Chapter Overview
This chapter contains conclusions and recommendations. There are three parts in the conclusion section, including conclusion of descriptive statistics, conclusion of PLS results, and conclusion of multiple regression results. Also, the study provided some recommendations for the managers of Taiwanese design companies. Finally there is a recommendation for future research on this topic.
Conclusions
Conclusion of 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.
Conclusions of PLS results
The empirical findings of this research proved 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 proved to be significant. It is relational capital that contributes to Taiwanese design companies’ performance instead of structural
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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.
Conclusions of multiple regression results
This study adopted multiple regression analysis (backward elimination) to evaluate the impact of intellectual capital on business performance and reached three major conclusions.
Firstly, in the three major intellectual capital components, most of the questions are proved to have positive influence on business performance. Several positive and significant questions are listed below. For the independent variables whose counts are not that frequent, please refer to Table 5.1 and Table 5.2 in Chapter V.
Conclusion of market leadership and financial performance indicators
¾ For human capital, the results indicated that team work (H4) is one of the most important factors that contribute to the market leadership and financial performance of a design company.
¾ For structural capital, implementing most of the great new ideas (S7) could lead to good success rate in launching new products (P9), profit growth (P4), sales growth (P5), and after-tax return on sales (P7).
¾ For relational capital, improving market share (R3) could be helpful to improve a design company’s market leadership and financial performance. Providing the most value-added service to customers (R6) could contribute to the firm’s overall response to competition (P8), success rate of launching new products (P9), overall business performance and success (P10), profit (P3), after-tax return on assets (P6),
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and after-tax return on sales (P7). In addition, support of sharing information from sector association (R23) is beneficial to enhance the organization’s overall business performance and success (P10), profit growth (P4), sales growth (P5), after-tax return on assets (P6), as well as after-tax return on sales (P7).
Secondly, with the process of economic development, Taiwan has gone through labor-intensive, technology-intensive, and come to knowledge-intensive stage. The findings of the study indicated that Taiwanese design industries are knowledge-intensive industries and that they are quite different than last century’s technology-intensive industry. Also, it is proved that the business model of benchmark manufacturing companies cannot copied or applied to design companies, because the elements of innovation in design industry is very different.
This study has found out the following major features of Taiwanese design industry:
¾ Design projects require more intuition than rationality. Fully rational behavioral (H14R) may have negative influence on business performance.
¾ The business model of design industry differs from that of manufacturing industry.
Manufacturing companies like LG and Foxconn intensify their business performance through adopting cost leadership strategy. However, cost leadership strategy (S1&S2) may not work in design industry.
¾ Design tasks are usually time-consuming, which is quite different from routine jobs in manufacturing industry. Since design service requires much time to ensure the quality, it takes more time to complete the whole transaction. In addition, even though it takes a lot of time to accomplish tasks (S5&S6), design companies could still have satisfying business performance.
¾ From the theory of knowledge management, we should create a knowledge management system to provide access to share information in order to improve the company’s business performance. However, since these design companies in Taiwan are small and medium sized enterprises, intellectual property rights are not well protected. Therefore, to ensure the benefit of the company, limiting the access of certain information (S11) is the second best alternative.
¾ Different from multinational companies, design companies in Taiwan are small and medium sized enterprises. This forces them to quickly respond to customers’
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requests. Thus, even though design companies don’t have high market share (R4), they can still have excellent business performance.
¾ As mentioned before, although the market share of design companies is not high, they still have confidence (R16) that they can quickly provide services that satisfy customers’ need.
Lastly, many other studies conducted intellectual capital research by using structural equation modeling (SEM) technique, such as PLS. This study not only used PLS to analyze the data, but also adopted multiple regression analysis, through the use of backward elimination method, to improve the problem of low R square values. All of the R square values of these multiple regressions have exceeded 97.0%, which means the models have high explanatory power over business performance.
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Recommendations
Recommendations for the government and managers of Taiwanese design companies (based on descriptive statistics)
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).
Recommendations for managers of Taiwanese design companies (based on multiple regression results)
This empirical study provided evidence of the interrelationships among intellectual capital components and their significant impact on business performance. However, some interesting empirical findings of this study pointed out the room for improvement. In pursuit for better business performance in design industry, the study proposes some recommendations to Taiwanese design company managers based on the perspective of
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market leadership and financial performance. And finally, recommendations are provided in the synthesized perspective. Nevertheless, this is a pilot study and much room is left for improvement in future researches on this topic.
¾ 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).
¾ 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).
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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).
¾ 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).
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 Taiwan. However, different research participants, and different research questions and methods would produce varying patterns of engagement that may add or deviate from the results of this study.
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 Taiwan may want to investigate different scopes of industry, use other methods, or discuss different issues. The following list specifies the type of research.
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1. 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.
2. Research with design industries in other countries, investigating their intellectual capital performance and its impact on business performance.
3. Research with qualitative research to compare and contrast with the findings of quantitative studies.
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References
2003-2006 Taiwan cultural and creative industry relevant statistics. (n. d.). Retrieved January 14, 2009, from http://www.cci.org.tw/
Bassi, L. J., & Van Buren, M. E. (1999). Valuing investments in intellectual capital.
Technology Management, 18(5), 414-432.
Birkinshaw, J., Morrison, A., & Hulland, J. (1995). Structural and competitive determinants of a global integration strategy. Strategic Management Journal, 16, 637-655.
Bontis, N. (1996). There's a price on your head: Managing intellectual capital strategically. Business Quarterly, 60(4), 40-47.
Bontis, N. (1997). Intellectual capital questionnaire. Hamilton: Canada: Institute for Intellectual Capital Research Inc.
Bontis, N. (1998). Intellectual capital: An exploratory study that develops measures and models. Management Decision, 36(2), 63-76.
Bontis, N. (1999). Managing organizational knowledge by diagnosing intellectual capital: Framing and advancing the state of the field. International Journal of Technology Management, 18(5-8), 433-462.
Bontis, N. (2001). Assessing knowledge assets: A review of the models used to measure intellectual capital. International Journal of Management Reviews, 3(1), 41-60.
Bontis, N. (2002). World congress of intellectual capital readings. Boston: Elsevier Butterworth Heinemann KMCI Press.
Bontis, N., Crossan, M., & Hulland, J. (2002). Managing an organizational learning system by aligning stocks and flows. Journal of Management Studies, 39, 437-469.
Bontis, N., Keow, W. C. C., & Richardson, S. (2000). Intellectual capital and business performance in Malaysian industries. Journal of Intellectual Capital, 1(1), 85-100.
Brooking, A., Board, P., & Jones, S. (1998). The predictive potential of intellectual capital. Technology Management, 16(1-3), 115-125.
Bukh, P. N., Larsen, H. T., & Mouritsen, J. (1999). Developing intellectual capital statements: Lessons from 23 Danish firms. International Symposium Measuring and Reporting Intellectual Capital: Experiences, Issues and Prospects.
Amsterdam.
Burns, T., & Stalker, G. M. (1961). The management of innovation. London:
Tavistock.
93
Cabrita, M. D. R., & Bontis, N. (2008). Intellectual capital and business performance in the Portuguese banking industry. International Journal of Technology Management, 43(1-3), 212.
Chen, J., Zhu, Z., & Xie, H. Y. (2004). Measuring intellectual capital: A new model and empirical study. Journal of Intellectual Capital, 5(1), 195-212.
Chen, M. C. (2001). The effect of information technology investment and intellectual capital on business performance. Unpublished National Central University, Taoyuan County, Taiwan.
Chen, M. C., Cheng, S. J., & Hwang, Y. (2006). An empirical investigation of the relationship between intellectual capital and firms' market value and financial performance. Journal of Intellectual Capital, 6(2), 159-176.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. in G. A. Marcoulides. In G. A. Marcoulides (ed.), Modern
Methods for Business Research, (pp. 295-366). NJ: Lawrence Erlbaum Associates.
Choo, C. W., & Bontis, N. (2002). The strategic management of intellectual capital and organizational knowledge. New York: Oxford University Press.
Council for Economic Planning and Development. (2005). Challenge 2008: National development plan (2002-2007). Retrieved January 23, 200, from
http://www.cepd.gov.tw/
Drucker, P. (1993). Post-capitalist society. Oxford: Butterworth-Heinemann.
Dzinkowski, R. (2000). The measurement and management of intellectual capital: An introduction. Management Accounting, 78(2), 32-36.
Edvinsson, L. (1998). Managing intellectual capital in Skandia. In P. H. Sullivan (Ed.), Profiting from intellectual capital: Extracting value from innovation (pp. 279).
New York: John Wiley & Sons, Inc.
Edvinsson, L., & Malone, M. (1997). Intellectual capital: Realising your company's true value by finding its hidden brainpower. New York: Harper Collins.
Edvinsson, L., & Sullivan, P. H. (1996). Developing a model for managing intellectual capital. European Management Journal, 14(4), 356-364.
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with
unobservable variable and measurement error. Journal of Marketing Research, 18, 39-50.
Grantham, C. E., Nichols, L. D., & Schonberner, M. (1997). A framework for the management of intellectual capital in the health care industry. Journal of Health Care Finance, 23(3), 1-19.
Guthrie, J. (2001). The management, measurement and the reporting of intellectual capital. Journal of Intellectual Capital, 2(1), 27-41.
94
Guthrie, J., & Petty, R. (2000). Are companies thinking smart? Australian CPA, 70(6), 62-65.
Huang, C. J., & Liu, C. J. (2006). Exploration for the relationship between innovation, IT and performance. Journal of Intellectual Capital, 6(2), 237-252.
Johnson, W. H. A. (1999). An integrative taxonomy of intellectual capital: Measuring the stock and flow of intellectual capital components in the firm. International Journal of Technology Management, 18(5-8), 562-575.
Lin, S. C., & Huang, Y. M. (2006). The role of social capital in the relationship between human capital and career mobility: Moderator or mediator? Journal of Intellectual Capital, 6(2), 191-206.
Lynn, B. E. (1999). Culture and intellectual capital management: A key factor in successful ICM implementation. International Journal of Technology Management, 18(5-8), 590-603.
Masoulas, V. (1998). Organizational requirements definition for intellectual capital management. International Journal of Technology Management, 16(1-3), 126.
McElroy, M. K. (2002). Social innovation capital. Journal of Intellectual Capital, 3(1), 30-39.
Ministry of Economic Affairs. (2005). Ministry of economic affairs 2005 "Taiwan design center promotion plan" design trend research report: A study about current situation of national design policy and future prospect. Retrieved March 20, 2009, from http://www.moea.gov.tw
Molyneux, A. (1998). IC and ASCPA: Seeking competitive advantage. Australia CPA, 68(5), 27-28.
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management, 23(2), 242-266.
Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company: How japanese companies manage the dynamics of innovation. New York: Oxford University Press.
Nunnally, J. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
Roos, G., & Roos, J. (1997). Measuring your company's intellectual performance.
Long Range Planning, 30(3), 413-426.
Roos, J., Roos, G., Edvinsson, L., & Dragonetti, N. C. (1998). Intellectual capital:
Navigating in the new business landscape. New York: New York University Press.
Stewart, T. (1997). Intellectual capital: The new wealth of organizations. New York:
Doubleday/Currency.
Sveiby, K. E. (1997). The new organizational wealth:Managing and measuring knowledge-based assets. New York: Berrett Koehler.
95
Taiwan Intellectual Capital Research Center, & Market Intelligence Center (Eds.).
(2006). Intellectual capital management. Taipei City: Hwa Tai Publishing.
Tsan, W. N., & Chang, C. C. (2006). Intellectual capital system interaction in Taiwan.
Journal of Intellectual Capitalurna, 6(2), 285-298.
Ulrich, D. (1998). Intellectual capital = competence x commitment. Sloan Management Review, 39(2), 15-26.
Van Buren, M. E. (1999). A yardstick for knowledge management. Training &
Development, 53(5), 71-78.
Wang, W. Y., & Chang, C. (2005). Intellectual capital and performance in causal models: Evidence from the information technology industry in Taiwan. Journal of Intellectual Capital, 6(2), 222-236.
Yang, S. M. (2008, July 20). Chang Guang-Ming: Taiwan expected to get more than 200 international design awards in 2008. Sina Finance News. Retrieved February, 11, 2009, from http://financenews.sina.com/cna/
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APPENDIX B. SURVEY OF THE STUDY
敬請將此份問卷轉交 貴公司主管(或 貴公司設計部門主管)，感謝！
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APPENDIX C. LIST OF EXPERTS
Name Title Suggestions
1. Make sure the 7-point Likert-Scale represents
“agreement/disagreement” or
“satisfaction/dissatisfaction.”
2. Need to explain what does the scale (1 to 10) of performance indicators stand for.
3. “Compared to major competitors” should be added to in the instruction text.
Hong- Siang Ciou
Design Director, China Productivity Center
1. What does “we” in the questions stands for?
It could cause misunderstanding if you didn’t make it clear.
2. Pay attention to the use of terms, for example, respondents might not understand what
“competence” means.
3. Make sure that respondents are kept anonymous; otherwise it could be difficult to collect questionnaires.
1. Terms such as costs per revenue dollar, revenue earned per employee, need to be revised to be more easily understandable for the
respondents. thesis in the cover letter, so that respondents won’t have prejudice before they answer.
Note: The name list is arranged according to alphabetic order.
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APPENDIX D. MATRIX OF LOADINGS AND
CROSS-LOADINGS
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Item Human Capital
Structural Capital
Relational Capital
Business Performance
P6 0.4047 0.3695 0.3851 0.8206
P7 0.3245 0.3265 0.3739 0.8563
P8 0.5406 0.5201 0.5614 0.9116
P9 0.5622 0.5403 0.5652 0.8489
P10 0.5634 0.4788 0.5874 0.8996
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APPENDIX E. MULTIPLE REGRESSION RESULTS
Multiple Regression of Independent Variables as Predictors for P1 (Industry Leadership)
Variables Equation 1 Equation 47
β value t-value β value t-value
H1 competence ideal level 0.127 0.529
H2R no succession training program 0.097 0.791
H3 planners on schedule -0.083 -0.455
H4 employees cooperate in teams 0.677** 2.822 0.569*** 4.950 H5R no internal relationships -0.017 -0.101
H6 come up with new ideas -0.111 -0.406 H7 upgrade employees’ skills -0.082 -0.374
H8 employees are bright -0.247 -0.740
H9 employees are best in industry 0.126 0.451
H10 employees are satisfied -0.201 -0.644 -0.364** -3.018 H11 employees perform their best -0.157 -0.370
H12 recruitment program comprehensive 0.028 0.137 H13R big trouble if individuals left 0.008 0.062
H14R rarely think actions through -0.158 -0.774 -0.207** -3.138 H15R do things without energy -0.037 -0.157
H16 individuals learn from others -0.203 -0.695
H17 employees voice opinions 0.363 1.328 0.247** 2.343 H18 get the most out of employees -0.315 -1.145
H19R bring down to others’ level 0.127 0.575 H20 employees give it their all 0.588 1.703
S1 lowest cost per transaction -0.292** -2.277 -0.315*** -5.773 S2 improving cost per revenue $ 0.101 0.704 0.135** 2.224
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S13R firm is bureaucratic nightmare -0.291 -1.148 S14 not too far removed from each other -0.010 -0.033 S15 atmosphere is supportive 0.041 0.150 S16R do not share knowledge 0.097 0.647 R1 customers generally satisfied 0.169 0.461 R2 reduce time to resolve problem 0.037 0.207
R3 market share improving 0.218 0.711 0.344*** 3.754 R4 market share is highest -0.073 -0.430
R5 longevity of relationships 0.227 0.918 0.394*** 4.294
R6 value added service 0.192 0.757
R7 customers are loyal -0.095 -0.258
R8 customers increasingly select us 0.071 0.258
R9 firm is market-oriented 0.015 0.071
R10 meet with customers -0.033 -0.105
R11 customer info disseminated 0.086 0.350 R12 understand target markets -0.086 -0.256 R13R do not care what customer wants -0.034 -0.112 R14 capitalize on customers' wants -0.188 -0.753
R15R launch what customers don't want 0.433 1.349 0.694*** 5.384 R16 confident of future with customer -0.231 -0.461 -0.742*** -4.365
R17 feedback with customer 0.271 1.061 0.247** 2.290
R18 react to competition -0.050 -0.262
R19 competitors' strength and weakness 0.078 0.521
R20 contact with sector 0.123 0.804 0.205** 2.924
R21 consider info from sector -0.168 -0.705 -0.160* -1.960 R22 decisions based on info from sector 0.086 0.388
R23 supports share of info from sector -0.042 -0.169
R23 supports share of info from sector -0.042 -0.169