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<p>In order to provide useful tools for researchers in the design of actions to promote participation in web surveys, it is key to study the characteristics that define the profile of a “web respondent”, so that specific interventions can be planned. In this contribution, which draws on data collected during the 2019 housing population census in Italy, we define the set of familial and geographical characteristics that correspond to a greater probability that the interviewed household will choose to respond online, by estimating a multilevel model. The profile of a “computer-assisted web interview household” (CAWI-H) is then defined, on the basis of the structural characteristics of this population. Moreover, the geographical distribution of households is studied according to their distance from the CAWI-H profile. The results show that households that are more distant from the CAWI-H profile have characteristics that correspond to segments of the population generally affected by economic and social fragility; they are mainly elderly, foreigners, residents in small towns, and people with a low level of education. It is to these households in particular that survey designers can address specific actions that can enhance their willingness to participate in web surveys.</p>
</abstract>

In order to provide useful tools for researchers in the design of actions to promote participation in web surveys, it is key to study the characteristics that define the profile of a “web respondent”, so that specific interventions can be planned. In this contribution, which draws on data collected during the 2019 housing population census in Italy, we define the set of familial and geographical characteristics that correspond to a greater probability that the interviewed household will choose to respond online, by estimating a multilevel model. The profile of a “computer-assisted web interview household” (CAWI-H) is then defined, on the basis of the structural characteristics of this population. Moreover, the geographical distribution of households is studied according to their distance from the CAWI-H profile. The results show that households that are more distant from the CAWI-H profile have characteristics that correspond to segments of the population generally affected by economic and social fragility; they are mainly elderly, foreigners, residents in small towns, and people with a low level of education. It is to these households in particular that survey designers can address specific actions that can enhance their willingness to participate in web surveys.

Characteristics of Respondents to Web-Based or Traditional Interviews in Mixed-Mode Surveys. Evidence from the Italian Permanent Population Census

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In order to provide useful tools for researchers in the design of actions to promote participation in web surveys, it is key to study the characteristics that...

Characteristics of Respondents to Web-Based or Traditional Interviews in Mixed-Mode Surveys. Evidence from the Italian Permanent Population Census

Online veröffentlicht: 16. März 2023

Seitenbereich: 1 - 26

Eingereicht: 01. März 2021

Akzeptiert: 01. Juli 2022

DOI: https://doi.org/10.2478/jos-2023-0001

Schlüsselwörter
Mixed-mode surveys, respondent profiling, multilevel models, computer assisted web interview (CAWI)

© 2023 Elena Grimaccia et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Characteristics of Respondents to Web-Based or Traditional Interviews in Mixed-Mode Surveys. Evidence from the Italian Permanent Population Census

Online veröffentlicht: 16. März 2023

Seitenbereich: 1 - 26

Eingereicht: 01. März 2021

Akzeptiert: 01. Juli 2022

DOI: https://doi.org/10.2478/jos-2023-0001

SchlüsselwörterMixed-mode surveys, respondent profiling, multilevel models, computer assisted web interview (CAWI)

© 2023 Elena Grimaccia et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Mixed-mode surveys, respondent profiling, multilevel models, computer assisted web interview (CAWI)