Effects Of Change Management On Organizational Performance In The Telecomunication Industry
[A CASE STUDY OF MTN NIGERIA]

Table 5 show the age classification of the respondents between the ages 26 to 35 years dominated the sample with 42.9% of the age distribution. This directly implies that the respondents are made of young and capable workforce who are well mature and should be capable of providing objective responses in the study. The table also reveals the distribution of the respondents’ gender by indicating 60.5% of the participants in the study as male and 39.5% as female and by implication the more male than female that took part in the study.
The distribution of the respondents’ qualification is equally dominated by well-educated and enlightened respondents with MSC/MBA Certificates representing 37.1% of the total population, 48.1% respondents had BSc/HND, 11.9% with NCE/diploma Certificates and a negligible 2.9% possess. The implication of the above analysis is that there is high possibility of obtaining objective responses from the respondents due to their high level of maturity and educational experiences. This is justifiable basically due to their age as well as educational status which depicts their relative exposure to the importance of this research study and will enable them appreciate the relevance of the study to their organizational effectiveness and thus made them provide unbiased responses to the questions contained in the questionnaires.

a.    Predictors: (Constant), Technological Change
To assess the extent of impact of Technological Change on organizational performance Simple linear regression analysis was carried out. The result of the regression model shown in table above indicates the value of the correlation coefficient R= .919 and the adjusted R- square = .844 give us some idea of how well our model generalizes and ideally we would like its value to be the same, or close to the value of R-square. In the above summary, the difference for the final model is a fair bit (0.845-0.844=0.001 or 0.1%). This shrinkage means that if the model were derived from the population rather than a sample it would account for approximately 0.1% less variance in the outcome. Thus, the aggregated effect of Technological Change on organizational performance is explained by the value of the R square, which indicates that 84.5% of Organizational performance is accounted specifically by the technological changes.