*4.6. Discussion*

Most of the MaaS literature reported in Section 2 referred to urban areas characterized by high-frequency and multimodal transport services. In this paper, the attention has been shifted from the urban to the extra-urban context characterized by weak transport demand and low-frequency transport services. The main objective of the paper was to propose a pre-test model for a preliminary evaluation of a MaaS system in an extra-urban context.

The proposed pre-test model had general validity in terms of specification and can be used to evaluate choice preference for the introduction of a sustainable MaaS system when an immediate response is required with a limited budget. The experimentation was carried out through a pilot sample and, therefore, can be used in the study area as a pre-test model in the feasibility step for the wider planning process of transport systems.

Considering also that this was a pilot survey and a pre-test model, the results can give some policy indications to decision takers and decision makers in the study area. Decision takers can use the pre-test model and the pilot study for support in the decision to proceed or not with the planning of a MaaS system through more extensive and in-depth studies. Decision makers can use the model and the pilot study for the design of an extended investigation and the calibration and validation of more advanced models in relation to the objectives and goals defined by decision takers.

A sustainable MaaS system cannot be achieved by adopting existing services and integrating them only through an information and communication technology system. A sustainable MaaS system must be planned and designed through the use of quantitative methods and models used in transportation engineering for estimating performances with simulations of user behaviors to achieve sustainable goals.

If it is necessary to evaluate the realization of a transport service that does not exist in a study area and is not present in similar territories, a survey using a large sample that builds detailed transport models can require significant implementation times and costs. The pilot sample and the pre-test model proposed in this paper fit into the preliminary evaluation phase when decision makers and decision takers want to understand if a system can be implemented and what to focus on for subsequent evaluations. The sample size considered in this paper was in the range considered for pre-test and pilot studies ([32,33]).

The model calibrated reproduced quite well the choices declared by users during the survey. In confirmation of what has emerged from other analyses mentioned in the text, bundles were more attractive for users who made journeys characterized by longer journey times and were less so for those who made short journeys. The attractiveness grew with the travel time and decreased with the cost of the package. The additional cost in the present scenarios influenced the preference for bundle cost. Considering the parking cost in a presented scenario (scenario 2), the MaaS preference probability started from higher probability values but increased less quickly.

The results obtained in terms of statistical indicators confirmed that with a pilot sample and the calibration of a pre-test model, preliminary information could be obtained regarding the possible feasibility of a MaaS system and the relevant variables to be further analyzed by means of a wider investigation and the calibration of a more in-depth model.

A pilot sample of users was considered and the following results obtained are to be considered preliminary and referred to the extra-urban context analyzed: the MaaS preference has a high variability, from 20% to 80%, and requires further investigation considering the small sample size; the MaaS preference increases with the travel time of the chosen travel alternative without the presence of the MaaS system; the elasticity is slightly influenced by travel time and is strongly influenced by price; and the MaaS preference is also influenced by a preference of the sample users towards MaaS, not directly linked to travel time and price.

#### **5. Conclusions**

In this paper, a Logit model was proposed for evaluating the preference for MaaS in an extra-urban context with weak demand. The model was specified, calibrated, and validated using a small sample size. The main purpose of the paper was to evaluate the possibility of using a model of this type for the design of a future, more extensive investigation. The model was considered as a pre-test model. The specification had general validity. The attributes to consider in utility had to be selected case by case. Even the calibrated

parameters and the relative numerical results were valid only for the specific case study in a pre-test model phase.

The model was tested in the area of Gioia Tauro in the south of Italy. In the study area, shared mobility services, such as bike sharing and car sharing, were not widely available. This was confirmed during the pilot survey by the interviewees: 76% traveled in their own cars, 38% never used public transport, and only 5% used local public transport every working day. In the survey, three MaaS scenarios (named 1, 2, and 3) each with three subscenarios (named A, B, and C) with increasing frequency of transport services and bundle cost were proposed to users. From the pilot survey, a Logit model was calibrated and validated with the maximum likelihood method considering four specifications for each scenario (I, II, III, and IV). In the first specification, two parameters were calibrated: one referring to time and one referring to cost. In the second specification, the age parameter was also calibrated. In the third specification, the constant parameter was calibrated with respect to the first specification. In the last specification, the label relative to the scenario was calibrated with respect to the third specification. From the first to the fourth specification, the VOT decreased while the ρ<sup>2</sup> increased. Consistent with the class of users surveyed, the fourth specification had better results, but the time parameter was not statistically significant based on a Student's *t*-test at a 95% confidence level.

In the case study, for long-distance journeys without parking payment in the current scenarios and for short-distance journeys, the elasticity was approximately 0.65, with highly variable preference probabilities (MaaS preference between 20% and 80% increasing with travel time). For long-distance journeys with parking payment in the current scenarios the elasticity was approximately 0.15 (MaaS preference around 50% slightly increasing with travel time).

These results indicate that the preference for MaaS grew with the increase in travel time and was strongly influenced by the price of the bundle. From the utility specifications, it can be observed that the inclusion of the 'scenario' variable led to a significant increase in the ρ<sup>2</sup> statistic (from 0.30 to 0.50 in scenario 1, from 0.20 to 0.44 in scenario 2, and from 0.36 to 0.51 in scenario 3). This variable had a positive sign in the calibrations in the case study. It was a label and an indicator of the preferences of sample users toward MaaS, and the variable was not necessarily linked to service-level variables.

The model has limits to be developed in future works. It was based on a pilot sample and, due to the small number of interviews, it was not possible to calibrate a greater number of parameters or other typology of random utility models, which would have allowed us to obtain a greater amount of information relating to MaaS.

The model must be considered as a pre-test model useful for designing a larger sample and a more general preference model. This work should be considered preliminary and could be the basis for building a MaaS preference model and carrying out a larger survey in order to calibrate a greater number of parameters considering the results obtained in this paper. Furthermore, other types of choice models could be specified and tested, as well as considering possible covariance between alternatives.

**Author Contributions:** Conceptualization, A.V.; methodology, A.V.; validation, A.F.; investigation, A.F.; data curation, A.F.; writing A.F. and A.V.; supervision, A.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research is partially supported by DIIES—Università di Reggio Calabria and by the project "La Mobilità per i passeggeri come Servizio–MyPasS", Fondi PON R&I 2014–2020 e FSC, Progetti di Ricerca PNR 2015–2020, codice identificativo ARS01\_01100.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** The survey considered in this paper involved anonymous responses.

**Data Availability Statement:** Data are unavailable due to privacy restrictions.

**Conflicts of Interest:** The authors declare no conflict of interest.
