Resultados de análisis de datos históricos

The sample size for this study was small, so it was decided to use Pearson‘s product moment coefficient method (Williams, 1983 and Cohen, 1988) to test the strength of relationships between variables. ―This method provides a better chance of an accurate measure when the sample size is small‖ (Wilbon, 1999, p.164).

Table 5.10 (p.137) summarizes the results of the correlation analyses of: 1) firm characteristics, including company type, company position, employee numbers, products produced, product type, R&D people, performance benchmark, major market and SRG; 2) technology management facets of strategic R&D, technology consciousness, formal planning and external technology acquisition; and 3) technology strategy facets of technology positioning, technology leadership and up-to-date plants and processes.

Following Cohen‘s (1988) approach, the strength of correlations were defined as low for ‗r‘ values between 0.10 and 0.29, moderate for values between 0.30 and 0.49, and high for values above 0.50.

The relationship between the 10 background variables was investigated using the Pearson product-moment correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity and homoscedasticity. There were significant medium positive correlations between the category of product and the type of company (r=0.475, p<0.01), between the category of product and the number of employees (r=0.385, p<0.01) and between the category of product and the products produced (r=0.370, p<0.01).

There was a statistically significant high positive correlation between the capital investment and the number of employees in a company, indicating more capital investment association with larger companies (r=0.796, p<0.01), as expected.

There was a statistically significant high positive correlation between SRG and number of employees (r=0.753, p<0.01) as well as between SRG and capital investment(r=0.729, p<0.01). This indicated that SRG was associated both with the size of the company and its capital investment. This implies that besides TS and TM dimensions, capital investment and the size of a firm also influences company performance and therefore should be used as control variables in further analyses.

There was a statistically significant (r=0.34, p<0.01) moderate positive correlation between strategic R&D and SRG, with more SRG associated with greater emphasis on R&D. There was a positive high and significant correlation between strategic R&D and capital investment (r=0.496, p<0.01), indicating an association between a firm‘s capital investment and its technology management emphasis on R&D.

There was a statistically significant high negative correlation between strategic R&D and the number of people employed in the R&D department (r=-0.786, p<0.01), with lower number of people in the R&D department associated with more emphasis in R&D Management. This result supports the strategic intent of most MNCs, who typically rely on their parent headquarters for R&D; it is a useful outcome of this study.

There was a statistically significant moderate positive correlation between strategic R&D and the number of employees in a company (r=0.425, p<0.01), indicating an association between the size of a company and its emphasis on R&D Management.

There was a statistically significant moderate negative correlation between strategic R&D and the type of company (r=-0.311, p<0.01). This indicates that some type of companies place more emphasis on strategic R&D compared to others, and this could provide an answer to the question as to why the locally owned firms did not engage much in R&D.

There was a statistically significant moderate negative correlation (r=-0.366, p<0.01) between the factor of external technology acquisition and the number of people in the R&D department, indicating greater emphasis on external technology acquisition associated with companies employing fewer people in R&D.

There was a statistically significant moderate positive correlation (r=0.405, p<0.01) between SRG and technology positioning, with more SRG associated with more emphasis on employing strategies to position the technology. There was a statistically significant moderate positive correlation (r=0.370, p<0.01) between technology position strategy and capital investment – an indication there was an association between companies laying more emphasis on technology positioning with those having greater capital investment initiative.

There was a statistically significant moderate positive correlation (r=0.307, p<0.01) between technology position strategy and number of employees in a company thereby indicating an association of companies laying more emphasis on technology positioning with the size of a company. There was a statistically significant moderate negative correlation (r=0.456, p<0.01) between the factor of technology positioning and the number of people in the R&D department, indicating greater emphasis on

technology positioning was associated with companies employing fewer people in R&D.

The relationship between the 10 background variables and the three new TS factors was investigated using the Pearson product-moment correlation coefficient. There was a statistically significant moderate positive correlation between SRG and technology positioning (r=0.326, p<0.01) with more SRG associated with more emphasis on employing strategies to position the technology.

There was a statistically significant moderate positive correlation (r=0.371, p<0.01) between technology position strategy and capital investment, indicating an association between companies with a high emphasis on technology positioning and those with capital investment initiative.

There was a statistically significant moderate positive correlation (r=0.307, p<0.01) between technology position strategy and the number of employees in a company, indicating an association between companies laying more emphasis on technology positioning with the size of company. There was a statistically significant moderate negative correlation (r=-0.456, p<0.01) between the factor of technology positioning and the number of people in the R&D department, indicating more emphasis on technology positioning was associated with companies employing fewer people in R&D.

There was a statistically significant moderate negative correlation (r=-0.404, p<0.01) between technology leadership strategy and the number of people in R&D, with

more emphasis on this strategy associated with R&D departments having fewer people.

There was a statistically significant moderate positive correlation (r=0.326, p<0.01) between up-to-date plants and processes strategy and the position of the respondent in the company, indicating an association on the emphasis on this strategy with the type of executive in the firm.

Strategic R&D had a statistically significant positive moderate correlation with technology consciousness (r=0.409, p<0.01), external technology acquisition (r=0.405, p<0.01) and up-to-date plants and processes (r=0.372, p<0.01), and a high correlation with technology positioning and technology leadership (r=0.579, p<0.01).

This seems to imply that firms focussing on technology leadership and its positioning lay more emphasis on carrying out strategic R&D activities.

Technology consciousness strategy had a statistically significant positive high correlation both with technology position (r=0.743, p<0.01) and up-to-date plants and processes (r=0.551, p<0.01). It had a moderate correlation with technology leadership (r=0.361, p<0.01). This seems to imply that firms who remain aware and vigilant on new technologies are more concerned with positioning themselves in the market, and therefore invest in their plants and processes.

Formal planning strategy had a statistically significant moderate correlation each with technology positioning (r=0.346, p<0.01), technology leadership (r=0.438, p<0.01) and up-to-date plants and processes (r=0.386, p<0.01).

External technology acquisition had a statistically significant moderate positive correlation both with technology positioning (r=0.380, p<0.01), and up-to-date plants and processes (r=0.323, p<0.01). This seems to be a similar result to that for technology consciousness.

Technology positioning had a statistically significant high positive correlation with technology leadership (r=0.547, p<0.01) and up-to-date plants and processes.

(r=0.587, p<0.01)

Source: From analysis of SPSS data of this research

1. ** Correlation is significant at the 0.01 level (2-tailed).

2. * Correlation is significant at the 0.05 level (2-tailed).

3. Alpha coefficients are on diagonal in italics.

5.7.1 Summary of Correlation Analysis

Correlation analysis of the background variables confirmed positive correlations between the category of main product (electrical, electronics, computers etc) with each of the following variables: type of firm (MNC, JV, LO, FO), number of employees and type of the product. This could help provide technology planners with a useful tool for determining which type of firm would best suit a particular product and what the size of the workforce of that firm should be.

The association of SRG with strategic R&D, technology positioning, capital investment and number of employees, and between capital investment and number of employees provides opportunities for further investigation. It had initially been perceived that only technology strategies (TS and TM) would influence SRG;

however, correlation analysis revealed the influence of capital investment and number of employees as well. It was thus decided to conduct regression analysis to determine the direction of these relationships (SRG being the dependent variable, and the two strategy variables as the independent variables), and include capital investment and number of employees as well as the control variables.