Response Times and Subjective Complexity of Food Choices: A Web-Based Experiment Across 3 Countries

Atzori, R; Pellegrini, A; Lombardi, GV; Scarpa, R

Response Times and Subjective Complexity of Food Choices: A Web-Based Experiment Across 3 Countries

Atzori, R Pellegrini, A Lombardi, GV Scarpa, R

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Publisher:: SAGE Publications
Publication Type:: Journal Article
Citation:: Social Science Computer Review, 2023, 41, (4), pp. 1381-1404
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Atzori, R
dc.contributor.author	Pellegrini, A
dc.contributor.author	Lombardi, GV
dc.contributor.author	Scarpa, R
dc.date.accessioned	2024-03-08T05:45:28Z
dc.date.available	2024-03-08T05:45:28Z
dc.date.issued	2023-01-01
dc.identifier.citation	Social Science Computer Review, 2023, 41, (4), pp. 1381-1404
dc.identifier.issn	0894-4393
dc.identifier.issn	1552-8286
dc.identifier.uri	http://hdl.handle.net/10453/176366
dc.description.abstract	Accurate collection of response times is one of the main advantages of web-administered stated choice experiments and it can be thought of as a behavioral indicator of cognitive effort. We use data from a food choice experiment administered across three countries and estimate a panel Mixed Multinomial Logit Model to obtain individual-specific utility weights. These are used to construct two utility-based measures of contextual choice complexity, which are combined with subjective measures of cognitive resources as well as indicators of opt-out selection. We first develop and then test hypothesized effects of complexity at the level of single choice task and choice sequence on response times. By using a log-linear random effects model with choice task response-time as dependent variable, we isolate these effects from other background variables. Results suggest that as our measures of complexity increase, so do response times and such effects are robust across the three countries. We argue that these results broadly support the validity of web-based choice surveys to measure food preference. We suggest that computers can help improve survey design by implementing algorithms to improve the overall efficiency of choice tasks design, for example, by using adaptive design algorithms that control cognitive challenges in accordance with the respondent’s predicted ability to tackle cognitive effort.
dc.language	en
dc.publisher	SAGE Publications
dc.relation	Swiss National Science Foundation187933
dc.relation	Swiss National Science Foundation199276
dc.relation.ispartof	Social Science Computer Review
dc.relation.isbasedon	10.1177/08944393211073585
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0806 Information Systems, 0807 Library and Information Studies, 0899 Other Information and Computing Sciences
dc.subject.classification	General Arts, Humanities & Social Sciences
dc.subject.classification	46 Information and computing sciences
dc.title	Response Times and Subjective Complexity of Food Choices: A Web-Based Experiment Across 3 Countries
dc.type	Journal Article
utslib.citation.volume	41
utslib.for	0806 Information Systems
utslib.for	0807 Library and Information Studies
utslib.for	0899 Other Information and Computing Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Business
pubs.organisational-group	University of Technology Sydney/Faculty of Business/Marketing Discipline
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2024-03-08T05:45:27Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	41
utslib.citation.issue	4

Abstract:

Accurate collection of response times is one of the main advantages of web-administered stated choice experiments and it can be thought of as a behavioral indicator of cognitive effort. We use data from a food choice experiment administered across three countries and estimate a panel Mixed Multinomial Logit Model to obtain individual-specific utility weights. These are used to construct two utility-based measures of contextual choice complexity, which are combined with subjective measures of cognitive resources as well as indicators of opt-out selection. We first develop and then test hypothesized effects of complexity at the level of single choice task and choice sequence on response times. By using a log-linear random effects model with choice task response-time as dependent variable, we isolate these effects from other background variables. Results suggest that as our measures of complexity increase, so do response times and such effects are robust across the three countries. We argue that these results broadly support the validity of web-based choice surveys to measure food preference. We suggest that computers can help improve survey design by implementing algorithms to improve the overall efficiency of choice tasks design, for example, by using adaptive design algorithms that control cognitive challenges in accordance with the respondent’s predicted ability to tackle cognitive effort.

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http://hdl.handle.net/10453/176366