Chapter Overview
This chapter introduces the process and results of multiple regression, using backward elimination method. Multiple regression findings are demonstrated based on the two categories of business performance indicators: market leadership and financial performance, as defined in the study. In addition, a discussion part is given to compare the significance of their influence in each intellectual capital construct.
Multiple Regression Findings
A multiple linear regression analysis was used to investigate whether the independent variables have statistical significance as predictor variables; ten enterprise performance indicators are used for the criterion variable. The independent variables are the sixty-one intellectual capital questions, which come from the three intellectual capital dimensions of Cabrita and Bontis’ (2008) study: human capital, structural capital, and relational capital. All the reverse-coded variables are recoded before running multiple regressions.
By using the backward elimination procedure, we examined the p-values for the 61 independent variables, and eliminated the highest insignificant variable in each equation.
This process is repeated until all remaining independent variables reach at least the 10%
level of significance. The first equations of each multiple regression are reported in Appendix E. The results of last equations for market leadership indicators and financial performance indicators were reported in Table 5.1 and Table 5.2.
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Table 5.1 Multiple Regression Results of Market Leadership Indicators (Independent Variables as Predictors for Business Performance) in the Final Equations
H4 employees cooperate in teams 0.569*** 4.950 0.606*** 6.439 0.613*** 6.126 0.483*** 5.013 0.384*** 4.703
H5R no internal relationships 0.087* 1.691
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R3 market share improving 0.344*** 3.754 0.326*** 4.395 0.281** 3.190 0.346*** 4.085 0.306*** 4.125
R4 market share is highest -0.128** -2.548 -0.235*** -3.906
R5 longevity of relationships 0.394*** 4.294 0.167** 2.093
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Note: Betas provided in the table are all standardized beta values. * p<0.1. **p<0.05. *** p<0.001. Independent variables that are insignificant in all ten regressions are not listed in this table.
52 Market Leadership
In Table 5.5, the value of R² ranged from 0.979 to 0.991, which means these intellectual capital components successfully explained the indicators of the market leadership. Theoretically, it is a very good model to explain a company’s market leadership.
In each regression, it is noted that the numbers of significant independent variables in descending order are the overall response to competition (24 variables), the future outlook (23 variables), the industry leadership (15 variables), the overall business performance and success (11 variables), and the success rate in launching new products (9 variables).
In the following paragraphs a detailed discussion is given on the empirical results.
Multiple regression results for industry leadership (P1)
In Equation 47, 15 variables show statistical significance to industry leadership. Of those 15 variables, 6 have negative parameters and 9 have positive parameters.
¾ Human capital construct
For the human capital construct, four questions show significance to industry leadership: H4 “employees cooperate in teams” has a positive parameter (0.509) and t-ratio (4.95) indicating significance at 0.1%, which means it takes a lot of teamwork for design company employees to accomplish their tasks, in order to strengthen the firms’
industry leadership. H10 “Employees are satisfied” has a negative parameter (-0.364) and t-ratio (-3.108) indicating significance at 5%, this implies in spite of that the firms’
industry leadership is satisfying; however, the managers think employees are not satisfied with the organization. H14R “Rarely think actions through” has a negative parameter (-0.207) and t-ratio (-3.138) indicating significance at 5%. Probably this is because the company’s characteristic is quite different from most companies, since design companies need more intuitive than rationality. Therefore, fully rational behavior will have negative impact on the company’s industry leadership. H17 “Employees voice opinions” has a positive parameter (0.247) and t-ratio (2.343) indicating significance at 5%; this implies encouraging employees to voice their opinion ensures the firms’ industry leadership.
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¾ Structural capital construct
For the structural capital construct, three questions show significance to industry leadership: S1 “lowest cost per transaction” has a negative parameter (-0.315) and t-ratio (-5.773) which is significant at 0.1%. It reflects that the managers self valuate that their company should not take the cost leadership strategy. The business model for design industry is quite different than manufacturing industries. Manufacturing companies like LG or Foxconn intensify their industry leadership by adopting cost leadership strategy.
S2 “improving cost per revenue dollar” has a positive parameter (0.135) and t-ratio (2.224) which is significant at 5%; this implies improving cost per revenue dollar helps ensure the organizations’ industry leadership. S11 “systems allow easy info access” has a negative parameter (-0.201) and t-ratio (-2.555) which is significant at 5%. According to knowledge management, we should share resources. Nevertheless, the result showed the uniqueness of design companies and that the constraints of information accessibility will ensure the company’s industry leadership.
¾ Relational capital construct
For the relational capital construct, eight questions show significance to industry leadership: R3 “market share improving” has a positive parameter (0.344) and t-ratio (3.754) which is significant at 0.1%; this implies improving market share is crucial for design companies to improve the firms’ industry leadership. R5 “longevity of relationships” has a positive parameter (0.394) and t-ratio (4.294) which is significant at 0.1%; this implies the longevity of the relationships with customers improves the companies’ industry leadership. R15R “launch what customers don't want” has a positive parameter (0.694) and t-ratio (5.384) which is significant at 0.1%; this implies launching new products that fit customers’ needs is crucial to a design company’s industry leadership. R16 “confident of future with customer” has a negative parameter (-0.742) and t-ratio (-4.365) which is significant at 0.1%; this implies even though customers know very well that the firms do not have high industry leadership they are still willing to do business with the companies. This may be due to the fact that these firms provided some services that might satisfy customers’ needs. R17 “feedback with customer” has a positive parameter (0.247) and t-ratio (2.290) which is significant at 5%; this implies
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getting as much feedback out of its customers as possible is important for a design company to ensure its industry leadership. R20 “contact with sector” has a positive parameter (0.205) and t-ratio (2.924) which is significant at 5%; this implies it is critical for design companies to maintain regular contact with the sector associations, either domestic or non-domestic, to share sector’s information, because this improves the companies’ industry leadership. R21 “consider info from sector” has a negative parameter (-0.160) and t-ratio (-1.960) which is significant at 10%. This point out the even though the firms already have good industry leadership, the managers still think they did not consider information as important as they should. R25 “competitors are sources of innovation” has a positive parameter (0.132) and t-ratio (2.174) which is significant at 5%; this implies considering competitors a source of innovation ensures the firm’s industry leadership.
The other questions show no statistical significance to industry leadership.
55 Multiple regression results for future outlook (P2)
In Equation 39, 23 variables show statistical significance to future outlook. Of those 23 variables, 11 have negative parameters and 12 have positive parameters.
¾ Human capital construct
For the human capital construct, four questions show significance to future outlook:
H4 “employees cooperate in teams” has a positive parameter (0.606) and t-ratio (6.439) which is significant at 0.1%; this implies it takes a lot of teamwork for design company employees to accomplish their tasks, in order to ensure the firms’ future outlook. H8
“employees are bright” has a negative parameter (-0.254) and t-ratio (-2.401) which is significant at 5%. It shows that even though the firms’ overall response to competition is satisfying, there is still room for the managers to encourage the staff’s creativity. H11
“employees perform their best” has a negative parameter (-0.376) and t-ratio (-2.942) which is significant at 5%. Despite that the firm has good future outlook, they still think their employees could not continue performing at their best. H18 “get the most out of employees” has a negative parameter (-0.166) and t-ratio (-1.819) which is significant at 10%. The companies did not fully utilize those under-utilized talents. This could mean the managers should focus on putting more efforts to explore the under-utilized knowledge.
¾ Structural capital construct
For the structural capital construct, nine questions show significance to future outlook: S1 “lowest cost per transaction” has a negative parameter 0.161) and t-ratio (-4.040) which is significant at 0.1%; this implies that the managers think that their firms should not take the cost leadership strategy. The business model for design industry is quite different than that of manufacturing industries. Manufacturing companies like LG or Foxconn intensify their industry leadership by adopting cost leadership strategy. S2
“improving cost per revenue dollar” has a positive parameter (0.156) and t-ratio (3.393) which is significant at 5%; this implies improving cost per revenue dollar helps ensure the organizations’ future outlook. S6 “transaction time is best” has a negative parameter (-0.160) and t-ratio (-2.991) which is significant at 5%. It indicated that even though the
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transaction times of these firms are not good, they can still retain their good future outlook. S8 “supports development of ideas” has a positive parameter (0.389) and t-ratio (3.233) which is significant at 5%; this implies that it is important for design companies to support the development of ideas in order to ensure the future outlook of the company.
S9 “develops most ideas in industry” has a positive parameter (0.251) and t-ratio (2.737) which is significant at 5%; this implies the development of new ideas and products plays a significant role in the firms’ future outlook. S10 “firm is efficient” has a negative parameter (-0.137) and t-ratio (-1.869) which is significant at 10%; this pinpointed that despite the fact that firms’ future outlook is satisfying, the managers still think the firm are not efficient enough. It is because under the constraints of the industries’ unique features, design companies might spend more time improving the quality of their service.
S13R “firm is bureaucratic nightmare” has a negative parameter 0.360) and t-ratio (-4.010) which is significant at 0.1%; this implies that even though the companies’ future outlook is satisfactory, the organizational structure of them is not efficient enough. It could be explained by question S10 that the company is not efficient. Therefore, the staff needs someone who can make decisions after discussing each issue of each agenda. S14
“not too far removed from each other” has a positive parameter (0.211) and t-ratio (2.291) which is significant at 5%; this implies that an appropriate organizational structure to ensure the close relation among employees is helpful to improve the future outlook. S16R “do not share knowledge” has a positive parameter (0.124) and t-ratio (2.896) which is significant at 5%; this implies sharing knowledge or ideas is vital for design companies since it enhances the companies’ future outlook.
¾ Relational capital construct
For the relational capital construct, ten questions show significance to future outlook: R3 “market share improving” has a positive parameter (0.326) and t-ratio (4.395) which is significant at 0.1%; this implies improving market share is crucial for design companies to improve the firms’ future outlook. R4 “market share is highest” has a negative parameter (-0.128) and t-ratio (-2.548) which is significant at 5%; this showed this question has the lowest score in this construct (the mean is 3.52). It indicates that even though the design companies do not have high market share, their future outlook is
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still satisfying. R5 “longevity of relationships” has a positive parameter (0.167) and t-ratio (2.093) which is significant at 5%; this implies the longevity of the relationships with customers improves the companies’ future outlook of the firm. R8 “customers increasingly select us” has a positive parameter (0.178) and t-ratio (2.040) which is significant at 5%; this implies customers’ preference of a design company to its competitors improves the company’s future outlook. R11 “customer info disseminated”
has a positive parameter (0.328) and t-ratio (3.732) which is significant at 0.1%; this implies dissemination of customer feedback is helpful to the company’s future outlook.
R12 “understand target markets” has a negative parameter (-0.340) and t-ratio (-3.626) which is significant at 5%; the mean of this question is 5.20. The results implies that despite the companies having a promising future outlook, the managers think they need to make employees understand more about the companies’ target markets. R14 “capitalize on customers’ wants” has a negative parameter (-0.304) and t-ratio (-3.594) which is significant at 5%; this implies that managers think their organizations have not fully capitalize on customers’ wants. Thus, the managers should fully utilize their staff’s under-utilized knowledge to transfer customers’ needs into promoting company’s future outlook. R15R “launch what customers don't want” has a positive parameter (0.474) and t-ratio (5.054) which is significant at 0.1%; this implies launching new products that fit customers’ needs is crucial to a design company’s future outlook. R19 “discuss competitors' strength and weakness” has a negative parameter 0.103) and t-ratio (-2.015) which is significant at 5%; this showed that the firms lack concern and understanding of competitors. The companies should pay more attention on potential competitors who are entering the market. R25 “competitors are sources of innovation”
has a positive parameter (0.272) and t-ratio (5.354) which is significant at 0.1%; this implies considering competitors a source of innovation ensures the firm’s outlook.
The other questions show no statistical significance to future outlook.
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Multiple regression results for overall response to competition (P8)
In Equation 38, 24 variables show statistical significance to overall response to competition. Of those 24 variables, 10 have negative parameters and 14 have positive parameters.
¾ Human capital construct
For the human capital construct, five questions show significance to overall response to competition: H4 “employees cooperate in teams” has a positive parameter (0.613) and t-ratio (6.126) which is significant at 0.1%; this implies it takes a lot of teamwork for design company employees to accomplish their tasks in order to strengthen the firms’ overall response to competition. H5R “no internal relationships” has a positive parameter (0.087) and t-ratio (1.691) which is significant at 10%; this implies the development and maintenance of internal relationships among various groups in design companies is helpful to the organizations’ overall response to competition. H8
“employees are bright” has a negative parameter (-0.233) and t-ratio (-2.201) which is significant at 5%; this indicated that even though the firms’ overall response to competition is satisfying, there is still room for the managers to encourage the staff’s creativity. H10 “employees are satisfied” has a positive parameter (0.268) and t-ratio (2.483) which is significant at 5%; this implies employees satisfaction is helpful to the company’s overall response to competition. H14R “rarely think actions through” has a negative parameter (-0.117) and t-ratio (-2.051) which is significant at 5%; this implies employees’ fully rational behaviors could become a hindrance to the company’s competitiveness.
¾ Structural capital construct
For the structural capital construct, seven questions show significance to overall response to competition: S4 “revenue per employee is best” has a positive parameter (0.196) and t-ratio (2.266) which is significant at 5%; this implies increasing revenue earned per employee in the firm enhances the firms’ overall response to competition. S5
“transaction time decreasing” has a negative parameter (-0.304) and t-ratio (-3.676) which is significant at 0.1%. This might due to the characteristics of design industry.
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Design tasks are usually time-consuming, which is quite different from standardized operation process in manufacturing industries. Since design service requires tremendous communication to ensure quality, it usually takes much time to complete a transaction. S6
“transaction time is best” has a positive parameter (0.153) and t-ratio (2.284) which is significant at 5%; this implies improving the time it takes to complete one whole transaction is helpful to the companies’ overall response to competition. S9 “develops most ideas in industry” has a positive parameter (0.378) and t-ratio (3.810) which is significant at 0.1%; this implies the development of new ideas and products plays a significant role in the firms’ overall response to competition. S10 “firm is efficient” has a negative parameter (-0.254) and t-ratio (-2.959) which is significant at 5%; this implies that despite the fact that the firms’ overall response to competition is satisfying, the managers still think the firm are not efficient enough. It is because under the constraints of the industries’ unique features, design companies might spend more time to improve the quality of their services. S13R “firm is bureaucratic nightmare” has a negative parameter (-0.279) and t-ratio (-3.249) which is significant at 5%; this implies that even though the companies’ overall response to competition is satisfactory, their organizational structures is not efficient enough. It could be explained by question S10 that the company is not efficient. Therefore, the staff needs someone who can make decisions after discussing each issue of each agenda. S16R “do not share knowledge” has a positive parameter (0.142) and t-ratio (2.945) which is significant at 5%; this implies sharing knowledge or ideas is vital for design companies since it enhances the companies’ overall response to competition.
¾ Relational capital construct
For the relational capital construct, twelve questions show significance to overall response to competition: R1 “customers generally satisfied” has a positive parameter (0.345) and t-ratio (2.623) which is significant at 5%; this implies customer satisfaction is beneficial to the company’s overall response to competition. R3 “market share improving” has a positive parameter (0.281) and t-ratio (3.190) which is significant at 5%; this implies improving market share is crucial for design companies to improve the firms’ overall response to competition. R4 “market share is highest” has a negative
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parameter (-0.235) and t-ratio (-3.906) which is significant at 10%; this question has the lowest score in this construct (the mean is 3.52). It indicates that even though the design companies do not have high market share, they still can respond to competition quickly.
Or it could be explained as most design companies in Taiwan are small and medium-sized enterprises, so they can respond to competition quickly. R6 “value added service”
has a positive parameter (0.253) and t-ratio (2.954) which is significant at 5%; this implies that providing the most positive value-added service to customers is helpful to design companies’ overall response to competition. R8 “customers increasingly select us”
has a positive parameter (0.233) and t-ratio (2.484) which is significant at 5%; this implies customers’ preference to a particular design company rather than its competitors improves the company’s overall response to competition. R11 “customer info disseminated” has a positive parameter (0.308) and t-ratio (2.958) which is significant at 5%; this implies dissemination of customer feedback is helpful to the company’s overall response to competition. R12 “understand target markets” has a negative parameter (-0.417) and t-ratio (-3.777) which is significant at 0.1%; the mean of this question is 5.20.
The results implies that despite the fact that the companies have quick response to competition, the managers think they need to make employees understand more about the companies’ target markets. R14 “capitalize on customers’ wants” has a negative parameter (-0.292) and t-ratio (-3.103) which is significant at 5%; this indicates that managers think their organizations have not fully capitalize on customers’ wants. Thus, the managers should fully utilize their staff’s under-utilized knowledge to transfer customers’ needs into company’s profits. R21 “consider info from sector” has a negative parameter (-0.192) and t-ratio (-2.237) which is significant at 5%; this pinpoints despite the fact that the firms already have quick response to competition, the managers still think they did not consider information from sector association as important as they should.
R22 “decisions based on information from sector” has a positive parameter (0.205) and t-ratio (2.489) which is significant at 5%; this implies it is important to consider information from sector associations in the firms’ strategic decisions because it improves the firms’ overall response to competition. R24 “share competitor information” has a negative parameter (-0.271) and t-ratio (-2.486) which is significant at 5%; this implies that in spite of the companies’ quick response to competition, the managers think they did
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not share competitor information in the firms as much as they should. If these companies introduce knowledge management system into the companies, they might improve their weakness in the future. R25 “competitors are sources of innovation” has a positive parameter (0.124) and t-ratio (2.049) which is significant at 5%; this implies considering competitors as a source of innovation ensures the firm’s overall response to competition is enhanced.
The other questions show no statistical significance to overall response to competition.
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Multiple regression results for success rate in new product launches (P9)
In Equation 53, 9 variables show statistical significance to success rate in new product launches. Of those 9 variables, 3 have negative parameters and 6 have positive parameters.
¾ Human capital construct
For the human capital construct, two questions show significance to success rate in new product launches: H4 “employees cooperate in teams” has a positive parameter (0.483) and t-ratio (5.013) which is significant at 0.1%; this implies it takes a lot of teamwork for design company employees to accomplish their tasks, in order to increase the firms’ success rate in new product launches. H8 “employees are bright” has a negative parameter (-0.202) and t-ratio (-1.772) which is significant at 10%; this implies that even though the firms’ success rate in new product launches is satisfying, there is still room for the managers to encourage the staff’s creativity.
¾ Structural capital construct
¾ Structural capital construct