Quality of Expenditure Data Collected With a Mobile Receipt Scanning App in a Probability Household Panel
This paper reports on a novel approach using smartphone technology to collect expenditure data in a probability household panel of the general population in Great Britain. Respondents were asked to download an app on their smartphone and report their purchases of goods and services over the period o...
Saved in:
Published in | Survey research methods Vol. 19; no. 2 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
European Survey Research Association
08.08.2025
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | This paper reports on a novel approach using smartphone technology to collect expenditure data in a probability household panel of the general population in Great Britain. Respondents were asked to download an app on their smartphone and report their purchases of goods and services over the period of one month. The app directed respondents to use the built-in camera to photograph all paper receipts that they received at a point of sale. In a separate diary section of the app, they were able to manually enter other expenditures, such as non-receipted payments. In this paper, we compare the quality of the reported expenditure with benchmark data from the Living Costs and Food Survey, the national budget survey in the United Kingdom. The results suggest that total expenditure reported with scanned receipts plus direct entry aligns closely with the national budget survey whereas app data from scanned receipts only clearly underestimate expenditure. Examining category-level expenditure similarly shows that for most categories, the reported expenditure from scanned receipts plus direct entry aligns more closely with the benchmark than scanned receipts only. In addition, the app data align more closely with the national budget survey for respondents who are older, male, have an above-median income, and live in rural areas. The implications of measurement differences vary: comparisons of estimated budget shares are closer to the benchmark for some categories than others. |
---|---|
AbstractList | This paper reports on a novel approach using smartphone technology to collect expenditure data in a probability household panel of the general population in Great Britain. Respondents were asked to download an app on their smartphone and report their purchases of goods and services over the period of one month. The app directed respondents to use the built-in camera to photograph all paper receipts that they received at a point of sale. In a separate diary section of the app, they were able to manually enter other expenditures, such as non-receipted payments. In this paper, we compare the quality of the reported expenditure with benchmark data from the Living Costs and Food Survey, the national budget survey in the United Kingdom. The results suggest that total expenditure reported with scanned receipts plus direct entry aligns closely with the national budget survey whereas app data from scanned receipts only clearly underestimate expenditure. Examining category-level expenditure similarly shows that for most categories, the reported expenditure from scanned receipts plus direct entry aligns more closely with the benchmark than scanned receipts only. In addition, the app data align more closely with the national budget survey for respondents who are older, male, have an above-median income, and live in rural areas. The implications of measurement differences vary: comparisons of estimated budget shares are closer to the benchmark for some categories than others. |
Author | Brendan Read Annette Jäckle Jonathan Burton Mick Couper Alexander Wenz |
Author_xml | – sequence: 1 fullname: Alexander Wenz organization: University of Mannheim, Mannheim Centre for European Social Research – sequence: 2 fullname: Annette Jäckle organization: University of Essex, Institute for Social and Economic Research – sequence: 3 fullname: Jonathan Burton organization: University of Essex, Institute for Social and Economic Research – sequence: 4 fullname: Mick Couper organization: University of Michigan, Institute for Social Research – sequence: 5 fullname: Brendan Read organization: University of Essex, Institute for Social and Economic Research |
BookMark | eNotjNtOAjEURRujiYD-gQ_9AbCXuXQeCaKQYMRbfJyctmegpLSTmWLk78XL00521lpDch5iQEJuOJtwxTN123f7W8FEPvnklRMTxUt1RgZcFdlYyoJfkmHf7xgrCqXYgLjnA3iXjjQ2dP7VYrAuHTqkd5CAzqL3aBJa-uHSlgJ9jNp5pC9o0LWJvhoIwYUNnbYtdeEErLuo4cT8FBfx0OM2ekvXENBfkYsGfI_X_zsi7_fzt9livHp6WM6mq7HlUqWxEbJisjLKlKXgoIuGawnIiiyrdC51ppmAgillwdqSaZFnoE4GslxYVnI5Isu_ro2wq9vO7aE71hFc_XvEblNDl5zxWFsLHGyTg6xUlmNelaiZtAVyoRtRGvkNGcRn_Q |
ContentType | Journal Article |
DBID | DOA |
DOI | 10.18148/srm/2025.v19i2.8178 |
DatabaseName | DOAJ Directory of Open Access Journals |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Statistics |
EISSN | 1864-3361 |
ExternalDocumentID | oai_doaj_org_article_dda1adf5a39845e597eb03d6e12bf27c |
GroupedDBID | 123 2WC 5VS ACHQT ADBBV AFMMW ALMA_UNASSIGNED_HOLDINGS BCNDV E3Z GROUPED_DOAJ KQ8 M~E OK1 OVT P2P TR2 |
ID | FETCH-LOGICAL-d138t-c239039c8c7721ab6f1b3ae06449b53b4b02a6088dadd70b254a8903e052d0713 |
IEDL.DBID | DOA |
IngestDate | Wed Aug 27 01:29:23 EDT 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 2 |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-d138t-c239039c8c7721ab6f1b3ae06449b53b4b02a6088dadd70b254a8903e052d0713 |
OpenAccessLink | https://doaj.org/article/dda1adf5a39845e597eb03d6e12bf27c |
ParticipantIDs | doaj_primary_oai_doaj_org_article_dda1adf5a39845e597eb03d6e12bf27c |
PublicationCentury | 2000 |
PublicationDate | 2025-08-08 |
PublicationDateYYYYMMDD | 2025-08-08 |
PublicationDate_xml | – month: 08 year: 2025 text: 2025-08-08 day: 08 |
PublicationDecade | 2020 |
PublicationTitle | Survey research methods |
PublicationYear | 2025 |
Publisher | European Survey Research Association |
Publisher_xml | – name: European Survey Research Association |
SSID | ssj0066880 |
Score | 2.339576 |
Snippet | This paper reports on a novel approach using smartphone technology to collect expenditure data in a probability household panel of the general population in... |
SourceID | doaj |
SourceType | Open Website |
SubjectTerms | data quality measurement error smartphone app spending data |
Title | Quality of Expenditure Data Collected With a Mobile Receipt Scanning App in a Probability Household Panel |
URI | https://doaj.org/article/dda1adf5a39845e597eb03d6e12bf27c |
Volume | 19 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8NAEF6kp17EJ77Zg9e0u9lssjn6KkWoFLTYW9gnBjSVmAr9984kEXrz4jXkAfNlZ78vM_mGkGsvs6ADC1EICQoU5SKdqTyyWEISwgNrxg_6s6d0ukgel3K5NeoLe8I6e-AucGPnNNcuSC1ylUgP_NcbJlzqeWxCnFnMvrDn_YqpLgenKbyW_Y9yCgj_-Kv-QJkvR988L-OR4jhWbcukv91NJntkt6eB9KZ7_D7Z8dUBGSLz64yTD0nZuVts6CpQ9CPG0vK69vReN5q2ct8CWaSvZfNGNZ2tDCxvCiTQQxKgz7YbRUSBZNKyghPmNSzcthF2Q6eg9j2WnehcV_79iCwmDy9306ifixA5LlQT2VjkTORWWaDGXJs0cCO0B3KR5EYKkxgW6xTSh4PklTEDGlAruMIzGTtUpcdkUK0qf0Iozx0LFmLLvUg008YYVBh5IrMMW0BPyS0GqfjsrC8KNKNuDwBERQ9R8RdEZ_9xk3MyRADb3jt1QQZNvfaXwAcac9VC_wM_K7UR |
linkProvider | Directory of Open Access Journals |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Quality+of+Expenditure+Data+Collected+With+a+Mobile+Receipt+Scanning+App+in+a+Probability+Household+Panel&rft.jtitle=Survey+research+methods&rft.au=Alexander+Wenz&rft.au=Annette+J%C3%A4ckle&rft.au=Jonathan+Burton&rft.au=Mick+Couper&rft.date=2025-08-08&rft.pub=European+Survey+Research+Association&rft.eissn=1864-3361&rft.volume=19&rft.issue=2&rft_id=info:doi/10.18148%2Fsrm%2F2025.v19i2.8178&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_dda1adf5a39845e597eb03d6e12bf27c |