The Impact Of Intellectual Capital On Business
Performance In Taiwanese Design Industry
Cheng-Ping Shih, Wen-Chih Chen,
Melton Morrison, National Taiwan
Normal University , Taiwan
ABSTRACT:
Transforming into a knowledge-based economy, there is an increasing need for
Keywords: Intellectual capital,
Structural capital, Relational capital, Business performance,
1. Introduction
In the era of knowledge economy, the intangible assets of a company have most likely taken the place of tangible assets and have probably become the most important resources that create value for enterprises nowadays. “Intellectual capital”, namely the knowledge assets, has become one of the most-discussed business management topics, and it determines success or failure of modern enterprises (Thomas, 2003). Many researchers regard intellectual capital as assets that generate a company’s competitive advantage and value (Bontis, 1999, 2001, Edvinsson & Malone, 1997; Roos & Roos, 1997; Stewart, 1997).
It could possibly be so for design industries as well, as its intangible assets are far more important than its tangible assets. This year Taiwan has so far obtained at least 165 international design awards, which is an improvement from the 133 awards in 2007, and 148 in 2006 (Yang, 2008). This is the evidence that Taiwanese design industry has the potential to contribute to the nation’s economy. It was the first time for design industry to be officially considered in “Challenge 2008 – National Development Plan”, in which design industry development is included as a sub-plan. Also, Taiwan Design Center (TDC), a national design center, was founded to foster the development of Taiwanese design industry.
Theoretically, many researchers have emphasized the influence of intellectual capital on business performance; and empirical studies are still developing. Moreover, even though some researchers has contributed to intellectual capital studies in the scope of Taiwanese high-tech and financial industry (Wang & Chang, 2005; Chen et al, 2006; Lin & Huang, 2006; Huang & Liu, 2006; Tsan & Chang, 2006), none of them have conducted empirical researches in design-related industries.
As a result, the researcher is interested in investigating the impact of intellectual capital on the performance of Taiwanese design industries. The paper thus examines the interrelationships among intellectual capital components and their influence on business performance respectively. Also, recommendations are provided to assist design company managers in managing the intellectual capital of their company.
Having the intentions to enrich
The design industry in
2. Literature Review
The concept of “intellectual capital” (IC) was first proposed by
an economic scholar named John Kenneth Galbraith (Edvinsson & Sullivan,
1996, p. 358; Edvinsson, 1998, p.279; Roos et al, 1998, p. 4). He used it to
explain the difference between a company’s market value and book value
and further advocated IC an intellectual action, instead of mere knowledge and
intelligence (
Edvinsson and Sullivan (1996) define IC as the knowledge assets that can be converted into value. Whereas Stewart (1997) argues IC is the sum of all the knowledge and abilities of the members that forms the company’s competitive advantage, including intellectual material like knowledge, information, intellectual property and experience that makes profit. Still yet, Ulrich (1998) considers intellectual capital originates from employees’ competence and commitment. Among the many studies, the definition of IC remains inconsistent. However, the common features of IC can still be seen: its intangibility, the fact that it creates value, and the growth effect of collective practice (Cabrita, & Bontis, 2008).
3. Intellectual Capital
Components
The previous section describes how the definition and the classification vary due to research directions and the background of the researchers. However, as Cabrita and Bontis (2008) have pointed out, a common taxonomy has emerged in which intellectual capital adopts a tripartite dimension which includes: human capital, structural capital and relational capital.
This paper therefore adopts the classification of Cabrita and Bontis’ (2008) study and defines these three major components of IC:
Ø human capital represents the individual knowledge stock of an organization as represented by its employees (Bontis et al., 2002);
Ø structural capital is a valuable strategic asset, which is comprised of non-human assets such as information systems, routines, procedures and databases;
Ø relational capital is the knowledge embedded in relationships with customers, suppliers, industry associations or any other stakeholder that influence the organization’s life.
4. Measurement Indicators Of
Intellectual Capital And Business Performance
Indicators used to measure IC varies from scholar to scholar, but many of
the indicators falls into the three major categories [human capital (HC),
structural capital (SC) and relational capital (RC)]. Additionally, Bontis has developed a
comprehensive Intellectual Capital Questionnaire in 2007, which was
administered in
5. Intellectual Capital
Studies
Previous studies (Bontis, 1998; Bontis et al., 2000; Cabrita & Bontis,
2008) identified the positive relationship between IC and business performance.
These are three empirical studies conducted respectively in
6. Taiwanese Design Industry
6.1. Background Of Taiwanese
Design Industry
According to the statement of “Challenge
2008 – National Development Plan” proposed by the CEPD (2005), Executive
Within the cultural and creative industry, the design industry shows great
potential to contribute to the nation’s economy. According to the latest
statistics (2003-2006 Taiwan Cultural and Creative Industry Relevant
Statistics, n. d.), the sales growth of the design industry contributed 55.69
billion NTD to the economy in 2006, which accounted for 9.5% of the entire
cultural and creative industry. It also ranked the second highest sales growth
among all
6.2. Characteristics
Of Design Industry
According to Oakley (1990), design projects are usually more irrational, unpredictable, and changing. Also, it requires much creativity from individuals. Design companies are usually more like organic organizations; this idea was proposed by Burns and Stalker (1961), which is suitable for companies situated in an unpredictable and changing environment. This kind of organizational structure provides the company with more flexibility and adaptability, and encourages creativity and innovation. On the other hand, it requires higher cost and more complicated administration to maintain the structure, which could be an obstacle to business performance.
6.3. Definition
And Scope Of Taiwanese Design Industry
Based on Taiwan Ministry of Economic Affairs[MOEA]
(2004) definition, the design industry refers to business that are involved in
product design and planning, product exterior design, mechanism design,
prototype and model production, fashion design, patent logo design, brand
visual design, graphic design, packaging design, webpage/multimedia design, and
design consultancy. Additionally, TDC represents the key organizations of
Taiwanese design industry, however, this research decided to take the companies
in the TDC sector catalog as research samples. In the classification of TDC,
the design industry falls into the following four categories: product design,
service design, activity design, and space design. TDC included space design as
its business scope, which is the slight difference from MOEA’s
definition.
6.4. Development Of Hypothesis
This research framework was developed in accordance with the
literature review. From the review, it was noticed that intellectual capital is
related to business performance. The Intellectual Capital Variables defined in
the study are in relation to Cabrita and Bontis’ (2008) classification of
intellectual capital: Human Capital, Structural Capital, and Relational
Capital. Their interrelation and their impact on Business Performance will be
tested.
Figure
1: Conceptual Framework Of This Study (Source: Revised From Cabrita And Bontis,
2008)
Previous studies have indicated that human capital is positively associated with structural capital and relational capital (Bontis, 1998; Bontis et al., 2000; Chen, 2001; Cabrita & Bontis, 2008); also, structural and relational capital respectively mediate the impact of human capital on business performance. Therefore, the following hypotheses are developed.
H1. Human capital is positively associated with structural capital.
H2. Human capital is positively associated with relational capital.
H3. Structural capital is positively associated with relational capital.
H4. Structural capital is positively associated with business performance.
H5. Relational capital is positively associated with business performance
6.5. Methods
A pilot test, reviewed by four
experts in this field, was administered in December 2008 and the data were
collected by paper questionnaire. For the pilot test sample, four executives of
Taiwanese design companies and six students from the extended education
division of Department of Fine Arts,
For the main study, the researcher contacted Taiwan Design Center (TDC) requesting permission to mail surveys electronically using their design industry catalog. The researcher explained by telephone and mails the research background, the research purpose, along with a note of confidentiality detailing that the data collected will be used solely for the researcher’s thesis and all names of companies will be excluded. Additionally, the researcher made phone calls by using the public catalog provided by the website of TDC (http://www.boco.com.tw). For every phone call, the researcher explained the purpose of the study and the contributions it may have to Taiwanese design industry. The participants were assured their anonymity and that the results will be sent to them if requested. Moreover, the researcher also reminded that the survey should be answered by managers or directors of the company as recommended by Bontis (1998) and Bukh et al (1999). Electric surveys are mailed to these respondents so as to reduce the trouble of replying to paper questionnaires and increase respondents’ willingness of reply.
After all the phone calls are made, the researcher waited and collected all the data. The data was coded and the information was keyed into the Statistical Package for Social Sciences (SPSS) PC 12.0 statistical software program.
6.5. Partial
Least Squares
Partial least squares (PLS) is a kind of structural equation modeling (SEM) technique. It is based on regression and originates from path analysis. As stated by Cabrita and Bontis (2008), it is a powerful tool in social and behavioral sciences where theories are formulated in terms of hypothetical construct, which are theoretical and cannot be observed or measured directly. Besides, PLS estimation does not require assumptions of normality or independence of observations. Moreover, it works well with small samples and is better suited for exploratory work. These are also the reasons that make PLS a more suitable analyzing method for this study.
Therefore, in this study, PLS is used to analyze intellectual capital data and business performance data. Through the use of PLS, the researcher can conduct confirmatory factor analysis and path analysis.
Due to the exploratory feature and small samples of this study, the researcher decided to adopt Visual PLS 1.04b1 as one of the major tools to investigate causal relationship between intellectual capital and business performance.
Finally, the “rule of thumb” for sample size requirements suggests that it will be equal to the larger of the following (Cabrita & Bontis, 2008):
i. 10 times the scale with the largest number of formative indicators (scales with reflective indicators can be ignored) or
ii. 10 times the largest number of antecedent constructs leading to an endogenous construct. In our study we applied the second requirement as all indicators are reflective. The final full test with interaction effects would have 3 constructs.
Therefore, a minimum of 30 (3 x 10) was required. Our sample size (87 samples) met the criterion.
6.6. Testing The Measurement Model
This
paper uses Cronbach’s alpha in SPSS and PLS approach to assess the
measurement model (outer model). All the Cronbach’s alpha values of the
four constructs exceeded 0.91 (0.942 for human capital; 0.914 for relational capital;
0.935 for relational capital; 0.958 for business performance).
Table 1 Measurement model results Constructs Number of items Cronbach’s Alpha Internal Consistency R² (%) Human 16 0.939 0.949 Structural 12 0.913 0.928 75.6 Relational 16 0.935 0.944 70.1 Performance 10 0.957 0.963 35.5 Loadings Human H1(0.7154), H3(0.7140), H4(0.7156), H6(0.7337), H7(0.6656), H8(0.8157), H9(0.6781), H10(0.8392), H11(0.8938), H12(0.7325), H15R(0.5482), H16(0.7487), H17(0.6493), H18(0.81829), H19R(0.5858), H20(0.8174) Structural S3(0.7704), S4 (0.6929), S5(0.6055), S7(0.7977), S8(0.8164), S9(0.7870), S10(0.6038), S11(0.6163), S12(0.6859), S13R(0.6079), S14(0.7800), S15(0.8314) Relational R1(0.8287), R2(0.6128), R3(0.7605), R5(0.6934), R6(0.7561), R7(0.8230), R8(0.7700), R9(0.4857), R10(0.6177), R11(0.7514), R12(0.7718), R13R(0.6554), R14(0.7605), R15R(0.6964), R16(0.8873), R24(0.5222) Performance P1(0.7531), P2(0.8353), P3 (0.8057), P4(0.9025), P5(0.8617), P6(0.8203), P7(0.8562), P8(0.9120), P9(0.8497), P10(0.9000) Source: This paper
Individual item reliabilities were evaluated by examining the loadings
of the measures with their corresponding construct. All loadings were greater
than 0.522 except the loading of R9, which is 0.4857; however, it is not too
low to be deleted (see Table 7). Convergent validity was assessed using the
internal consistency measure, developed by Fornell and Larcker (1981). All
values for the four constructs exceeded 0.7, as recommended by Nunnally (1978).
6.7. Reliability And Validity: Cronbach’s Alpha And Individual Item
Reliabilities
The
reliability of the final test is inspected using Cronbach’s alpha. The
reliabilities for each of the four constructs were greater than 0.86, which
exceeds the criterion of 0.7, considered good for exploratory research
(Nunnally, 1978). Then, PLS is used to assess individual item reliabilities in
the purpose of confirming factor findings. At early stages of scale
development, loadings of 0.5 or greater maybe acceptable if there exists
additional indicators for describing the latent construct (Chin, 1998). Therefore,
items with loadings of 0.5 or greater are retained. There are other authors
(Birkinshaw et al, 1995) who have also followed this criterion in their
exploratory studies. Table 2 shows the results of PLS loadings on all the
items.
Table 2 PLS
loadings Items Loading Items Loading Items Loading Items Loading H1 0.7116 S1 -0.0429 R1 0.7935 P1 0.7550 H2R 0.2901 S2 0.0522 R2 0.5848 P2 0.8353 H3 0.7169 S3 0.7699 R3 0.7495 P3 0.8061 H4 0.7166 S4 0.6938 R4 0.3555 P4 0.9023 H5R 0.2611 S5 0.6162 R5 0.6736 P5 0.8617 H6 0.7339 S6 0.3335 R6 0.7546 P6 0.8206 H7 0.6619 S7 0.7976 R7 0.8066 P7 0.8563 H8 0.8087 S8 0.8126 R8 0.7590 P8 0.9116 H9 0.6665 S9 0.7866 R9 0.5124 P9 0.8489 H10 0.8365 S10 0.6127 R10 0.6102 P10 0.8996 H11 0.8920 S11 0.6117 R11 0.7459 H12 0.7353 S12 0.6829 R12 0.7647 H13R 0.1934 S13R 0.6052 R13R 0.6469 H14R 0.4964 S14 0.7767 R14 0.7450 H15R 0.5569 S15 0.8279 R15R 0.6802 H16 0.7550 S16R -0.0241 R16 0.8782 H17 0.6453 R17 0.5328 H18 0.8123 R18 0.3527 H19R 0.5958 R19 0.3338 H20 0.8128 R20 0.3107 R21 0.4583 R22 0.3402 R23 0.4751 R24 0.5666 R25 0.2064
Item
R17 (We get as much feedback out of our customers as we possibly can under the circumstances)
was dropped because it was loaded incorrectly at 0.5449 for the human capital
construct when we used PLS techniques. This left us with 16 indicators for the
human capital construct; 12 indicators for structural construct; 16 indicators
for relational capital and; 10 items to measure performance. The researcher
compared the results with the studies administered in
According
to Cabrita and Bontis (2008), in spite of that the measurement and structural
parameters are estimated together, a PLS model is analyzed and interpreted in
two stages: the assessment of the reliability and validity of the measurement
model, and the assessment of the structural model. The sequence ensures
reliable and valid measures of constructs before we try to draw conclusions
with regard to the relationships among the constructs.
Table 3
Reliable Items – Comparing Studies in Human capital Structural capital H6 H8 H9 H11 H15R H18 H20 H3 H8 H10 H11 H20 H1 H3 H5R H6 H7 H8 H9 H10 H11 H12 H15R H17 H18 H20 H1* H3** H4 H6** H7* H8*** H9** H10** H11*** H12* H15R** H16 H17* H18** H19R H20*** S1 S2 S3 S4 S5 S6 S10 S7 S9 S10 S11 S12 S2 S3 S6 S7 S8 S9 S10 S11 S12 S15 S3** S4* S5* S7** S8* S9** S10*** S11** S12** S13R S14 S15* Relational capital Performance R1 R5 R6 R8 R9 R14 R15 R5 R6 R7 R10 R14 R16 R17 R6 R8 R9 R10 R11 R14 R16 R17 R18 R19 R20 R21 R1* R2 R3 R5** R6** R7* R8** R9** R10** R11* R12 R13R P2 P3 P4 P5 P6 P7 P8 P9 P10 P2 P3 P4 P5 P6 P7 P8 P9 P10 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P1 P2*** P3*** P4*** P5*** P6*** P7*** P8*** P9*** P10*** R22 R23 R14*** R15R* R16** R24 *reliable
measures in the **reliable
measures in the *** reliable
measures in all four studies Source: Revised from
Cabrita and Bontis’ (2008) study\
6.8. Results
The data analysis method used in this paper is Partial Least Squares
(PLS). PLS is used to analyze
simultaneously the interrelationships among all the constructs. Additionally, in order to
evaluate the statistical significance of the loadings and the path coefficients
(standardized betas), a jackknife analysis was performed. In this case 43
sub-samples were created by two cases from the total data set. By applying the
jackknife formula, PLS estimates the parameters for each sub-sample and compute
the “pseudovalues” (Table 4). Four paths (human capital to
structural capital, human capital to relational capital, structural capital to
relational capital, and relational capital to performance) have shown
significance at the p-value < 0.10. Results showed that the explanatory
power (R²) for the model is 35.5 %. Nevertheless, the path between structural
capital and business performance was not significant and thus didn’t
support the hypothesis.
Table 4 PLS Path Analysis Results
(Standardized Beta Coefficients and Adjusted T-values) Path Hypotheses β-path Adj. t-value Sig. Support Direction H→S H1 0.870 22.261 *** V + H→R H2 0.244 1.136 * V + S→R H3 0.616 3.295 *** V + S→P H4 0.087 0.280 not sig. X + R→P H5 0.521 1.747 ** V + * p < 0.10.
**p <0.05. *** p <0.001.
Figure
1 below demonstrates the results for the structural model. The results pinpoint
that the three constructs that forms intellectual capital really affect one
another. Also, human capital is the most important construct in the context of
the model given its substantive beta value.
One
important benefit of the PLS methodology is that it makes it possible to
separate direct and total effects of the variables included in the model
(Cabrita & Bontis, 2008). As we can see from Figure 1.2, decomposition of
effects shows that Human Capital (HC) has important effects on both structural
capital (0.870) and relational capital (0.244). Human capital influences
relational capital not only directly (0.244) but also indirectly through the
structural capital (0.870 x 0.616 = 0.536), giving a total effect of 0.780.
Furthermore, human capital also influences business performance indirectly HC→RC→P
(0.244 x 0.521) and HC→SC→RC→P (0.870 x 0.616 x 0.521).
Figure 1: Major Structural Model
* p < 0.15. **p <0.05. *** p
<0.001.
6.8.1. PLS Findings: Human Capital
Concerning
human capital, the executives showed high agreement to H4, which shows that
many managers agree that their employees cooperate in teams. H20 pointed out that the employees gave it their
all which makes the company different from the others in the industry. The
lowest score of H13R indicated that if certain individuals in the firm
unexpectedly left, they would be in big trouble. However this is not too
significant to notice (See Table 5).
|
Table 5
Human Capital by Likert Scale, Mean, and Standard Deviation (N=87) |
||||
|
|
Min. |
Max. |
Mean |
Std.
Deviation |
|
H1 competence ideal level |
1 |
7 |
4.82 |
1.317 |
|
H2R no succession training
program |
1 |
7 |
4.92 |
1.894 |
|
H3 planners on schedule |
1 |
7 |
4.56 |
1.412 |
Table 5 continued
Min. Max. Mean Std. Deviation H4
employees cooperate in teams 2 7 5.92 1.183 H5R no internal relationships 1 7 5.29 1.670 H6 come up with new ideas 1 7 5.41 1.369 H7 upgrade employees' skills 1 7 5.46 1.429 H8 employees are bright 2 7 5.44 1.158 H9 employees are best in industry 2 7 5.22 1.125 H10 employees are satisfied 1 7 5.18 1.225 H11 employees perform
their best 2 7 5.36 1.131 H12 recruitment program
comprehensive 2 7 4.98 1.312 H13R big trouble if
individuals left 1 7 4.43 1.821 H14R rarely think
actions through 1 7 4.54 1.546 H15R do things without
energy 1 7 5.37 1.390 H16 individuals learn
from others 1 7 5.45 1.265 H17 employees voice
opinions 2 7 5.07 1.246 H18 get the most out of
employees 2 7 5.30 1.221 H19R bring down to
others' level 2 7 5.29 1.405 H20 employees give it
their all 2 7 5.56 1.208 Note: The 7-Point Likert scale is used; R represents
reverse coded items, but are positively coded before analysis
6.8.2. PLS Findings: Structural Capital
In relation to structural capital, item S8, S13R, and S15 pinpointed that
the culture and the atmosphere of most companies are supportive and comfortable
and that they support the development of new ideas and products. Also, the
organization is not a “bureaucratic nightmare,” which means the
organizational structure is quite flexible. However, the lowest score of S1
showed the managers’ disagreement and that their companies have the
lowest cost per transaction in the industry (See Table 6).
|
Table 6 Structural Capital by Likert Scale, Mean,
and Standard Deviation (N=87) |
||||
|
|
Min. |
Max. |
Mean |
Std.
Deviation |
|
S1 lowest cost per
transaction |
1 |
7 |
3.80 |
1.598 |
|
S2 improving cost per
revenue $ |
1 |
7 |
4.22 |
1.458 |
|
S3 increase revenue per
employee |
2 |
7 |
4.94 |
1.124 |
|
S4 revenue per employee is best |
1 |
7 |
4.76 |
1.320 |
|
S5 transaction time
decreasing |
1 |
7 |
4.55 |
1.292 |
|
S6 transaction time is best |
1 |
7 |
4.25 |
1.323 |
|
S7 implement new ideas |
2 |
7 |
5.06 |
1.297 |
|
S8 supports development of ideas |
1 |
7 |
5.80 |
1.199 |
|
S9 develops most ideas in
industry |
1 |
7 |
5.26 |
1.316 |
|
S10 firm is efficient |
1 |
7 |
4.95 |
1.266 |
|
S11 systems allow easy info
access |
1 |
7 |
5.01 |
1.451 |
|
S12 procedures support
innovation |
1 |
7 |
4.90 |
1.347 |
|
S13R firm is bureaucratic nightmare |
1 |
7 |
5.63 |
1.356 |
|
S14 not too far removed from
each other |
1 |
7 |
5.41 |
1.394 |
|
S15 atmosphere is supportive |
1 |
7 |
5.51 |
1.380 |
|
S16R do not share knowledge |
1 |
7 |
5.17 |
1.740 |
|
Note: The 7-Point Likert scale is used. R represents reverse coded items, but are positively coded
before analysis |
||||
6.8.3. PLS Findings: Relational Capital
Table 7 Relational Capital by Likert Scale,
Mean and Standard Deviation (N=87) Min. Max. Mean Std. Deviation R1
customers generally satisfied 3 7 5.59 1.018 R2
reduce time to resolve problem 1 7 5.00 1.347 R3
market share improving 2 7 4.79 1.374 R4
market share is highest 1 7 3.52 1.477 R5 longevity
of relationships 1 7 4.87 1.265 R6
value added service 1 7 5.20 1.310 R7
customers are loyal 2 7 5.30 1.259 R8
customers increasingly select us 1 7 4.90 1.239 R9
firm is market-oriented 1 7 4.72 1.300 R10
meet with customers 2 7 5.56 1.198 R11
customer info disseminated 3 7 5.26 1.289 R12
understand target markets 1 7 5.20 1.284 R13R
do not care what customer wants 1 7 6.00 1.248 R14 capitalize
on customers’ wants 1 7 5.62 1.287 R15R
launch what customers don't want 2 7 5.70 1.202 R16
confident of future with customer 1 7 5.71 1.238 R17
feedback with customer 1 7 5.64 1.161 R18 react
to competition 2 7 5.07 1.283 R19
discuss competitors' strength and weakness 1 7 5.00 1.525 R20
contact with sector 1 7 4.44 1.568 R21
consider info from sector 1 7 4.54 1.328 R22 decisions
based on info from sector 1 7 4.51 1.311 R23
supports share of info from sector 1 7 4.74 1.316 R24
share competitor info 1 7 5.37 1.192 R25
competitors are sources of innovation 1 7 4.78 1.603 Note: The
7-Point
Likert scale is used. R represents reverse coded
items, but are positively coded before analysis
In the dimension of relational capital, five variables showed the
managers’ agreement concerning the aspects of customers. Item R13R, R14,
R15R, R16, R17 showed that design companies generally care about what customer
thinks or wants from them. They capitalize on customers’ wants and needs
by: continually striving to make them satisfied, getting as much feedback out
of customers as they possibly can, and launching services or products that fits
customers’ needs. Also, they feel confident that their customers will
continue to do business with them. Nevertheless, R4 pointed out the market
share of design companies are not usually high (See Table 7).
From
all the tables above, the researcher has decided to show the top 5 and the bottom
5 intellectual variables as indicated by the respondents. In Table 8 we can see
that Taiwanese design companies do care about customers’ opinions and
needs, they have confidence in repeat customers, and they launch new products
or services that fits customers’ needs. Also, the employees cooperate in
teams and the company supports the development of new ideas and products.
Table 8 Top Five Intellectual Capital Responses
(N=87)
|
Items |
Score |
Descriptions |
|
R13R |
6.00 |
We generally do not care about what the
customer thinks or wants from us |
|
H4 |
5.92 |
The firm gets the most of out of its
employees when they cooperate with each other in team tasks |
|
S8 |
5.80 |
Our company supports the development of new
ideas and products |
|
R16 |
5.71 |
We feel confident that our customers
will continue to do business with us |
|
R15R |
5.70 |
We often launch something new only to
find out that our customers do not want it |
In
Table 9 we can see that Taiwanese design companies generally don’t have a
high market share, they don’t focus much on improving cost per
transaction and cost per revenue dollar, neither on time to complete a whole
transaction. In addition, if certain individuals in the firm unexpectedly left,
the company would be in big trouble.
Table 9 Bottom Five Intellectual Capital Responses
(N=87)
|
Items |
Score |
Descriptions |
|
R4 |
3.52 |
Our market share is the highest in the
industry |
|
S1 |
3.80 |
Our organization has the lowest costs
per transaction of any in the industry |
|
S2 |
4.22 |
We have continually been improving our
costs per revenue dollar |
|
S6 |
4.25 |
The time it takes to complete one whole
transaction is the best in the industry |
|
H13R |
4.43 |
If certain individuals in the firm
unexpectedly left, we would be in big trouble |
7. Discussion
From
the descriptive statistics, we have found out some characteristics of intellectual
capital in Taiwanese design industry. The results showed that employees work in
teams in design companies (H4) to complete tasks, and they give it their all
when they work (H20). Also, if certain individuals unexpectedly left, the firm
would be in big trouble (H13R). This might be due to the fact that design
companies are usually small-scaled and teamwork plays a crucial role in
contributing to company’s performance.
Moreover,
the organizational structure of design companies is not bureaucratic (S13) and
supports the development of new ideas and products. Also, the culture of the
design companies is usually supportive (S15). Additionally, the managers
don’t seem to focus on reducing costs (S1). It can be inferred that
design companies needs a supportive culture and flexible organizational
structure to support creation and innovation. However, to maintain a working
environment like this, some efficiency might be sacrificed in replace of more
flexibility.
Furthermore,
customers’ needs (R14 to R17) are considered crucial in the design
industry. Another fact is that design companies don’t seem to have high
market share (R4). There are few design companies that possesses high market
share in
All
of the hypotheses were supported except hypothesis 4 (H4: Structural
capital is positively associated with relational capital). After analyzing the research data, the
researcher is interested in whether there are other factors, such as number of
employees in a company, or company age, that influence the impact of structural
capital on business performance. For this reason, the researcher divided the 87
samples into four sample groups to examine if there is a trend in the change of
the path coefficient.
To
do so, the researcher first divided the sample into two sample groups: Sample B
(companies with less than five employees, 34 samples) and Sample C (companies
with more than five employees, 53 samples) and ran PLS separately to see the
difference. The results indicated that all path coefficients on the structural
model of Sample C (Please see Figure 1.2), are significant at p-value <0.05;
while Sample B companies, only three paths are significant at p-value <
0.15.
To examine whether there is a trend of the change, the researcher picked
another two sub-samples respectively from Sample B and Sample C. Out of Sample
B’s 34 samples, 32 companies of age less than 15 years are picked out and
named Sample A; out of Sample C’s 53 samples, 40 companies of age more
than 5 years are picked out and named Sample D. Thus Sample A to D are
manipulated to represent respectively, a sample group with younger companies
and the other with older companies, i.e., Sample A to Sample D represents
companies with fewer employees (or younger companies) to those with more
employees (or older companies).
.
Figure 2:
Structural Models of Different Samples Groups
Note: * p < 0.1. **p
<0.05. *** p <0.001. T- stat in brackets.
Samples A to D represents companies with different numbers of employees
(from few to many) or companies with different age (from young to old)
The
results showed some interesting findings. When the company has fewer employees or
younger like in Sample A and Sample B, the results is more supportive of the
hypotheses when compared to those with more employees or those older ones
(Sample C and D) since the beta values were bigger and more significant. In
addition, the explanatory power of small-scale samples was also bigger. We can
thus infer that with growth of the number of employees or company age of a
design company, the extent to which intellectual capital contributes to a
design company’s performance decreases, especially the structural
capital. The structural capital becomes even negatively correlated with
business performance when the company grows.
Unlike the samples of previous studies (Bontis, 1998; Bontis et al., 2000; Cabrita & Bontis, 2008; Chen, 2001), design companies have many characteristics that are not possessed by other industries. The results correspond to the literature saying that design projects are usually more irrational, unpredictable, and changing, and they require much creativity of individuals (Oakley, 1990). Moreover, these results again supported the fact that design companies are more like organic organizations. This unique characteristic makes design industry more easily to cope with the unpredictable and changing environment. It also provides the company with more flexibility and adaptability, and encourages creativity and innovation. However, the disadvantage lies in that it requires higher cost and more complicated administration to maintain the structure, which could be an obstacle of business performance.
However, one limitation lies in the results is that the samples in the study contain companies that are not traditional design companies, such as the design or R&D departments of a technology companies. It is possible that these non-traditional design companies are more like manufacturing companies whose structural capital has significant influence on business performance. That is to say, an inclusion of these samples (in order to retain merely traditional design companies) might lead to different research results. Last but not least, the PLS results of the study also indicated the limitation of use of Cabrita and Bontis’ (2008) model.
8. Conclusions
The
empirical findings of this research suggests that the human capital of
Taiwanese design industry have positive influence on structural capital, and
structural capital have positive impact on relational capital. The path of
human capital to relational capital and structural capital to business
performance is not shown to be significant. However, relational capital is a
significant mediator that contributes to Taiwanese design companies’
performance instead of structural capital. That is to say, the talents of
design companies are helpful in building the firms—information systems,
routines, procedures and databases—instead of maintaining good
relationship with the organizations’ stakeholders. However, good
relationship with the companies’ customer, competitor, and sector
association is vital to design companies’ good performance.
In
addition, deeper investigation found out that the model of the study is more
appropriate in explaining the business performance of younger companies or
companies with fewer employees, which left room for future research
improvement. Other variables such as the capital or sales revenue of design
companies could be added into the research model to see if the model
explanatory power could be improved.
Furthermore,
the empirical findings of this research are also in support of the fact that
that the human capital of Taiwanese design industry not only has positive
influence on structural capital and relational capital (the mediators), but
also positively impact on business performance. Structural capital also
positively influences relational capital as hypothesized. Besides, relational
capital shows a positive association with business performance, while the
positive impact of structural capital on business performance is not
significant. This might result from the characteristics of Taiwanese design
companies’ organizational structure. Their organic structure brought the
firm the advantage of high flexibility and adaptability, however, the
efficiency of the organization is sacrificed as it is difficult and it takes
much cost to maintain such a structure.
The
results indicated that with the growth of number of employees and company age,
the impact of structural capital on business performance decreases, or even
have negative impact on business performance. Also, the explanatory power of
intellectual capital on business performance reduces. However, this might
result from the special sample of the study. The sample of this research
includes not only traditional design companies, but also some design or R&D
department of technology companies, design sector associations, etc., as they are
also included in TDC’s catalog. That is to say, a sample that excluded
these non-traditional design companies might lead to different results, which
leaves room for future study improvement.
9. Descriptive
Statistics
Results
of this study showed some characteristics of intellectual capital in Taiwanese
design companies. Concerning human capital, Taiwanese design industry
emphasizes teamwork and employees give it their all when they work.
Additionally, because design companies are usually small-scaled, every employee
plays a certain crucial role in the company. In relation to structural capital,
the organizational structure of design companies is an organic structure which
features its flexibility. The culture of the firm is supportive and fosters the
development of new products and ideas. As to relational capital, the
interaction between the firm and customers is crucial to the company. Design
companies make profit by striving for understanding and satisfying
customers’ needs.
10. Recommendations
Based
on the findings of this study the following recommendations are devised.
10.1. Recommendations For Government And Managers
Of Taiwanese Design Companies
As far as the government is concerned, it
should provide Taiwanese design companies with the education such as team
building (H4), compensation and benefit system, succession training (H13R), and
motivating and leading employees (H20). This could be conducted by holding
international academic conferences or symposiums to boost Taiwanese design
company managers’ interaction with foreign scholars to learn from their
experiences. Also, the government should continuously hold and improve
international exhibition or competition, so that design companies could have
more opportunities to introduce their service to customers (R14 to R17).
Concerning managers of design companies,
for the human capital construct, they should encourage employees to work in
teams (H4) and motivate them to give it their all (H20). Besides,
employees’ compensation and benefit need to be improved to retain talents
in the company, as well as develop appropriate succession plan for
employees’ unexpected leave (H13R). For structural capital construct,
managers should create an organic structure (S13R) and a supportive atmosphere (S15)
where employees can be inspired and creative. Moreover, cost leadership
strategy might not work well for design companies (S1), which is worth noticing
for managers. Concerning relational capital, the company should incorporate
customer relationship management systems; the managers should capitalize on
customers’ wants (R14), launch products that fit their needs (R15R), and
get feedback from customers (R17).
10.2. Recommendations
From The Perspective Of Market Leadership
Managers
can improve the companies’ market leadership through the three
intellectual capital components respectively.
First, from human capital construct, design companies need to improve
employee satisfaction (H10); employees’ loyalty need to be enhanced since
their devotion to the company does not seem to be satisfying (H11); managers should
strive for fully utilizing employees’ under-utilized talents and
discovering their potential (H18).
Second,
from structural capital construct, the efficiency of
task accomplishment needs to be improved (S10);
the companies should reinforce their decision making
system. Also, the managers should ask their staff to take the
responsibility to make decisions after discussing important issues (S13R).
Third,
from relational capital construct, design companies lack of concern and
understanding of competitors, and more attention should be paid to their
potential competitors (R19).
10.3. Recommendations
From The Perspective Of Financial Performance
Managers
can improve the companies’ financial performance through the three
intellectual capital components respectively.
First, from human capital construct, a more comprehensive staffing
program need to be developed to recruit talents (H12); employees are too passive in voicing their opinions, so
managers should discuss problems with them and encourage them to be more
active and constructive (H15R); also, in order
to achieve the objectives of the firm, managers should provide more incentives
for employees to give their all (H20).
Second,
from structural capital construct, the company should
create a supportive and comfortable culture that helps employees to produce new
ideas (S9); hire employees that can work as a
team, instead of those who are too self-centered and not willing to cooperate
with others (S14).
Third,
from relational capital construct, the firm should spend more time meeting with
customers (R10); with public recognition of intellectual property right
protection, the managers might consider to establish knowledge management system
to enhance sharing of customer feedback (R11).
10.4. General Recommendations (Market Leadership
And Financial Performance)
Managers
can improve the companies’ entire business performance through following
aspects.
First,
from human capital construct, companies should create an environment where
employees can brainstorm for creativity freely (H8) in order to improve
companies’ business performance.
Second,
from relational capital construct, employees should be trained to understand
the firms’ target market more (R12). Also, the idea that good business
performance comes from satisfying customers’ needs and capitalizing on
their wants (R14) should be encouraged in the company; Additionally, design
companies need to consider information from sector association more (R21); and
lastly, the company should introduce knowledge management system to enrich the
share of competitor information (R24).
10.5. Recommendations For Future
Research
The
contribution of the study lies in assessing the interrelations among
intellectual capital components and their influence on business performance of
design companies in
Despite the many researches on intellectual capital, there is very little
research focusing on the scope of design industry. As a result
if researchers interested in pursuing an even stronger understanding of intellectual
capital in
Ø
Adding other variables such as the scale
of the company, e.g., sales revenue, or capital, to see if they change the
intellectual capital and the relationship between intellectual capital and
business performance.
Ø
Research with design industries in other
countries, investigating their intellectual capital performance and its impact
on business performance.
Ø
Research with qualitative research to
compare and contrast with the findings of quantitative studies.
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Guang-Ming:
About the Authors:
Dr. Cheng-Ping Shih is an Associate Professor in the
International Human Resources Department (IHRD) at the National Taiwan Normal
University (NTNU); Graduate Students Dormitory 1- 1- C, No. 88, Sec. 4, Ting
–
Wen-Chih Chen
is a graduate of the IHRD at NTNU. He holds a masters degree in this discipline.
He is currently deployed to the Taiwan army; Graduate Students Dormitory 1- 1-
C, No. 88, Sec. 4, Ting –
Melton Morrison is currently a second year student at
NTNU, perusing his Masters Degree in IHRD.
He currently holds a Bachelors Degree in Math Education from the