Project Managers' Teamwork Competencies - Research Paper

Introduction

The three hypotheses are tested by analyzing variables on project managers' teamwork competencies, creativity competencies, delivery of successful innovation (time), delivery of successful innovation (cost), delivery of successful innovation (quality), and project manager innovation environment (resources) to establish relationships. The methodology applied in developing the relationships between the variables is regression analysis. Regression models express dependent variables as functions of predictor or independent variables. The slope of the regression model determines the direction and significance of the association between the variables. In this case, both dependent and independent variables have multiple factors. Thus, the multivariate regression model was developed using SPSS. The model is appropriate since it permits the inclusion of multiple dependent and independent variables.

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Various tests were conducted before developing the model to ensure that the model is reliable and appropriate for the data. They included tests of outliers, descriptive statistics, tests of normality, and factor analysis.

Tests of Outliers

Outliers are observations that are abnormally distant from other values in a population. The test of outliers is vital since outliers distort other statistical tests. Significant or extreme outliers interfere with the tests, thereby leading to inaccurate conclusions about the relationship between variables. Outliers were identified using histograms, box plots, Normal Q-Q plots, and steam-and leaf plots. The graphs indicate that each of the variables had some responses classified as outliers. However, the responses are categorical variables, and there is no evidence of extreme outliers that would interfere with the test results.

Descriptive Statistics

The means for the project manager's teamwork competencies (TM18 to TM23) were between 3.8 and 4, as shown in Appendix 2. This indicates that most of the respondents considered the project manager's teamwork competencies as either moderately important (3) or important (4). The averages of all the responses for the project manager's creativity competencies (CR24 to CR29) were higher than 3 but less than 4. This implies that most respondents considered the factor are moderately important. The averages for the responses of the three delivery successful innovation variables (cost, time, and quality) ranged between 3.6 and 3.9. It indicates that the respondents considered factors such moderately important.

The medians for each of the variables and the component factors were 4. It implies that half of the respondents considered the project manager's competencies and delivery of successful innovation as either critical or very important. The inter-quartile range of each of the variables and their component factors are either 1 or 2. It indicates that a higher percentage of the respondents considered the factors as essential or higher than those who considered them as 'slightly important' or 'not important'.

Assessment of Normality

Normality implies that the variables follow a normal distribution. This test is significant since normality is a precondition for regression analysis. The normality tests for the variables were conducted using the Shapiro-Wilk and Kolmogorov-Smirnov tests. These tests examine the null hypothesis that the sample comes from a normal distribution. As shown in Appendix 3, the significance of the Shapiro-Wilk and Kolmogorov-Smirnov statistics for all the variables used in this analysis are zero. The significance is less than 5%, implying that the null hypothesis stating that the samples come from a normal distribution should be rejected. Thus, it can be inferred that all the variables do not follow a normal distribution.

Reliability Test

Reliability test evaluates the properties of measurement scales and the corresponding components. It determines the reliability of a scale and the relationship between items in the scale. Inter-class correlations help assess the internal reliability of the measurement scale. As shown in Appendix 4, the F-statistic for the model is 10.775 with a significance of 0.00. This indicates that the measurement scales are reliable. The mean inter-item correlations are 0.395, while the minimum inter-item correlation coefficient is 0.147. This suggests that there are significant inter-item correlations between the various measurement classes. The minimum inter-correlation is more than zero, suggesting that none of the inter-item correlations show no correlation.

Factor Analysis

Factor analysis is a technique for data reduction by analyzing complex relationships between variables. It helps in identifying factors or variables that are well represented by the underlying factors. A factor or variable that is well-represented by retained factors should be reduced to improve the accuracy of the regression model. The Kaiser-Meyer-Olkin (KMO) and Bartlett's tests are conducted to determine if it is useful to do factor analysis. As shown in Appendix 5, Kaiser-Meyer-Olkin Measure of Sampling Adequacy is 0.935. The value is close to 1, indicating that a large proportion of the variance in the variables is caused by the underlying factors or components. The Bartlett's test of sphericity tests the null hypothesis that the correlation matrix of the variables and factors is an identity matrix. If the null hypothesis is correct, it indicates that the variables and factors are unrelated; hence, there is no need for factor analysis. The approximate Chi-Square for Bartlett's test of sphericity is 6020.592 with a significance of 0.000. It means that the null hypothesis claiming that the variables and factors are unrelated is not true. Thus, the variables are correlated. The above two tests indicate that the variables are related; hence, a factor analysis would be useful.

Communalities indicate that the proportion of changes in a variable that can be explained by the underlying factors, while the extraction indicates the percentage of the variation explained by retained factors. As shown in Appendix 5, the extraction values of each of the 28 variables are greater than 0.5. This indicates that a significant percentage of the variables can be explained by the retained factors.

Regression

The regression model is used to test each of the three hypotheses. The significance of the coefficient of a variable in the model determines whether it has a significant effect on the response variable or not. The multivariate model incorporates multiple dependent and predictor variables. The

Teamwork Competencies and Successful Delivery of Innovation (Time)

The regression model indicates that most of the coefficients of project manager's teamwork competencies are not statistically significant. Most of the significance values of the coefficients are greater than 0.05. Only TM18 has a significant association with T167 and T171. Only TM21 and TM22 have significant associations with T168, T169 and T170. The results indicate that most of the factors of project managers' teamwork competencies do not have significant influence on the successful delivery of innovation project (time).

Teamwork Competencies and Successful Delivery of Innovation (Cost)

The coefficient...