principle that the ﬁrm should always protect and strengthen core
competencies. Firm NPD capability is hypothesized to positively inﬂuence NPD program
performance.

Data were collected from US. high-tech ﬁrms through a questionnaire survey.
The sample represented a wide variety of industries, including chemical, mechanical,
electronics, aircraft, instrument, and computer software. The respondents were executives
in charge of NPD, such as vice presidents of R&D or engineering. This ensured that the
respondents provide accurate information on the management of ﬁrm NPD program and
ﬁrm level operations.

The above hypotheses were tested through a series of regressions. The results
support hypothesis l—the greater the importance of NPD tasks, the less the extent of
extemalization. The result is consistent with the principles of internalization theory and
the resource-based view of the ﬁrm. That is, when NPD tasks are very important for
customer value creation and for building and strengthening ﬁrm core competencies, the
ﬁrm is likely to internalize these tasks. The ﬁrm can thus establish the core competencies
by focusing on the key technologies and then take advantage of superior competitive
position in the marketplace.

The results are consistent with previous studies on small technology based ﬁrms
(Kurokawa 1997) and ﬁrms in pharmaceutical industry (Pisano 1990). Executives
interviewed during the study also support the notion of externalizing non-core tasks to
increase R&D department focus. The R&D department can act more strategically to deal

with the unstable market.

105

 

The data do not support hypothesis 2—the greater the complexity of NPD tasks,
the greater the extent of extemalization. Further analysis found a U-shape relationship
between complexity of NPD tasks and the extent of extemalization. The ﬁrm extemalizes
low and high complex NPD tasks and intemalizes the middle.

Extemalizing highly complex tasks is consistent with the principle of
internalization theory and the resource-based view of the ﬁrm. First, there is a cost
analysis in the decision-making. Highly complex NPD tasks may require the ﬁrm to
invest greatly to perform these tasks. Thus, the ﬁrm choose to externalize these tasks
enhance the efﬁciency of NPD. Second, the time pressure does not allow the ﬁrm to
internalize these complex tasks. For ﬁrms in a highly competitive environment, the need
for investment in the NPD process and the time pressure would be the dominant factors in
decision-making.

Surprisingly, it is found that the ﬁrm extemalizes low complex tasks. One
explanation would be the value-adding perspective in NPD. The ﬁrm should invest
heavily only in its core competencies and wherever it sees a unique opportunity for
adding value. Quinn and Hilmer (1994) pointed out that the ﬁrm should select and
perform activities that will create unique value and competitive edge. As the ﬁrm focuses
on value-adding tasks in NPD, it is willing to externalize more routine, low value-added
research and technical activities. In other words, the ﬁrm would externalize low complex
NPD tasks. The tasks in the middle are likely to have the great value-creation potential.
This deserves the systematic examination in future research.

The results support the moderating effect of the importance of NPD tasks on the

relationship between extemalization and NPD capability. In particular, evidence is found

106

 

that the relationship between extemalization and NPD capability decreases from positive
to negative as the level of the importance of NPD tasks increases. In other words,
externalizing unimportant NPD tasks contributes to NPD capability. Extemalizing very
important NPD tasks weakens NPD capability.

Hypothesis 4 is supported by the data. According to hypothesis 4, the relationship
between extemalization and NPD program performance decreases from positive to
negative as the level of the importance of NPD tasks increases. Extemalizing unimportant
NPD tasks enables the ﬁrm to reduce cost, increase speed, and improve the quality of new
product development. Extemalizing very important NPD tasks may result in the loss of
the identity of the ﬁrm in the marketplace, leading to poor NPD program performance.

This result suggests that when making extemalization or internalization decisions,
assessing the importance of NPD tasks is vital. Extemalizing unimportant NPD tasks
allows the ﬁrm to have a more focused strategy and frees limited resources for more
value-added and/or strategic applications, thus strengthening NPD capability.
Extemalizing NPD tasks that are closely related to ﬁrm core competencies and/or to
customer value creation would run the risk of losing ﬁrm core competencies. NPD
managers must be aware that core competencies are the base for ﬁrm survival. Satisfying
customers is the ultimate goal of NPD. NPD tasks that are related to ﬁrm core
competencies and customer satisfaction should be under the ﬁrm’s control. It is also
noted that the purpose of externalizing NPD tasks is better utilization of ﬁrm internal
resources and capabilities.

One danger of extemalization is the loss of ﬁrm core competencies. For example,

other ﬁrms may imitate the ﬁrm’s key technology and compete with the ﬁrm. Eventually,

107

Vt, IJ'T

n-u-‘LZ. '

 

the ﬁrm may lose core competencies and be in a difﬁcult situation in the marketplace.
This is consistent with the opinion of interviewees. Many executives hold that an
extemalization strategy enables the ﬁrm to free some resources and capabilities to work
on more value-added technology. At the same time, they warned that the ﬁrm NPD
capability and performance might suffer if it forgot to protect core competencies.
Consistent with the NPD literature, NPD capability positively inﬂuences NPD
program performance. NPD capability is the base for ﬁrm to develop competitive
products. Grifﬁn (1997a, 1997b) and Li and Calantone (1998) stress the product
competitive advantage in the marketplace. This requires the ﬁrm to have high NPD
capability and develop products effectively and efﬁciently. Furthermore, only with a
super NPD capability can the ﬁrm deal with changing customer tastes and develop

products customers want.

108

Goodifgn
Poor figm
_ 4»

Lose Core Competencies

\ ﬂ ..............................................................

Figure 7.1: Three Types of Barbell Design

 

(a)

   

 

 

Figure 7.1 illustrates the importance of extemalization. Scenario (a) is the ideal
barbell design, in which the ﬁrm has strong internal capability. At the same time, the ﬁrm
uses external resources and capabilities to the greatest extent. Scenario (b) is a poor
design. Even though the ﬁrm possesses strong internal capability, it does not effectively

mobilize external factors. Scenario (c) is the worst case, in which the ﬁrm loses

109

everything because of too much extemalization. Once again, protecting and strengthening
the core competencies during the extemalization is emphasized.
The Second Model

The second model is built mainly on the principle of internalization, i.e.,
leveraging internal capabilities (strengthening the “bar” of the barbell). Internalization
theory advises to internalize critical NPD tasks. The resource-based View of the ﬁrm
recommends continuously enhancing internal capability. How to get knowledge from
other ﬁrms in order to improve ﬁrm NPD capability is the main theme in the second
model, as the resource-based view of the ﬁrm explicitly underscores that knowledge is a
critical source for competitive advantage. It is proposed that relationship strength
positively inﬂuences the level of tacit knowledge obtained and negatively affects the level
of novel knowledge obtained. It is also hypothesized that partner non-redundancy
positively affects the level of novel knowledge obtained. The level of both tacit
knowledge and novel knowledge obtained positively inﬂuences ﬁrm NPD capability,
which in turn affects ﬁrm NPD program performance. These theoretical predictions were
tested using structural equation modeling.

The results support hypothesis 6. Relationship strength is positively related to the
level of tacit knowledge obtained from the partner ﬁrm. Tacit knowledge transfer requires
in—depth, frequent, two-way interactions, which is the characteristic of strong
relationships. It is noted that tacit knowledge is not likely to be transferred completely
from one ﬁrm to the other. The transferring of tacit knowledge is a cumulative process.
The stronger the relationships, the more likely the ﬁrm is to get higher level of tacit

knowledge.

110

 

Hypothesis 7 is supported by the data. Relationship strength is negatively related
to the level of novel knowledge obtained. NPD requires innovative ideas and new
knowledge. One disadvantage of strong relationships is the difﬁculty of obtaining new
knowledge from partners. This study suggests that new knowledge is more likely to be
found in ﬁrms not closely related.

Uzzi (1996) stresses the value of both strong and weak ties to competitive
advantage. Different ties have different roles. The optimal network structure is composed
of a few strong ties and many (large number of) weak ties. Obtaining tacit knowledge
from strong ties is more efﬁcient because it requires repeated transactions. Obtaining
novel knowledge is more efﬁcient from a large number of weak ties.

Surprisingly, partner non-redundancy is not correlated with the level of novel
knowledge obtained. Hypothesis 8 is not supported. . In the two-group analysis, a positive
relationship is found in ﬁrms with high collaborative experience, but only signiﬁcant at a
marginal level (p=0.1). Redundant partners are those closely related to other ﬁrms in the
network. It is likely that managing similar partners is easier than dealing with a wide
diversity of ﬁrms in the network. Processing information from wide variety of ﬁrms takes
time and requires more experience. It is likely that valuable, novel knowledge is ignored
due to too many distractions. This ﬁnding, however, cannot lead to the conclusion that
more redundant partners are better in the network. Bartunek and Moch (1987) ﬁnd that
the ﬁrm is not willing to accept new knowledge or make change unless organizational
members experience a crisis or to perceive that their existing schema is inadequate.
Managing a wide diversity of ﬁrms in the network is a challenge for marketing managers.

It is suggested that the ﬁrm develop efﬁcient mechanism to manage external knowledge.

11]

 

The levels of both tacit knowledge and novel knowledge obtained are positively
related to NPD capability, supporting Hypotheses 9 and 10. This ﬁnding is consistent
with the resource-based view of the ﬁrm, which continuously stresses the role of
knowledge in ﬁrm NPD. Liebeskink (1996) states that the efﬁcient way to protect
valuable knowledge is to obtain knowledge from outside ﬁrms. Rokeach and Grube
(1979) also note that the ﬁrm that obtains knowledge from partner ﬁrms is more active
than the ﬁrm that creates knowledge relying on its own. As NPD becomes more complex
and requires knowledge the ﬁrm does not have, obtaining knowledge from other ﬁrms
become critical.

The ﬁrm with high collaborative experience gets less tacit knowledge from strong
relationships than the ﬁrm with low collaborative experience. This contradicts Hypothesis
11. One explanation is the rigidity of decision making of the ﬁrm with high collaborative
experience. Simonin (1997) points out that previous collaborative experience alone does
not ensure that a ﬁrm will beneﬁt from a collaboration. Staw (1981) suggests that prior
experience may also induce rigid decision behaviors, or a tendency to process information
in an automatic, habitual manner. The experienced ﬁrm, for example, is likely to acquire
only the type of information with which it is familiar, which may result in judgment bias.
Staw (1991) warns about the problems of belief structure rigidity and other related
constructs, such as selective perception, perceptual screens, and escalation of
commitment. The ﬁrm with low collaborative experience is likely to be that newly
emerged in the market place. It is active, eager to learn, and follows the formal rule of
knowledge acquisition, resulting in more tacit knowledge transfer.

The ﬁrm with high collaborative experience gets more novel knowledge from

112

 

weak relationships and from non-redundant partners, supporting hypotheses 12 and 13.
Collaborative experience is important for obtaining novel knowledge. Both relationship
strength and partner non-redundancy have a positive effect on the level of novel
knowledge obtained for the ﬁrm with high collaborative experience. For the ﬁrm with
low collaborative experience, these two relationships are not signiﬁcant. Powell, KOput,
and Smith-Doerr (1996) argue that collaborative experience is necessary to access new,
diverse information. On the one hand, the ﬁrm with low collaborative experience is likely
to have a smaller number of ﬁrms in the network. On the other hand, the ﬁrm with low
collaborative experience lacks the capability to manage a diverse portfolio of ties, leading
to the insigniﬁcant impact of relationship strength and partner non-redundancy on the
level of novel knowledge obtained.
Contributions to Theory and Research

To the NPD Literature

Research on NPD is criticized as being “atheoretical”, which inhibits the full
understanding and explanation of NPD activities (Brown and Eisenhardt 1995). Montoya-
Weiss and Calantone (1994) call for the integration of NPD literature using a theoretical
framework. This study is a valuable attempt to ﬁll this gap to frame NPD problems by
expanding the vision of internalization theory and the resource-based View of the ﬁrm.

The rationales of internalization theory and the resource-based view of the ﬁrm ﬁt
excellently with the present research question. When considering the extemalization
problem, internalization theory advises to externalize unimportant tasks and internalize
critical ones. The research-based view of the ﬁrm advocates internalizing tasks that are

closely related to ﬁrm core competencies or customer value creation.

113

f 5.1..qu

 

The resource-based view of the ﬁrm proposes to get knowledge from partner
ﬁrms in order to enhance NPD capability. Both tacit knowledge and novel knowledge
contribute to NPD capability development. Expanding on the work of Hansen (1999), this
study suggests getting tacit knowledge from strong relationships and novel knowledge
from weak relationships.

This study also advocates mobilizing both internal and external resources and
capability to develop NPD capability and to improve NPD program performance by
applying the most recently developed resource-based view of the ﬁrm. The internalization
principle speciﬁes the leverage of internal resources and capabilities, i.e., the best
utilization of internal factors. The extemalization principle indicates the leverage of
external resources and capabilities, i.e., to mobilize external resources and capabilities to
the greatest extent in NPD.

The study is driven by an interest in understanding how to strategically manage a
portfolio of NPD tasks. A review of the literature revealed that little attention was given
by scholars on the three research questions raised in Chapter One. A large scale empirical
study has been lacking. In the present case, a conceptual model was developed based on
internalization theory and the resource-based view of the ﬁrm. A set of hypotheses was
tested with data from survey research involving R&D managers across a range of US.
industries.

This is the ﬁrst study to clearly address the paradigm shift from barbell to football,
i.e., from do-it-all to share-the-burden. Research on this issue is imperative as the

competition in the marketplace becomes increasingly brutal. It is hoped that this study

114

will begin a research stream that systematically examine the strategic management of
NPD.
To Internalization Theory and Resource-based View of the Firm

This study also contributes to the development of internalization theory and the
resource-based view of the ﬁrm in the NPD domain. This study is the ﬁrst attempt to test
the principle of extemalization theory in NPD. Constructs of internalization theory were
operationalized. Firm core competencies and customer value creation were identiﬁed as
critical for ﬁrm success. Measures based on both theories were developed in the NPD
context.

Implications for Managers

The study answers the managerial question of how to strategically manage a
portfolio of NPD tasks to speed up product development, to increase quality, and to
decrease cost. It provides some guidelines to managers for deciding what kinds of NPD
tasks should be performed in-house and what kinds of NPD tasks should be given to other
ﬁrms. Signiﬁcant negative relationship between extemalization and NPD capability, as
well as between extemalization and NPD program performance warns NPD managers to
protect core competencies in strategic decision-making.

The ﬁndings on the relationship between the complexity of NPD tasks and
extemalization of NPD tasks suggest that the ﬁrm is likely to externalize both low and
high complex NPD tasks. On the one hand, low complex tasks are usually industrial
standard designs, which add little value to the ﬁrm. One the other hand, high complex
NPD tasks need great investment if the ﬁrm wants to develop them in-house.

Extemalizing both low and high complex NPD tasks is likely to be the best choice.

115

 

Both tacit knowledge and novel knowledge are critical for the development of
ﬁrm NPD capability. This study tells managers that tacit knowledge, which usually is
uncoded, is more likely to be transferred between ﬁrms in strong relationships. Novel
knowledge, however, is likely to be found in the ﬁrm not closely related.

The extemalization dilemma—to internalize or to extemalize—is of central
importance. While cost is always important in any business decision, managers should
consider strategic issues in conjunction with ﬁnancial issues. Companies that continue to

make decisions based solely on cost will eventually wither and die, as many already have.

Limitations and Future Research Directions

First, this study lacks a dynamic dimension in the model. It is recommended that
longitudinal data be collected to study how extemalization affects ﬁrm long-term
performance.

Second, this study focuses on high-tech industries, which are in a highly
competitive environment. The story may differ in other industries. In a highly competitive
environment, the speed in NPD development weighs high in strategic decision-making.
For ﬁrms in a relatively low competitive environment, the cost of NPD may be the major
consideration. Data should be collected in other industries to test the model.

Third, extemalization may take different forms such as strategic alliances or
market-based transactions. Strategic alliance may desirable if the tasks are important for
core competencies and include frequent transactions. For NPD tasks that are unimportant

for core competencies and involve few transactions, a traditional market-based

116

 

relationship is recommended. The use of different organizational forms to manage
extemalization is an important area for future research.

Future research could also explore other ways to leverage external resources and
capabilities, such as external acquisition, strategic alliance, supplier integration, and

customer involvement in NPD.

117

m

 

REFERENCES

Aiken, Leona S. and Stephen G. West (1991), Multiple Regression: Testing and
Interpreting Interactions, Newbury Park, CA: Sage Publications.

Anderson, James C. and David W. Gerbing (1982), “ Some Methods for Respecifying
Measurement Models to Obtain Unidimensional Construct Measurement,”
Journal of Magketing Research, 19 (4), 453-460.

Anderson, James C. and James A. Narus (1990), “A Model of Distributor Firm and
Manufacturer Firm Working Partnerships,” Journal of Marketing, 54 (1), 42-58.

Armstrong, J. Scott and Terry. Overton (1977), “Estimating Nonresponse Bias in Mail
Surveys,” Journal of Marlgting Reseam, 14(3), 396-402.

Ashman, Darcy, L. David Brown, and Elizabeth Zwick (1998), “The Strength of Strong
and Weak Ties: Building Social Capital for the Formation and Governance of
Civil Society Resource Organizations,” NonProﬁt Maﬂgement and Leadership, 9
(2), 153-171.

Barney, Jay B. (1986), “Organizational Culture: Can It Be a Source of Sustained
Competitive Advantage?” ﬂdemv of Manggement Review, 11 (3), 656-666.

Barney, Jay B. (1991), “Firm Resources and Sustained Competitive Advantage,” Journal
of Management 17 ( 1), 99-120.

Bartunek, J. and M. Moch (1987), “First-Order, Second-Order, and Third-Order Change
an Organization Development Interventions: A Cognitive Approach,” Journal of
Qiplied Behavior Science, 23 (3), 483—500.

Bonaccorsi, Andrea and Andrea Lipparini (1994), “Strategic Partnerships in New Product
Development: An Italian Case Study,” Journal of Product Innovation
Management, 11 (2), 134-145.

Bonner, Joseph Michael (1999), “Customer Involvement in New Product Development:
Integration Intensity and Customer Network Issues,” Dissertation, University of
Minnesota.

Brockhoff, Klaus (1992), “R&D Cooperation Between Firms: A Perceived Transaction
Cost Perspective,” Management Science, 38 (4), 514-524.

Brown, Shona L. and Kathleen M. Eisenhardt (1995), “Product Development: Past

Research, Present Findings, and Future Directions,” Academy of Management
Review, 20 (2), 343-378.

118

 

Buckley, Peter J. (1983), “New Theories of International Business: Some Unresolved
Issues,” In The Growth of Internationgl Business, Mark C. Casson, ed. London:
Allen & Unwin, 34-50.

Buckley, Peter J. (1988), “The Limits of Explanation: Testing the Internalization Theory
of the Multinational Enterprises,” Journal of International Studies, 19 (2), 1-16.

Buckley, Peter J. and Mark C. Casson (1976), The Future of the Multinati_onpl Enterprise,
London: Macmillan.

n; n A.—

Buckley, Peter J. and Mark C. Casson (1998), “Models of the Multinational Enterprise,”
Joum_al of International Business Studies, 29 (1), 21-44.

 

Burt, Ronald (1983), Applied Network Analysis: A Methodological Introduction, Beverly _
Hills: Sage Publications. ’

Burt, Ronald (1992), Structural Holes: The Social Structure of Competition, Cambridge,
MA: Harvard University Press.

Byrne, B. M. (1994). Structural Equation Modeling with E08 and EOS/Windows: Basic

Concgpts, Applications, and Progamming, Thousand Oaks, CA: Sage
Publications.

Calantone, Roger J. and Robert G. Cooper (1979), “A Discriminant Model for Identifying
Scenarios of Industrial New Product Failure,” Journal of the Academy of
Marketing Science, 7 (3), 163-83.

Calantone, Roger J. and Robert G. Cooper (1981), “New Product Scenarios: Prospects for
Success,” Journal of Marketing, 45 (2), 48-60.

Calantone, Roger J. and C. Anthony di Benedetto (1988), “An Integrative Model of the
New Product Development Process,” Journal of Product Innovation Management.
5(9), 201-15.

Casson, Mark C. (1982), “Transaction Costs and Theory of MNEs,” in New Theory of the
Multinational Enterprise, Alan M. Rugrnan, ed. New York: St. Martin’s Press.

 

Casson, Mark C. (1984), “The Theory of Vertical Integration: A Survey and Synthesis,”
Journal of Economic Studies, 11 (2), 3-43.

Casson, Mark C. (1994), “Why Are Firms Hierarchical?” International Joumpl of the
Economics of Business, 1 (1), 3-40.

119

Churchill, Gilbert A. (1979), “A Paradigm for Developing Better Measures of Marketing
Constructs,” Journal of Marketing Researph, 16 (1), 64-70.

Clark, Kim B. and Takahiro Fujimoto (1990), “The Power of Product Integrity,” Harvard
Business Review, 68 (6), 107-118.

Coase, Ronald Harry (1937), “Nature of the Firm,” Economica, 4, 386-405.

Cohen, Morris A. and Patricia Cohen (1983), Applied Multiple Regression/Correlation
Analysis for Behavioral Science, Hillsdale, NJ: Lawrence Erlbaum Associates.

Collis, David J. (1994), “Research Note: How Valuable Are Organizational
Capabilities?” Strategic Management Journal, 15 (Special Issue), 143-152.

 

Constant, David, Lee Sproull, and Sara Kiesler (1996), “The Kindness of Strangers: The
Usefulness of Electric Weak Ties for Technical Advice,” Organization Science, 7
(2), 119-135.

Cooper, Robert G. (1979), “The Dimensions of Industrial New Product Success and
Failure,” Journal of Marketing, 43 (3), 93-103.

Cooper, Robert G. (1984), “The Performance Impact of Product Innovation Strategies,”
European Journal of Marketing, 18 (5), 5-54.

Cooper, Robert G. (1993), Winning at New Products: Accelerating the Process from Idea
to Launch, Reading, MA: Addison-Wesley.

Cooper, Robert G. and Elko J. Kleinschmidt (1987), “New Products: What Separates
Winners from Losers?” The Journal of Product Innovation Management 4(3),
169-184.

Crawford, Merle (197 7), “Marketing Research and New Product Failure Rates,” Journal
of Marketimz, 41 (2), 51-61.

Croisier, Bernard (1999), “The Governance of External Research: Empirical Test of
Some Transaction-Cost Related Factors,” R&D Management, 28 (4), 289-298.

Damanpour, Fariborz (1991a), “Innovation Adoption and Organizational Performance,”
In Innovation Creativity at Worﬂsychological and Organizational Strategies, M.
A. West and J. L. Farr, Eds. West Sussex, England: John Wiley & Sons Ltd.

Damanpour, Fariborz (1991b), “Organizational Innovation: A Mete-Analysis of Effects

of Determinants and Moderators,” Academy of Management Journal, 34 (3), 555-
590.

120

Das, T.K. and Bing-Sheng Teng (2000), “A Resource-Based Theory of Strategic
Alliance,” Journﬂf Management, 20 (1), 31-61.

Davies, H. (1977), “Technology Transfer Through Commercial Transactions,” Journal of
Industrial Economy, 26 (2), 161 -1 75.

Day, George S. and Robin Wensley (1988), “Assessing Advantage: A Framework for
Diagnosing Competitive Superiority,” Journal of Marketing, 52 (2), 1-20.

DeVellis, Robert F. (1991), Scale Development: Theory and Applications, Newbury Park, .
CA: Sage. 1

D02, Yves L. and Gary Hamel (1998), Alliance Advantage: The Art of Creating Value
Through Partnering. Boston : Harvard Business School Press.

 

Doz, Yves L., Paul M. 01k, and Peter Smith Ring (2000), “Formation Processes of R&D F
Consortia: Which Path to Take? Where Does It Lead?” Strategic Management
Journal, 21 (3), 239-266.

Dumaine, B. (1989), “How Managers Can Succeed Through High Speed,” Fortune, l3
(2), 54-59.

Durvasula, Srinivas, J. Craig Andrews, Steven Lysonski, and Richard G. Netemeyer
(1993), “Assessing the Cross-National Applicability of Consumer Behavior
Model: A Model of Attitude Toward Advertising in General,” Journal of
Consumer Research, 19(2), 626-636.

Dutton, Barbara (1992), “US Car Companies: Changing Fast Enough?” Manufacturing
Systems, 10 (1), 12-13.

Dwyer, F. Robert, Paul H. Schurr, and Sejo Oh (1987), "Developing Buyer-Seller
Relationships," Journal of Marketing, 51 (2), 11-27.

lDyer, Jeffrey H. and William G. Ouchi (1993), “J apanese-Style Partnerships: Giving
Companies 3 Competitive Edge,” Sloan Management Review, 35 (1), 51-58.

Eliashberg, J ehoshua and Thomas S. Robertson (1988), “New Product Preannouncing
Behavior: A Market Signaling Study,” Journal of Marketing Research, 25 (3),
282-292.

Fine, Charles H. (1998), Clockspeed: Winning Industry Control in the Age of Temporary
Advantage, MA: Perseus Books Group.

121

Fisher, Robert J., Elliot Maltz, and Bernard J J aworski (1997), “Enhancing
Communication Between Marketing and Engineering: The Moderating Role of
Relative Functional Identiﬁcation,” Jomnal of Marketing, 61 (3), 54-70.

Friar, J. and M. Horwitch (1985), “The Emergence of Technology Strategy: A New
Dimension of Strategic Management,” Technology in Society, 7, 143-178.

Gabbay, Shaul M. and Ezra W. Zuckerman (1998), “Social Capital and Opportunity in
Corporate R&D: The Contingent Effect of Contact Density on Mobility
Expectations,” Social Science Research, 27 (2), 189-217.

Garbarino, Ellen and Mark S Johnson (1999), “The Different Roles of Satisfaction, Trust,
and Commitment in Customer Relationships,” Journal of Marketing, 63 (2), 70-
87.

Garvin, David A. (1988), Managing Quality, New York: The Free Press.

Gatignon, Hubert and Jean-Marc Xuereb (1997), “Strategic Orientation of the Firm and
New Product Performance,” Journal of Marketing Research, 34 (1), 77-90.

Gerbing, David W. and James C. Anderson (1988), “An Updated Paradigm for Scale
Development Incorporating Unidimensionality and Its Assessment,” Journal of
Marketing Researc_h, 25 (2), 186-192.

Goes, James B. and Seung Ho Park (1997), “Interorganizational Links and Innovation:
the Case of Hospital Services,” Academy of Management Journal, 40 (3), 673-
696.

9

Graham, M. (1985), “Corporate Research and Development: The Latest Transformation,’
Technology in Society, 7, 179-196.

Grant, Robert M. (1991), “The Resource-Based Theory of Competitive Advantage:
Implications for Strategy Formulation,” California Management Review, 33 (3),
1 14-135.

Grant, Robert M. (1996), “Toward A Knowledge-Based Theory of the Firm,” Strategic
Management Journal, 17, 109-122.

Grant, Robert M. (1997), “The Knowledge-Based View of the Firm: Implications for
Management Practice,” Long Range Flaming, 30 (3), 450-454.

Grant, Robert M. and Charles Baden-Fuller (1995), “A Knowledge-Based Theory of
Inter-Firm Collaboration,” Academy of Management J ourna_l, Best Paper
Proceedings, 17-21.

122

Grifﬁn, Abbie (1997a), “PDMA Research on New Product Development Practices:
Updating Trends and Benchmarking Best Practices,” Journal of Product
Innovation Management, 14 (6), 429-458.

Grifﬁn, Abbie (1997b), “The Effect of Project and Process Characteristics on Product
Development Cycle Time,” Journal of Marketing Research, 34 (1), 24-35.

Gundlach, Gregory, Ravi Achrol, and John T. Mentzer (1995), “The Structure of
Commitment in Exchange,” Journal of Marketing, 59 (1), 78-92.

Hair, Joseph F., Jr., Rolph E. Anderson, Ronald L. Tatham, and William C. Black (1995),
Multivariate Data Analysis, 4th ed. Englewood Cliffs, NJ: Prentice Hall.

Hakansson, Hakan (1989), Corporate Technological Behavior: Cooperation am
Networks, New York: Routledge.

Han, J in K., Namwoon Kim, and Raj endra K. Srivastava (1998), “Market Orientation and
Organizational Performance: Is Innovation a Missing Link?” Journal of
Marketing, 62 (4), 30-45.

Hansen, Morten T. (1999), “The Search-Transfer Problem: The Role of Weak Ties in
Sharing Knowledge across Organization Subunits,” Administrative Science

Quarterly, 44 (1), 82-111.

Hedlund, Gunnar (1994), “A Model of Knowledge Management and the N-Form
Corporation,” Stpategic Management Journal, 15 (Special Issue), 73-90.

 

Heide, Jan B. and George John (1992), “Do Norms Matter in Marketing Relationships?”
Journal of Marketing, 56 (2), 32-44.

Hennart, Jean Francois (1982), A Theory of Multinational Enterprise, Ann Arbor, MI:
University of Michigan Press.

Hobday, Mike (1998), “Product Complexity, Innovation and Industrial Organization,”
Research Policy, 26 (2), 689-710.

Howells, Jeremy (1999), “Research and Technology Outsourcing,” Technology Analysis
and Sgtegic Management, 11 (1), 17-29.

Hurley, Robert F., and G. Tomas M. Hult (1998), “Innovation, Market Orientation, and
Organizational Learning: An Integration and Empirical Examination,” Journal of
Marketing, 62 (3), 42-54.

Inkpen, Andrew C. (1998), “Learning and Knowledge Acquisition Through International
Strategic Alliances,” The Academy of Management Executive, 12 (4), 69-80.

123

Jaccard, James, Choi K. Wan, and Robert Turrisi (1990), “The Detection and
Interpretation of interaction Effects Between Continuous Variables in Multiple
Regression,” Multivariate Behavioral Research, 25 (3), 467-78.

Jacobson, Robert and David A. Aaker (1987), “The Strategic Role of Product Quality,”
Journal of Mapketing, 51 (4), 31-44.

Jaworski, Bernard J ., Vlasis Stathakopoulos, and H. Shanker Krishnan (1993), “Control
combinations in marketing: Conceptual framework,” Journal of Marketing, 57 (1),
57-69.

Johnston, J. (1984), Econometric Methods, 3rd ed. New York: McGraw-Hill.

Kazanjian, Robert K. and Hayagreeva Rao (1999), “Research Note: The Creation of
Capabilities in New Ventures—A Longitudinal Study,” Organization Studies, 20
(1), 125-142.

Kessler, Eric H. and Alok K. Chakrabarti (1996), “Innovation Speed: A Conceptual
Model of Context, Antecedents, and Outcomes,” The Agoademv of Management
Review, 21 (4), 1143-1191.

Killing, J . P. (1983), Strategies for Joint Venture Success, New York: Praeger.

Kozlowski, Steve W. J. and Brian M. Hults (1986), “Joint Moderation of the Relation
Between Task Complexity and Job Performance for Engineers,” Journal of
Applied Psychology, 71 (2), 196-202.

Kraatz, (1998), “Learning by Association? Interorganizational Networks and Adaptation
to Environmental Changes,” Academy of Management J oumal, 41 (6), 621-643.

Krause, Daniel R., Thomas V. Scannell, and Roger J. Calantone (2000), “A Structural
Analysis of the Effectiveness of Buying F irms’ Strategies to Improve Supplier
Performance,” Decision Science, 31 ( 1), 33-55.

Kurokawa, Susumu (1997), “Make-or-Buy F ecisions in R&D: Small Technology Based
Firms in the United States and Japan,” IEEE Transactions on Engineering
Management, 44 (2), 124-134.

Langlois, Richard N. and Paul L. Robertson (1992), “Networks and Innovation in a

Modular System: Lessons from the Microcomputer and Stereo Component
Industries,” Research Policy, 21 (4), 297-313.

124

Li, Tiger and Roger J. Calantone (1998), “The Impact of Market Knowledge Competence
on New Product Advantage: Conceptualization and Empirical Examination,”
Journal of Marketing, 62 (4), 13-29.

Liebeskind, Julia Porter (1996), “Knowledge, Strategy, and the Theory of the Firm,”
Strategic Management Journal, 17 (Special Issue), 93-107.

Lin, Xiaohua and Richard Germain (1999), “Predicting International Joint Venture
Interaction Frequency in U.S.-Chinese Ventures,” Journal of International
Marketing, 7 (2), 5-23.

Lowe, Julian and Peter Taylor (1998), “R&D and Technology Purchase Through License
Agreements: Complementary Strategies and Complementary Assets,” R&D
Management, 28 (4), 263-278.

 

Lusch, Robert F. and James R. Brown (1996), “Interdependency, Contracting, and
Relational Behavior in Marketing Channels,” Journal of Marketing, 60 (4), 19-38.

Madhavan, Ravindranath and Rajiv Grover (1998), “From Embedded Knowledge to
Embodied Knowledge: New Product Development as Knowledge Management,”
Journg of Marketing. 62 (4), 1-12.

Magee, John F. (1992), “Strategic Alliances: Overcoming Barriers to Success,” Chief
Executive, 81 (1 1/ 12), 56-60.

Maltz, Elliot and Ajay K. Kohli (1996), “Market Intelligence Dissemination Across
Functional Boundaries,” J ourgal of Marketing Research, 33 (1), 47-61.

Mason, Charlotte H. and William D. Perreault (1991), “Collinearity, Power, and
Interpretation of Multiple Regression Analysis,” Journal of Mapketing Research,
28 (3), 268-80.

McCabe, Donald L. (1987), “Buying Group Structure: Constriction at the Top,” Journal
of Marketing. 51 (4), 89-98.

McEvily, William and Akbar Zaheer (1997), “Bridging Ties: A Source of Firm

Heterogeneity in Competitive Capabilities,” Working Paper, University of
Minnesota.

McQuiston, Daniel H. (1989), “Novelty, Complexity, And Importance As Causal
Determinants,” Journal of Marketing, 53 (2), 66-79.

Meyer, M. H. and E. B. Roberts (1986), “New Product Strategy in Small Business Based
Firms: A Pilot Study,” Management Science, 32 (7), 806-821.

125

Millson, Murray R., S. P. Raj, David Wilemon (1996), “Strategic partnering for
developing new products,” Research Technolggy Management, 39 (3), 41-49.

Minahan, Tim (1998), “Platform Teams Pair with Suppliers to Drive Chrysler to Better
Designs,” Design News, 53 (10), 33-37.

Mohr, Jakki J. and John Nevin (1990), "Communication Strategies in Marketing
Channels: A Theoretical Perspective," Journal of Marketing. 50 (4), 36-51.

Mohr, J akki J. and Robert Spekman (1994), “Characteristics of Partnership Success:
Partnership Attribute, Strategic Management Journal, 15 (2), 135-152,

Mohr, J akki J ., Robert J. Fisher, and John R. Nevin (1996), “Collaborative
Communication in Interﬁrm Relationships: Moderating Effects of Integration and
Control,” Journal of Marketing, 60(3), 103-115.

Monczka, Robert M. and Robert J. Trent (1991), “Global Sourcing: A Development
Approach,” International Journal of Purchasing and Materials Management, 11
(2), 2-8.

Monczka, Robert M., Robert B. Handﬁeld, Thomas V. Scannell, Gary L. Ragatz, and
David J. Prayer (2000), New Product Development: Stgrtegies for Supplier
IntegIation, Milwaukee, Wisconsin: ASQ Quality Press.

Montoya-Weiss, Mitzi M. and Roger J. Calantone (1994), “Determinants of New Product
Performance: A Review and Meta-analysis,” Journal of Product Innmtion
Management, 11 (5), 397-418.

Moorman, Christine and Anne S. Miner (1997), “The Impact of Organizational Memory
on New Firm performance and Creativity,” Journal of Marketing Research, 34 (1),
91-1 06.

Moorman, Christine, Gerald Zaltman, and Rohit Deshpande (1992), “Relationships
Between Providers and Users of Market Research,” Journal of Marketirg
Research, 29 (3), 314-328.

Moorman, Christine and Rebecca J. Slotegraaf (1999), “The Contingency Value of
Complementary Capabilities in Product Development,” J oml of Marketing

Research, 36 (2), 239-257.

Morgan, Robert M. and Shelby D. Hunt (1994), “the Commitment-Trust Theory of
Relationship Marketing,” Journal of Marketing, 58 (3), 20-38.

Nonaka, Ikujiru (1994), “A Dynamic Theory of Organizational Knowledge Creation,”
Organizational Science, 5 (1), 14- 37.

126

Osborn, R. N. and C. C. Baughn (1990), “Forms of Inter-organizational Governance for
Multinational Alliances,” Academy of Management J ournal, 33 (3), 503-519.

 

Parasuraman, A. (1997), “Reﬂections on Gaining Competitive Advantage Through
Customer Value,” Journal of the AcademyI of Marketing Science, 25 (2), 154—161.

Penrose, Edith (1959), The Theory of the Growth of the Firm, Oxford: Blackwell.

Pisano, Gary P. (1990), “The R&D boundaries of the Firm: An Empirical Analysis,”
Administrative Science Quarterly, 35 (1), 153-176.

Porter, Michael (1980), Competitive Strategy. New York: Free Press.

Porter, Michael (1990), The Competitive Advantage of Nations, New York: Free Press.

Powell, W. W., K. W. Koput, and L. Smith-Doerr (1996), “Interorganizational
collaboration and the locus of innovation: Networks of learning in

biotechnology,” Administrative Science Quarterly, 41 (1) 116-145.

Prahalad, C. K. and Gary Hamel (1990), “The Core Competence of the Corporation,”
Harvard Business Review, 68 (3), 79-91.

Proctor, Paul (1999), “Boeing Hones New 550-Seat Transport Design,” Aviation Week &
Space Technology, 150 (17), 39.

Quinn, James Brian (2000), “Outsourcing Innovation: The New Engine of Growth,”
Sloan Mﬂgement Review, 41 (4), 13-28.

Quinn, James Brian (1999), “Strategic Outsourcing: Leveraging Knowledge
Capabilities,” Sloan Management Review, 40 (4), 9-21.

Quinn, J arnes Brian and Frederick G. Hilmer (1994), “Strategic Outsourcing,” Sloan
Management Review, 35 (4), 43-54.

Ragatz, Gary L., Robert B. Handﬁeld and Thomas V. Scannell (1997), “Success Factors
for Integrating Suppliers into Innovation,” J ourpal of Product Innovation
Management, 14(3), 190-202.

Rindﬂeisch, Aric and Christine Moorman (2001), “The Acquisition and Utilization of
Information in New Product Alliances: A Strength-of-Ties Perspective,” Journal

of Marketing, 65 (2), 1-18.

Roberts, E. B. and M. H. Meyer (1991), “Product Strategy and Corporate Success,” IEEE
Engineering Management Review, 19 (1), 4-18.

127

Robertson, Thomas S. and Hubert Gatignon (1998), “Technology Development Mode: A
Transaction Cost Conceptualization,” Strategic miragement Journal, 19 (6), 515-
53 1.

 

Rogers, Everett M. (1995), Difﬁision of Innovations, New York: Free Press.

Rokeach, M. and J. Grube (1979), “Can Values Be Manipulated Arbitrarily?” in M.
Rokeach (ed.), Understanding Human Values: Individual and Societal, New York:
The Free Press.

Rosenthal, Stephen R. (1992), Effective Product Design and Development: How to Cut
Ed Time and Incraase Customer Satisfaction, Homewood, IL: Business of One
Irwin.

Roth, Aleda V. and William E. Jackson IH (1995), “Strategic Determinants of Service
Quality and Performance: Evidence from the Banking Industry,” Management
Science, 41 (11), 1720-33.

Rothwell, R. (1972), Factors for Success in Industrial Innovation, Proiect SAPPHO-A
Comparative Study of Success and FJailure in Industrial Innmgrtion, Brighton, UK:
Science Policy Research Unit, University of Sussex.

Rowley, Tim, Dean Behrens, David Krackhardt (2000), “Redundant Governance
Structures: An Analysis of Structural and Relational Embeddedness in the Steel
and Semiconductor Industries,” Strategic Management Journal, 21 (3), 369-3 86.

Rubenstein, Albert H. (1994), “Trends in Technology Management Revised,” IEEE
Transactions on EngineeringManagement, 41 (4), 335-341.

Rugman, A. M. (1980), “A New Theory of the Multinational Enterprise:
Internationalization Versus Internalization,” Columbia Journal of World Business,
15 (1), 23-29.

Rugrnan, A. M. (1981), _In_side the Multinationals: the Economics of Internal Markets,
New York: Columbia University Press.

Rumelt, R. (1974), Strategy, Structurea and Economic Performanpe, Cambridge, MA:
Harvard Business School Press, Division of Research.

Sethi, Raj esh (2000), “New Product Quality and Product Development Teams,” Journal
of Marketing. 64 (2), l-14.

128

Simonin, Bernard L. (1997), “The Importance of Collaborative Know-How: An
Empirical Test of the Learning Organization,” Academy of Maragement Journal,
40(5), 1150-1174.

Simonin, Bernard L. (1999), “Transfer of Marketing Know-How in International Strategic
Alliances: An Empirical Investigation of the Role and Antecedents of Knowledge
Ambiguity,” The Journal of International Business Studies, 30 (3), 463-490.

Singh, Kulwant (1997), “The Impact of Technological Complexity and Interﬁrm
Cooperation on Business Survival,” Academy of Management J oumal, 40 (2),
339-367.

Slater, Stanley F. (1997), “Developing A Customer Value-Based Theory of the Firm,”
Joumﬂf the Academy of Marketing Science, 25 (2), 162-167.

Song, Michael and Mark E. Parry (1997), “The Determinants of Japanese New Product
Successes,” Journal of Marketing, 34(1), 64-76.

Staw, B. (1981), “The Escalation of Commitment to A Course of Action,” Academy of
Management Review, 6 (4), 577-587.

Stump, Rodney L. and Jan B. Heide (1996), “Controlling Supplier Opportunism in
Industrial Relationships,” Journal of Marketing, 33 (4), 431-441.

Subramaniam, Mohan (1999), “Transfer and Deployment of Knowledge Across Country
Borders for Global New Product Development Capability, working paper 99-03,
CIBER, School of Business Administration, University of Connecticut.

Taggart, James H. (1997), “R&D Complexity in UK Subsidiaries of Manufacturing
Multinational Corporations,” Technovation, l7 (2), 73-84.

Tatikonda, Mohan V. and Stephen R. Rosenthal (2000), “Technology Novelty, Project
' Complexity, and Product Development Execution Success: A Deeper Look at
Task Uncertainty in Product Innovation,” IEEE Transactions on Engineering
Management, 47 (1), 74-87.

Teece, David J. (1981), “Multinational Enterprise: Market Failure and Market Power
Consideration,” Sloan Maaagement Review, 22 (3), 3-17.

Teece, David J. (1996), “Firm Organization, Industrial Structure, and Technological
Innovation,” Journal of Economic Behavior and Organization, 31 (2), 193-224.

Tidd, Joe (1995), “Development of Novel Products Through Intraorganizational and

Interorganizational Networks: the Case of Home Automation,” the Journal of
Product Innovation Management, 12 (4), 307-322.

129

Ulrich, Karl T. and Stephen D. Eppinger (1995), Product Design and Development, New
York: McGraw-Hill, Inc.

Uzzi, B. (1996), “The Sources and Consequences of Embeddedness for the Economic
Performance of Organizations: The Network Effect,” American SocioloaTcal
Review, 61 (4), 674-698.

 

van den Bosch, F.A.J. and RC. Elferich (1993), “Make, Buy or Cooperate Decision with
Respect to Research and Development in International Business Networks,”
Advances in International Marketig, 5, 191-201.

Venkatesan, Ravi (1992), “Strategic Sourcing: To Make or Not to Make,” Harvard
Business Review, 70(6), 98-107.

Verona, Gianmario (1999), “A Resource-Based View of Product Development,”
Academy of Management Review, 24 (1), 132-142.

Veugelers, Reinhilde and Bruno Cassiman (1999), “Make and Buy in Innovation
Strategies: Evidence from Belgian Manufacturing Firms,” Research Policy. 28 (1),
63-80.

Wemerfelt, Birger (1984), “A Resource-Based View of the Firm,” Strategic Management
Journal, 5 (2), 171-181.

Williamson, Oliver E. (1975), Markets and Hierarchies: Analysis and Antitrust
Implications, New York: The Free Press.

Williamson, Oliver E. (1991), “Comparative Economic Organization: The Analysis of
Discrete Structural Alternatives,” Administrative Science Quarterly, 36 (2), 269-
296.

 

Wilson, Darryl D. and David A. Collier (2000), “An Empirical Investigation of the
Malcolm Baldrige National Quality Award Causal Model,” Decision Sciences, 31
(2), 361-390.

Wind, Jerry and Vijay Mahajan (1997), “Issues and Opportunities in New Product
Development: an Introduction to the Special Issue,” Journal of Marketing
Research 34(1), 1-12.

 

Woodruff, Robert B. (1997), “Customer Value: The Next Source for Competitive
Advantage,” Journal of the Academy of Marketing Science, 25 (2), 139-153.

Wysocki, Jr., Bernard (1999), “Change Machine: Xerox Recasts Itself as Formidable
Force in Digital Revolution --- Copier Giant Is Battling: A Challenge from Canon

130

for Top of Ofﬁce Market --- Putting Label ‘on Everything’,” Wall Street Journal,
Feb. 2, A1.

Yassine, Ali A. and Donald R Falkenburg (1999), “A Framework for Design Process
Speciﬁcations,” Journal of Engineerig Design, 10 (3), 223-234.

131

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