Sharing Knowledge For Creative Product Development In A Malaysian
Electronics Company
Poh Kiat Ng, Kian Siong Jee, Multimedia
University, Melaka, Malaysia
ABSTRACT:
The purpose of this paper
is to investigate the influence of knowledge management on creative product
development in a Malaysian electronics company. Using a survey-based method, a
total of 226 survey responses were collected back from product development
personnel. These were then analyzed using reliability, linear regression and
multiple linear regression analysis. It was found that combination had the
strongest influence on creative product development. Despite the drawback in
socialization’s influence, it would be still be beneficial for this company to
provide more room for socialization activities to enrich the idea generation
for more creative product development performance. This study stresses on the applied
mechanism of knowledge sharing in an electronics company with an emphasis on
creative product development, which is important for other electronics
companies to identify for a sustainable competitive advantage in the market.
The findings suggest key implications for the practice and research concerning
knowledge management and product development in companies and related
initiatives.
Keywords: Knowledge management,
Malaysia, Sharing, Electronics.
1. Introduction.
As new businesses begin to
grow and advance, knowledge sharing activities are seen to become increasingly
more important in developing strategic partnerships and boundary spanning
activities (Quah, 2001). Companies that face
difficulties in developing policies and organizing resources often turn to
knowledge management practices to sustain their competitive advantage and
innovativeness (Love and Roper, 2009).
Many countries such as Malaysia have made the
move towards becoming a knowledge-based society as their primary national
development goal (Baber, 2001). On the contrary, although many Malaysian companies claim that
they are practicing knowledge management, few were successful mainly due to the
fact that there appears to be no studies on the relationship between knowledge
sharing practices and performance outcomes (Cong and Pandya,
2003).
In addition, literature
search seems to indicate that little if any studies have been conducted on
factors that promote or impede creative product development performance in
companies from developing countries such as Malaysia. It was found that few
studies have been carried out on the systemic effects of industrial practices
such as knowledge management on creative product development performance in
Malaysian companies today. Hence, the main objective of this paper is to
investigate the roles of knowledge management in creative product development
performance with the following developed hypothesis:
Hypothesis 1: Knowledge management
influences creative product development in a Malaysian electronics company.
In this empirical study,
the factors that affect knowledge sharing behaviours among the engineers,
managers and other executives of a Malaysian electronics company will be
analysed and discussed. The roles of all the knowledge management elements will
be linked to creative product development performance by using statistical
analyses methods such as reliability analysis, linear regression and multiple
linear regression.
2. Literature Review
According to Thamhain (2004), successful product development is achieved
through effective knowledge sharing among teams in very complex, uncertain and
equivocal environments. This process requires the combination of knowledge
management skills and the technology for better and productive management of
activities in engineering design phases (Thamhain,
2004).
For this study, the
sub-variables of knowledge management that are further discussed in the next
section include socialization, externalization, combination and
internalization. These knowledge management sub-variables are based on the SECI
model by Nonaka and Takeuchi (1995).
2.1. Socialization
Socialization can be
defined as the act of creating new tacit knowledge by relying on tacit
knowledge sources through social interaction (Vaccaro
et al., 2009). Socialization results in
sympathized knowledge (Shared mental models, technical skills, and shared
experience) and is usually driven through apprenticeship rather than documents
or manuals (Nonaka and Takeuchi, 1995; Choi and Lee, 2002; Salmador and Bueno, 2007).
Through the socialization
process, individuals can acquire tacit knowledge by observation, imitation and
practice (Bolloju et al., 2002). Through
socialization, individuals share experiences to understand one another and
incorporate the others’ feelings and beliefs in discussions (Linderman et al., 2004).
However, tacit knowledge is often a result from
implicit learning, which is context-specific, personal and difficult to
communicate (Mittendorff et al., 2006). Companies
have to carefully transform aspects of tacit knowledge into explicit knowledge to
avoid the loss in production efficiency and innovativeness (Gold et al., 2001).
Nevertheless, excessively controlling socialization to quantify that knowledge
could also limit the creativity in product development. Hence, the following hypothesis is
proposed:
Hypothesis 2: Socialization
influences creative product development in a Malaysian electronics company.
2.2. Externalization
Externalization is defined
as an act of codifying or converting tacit knowledge into explicit knowledge,
characterized by more formal interactions (such as expert interviews) and
activities (such as the documentation of lessons learned from a project) (Hoegl and Schulze, 2005). It occurs in the process of
concept creation and is triggered by dialogue(s) or collective reflection (Choi and Lee, 2002).
The externalization process
aims at diminishing the knowledge dependence among individual organization
members, thus making knowledge independent from individuals (Berends et al., 2007). In new product development, externalization
can make an abstraction tangible enough to be integrated, elucidated and
disseminated as product design knowledge
among design teams (Tseng and Huang, 2008).
Nevertheless,
externalization processes are time consuming and not easily supported by
existing communication technologies, causing them to remain largely based on
face-to-face interactions or in documentation (Vaccaro
et al., 2009). This reflects strongly on a company’s creative product
development performance. Thus, the following hypothesis is proposed:
Hypothesis 3: Externalization
influences creative product development in a Malaysian electronics company.
2.3. Combination
Combination is defined as
an act of creating new explicit knowledge by exchanging, merging, categorizing,
reclassifying and synthesizing existing explicit knowledge held by individuals
in a company (Bolloju et al., 2002; Vaccaro et al., 2009). Combination gives rise to systemic
knowledge that can be used to create prototypes and new technological
components (Nonaka and Takeuchi, 1995).
Combination involves
collecting internal and external explicit knowledge from a company, combining
them into a more structured manner and disseminating them among members of the
company (Hoegl and Schulze, 2005). The formation of the more complex and systematic explicit
knowledge by sorting, categorizing and re-contextualizing of its former form
can be embodied into action and practice (Linderman
et al., 2004; Li et al., 2009).
However, it may not be
certain whether combination leads to efficient new product development or
productivity improvement (Sapienza et al., 2004).
There appears to be limited evidence on the effects of combination on creative
product development performance. Therefore, the following hypothesis is
proposed:
Hypothesis 4: Combination influences
creative product development in a Malaysian electronics company.
2.4. Internalization
Internalization is defined
as an act of converting an organization’s explicit knowledge into individual
and group level tacit knowledge (Vaccaro et al.,
2009). Through internalization, individuals integrate shared explicit knowledge
with their previous knowledge in order to update their mental models and
produce new tacit knowledge (Bolloju et al., 2002).
Internalization occurs
through re-experiencing what was learned, as is often the case in
learning-by-doing (Linderman et al., 2004). Internalization
leads to knowledge creation which can change the practice of understanding and
doing things in a company and promote the actualization of new product
development (Martın-de-Castro et al., 2008; Li
et al., 2009).
However, the unwillingness to internalize knowledge among teams
is a challenge when it becomes more costly and difficult to transfer knowledge
from a company’s headquarters to its subsidiaries (Li and Hsieh, 2009). This
drawback in internalization restricts a company’s creativity in product
development. Hence, the following sub-hypothesis is proposed:
Hypothesis 5: Internalization
influences creative product development in a Malaysian electronics company.
3. Creative Product
Development
Understanding
creative product development in a development team is of paramount importance,
especially in the high technology industries where creativity is a key resource
(Tu, 2009). Creative product development can be broken down into two components
which include creativity and product development performance.
3.1. Creativity
Creativity is defined as a
skill that can generate and translate ideas, talents and vision into a
practical, new and useful external reality (Goel and
Singh, 1998). Creativity is important in product development because the
starting idea is almost never commercialized until after some substantial and
innovative modification or redesign (Stevens et al., 1999).
Ill-informed interventions,
however, may also have a negative impact on team creativity and innovativeness,
and ultimately on the quality and performance of the final product (Bonner et
al., 2002). Also, there are times when paying too much attention to operational
concerns and practicalities at a too early stage of a project can constrain the
conceptual flexibility and creativity of a team (Olson et al., 2001).
3.2. Product Development
Performance
Product development
performance is defined as the level of successfulness in commercializing new
products that involves the entire supply chain (Customers, suppliers,
distributors, engineers and marketing executives) (Iyer
et al., 2006). For a competitive product development performance, knowledge from many
different specialists with extensive education and training is required to
design and produce new products (Schmickl and Kieser, 2008).
However, high failure rates
suggest that the management’s knowledge on the transformation process (Where
ideas are turned into successful new products) is far from perfect,
particularly for more innovative development projects (Bonner et al., 2002). This shows that companies need to effectively
understand and manage risks associated with developing new products since there
is a persistently high probability of new product failure and large financial
loss (Schmidt et al., 2009).
The abovementioned issues show that in order for
companies to survive the dynamic changes in the current market, there is a need
to integrate high levels of creativity in product development to expand a
company’s competency in developing highly complex and novel products. Figure 1
presents the proposed hypothetical research framework of this study.
Figure 1: The Hypothetical
Research Framework
4. Research Method
The selected company for
this study started up in Malacca, Malaysia, at the year 1999. This company has
about 43,000 employees worldwide. Out of that amount, 6000 of them are engaged
in research and development. Besides
Malaysia, this company also functions in Germany, Austria, France,
Taiwan, Singapore and China.
Data provided by this company on projects since
2009 suggests that the company has 3000 projects in total. Due to turnover
rates, transfers and resignations of project leaders, some projects are
discontinued. As a result, 2100 survey forms were handed out to all the product
development managers and engineers in the company.
The unit of analysis was the product development
personnel’s respective projects in the company. A total of 6 weeks was used to
gather the data. Overall, 226 usable surveys responses were collected back,
which produced a response rate of 11%. The data was analyzed using
the SPSS 18, a quantitative application used for multivariate analysis. The
statistical methods utilized were reliability analysis, linear regression and multiple linear regression.
5. Results
Reliability analysis was
used to determine the reliability of the survey items in this study. Table 2
presents the results of the analysis for all four sub-variables of knowledge
management (Socialization, Externalization, Combination and Internalization)
and creative product development.
Table 2: Reliability Analysis For
Knowledge Management And Creative Product Development
|
Variable |
Cronbach’s
alpha, α |
Number
of items |
Sources |
|
Knowledge management |
0.891 |
20 |
(Lee and Choi,
2003) |
|
Socialization |
0.859 |
5 |
|
|
Externalization |
0.869 |
5 |
|
|
Combination |
0.897 |
5 |
|
|
Internalization |
0.883 |
5 |
|
|
Creative product development |
0.766 |
8 |
(Lee and Choi,
2003; Tan and Vonderembse, 2006) |
The reliability analysis
results show that the Cronbach’s alpha for every
single component is adequately above 0.700, which signifies high reliability (Nunnally and Bernstein, 1994; Cronbach
and Shavelson, 2004). These results provide evidence
that the items in the survey instrument used for this study are reliable.
Linear regression analysis
was used to evaluate hypotheses 2, 3, 4 and 5. Table 3 presents the results of
the linear regression analysis to evaluate ‘Hypothesis 2: Socialization influences
creative product development in a Malaysian electronics company.’ An R2 of 0.249 is
reported with this regression analysis, indicating that 24.9% of the variance in creative product development can
be explained by socialization. This relationship is considered to be moderately
correlated due to the correlation coefficient calculated (R=0.499). Socialization establishes an importance towards creative
product development with a reported β
of 0.404. In addition to that, the model is significant as indicated by the
ANOVA results of F (1, 225) = 74.444,
p<0.001. Therefore, the influence
of socialization on creative product development is positive and significant,
and hypothesis 1 is not rejected.
Table 3: Linear Regression For
Socialization – Creative Product Development
|
Predictor |
β |
Std. Error |
t |
F |
R |
R2 |
|
(Constant) |
2.495 |
0.185 |
13.500 |
74.444*** |
0.499 |
0.249 |
|
Socialization |
0.404 |
0.047 |
8.628*** |
(Notes: * p<0.05;
** p<0.01; *** p<0.001; N=226; Durbin Watson = 1.343)
Table 4 presents the
results of the linear regression for ‘Hypothesis 3: Externalization influences
creative product development in a Malaysian electronics company’. An R2 of 0.338 is
reported with this regression analysis, indicating that 33.8% of the variance in creative product development can
be explained by externalization. The strength of the relationship is considered
to be moderately correlated due to the correlation coefficient computed (R=0.582). Externalization establishes an
importance towards creative product development with a reported β of 0.480. Additionally, the model
is significant as indicated by the ANOVA results of F (1, 225) = 77.214, p<0.001.
Therefore, the influence of externalization on creative product development is positive and significant. Hence,
hypothesis 3 is not rejected.
Table 4: Linear Regression For
Externalization – Creative Product Development
|
Predictor |
β |
Std. Error |
t |
F |
R |
R2 |
|
(Constant) |
2.129 |
0.184 |
11.574 |
77.214*** |
0.582 |
0.338 |
|
Externalization |
0.480 |
0.045 |
10.704*** |
(Notes: * p<0.05;
** p<0.01; *** p<0.001; N=226; Durbin Watson = 1.462)
Table 5 displays the
results of the linear regression analysis used to evaluate ‘Hypothesis 4: Combination
influences creative product development in a Malaysian electronics company’. An R2 of 0.419 is
reported with this regression analysis, indicating that 41.9% of the variance in creative product development is
explained by combination. This relationship is considered to be moderate due to
the correlation coefficient (R=0.711).
Combination establishes an importance towards creative product development with
a reported β of 0.471. In
addition to that, the model is significant as indicated by the ANOVA results of
F (1, 225) = 161.306, p<0.001. Therefore, the influence of
combination on creative product development
is positive and significant. Hence, hypothesis 4 is not rejected.
Table 5: Linear Regression For
Combination – Creative Product Development
|
Predictor |
β |
Std. Error |
t |
F |
R |
R2 |
|
(Constant) |
2.193 |
0.152 |
14.441 |
161.306*** |
0.647 |
0.419 |
|
Combination |
0.471 |
0.037 |
12.701*** |
(Notes: * p<0.05;
** p<0.01; *** p<0.001; N=226; Durbin Watson = 1.559)
Table 6 presents the
results of the linear regression analysis used to evaluate ‘Hypothesis 5: Internalization
influences creative product development in a Malaysian electronics company’. An R2 of 0.399 is
reported with this regression analysis, indicating that 39.9% of the variance in creative product development is
explained by combination. This relationship is considered to be moderate due to
the correlation coefficient (R=0.631).
Internalization establishes an importance towards creative product development
with a reported β of 0.512. In
addition, the model is significant as indicated by the ANOVA results of F (1, 225) = 148.548, p<0.001. Therefore, the influence of
internalization on creative product development is positive and significant. Hence, hypothesis 5 is not rejected.
Table 6: Linear Regression For
Internalization – Creative Product Development
|
Predictor |
β |
Std. Error |
t |
F |
R |
R2 |
|
(Constant) |
1.989 |
0.174 |
11.452 |
148.548*** |
0.631 |
0.399 |
|
Internalization |
0.512 |
0.042 |
12.188*** |
(Notes: * p<0.05;
** p<0.01; *** p<0.001; N=226; Durbin Watson = 1.670)
A multiple linear
regression using the stepwise method was conducted to evaluate ‘Hypothesis
1: Knowledge management influences creative product development in a Malaysian
electronics company’. The total amount of independent variables tested
was four (Socialization, Externalization, Combination and Internalization) for
hypothesis 1. Using the formula provided by Tabachnick
and Fidell (2001), the minimum sample size required
would be 50 + (8 × 4) or 82 respondents. As such, the sample size criterion was
met for this study.
Regression formulae are
based on the assumption that residuals are normally distributed around the
predicted dependent variable scores. For this study, normal probability plots
were generated to test this. In the normal probability plots, since the points
were in a reasonably straight diagonal line from bottom left to top right, it
can be confirmed that there were no major deviations from normality (Tabachnick and Fidell, 1996; Pallant, 2005). For the normality test, the measure of
kurtosis and skewness values for the variables tested
were within the prescribed |1.0| range (Tabachnick
and Fidell, 1996).
With the aforementioned
assumptions satisfied, all of the four independent variables were regressed
against creative product development and the results are summarized in Table 7.
Table 7: Multiple Linear Regression
For Knowledge Management – Creative Product Development
|
Predictor |
β |
Std. Error |
t |
F |
R |
R2 |
|
(Constant) |
1.750 |
0.166 |
10.534*** |
104.331*** |
0.695 |
0.483 |
|
Combination |
0.294 |
0.049 |
6.045*** |
|||
|
Internalization |
0.286 |
0.054 |
5.287*** |
(Notes: * p<0.05;
** p<0.01; *** p<0.001; N=226; Durbin Watson = 1.645)
During the stepwise
multiple linear regression, it was found that two out of the four sub-variables
of knowledge management (Socialization and combination) were automatically
excluded from the further analysis. This was due to their insignificance (p>0.05) in terms of relationship with
creative product development. The remaining sub-variables (Combination and
internalization) which were found to be significant (p<0.001) were hence regressed against creative product
development.
An R2 of 0.483 is reported with this
regression analysis, indicating that 48.3%
of the variance in creative product development is explained by both
combination and internalization. The relationship between the variables for
hypothesis 1 is considered to be moderate due to the correlation coefficient
obtained (R=0.695). In addition, the
model is significant as indicated by the ANOVA results of F (4, 221) = 104.331, p<0.001.
Table 7 presents the results of the analysis to assert that knowledge
management makes a significant and unique contribution (with reported
significance levels of less than 0.001) to creative product development. As
such, it can be concluded that knowledge management influences creative product
development, resulting in hypothesis 1 not being rejected.
6. Discussion
From the linear regression
analyses of hypotheses 2, 3, 4 and 5, it is evident that all of the four modes
of knowledge management (Socialization, externalization, combination and
internalization have a positive and significant influence on creative product
development. This finding is consistent with the fact that knowledge management
does indeed help to foster successful product development and generates
significant value to a company through its indefinable advantages (Liebowitz, 1999; Thamhain, 2004).
Also, from the linear
regression analyses, it was found that the relationship between combination and
creative product development is the strongest (R=0.647) among that of the other sub-variables. These findings
indicate that this company practices extensive and systematic documentation of
their standards and processes so that they can be embodied easily into
trainings, workshops and projects (Linderman et al.,
2004; Li et al., 2009).
The socialization aspect
however, appears to be the weakest among the four modes in relation to creative
product development (R=0.499),
probably because this electronics company runs based on highly sequential and
systematic manufacturing processes that are not only long by nature, but also
complex. Thus, the management and staff may not emphasize much on capturing
tacit knowledge to enhance creative product development. Instead, it may appear
to be more important for the company to focus more on existing problems and
backend technologies in their manufacturing processes.
In addition, the relative
predictive importance of internalization towards creative product development
was also found to be the highest (β=0.512),
followed by that of externalization (β=0.480),
combination (β=0.471) and
socialization (β=0.404). This
finding shows that it was also equally important for this firm to internalize
their product development processes apart from combining them. Although it may
not always be easy due to cost and location constraints (Li and Hsieh, 2009),
converting combined and systemic knowledge into operational knowledge is
essential for this firm to ensure that their policies, standards and procedures
are put into practice.
Furthermore, upon using
stepwise multiple linear regression to evaluate hypothesis 1, it was found that
only combination and internalization were significantly correlated with
creative product development. The socialization and externalization
sub-variables were removed from the regression due to their insignificance in
the overall relationship. This finding strengthens the preceding suggestion on
the company’s manufacturing strategy and processes which are geared towards
solving existing problems and developing existing processes.
However, the relationship
between all the sub-variables of knowledge management and creative product
development appear to be only moderately correlated. This finding is consistent
with the contingency theory, which suggests that there is no optimal, near
optimal or uniformly efficient way in managing an organization (Galbraith,
1973). It is plausible that the dominance in complete effectiveness of
knowledge sharing practices in this firm with respect to creative product
development is muddied by other industrial practices such as total quality
management, concurrent engineering or supply chain management.
7. Conclusion
In this study, it was found
that the influence of combination on creative product development was the
strongest in the company among the other sub-variables. This was most likely
due to the company’s efficient systems, documentation processes and standards.
Apart from that, socialization proved to be the weakest influence among the
four modes. However, in order to nurture creativity in product development, it
would be wise for a company to provide more room for socialization activities
to enrich the idea generation among employees. Thus, socialization activities
in fact are not to be taken lightly, much less ignored in product development.
Also, from the overall
multiple linear regression analysis, it was found that socialization and
externalization were excluded due to their insignificance in the relationship.
This may be because externalization activities are time consuming and
socialization activities capture tacit knowledge which is cognitive and
subjective. The company chosen for this study may need to identify various
means such as coffee klatches or brown bag sessions in order to promote
socialization activities that can enrich the shared information among
employees.
Also, since externalization
activities often tend to remain largely in face-to-face interactions, the
company can actually make a compromise by investing in various communication
facilities that cater for face-to-face meetings or social interactions. Access
to various social networks such as Facebook, Rypple or Twitter should also be encouraged to promote a
less structured and non-stressful environment, which in turn leads to
creativity development.
The limitation in this
study is the sampling method employed which limits the generalizing of this
study beyond the context of this firm. Due to time and budgetary constraints,
this study took on a case study approach in which it was only conducted within
a large Malaysian electronics company. As such, the findings of this study
needs to be interpreted within this context. Apart from that, a simultaneous
modelling analysis in this study is not possible because the variables cannot
be simultaneously tested against each other. This limits the possibility of
discovering more relations among the dependent and independent variables.
In addressing the above, it
is suggested as a future method, to conduct the study in as many electronics
companies in Malaysia as possible. This certainly would allow generalizing the
findings and hypotheses put forward in this study. Another suggestion is to
conduct in-depth qualitative studies in each technology cluster or business
unit of this company to further examine its organizational context for more in
depth understanding on the role of knowledge management in creative product
development.
In addition, a structural
equation modelling (SEM) approach using a combination of statistical data and
qualitative causal assumptions can be used in order to test and estimate causal
relationships. AMOS software can be utilized for this analysis. Using this
approach, the variables for this study are capable of being tested
simultaneously instead of the conventional method where they are linearly
tested with only one variable against another.
All in all, this study
provided empirical evidence that knowledge management does indeed influence
creative product development in a Malaysian electronics manufacturing company.
In this study, socialization and externalization factors are found to be often
overlooked in creative product development and deserve serious attention
towards the progress and eventual success of product development projects.
8. Acknowledgements
The researchers would like to thank Professor Dr. Nirwan
Idrus from the Faculty of Engineering and Technology
in Multimedia University Malaysia for his invaluable comments and guidance in
this study.
9. References
Baber, Z. (2001), The
Emerging Triple-Helix of Science-Industry-University in Japan and Singapore,
Bulletin of Science, Technology & Society, 21(5), 401-408.
Berends, H., Vanhaverbeke,
W. and Kirschbaum, R. (2007), Knowledge Management
Challenges in New Business Development: Case Study Observations, Journal of
Engineering and Technology Management, 24(4), 314-328.
Bolloju, N., Khalifa,
M. and Turban, E. (2002), Integrating Knowledge Management into Enterprise
Environments for the Next Generation Decision Support, Decision Support
Systems, 33(2), 163-176.
Bonner, J. M., Ruekert, R. W. and Walker, O. C. (2002), Upper Management
Control of New Product Development Projects and Project Performance, Journal of
Product Innovation Management, 19(3), 233-245.
Choi, B. and Lee, H. (2002), Knowledge
Management Strategy and Its Link to Knowledge Creation Process, Expert Systems
with Applications, 23, 173-187.
Cong, X. and Pandya, K. V. (2003), Km Issues in Public Sector, Journal
of Knowledge Management, 1(2), 25-33.
Cronbach, L. J. and Shavelson,
R. J. (2004), My Current Thoughts on Coefficient Alpha and Successor
Procedures, Educational And Psychological Measurements, 64(3), 391-418.
Galbraith, J. R. (1973),
Designing Complex Organizations, Addison-Wesley, Boston, Massachusetts.
Goel, P. S. and Singh, N. (1998),
Creativity and Innovation in Durable Product Development, Computers &
Industrial Engineering, 35(1-2), 5-8.
Gold, A. H., Malhotra, A. and Segars, A. H.
(2001), Knowledge Management: An Organizational Capabilities Perspective,
Journal of Management Information Systems, 18(1), 185-214.
Hoegl, M. and Schulze, A. (2005), How to
Support Knowledge Creation in New Product Development: An Investigation of
Knowledge Management Methods, European Management Journal, 23(3), 263-273.
Iyer, G. R., LaPlaca,
P. J. and Sharma, A. (2006), Innovation and New Product Introductions in
Emerging Markets: Strategic Recommendations for the Indian Market, Industrial
Marketing Management, 35, 373-382.
Lee, H. and Choi, B. (2003), Knowledge Management Enablers, Processes
and Organizational Performance: An Integrative View and Empirical Examination, Journal
of Management Information Systems, 20(1), 179-228.
Li, C.-Y. and Hsieh, C.-T.
(2009), The Impact of Knowledge Stickiness on Knowledge Transfer
Implementation, Internalization, and Satisfaction for Multinational
Corporations, International Journal of Information Management, 29(6), 425-435.
Li, Y.-H., Huang, J.-W. and
Tsai, M.-T. (2009), Entrepreneurial Orientation and Firm Performance: The Role
of Knowledge Creation Process, Industrial Marketing Management, 38(4), 440–449.
Liebowitz, J. (1999), Key Ingredients to the
Success of an Organization’s Knowledge Management Strategy, Knowledge and
Process Management, 6(1), 37–40.
Linderman, K., Schroeder, R. G., Zaheer, S., Liedtke, C. and Choo, A. S. (2004), Integrating Quality Management
Practices with Knowledge Creation Processes, Journal of Operations Management,
22(6), 589–607.
Love, J. H. and Roper, S.
(2009), Organizing Innovation: Complementarities between Cross-Functional
Teams, Technovation, 29(3), 192-203.
Martın-de-Castro, G., Lopez-Saez, P. and Navas-Lopez, J. E.
(2008), Processes of Knowledge Creation in Knowledge-Intensive Firms: Empirical
Evidence from Boston’s Route 128 and Spain, Technovation,
28(4), 222-230.
Mittendorff, K., Geijsel,
F., Hoeve, A., Laat, M. d.
and Nieuwenhuis, L. (2006), Communities of Practice
as Stimulating Forces for Collective Learning, Journal of Workplace Learning,
18(5), 298-312.
Nonaka, I. and Takeuchi, H. (1995), The
Knowledge-Creating Company: How Japanese Companies Create the Dynamics of
Innovation, Oxford University Press, New York.
Nunnally, J. and Bernstein, I. (1994),
Psychometric Theory, McGraw-Hill Publication, New York.
Olson, E. M., Walker, O.
C., Ruekert, R. W. and Bonner, J. M. (2001), Patterns
of Cooperation During New Product Development among Marketing, Operations and
R&D: Implications for Project Performance, Journal of Product Innovation
Management, 18(4), 258-271.
Pallant, J. (2005), Spss
Survival Manual: A Step by Step Guide to Data Analysis Using Spss Allen & Unwin, NSW.
Quah, D. (2001), The Weightless Economy
in Economic Development, Information Technology, Productivity and Economic
Growth: International Evidence and Implications for Economic Development, M. Pohjola, Oxford University Press, Oxford.
Salmador, M. P. and Bueno,
E. (2007), Knowledge Creation in Strategy-Making: Implications for Theory and
Practice, European Journal of Innovation Management, 10(3), 367-390.
Sapienza, H. J., Parhankangas,
A. and Autio, E. (2004), Knowledge Relatedness and
Post-Spin-Off Growth, Journal of Business Venturing, 19(10), 809–829.
Schmickl, C. and Kieser,
A. (2008), How Much Do Specialists Have to Learn from Each Other When They
Jointly Develop Radical Product Innovations?, Research Policy, 37(3), 473-491.
Schmidt, J. B., Sarangee, K. R. and Montoya, M. M. (2009), Exploring New
Product Development Project Review Practices, Journal of Product Innovation
Management, 26(5), 520-535.
Stevens, G., Burley, J. and
Divine, R. (1999), Creativity + Business Discipline = Higher Profits Faster
from New Product Development, Journal of Product Innovation Management, 16(5),
455-468.
Tabachnick, B. G. and Fidell,
L. S. (1996), Using Multivariate Statistics, HarperCollins College Publishers,
New York.
Tabachnick, B. G. and Fidell,
L. S. (2001), Using Multivariate Statistics Allyn and
Bacon, Boston.
Tan, C. L. and Vonderembse, M. A. (2006), Mediating Effects of
Computer-Aided Design Usage: From Concurrent Engineering to Product Development
Performance, Journal of Operations Management, 24(5), 494-510.
Thamhain, H. J. (2004), Linkages of Project
Environment to Performance: Lessons for Team Leadership, International Journal
of Project Management, 22(7), 533-544.
Tseng, T.-L. B. and Huang,
C.-C. (2008), Design Support Systems: A Case Study of Modular Design of the
Set-Top Box from Design Knowledge Externalization Perspective, Decision Support
Systems, 44(4), 909–924.
Tu, C. (2009), A Multilevel
Investigation of Factors Influencing Creativity in Npd
Teams, Industrial Marketing Management, 38(1), 119-126.
Vaccaro, A., Veloso, F. and Brusoni, S. (2009), The Impact of Virtual Technologies on Knowledge-Based Processes: An Empirical Study, Research Policy, 38(8), 1278–1287.
About the Authors:
Poh Kiat Ng is a Lecturer at the Faculty of Engineering and Technology, Multimedia University, Malaysia. His research interests include quality management, engineering education, ergonomics, biomechanics, manufacturing management, concurrent engineering and knowledge management. E-mail: pkng@mmu.edu.my; Tel: +606-2523044
Kian Siong Jee is both a Lecturer and PhD candidate at the Faculty of Engineering
and Technology, Multimedia University, Malaysia. His research interests are in
the areas of manufacturing technology, manufacturing systems, manufacturing
management, materials engineering, maintenance engineering, green technology,
quality management, engineering education and knowledge management. Email: ksjee@mmu.edu.my;
Tel: +606-2523099.