Implementation of outcome-based road maintenance contracts (OPRC) to improve the efficiency of the road sector in Ukraine
Bibliographic record
Abstract
Introduction. Current trends in the development of transport infrastructure show the growing role of effective road management mechanisms that ensure high quality of service while optimising the use of financial resources. The article examines the essence, principles and features of Output and Performance-Based Road Contracts (OPRC), which are an effective alternative to traditional forms of contracting based on payment for the volume of work performed. The author emphasises the key problems of the classical approach to road network maintenance, in particular, the lack of incentives for long-term maintenance of the technical condition of assets, insufficient level of innovation and budget overruns. Problem. The traditional system of road maintenance in Ukraine is based on payment for the volume of work performed, which often leads to inefficient use of budget funds, insufficient incentives for contractors to maintain the long-term quality of road assets, and complicates control over the results. Combined with the deterioration of the network and limited funding, these factors create a need for new approaches to road management. Objective. To investigate the essence, principles and effectiveness of OPRC implementation compared to traditional forms of road maintenance, as well as to summarise the results of the first pilot project of this type in Ukraine, taking into account international experience. Materials and methods. The study uses analytical, comparative and systemic approaches, as well as elements of economic analysis. An overview of international practices of OPRC implementation (Canada, Brazil, Australia, and EU countries) was conducted, as well as an analysis of the national pilot project on the M-06 Kyiv-Chop highway (km 434–621) implemented in 2014-2021. Results. It has been established that the implementation of OPRC provides budgetary savings in the range of (10-40) % compared to traditional approaches, contributes to improving the technical condition of road assets and the level of traffic safety. The results-based management model creates clear incentives for contractors to introduce innovative technologies and effective planning, increases transparency of interaction between the customer and the contractor, and improves the quality of road services for users. Conclusions. Performance-based contracts are an effective tool for modernising Ukraine’s road maintenance system. Their widespread use will contribute to the rational use of funds, increase the durability of road surfaces, enhance private sector participation, and improve road safety. The experience of the pilot project on the M-06 confirms the feasibility of scaling up this practice at the national level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".