Skip to main content
SpringerLink
Log in

Web Surveys: Profiles of Respondents to the Italian Population Census

  • Conference paper
  • First Online:
Studies in Theoretical and Applied Statistics (SIS 2021)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 406))

Included in the following conference series:

Abstract

Identifying the profile of the “web respondent” can help survey designers to promote the participation in web-based surveys, with the aim of enhancing timeliness and reducing costs of data collection. This study reports results from a mode comparison, between a Computer Assisted Web Interview and a Computer Assisted Personal Interview. The aims are to assess the familial and geographical characteristics corresponding to a greater probability of choosing to respond to a web survey, and to identify the web respondents’ profile. Logit models with different specifications have been estimated on the probability of answering via web, based on the 2019 Italian population census data. Regional fixed effects, geographical covariates referring to the municipalities, and interactions were all included in the model to control for the variability of the territories. Results show that the households with a lower level of education, composed by foreigner members, residing in the South of Italy, or in small municipalities, present a lower probability of answering to a web survey, and can be made subject of specific actions in order to increase the share of web respondents.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Antoun, C., Couper, M.P., Conrad, F.G.: Effects of mobile versus PC web on survey response quality: a crossover experiment in a probability web panel. Public Opin. Q. 81, 280–306 (2017)

    Article  Google Scholar 

  2. Benassi, F., Naccarato, A.: HHs in potential economic distress. A geographically weighted regression model for Italy, 2001–2011. Spat. Stat. 21, 362–376 (2017)

    Google Scholar 

  3. Bethlehem, I., Cobben, F., Schouten, B.: Handbook of Nonresponse in HH Surveys. Wiley, New Jersey, USA (2011)

    Book  Google Scholar 

  4. Bianchi, A., Biffignandi, S., Lynn, P.: Web-face-to-face mixed-mode design in a longitudinal survey: effects on participation rate, sample composition, and costs. J. Official Stat. 33(2), 385–408 (2017)

    Article  Google Scholar 

  5. Biffignandi, S., Pratesi, M.: Modelling the respondents’ profile in a web survey on firms in Italy. In: Ferligoj, A., Mrvar, A. (eds.) Development in Social Science Methodology. FDV, Metodoloski zvezki, Ljubljana (2002)

    Google Scholar 

  6. Blom, A.G., Bosnjak, M., Das, S., Cornilleau, A., Cousteaux, A., Douhou, S., Krieger, U.: A comparison of four probability-based online and mixed-mode panels in Europe. Soc. Sci. Comput. Rev. 1–18 (2015)

    Google Scholar 

  7. Calinescu, M., Schouten, B.: Adaptive survey designs to minimize survey mode effects—a case study on the Dutch Labor Force Survey. Surv. Methodol. 41(2), 403–425 (2015)

    Google Scholar 

  8. Cellini, R., Torrisi, G.: Regional resilience in Italy: a very long-run analysis. Reg. Stud. 48(11), 1779–1796 (2014)

    Article  Google Scholar 

  9. Chieppa, A., Gallo, G., Tomeo, V., Borrelli, F., di Domenico, S.: Knowledge discovery for inferring the usually resident population from administrative registers. Math. Popul. Stud. 26(2), 96–102 (2018)

    MathSciNet  Google Scholar 

  10. Citro, C.F.: From multiple modes for surveys to multiple data sources for estimates. Surv. Methodol. 40(2), 137–161 (2014)

    Google Scholar 

  11. Cobben, F., Bethlehem, J.G.: Web panels for official statistics, Discussion paper 201307. Statistics, The Hague, The Netherlands (2013)

    Google Scholar 

  12. Cracolici, M.F., Cuffaro, M., Nijkamp, P.: Geographical distribution of unemployment: an analysis of provincial differences in Italy. Growth Chang. 38(4), 649–670 (2007)

    Article  Google Scholar 

  13. Crescenzi, F., Sindoni, G.: The combined use of multiple data sources in the population census. In: Proceedings of the UNECE Group of Experts on Population and Housing Censuses, 30 September–2 October 2015, Geneva (2015)

    Google Scholar 

  14. D’Alò, M., Falorsi, S., Fasulo, A., Solari, F.: Sample design for the integration of population census and social surveys. In: Petrucci, A., Racioppi, F., Verde, R. (eds.) New Statistical Developments in Data Science. SIS 2017, Florence, Italy, June 28–30, pp. 191–202. Springer International Publishing, Switzerland (2019)

    Google Scholar 

  15. Durrant, G.B., Steele, F.: Multilevel modelling of refusal and non‐contact in HH surveys: evidence from six UK government surveys. J. R. Stat. Soc. Ser. A—Stat. Soc. 361–381 (2009)

    Google Scholar 

  16. Espinosa, J., Hennig, C.: A constrained regression model for an ordinal response with ordinal predictors. Stat. Comput. 29, 869–890 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  17. European Union: Regulation of the European Parliament as Regards the Territorial Typologies 2017/2391. Official Journal of the European Union (2017)

    Google Scholar 

  18. Eurostat: Digital Economy and Society Statistics—HHs and Individuals. Luxemburg (2020). https://ec.europa.eu/eurostat/statistics-explained/index.php/Digital_economy_and_society_statistics_-_HHs_and_individuals

  19. Eurostat: Applying the Degree of Urbanisation. A Methodological Manual to Define Cities, Towns and Rural Areas for International Comparisons, 2021 edn. Luxemburg, Eurostat (2021)

    Google Scholar 

  20. Gallo, G., Paluzzi, E.: I censimenti nell’Italia unita. Le fonti di stato della popolazione tra il XIX e il XXI secolo. In: “I censimenti fra passato, presente e futuro” Torino, 4–6 dicembre 2010, ANNALI DI STATISTICA ANNO 141—SERIE XII—VOL. 2, ISTAT (2012)

    Google Scholar 

  21. Hargittai, E.: Second-level digital divide: differences in people’s online skills. First Monday 7(4) (2002)

    Google Scholar 

  22. ISTAT: Preliminary experimental results on the Italian population and housing census estimation methods. In: Proceedings of the Twentieth Conference of European Statisticians Group of Experts on Population and Housing Censuses, 26–28 September, 2018. United Nations Economic Commission for Europe, Geneva (2018)

    Google Scholar 

  23. ISTAT: Nota tecnica sulla produzione dei dati del Censimento Permanente: la stima della popolazione residente per sesso, età, cittadinanza, grado di istruzione e condizione professionale per gli anni 2018 e 2019 (2020)

    Google Scholar 

  24. Jensen, P.: Towards a register based statistical system—some Danish experience. Stat. J. 1(3), 341–365 (1983)

    Google Scholar 

  25. de Leeuw, E.D.: Mixed mode: past, present, and future. Surv. Res. Methods 12(2), 75–89 (2018)

    Google Scholar 

  26. de Leeuw, E.D., Suzer-Gurtekin, Z.T., Hox, J.J.: The design and implementation of mixed-mode surveys. In: Johnson, P., Pennell, B.E., Stoop, I.A.L., Dorer, B. (eds.) Advances in Comparative Survey Methods: Multinational, Multiregional, and Multicultural contexts (3MC), pp. 387–408. Wiley, New York (2019)

    Google Scholar 

  27. Maslovskaya, O., Durrant, G.B., Smith, P.W.F., Hanson, T., Villar, A.: What are the characteristics of respondents using different devices in mixed-device online surveys? Evidence from six UK surveys. Int. Stat. Rev. 87(2), 326–346 (2019)

    Article  Google Scholar 

  28. Pratesi, M., Lozar Manfreda, K., Biffignandi, S., Vehovar, V.: List-based web surveys: quality, timeliness and nonresponse in the steps of the participation flow. J. Official Stat. (2004)

    Google Scholar 

  29. Rivero, M.S., Rangel, M.C.R., Martín, J.M.S.: Geotourist profile identification using binary logit modeling: application to the Villuercas-Ibores-Jara Geopark (Spain). Geoheritage 11, 1399–1412 (2019)

    Article  Google Scholar 

  30. UNECE (United Nations Economic Commission for Europe): Population definitions at the 2010 censuses round in the countries of the UNECE region. Paper presented to the Fifteenth Meeting of Group of Experts on Population and Housing Censuses. Geneva, 30 September–3 October 2013 (2013)

    Google Scholar 

  31. UNECE (United Nations Economic Commission for Europe): Guidelines on the Use of Registers and Administrative Data for Population and Housing Censuses. ECE/CES/STAT/2018/4. United Nations, New York, UNECE (2018)

    Google Scholar 

  32. UNSD (United Nations Statistical Division): Guidelines on the Use of Electronic Data Collection Technologies in Population and Housing Censuses. United Nations, New York (2019)

    Google Scholar 

  33. Wooldridge, J.M.: Introductory Econometrics: A Modern Approach, 5th edn. Cengage Learning, Boston (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. ISTAT - Istituto Nazionale di Statistica, Via Cesare Balbo, 16, 00184, Rome, Italy

    Elena Grimaccia & Gerardo Gallo

  2. Department of Economics, Roma Tre University, Rome, Italy

    Alessia Naccarato

Authors
  1. Elena Grimaccia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alessia Naccarato
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gerardo Gallo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elena Grimaccia .

Editor information

Editors and Affiliations

  1. Department of Economics and Management, University of Pisa, Pisa, Italy

    Nicola Salvati

  2. Department of Economics and Statistics, University of Salerno, Fisciano, Salerno, Italy

    Cira Perna

  3. Department of Economics and Management, University of Pisa, Pisa, Italy

    Stefano Marchetti

  4. School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW, Australia

    Raymond Chambers

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Grimaccia, E., Naccarato, A., Gallo, G. (2022). Web Surveys: Profiles of Respondents to the Italian Population Census. In: Salvati, N., Perna, C., Marchetti, S., Chambers, R. (eds) Studies in Theoretical and Applied Statistics . SIS 2021. Springer Proceedings in Mathematics & Statistics, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-031-16609-9_32

Download citation

Publish with us

Policies and ethics

Search

Navigation