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Data-driven nature of Smart City implies an increasingly urgent need to track and deepen citizens behaviors and patterns, in order to build a coherent knowledge background on current state-of-the-art, as well as to shape realistic modeling of future perspectives and scenarios. Mobility planning in this direction represents a key-challenge due to the highly sensitive kind of data that are required and shared. In this direction, transport research and studies have evolved during time in order to define methodological approaches able to represent and model users’ behavior properly. Similar researches were conducted initially through the direct involvement of users’ through the implementation of surveys and interviews profiling respondents and respective patterns. Subsequently, technology evolution has made mobility tracking more and more an automated process through sensors and mobiles, thus requiring similar surveys to test and fine-tune Big-Data processing. Nowadays, telephone and web interviews still constitute consolidated techniques to deepen revealed and stated mobility intention and preferences of users within targeted initiatives (e.g. pilots and innovative services), nevertheless, representativeness of obtained results seem to waver. Despite statistical stratification of investigated samples, interviews’ results may lead to an overall misrepresentation of the global population, thus questioning the legitimacy of their usage on a large scale. To address similar issues, present contribution focuses on Genoa Smart City Project (IT), investigating potential scenarios leading to the implementation of targeted restrictions to private vehicles’ access to the city center to support sustainable mobility transition, as an interesting case-study to assess potential mismatch between statistical sampling and population representativeness due to the chosen research approach, as well as to face it properly from a methodological point of view. Stemming from the surveys’ first results, wider consideration on potential integrated and mixed approaches will be provided.

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Hide and Track: How Interviews Work for Investigating Users’ Mobility Habits, Genoa Smart City Case-Study

  • 会议论文

  • 发表日期：

    2026年

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  • Valentina Costa,
  • Ilaria Delponte

摘要

Data-driven nature of Smart City implies an increasingly urgent need to track and deepen citizens behaviors and patterns, in order to build a coherent knowledge background on current state-of-the-art, as well as to shape realistic modeling of future perspectives and scenarios. Mobility planning in this direction represents a key-challenge due to the highly sensitive kind of data that are required and shared. In this direction, transport research and studies have evolved during time in order to define methodological approaches able to represent and model users’ behavior properly. Similar researches were conducted initially through the direct involvement of users’ through the implementation of surveys and interviews profiling respondents and respective patterns. Subsequently, technology evolution has made mobility tracking more and more an automated process through sensors and mobiles, thus requiring similar surveys to test and fine-tune Big-Data processing. Nowadays, telephone and web interviews still constitute consolidated techniques to deepen revealed and stated mobility intention and preferences of users within targeted initiatives (e.g. pilots and innovative services), nevertheless, representativeness of obtained results seem to waver. Despite statistical stratification of investigated samples, interviews’ results may lead to an overall misrepresentation of the global population, thus questioning the legitimacy of their usage on a large scale. To address similar issues, present contribution focuses on Genoa Smart City Project (IT), investigating potential scenarios leading to the implementation of targeted restrictions to private vehicles’ access to the city center to support sustainable mobility transition, as an interesting case-study to assess potential mismatch between statistical sampling and population representativeness due to the chosen research approach, as well as to face it properly from a methodological point of view. Stemming from the surveys’ first results, wider consideration on potential integrated and mixed approaches will be provided.