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4.2.2. Establish the Effect of Organization Structure Practices on the Performance of KEeRRA The first objective of the study was to assess the influence of organizational structure on the performance of the Kenya Rural Roads Authority. In this regard, practices of the organizational structure were found to have a significant positive influence on the organizational performance of KeRRA (B=0.279, p=0.024) thereby rejecting the null hypothesis Ho1, which states that organization structure does not have a significant influence on the performance of KeRRA. This means that a unit change in organizational structure practices causes a 0.279-unit change in organizational performance and the change is significant. This implies that organizational structure is a significant predictor of firm performance at KeRRA.

Table 2 4.2.2. Establish the Effect of Organization Structure Practices on the Performance of KEeRRA The first objective of the study was to assess the influence of organizational structure on the performance of the Kenya Rural Roads Authority. In this regard, practices of the organizational structure were found to have a significant positive influence on the organizational performance of KeRRA (B=0.279, p=0.024) thereby rejecting the null hypothesis Ho1, which states that organization structure does not have a significant influence on the performance of KeRRA. This means that a unit change in organizational structure practices causes a 0.279-unit change in organizational performance and the change is significant. This implies that organizational structure is a significant predictor of firm performance at KeRRA.

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Keeping in perspective the aforementioned literature and hypotheses, the following conceptual framework is proposed in this study shown in Figure 1. 3. Research Methodology eee EEE OEE ESE SEE ENDED The study employed a correlation research design. The study was conducted in 47 Counties in Kenya. Accordinc to KeRRA’s structure, each county constitutes an administrative region. These are headed by Engineers. Besides the technical department, the regional offices also include supply chain management, Information technology, and accounting departments. This study targeted 47 respondents comprising Engineers (County KeRRA Office Managers) involved in routine road project supervision. Due to a small number of possible study respondents, the study adopted a saturated sampling technique to select the final sample in which a total of 10 respondents were isolated and used for the pilot study as part of a reconnaissance survey. Thereafter, the remaining 37 respondents were targeted for the main study. Cooper and Schindler (2003) provide for a range of 10% subjects, not necessarily statistically selected. The pilot study was essential to pre-test the research instrument to enhance the instrument’s validity and reliability. Primary data was collected using pre-validated questionnaires. The questionnaire has five sections, namely: A, B, C, D, and E, dealing with demographics, organizational structure, resource allocation, environmental uncertainty, and performance respectively. A 5-Likert scale was used to rate staff’s perception of various strategic implementation issues and their contribution to performance.
Keeping in perspective the aforementioned literature and hypotheses, the following conceptual framework is proposed in this study shown in Figure 1. 3. Research Methodology eee EEE OEE ESE SEE ENDED The study employed a correlation research design. The study was conducted in 47 Counties in Kenya. Accordinc to KeRRA’s structure, each county constitutes an administrative region. These are headed by Engineers. Besides the technical department, the regional offices also include supply chain management, Information technology, and accounting departments. This study targeted 47 respondents comprising Engineers (County KeRRA Office Managers) involved in routine road project supervision. Due to a small number of possible study respondents, the study adopted a saturated sampling technique to select the final sample in which a total of 10 respondents were isolated and used for the pilot study as part of a reconnaissance survey. Thereafter, the remaining 37 respondents were targeted for the main study. Cooper and Schindler (2003) provide for a range of 10% subjects, not necessarily statistically selected. The pilot study was essential to pre-test the research instrument to enhance the instrument’s validity and reliability. Primary data was collected using pre-validated questionnaires. The questionnaire has five sections, namely: A, B, C, D, and E, dealing with demographics, organizational structure, resource allocation, environmental uncertainty, and performance respectively. A 5-Likert scale was used to rate staff’s perception of various strategic implementation issues and their contribution to performance.
4.2. Regression Model and Hypothesis Test 4.6.1. ENVECt Of IT alegid IMpiemMentauiONn Factors ON Ui GahiiZatiOnadl Frerlormance To actualize the study objectives, a regression analysis between the three dimensions of strategic implementation factors, namely: Organization structure, resource allocation, environmental uncertainty, and organizational performance was undertaken. The direction and magnitude of influence or effect of each of the dimensions of strategic implementation factors on organizational performance were eventually established using the regression model whose findings were presented in Tables 2, 3, and 4.
4.2. Regression Model and Hypothesis Test 4.6.1. ENVECt Of IT alegid IMpiemMentauiONn Factors ON Ui GahiiZatiOnadl Frerlormance To actualize the study objectives, a regression analysis between the three dimensions of strategic implementation factors, namely: Organization structure, resource allocation, environmental uncertainty, and organizational performance was undertaken. The direction and magnitude of influence or effect of each of the dimensions of strategic implementation factors on organizational performance were eventually established using the regression model whose findings were presented in Tables 2, 3, and 4.
Table 3 shows the ANOVA results of the estimated model. The data test revealed that F (3, 30) = 33.550 at p= 0.000, which is an indication that the model fits the research data well. The researcher can, therefore, deduce that all the independent variables (i.e., organizational structure, resource allocation, and environmental uncertainty) jointly explain organizational performance at KeRRA. Peseta If] taVIGoc, 9, dil +. Table 2 gives the model summary which shows that the proportion of variance in the organizational performance, that is explained by the independent variables, is 77% (RF? = .770, p=0.000). The coefficient of determination (R? = 0.770) and the model are acceptable since the F-statistic is significant and suggests that the independent variables jointly influence the dependent variable. The value of Durbin-Watson is 1.658. Generally, the value of the Durbin-Watson statistic ranges from 0 to 4. As arule of thumb, the residuals are uncorrelated if the Durbin-Watson statistic is approximately 2. A value close to 0 indicates a strong positive correlation, while a value of 4 indicates a strong negative correlation. The computed value is also close to 2, which indicates the absence of serial correlation.
Table 3 shows the ANOVA results of the estimated model. The data test revealed that F (3, 30) = 33.550 at p= 0.000, which is an indication that the model fits the research data well. The researcher can, therefore, deduce that all the independent variables (i.e., organizational structure, resource allocation, and environmental uncertainty) jointly explain organizational performance at KeRRA. Peseta If] taVIGoc, 9, dil +. Table 2 gives the model summary which shows that the proportion of variance in the organizational performance, that is explained by the independent variables, is 77% (RF? = .770, p=0.000). The coefficient of determination (R? = 0.770) and the model are acceptable since the F-statistic is significant and suggests that the independent variables jointly influence the dependent variable. The value of Durbin-Watson is 1.658. Generally, the value of the Durbin-Watson statistic ranges from 0 to 4. As arule of thumb, the residuals are uncorrelated if the Durbin-Watson statistic is approximately 2. A value close to 0 indicates a strong positive correlation, while a value of 4 indicates a strong negative correlation. The computed value is also close to 2, which indicates the absence of serial correlation.
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BusinessStrategy ImplementationContingency Theory
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