Purpose
Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches – in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and “big data.”
Design/methodology/approach
Insights and lessons learned about these emerging trends are drawn from recent published articles and relevant scientific conference papers.
Findings
Each new trend has its own timeline in terms of methodological maturity. While mobile technologies for data capture are being rapidly adopted, particularly the use of internet-based surveys conducted on mobile devices, nonprobability sampling methods remain rare in most government research. Resource and quality pressures combined with the intensive research focus on new sampling methods, are, however, making nonprobability sampling a more attractive option. Finally, exploration of “big data” is becoming more common, although there are still many challenges to overcome – methodological, quality and access – before such data are used routinely.
Originality/value
This paper provides a timely review of recent developments in the field of data collection strategies, drawing on numerous current studies and practical applications in the field.
[1]
Robert Santos.
Presidential Address Borne of a Renaissance—A Metamorphosis for Our Future
,
2014
.
[2]
Marika de Bruijne,et al.
Comparing Survey Results Obtained via Mobile Devices and Computers
,
2013
.
[3]
Tom Wells,et al.
Filling the Void: Gaining a Better Understanding of Tablet-based Surveys
,
2013
.
[4]
Mick P. Couper,et al.
Mobile Web Survey Design: Scrolling versus Paging, SMS versus E-mail Invitations
,
2014
.
[5]
Thomas R. Ioerger,et al.
Precision and Disclosure in Text and Voice Interviews on Smartphones
,
2015,
PloS one.
[6]
Jelke Bethlehem,et al.
Selection Bias in Web Surveys
,
2010
.
[7]
D. Lazer,et al.
The Parable of Google Flu: Traps in Big Data Analysis
,
2014,
Science.
[8]
R. Groves.
Nonresponse Rates and Nonresponse Bias in Household Surveys
,
2006
.
[9]
Vesa Virtanen,et al.
Reducing Nonresponse by SMS Reminders in Mail Surveys
,
2007
.
[10]
Mario Callegaro,et al.
Mobile technologies for conducting, augmenting and potentially replacing surveys
,
2014
.
[11]
Michael W. Link,et al.
Life360: Usability of Mobile Devices for Time Use Surveys
,
2010
.