**2. Materials and Methods**

The research is carried out by introducing a phase of data acquisition according to face-to-face interviews using a survey format and then processing the data through an AHP methodology. The interviews were conducted through the PAPI method (pen and paper interview-paper questionnaire interview) [57]. In fact, the paper questionnaire interview is the most classic of the survey techniques. The interviews were completed by recording the respondent's answers on a paper questionnaire. Then, the data are entered into a database and analyzed. The database is created in an excel sheet in which the quantitative data have previously been collected in order to be quantified and normalized via equations. The interview approach allows the direct exploration of the perceived sensations through a bottom-up approach. This strategy is also useful to spread a democratic urban planning that can motivate di fferent population groups to cooperate with the local administration [58,59]. The interviews were conducted before the pandemic phase when there were no restrictions on the flow of people moving outdoors. Each interview lasted less than 7 min in order not to cause stress in the interviewed user. The interview involved the acquisition of socio-demographic data and perception of the paths through the evaluation of the LOS (Level of Service) and the definition of the feelings felt in terms of safety, comfort, and confusion. More specifically, the questionnaire that was used consists of three parts and eight questions in total. The first part includes 3 questions concerning the profile of the respondent. Two more questions, which are included in the second part, ask the respondent to show the frequency of use of the road network and his preferences about the four itineraries. The last two questions of the second part request from the respondent to rate the level of service (LOS) of the infrastructure and the possibility to go on walk in the road network. The third part of the questionnaire collects the data that are necessary for the AHP analysis. In this part, the respondent had to compare the four itineraries in pairs using a nine-point scale. This process was accomplished three times in order to collect data concerning the safety, the comfort, and the confusion that the pedestrians feel during the use of the infrastructure. The research steps dealt with in this work are schematically shown in Figure 2.

**Figure 2.** Flow-chart related to the research steps related to the study of the choice of itinerary in the urban area of Rijeka.

A specific questionnaire was defined and administered to citizens and tourists allowing a comparison of the results and providing useful judgments to the Local Administrators for the improvement of the connection routes to the examined areas. The choice of the itinerary is often evaluated through mathematical modeling that correlates different input parameters selected by the user through direct or indirect surveys on one's walking habits. This work aims to describe the selection of the itineraries through the AHP method relating to an area of the city of Rijeka with a high pedestrian flow rate and shows how users can choose one of the proposed itineraries, considering as positive aspects those related to safety and comfort and as negative aspects those related to chaos.

A number of factors can induce and facilitate the creation of a city that can encourage walking. Although each city has its own culture, climate built environment, and social built environment, the fact that the local context and priorities are integrated is also essential; this creates the best walking environment for a city and its people.

### *2.1. Analytical Hierarchy Process (AHP)*

The method that was used for the data analysis of the research is the Analytical Hierarchy Process (AHP). AHP is a Multi-Criteria Analysis (MCA) method, developed by [60]. MCA is a method that is commonly used in the Decision-Making Theory and takes into account all available parameters. It is a complex process that aims to resolve each problem that the surveyor might have. The goal of MCA is the approach of multiple solutions that present the best possible option in the majority of available criteria of the problem [61]. The transparency and mathematical structure of this technique is what establishes it as the most suitable in accomplishing the concept of sustainability by many researchers. Furthermore, its practical value in combination with a user-friendly software increases its attractiveness to practitioners [62]. Through the Analytical Hierarchy Process (AHP), a multicriteria evaluation, it is possible to assign priorities to a series of decision-making alternatives, relating qualitative and quantitative assessments, otherwise not directly comparable, and combining multidimensional scales of measurements in a single priority scale, as in Figure 3.

**Figure 3.** The approach to decision making and different situations [63,64].

AHP has the advantage of quantifying quality data that are collected. At first, it defines some criteria with which it creates pairs of comparisons. The goal of the method is to attribute a weight in each criterion that will define its importance. The higher the weight of a criterion, the more important it is [65]. The attribution of the weight is performed by comparing the criteria in pairs using a scale. There are several scales that can be used that stem from psychological theories [66]. One of the most used scales in AHP is the Saaty scale. It is a nine-point scale where 1 is the minimum value and 9 is the maximum. In between these values, numbers 3, 5, and 7 are used. Number 1 is considered the weight multiplied by the criteria that shows the absolute balance in a comparison pair. It is a scale based mainly on empirical studies [60]. The attribution of a weight to each criterion leads into the final ranking of the criteria. For an AHP to be considered complete, all possible pairings of comparisons must be created so that all criteria can be compared.

Cases with a high number of criteria and therefore a high number of comparative pairs may make the research difficult, thus, some comparative pairs may be excluded. In such cases, it is preferred (suggested) to create the minimum number of comparison pairs required in order to acquire the rest of the comparison pairs from them. The number of comparison pairs results from the formula n (n−1)/2 where n equals to the number of criteria [60]. Finally, the AHP method is able to calculate the possible inconsistency between the survey responses using a specific index called Consistency Index (CI). This index has its lowest value as zero (0). The closer to zero the CI is, the smaller the inconsistency. In particular, if CI/RI < 0.1, where RI stands for Random Index (Consistency Index for Random Entries), the inconsistencies are considered acceptable [60].
