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Modelling final outcome and length of call sequence to improve efficiency in interviewer call scheduling

Modelling final outcome and length of call sequence to improve efficiency in interviewer call scheduling
Modelling final outcome and length of call sequence to improve efficiency in interviewer call scheduling
Survey practitioners are increasingly interested in how best to use paradata to improve data collection processes. One particular question is if it is possible to identify early on during fieldwork sample cases that may require a long time, and therefore a lot of financial and staff resources, until interviewing is completed. More specifically, we aim to identify cases with long unsuccessful call sequences. This paper models call record data predicting final call outcome and length of a call sequence. Separate binary and joint multinomial logistic models for the two outcomes are presented, accounting for the clustering of households within interviewers. Of particular interest is to identify explanatory variables that predict final outcome and length of a call sequence. The study uses data from Understanding Society, a large-scale UK longitudinal survey. The work has implications for responsive and adaptive survey designs. The results indicate that modelling outcome and length of a call sequence jointly improves the fit of the model. Outcomes of previous calls, in particular from the most recent call, are highly predictive. The timing of calls and interviewer observation variables, although significant in the models, only slightly improve the predictive power.
2325-0984
397-424
Durrant, Gabriele
14fcc787-2666-46f2-a097-e4b98a210610
Maslovskaya, Olga
9c979052-e9d7-4400-a657-38f1f9cd74d0
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Durrant, Gabriele
14fcc787-2666-46f2-a097-e4b98a210610
Maslovskaya, Olga
9c979052-e9d7-4400-a657-38f1f9cd74d0
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940

Durrant, Gabriele, Maslovskaya, Olga and Smith, Peter W.F. (2015) Modelling final outcome and length of call sequence to improve efficiency in interviewer call scheduling. Journal of Survey Statistics and Methodology, 3 (3), 397-424. (doi:10.1093/jssam/smv008).

Record type: Article

Abstract

Survey practitioners are increasingly interested in how best to use paradata to improve data collection processes. One particular question is if it is possible to identify early on during fieldwork sample cases that may require a long time, and therefore a lot of financial and staff resources, until interviewing is completed. More specifically, we aim to identify cases with long unsuccessful call sequences. This paper models call record data predicting final call outcome and length of a call sequence. Separate binary and joint multinomial logistic models for the two outcomes are presented, accounting for the clustering of households within interviewers. Of particular interest is to identify explanatory variables that predict final outcome and length of a call sequence. The study uses data from Understanding Society, a large-scale UK longitudinal survey. The work has implications for responsive and adaptive survey designs. The results indicate that modelling outcome and length of a call sequence jointly improves the fit of the model. Outcomes of previous calls, in particular from the most recent call, are highly predictive. The timing of calls and interviewer observation variables, although significant in the models, only slightly improve the predictive power.

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Durrant et al_Paper modelling length and outcome_for eprints.pdf - Author's Original
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Durrant%20et%20al.%202015%20JSSAM_modelling%20length%20and%20outcome_final.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 17 March 2015
e-pub ahead of print date: 3 July 2015
Published date: September 2015
Organisations: Social Statistics & Demography, Social Sciences

Identifiers

Local EPrints ID: 375803
URI: http://eprints.soton.ac.uk/id/eprint/375803
ISSN: 2325-0984
PURE UUID: f6743ad4-e6de-4b92-801b-e5cd1408216c
ORCID for Gabriele Durrant: ORCID iD orcid.org/0009-0001-3436-1512
ORCID for Olga Maslovskaya: ORCID iD orcid.org/0000-0003-3814-810X
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

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Date deposited: 15 Apr 2015 14:20
Last modified: 18 May 2024 01:40

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