The Application of Npd Tools in Singapore

7/28/2019 The Application of Npd Tools in Singapore

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IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 53, NO. 4, NOVEMBER 2006 543

The Application of New Product Development Toolsin Industry: The Case of Singapore

Kah-Hin Chai, Member, IEEE, and Yan Xin, Student Member, IEEE

AbstractLiterature suggests that new product development(NPD) is critical for industrial firms to gain a competitive ad-vantage. Intriguingly, the systematic application of NPD tools inindustry, despite the extensive effort that has been invested andthe benefits that can be obtained, remains mostly uncommon.By conducting ten semi-structured interviews with selected aca-demics and industrialists and using a sample of 67 industrialfirms in Singapore for questionnaire survey, this empirical studyinvestigates the diffusion and adoption of NPD tools in industry.It also probes the factors which may affect the application of NPDtools. Our findings reveal that the application of NPD tools is stillunder-exploited in most of the industrial companies in Singapore.Although the application of NPD tools is affected by many factors,

the most significant are management support in the company andthe innovativeness orientation of the company. Surprisingly, wefound that the usefulness of tools has little influence on whether atool is adopted or not.

Index TermsIndustry application, new product development(NPD), tools and techniques.

I. INTRODUCTION

NEW product development (NPD) is critical for long-term

firm performance [1] and has become a major source

of competitive advantage as companies face an increasingly

volatile external environments characterized by shorter productcycle time and ever quickening technological developments

[2]. According to a survey conducted by the Product Devel-

opment and Management Association (PDMA), successful

high technology firms have found that more than 50% of their

current sales came from new products [3]. Due to the high

cost, inherent technical and commercial risks, new product

development (NPD) is perceived as a high-risk activity that is

prone to disappointing success rates [2], [4][7].

Over the last few years, several NPD process models, tools

and techniques purporting to improve the NPD performance

have been developed by academics, consultants and practi-

tioners and implemented by companies [8], such as qualityfunction deployment (QFD), design of experiment (DOE) and

failure mode and effect analysis (FMEA) [3], [9], [10]. Indeed,

tools and techniques play a key role in a company-wide ap-

proach to continuous improvement [9]. There are two aspects of

tools application: adoption and diffusion [11]. Adoption refers

Manuscript received May 1, 2005; revised October 1, 2005 and December 1,2005. Review of this manuscript was arranged by Department Editor J. K. Pinto

The authors are with the Industrial and Systems Engineering Department,National University of Singapore, Singapore 119260, Singapore (e-mail:[email protected]; [email protected]).

Color versions of Figs. 1 and 2 are available online at http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TEM.2006.883708

to a firms decision either to use a tool in the NPD process

or to reject the use of such an instrument. Diffusion refers to

the cumulative number of firms that has adopted NPD tools

or techniques over time, including both within the company

and across different companies. It is indicated that there is a

positive relationship between the application of NPD tools and

the companies performance [10], [11].

Intriguingly, the systematic application of NPD tools in in-

dustry, despite the extensive effort that has been invested and

the long-term benefits that may be achieved, remains mostly

uncommon [9], [12]. Some possible reasons which may ac-

count for the low usage of NPD tools have been revealed in pre-vious studies. However, most of the studies have focused on fac-

tors related to cultural, organizational, and project differences

[11], [13][17]; few have examined in detail the influence of

those factors pertinent to the tool itself such as usefulness and

user-friendliness. The relative importance of these factors on the

application of NPD tools has never been discussed. In addition,

these studies tend to examine only the diffusion of tool applica-

tion [3], [17][19] in industrial countries such as the US, Britain

and Japan, with no prior study in developing or newly developed

economies such as Singapore.

Addressing this gap, this paper investigates the adoption of

NPD tools in Singapore as measured by frequency and thor-oughness of the tools used. Tool related factors that may affect

the application of NPD tools in industry are also explored. The

research questions of this study are: 1) What are the commonly

used NPD tools in industry? 2) How frequently and to what ex-

tent are these tools used? 3) What are the factors that affect the

application of NPD tools in industry? 4) What is the relative im-

portance of these factors?

II. LITERATURE REVIEW

NPD success is closely linked to the activities carried out in

the NPD process, how well they are executed, and the complete-

ness of the process [7], [20]. Griffin [8] notes that the bestcompanies are more likely to use some type of formal NPD

process than the rest. By dividing the NPD process into man-

ageable stages for planning and control, companies can increase

the probability of success and limit unnecessary expenditures

[21]. Although there appear to be many different NPD process

models, most of them consist of activities such as concept gen-

eration, product definition, prototyping, testing, manufacturing

ramp-up and market launch.

A number of tools and techniques have been developed over

the years to improve NPD performance [3], [9], [10]. Many of

these NPD tools have been created to address certain specific

problems and tend to be used in particular stages of the NPD

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544 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 53, NO. 4, NOVEMBER 2006

process [12].However,toolssuchasbrainstormingandQFDmay

serve more than one purpose and can be used in many stages of

NPD [10], [11]. Over the years, studies have been conducted on

the applications of NPD tools like analytical hierarchy process

(AHP) [22], benchmarking [15], brainstorming [10], [23], [24],

conjoint analysis [25][28], DOE [29], FMEA [30], focus group

[12], in-home use test [10], and QFD [3], [16] in industry. Em-pirical research has shown that sometimes users utilize the tools

in a rather flexible manner [10], at times for purposes for which

they were not designed [10]. Some companies even reinvent the

tools to fit their special requirements [19]. While the use of these

tools does notguarantee NPDsuccess,theyhelp to identify prob-

lems more systematically, complementing the companys effort

to improve on the NPD outcome [31].

Although studies have reported a high degree of satisfaction

for the NPD tools used [12], [32], a low level of application has

also been reported [12], [33], especially when compared to the

application in a manufacturing environment [9], [34]. Except for

the relatively high usage rate of brainstorming, benchmarking,

and focus group, the application of most of the other tools, suchas QFD and DOE, was limited [3], [10], [12], [15], [17], [21].

The above discussions led to the question of what factors de-

termine the application of NPD tools. In previous literature, fac-

tors such as differences in culture [14], [17], characteristics of

organizations [11], [13], [15], [16], [35], novelty of projects or

products [17], and even on the usability and utility derived from

the tool itself [12], [19], [36] have been discussed. However,

there is yet a comprehensive study on all the true factors to be

written which determine the application of these tools in indus-

tries.

Numerous studies have been carried out that focus on interna-

tional comparison and show that culture affects the NPD successand, thus, influences the application of NPD tools [14], [18]. For

instance, it has been reported that the Mediterranean culture of

Spain has a tendency to reject change, and this has a negative

impact on the application of NPD tools [37]. In regard to the

characteristics of the organization, it has been found that the

level of interdepartmental communication, the number of stages

in the NPD process, the number of department involved in NPD

process and the companys NPD strategy were all related to the

application of NPD tools [11]. In a recent study, Rigby [15] has

found that top-down management support has a positive impact

on the tools adoption, which confirmed the results of McQuater

et al. [9] and Nijssen and Frambach [11]. Tidd and Bodley [17]

have investigated the influence of project novelty on the adop-

tion of NPD tools and found that a small number of tools ap-

pear to be more effective in high novelty projects. With regard

to the tool related factors, it has been found that complexity of

the tool, such as difficult-to-use, hard-to-learn, and the lack of an

easy-to-use software affect the application of NPD tools nega-

tively [11], [36]. In addition, high monetary cost and inaccurate

forecasting also influence the tool application negatively [12].

In order to enhance the application of NPD tools in industry,

Mahajan and Wind [12] propose that the time needed to imple-

ment a tool has to be reduced and that strong top management

support needs to be present

As NPD has become a critical factor for company compe-tence and since tool application can improve the NPD perfor-

mance, a more comprehensive understanding of the application

of NPD tools is necessary. However, most previous studies tend

to examine only a single aspect of tool application: diffusion.

With the exception of Calantone et al. [22] and Cristiano [38],

very few studies have examined the frequency and thoroughness

of tools adoption in industries. Indeed, most literature on NPD

tools tends to focus on what the tools are for and how to applythem, with little emphasis on the level of application. With re-

gard to factors affecting tool application, previous studies have

tended to focus on environmental factors such as culture, but

few of them examine the effect of industry nature. In addition,

controllable factors, especially factors related to the tools them-

selves, have not been investigated systematically. In particular,

there is no study which investigates the relative importance of

the identified factors in different industries. Thus, there is a need

to identify the more important factors so that the level of tool

application could be improved. As indicated by Cooper [39],

environmental variables do not play a critical role in deciding

NPD success whereas controllable variables have a strong im-

pact. Therefore, this study will focus on controllable factors, i.e.,tool related factors and organization related factors in different

industries.

III. RESEARCH DESIGN

This research adopted a combination of case study and survey

method. The case studies, together with a literature review, were

used to generate hypotheses. These hypotheses were then tested

in a survey. According to Tiwana and Bush [40], this sequen-

tial progression of qualitative to quantitative methods across dif-

ferent phases of a study allows for a much richer and grounded

understanding of the research phenomenon.

IV. CASE STUDY AND QUALITATIVE RESULTS

A. Case Study

We conducted ten semi-structured interviews ranging from

half an hour to one and a half hours to complement the litera-

ture review in order to develop the hypotheses. Unlike previous

studies [19], we included the practitioner as well as the academic

perspectives to highlight any similar or conflicting views. These

helped to provide valuable insights. By adopting a semi-struc-

ture approach, centered on a standard set of questions, intervie-

wees were allowed to express and explain their perceptions as

they choose, while maintaining the focus of the research. The in-

terview questions were sent to all interviewees in advance to en-

sure that interviewees were properly prepared. Table I describes

the list of interviewees and their associated information.

All the interviews were tape-recorded and transcribed to fa-

cilitate an accurate interpretation. The interviews were struc-

tured around the following questions for the practitioners and

academics, respectively.

To Practitioners:

What are the NPD tools commonly used in your company?

What are the benefits and shortcomings of these tools?

What characteristics of NPD tools affect your choice of

use?

What other factors affect your choice of NPD tools?To Academics:



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CHAI AND XIN: APPLICATION OF NEW PRODUCT DEVELOPMENT TOOLS IN INDUSTRY 545

TABLE I

LIST OF INTERVIEWEES

What are your opinions of some of the NPD tools?

What characteristics of NPD tools affect the choice of in-

dustries?

What other factors contribute to the successful implemen-

tation of NPD tools in industry?Transcripts of the interview were sent back to the various in-

terviewees to check the accuracy of the interpretation. Based on

the results of the interviews and previous literature review, we

developed five hypotheses on the possible factors influencing

the application of NPD tools.

B. Qualitative Results

Based on the interviews, the most commonly adopted tool

in the seven companies is benchmarking, which is adopted by

all the companies. Besides its usefulness in NPD process, the

application of benchmarking is likely to be associated with the

flexibility of the tool itself. FMEA and DOE are also adopted bythe majority of the companies interviewed. In contrast, although

QFD is strongly encouraged by some academics, none of the

companies interviewed used the tool. The practitioners who are

aware of QFD found it was tedious and time consuming, even

though they agreed that the use of QFD might bring benefits to

the companies.

From the gathered data, it is not apparent that there are any

significant differences between the perspectives of practitioners

and academics pertinent to the reasons for application of NPD

tools. Instead, the academics agreed that some tools required

more time and commitment to be successfully implemented. It

is likely that many companies do not apply tools which take

more time when product development cycles are getting shorter.However, the interviewed academics believe companies need

more patience in order to enjoy maximum benefits of the tools

in the long run.

V. THEORY AND HYPOTHESIS

Based on the literature review as well as the interviews con-ducted, two categories of factors have been identified. These cat-

egories are: tool related factors and organization related factors.

A. Tool Related Factors

1) Usefulness: The two primary reasons for companies to

use NPD tools are to identify problems and improve the suc-

cess rates of new products [12], [19]. A tool is worth using

on the condition that it provides certain value, tangible or in-

tangible, to the user. According to the Technology Acceptance

Model [41], perceived usefulness is a major factor which influ-

ences the users decision about how and when they will use a

new technology. Micheal et al. [42] suggest that the decisionto adopt a new product is based on the evaluation of the costs

and benefits of the new product. Project improvement and re-

duction in development time are tangible benefits which can be

observed in a relatively short time. In contrast, intangible ben-

efits, such as better understanding of customer needs and im-

provement in communication between cross-functional teams,

are likely to be revealed in the long run. Because most Strategic

Business Units (SBU) take a short-term perspective when eval-

uating a new products success [12], tangible benefits are more

important for companies when deciding whether to use a tool or

not. This finding is in line with Nijssen and Frambach [19], who

indicate that prediction inaccuracies are one of the major short-

comings of the NPD tools like QFD, which can be detected ina short period of time. To most of the interviewees in our study,



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TABLE II

OBSERVATION FROM INTERVIEW AND RELATED LITERATURE

usefulness is a primary consideration among the internal fac-

tors that may influence the application of NPD tools. However,

most of the practitioners are more concerned with the tangible

benefits that can be achieved even though usefulness encom-

passes both tangible and intangible benefits. Altogether, tools

with higher level of usefulness, in particular those which bringmore tangible benefits, will attract more companies to use them.

Thus, our first hypothesis is as follows.

H1: NPD tools which bring higher tangible benefits will

have higher level of application in industry .

2) User-Friendliness: Two fundamental aspects of

user-friendliness are easy-to-use and easy-to-learn. Easy-to-use

is the degree to which users are able to use the tool prop-

erly without much support from consultants or academic

researchers. Easy-to-learn refer to the level of difficulty to

master a tool. If a tool is complicated, hard to learn, difficult

to practice, and does not have any easy-to-use software thatsupports the approach, then most likely it will not be accepted

[36]. It is very difficult to achieve widespread use of any tool

that takes more than a day or two to learn [36]. Since fast

development of new products leads to greater profitability

and competitive advantage [43][45], and one-fourth of the

lifetime profits attributed to a new product could be lost by an

introduction delay of six months [46], time has become thetop priority for many firms [47]. In order to speed up the NPD

process, the efficiency of the tools must be considered because

any delay is costly to firms. A tool which requires a long period

of time to learn is likely to lead to unwillingness to use [36],

especially for projects that demand short cycle time. Therefore,

tools which are easy-to-use and easy-to-learn are more likely

to be adopted. Consistent with the statements above, the results

of our interviews also reveal that time required to use a tool

is a very crucial consideration when determining the choice

of tools in many companies. Thus, we put forward the second

hypothesis.

H2: NPD tools with higher level of user-friendliness willhave a higher level of application in industry.



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B. Organization Related Factors

1) Innovative Orientation of the Company Strategy:

Strategic orientation is a determinant of a competitive sus-

tainability [48]. According to the typology of differentiation

strategy introduced by Porter [49], [50], a company can develop

competitive advantage by producing innovative products. The

stronger the innovative orientation of the company strategy,the more commanding the role NPD plays in overall business

activities [51]. Innovativeness can be defined in terms of the

products newness relative to the firm and the newness relative

to the outside world [51], [52]. From the firms perspective, in-

novative products provide the possibility of defining the market

or technological standards, creating barriers to a competitors

entry [53], thus providing the firm with above-normal economic

returns for a period of time. However, innovative products are

also associated with high risks [54]. The design, manufacturing,

and marketing methods of innovative products are often less

well known for firms [53]. In addition, customer needs are often

not well defined and competitor capabilities are not clearlyestablished [55], leading to higher uncertainty in developing

innovative products. As NPD tools help to identify problems

systematically [31], [34], the uncertainty due to the innovative

products may be decreased by using NPD tools. For instance,

QFD and conjoint analysis can help companies to understand

and translate customer preference and expectation into the

appropriate design requirements in the early stage of NPD,

mitigating the risk and uncertainty related to innovative prod-

ucts. Therefore, the development of innovative products may

lead companies to adopt more NPD tools in order to reduce the

uncertainty and improve NPD performance. Three practitioners

and two academics in our interview also point out that devel-

opment project of entirely new products, often also the mostinnovative for the firmsundertakingsuch project, make more use

of tools than development projects of marginal improvement.

Therefore, we propose that a high innovative orientation of the

company strategy will encourage tool application. In addition,

studies have found that the R&D and innovative level varies

across different industry categories [56][58]. For instance, the

electronic industry in general has a higher emphasis on R&D

and innovation than mechanical industry. In an industry with

higher level of R&D and innovation, the company strategy will

inevitably be more innovative oriented than those industries with

lower level of R&D, and innovation as otherwise such company

is not likely to survive the competition. As such, the applicationof NPD tools in an industry with higher level of R&D and

innovation will be naturally higher than an industry with lower

level of R&D and innovation. Consequently, the effect of the

innovative orientationof the company strategy on the application

of NPD tools in a high R&D and innovation industry will be

less significant than the effect in an industry with low R&D and

innovation level. Thus, we develop the following hypotheses.

H3a: A higher innovative orientation of the company

strategy will lead to a higher level of NPD tools application

in industry.

H3b: This effect will be less significant in an industry with

higher R&D and innovation level than in an industry withlower R&D and innovation level.

2) Management Support: It is now commonly believed that

management support is vital to the success of NPD. In general,

this support may include 1) sufficient resources, in the form of

people, time, and money, for creativity and excellence in NPD

to take place [59][61]; 2) personal involvement in the NPD

program [16], [62], [63]. The importance of management sup-

port for successful innovation and NPD process has been welldocumented in the previous literature [2], [37], [64]. Yap and

Souder [65] have found that early top management involvement

can enhance the NPD success rate. Rigby [15] has indicated that

top-down management support contributes to the successful im-

plementation of NPD tools. For instance, the successful appli-

cation of QFD is highly affected by management support [35].

Indeed, the lack of NPD tools application has been attributed to

the low level of awareness among managers of the existence of

these NPD tools [12] as well as their limited faith in the useful-

ness of these tools [21]. Thus, we propose the following.

H4: A higher level of management support will lead to a

higher level of NPD tools application in industry.

3) Firm Size: The impact offirm size on the adoption of in-

novation and the application of NPD tools has been investigated

in previous research. Kimberley and Evanisko [66] have found

that large firms adopt innovation more quickly than small firms.

Generally, large organizations have more formal NPD process

than small firms. As such, NPD tools may be more commonly

used in larger organizations than in smaller ones. Moreover,

large organizations may need more new products to support

their organization, which will stimulate the application of NPD

tools. In contrast, scarcity of resources is a major disadvantage

for many small firms. The number and variety of specialists that

these firms can afford to employ is limited. Thus, a lack of bothbreadth and depth of expertise may constrain most small firms

to developing products within their narrow areas of competency

[65]. In addition, small firms seldom have sufficient resources

to sustain many failures before developing a successful product.

Their scarce resources must be at least partially deployed on low

risk projects, line extensions and me-too products that protect

their survival. Therefore, small firms have lower needs to use

NPD tools because of the lower rate of NPD, as well as the lower

rate of developing innovative products. On the other hand, the

effect offirm size on R&D level may depend on the nature of in-

dustry. Frenkel et al. [57] and Shefer and Frenkel [67] found in

industries with low R&D and innovation level such as mechan-

ical based industry, there is no significant relationship between

the intensity of R&D activities and the company size. Conse-

quently, the effect of the firm size on the application of NPD

tools will be lower in the industry with low R&D and innova-

tion level. Therefore, we propose the following.

H5a: Firm size has a positive effect on the application of

NPD tools in industry.

H5b: This effect will be less significant in an industry with

lower R&D and innovation level than in an industry with

higher R&D and innovation level.

The five hypotheses developed based on interview and liter-ature are listed in Table II.



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VI. QUESTIONNAIRE SURVEY

A. Implementation of the Questionnaire Survey

A questionnaire survey is conducted to understand the in-

dustrial perspective on the application of NPD tools and to test

our hypotheses. Our survey is conducted among Singapores

manufacturing companies by posted questionnaires. The mainmailing list is that used by Singapore Economic Development

Board (EDB) for their survey of all manufacturing companies

in Singapore. Based on standard industrial classification (SIC)

code 1987, the five targeted categories covered in this study

are: (34) Fabricated Metal Products, (35) Industrial Machinery

and Equipment, (36) Electronic and Other Electrical Equip-

ment, (37) Transportation Equipment, and (38) Instruments

and Related Products. To supplement the above, we added the

same categories of companies from the Singapore 1000 list,

which is a government ranking of the 1000 best performance

companies in Singapore based on their financial results.

One constraint of this research is the lack of a list of com-

panies which are known to carry out NPD in Singapore. For the

purpose of our research, we focused on senior managers in R&D

department or project leaders in NPD project teams. We wanted

to assure that most of our respondents would be familiar with

our topic and the NPD practices in their companies. Our design

of survey was based on Frohlichs [68] technical note so as to

improve the response rate of the survey returns. We mailed each

company a covering letter with university letterhead explaining

the aims and benefits of the research, a copy of the questionnaire

and a postage pre-paid envelope. In the questionnaire, neces-

sary definitions of NPD tools were provided. Two weeks after

the first mailing, a reminder letter was sent to those companies

which had not yet replied. We did not send a second reminderletter since a second reminder letter can not significantly im-

prove the response rate as compared to the first reminder letter

[69]. No tokens were provided to participants for filling this

survey. Instead, we sent a summary of research findings should

the respondent prefers.

The questions were reviewed by four people knowledgeable

on the NPD process and the application of NPD tools for its

content validity. They were a director (industry and operation)

of a research institute with more than 30 years of industry expe-

rience, a research scientist in a company, a senior lecturer ma-

joring in NPD, and a senior visiting fellow at a university with

25 year industry experience. These reviews let to minor changes

in the wordings of the questions for better suitability for com-

panies in Singapore. The construct validity of the questionnaire

was tested by conducting a confirmatory factor analysis. The

results show that all the items are loaded higher (range from

0.575 to 0.875) in the expected factor and lower in the other fac-

tors, which confirm the construct validity of the questionnaire

[70]. The reliability of the questions was tested by computing

the Cronbachs alpha coefficient and was found to range from

0.67 to 0.89 (see Table V), all within the acceptable range [70],

[71].

B. Measures

The unique dependent variable in this study is the applica-tion of NPD tools in industry. Two dimensions of application

are measured, they are adoption and diffusion. Following pre-

vious studies, adoption was measured by frequency [22] and

thoroughness [38], diffusion within an organization was mea-

sured by number of tools adopted per company, and diffusion

among organizations was measured by number/percentage of

companies adopted each NPD tool [72]. Based on previous lit-

erature and our case study, eight tools which have a relativelyhigh awareness rate are included in our questionnaire. The in-

dependent variables in this study are the possible factors which

may affect the application of NPD tools in industry. Except

for firm size, which is measured by natural logarithm of the

full-time employee number [73], [74], all the other factors are

measured by attitudinal statements. Each statement was mea-

sured by a 5-point Likert-type scale ( ,

). With regards to industry, we grouped the

five industry sectors in our list into two categories based on their

technological character [67]. The first group, Industry group I,

is mechanical based which includes fabricated metal products,

industrial machinery and equipment, and transportation equip-

ment. The second group, Industry group II, is electrical basedand commonly seen as more high-tech, includes electronic and

other electric equipment, and instruments and related products.

This group of industries is also perceived to have higher uncer-

tainty and tend to focus on R&D and innovation than the first

group of industries [56][58].

VII. RESULTS AND DISSCUSSION

Out of 1426 companies in the mailing list, 986 were unre-

turned, 317 were returned, 117 were undelivered due to inac-

curate address, 5 companies have closed down, and 1 company

telephoned to decline participation. The overall response rate

wasabout 25%, which is satisfactory for this kind of survey [75],[76]. Among the companies that responded, 248 were not cur-

rently engaged in NPD, another two companies with NPD sent

incomplete replies. The useable data, thus, dropped to 67 com-

panies, which was 5.14% of the companies. This response rate is

slightly lower than the response rate (7.1%) conducted by Wan

et al. [77] on the NPD activities in Singapore. We attribute the

low response rate to the incapability of identifying companies

which were known to have NPD. Another limitation was the in-

accuracy of the list. The database we used was last updated in

2002.

Some of the respondents names or the targeted companies

addresses have changed, while some companies have closeddown. Given these limitations, we believe the response rate is

acceptable. The largest group of respondents is R&D manager

(about 44%, see Table III), and other managers covered about

42% of the responses. Thus, it could be expected that the re-

sponses were familiar with our topic and the NPD practices in

their companies. The company size in the respondents profile

(see Table III) shows that about 73% companies are small and

medium size, with less than 500 full time employees.

In this survey, we found that the average tools applied in each

company (diffusion within company) was about four, which was

higher than the three that was reported by Nijssen and Frambach

[11] in their survey of 125 Dutch companies with a list of thir-

teen NPD tools. For the number of companies that adopted eachtool (diffusion among companies, see Fig. 1), it was found that



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TABLE III

PROFILE OF THE RESPONDENTSJOB TITLE OF RESPONDENTS AND COMPANY SIZE

Fig. 1. Number of company use NPD tool and thoroughness level.

the most commonly used tools were brainstorming (59 compa-

nies or 88% of the respondents), benchmarking (43 companies

or 64%), DOE (55%), and FMEA (55%). All of these four tools

were used by more than half of the companies. In particular,

brainstorming was used by about 90% of the companies. The re-

sults of our survey confirm the findings from previous studies on

the high usage of brainstorming and benchmarking [10], [15],

[21], [24], and on the low usage of QFD [3], [16], [17], [24].Considering thoroughness (see Fig. 1), FMEA was the tool

most thoroughly used among the tools we surveyed, with a mean

of 3.97 and a standard deviation of 0.83 (under 5-point Likert-

type scale, , ). The thoroughness

level of all the tools was centered on 3 and 4.

With regards to frequency of use (see Fig. 2), brainstorming

( ) and benchmarking ( ) were the

most frequently used tools in pre-development stage, conjoint

analysis ( ) and FMEA ( ) were

the two most frequently used tools in development stage, and

in-home use test was the most frequently used tool in post devel-

opment stage, with a mean of 3.95. Our study confirms that most

NPD tools were designed to address certain specific problems atdifferent stages of NPD process [12]. For instance, in-home use

test was the least commonly used tool in pre-development stage,

but the most commonly used tool in post- development stage.

The survey also reveals that the variation of application fre-

quency for these NPD tools is smaller in development stage than

in pre-development and post-development stages. This could be

explained by the nature of the three different stages. At pre-de-

velopment stage, more uncertainty is involved because of the

fuzzy nature [6], [78], [79], therefore, the practice and knowl-edge of which tool to use are less established. Whereas in the

development stage, the objective is more certain [80] and hence

engineers are usually more assured about their tasks and what

tool to use. At the post-development state, although the objec-

tive is clear, a wide range of other tools (especially those re-

lated to production) could be used due to the variety of tasks in-

volved in, such as testing, trial, and launch [81]. This may lead

to lower frequency of NPD tools used at post development. We

also found that among the 29 companies which use QFD, 20 of

them also use FMEA, indicating the existence of QFD/FMEA

interface [30].

The result of the regression analysis performed to test our

hypotheses is shown in Table IV (Refer to the column of Allfirms). Five hypotheses in our model were supported by the



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Fig. 2. Frequency of the application of NPD tools.

TABLE IVREGRESSION RESULTS FOR FACTORS RELATED TO THE APPLICATION OF NPD TOOLS.

survey results. They are: 1) innovative orientation of company

strategy (H3a); 2) less significant effect of innovative orienta-tion of company strategy in industry with higher R&D and in-

novation level; 3) level of management support (H4); 4) the size

of the company (H5a); 5) less significant effect of size in the

industry with lower R&D and innovation level. The impact of

user-friendliness of the tools application (H2) was found to be

negative on the application of NPD tools, instead of the hypoth-

esized positive relationship. With regards to usefulness of the

NPD tool (H1), although the effect is positive, it is not statis-

tically significant. Thus, these two hypotheses were not sup-

ported.

Our hypotheses predicted that the degree of user-friendliness

of NPD tools should positively affect (H2) the application of

NPD tools. However, we found significant negative impact ofthis factor on the tool application. A closer examination of pre-

vious studies reveals similar contradictory prediction of the ef-

fect of user-friendliness on tools application in industries. Formost NPD tools, training and education were required [34]. Mc-

Quater et al. [9] found that poor training negatively impact the

adoption of tools. According to Killander [36], the lack of wide-

spread of tools could be due to the difficulty of learning the

tools. This implies that high level of user-friendliness of the

NPD tools might bring high leveltool application. However, Yap

and Souder [65] found that the use of easy-to-use, off-the-shelf

technologies seldom completely solved problems and would

hinder the commercial success. Similarly, in our study, the re-

sults show that the main reason of not using DOE, FMEA, and

focus group is time consuming and the main reason for not

using QFD is too complex to use, both of which can be re-

lated to user-friendliness. These findings indicate that althoughsome tools (e.g., QFD) have been highly advocated by acade-



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TABLE V

MEASURE OF THE VARIABLES IN THE QUESTIONNAIRE

mies for their usefulness, they are not commonly used due to

the low user-friendliness. In contrast, our survey shows that the

main reasons for not using benchmarking and brainstorming, the

two most commonly used tools in our survey, are little tangible

benefits, which is related to usefulness. As such, the advantage

of high user-friendliness could be reduced by the disadvantage

of low usefulness of these tools. This is particular true for small

and medium firms [65], which constitute 75% of our sample.

The positive impact of usefulness of the NPD tools on the ap-

plication of NPD tools was a prediction in our study (H1). How-

ever, surprising, we observe little significant impact of the tool

usefulness on the tool application in industry. One possibilityis in the presence of macro factors with wider impact such as

company strategy and management support, the usefulness of

tool itself become less a driver for tool application in industry.

By examining the standardized coefficients , we obtain the

relative importance of all the factors on the application of NPD

tools. Among all the factors, management support in the com-

pany and innovative orientation of company strategy are the two

most remarkable ones. Both of them are highly correlated to tool

application in industries.

Comparing the regression results between the two industries

groups (I and II) (see Table IV), we find that management sup-

port and innovative orientation of the company strategy posi-

tively affect the application of NPD tools, while user-friend-liness of the NPD tool negatively affects tools application in

both industry groups, albeit with varying degrees. The inno-

vative orientation of the company strategy is the most signifi-

cant factor which positively affects the tools application in the

mechanical based industry (with and ),

but shows less significant effect in the electrical based industry

(with and ), as predicted by our hypoth-

esis H3b. As indicated by Bauly [82], in Singapore, the NPD

level of the mechanical based industry is lower than the elec-

trical based industry significantly. This could also be confirmed

from our data by using the independent sample t-test, which

shows that the application of NPD tools in the first group is sig-

nificantly (significant level is 0.05, two-tailed) lower than thesecond group. Therefore, when the mechanical based industry

do NPD, it becomes a major activity for them and hence their

innovative orientation is more important than in the electrical

based industry. The other difference is that firm size has no ef-

fect on the tools application in the mechanical based industry,

but significantly positive related to the application of NPD tools

in the electrical based industry, which confirms our hypothesis

H5b. This may because the effect of the firm size on the tools

application may be weakened due to low degree of NPD in the

mechanical based industry.

VIII. CONCLUSION AND IMPLICATION

This research contributes to the understanding on the appli-cation of NPD tools and the factors that may affect the tool ap-



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plication in the context of Singapore. It was found that about

four tools were applied per company. Among the tools we se-

lected, brainstorming is the most commonly used tool in in-

dustry. Benchmarking, DOE, and FMEA are also applied by

more than half of the respondents. The thoroughness level of

all the tools was centered on 3 and 4 (under 5-point Likert-type

scale, , and ), with FMEA as thehighest level ( ). W ith regard to frequency, our find-

ings confirm that most NPD tools were designed to address cer-

tain specific problems at different stages of NPD process. From

the research findings, it is evident that management support, in-

novative orientation of company strategy, and firm size are posi-

tively affecting the application of NPD tools. In particular, man-

agement support is the most critical factor.

There are several implications from the findings. First, the

negative impact of the user-friendliness and the insignificant

impact of usefulness indicated that a balance is required when

designing, improving, and choosing the NPD tools. For spe-

cific tools, such as QFD and FMEA, they may have a higher

level of usefulness but lower level of user-friendliness. For gen-eral tools such as brainstorming and benchmarking, the level

of user-friendliness needs to be high but in turn the usefulness

level will be low. In such a situation, the selection of NPD tools

should be based on the unique requirement of the company in-

volved. This suggests that when designing the tools, researchers

should consider the demand of the end users closely rather than

compromising tool usefulness by over-emphasizing user-friend-

liness in order to reduce training costs for companies. Second,

the findings of this study could also give some insights to in-

dustrial practitioners. Our findings show that management sup-

port is the most influential factor on the application of NPD

tools. This is consistent with studies in the area of innovationadoption where top management is vital [83]. Since the use of

NPD tools will increase NPD success, managers should show

strong commitment to the use of such tools. Third, the signifi-

cant impact of the innovative orientation of company strategy on

the application of NPD tools implies that managers should re-

alize that without an innovative orientation at the organizational

level, advocating the application of NPD tools at a project level

could be futile. Finally, the high unknown rate (38%) of QFD,

a tool well researched and widely recommended by academics,

clearly demonstrates the gap between academic proposition and

industrial reality. It is clear that academics need to increase and

channel more effort in transferring such tools to industry, rather

than developing new tools with little prospect of real use in in-

dustry.

Although this research has generated a new understanding on

the topic through a combination of past literature, case studies,

and questionnaire survey, there are several limitations which

require future research. First, while we have identified the level

and factors affecting the application of NPD tools in industry,

companies themselves still have to choose NPD tool based

on their unique condition (e.g., education level of employees,

access to expert for training, history) it is, thus, useful to see

how these conditions would affect the choice of NPD tools,

as well as when and why companies design their own NPD

tools. Such studies may be in the form of in-depth, longitudinalqualitative case study approach comparing a small group of

companies. Second, one limitation for this is that the number of

toolseightcan be too large. A detailed investigation could

not be conducted on each tool without significantly length-

ening the questionnaire. Therefore, the combination of these

general and specific tools may not describe the level of tool

application quite accurately. Future research could focus on

less number of tools in order to get a better understanding. Oneapproach may involve conducting case studies which track the

application of different NPD tools in one or more companies.

This kind of study could help us to understand the benefit of

each tool more accurately and make better use of different

NPD tools. Third, although industrial difference has been taken

into account in our analysis, the small sample size constraints

the analysis. Further study focusing on specific industry with

large sample size will be meaningful. Fourth, the low response

rate warrants caution when generalizing the findings. Future

studies should ensure a high response rate by considering

telephone or face-to-face structured interviews. Finally, the

data collected for this study used the key informant approach

[84], [85], at such all conclusions should be interpreted withthis possible bias in mind. Two significant drawbacks of the

key informant approach are: 1) Information bias due to the

differences related to the informants varying organizational

roles [86], individuals memory failure or inaccurate recalling

of past events [87], which may lead to un- comprehensive

understanding of the events in the company; 2) Random error

results from hindsight bias, attributional bias, subconscious

attempts to maintain self-esteem, or impression management

[88], [89], which may result in less correspondence between

informant reports and actual events. Therefore, future studies

should consider multiple respondents from different seniority

and functional background.

ACKNOWLEDGMENT

The authors would like to thank J. Bauly, C. M. Yap, and E.

Thia for their advice and assistance, and both the department

editor and the anonymous reviewers for their helpful comments

and suggestions on earlier drafts of this paper.

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Kah-Hin Chai (M02) received the Ph.D. degreein the area of manufacturing management from theCambridge University, Cambridge, U.K., in 2000.He received the Masters. degree in manufacturing

management from the University of South Australia,Mawson Lakes, Australia, in 1996, and the Bachelordegree in electrical engineering from University ofTechnology Malaysia, Selangor, Malaysia, in 1992.

He is an AssistantProfessor with the Industrial andSystems Engineering Department, National Univer-sity of Singapore (NUS), Singapore. His work expe-

rience includes management consulting and semiconductor manufacturing inSingapore and Malaysia. His current research interests are new product de-

velopment, service innovation, and knowledge management. He has publishedin IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, the Journal of Ser-

vice Research, Creativity and Innovation Management, and the InternationalJournal of Technology Management.

Yan Xin (S05) received the Master degree in engi-neering in the area of engineering management fromthe National University of Singapore (NUS), Singa-pore, in 2005 and the Bachelor degree in engineeringfrom Xian Jiao Tong University, Xian, China, in1998. She is working towards the Ph.D. degree in In-dustrial and Systems Engineering Department, NUS.

Before joining NUS, she worked at supply chainmanagement in China. Her current research areas are

service development and innovation.

The Application of Npd Tools in Singapore

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