*3.3. Ordinal Logistic Regression Model Estimation Result*

Ordinal logistic regression model was used to predict the relationship between the ordinal outcome and independent variables towards urban cadastral system level of excellence. From Table 5, it can be noted that policy and strategy, leadership, resource and partnership, process, and customer result are variables which are not statistically significant (*p* values > 0.05).

**Table 5.** Coefficients that estimates the influence of independent variables on the dependent.


Based on this evidence, we retain the null hypothesis and reject the alternative hypothesis. To interpret the result, cadastral system policy and strategy, quality of leadership, provided resource and partnership, existing process to deliver services, and the satisfaction result of the customer have no significant effect on the organizational achievements. This does not mean that those variables do not affect, rather they affect the performance of the cadastral organization with less significance. For instance, the quality of cadastral policy and strategy affects the organization with 0.354 amounts. When the independent variable (policy and strategy) increases with 1 unit, the dependent variable (organizational result) will increase with 0.354 amounts.

On the other hand, People, People Result, and Societal Result are statistically significant (*p* values < 0.05), which in this case reject the null hypothesis and accept the alternative hypothesis. Based on significance values (*p* values), People, People Result, and Societal Result have a significant effect on the success of the organizational achievements.

Table 6 provides the results of the ordinal logistic regression model. According to the results, all thresholds are statistically significant at the significance level of 0.05.


**Table 6.** Estimated coefficients, assigned weights, and mean response rate.

The column of Calculated Coefficients or Estimates (β) provides the values for β<sup>1</sup> to β*<sup>n</sup>* for this equation; the column Assigned Weight (taken from the EFQM excellence model) presents the weights for the respective independent variables, and the column Mean (X) Values presents the average values for all respondents in each variable. Expressed in terms of the variables used in this table, the regression equation for the overall performance of the organization is calculated based on Equation (1).

*Cadastral system achievement* (*Y*) = (0.354 ∗ 1 ∗ 3.12) + (0.489 ∗ 0.8 ∗ 3.25) + (1.120& ∗ 0.9 ∗ 2.97) + (0.508 ∗ 0.9& ∗ 3.95) +(0.540 ∗ 1.4 ∗ 3.97) + (1.724 ∗ 0.9 ∗ 3.37) + (1.657 ∗ 2.0 ∗ 2.65) +(0.281 ∗ 0.6 ∗ 3.41) = 24.916 (2)
