Consumer preference attributes for alternative food products

Digital dietary coaches can supplement current approaches for guiding consumers towards healthier behavior. In addition to taking into account the individual client’s health status, digital coaches must also link to her or his personal preferences and habits and to any contextual factors such as location and time of the day. We address the question which food attributes are needed to generate an advice that is fully personalized and situational. In the first part of this study, we have made a systematic analysis of food item attributes and the way in which they are used in making food choices. We distinguish between (1) food attributes as such, (2) consumer attributes (preferences, profile, habits, etc.) and (3) context attributes(time, occasion, situation, etc.). One source for finding attributes is human behavior theory. In addition, we apply a more empirical approach by analyzing attributes that dietitians and food experts use in practice. In the second part of this study we have asked consumers to indicate which food selection criteria they use in practice. We list the sets of attributes and discuss how they can be used to automatically infer preferred food items from personal and situational data. Although fully automatic generation of food alternatives is not yet possible, dietitians and life style coaches can benefit from the data that is already available. A number of web services is currently under development to access the data programmatically, for example in dietary apps.

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Bibliographic Details
Main Authors: Top, Jan, Timmer, Mariëlle, van Rooijen, Lorijn
Format: External research report biblioteca
Language:English
Published: Wageningen Food & Biobased Research
Subjects:Life Science,
Online Access:https://research.wur.nl/en/publications/consumer-preference-attributes-for-alternative-food-products-2
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spelling dig-wur-nl-wurpubs-6113532024-12-03 Top, Jan Timmer, Mariëlle van Rooijen, Lorijn External research report Consumer preference attributes for alternative food products 2023 Digital dietary coaches can supplement current approaches for guiding consumers towards healthier behavior. In addition to taking into account the individual client’s health status, digital coaches must also link to her or his personal preferences and habits and to any contextual factors such as location and time of the day. We address the question which food attributes are needed to generate an advice that is fully personalized and situational. In the first part of this study, we have made a systematic analysis of food item attributes and the way in which they are used in making food choices. We distinguish between (1) food attributes as such, (2) consumer attributes (preferences, profile, habits, etc.) and (3) context attributes(time, occasion, situation, etc.). One source for finding attributes is human behavior theory. In addition, we apply a more empirical approach by analyzing attributes that dietitians and food experts use in practice. In the second part of this study we have asked consumers to indicate which food selection criteria they use in practice. We list the sets of attributes and discuss how they can be used to automatically infer preferred food items from personal and situational data. Although fully automatic generation of food alternatives is not yet possible, dietitians and life style coaches can benefit from the data that is already available. A number of web services is currently under development to access the data programmatically, for example in dietary apps. en Wageningen Food & Biobased Research application/pdf https://research.wur.nl/en/publications/consumer-preference-attributes-for-alternative-food-products-2 10.18174/587331 https://edepot.wur.nl/587331 Life Science (c) publisher Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Life Science
Life Science
spellingShingle Life Science
Life Science
Top, Jan
Timmer, Mariëlle
van Rooijen, Lorijn
Consumer preference attributes for alternative food products
description Digital dietary coaches can supplement current approaches for guiding consumers towards healthier behavior. In addition to taking into account the individual client’s health status, digital coaches must also link to her or his personal preferences and habits and to any contextual factors such as location and time of the day. We address the question which food attributes are needed to generate an advice that is fully personalized and situational. In the first part of this study, we have made a systematic analysis of food item attributes and the way in which they are used in making food choices. We distinguish between (1) food attributes as such, (2) consumer attributes (preferences, profile, habits, etc.) and (3) context attributes(time, occasion, situation, etc.). One source for finding attributes is human behavior theory. In addition, we apply a more empirical approach by analyzing attributes that dietitians and food experts use in practice. In the second part of this study we have asked consumers to indicate which food selection criteria they use in practice. We list the sets of attributes and discuss how they can be used to automatically infer preferred food items from personal and situational data. Although fully automatic generation of food alternatives is not yet possible, dietitians and life style coaches can benefit from the data that is already available. A number of web services is currently under development to access the data programmatically, for example in dietary apps.
format External research report
topic_facet Life Science
author Top, Jan
Timmer, Mariëlle
van Rooijen, Lorijn
author_facet Top, Jan
Timmer, Mariëlle
van Rooijen, Lorijn
author_sort Top, Jan
title Consumer preference attributes for alternative food products
title_short Consumer preference attributes for alternative food products
title_full Consumer preference attributes for alternative food products
title_fullStr Consumer preference attributes for alternative food products
title_full_unstemmed Consumer preference attributes for alternative food products
title_sort consumer preference attributes for alternative food products
publisher Wageningen Food & Biobased Research
url https://research.wur.nl/en/publications/consumer-preference-attributes-for-alternative-food-products-2
work_keys_str_mv AT topjan consumerpreferenceattributesforalternativefoodproducts
AT timmermarielle consumerpreferenceattributesforalternativefoodproducts
AT vanrooijenlorijn consumerpreferenceattributesforalternativefoodproducts
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