Tailored communication changes consumers’ attitudes and product preferences for genetically modified food

Sleboda, Patrycja; Lagerkvist, Carl Johan

doi:10.1016/j.foodqual.2021.104419

Cited by 12 publications

(7 citation statements)

References 78 publications

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“…These results support preceding literature that suggests CSR is associated with consumer reaction toward GMFs (Pino et al, 2016;Boccia and Covino, 2021;Rabbanee et al, 2021). Prior research on consumer behavior toward GMFs mainly focused on the effects of one or a few rare factors separately Jiang and Zhang, 2021;McKenzie et al, 2021;Rabbanee et al, 2021;Levi, 2022;Sleboda and Lagerkvist, 2022), while in this study, important influential factors were studied together and the analysis of their effects simultaneously to determine priorities. Consequently, we point to consumers' concerns, occupational status, and consumer autonomy as other important aspects of consumer decision-making toward GMFs.…”

Section: Theoretical Implicationsupporting

confidence: 84%

Modeling adoption of genetically modified foods: Application of Rough Set Theory and Flow Network Graph

Akbari¹,

Mahavarpour²,

Moshkdanian³

et al. 2023

Front. Sustain. Food Syst.

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IntroductionThe main purpose of this study is to extract the rules and patterns governing the behavioral intention of consumers towards the adoption of genetically modified foods (GMFs).MethodThe proposed method is a combination of Rough Set Theory (RST) and Flow Network Graph (FNG). Data was collected from 386 consumers to extract rough rules. 13 rules have been chosen from 289 original rules that were divided into three groups: low, medium, and high intention to use GMFs. They were chosen because of the support values and other indexes that were used in the RST. Eventually, to interpret the performance of the generated rules, FNG were illustrated for each decision-making class, and seven patterns were extracted.ResultsThe findings confirm that corporate social responsibilities, consumer concerns, occupational status, and consumer autonomy are more important than other observed dimensions in consumers' decision-making. Moreover, the findings illustrate that combining Rough Set Theory and Flow Network Graph could predict customers' intentions and provide valuable information for policy-makers in related active industries.DiscussionBased on the analysis outcomes, the most significant factors that affect consumers' intention to use GMFs are: “consumer perception of CSR”; “consumer concerns”; “occupational status”; and “consumer autonomy”. Thus, managers and policymakers must pay more attention to these concepts when they survey consumer intention behavior.

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Section: Theoretical Implicationsupporting

confidence: 84%

Modeling adoption of genetically modified foods: Application of Rough Set Theory and Flow Network Graph

Akbari¹,

Mahavarpour²,

Moshkdanian³

et al. 2023

Front. Sustain. Food Syst.

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“…This points to taking a step back in making any specific, targeted recommendations for information dissemination, as was suggested by Sleboda & Lagerkvist. 106 If messaging is created for different GM attributes, information overload may lead to increased confusion over risks, benefits, reasons to support, reasons to support, etc. For example, as new technologies are found to produce that people care about, including plant health and a secure food supply, specific communication about these may improve overall support.…”

Section: Discussionmentioning

confidence: 99%

U.S. consumer support for genetically modified foods: Time trends and assessments of four GM attributes

Kolodinsky,

Rose,

Danielsen

2023

GM Crops & Food

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There is a large literature about consumer acceptance of GM foods dating back almost three decades, but there are fewer studies that investigate how support for specific GM attributes contribute to general support for novel plant technologies. In addition, there is little information on how support has changed over time. Using survey data from 2018 to 2023 in a U.S. State (Vermont) ( n = 3101), we analyze changes in support for a variety of GM attributes over time. There are three major findings. First, there is movement toward neutrality in support for various GM attributes, but opposition continues. Second, there is variability in support for different GM attributes. People are most supportive (least opposed) to GM attributes that improve flora (plant health or drought tolerance), and most opposed (least supportive) of attributes that impact fauna (specifically fish). Third, multivariate regression reveals that assessments of individual GM attributes contribute to levels of overall support of the use of GM technologies in agricultural production.

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“…The presentation of information about the 3D food printing process and its benefits did not increase sensory attribute acceptance or perceived quality for any product, with the exception of the aroma of gummy candy carrots. Previous studies of novel technologies suggest that information must be tailored to the needs of the consumer to generate positive attitude change [ 40 ]. While our study participants indicated they consumed food products similar to the study food they evaluated, the information presented may not have resonated with their needs and interests, i.e., potato Smile ® panel participants were familiar with pureéd foods, they did not consume them.…”

Section: Discussionmentioning

confidence: 99%

Effect of Labelling and Information on Consumer Perception of Foods Presented as 3D Printed

Feng

Khemacheevakul

Siller

et al. 2022

Foods

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Labelling and information have been shown to increase acceptance of novel food technologies. The novel technology of 3 Dimensional Printing (3DP) of foods is not well known among consumers. The study aim was to investigate the effect of the 3DP label and benefits information on consumer acceptance and perception of plausible 3DP foods. Commercially available foods, such as milk chocolate swirls, gummy candy carrots, and baked potato Smiles®, represented 3DP benefits, and each was evaluated in a sensory panel. Participants rated acceptance and perceived quality after each of three product presentations; first labeled “conventional”, then labeled “3D printed”, and again labeled 3D printed after information presentation. Participants indicated product preference after the third presentation. Food Technology Neophobia (FTN), attitude, and previous 3DP knowledge were queried. Quality rating of chocolate swirls and gummy candy carrots increased when labeled as 3DP versus conventional; information did not further increase quality ratings. Participants preferred 3DP chocolate swirls and gummy candy carrots to conventional in the final evaluation. Label and information did not change flavor, texture, or overall acceptance ratings for any product. Attitude towards 3DP of foods increased with lower FTN. Future studies could tailor information to consumer interests and knowledge gaps that highlight relevant benefits of 3DP.

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Tailored communication changes consumers’ attitudes and product preferences for genetically modified food

Cited by 12 publications

References 78 publications

Modeling adoption of genetically modified foods: Application of Rough Set Theory and Flow Network Graph

Modeling adoption of genetically modified foods: Application of Rough Set Theory and Flow Network Graph

U.S. consumer support for genetically modified foods: Time trends and assessments of four GM attributes

Effect of Labelling and Information on Consumer Perception of Foods Presented as 3D Printed

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