Abstract
| Original language | English |
|---|---|
| Article number | 04019025 |
| Number of pages | 12 |
| Journal | Journal of Infrastructure Systems |
| Volume | 25 |
| Issue number | 3 |
| Early online date | 2 Jul 2019 |
| DOIs | |
| Publication status | Published - Sept 2019 |
| MoE publication type | A1 Journal article-refereed |
Funding
In deterministic models, asset condition is predicted as a precise value on the basis of mathematical functions of observed or measured variables, such as subgrade strength, axle load applications, pavement layer thicknesses and properties, and environmental factors and their interactions (Robinson et al. 1998). In deterministic models, it is typical to present deterioration in the form of a declining curve in which the units are asset value in monetary terms, a technical indicator, or a composite condition index. In probabilistic models, the changing of an asset or asset component to another condition class (getting worse, in deterioration modeling) is based on either heuristic or empirical probabilities. On a chronological scale, subsequent probabilistic events form a Markov chain. Both methods can be used side by side. The choice of model is partly contextual, depending on the available data, the object of application, and the preferences of the analyst. However, if data are available, probabilistic empirical models give more accurate predictions (Sirvio 2017). The OECD manual for measuring capital (OECD 2009) recommends “the use of geometric patterns of depreciation because they tend to be empirically supported, conceptually correct and easy to implement.” In a straight-line depreciation case, the annual depreciation (deterioration) is 1=t, where t is the expected service life. When we assume that the service value of an asset is an accumulated stock of expected benefits that are consumed or depreciated year by year as the asset is being used, we need to deduct the consumed value from the stock. The rate of return of the stock determines the amount of stock to be consumed. The OECD (2009) guidelines refer to “storage of wealth.” This is identical to the concept specified by CPA (2013), that “future economic benefits are synonymous to service potential.” We use a generic model incorporating the following variables. This model was applied to a study initiated by VTT Technical Research Centre of Finland Ltd. and funded by the Finnish Transport Agency (Leviäkangas et al. 2017). The variables are: t = service life of an asset in years; without maintenance the asset will be totally consumed by year t; n= 0; 1; 2; : : : ;t; indicating the year between 0 and final year t; i = selected time value of money; interest rate; the rate refers to the annual rate of return generated by an asset; I0, In = investment made in year 0 and improvements and additional investments in year n; B = total future net benefits, generated by an asset over its entire service life; and SV = service value of an asset (expressed as a percentage 0% :: : 100%).
Keywords
- Accounting
- Asset
- Benefit
- Infrastructure
- Service value
