Factor analysis was used to reduce the original number of items in the survey. The literature review identified several variables which could be used to measure two
dimensions which define strategic technology management. These two dimensions are referred to as technology management (TM) and technology strategy (TS). A thorough analysis of the environment in which the survey was carried out revealed that 32 items could be used to measure these dimensions. According to the respondents to the pilot study, these items were deemed suitable for use in the main questionnaire.
Principal Component Analysis (PCA) was selected for extracting the factors. PCA helped in the evolution of a new set of factors and some new combinations of factors.
The PCA is a data reduction technique that helps identify a structure within data (Dillon & Goldstein, 1984) while retaining the original information as much as possible. In order to determine the appropriateness of the factor analytic framework, a number of methods were employed. These included Bartlett‘s test of sphericity and Kaiser-Meyer-Oslen‘s (KMO) test. The 16 strategy items were factor analysed using the PCA method.
Kaiser‘s criterion with an Eigen value of greater than 1.0 was used to determine the number of factors to be extracted. Since the simplification rather than the minimization of factors was the goal, and since these factors were subsequently to be used in regression analysis which required that they be independent, it was decided to rotate them using Oblimin with Kaiser normalisation (as can be seen in Table 5.8, p.125). The extraction using PCA for the technology strategy variables revealed that three components accounted for 71.3% of the total variance.
Table 5.8: TS items: rotated factor loading
Items Components
1 2 3
1. Pursuing high technical risk 0.644 2. Having reputation for tech.
Innovation
0.852 3. Dominance in key technologies 0.897 4. Importance of advanced 6. Employing pacing technologies 0.803 7. Using state-of-the-art tools 0.861 8. Reducing of product
development time
0.575 9. Increasing no. of products 0.597 10. Continuously improving 13. First in introducing low cost
products
0.790 14. Unique products manufacturing
capability
0.866
15. Low manufacturing cost 0.901
16. Improving production flexibility
0.790
Source: From analysis of SPSS data of this research
Hair, Anderson, Tatham & Black (1992, p.239) suggest that loadings of 0.5 and above can be considered very significant, although loadings of 0.19 and 0.26 (at 5 and 1 percent level of significance) can be significant if the sample size is below 100.
The factor analysis revealed three factor components. The first component had 10 items that reflected technology posture, technology level, and product development intensity of the firm. This amounts to treating technology as a key positioning factor.
This factor was named technology positioning.
The second component had three items that relate to the firm‘s position on leading in the discovery of new technologies and introducing innovative and low cost products at the right time. This factor was named technology leadership.
The third component had three items about manufacturing unique products in reduced times with lower process costs. These could be grouped under the category of the incorporation of new technology into the firm’s plant and facilities. However, this factor was named up-to-date plants and processes.
The extraction using PCA for the technology management variables revealed that four components accounted for 83.2% of the total variance. The rotated factor loadings are presented in Table 5.9 (p.128).
Of the four components which were extracted, the first component had seven variables that reflected aspects such as ‗R&D investment‘, its ‗organization and management‘ and a ‗focus on acquisition of technology within firms‘. Thus, as this
component was about the emphasis placed on R&D and its linkage with other business operations and it was named strategic R&D.
The second component had four variables on ‗technology awareness‘ and one on
‗market driven programs‘; these relate to the emphasis placed on keeping abreast with emerging technologies, and so the component was branded technology consciousness.
The third component had two variables and was about ‗technology and product planning‘, reflecting a firm‘s attitude to using formal processes to plan and select technology; this component was termed formal planning.
The fourth component, which concerns the in-country external acquisition of technology, had only two variables; these related to the acquisition of technology through universities or through other companies in Malaysia. This new element was named as external technology acquisition. As the third and fourth components each had only two variables, there may be a problem with content validity. This is a limitation which is acknowledged, and it is considered later in the study.
Table 5.9: TM items - rotated factor loading
Items Component
1 2 3 4
1. Awareness of existing technologies 0.930
2. Awareness of emerging technologies 0.932
3. Awareness of innovative technologies 0.922
4. Awareness of competing technologies 0.922
5. Technology acquisition-within firms in Malaysia
0.806
6. Technology acquisition-Universities, Labs 0.729
7. Technology acquisition-from outside firms within Malaysia
0.902
8. Market-driven programs 0.556
9. Product-driven programs 0.837
10. Formal planning processes 0.657
11. R&D integrated programs 0.940
12. Researchers empowered 0.956
13. Rewarding R&D success 0.909
14. High R&D investment 0.935
15. Ensuring high return on R&D investment 0.954
16. External R&D funding 0.772
Source: From analysis of SPSS data of this research
These newly conceptualized factors that define the Technology Strategy and Technology Management dimensions appear are somewhat different to those proposed in the original framework and to those developed by Herman (1998). It is this difference that could well be so useful for making comparisons with those developed for the West, and for the development of technology strategies that are conducive to the operating environment. Reliability tests were conducted next so as to determine the robustness of these measures.