# Determination of Factors Influencing Road Transport Demand: Evidence from Croatia
## 5 Discussion and Conclusions
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Factor**} & \multirow{2}{*}{**Description**} & \multicolumn{3}{c}{**Average Annual Rate of Change (N = 13)**} \\ \cline{3-5}  & & **AADT** & **ASDT** & **AODT** \\ \hline Tourist overnight stays (rates of change) & Pearson coefficient & 0.524886 & 0.37686 & 0.449845 \\  & Significance level & 0.0655 & 0.2043 & 0.1230 \\
**Tourist overnight stays (domestic, rates of change)** & Pearson coefficient & 0.803133 & 0.67616 & 0.758028 \\ Tourist overnight stays (foreign, rates of change) & Significance level & 0.0009 & 0.0112 & 0.0027 \\ Tourist overnight stays (foreign, rates of change) & Pearson coefficient & 0.406913 & 0.274315 & 0.330478 \\  & Significance level & 0.1676 & 0.3644 & 0.2701 \\ Population (total) & Pearson coefficient & \(-\)0.01209 & \(-\)0.16602 & 0.016728 \\  & Significance level & 0.9687 & 0.5878 & 0.9567 \\ Population (rates of change) & Pearson coefficient & 0 & \(-\)0.25277 & 0.043634 \\  & Significance level & 1.0000 & 0.4047 & 0.8874 \\ Active population (rates of change) & Pearson coefficient & 0.180969 & \(-\)0.07522 & 0.249195 \\  & Significance level & 0.5541 & 0.8071 & 0.4116 \\
**Number of registered motor vehicles** & Pearson coefficient & 0.787546 & 0.636169 & 0.727551 \\
**(rates of change)** & Significance level & 0.0014 & 0.0194 & 0.0048 \\
**Number of registered passenger cars** & Pearson coefficient & 0.811358 & 0.689157 & 0.745957 \\
**(rates of change)** & Significance level & 0.0008 & 0.0092 & 0.0034 \\
**Road transport of goods (rates of change)** & Pearson coefficient & 0.740768 & 0.512293 & 0.69087 \\  & Significance level & 0.0038 & 0.0735 & 0.0089 \\ Rail transport of goods (rates of change) & Pearson coefficient & \(-\)0.14779 & \(-\)0.0891 & \(-\)0.21274 \\  & Significance level & 0.6299 & 0.7722 & 0.4853 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._common cause was of a political-economic nature. Specifically, political pressure and misrepresented strategic project displays, such as unjustified increases in expected project benefits, often lead to poor-quality forecasts. Special attention is given to political-economic causes in public-private partnership projects. Based on the findings of this research, similar causes of forecasting errors in road transport demand can be assumed for the Republic of Croatia, as well as a lack of expert control over traffic projects containing forecasts. According to the analysis of available projects, it can be concluded that forecasting is not used as a key factor in the decision-making process regarding the efficiency and necessity of individual transport projects. Instead, it is often treated as a formal part of the documentation or used to present a project as more significant for society than it actually is. Despite the undeniable fact about the necessity and importance of forecasting in road transport, as well as the low accuracy of existing forecasting models, no exact models have been established for evaluating the quality of road transport demand forecasts. In fact, one of the main reasons for the ease of manipulating forecasts (whether caused by the optimism of planners or political-economic factors) arises from the difficulty in evaluating the quality of forecast results. Accordingly, the research in this paper focuses on determining the relationships between the annual rates of change in road transport demand intensity and economic, demographic, as well as traffic and transport indicators. In this way, it is possible to analyze economic, demographic, as well as traffic and transport trends through the forecast result and, consequently, more easily conclude the likelihood of a specific outcome, i.e., the quality of the forecast. One of the key findings of this research is the identification of factors that exhibit percentage changes similar to AADT, as well as those that demonstrate opposite trends.