Annals of Business Administrative Science 5 (2006) 67-98
Available at www.gbrc.jp

Online ISSN 1347-4456 Print ISSN 1347-4464©2006 Global Business Research Center

Reconsidering Novel Technology
Introduction Strategies: Impacts ofTechnology, Design, and Market Attributes on 118
Japanese Product Development Projects

Masanori YASUMOTO
Department of Business Administration, Aoyama Gakuin University
Manufacturing Management Research Center, the University of Tokyo
E-mail: yasumo@busi.aoyama.ac.jp

Abstract: This study reconsiders product development strategies for the introductionof advanced technologies into new products. The exploitation and exploration ofnovel technologies in product development are critical issues for manufacturing firms.
Yet, thus far, the concept and determinants of novel technology introduction
strategies have often been blurred. Drawing on 118 successful Japanese assembly
product development projects, this study attempts to elaborate the concept of novel
technology introduction strategies and explores the effects of other determinants on
the strategies. The study finds two alternative novel technology introduction
strategies: technology integration and separated technology development. The
results demonstrate that successful projects exploit either of these strategies
according to knowledge regarding product designs and/or customer/market needs aswell as technological uncertainty. The findings of this study should help firms contrive
to develop novel technology introduction strategies at the project level, as well as
multiproject strategies at the business level.
Keywords: technology integration, separated technology development, productattributes

Introduction
Cross-functional

collaborative practices across different development
integration

andassociatedstages (e.g., overlapping, preliminary information
67

Yasumotoexchange, and so on) are critical factors for project

Yet, the industrial volatility resulting fromsuccess (Brown & Eisenhardt, 1995; Clark &interfirm modularity and related open interfirm

Fujimoto, 1991). Furthermore, researchers have

networks also draws our attention to another novel

found

relatedtechnology introduction strategy (e.g., Chesbrough,practices to be vehicles of exploratory knowledge

2003; Christensen, Verlinden, & Westerman, 2002).

creation (Benner & Tushman, 2003; Iansiti & Clark,

This strategy exploits basic product design rules and1994; Kusunoki, Nonaka, & Nagata, 1998).

standardized element technologies that are preparedcross-functional

integration

andThe interest in technological changes andby developers who are not involved with specificrelated industrial dynamism highlights the role ofproduct development projects. A typical case is the

cross-functional integration for novel technology

product development based on product modularity,

introduction (e.g., Chesbrough & Kusunoki, 2001;

which is found particularly in digital product

Eisenhardt & Tabrizi, 1995; Henderson & Clark,segments such as software, personal computers,

1990; Iansiti, 1997; Tatikonda & Rosenthal, 2000).

network systems, and so on (e.g., Baldwin & Clark,

Rapid technological changes have dramatically

1999; Cusumano & Yoffie, 1998; MacCormack &shortened product life cycles in hi-tech industries.

Verganti, 2003; MacCormack, Verganti, & Iansiti,

Industrial volatility urges firms to employ novel

2001). In relation to the design concept of “producttechnologies fasterthearchitecture,” these studies suggest that firms may

industrial volatility, cross-functional integration andrefurbish a portion of a product system by adopting

associatedelement technologies from outside the productthan ever.

practicesfor

Reflecting

novel

technology

introduction are regarded as key factors for project

developmentgroup,

therebyfosteringnovel

success in high-tech industries.

technology introduction in volatile industries.

Levels of product development performances,

At the same time, the surge of globalizationsuch as productivity, development speed, andencourages firms to prepare technologies apart fromproduct quality, depend on how firms choose andproduct development in order to quickly release arefine novel technologies so that the technologies

variety of products at a low cost (Tatikonada &work

Stock, 2003). For instance, wireless handset

well

Cross-functional

togetherinnewintegration

teams

products.
for

novel

manufacturers in China make use of the interfirm

technology introduction are reported to contribute tomodularity of “modular production networks”

the performance of product development based on(Sturgeon, 2002) in which specialized suppliers

novel technologies (e.g., Eisenhardt & Tabrizi, 1995;

provideGobeli & Foster, 1985; Gomory, 1989; Iansiti, 1997;

cores/platforms,

Song & Xie, 2000; Tatikonda & Rosenthal, 2000).

software, etc.) to help handset manufacturers release68

elementtechnologies
components,(i.e.,

wirelesshandsetdesigns,

Reconsidering novel technology introduction strategies

a new model every 2-3 months. In the mean time,

Chesbrough, 2003) at the business level. Yet, themajor global wireless handset manufacturers attemptlack of knowledge about the determinants of novel

to adapt to the diversity of the global market bytechnology introduction strategies would hamper

separating

firms from the effective exploitation and exploration

theirproprietary

core

technology

development (i.e., handset platform development)of technologies.

from specific handset model development projects

Drawing on the data from successful product(Funk, 2002).
The

issuesthis study is to explore how firms utilize novel

introduction

technology introduction strategies. Based on a

strategies at the project level. First, whether thecontingency perspective, the article posits thatconcept of novel technology introduction strategies

product development strategies for novel technology

is explicit is still open to doubt. The concept seems

introduction may differ according to product andrather vague as it includes several interrelated

marketproduct development strategies. Second, we may ask

change/novelty.

pertaining

above

development projects of Japanese firms, the aim oftosituationnovel

reveals

technology

two

attributes

as

well

as

technologicalwhat the determinants of each novel technology

While focusing on project level strategies for

introduction strategy are. When novel technologies

novel technology introduction, the attempt of thisare introduced, other factors like design and market

study also contributes to elucidating the impacts of

attributes may influence the choice of the apt novel

critical factors of effective platform/multiprojecttechnology introduction strategies.

strategies on novel technology introduction (e.g.,

These issues confuse the relevance between the

how platform and derivative projects should eachdeterminants of novel technology introduction

play different roles according to the factors). Since

strategies and the technology introduction strategies

the purpose of the article rests in hypothesis

themselves. The choice of novel technology

generating rather than hypothesis testing, the study

introduction strategies is one of the most critical

does not hypothesize any specific causality. All weissues for manufacturing firms (Iansiti, McFarlan, &predict is that product development strategies forWesterman, 2003). At the project level, firms innovel technology integration may differ according toturbulent environments need to make proper use of

product attributes.

novel technology introduction strategies, which arecloselyinterrelatedtoThe outline of the paper is as follows. First, we

platform/multiprojectreview past researches to streamline the concepts ofstrategies (e.g., Krishnan & Gupta, 2001; Robertson

product& Ulrich, 1998; Tatikonda, 1999; Ulrich & Ellison,

determinants, on the basis of which we propose

1999) and related outsourcing strategies (e.g.,generic
69

development

predictions

strategies

based

on

a

and

their

contingency

Yasumotoperspective.

Reflecting

thesepredictions,

we

In

the

1990s,

researchers

collected

theexamine the questionnaire-based data from 118

product/industry-specific data of successful projects

successful Japanese assembly product development

andprojects. Finally, from the results, we attempt tostrategies

draw

Drawing on the data of about 30 super computer or

implications

about

novel

technology

introduction strategies.

exploredforeffective

product

development

introducing

novel

technologies.

workstation development projects of US andJapanese firms, Iansiti (1997) examined productBackgrounds
Product

development projects that were accompanied by coredevelopment

strategies

for

novel

technology development.

technology introduction

The study suggested that the “system-focused”

Since the 1990s, researchers have suggested thatapproach fosters “technology integration” among

effective product development strategies may differ

related functional groups; this is characterized byaccording to product attributes and/or industrial

overlapping

dynamism (e.g., Eisenhardt & Tabrizi, 1995; Song &communication

Montoya-Weiss, 2001; Song & Xie, 2000; Souder,development

Sherman, & Davis-Cooper, 1998; Tatikonda &groups.

Rosenthal, 2000; Yasumoto & Fujimoto, 2005a). The

approach, the system-focused approach results in theline of studies revealed that the mode of novel

development of more radical technologies in atechnology introduction is contingent upon productshortercharacteristics

dynamism.

demonstrated that the technological uncertainty in

Therefore, our next step is to examine how firms

advanced core technology development enhances theemploy product development strategies in relation to

integration for novel technology introduction.

and/orindustrial

novel technology introduction.

effective

product

theassociatedintensive

betweenelementtechnology

product/processengineeringandCompareddevelopment

to

the

lead

“element-focused”

time.

The

study

Also, several generic studies drawing on large
sample data from various industries suggested thatFirst, let us review how researchers havecharacterizedanddevelopment

cross-functional integration is critical for developing

strategies for novel technology introduction. From

new products with novel technologies (e.g., Song &the mid-1980s, drawing on the successful cases ofMontoya-Weiss, 2001; Song & Xie, 2000; Tatikonda

technology-based product development projects,& Rosenthal, 2000). The line of studies suggested

researchers have attempted to explore effective

that

product development strategies for introducing novel

advanced

technologies into new products (e.g., Gobeli &product/process engineering groups are critical for

Foster, 1985; Gomory, 1989).

the70

communication

andtechnology

successful

overlappingdevelopment

commercializationofbetweenandnovel

Reconsidering novel technology introduction strategies

technologies.

processThese

studiesstressed

the

role

of

involves

close

manufacturer-suppliercollaborations as well as cross-functional integration

cross-functional integration for novel technology

withindevelopment and introduction. However, the concept

technology introduction strategies are, at large,ofidentified with cross-functional integration withincross-functional

confusingintegration

technology

often

involves

integration

withmanufacturers.

In

the

analysis,novel

and across firms.

cross-functional integration at the product/process

Product development capabilities that yieldengineering stages (e.g., Eisenhardt & Tabrizi, 1995;

complex/novel, and thus, inimitable products are

Olson,

regarded as sources of competitiveness (Anderson,

Walker,&Ruekert,

1995;

Song

&

Montoya-Weiss, 2001; Song & Xie, 2000; Takeishi,

1999;

Pil

&

Cohen,

2006).

Cross-functional

2002; Tatikonda & Rosenthal, 2000).

integration is highlighted because of its contribution

Eisenhardt and Tabrizi (1995) examined 72

to developing these complex/novel products. The

development projects involving computer products,

interdependency between product elements enhances

such

as

personalcomputers,

supercomputers,

the problem-solving by means of overlapping

peripheralproducts,

andbetween stages, design-test-build cycle iterations,environments,

and the related tight coordination between engineers

cross-functional integration contributes to rapid(Adler, 1995; Clark & Fujimoto, 1991; Iansiti, 1997;

product development. Yet, the distinction between

Terwiesch & Meyer, 2002; Thomke, 1997). Thus,

technology

cross-functionaltight cross-functional integration and associatedintegration at the product/process engineering stages

practices are effective for the product complexity ofstill remains blurred in the study. This problem

automobiles (Clark & Fujimoto, 1991).

workstations,concluded

and

that

under

volatile

integration

andobscures the required range of coordination in novel

Yet, the accumulation of industry/producttechnology introduction.

specific studies shows that novel technology

On the other hand, when examining knowledge

integration is distinguished from cross-functional

partitioning in automobile development projects,

integration at the product/process engineering stages.

Takeishi (2002) found that when an automobile

For instance, Iansiti and Clark (1994) asserted thatproject includes the development of components

technology integration, which deals with highbased on new technologies, the fluidity of thetechnological uncertainty (e.g., super computers), isboundaries of knowledge calls for overlapping

an effective product development strategy for

problem-solving
boundaries(e.g.,

processesevendesign-in

acrossfirm

technology-based complex products. In contrast,

activities).

The

automobile

exchange/sharing of specific knowledge in thedevelopment

calls

for

“internal

integration”—cross-functional integration at the71

Yasumotoproduct/process engineering stages—to deal with theof product performance, without tight organizational

product complexity, and “external integration” tocoordination

deal with the uncertain customer/market needs.

Langlois & Robertson, 1992). Thus, relatively(Garud&Kamaraswamy,

1995;

Both the cross-functional integrations are

successful developers of a more modular product do

vehicles to enhance the coordination between

not call on cross-functional integration at theelements. Nevertheless, it should be noted that

product/process engineering stages; rather, they form

technological uncertainty stemming from drastic

a federation of many small module-specific teams

technological change is the factor that demands

that are relatively independent of each othertechnology integration. This factor requires us to(Cusumano & Yoffie, 1998; MacCormack &distinguish novel technology introduction strategies

Verganti, 2003; MacCormack, Verganti, & Iansiti,

from cross-functional integration, which aims at2001).

improving and/or reusing current technologies, at theThese

product/process engineering stages.

contrastingnovel

technology

introduction strategies indicate that technology
introduction strategies can be divided into two types,

Making proper use of product development“technology integration” and “separated technology

capabilities

development,” on the basis of the level of productOn the contrary, since the 1990s, product modularity

design stability. The difference in novel technology

and related open intefirm networks seem to haveintroduction strategies can be partly attributed to thebeen increasingly eroding the importance ofdesign attributes of the concerned product. Productcross-functional integration and associated practices,complexity, which arises from the insufficiency ofwhich were once regarded as one of the most criticalarchitectural knowledge of the relationships between

factors

productofeffective

product

development

elements,

has

impactsonproduct(Chesbrough, 2003; Christensen, Verlinden, &development projects. The patterns of productWesterman, 2002; Gawer & Cusumano, 2002;

innovations reflect the architectural stability of theSturgeon, 2002). Studies have suggested that

product design (Chesbrough & Kusunoki, 2001;

modular product designs enable manufacturers toHenderson & Clark, 1990).
Novel technology introductions and related

break down complex problem-solving into a set of
localized problem-solving steps (Baldwin & Clark,

product

1999). Modularity permits the rapid introduction of

integration due to the insufficiency of bothnovel elements/technologies into products at acomponent and system knowledge (Iansiti, 1997).

relatively low cost.

Takeishi (2002) further elucidated the integration forThis advantage enables the drastic improvement

designchanges

lead

totechnology

novel technology introductions within and between
72

Reconsidering novel technology introduction strategies

firms,

examiningthemanufacturer-supplieradvancedcomponent/element

technology

relationships in the automobile industry. When novel

development from specific product development

technologies have impacts on the architecturalprojects due to the insufficient knowledge of theknowledge of product design, firms are liable tointerrelationships between components.

coordinate between elements even across firms toEven the decomposability of products into

compensate for the insufficiency of architectural

relatively independent components, such as modules,

knowledge related to the product system and its

iscomponents.

knowledge is provided (Baldwin & Clark, 1999;

Generic studies based on large sample data

notsecureduntil

sufficientarchitectural

Ulrich, 1995). Facing the interdependencies between

from various industries have also demonstrated thecomponents,

firms

cannotdivideproduct

impacts of the architectural stability of productdevelopment tasks into distinctive subtasks (vondesigns. When the concerned products are complex,

Hippel, 1990). Thus, firms cannot introduce novel

technological uncertainty is likely to enhance thetechnologies without technology integration whenneed for cross-functional integration (Tatikonda &decomposability is not secured due to the lack of

Rosenthal, 2000). Compared to the case of

stable product designs.

incremental model change projects, projects forOn the other hand, the separation of technology

novel products, which include design changes, urge

development from the product/process engineeringfirms to adopt the cross-functional integration andstages alleviates heavy task loads in the development

relatedoverlap

elementtechnology

of complex products. Stable designs, such as

product/processengineering

platforms, provide the architectural knowledge(Olson, Walker, & Ruekert, 1995; Song &between product elements, and thus, save the cost

Montoya-Weiss, 2001; Song & Xie, 2000).

and time involved in the integration of thesedevelopment

betweenand

Nevertheless, element technologies can be
developed

so

that

they

are

separated

elements (Baldwin & Clark, 1999; Cusumano &fromNobeoka, 1997; Funk, 2002; Tatikonda, 1999). This

product/process engineering and are introduced into

efficiency increases the organizational flexibility of

products when the architectural attributes of the

product development in response to environmental

product designs are provided or relatively stable.

variety and/or volatility (Krishnan & Gupta, 2001;

Firms need to design their products aligned with

Sanchez & Mahoney, 1996).

novel technology development, unless sufficient

Following the perspectives in terms of novel

architectural knowledge is provided by stable

technology introduction and product designs, we candesigns (e.g., Baldwin & Clark, 1999). Without thestreamline product development strategies (Figure

stability of product designs, firms cannot separate

1).
73

YasumotoFigure 1.

Separated
Yes Technology

Development

Novel
Technology
Introduction
No

Technology
Integration

Patchwork

Engineering
Integration

Hig

Low

Architectural Knowledge of
Product Design (Design Stability)

technologicalFunk, 2002; MacCormack & Verganti, 2003;

providethe

MacCormack, Verganti, & Iansiti, 2001; Ulrich &minimum conditions to adopt either of the novel

Ellison, 1999). In volatile environments, novel

technology introduction strategies. Yet, ultimately,

technology development is separated even from thethe adoption of the strategies would depend upon

product development for existing businesses/markets

market factors.

(Iansiti, McFarlan, & Westerman, 2003).

Product

attributeschange/novelty

and

and

complexity

Organizational flexibility to market variety

Eisenhardt and Tabrizi (1995) elucidated that in
the

field

of

the

and/or volatility would depend upon the architecturaltheattributes of the product designs. Yet, these“experiential approach” contributes to shortening theconflicting suggestions about industrial volatility

development of lead time to a greater extent than in

may result from the insufficient attention to thethe “compression approach” based on planning andeffects of market attributes. The effects of market

overlapping in relatively stable environments. Yet,

uncertainty under the concept of industrial volatility

firms could augment the organizational flexibility toare often entangled with the effects of technologicalthe level of environmental volatility. Firms may alsochange/novelty. Many of the studies conducted seemintroduce advanced

element technologies into

to regard industrial volatility simply as technologicalproducts

modularized

technology

change/novelty and focus on the dynamism of thedevelopment, independent of product development

technologies (e.g., Chesbrough & Kusunoki, 2001;(e.g., Chesbrough, 2003; Cusumano & Yoffie, 1998;

Christensen, 1997).

cross-functional

rapidly

evolving

integration

throughproducts,

relevant

to74

Reconsidering novel technology introduction strategies

With

regardmanagement,

toproduct

Eisenhardt

examines how successful projects adopt novel

examined the impacts of model change cycles as thetechnology introduction strategies according tovariable

product and market attributes.

industrial

Tabrizi

product/process engineering. Second, the study(1995)

ofanddevelopment

volatility,

particularly

highlighting the relationship of the cycles with

Because of the variety of products, modern

technological change/novelty. Nevertheless, at the

manufacturing firms are required to employ novel

same time, the line of studies also stressed thattechnology introduction strategies with regard tomarket variability calls for product development

product

capabilities based on cross-functional integration

dynamism. Examining the contingent application of(Eisenhardt & Martin, 2000). As such, model change

the strategies would help us understand how firms

cycles may reflect both technological change/novelty

can successfully introduce novel technologies intoand market variability, resulting in the impacts ofthe concerned products.

market factors on the choice of novel technology

forindustrial

contingency analysis is relatively simple, actual dataenhancescollection and empirical analysis is not easy, partly

technology integration in coping with technologicalbecause of some difficulties in measuring productuncertainty only when architectural knowledge ischaracteristics,

also simultaneously insufficient. In contrast, firms

performances across various industries. After trying

maydeveloped

various methods, we decided to use subjective

elsewhere so long as the concerned product designs

measures as the main yardsticks, and considered thatare stable. This study sheds light on the impacts ofeach of the respondents would have a broad

market and product attributes, presuming thatperspective in evaluating product development

successful projects make proper use of novel

strategies.

exploitchange/novelty

and/orAlthough the basic logic of the present

introduction strategy remaining blurred.
Technologicalcharacteristics

varioustechnologies

technology introduction strategies according todevelopment

strategies,

andIn this study, we measured the “perceived”

product and market attributes.

characteristics of the product in question and the
product development practices. Levels of productResearch direction and data collection

development performance were also measured in

Basic direction

terms of respondents’ perceptions. This method may

Let us describe the direction of our analysis. First,

have some potential problems with regard to

the study attempts to classify novel technology

measurement and validity. There is a fundamental

introduction strategies by sorting them on the basis

trade-off here between accuracy and comparabilityofcross-functional

integration

during75

Yasumotoof data. 1

selected the variables and designed the questionnaire.

After considering the trade-off, we presumed

We then proceeded to the questionnaire survey.

that objective environments, novel technology

We collected data in July 1997, through aintroduction strategies, and aspects of performancequestionnaire survey mailed to 700 business units

would be aligned in projects that project leaders

and research laboratories of Japanese public firms.

themselves regarded

The survey inquired about product development

as successful. Therefore,

focusing on projects deemed as successful, we also

projects

examined

products.

therelationshipbetweenproductcharacteristics and estimated the success levels ofofcommercialized

mass-production

The unit of analysis was an individual project of

product development strategies.

product development. Some of the surveys were sent
to different business units or institutes within the

Data Collection

same multidivisional company. We asked the

We combined clinical field studies and statisticalpotential respondents to select a relatively successful

data collection. First, from 1995 to 1997, we visitedproject that they had direct experience with in recent

32 development projects involving products fromyears, and to consistently answer the questions about

various industries, such as the apparel, automobile,

this particular project. 2

construction equipment, chemical textile and resin,
consumerelectronics,

communicationelectronic

components,

pharmaceuticals,

industrial

We received 203 completed surveys (response

devices,

rate: 29%) from 145 firms by the end of October

food/beverage,

1997. We checked the nonresponse bias with regard

industrial

to firm size (sales). 3 No significant difference inmachinery, mechanical parts, medical equipment,

firm size between the respondent firms and otheroffice equipment, precision mechanics, software, andpotential respondent firms was found (t = 1.34, p =toiletrythe0.18). The product development of the 203

product/industrial categories we intended to study inrespondent firms was spread across a variety of

our questionnaire survey. Combining our knowledge

products/industries:

from both the literature survey and field research, we

food/beverage, chemical, pharmaceutical and rubber,industry,

covering

chemical,virtuallyalltextileandapparel,consumer chemical and toiletry, metal, electronics,
1

A popular method for understanding effective or
adaptive strategies is the pair approach. This approach
involves asking the respondent firms to name a pair ofprojects, a successful and an unsuccessful one from theirpoint of view, and to evaluate the level of adoption oreffectiveness of each routine. If the level is significantly
different between the pairs for a given routine, we cansay that it is an effective or adaptive routine. In reality,
however, it is rather difficult to get responses about
failed projects from firms.

2Core project members had, on an average, worked at the
respondent firms for 14.21 years. Projects for novel
product categories accounted for 23.98% of the samples.
The mean period after the first model of the productgenre was released was 10.13 years, and the mean
generation period of the product in the product line was
3.14 years.
3
The mean of the sales of the potential respondent firms
was 6.84 billion yen.

76

Reconsidering novel technology introduction strategies

systems and software, precision mechanics, andtransportation

machines.

The

diffusionengineering stages.

of

We presumed that the ratio of engineering hours

respondents by industry was not significantly

to the total product engineering hours for thedifferent from that of potential respondent firms.

product/component

designwould

reflect

thefundamental product complexity of the product inFocusing on assembly product development

question. The fundamental complexity would define

projects

the knowledge level with regard to the productIn our analysis, we chose assembly productstructure. Firms of assembly products at least

development project cases in order to examine ourpossess the knowledge that an assembly product ispredictions using more controlled data settings. We

designed as a set of distinctive components.

attempted to divide the samples into two groups:

Accordingly, assembly product development projects“assembly product” and “process product” groups. 4

are expected to allocate many of the resources toInnovation management studies have suggested that

product/component design and related prototyping

product development capabilities are different

and testing.

between assembly products and process products

On the contrary, in many cases, firms of process(e.g., Kusunoki, Nonaka, &, Nagata 1998; Utterback,products scarcely have sufficient knowledge to1994). Kusunoki et al. asserted that effective productarticulate the structure of a process product into a set

development capabilities are significantly differentofbetween these groups according to the difference indevelopment projects use most of the resources for

assembly/system and process/material development

process design and related prototyping/testing. The

project groups.

difference in knowledge level with regard to thephysicaldesigns.

Thus,

process

product

However, the distinction between assembly andfundamental product complexity could bring aboutprocess products is not as clear as is usually

the critical differences between the assembly andexpected. For instance, products with a small amountprocess product groups with regard to the productof components/ingredients are not always processdevelopment strategies they use.
Reflecting

products and visa versa. We asked the respondents tothisdifference,

wetentatively

provide the ratio of engineering hours to the total

divided the samples on the basis of the ratio of 36%

product

andsince the mean of the ratios was 35.13%. 5 The mean

product/processengineering hours ratio of the assembly productengineering

component

4

design

hours
in

for
the

product

5

See Yasumoto and Fujimoto (2005b) for details of theentire analysis including the process productdevelopment group and other product development
strategies and factors.

77

The ratio of engineering hours for product/component
design to total engineering hours had a significant
positive correlation with the amount of productelements/design drawings (r = .30, p < 0.01).

Yasumotogroup was 43.06% while that of the process productdevelopment projects (e.g., Clark & Fujimoto, 1991;

group was 23.26%. The ratio of the assembly

Iansiti, 1997). Since the unit of analysis in our study

product group seemed to be relatively low. The

was a single product development project, we

reason for this is that many of the resources werecollected the data of six performance variables of theallocated to prototyping and testing even in assembly

product in question: customer satisfaction/total

product development projects.

quality, engineering hours, development lead time,

In order to confirm the differences in statisticalstructure

betweenthese

groups,we

specific functional performance, sales/market share,and profit. 6

appliedBrown-Forsythe’s F-test to the ratio of engineering

Considering the problem of comparability ofhours for product/component design. The standard

performancedeviations of the assembly and process productrespondents to check each of the performance levels

groups were 1.98 and 2.59, respectively. The result

on a 5-point Likert scale (1 = “not successful at all”

evidenced the significant difference in the varianceto 5 = “highly successful”). Objective performance

between the assembly and process product groups (Fmeasures= 12.96, p < 0.0001). The distinction between theinterindustrial studies. Even though we could

assembly and process product groups could also

successfully collect objective performance data, thehave significant implications in terms of statisticalcomparison of data across various industries would

structure.

be almost impossible.

arebetweennotindustries,

deemedweappropriate

asked

for

After the elimination of the samples that

On an average, across all the product types, theincluded defect values, we focused on the 118

performance scores of the sample projects appeared

assembly product group samples for our analysis.

rather high. With regard to all the measures, every

The assembly product group included the following

respondent estimated the selected project as more orindustries/products: computer systems/software (n =less successful. Mean scores of customer satisfaction

12), consumer electronics (n = 23), electronic partsand functional performance and sales/market share(n = 21), industrial machinery (n = 24), mechanicalwere particularly high in the assembly productparts (n = 7), precision mechanics (n = 24), andgroup: 4.41, 4.37, and 4.22, respectively (4.46, 4.40,

transportation machines (n = 7).

and 4.24 across all the industries). This might
indicate that in all the industries, customer

Product development performancesatisfaction/total quality, functional performance,

Much of the literature on product development

and sales/market share are particularly criticalmanagement has considered project performance in
6order to identify the effective attributes of product78

All the performance variables significantly contributed
to sales and profits (p < 0.01).

Reconsidering novel technology introduction strategies

performance measures for successful projects.

terms of similar performance criteria.

In order to verify that the respondents applied
similar success criteria, we collected data on success

Product development strategies

criteria by asking respondents to choose the latter

We questioned the respondents about 19 variables offrom five alternatives (multiple-choice format). The

product development strategies, and conducted a

success criteria that the respondents chose werefactor analysis. The respondents of the questionnaire“compared with those of the products of rivalry

were asked if each of the descriptions (mentioned

firms” (n = 148, 37.19%), “past products” (n = 109,

later)

27.39 %), “past products of the concerned firm” (n =development project in question; they were asked to67, 16.83 %), “success criteria within the concerned

respond by comparing the concerned product tofirm” (n = 71, 17.84 %), and “others” (n = 3, .75 %).

other products in general. Responses were madeThe ratios with regard to the success criteria wereusing a 5-point Likert-scale (1 = “not successful at

not significantly different between the assembly andall” to 5 = “quite successful”).

process

productgroups, 7

fittedacharacteristic

of

the

producttheAfter eliminating 15 cases with defect values,

respondents adopted similar success criteria even

we applied factor analysis (principal components

across multiple industries.

analysis) to 188 samples, selected the factors with an

implyingthat

We also examined the differences in the mean

eigenvalue greater than one (1.00), and following

scores and the variance of each performance

past studies, named the selected factors “types ofmeasure between the assembly and process productdevelopment strategies” (Appendix 2). The measuresgroups (Appendix 1). In spite of the difference

loaded mostly on separate factors, and all the factor

between the groups, we could not identify any

loadings were above 0.40, which is a common

significant differences. This result seemed to suggest

threshold for acceptance. The factor analysis modelthat despite the variety of industries, the subjective

fitted the data reasonably well (χ square = 888.495,

project performance estimation, which indicates how

df = 210, p < 0.001).
From the original factor analysis, we chose theproject managers prioritize performance variables, ofthe project managers, was similar across the sample

results

projects. Thus, it could be concluded that across alltechnology development, function design, productthe industries, respondents would provide data indesign, prototyping and testing, and manufacturing

7

of

11

variables

concerning

element

process design. 8 We identified three factors related
The results were as follows: “compared with products ofrivalry firms” (χ square = 0.01, p = 0.98), “comparedwith past products” (χ square = 0.01, p = 0.92),“compared with past products of the concerned firm” (χsquare = 0.02, p = 0.89), and “compared with successcriteria within the concerned firm” (χ square = 0.61, p =0.44).

to
8

79

novel

technology

introduction

andWe eliminated three factors and variables related toconcept integration, front-loading, and leadership, fromthe original result of the factor analysis on 19 variables.

Yasumotoproduct/process engineering, and used the cases of

element technologies in the early stages.

the assembly product group for our analysis. 9

Project members need to collaborate among

We found that Factor 1 (eigenvalue = 3.96,

technology and product/process development groups

contribution ratio = 0.21, α = 0.82) consisted ofto effectively integrate novel technologies into

variables

theproducts (Iansiti, 1997; Tatikonda & Rosenthal,

product/process engineering stages and overlapping

2000). This is nothing more than “technology

between the product and process engineering stages.

integration” (Iansiti, 1997). For instance, in superTherefore, Factor 1 was named “engineeringcomputer product development, from the early

integration.” The factor included cross-functional

stages,integration

intensive searches and simulations of materials,

such

acrossascommunicationengineeringatsections

andproduct

development

projects

conduct

components, and product designs.

overlapping between product engineering stages andFactor 3, the second factor of novel technology

premanufacturing stages.
Effective overlapping contributes to shortening

introduction into products, was heavily loaded withlead time, thereby increasing the accuracy of thethe variables of separation of element technology

simulation (Clark & Fujimoto, 1991). Whiledevelopment from product/process engineering.

overlapping between related stages is not necessarily

Therefore,

we

accompanied by communication between the stages,

technology

development”

information exchange is critical for effective

contribution ratio = 0.06, α = 0.60). Studies reported

problem-solving in overlapping (Adler, 1995; Clark

that the separation of novel technology development& Fujimoto, 1991; Terwiesch & Meyer, 2002). This

from current product development enables firms to

is nothing more than cross-functional integration at

respond to drastic technological changes while

the product/process engineering stages.

pursuing effective product development based on

Factor 2, the first factor of a novel technology

current

calledtechnologies

thisfactor“separated(eigenvalue(Iansiti,=

McFarlan,

1.18,

&

introduction strategy, was named “technology

Westerman, 2003). Firms may reduce technologicalintegration” (eigenvalue = 1.41, contribution ratio =uncertainty in product development by the separation

0.07, α = 0.71) as it was heavily loaded with fiveof element technology development. Separating

variables related to the search and simulation ofproblem-solving with regard to element technology

9development
All the strategies are significantly correlated with thecollaboration with suppliers (r = 0.24, p < .0.01; r = 0.3,
p < 0.01; r = 0.21, p < 0.05). The collaboration with
suppliers could work with any of the strategies. These
results partly explicate why novel technology
introduction strategies were not distinguished fromcross-functional integration—in terms of supplierinvolvement—at the engineering stages (e.g., Takeishi,
2002).

fromproduct/processengineering

diminishes the search and simulation for technology
integration

undertakentoaccelerate

product

engineering per se in each project (Cusumano &Nobeoka, 1998; Cusumano & Yoffie, 1998; Funk,
80

Reconsidering novel technology introduction strategies

2002; MacCormack, Verganti, & Iansiti, 2001).

characteristics of target markets would depend upon

The relationships of these strategies withthe target customers of the product in question. In

aspects of product development performance further

the development projects for many consumer goods

revealed

distinctions.

such as automobiles, consumer electronic appliances,

Therefore, we examined the correlations between

and so on, customer needs are uncertain and/or

aspects of product development performance andequivocal. For example, while exterior styling, color,strategies (Appendix 3). The analysis demonstrated

aesthetic design, and feelings are critical factors inthatsignificantly

automobile development, these ergonomic features

correlated with all the performance measures, withcan hardly be defined in an articulate manner;the exception of customer satisfaction/total quality (pmoreover, changes in tastes are also difficult to< 0.01 or p < 0.05). At least for the sample Japanesepredict (Clark & Fujimoto, 1991; Iansiti & Clark,

product development projects, most of the aspects of1994).

thenecessity

engineering

productofintegration

development

these

was

performance

could

be

On the contrary, the goal specifications of

attributed to engineering integration.

business/industrial products (e.g., products forTechnology integration was significantly related

businessmen, professionals, SOHO, hospitals) canto several specific aspects of performance such as

be derived from specific functional criteria such as

customer satisfaction/total quality and specificprocessing speed, capacity size, and so on (e.g.,functional performance. Yet, separated technology

Christensen, 1997; Iansiti, 1997). For example,

development did not show a significant correlation

Iansiti described the advancement in a single

with any of the performance measures. These

technological function—processing capacity—as thedifferences supported the fact that these productmajor goal of super computer development. Thus, indevelopment strategies are mutually distinguishable

contrast

also in terms of the aspects of performance.

development projects, developing industrial products

to

the

cases

of

consumerproduct

are focused on relatively instrumental and specified

Analysisfeatures that are sometimes directly provided by theDoes market differences matter?

customers (von Hippel, 1994).

We may presume that the predictability of productHowever, this simple categorization of thedevelopment strategies depends upon the distinction

target market—whether consumer or industrial—has

between consumer and industrial products. 10 The

the risk of obscuring more specific market

10characteristics, 11 which might be perceived by
We asked the respondents to choose the mostapproximate product category—in terms of the target
market—from two categories: consumer products (= 1)or industrial products (= 0). The number of consumer
assembly products was 35 (29.66%), while that of

11

81

industrial assembly products was 83 (70.34%).
The mean number of competing products—10.18—in
the consumer product group was significantly larger

Yasumotoproject members as having direct impacts on productimpacts of technological change/novelty. Yet, thesedevelopment

factors

strategies.

Product

development

arerarelyexaminedseparately

fromstrategies are not adopted according to thecustomer/market volatility (e.g., Christensen, 1997;

dichotomy of markets, which could be fluid

Cusumano & Yoffie, 1998; Dater, 1997; Eisenhardt

according to the attributes of target customers. Even

& Tabrizi, 1995; MacCormack, Verganti, & Iansiti,

consumer/industrial products (e.g., copiers, personal2001).

computers, software, wireless phones, etc.) are often

Further,tailored to industrial/consumer customers.

theintensityoftechnology

development was measured by the quantity of

The fluid boundary between consumer andpreceding patents related to the product (e.g.,industrial products made us infer that perceived

Tatikonda & Rosenthal, 2000). However, themarket uncertainty rather than market dichotomy has

quantity of patents could be largely related to themore direct impacts on product development

complexity of the concerned products; 12 this means

strategies. The dichotomous characterization of thethat in general, products with more distinctive

target markets would blur the factors that have direct

elements could yield more patents. It should also be

impacts on product development strategies. Thus, wenoted that as demonstrated in pharmaceuticalcontrived several perceived measures to explicate

industries, patents do not necessarily account for

product development strategies.

firms’ capabilities (Henderson & Cockburn, 1994).
Thus, following Song and Montoya-Weiss (2001),

Independent variables
We

employedcharacteristics.

three
With

we attempted to measure perceived technologicalmeasuresregardtoofproduct

uncertainty.

technologicalOn the other hand, we measured the level of

uncertainty, we measured “necessity of element

product complexity by using two measures. First, we

technology development” with a 5-point Likert scaleattempted to measure the “quantity of evaluated(1 = “not necessary at all” to 5 = “extremely

product functions,” which was checked in the testnecessary”). Past studies have mainly focused on theprocess of the concerned projects. We asked the
respondents to check the approximate number on athan that in the industrial product group—6.12 (F = 6.46,
p < 0.01). Also, the mean period—21.57 months—of thestandard model change cycle of the consumer productgroup was significantly shorter than that of theindustrial product group—36.3 months (F = 6.82, p< .0.01). These differences indicate that competition is,in general, more intensified in consumer productmarkets than in industrial ones due to the fundamental
unpredictability of customer/market needs. In practice,
the consumer product group was significantly correlatedwith the elusiveness of customer/market needs (r = 0.29,
p < 0.01).

12

82

The quantity of patents were significantly related toboth the necessity of element technology development(r = 0.19, p < 0.05) and technology integration (r = 0.2,
p < 0.05). Yet, the quantity of patents was alsosignificantly correlated with the quantity of evaluatedproduct functions (r = 0.27, p < 0.01), the quantity of
product elements/design drawings (r = 0.22, p < 0.01),
and the number of project members (r = 0.25, p < 0.01).
These results showed that the quantity of patents is
related to quantitative product complexity rather thantechnological uncertainty.

Reconsidering novel technology introduction strategies

5-point logarithm scale (1 = “1,” 2 = “10,” 3 =independent components,” using a 5-point Likert“100,” 4 = “1,000,” 5 = “10,000”). 13 Productscale (1 = “extremely low” to 5 = “extremely high”).

complexity could be captured in terms of the amount

Product design complexity, which could, for instance,ofAn

be characterized by the concept of productautomobile has product complexity largely because

architecture, determines the mode of organizational

an automobile consists of 20,000 to 30,000 parts.

coordination (Sanchez & Mahoney, 1996; Ulrich,product

elements(Anderson,1999).

1995).

Other things being equal, a larger amount ofevaluated product functions will be related to several

Finally, we measured the “elusiveness ofinterdependent elements and are attained as thecustomer/market needs” as the variable of market

results of the synthesis of the interdependent

uncertainty, using a 5-point Likert scale (1 = “notelements. In effect, Kusunoki (1999) considerednecessary at all” to 5 = “extremely necessary”). 14

product complexity in terms of the amount of

The impacts of market volatility are often consideredevaluated product functions, thereby explicating thein terms of the model change cycle (e.g., Eisenhardt

cross-functional integration and related routines in& Tabrizi, 1995; MacCormack, Verganti, & Iansiti,

Japanese semiconductor firms.

2001). When the model change cycle is short, firms

Nevertheless, we predicted a fundamental

can hardly have sufficient knowledge of the

difficulty in measuring product complexity with therequirements

quantity of product elements. The amount of productindustrial volatility does not necessarily cause

elements may be independent of the level ofmarket uncertainty.

interdependencies. Product complexity has been
conceptualized

in

terms

of

the

level

of

customers/markets.

Yet,

such

In volatile markets, faster product releases canofhelp firms obtain a competitive advantage againstinterdependencies between product elements, which

competitors (Dater, 1997). Volatile markets in terms

define the required knowledge, cost, and time forof the model change cycle encourage firms to adopt

realizing a new product (e.g., Baldwin & Clark,cross-functional routines to develop products faster

1999; Garud & Kamaraswamy, 1995; Langlois &than competitors (e.g., Eisenhardt & Martin, 2000;

Robertson, 1992).
14

Thus, we also measured the architectural
attributes of product complexity with the level of“decomposability of the concerned products into

13

The quantity of evaluated product functions had
positive correlations with the quantity of productfunctions required by customers (r = 0.26, p < 0.01) andthe amount of product elements (r = .49, p < 0.01).

83

Model change cycles had a slight negative correlation
with the elusiveness of customer/market needs (r =–0.15, p < 0.10). The mean of the supplier involvementoftheconsumerproductgroup—3.98—was
significantly larger than that of the industrial productgroup, 3.50 (F = 3.19, p < 0.01). On the contrary, themean of the customer involvement of the consumer
product group—3.17—was slightly smaller than that of
the industrial product group, 3.17 (F = 3.19, p < 0.10).
These results indicate that facing more customer/market
needs uncertainty, consumer product development
projects are liable to adopt suppliers’ capabilities.

Yasumoto

Eisenhardt & Tabrizi, 1995). Nevertheless, volatile

projects. After the examination of the correlations

markets may also urge firms to separate element

between independent and context variables, wetechnology

product/process

decided to use three context variables—model

engineering in order to quickly adopt novel elementchange cycle, industrial difference, and producttechnologies for products (e.g., Chesbrough, 2003;

novelty—for our analysis. Project size, 15 which we

Cusumano & Yoffie, 1998; MacCormack andmeasured with the number of core project members,

Verganti, 2003; MacCormack, Verganti, & Iansiti,

was substituted by the product complexity variable:

2001). These conflicting findings may arise because

the quantity of evaluated product functions.

development

frommodel change cycle as a variable of industrial
dynamism

could

reflect

bothmarketFirst, with reference to the past studies

andreviewed in the previous section, we measured thetechnological volatilities.

real duration of the standard “model change cycle”

A shorter model change cycle may not be an(months) within the market of the concerned product.

appropriate variable of market uncertainty since theSecond, we divided the samples into two industry

model change cycle often reflects the velocity of

categories (1 = “electronic” or 0 = “mechanical”)

technological change rather than market uncertainty

according to the industrial categories of the products(YasumotoThe

concerned. The difference between these two

customer/market needs of personal computers areindustries is important since the impacts of productnot necessarily more uncertain than those ofdesign attributes are more emphasized in the case of

automobiles, even though the former’s model change

electronic industries than in the case of mechanicalcycle is much shorter than that of the latter.

ones (e.g., Baldwin & Clark, 1999).

&

Fujimoto,

2005a).

Automobile firms may face more ambiguous

The number of electronic products was 56

customer/market needs even when the model change(47.46%), while that of mechanical products was 62

cycle is long (i.e., several years) (Clark & Fujimoto,(52.54%). Electronic products included computer1991). Thus, we decided to adopt a more direct

systems/software,measure of market uncertainty.

electronic parts. Mechanical products included

consumerelectronics,

andindustrial machinery, mechanical parts, precision
Contexts

mechanics,

In order to examine the contextual differences

variable was used as a dummy variable.

between product types, we measured several context

15

variables related to the concerned products. These
context variables were expected to provide thefundamental conditions of the product development
84

andtransportation

machines.

This

Studies have suggested that the scale of an organizationinfluences the organizational structure. See Clark andFujimoto (1991). The number of project members was
positively correlated with the quantity of evaluatedproduct functions (r = 0.31, p < 0.01) and the amount of
product elements (r = 0.5, p < 0.01). The number ofproject members depends on product complexity.

Reconsidering novel technology introduction strategies

Third, we considered “product novelty” ascycle instead of the elusiveness of customer/market

another context variable. This variable was also usedneeds, which had a slight negative correlation withas a dummy variable. We asked respondents whether

model change cycle (r = –0.15, p < 0.10). In model 3,

or not the concerned product was completely new to

two context variables were added to model 1. In

the preceding product genre within the respondent

model 4, the interaction terms for the three productfirm (1 = “novel” or 0 = “conventional”). The

characteristic variables were added to model 1. In

number of novel products was 27 (22.88%), whilemodel 5, the context variables were added to modelthat of conventional products was 91 (77.12%).

4. In the other potential models, either the R squares

Product novelty could have significant impacts on

or F-values decreased drastically compared to in the

product development strategies (Olson, Walker, &presented models, with the exception of model 2.

Ruekert, 1995; Song & Xie, 2000).

Thus, in order to simplify our examination, we

The question was intended to capture productdecided to consider the four presented models 1, 3, 4,

novelty in terms of the distinction between
conventional

products

followingpast

and 5.

product

The variation inflation factors (VIF) andtechnologies and novel products without any

condition indexes associated with each of thepreceding product technologies. If firms do not haveregression coefficients ranged from 1.03 to 1.08, andpreceding product models/lineups of the concerned

the condition indexes associated with each of the

product, firms can hardly reuse the knowledge,

regression coefficients were below 2.56. The results

namely, the marketing, technologies, design, parts,

suggested no serious problems with multicollinearity

and/or manufacturing process of the precedingin any of our models.

products.

For each of the variables, we paid attention to
the significant effects that were common across the

Resultsmodels. Yet, it is important to note that the main

We considered five multiregression analysis models

effects of the product characteristics remained robustfrom the product characteristics and context

in all the models, even when the interaction terms

variables with regard to the two novel technology

andintroduction strategies. Table 1 shows the results (seeinteraction terms and context variables increased thethe correlation matrix between these variables in

R squares slightly, while reducing the F-values;

Appendix 4).

further, they rarely showed prominent effects oncontext

variables

were

included.

These

Model 1 was the baseline model that included

novel technology introduction strategies. These

only product characteristics as the main factors.

results suggested that each of the factors could

Model 2 examined the effects of the model change

severally explicate novel technology introduction85

Yasumoto

Table 1. Results of multiple regression analysis
Technology Integration
Independent and Context Variables

Model 1

Necessity of Element Technology Development

Separated Technology Development

Model 2Model 3Model 4Model 5Model 1Model 2Model 3Model 4Model 5**0.33 **0.32**0.32**0.36 **0.35

*0.18

✝0.16

*0.20

*0.17

*0.19

0.03

**0.20*0.19*0.18 **0.21*0.19

Decomposability into Independent Components**-0.28 **-0.25 **-0.28 **-0.25 **-0.25

0.00

0.10

0.12

0.10

0.10

Elusiveness of Customer/Market Needs✝-0.15

Quantity of Evaluated Product Functions

-0.01

0.03

0.00

**-0.23

0.10-0.14 ✝-0.16-0.14

Necessity of Element Technology Development*Quantity of Evaluated Product Functions

-0.10

-0.06

0.03

0.01

Necessity of Element Technology Development*Decomposability into Independent Components

0.11

✝0.15

0.05

0.03

Necessity of Element Technology Development*Elusiveness of Customer/Market Needs
Quantity of Evaluated Product
Functions*Decomposability into Independent
Components
Quantity of Evaluated Product Functions*Elusiveness of
Customer/Market Needs

0.09

0.12

0.13

0.11

0.10

0.10

-0.07

-0.05

-0.05

-0.07

-0.05

-0.04

Decomposability into Independent
Components*Elusiveness of Customer/Market Needs

0.00

-0.02

-0.13

-0.11

0.00

Model Change Cycle
Industry Dummy (0 = mechanics, 1 = electronics)
Product Novelty (dummy, 0 = conventional, 1 = novel)

0.20**6.05R square
F

0.17
*5.05

**-0.23 **-0.24 **-0.24

0.06
-0.10
0.13
0.20
**4.58✝-0.16
✝0.15
0.25
0.27
**3.0 **2.96

0.14**5.130.03
0.00**-0.21✝-0.19
0.07
0.16
0.17
0.19
*2.77 **4.74 **2.62 **2.65

notes: n = 118. Standardized values of dependent and independent variables were used for all the models.
† p < .10, * p < .05, ** p < .01

strategies.
The

task loads for element technology development atnecessityofelementtechnology

the product/process engineering stages could be

development and technological uncertainty strongly

alleviatedbyseparating

elementtechnology

explained both technology integration (p < 0.01) anddevelopment from product/process engineering.

separated technology development (p < 0.05). Yet,

On the other hand, the decomposability ofseparated technology development was explicated byproducts into independent components, which would

the quantity of evaluated product functions andindicate product complexity in terms of architectural

quantitative product complexity (p < 0.05 or p <stability, did not show any significant effects on0.01), rather than technological uncertainty.

separated

technology

development,butsignificant

negative

impacts

technology

The result evidenced that element technology

on

had

development

shouldbeseparatedfrom

integration (p < 0.01). The result revealed that

product/processengineering,particularly

whenprojects are liable to adopt technology integration

quantitative product complexity is relatively high.

when architectural knowledge, which provides the

Accordingly, the task loads of product/process

stability

engineering are high as the projects need to cope

independency of each component, is insufficient.

with a variety of element technologies. Thus, theofproduct

designstosecurethe

These results seem to support the finding86

Reconsidering novel technology introduction strategies

concerning product architecture such as modularity

However, technology integration did not show suchand platform management. Yet, we should note thata difference. These results suggested that firms

decomposability

toemploy separated technology development in ordermodularized product development based on ato respond to each of the specific requirements

separated core technology/platform development.

directly designated by customers.

is

not

necessarily

bound

The results did not show any significant effects ofdecomposability

onseparated

Finally, the model change cycle and industry

technology

dummy did not have any effects on either of thedevelopment.

novel technology introduction strategies. These

These results on the decomposability ofindustrial variables per se did not determine theproducts into independent components are in

novel technology introduction strategies. Instead,accordance with those on product novelty. Productmore specific product attributes, namely, productnovelty, which is liable to arise with drastic design

complexity and market uncertainty, are the criticalchanges, had slightly significant positive effects ondeterminants of novel technology introduction

technology introduction (p < 0.10); however, it had

strategies.

significant negative effects on separated technology

Discussion

development (p < 0.01 or p < 0.10).
The elusiveness of customer/market needs had

The concept of cross-functional integration included

significant negative effects on both the strategies (pa broad range of organizational routines for< 0.01 or p < 0.10). The results revealed that firms

information exchange and collaboration between

are not liable to adopt novel technologies unlessfunctionalcustomer/market needs are relatively explicit. In

cross-functional integration has been generalized as

particular, separated technology development was

the bundle of communication and collaboration forelucidated by explicit customer/market needs. The

knowledge

strategy of separated technology development wasorganizational units (e.g., Brown & Eisenhardt,

slightly correlated with customer involvement (r =1995; Clark & Fujimoto, 1991; Eisenhardt & Tabrizi,

0.15, p < 0.10), while technology integration was not.

1995; Iansiti, 1997; Iansiti & Clark, 1994; Kusunoki,

Accordingly,

Nonaka, & Nagata, 1998; Takeishi, 2002).

industrial

product

development

units.

In

processing

many

past

acrossstudies,functional

projects, which entail customer involvement more

To further examine cross-functional integration,

than consumer development projects do (F = 39.21,

the analysis began with the demonstration of the fact

p < 0.001), are more liable to adopt separated

that technology integration is distinguished fromtechnology development as compared to consumer

cross-functional integration at the product/processdevelopment projects (F = 11.24, p < 0.001).

engineering stages (i.e., engineering integration).
87

Yasumoto

Then, we verified that novel technology introduction

necessarily contribute to fundamental

strategies are divided into technology integration andinnovativeness, which results from organizational

separated technology. Following the distinctions

capabilities

between product development strategies, the study

Element technologies such as standardized modules

provided evidence that successful projects choose

in particular, could be transferable between firms

either of the novel technology introduction strategies

and/or imitated by other firms, so that these

according to product characteristics and/or contexts.

technologies would not necessarily secure firms’

The results showed that both the strategies arise

competitiveness (Anderson, 1999; Pil & Cohen,

from the necessity for novel technologies. Yet,

(Henderson&

Cockburn,

product

1994).

2006).

technology integration would be effective in the caseEven if a large portion of a product comprises

where the architectural knowledge of productmodularized/standardized components, a firm thatdesignsthehas the capabilities to manage the interdependencies

decomposability of the products into independent

between the components and integrate them (Brusoni

components. This novel technology introduction& Prencipe, 2001) would be prominent in markets.

strategy is particularly critical in order to realize

In practice, the data showed that technology

drasticisnotsufficienttechnologicalarchitectural

tochanges,changesofsecurewhich

involveintegration contributes to some aspects of productproduct

designs

development(Chesbrough & Kusunoki, 2001; Henderson & Clark,

performance,

particularly

specific

functional performance.

1990; Iansiti, 1997). Technology integration is

Nevertheless, technology integration, which

suitable for industrial volatility in the sense of drastic

encourages firms to design products aligned withtechnological change, though seemingly contributing

novel component development, requires cost andto respond to both market and technologicaltime for each project. Firms can utilize separated

volatility (Eisenhardt & Martin, 2000; Eisenhardt &technology development to reduce the task load of

Tabrizi, 1995).

each development project (Cusumano & Nobeoka,

Cross-functionalnovel

1998; Krishnan & Gupta, 2001; MacCormack &exploratory

Verganti, 2003; Tatikonda, 1999). The results

knowledge creation for the acquisition of novel

suggested that this strategy is particularly calledknowledge, which competitors can hardly imitate orupon for the development of quantitatively complex

acquire (Benner & Tushman, 2003; Iansiti & Clark,

products, which accordingly include a variety of

1994; Kusunoki, Nonaka, & Nagata, 1998). Each ofelement technologies changing at uneven paces.

technology

theelement

integration

introduction

technologies,

enables

such

for

as

patented

Past studies have also suggested that separated

technologies and modularized components, does nottechnology
88

developmentmaycontributetoReconsidering novel technology introduction strategies

shortening product development lead time and would

radicalthus be flexible to industrial volatility (e.g.,

integration can hardly cope with market andCusumano & Yoffie, 1998; MacCormack, Verganti,

technological& Iansiti, 2001; Thomke, 1997). However, rather

technology

than technological uncertainly and model change

technology integration. The attempt to utilize

cycle, this strategy was explicated by the specificity

separated technology development, which is adopted

of customer/market needs, which, above all, arein conventional product development projects rather

directly provided by customers (von Hippel, 1994).

than novel ones, would be indispensable for

These findings allow us to infer that separated

responding to the product design varieties following

technology development could be flexible to a

product designs verified in preceding projects.

variety of specific customer/market needs andtechnologicalchanges,varieties/variations.
development

would

technology

Separatedcomplement

Simply relying on either of the strategies would

technologies, rather than to industrial volatility.

jeopardize firms’ competitiveness in the age of

The impacts of industrial volatility are often

interfirm modularity and related open interfirm

considered in terms of model change cycle (e.g.,

networks (e.g., Chesbrough, 2003; Christensen,

Cusumano & Yoffie, 1998; Eisenhardt & Tabrizi,

Verlinden, & Westerman, 2002; Gawer & Cusumano,

1995; MacCormack, Verganti, & Iansiti, 2001). In

2002; Sturgeon, 2002). Firms need to refurbish core

volatile industries, faster product releases could help

technologies on one hand, and employ element

firms obtain a competitive advantage against

technologies for various customers/markets on thecompetitors (Dater, 1997). Thus, in terms of modelother. Any single novel technology introductionchange cycles, volatile industries encourage firms tostrategy at the project level can hardly cope with

developcompetitors.

“variety” or “volatility.” The role of mediating

Nevertheless, we did not find any significant effects

between conflicting requirements is assigned toof model change cycle on novel technology

contrived product design strategies, for instance,

introduction

conflicting

multiproject/platform strategies that are beyond

strategies, technology introduction and separated

single product development projects (e.g., Cusumano

technology

development,& Nobeoka, 1998; Funk, 2002; Krishnan & Gupta,

appropriatelybyquantitative

product

products

fasterstrategies.

than

Both

are

the

explicatedtechnologicalcomplexity,

more

uncertainty,

2001; Tatikonda, 1999; Ulrich & Ellison, 1999).

product

decomposability, and/or market uncertainty. The

Conclusions

results suggest that industrial volatility per se is not

Preceding studies have particularly focused on theas critical as these factors.

impacts of technological change/novelty on product

While adaptive to industrial volatility with

development, and have emphasized cross-functional
89

Yasumotointegration for novel technology introduction (e.g.,would adopt novel technology introduction strategies

Eisenhardt & Tabrizi, 1995; Iansiti, 1997; Song &according to customer/market attributes.

Xie, 2000; Tatikonda & Rosenthal, 2000). In the line

The results revealed that both novel technology

of studies, the effects of design and market attributes

introduction strategies are adaptive to relatively

were often blurred and confused with those of

explicit customer/market needs. Yet, separated

technological change/novelty. Yet, the results heretechnology development responds to a variety ofindicated that technological change/novelty, productspecificdesign, and customer/market needs, each havecustomers; on the other hand, technology integrationdifferent effects on novel technology introduction

focusesstrategies.

performance. Technology integration is the strategy

The architectural attributes of product design
could

determine

innovations

the

range

(Chesbroughspecific

aspects

providedofbytechnologicalsuitable in the case of strong industrial volatility

technologicalcaused by drastic technological changes. In contrast,
the aim of separated technology development is toHenderson & Clark, 1990). Novel technology

respond to the varieties of specific customer/market

introduction with drastic element technology change

needs and technologies rather than industrial

may erode the decomposability between productvolatility. Separated technology development isdesigns and elements, and would thus enhancenecessary when drastic technological changes

technology integration for problem-solving (Iansiti,

through technology integration are not geared to1997; Takeishi, 2002). Yet, novel technology

existing customers/markets (e.g., Iansiti, MacFarlan,

introduction& Westerman, 2003).

notKusunoki,ondirectly

2001;

does

&

of

requirements

necessarily

resultintechnology integration (Chesbrough, 2003; Iansiti,

Simply relying on technology integration is a

McFarlan, & Westerman, 2003).

ratherrisky

approach,eventhoughfirms’

Firms may separate technology developmentcompetitive advantages rest in their capabilities tofrom each of its specific projects and introduce new

integrate various elements. Refurbishing productelement technologies into a portion of the productdesigns and components for each novel technology

systems (e.g., Chesbrough, 2003; Cusumano &introduction would not be effective, particularly

Yoffie, 1998; MacCormack & Verganti, 2003). The

where open interfirm networks to foster productdifference between the two strategies mostly

development

emerges from design attributes and quantitative

Christensen, Verlinden, and Westerman, 2002;

product complexity and decomposability, which

Sturgeon, 2002). At the business level, beyond theprovidetechnology

project level, firms need to integrate various

introduction modes. Reflecting the difference, firms

technologies, paying sufficient attention to boththeconditions

for

novel

90

are

shaped(Chesbrough,2003;

Reconsidering novel technology introduction strategies

unevenchangesofvariouselements

and(Yasumoto & Fujimoto, 2005b). In spite of theinterdependencies between components (Brusoni &functional novelty and product integrity, the problem

Prencipe, 2001).

ofproduct

development

strategies

ruins

the

In order to make proper use of both novel

competitiveness of Japanese firms in the worldtechnology introduction strategies, firms shouldmarket in terms of cost, speed, and product variety.

devise coherent product development strategies, such

The implications from this study would spell out theas multiproject/platform strategies, at the businessnature of these problems.

level (Cusumano & Nobeoka, 1998; Robertson &In closing, this study may be regarded as an

Ulrich, 1998; Tatikonda, 1999). Without productattempt to bridge the chasm between generic andstrategies to increase the flexibility at the businessindustry-specific studies in the field of productlevel, firms may face the problem of optimization

development

withinattempted

singleprojects,

forexample,tomanagement.

The

present

study

examinepastfindings

fromover-specification and high product cost despite highindustry-specific studies within a generic study

project performance (Clark & Fujimoto, 1991;

context. Hereafter, drawing on the cases of specificCusumano & Nobeoka, 1998; Funk, 2002).

industries, we should further excavate how the

The

case

phone

implications on novel technology introduction

emblematic

strategies are related to product architectures andexample. While rapidly commercializing a variety ofplatform/multiproject strategies. At the same time,advanced technologies in the world, Japanese mobile

we also need to conduct international research as thephone handset manufacturers’ performances are

results in this study may be influenced by themostly not prominent in the world of mobile phone

attributes that are specific to Japan. While we areindustries.

havestill taking initial steps in this research area, this line

commercialized novel technologies focusing on theof study seems to deserve further exploration in

Japanese market without sufficient consideration ofterms of both content and methodology.

manufacturersofJapanesemobilemight

providetheJapanesemanufacturers

product lineup strategies and platform management
for the world market (Funk, 2002).

* The data used in this study was collected by

In effect, in most of the regular handset modelmeans of collaborative research with Professor

development projects, Japanese manufacturers are

Takahiro Fujimoto (the University of Tokyo).

liable to employ technology integration changing thehandset architectural attributes, resulting in them

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Appendices
Appendix 1. Performance differences between assembly and process product groups
Number of
Samples
Assembly means.d.
Process mean
s.d.

118

Profit

4.41

3.75

3.81

4.37

4.22

0.62

0.77

0.86

0.61

0.79

0.74

70

4.53

3.80

3.84

4.47

4.18

3.92

0.50

0.70

0.81

0.53

0.73

0.79

188

1.36
1.06
4.45

0.68
0.45
3.77

0.39
0.15
3.82

1.28
1.51
4.41

-0.98
0.19
4.21

-0.04
0.19
3.91

0.57

0.74

0.83

0.58

0.76

0.76

t
Ｆ
Total means.d.

Customer
Product
Product
Specific
Satisfaction
Sales/Market
Development Development Functional
Share/TotalCost
Lead time
Performance
QualityNote: Double-sided t-test and O'Brien's F-test. † p < .10, * p <.05, ** p <.01

Appendix 2. Factor analysis of product development strategies

Factor 1

Factor 2

Factor 3

mean

s.d.

Engineering
Integration

Technology
Integration

Separated
Technology
Development

Alternative core technologies were compared andanalyzed using prototypes in order to realize theproduct's concept and specifications.

3.56

1.05

0.09

0.73

-0.12

Alternative designs were prototyped and screened
within a spcified search range in order to achieve thetarget product specification and performance.

3.39

0.92

0.11

0.64

0.23

Effective coordination and communication were madebetween advanced element technology development
department and product development department.

3.63

0.97

0.10

0.51

-0.10

Period of core technology development was
overlapped with period of product concept/specification
development.

3.74

0.92

0.17

0.54

0.05

Core technologies were separately developed inadvance of product engineering.

3.66

1.19

0.00

0.46

0.60

The components were developed separetely bycomponent development groups.

3.33

0.96

0.14

-0.11

0.75

Intensive communication was made between members
in element technology development stages.

3.49

0.84

0.11

0.30

0.47

Period of product engineering was overlapped with thatof process engineering.

3.58

0.95

0.54

0.21

0.15

Effective coordination and communication were madewithin product engineering group.

4.01

0.76

0.84

0.03

0.00

Effective coordination and communication were madebetween product engineering department and processengineering/ production technology department.

3.84

0.83

0.76

0.20

-0.04

Intensive communication was made among members
in test/experiment stages.

3.82

0.76

0.65

0.08

0.13

Note: n = 188. Factor loadings were varimax rotated.
The shaded cells indicate values larger than 0.4 or smaller than -0.4.
Eigen Value
Eigen
Value
Product Development Routine Factor 1
Product Development Routine Factor 2
Product Development Routine Factor 3

3.96
1.41
1.18

96

Contribu
tion
Ratio
0.21
0.07
0.06

Cronbachα
0.82
0.71
0.60

3.91

Reconsidering novel technology introduction strategies

Appendix 3. Correlation analysis between development strategies and performances
Separated
Technology
Development

Mean

S.D.

Engineering
Integration

Customer
Satisfaction/Total Quality

4.41

0.62

0.10

0.14✝

-0.05

Product Development
Cost

3.75

0.77

0.17*

0.11

-0.03

Product Development
Lead time

3.81

0.86

0.23**

0.08

0.02

Specific Functional
Performance

4.37

0.61

0.15*

0.16*

0.04

Sales/Market Share

4.22
3.91

0.79
0.74

0.26**
0.17*

-0.03
0.10

-0.03
-0.07

ProfitNote: n = 118

Technology
Integration† p < .10, * p < .05, ** p < .01

Appendix 4. Correlation matrix between multiple regression model variables
Mean

S.D.

1

1 Technology Integration

-0.18

0.94

1.00

2 Separated Technology
Development

0.25

0.87

0.04

1.00

3 Necessity of Element
Technology Development

3.62

1.30

**0.32

*0.19

1.00

4 Quantity of Evaluated
Product Functions

2.88

0.83

0.07

0.10

-0.04

1.00

5 Decomposability into
Independent Components

3.16

1.22

**-0.23

✝0.14

0.10

-0.08

1.00

6 Elusiveness of
Customer/Market Needs

2.54

1.25

-0.09

**-0.23

0.10

0.01

-0.09

1.00

7 Model Change Cycle (MO.)

31.78

28.47

0.04

0.04

0.00

-0.10

-0.07

✝-0.151.00

8 Industry (dummy, 1 =electronics/0 = machinery)

0.53

0.50

-0.09

-0.03

0.02

0.07

-0.09

✝0.13

**-0.49

1.00

9 Product Novelty (dummy, 1= novel/0 = conventional)

0.22

0.42

0.08

-0.11

✝0.15

0.08

0.02

0.02

-0.02

0.09

Note: n = 118

2

3† p < .10, * p < .05, ** p < .01

97

4

5

6

7

8

9

1.00

Yasumoto98

ABAS: Annals of Business Administrative ScienceVol. 5 December 2006

CHIEF EDITOR

Junjiro Shintaku

University of TokyoEDITORIAL BOARD

Makoto Abe
University of Tokyo
Takahiro Fujimoto University of Tokyo
Makoto Kasuya
University of Tokyo
Nobuo Takahashi University of Tokyo
Technical Editor: Maki Nishida, Global Business Research Center

ABAS: Annals of Business Administrative Science is published annually in December by
Global Business Research Center, Hongo, Bunkyo-ku, Tokyo, JAPAN. http://www.gbrc.jp