Planning and Prioritisation Model

Two models are being proposed for planning and prioritisation of rural roads in Punjab based on the category of the project and type of intervention. These models are developed keeping in view the category of road project typically employed in the Punjab. Since each project type has its own dynamics, the set of indicators relevant for each project type varies accordingly. Similarly, the weightings among the indicators also vary for each model. For instance, an indicator variable that has more importance in the new construction may not be that important for the road considered for rehabilitation and vice versa. Therefore, it is recommended that each model will have its own set of indicators and weightings assigned to each indicator. Mainly, two models are proposed to be developed which are as following. I. Model for construction of new rural roads II. Model for rehabilitation/ improvement of existing rural road

Each model have its own set of indicators and weightings. Indicators are assigned to each model based on its relevance to the type of intervention. Broadly, four indicators i.e. traffic volume, pavement condition, previous work and public transport route are only incorporated in the model for rehabilitation/ improvement of rural roads. These indicators are relevant only in case of intervention on an already existing road and are therefore included in its model.

Weighting of indicators for both models is done using AHP technique explained earlier in the report. AHP (Analytic Hierarchy Process) is an unbiased process, which evaluates the reliability of decision-makers about their judgments, both direct and online survey conducted for this purpose. To check the consistency and reliability of the survey following formula, as given by Saaty (2008) was used CR=CI/RI Where: CR = Consistency Ratio, CI = Consistency Index, RI = Random Index, The random index value depends upon the number of parameters that are compared, the formula for Consistency Index (CI) is as under: CI=(λ-n)/(n- 1) Where: λ = Matrix Eigenvalue, n = Matrix Size, While λ ≥ n and the difference is used to measure the judgment consistency. So, when λ is closer to n, the judgment is more consistent. The value consistency ratio (CR) must be CR ≤ 0.1 (less than 10%), which shows judgment or evaluation consistency. The assigned weights to dimensions and indicators for the “Rehabilitation/ Improvement of Existing Rural Roads” Model and “Construction of New Rural Roads” Model are given as under