SINFONICA – Interviews, Focus Groups and Workshops - Understanding expectations, concerns and desires toward CCAM
Description
General Comments This collection of these datasets is part of the EU project SINFONICA . SINFONICA project aims to develop effective and innovative strategies, methods, and tools to engage users, providers, and stakeholders within the Cooperative, Connected, and Automated Mobility (CCAM) ecosystem. This includes citizens, particularly vulnerable users, transport operators, public administrations, service providers, researchers, and vehicle and technology suppliers. The objective is to systematically gather, understand, and organize their needs, desires, and concerns regarding CCAM. One of the expected results from SINFONICA is to understand, assess, and evaluate the accessibility and inclusiveness of digital transport solutions in European areas and especially of CCAM, but also to identify gaps and unmet needs. The current collection of datasets consists of information gathered through interviews, focus groups and workshops. The interviews and focus groups explored various topics, such as the types of transport modes participants use for different purposes, including traveling to paid work, care work, school, grocery shopping, social activities, sports or leisure activities, and other destinations. Follow-up questions addressed reasons for not using public transport, preferences for shared mobility, and the approximate distance to participants' most frequent destinations. Participants were also asked about their priorities when choosing transportation, whether their needs are met by their regular transport modes, and the limitations they face in their travel due to various factors, including digital issues. They shared recommendations for transport products or services and discussed their access to transport-related apps, their preferences for these apps, and their level of interest and confidence in using technology for mobility purposes. Through the workshops, stakeholders were asked to discuss a critical analysis of present mobility, investigate the potential of CCAM to meet mobility needs, and co-define inclusive and accessible CCAM requirements. For more information about the structure of the questions and the guidelines see D2.2 “Participatory methods to capture mobility needs and future expectations from CCAM process”. The data collection was conducted at four different research sites namely Trikala – Greece, Hamburg – Germany, Noord Brabant – Netherlands and West Midlands – UK.Approximately 300 interviews took place with participants ranging from different types of vulnerabilities like physical and cognitive.Approximately 200 participants during focus groups. Citizens with different ages, citizens with different level of income, citizens living in areas with different access to public transportation.Approximately 200 participants during 12 workshops with different types of stakeholders (Transport operators, Public Administration, etc.)The data were initialy collected in the local languange, in three rounds, and then the local group of Interest had to translate them into English. Interviews First Round of Interviews ElderlyCognitive DisabilitiesDigital Vulnerable PeopleWomen and gender related vulnerabilitiesYoung (18-25)MigrantSingle Parent FamilyRural inhabitantCyclistPhysical DisabilitiesLow IncomeUniversity StudentTotalDateGR535550050205352nd half of 2023NB555555450000392nd half of 2023HH211450005300212nd half of 2023WM551551000550322nd half of 2023 Second Round of Interviews ElderlyCognitive DisabilitiesDigital Vulnerable PeopleWomen and gender related vulnerabilitiesYoung (18-25)MigrantSingle Parent FamilyRural inhabitantCyclistPhysical DisabilitiesLow IncomeUniversity StudentTotalDateGR323330030003201st half of 2024NB333333430000251st half of 2024HH212330007100191st half of 2024WM325320000330211st half of 2024 Third Round of Interviews ElderlyCognitive DisabilitiesDigital Vulnerable PeopleWomen and gender related vulnerabilitiesYoung (18-25)MigrantSingle Parent FamilyRural inhabitantCyclistPhysical DisabilitiesLow IncomeUniversity StudentTotalDateGR222220020002142nd half of 2024NB222222220000162nd half of 2024HH113300001700162nd half of 2024WM222220000210132nd half of 2024 Focus GroupsThis chapter provides a brief description of data collected from focus groups conducted across four groups of interest, with three rounds of focus groups organized for each (see also D2.1 and D.2). The first round focused on citizens of different age groups, including those aged 25–35, 35–45, 45–65, and 66 and older. The second round addressed citizens with varying income levels—low, medium, and high. The third round concentrated on citizens living in areas with different access to public transportation, comparing individuals in urban areas who have easy access to public transport with those in rural areas located far from public transport stops.First Round - Citizens of Different Ages 26-35 years old35-45 years old46-65 years old66+ years oldDateGR66662nd half of 2023HH58382nd half of 2023WM710992nd half of 2023NB47482nd half of 2023Second Round - Citizens with Different Level of Income Low IncomeMedium IncomeHigh IncomeDateGR5551st half of 2024HH9* 2nd half of 2024WM8771st half of 2024NB6881st half of 2024* No information about the income level.Third Round - Citizens living in areas with different access to public transportation People with easy access to public transportPeople living far from public transport stops.DateGR562nd half of 2024HH5122nd half of 2024WM672nd half of 2024NB662nd half of 2024 Workshops From each research site, a set of three rounds of workshops took place, summing up to 12 documents/reports. Each report consisted of textual data in a form of interviews given by stakeholders involved in CCAM ecosystem (ex. Service Providers, Transport Operators, etc.). These reports were summaries of the interviews by the project partners. The reports were translated from the local language to English.Each report consisted of textual data in a form of interviews given by stakeholders involved in CCAM ecosystem (ex. Service Providers, Transport Operators, etc.). The research objectives of the task were to identify and organize each stakeholder’s mentions about recommendations/suggestions along with concerns/barriers Greece- TrikalaGermany - HamburgWest MidlandsBoord BrabantTheme of the Workshop1st WorkshopTime Conducted1st half 20241st half 20241st half 20241st half 2024Critical analysis of the mobility of the present. Identify the most common barriers encountered in daily and/or occasional mobility and jointly imagine protentional solutions, with special focus on technological solutions. N. Participants20231022 2nd WorkshopTime Conducted1st half 20241st half 20242nd half 20241st half 2024Investigation on the CCAM potential to meet mobility needs – discussion about expectations desires and concerns. N. Participants21181016 3rd WorkshopTime Conducted2nd half 20242nd half 20242nd half 20241st half 2024Co-definition of the requirements for an inclusive, equitable and accessible CCAM deployment. Consider the needs of the users, while considering the abilities and constrains that developers, operators and policy makers face. N. Participants25161213 AnonymizationTo ensure compliance with data protection regulations and to uphold ethical research standards, it was necessary to anonymize the dataset. Anonymization protects the privacy and confidentiality of individuals by removing or obfuscating any personally identifiable information (PII) that could be used to trace data back to a specific person. Given that many answers were given in free text, we had to mask words what reveil places, names, home adresses, etc. By anonymizing the dataset, we ensure that individuals cannot be re-identified, thereby reducing the risk of data misuse and enhancing trust in how the data is handled. On the free text answers you will find masked words as follows:[PERSON] --> Person names[ORG] --> Organization names[GPE] --> Geopolitical entities (countries, cities)[LOC] --> General locations (non-political)[FAC] --> Facilities (buildings, airports, highways)[NORP] --> Nationalities, religious, political groups[DATE] --> Dates[AGE] --> Human age[SALARY] --> Salaries, incomes[POSTAL_CODE] --> Postal codes[GPS_COORDINATES] --> GPS coordinates (lat/lon pairs)[DISABILITY] --> Disabilities or impairments (keyword-based) To further anonymize the sociodemographic data and avoid participants to be identifiable, we masked the variables, age, household size, educational level and nationality. More specifically the age, and the household size was agreegated into bins instead of absolute values. The educational level was agreegated to three levels (Primary, Secondary, Tertiary) instead of six. The nationality if wasn't one of the research sites and it assigned the value 'other'.
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Metrics Over Time
Publication Details
Subfield
Sociology and Political Science
Field
Social Sciences
Domain
Social Sciences
Confidence Score
51%
Source
Scholar Data Model