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Mode effect analysis in the case of daily passenger mobility survey

Author

Listed:
  • Centrih Vasilij

    (Statistical Office of the Republic of Slovenia, Ljubljana, Slovenia)

  • Viršček Andrej

    (Statistical Office of the Republic of Slovenia, Ljubljana, Slovenia)

  • Smukavec Andreja

    (Statistical Office of the Republic of Slovenia, Ljubljana, Slovenia)

  • Bučar Nataša

    (Statistical Office of the Republic of Slovenia, Ljubljana, Slovenia)

  • Arnež Marta

    (Statistical Office of the Republic of Slovenia, Ljubljana, Slovenia)

Abstract

In the autumn 2017, The Statistical Office of the Republic of Slovenia (SURS) has conducted for the first time a survey on daily passenger mobility of Slovenian residents. The key statistics are on persons’ daily traveling habits, such as number of trips, travelled distance, time spent on traveling, and so on. Two independent samples were selected for the simultaneous collection of data by two modes, face-to-face interview (CAPI) and online questionnaire (WEB). The goal of this study is to identify the possible sources of mode measurement errors, with the objective to better design and thus improve the whole data collection process. The detailed mode effect analysis is performed by the comparison of the key statistic estimates and the use of regression models. Usually the measurement mode effect is an issue in surveys on the more sensitive topics or persons’ opinions. This work points out that, first, the mode measurement effect can be an issue also in a more factual survey content, and second, the corresponding statistical data processes can have an important contribution to minimising measurement errors. The results show that WEB respondents are inclined to join two or more trips into one reported, which gives lower estimate of average number of daily trips. The main reason is the demanding questionnaire content. Additionally, the complex data editing process was still insufficient to correct completely for such measurement error. The possible improvements of the data collection process are also discussed.

Suggested Citation

  • Centrih Vasilij & Viršček Andrej & Smukavec Andreja & Bučar Nataša & Arnež Marta, 2020. "Mode effect analysis in the case of daily passenger mobility survey," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(2), pages 43-57, December.
  • Handle: RePEc:vrs:crebss:v:6:y:2020:i:2:p:43-57:n:5
    DOI: 10.2478/crebss-2020-0010
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    References listed on IDEAS

    as
    1. Eckman Stephanie & de Leeuw Edith, 2017. "Editorial – Special Issue on Total Survey Error (TSE)," Journal of Official Statistics, Sciendo, vol. 33(2), pages 301-301, June.
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    3. Caroline Bayart & Patrick Bonnel, 2015. "How to Combine Survey Media (Web, Telephone, Face-to-Face): Lyon and Rhône-alps Case Study," Post-Print halshs-01663683, HAL.
    4. Patrick Bonnel & Caroline Bayart & Brett Smith, 2015. "Workshop Synthesis: Comparing and Combining Survey Modes," Post-Print halshs-01663724, HAL.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    data comparability; mixed mode surveys; mode measurement effect; mode selection effect;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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