Section 4.5.1). The formula is only applicable to VD relationships that are of the BPR form.
𝑉𝐻𝑇𝑚 𝑉𝐻𝑇ℎ≅ ( 𝑉𝑚 𝑉ℎ) 𝑏+1 (4.9) where
VHTm and VHTh = total VHT for all the network links for scenarios /
alternatives h and m, respectively Vm and Vh = AM-peak volumes (veh/h) for scenarios /
alternatives h and m, respectively
Page | 118 Taking h to be the null alternative, VHTm was then the unknown.
Two different forms of the BPR function were applied in the Visum model to account for different VD relationships on different road classes. A b-value of 8 was ultimately used for road classes 1 and 2, and 6 was used for road classes 3 to 5 (see Chapter 5). For the extrapolation procedure b was equalled to 7.
According to AASHTO (2010) “the technique works best in cases in which most user benefits result from travel-time savings, or other savings that are proportional to such benefits”. Since travel speed, the input to the VOC equation, is related to travel-time, the technique was appropriate to use for the estimation of VOC and total travel-time savings.
Once all the AM-peak benefits were defined, it was assumed that the PM-peak benefits equal to half of these, because a broader PM peak is assumed to be observed due to combined work and shopping return trips, but mainly because the schools end in the middle of the day.
An issue that does arise with this type of extrapolation is how to deal with peak spreading. From the mathematical perspective, there is no limit to the traffic volumes and congestion levels that might be predicted for a link or intersection in a road network. In reality though, trip makers alter their times of travel when the delays on the network become too great. Without taking peak spreading behaviour into account, the results of benefit analyses may be an overestimation of the true benefits that will be realised with the improvement. The issue of peak spreading is addressed again Chapter 6.
In conclusion, the extrapolation procedures discussed in this subsection were applied to all those benefits directly related to changes in the traffic volumes traversing the road network, i.e. benefits relating to VOC, travel time, CO2 emissions and health. As already stated, the other total monetary
benefits were calculated by making use of the CPI inflation rate. These benefits (per scenario and per user group, incl. the authorities) were then added to the total traffic-volume-related benefits to obtain the overall monetary project benefits of the alternative. The qualitative benefits, for which no extrapolation was needed, were given as an extra.
4.8 BICYCLE-SHARING REVENUE ASSESSMENT
The sources of potential revenue for the bicycle-sharing scheme were identified to be:1. annual membership and access fees, and 2. advertising
The proposed annual membership and access fees were calculated from the present travelling expenses of the potential users, and the Matie bike subscription fee. These travelling expenses included VOC, student parking tariffs and the annual membership fee of the Somerset West Bus Fund (for scholars). Market research was undertaken to determine the potential advertising revenue the scheme is able to generate.
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4.9 BICYCLE-SHARING CASH FLOW ANALYSIS
4.9.1 ECONOMIC ANALYSIS VS. FINANCIAL ANALYSIS
There are two different approaches to estimating the net-benefits of a project investment. An economic evaluation assesses public profitability, whilst a financial analysis evaluates private profitability. An economic evaluation was hence undertaken to evaluate the profitability of the theoretical bicycle- sharing scheme to authorities, and a financial analysis determined the profitability of the scheme to the bicycle-share users, remaining road users and society as a whole. To convert a financial cost to an economic cost, a shadow price factor is applied to it. This factor is employed to exclude tax, profit and subsidy from market prices.
The VOC and VOT calculations are financial analyses. Hence, for the evaluation of the benefits to the individual road users and cyclists, the calculated values could be used, but for the general benefits to be reaped by the authorities, a shadow price factor had to be applied. A value of 0.8 was used for this factor. The construction costs of the Drop-and-Go zones and Park-and-Rides are also financial costs even though they exclude VAT. These costs were multiplied by a factor of 0.89 to take them to the economic costs. This is in line with the recommendations given by the Guidelines for Conducting the
Economic Evaluation of Urban Transport Projects(Municipality of Cape Town, 1994). No shadow price factors were applied to the costs of the bicycle-sharing equipment.
4.9.2 SELECTION OF THE ECONOMIC EVALUATION TECHNIQUE
Off-the-shelf economic evaluation packages that aid in the CBA of road projects are available, but a manual calculation was preferred for this research project, as it was easier to account for all the different costs and benefits to the various trip makers and to the authorities. Additionally, the subject of bicycle-sharing deviates quite a lot from the typical road projects evaluated in practice.The economic viability of the theoretical bicycle-sharing scheme for school and university destined commuter traffic in the town of Stellenbosch was determined using three economic evaluation techniques, each with its own performance measure. The techniques were:
1. Net Present Value (NPV) 2. Benefit / Cost Ratio (BCR) 3. First Year Rate of Return
4.9.2.1 NET-PRESENT-VALUE TECHNIQUE
In the NPV technique, the present worth of the investment costs (incl. maintenance and operational costs) is subtracted from the present worth of all the future project benefits. The present worth of the costs and benefits is calculated using the discount rate explained and defined in Section 4.5.2.5.1. The formula for these present worth of costs (PWOC) and benefits (PWOB) are shown in Equations 4.10 and 4.11, respectively. For the null alternative, the first term in Equations 4.10 falls away, because the investment costs of the existing road network are taken as sunk costs. The formula is given as Equation 4.12. 𝑃𝑊𝑂𝐶 = ∑ Ct (1+𝑑)t+ ∑ (𝑀+𝑂+𝑈)t (1+𝑑)t n t=k j t=0 (4.10)
Page | 120 where
PWOC = present worth of costs
t = evaluation period
d = risk-free discount rate
Ct = implementation costs incurred over the period t
(MO + U)t = maintenance, operational and user costs incurred over period t
𝑃𝑊𝑂𝐵 = ∑ 𝐵𝑡
(1+𝑑)𝑡
𝑛
𝑡=𝑘 (4.11)
where
PWOB = present worth of benefits
Bt = benefits reaped over period t
NPV = ∑
Bt (1+𝑑)t− ∑
Ct (1+𝑑)t j t=0+
𝑆𝑡 (1+𝑑)𝑡 n t=k (4.12) whereNPV = net present value of benefits
St = terminal salvage value of the project
All projects reflecting a positive NPV are economically viable; the project alternative with the highest value is the most so.
4.9.2.2 BENEFIT / COST RATIO TECHNIQUE
In the BCR technique, the ratio between the PWOC and PWOB is determined. This ratio makes the economic viability of a proposed project immediately apparent to decision makers. The formula is given as Equation 4.14. A ratio greater than 1 denotes economic viability; the project alternative with the highest ratio is economically the most advantageous. The economic viability of a project or alternative is seen as medium when the BCR lies between 1.5 and 2, and high when it is above 2.
BCR = ∑
Bt (1+𝑑)t/[ ∑
Ct (1+𝑑)t+ ∑
(𝑀+𝑂+𝑈)t (1+𝑑)t − 𝑆𝑡 (1+𝑑)𝑡 n t=k]
j t=0 n t=k (4.13)4.9.2.3 FIRST-YEAR-RATE-OF-RETURN TECHNIQUE
The FYRR technique is the same as the BCR technique, except that only the first-year benefits are evaluated over the total project costs.
4.10 BICYCLE-SHARING SENSITIVITY ANALYSIS
The bicycle-sharing sensitivity analysis has been mentioned a few times in this section. A sensitivity analysis is a way of formally recognising the uncertainty of key factors used in an analysis, such as a CBA, and experimenting with alternative values in the re-calculation of costs and benefits. When a future projection is made with values that comprise a degree of uncertainty, this uncertainty becomes
Page | 121 even greater, and hence it is important for sensitivity analyses to be performed. In general though, if a project is found to be feasible (or infeasible) irrespective of the exact value used for some of the variables, then the analysist can be more confident about his / her methodology and assumptions. The sensitivity analysis described here is different to the scenario analysis portrayed in Section 4.5.2.2 in that the sensitivity analysis is carried out to test the sensitivity of the project findings to changes in the value of those parameters for which there was uncertainty, and the scenario analysis more has to do with the effect different designs have on the outcome. Because a great number of scenarios were already being tested, the bicycle-sharing sensitivity analysis looked only at the effects of the following variables:
1. VOT – VOT = 0.25 × hourly wage (instead of 0.5); and
2. vehicle occupancy – using 1.2 passengers per vehicle instead of 1.5. They both relate to the travel-time cost.
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