A Comparison of Car Sharing Organizational Models: An Analysis of Feasible Efficiency Increase through a Centralized Model 1
Bibliographic record
Abstract
Car sharing seems to have the necessary characteristics to compete in the fulfilment of the gap between mobility offer and demand at international level considering that an offer exclusively based on collective transport systems is not appropriate to satisfy some of the modern transport needs. Nevertheless it is only after the system reaches an economic equilibrium that it will be possible to include car sharing between the new travelling modes provided to the community without aggravating the already exhausted public finances devoted to mobility. In this sense, this work focuses on the organizational model and particularly on its possible efficiency derived from a transition from the current model made of autonomous Local Units to a centralized model. Therefore the main goal of this work is that of evaluating if the centralization of some service costs and a different organizational structure could create cost reduction with the scope of improving the economic equilibrium conditions. This work shows, through a summary of the main international organizational models and an analysis of the Italian case, how the car sharing system can be managed without public contribution (or with contributions devoted only to the start-up phase) and determine an entrepreneurial reality in the case of the development of a centralized organization and avoiding the presence of a plurality of small local operators. It is therefore desirable that the new car sharing operative realities and the already existing ones with a decentralized nature evolve from a fragmented and local organizational phase towards a more mature phase where there a only a few operators or a unique operator in the market. After a review of the main European models of car sharing organization, the attention is placed on the Italian organizational model and particularly on the possible efficiency increase derived from the transition from the current model organized in different Organizational Local Units (one for each city where the service is active) towards a centralized model. The main goal of the study is then to evaluate in which degree the centralization of some service and structure costs and a centralized organizational structure could provide significant cost containments with the scope of improving the economic equilibrium conditions and to allow a development of an alternative mobility system to that of the private vehicles.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".