Marketing Clues on the Label Raise the Purchase Intention of Genetically Modified Food

Methods to assess ambivalence towards food and diet: a scoping review

BACKGROUND

Ambivalence towards food and diet, which favours behavioural inertia, might be a barrier to adopting healthier eating behaviours. Measuring it can help researchers to better understand its relationship with behaviour change and design interventions aimed at resolving it. In this scoping review, we map and describe methods and tools employed in studies to assess, measure or classify the ambivalence of participants towards food- and diet-related attitude objects.

METHODS

In accordance with Joanna Briggs Institute guidance for conducting scoping reviews, we retrieved peer-reviewed studies from MEDLINE, CINAHL, PsycINFO, Web of Science, FSTA and Food Science Source and preprints from PsyArXiv and MedRxiv. Two independent reviewers screened the articles. We considered for inclusion peer-reviewed studies and preprints that assessed the ambivalence of participants of any age, sex or sociodemographic group towards food and diet.

RESULTS

We included 45 studies published between 1992 and 2022, which included participants from 17 countries. Eighteen methods were employed across the included studies to assess different types of ambivalence (felt, potential or cognitive-affective), the most frequent of which were the Griffin Index, the Subjective Ambivalence Questionnaire, the MouseTracker Paradigm and the Orientation to Chocolate Questionnaire.

CONCLUSION

This scoping review identified several methods and tools to assess different types of ambivalence towards food- and diet-related objects, providing an array of options for future studies.

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

Introduction

The 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).

Method

The 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.

Results

The 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.

Discussion

Based 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.

Analysis of Decisive Elements in the Purchase of Alternative Foods Using Bivariate Probit Model

There has been growing attention among major developed countries to alternative food products using vegetable-derived ingredients to help animal welfare and environmental sustainability. The development of ICT technology and awareness of animal welfare, health, and environmental damage have led to a rise in alternative food products. This study explains consumer selection attributes for alternative foods in categories of intrinsic and extrinsic attributes, storage and usage, ethical consumption, awareness of the environment, and vegetarianism. It also intends to clarify the connection between purchase intentions and purchase preferences caused by selection attributes. The bivariate probit model (BPM) was used to quantitatively analyze consumers’ selection attributes for alternative foods. Element analysis was conducted on twenty-three variables for alternative food selection attributes to derive five elements: quality and safety, environmental awareness, product specifications, ethical consumption, and storage and usage. Analysis indicated that of the five selection attributes, quality and safety and ethical consumption significantly affected vegetarian or semi-vegetarian purchase intentions and preferences. This study intends to identify the elements that affect consumer purchase intentions for alternative foods introduced from an expanding alternative food market, investigate directions for future food development, and provide useful information for consumption promotion strategies.