Do Household Attitudes about Food Defense and Food Safety Change Following Highly Visible National Food Recalls?

With a serious food safety situation in China, lots of major food recalls have been initiated. This study examined the key determinants underlying consumers’ protection and behavioral intention in response to major food recalls. An augmented protection motivation theory model (PMT) was developed by incorporating trust in food safety management and food recall concern into the original PMT. Structural equation model analysis was conducted using survey data in China (N = 631). The results showed that perceived knowledge significantly and positively influence protection motivation via its positive influence on the threat appraisal and coping appraisal. Moreover, protection motivation, trust in food safety management (TFSM), and food recall concern (FRC) significantly affect protection behavior intention. It was indicated that the inclusion of TFSM and FRC into the PMT significantly increase the explanatory power of the PMT model. Further analysis of quadratic regression demonstrated that the relationship between perceived knowledge and protection motivation presented an inverted U shape, which indicates the importance of continuous education in developing consumers’ food safety knowledge. Implications for future research are discussed.

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Analysis and Assessment of Food Traceability Status in China

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.396-398.1353 ◽

2011 ◽

Vol 396-398 ◽

pp. 1353-1357 ◽

Cited By ~ 1

Author(s):

Li Mei Liu ◽

Heng Qian ◽

Yong Chao Gao ◽

Ding Wang

Keyword(s):

Food Safety ◽

Food Chains ◽

Support Tool ◽

Food Traceability ◽

The Status ◽

Food Recalls ◽

Further Development

Food traceability is a support tool for preventing and improving food safety problems. The purpose of food traceability is to collect the flow and transformation information of food-related materials in the food chains. When faced with a food safety crisis, we can find the source of the problem and track the flow of products from the information, and effectively carry out food recalls. In this paper, the status of food traceability in China is deeply analyzed from the laws, regulations, standards, traceability techniques and systems construction, and validity of internal and external traceability in food chains is assessed retrospectively. Then some recommendations for the further development of China's food traceability are proposed.

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Combining analysis tools and mathematical modeling to enhance and harmonize food safety and food defense regulatory requirements

International Journal of Food Microbiology ◽

10.1016/j.ijfoodmicro.2010.01.015 ◽

2010 ◽

Vol 139 ◽

pp. S48-S56 ◽

Cited By ~ 21

Author(s):

Robert L. Buchanan ◽

Bernd Appel

Keyword(s):

Mathematical Modeling ◽

Food Safety ◽

Regulatory Requirements ◽

Analysis Tools ◽

Food Defense

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Perceived food safety and food defense responsibility for farmers, transporters, retailers and consumers

British Food Journal ◽

10.1108/bfj-03-2021-0261 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Ronald B. Larson

Keyword(s):

Food Safety ◽

Design Methodology ◽

Food Contamination ◽

Grocery Stores ◽

Multivariate Models ◽

Cost Share ◽

Content Type ◽

Cultural Measures ◽

Contaminated Food ◽

Food Defense

PurposeContaminated food is a major source of illnesses around the world. This research seeks to learn how people assign responsibility for two food contamination risks and how they allocate costs to reduce these risks to four members of the food supply chain. The aims are to identify differences between countries and test options to control for cultural differences.Design/methodology/approachA random sample of online panellists from six countries (N = 6,090) was surveyed on how they assigned responsibility for controlling natural and accidental food contamination (traditional food safety) and for controlling intentional contamination (food defense) to farmers, transporters/distributors, retailer grocery stores/restaurants and consumers. They were also asked how they would allocate food safety and defense costs to the four groups. Differences between countries were tested with dummy variables and cultural measures.FindingsIn nearly every country, respondents assigned the least responsibility and allocated the smallest cost shares to consumers. In multivariate models, responsibility and cost-share results differed, suggesting that preferences varied by country and that respondents did not allocate costs the same way they assessed responsibility. The food safety and defense models also differed, implying that the respondents believed the two sources of contamination represented different risks.Originality/valueThis is the first study to examine how adults allocate the responsibility and costs for food safety and defense to farmers, transporters/distributors, retailer grocery stores/restaurants and consumers. Other research did not differentiate between these two food risks. This study also compared Hofstede's cultural measures with the recently developed Minkov's cultural measures.

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Food Defense – do conceito às atuais exigências do mercado internacional

Research Society and Development ◽

10.33448/rsd-v10i17.24175 ◽

2021 ◽

Vol 10 (17) ◽

pp. e201101724175

Author(s):

Elaine Leão Inácio de Melo Andrade ◽

Gilberto Carvalho de Oliveira ◽

Otniel Freitas Silva

Keyword(s):

Food Security ◽

Food Safety ◽

Drug Administration ◽

Food Quality ◽

Web Of Science ◽

Food And Drug Administration ◽

Food Fraud ◽

Food Defense ◽

Safety Systems

O conceito food defense emergiu nos EUA como resposta aos atentados terroristas do 11 de Setembro, em 2001. A Food and Drug Administration (FDA) e outras agências desenvolveram medidas para proteger a cadeia alimentar do país aos ataques maliciosos. O objetivo consistia em adotar medidas preventivas da contaminação intencional da água e alimentos, onde indivíduos recorrem a agentes (biológicos, químicos ou físicos) com o intuito de causar prejuízos às organizações, governos ou à população. A vulnerabilidade da cadeia alimentar propiciou a difusão deste conceito através de normas certificáveis como: International Featured Standards (IFS), British Retail Consortium (BRC) e Food Safety Systems Certification (FSSC 22000). Este estudo tem como objetivo a emergência do conceito food defense (defesa alimentar), junto aos termos já conhecidos: food quality (qualidade alimentar), food safety (segurança alimentar), food security (acessibilidade alimentar) e food fraud (fraude alimentar), através das regulamentações, leis, metodologias e ferramentas para implementação de food defense nas cadeias de produção e distribuição de alimentos de empresas exportadoras até empresas familiares. Metodologia: análise qualitativa através de pesquisa bibliográfica nas bases Scopus, Web of Science e SciELO. Espera-se que os resultados deste estudo despertem a necessidade de formar profissionais da área de alimentos conhecedores do conceito food defense, e que orientem a adoção de medidas conceituais e práticas que previnam e controlem a contaminação intencional de alimentos, de forma a atender às exigências dos mercados consumidores e às normas e legislações vigentes pertinentes à qualidade e segurança dos alimentos.

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Make It Safe

10.1071/9780643100237 ◽

2010 ◽

Cited By ~ 1

Author(s):

Keyword(s):

Food Safety ◽

Small Businesses ◽

Manufacturing Industry ◽

Small Scale ◽

Safety Hazards ◽

Safety Risks ◽

Food And Beverage ◽

Control Food ◽

Food Recalls ◽

Safety Systems

All people involved with preparation of food for the commercial or retail market need a sound understanding of the food safety risks associated with their specific products and, importantly, how to control these risks. Failure to control food safety hazards can have devastating consequences for not only the consumer, but also the food manufacturer. Make It Safe provides practical guidance on how to control food safety hazards, with a specific focus on controls suitable for small-scale businesses to implement. Small businesses make up around two-thirds of businesses in Australia’s food and beverage manufacturing industry. This book is aimed at those small-scale businesses already in or considering entering food manufacture. Those already operating a small business will develop a better understanding of key food safety systems, while those who are in the ‘start-up’ phase will gain knowledge essential to provide their business with a solid food safety foundation while also learning about Australian food regulations relevant to food safety. The content will also be useful for students studying food technology or hospitality who wish to seek employment in the manufacturing industry or are planning on establishing their own manufacturing operation. Illustrated in full colour throughout, Make It Safe outlines the major food safety hazards – microbial, chemical and physical – which must be controlled when manufacturing all types of food products. The control of microbial hazards is given special emphasis as this is the greatest challenge to food manufacturers. Topics covered include: premises, equipment, staff, product recipes, raw ingredients, preparation, processing, packaging, shelf-life, labelling and food recalls. Key messages are highlighted at the end of each chapter.

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Detecting reports of unsafe foods in consumer product reviews

JAMIA Open ◽

10.1093/jamiaopen/ooz030 ◽

2019 ◽

Vol 2 (3) ◽

pp. 330-338 ◽

Cited By ~ 2

Author(s):

Adyasha Maharana ◽

Kunlin Cai ◽

Joseph Hellerstein ◽

Yulin Hswen ◽

Michael Munsell ◽

...

Keyword(s):

Machine Learning ◽

Food Safety ◽

Food Product ◽

Food Products ◽

Good Health ◽

Consumer Product ◽

Product Reviews ◽

Applied Machine Learning ◽

Under Sampling ◽

Food Recalls

Abstract Objectives Access to safe and nutritious food is essential for good health. However, food can become unsafe due to contamination with pathogens, chemicals or toxins, or mislabeling of allergens. Illness resulting from the consumption of unsafe foods is a global health problem. Here, we develop a machine learning approach for detecting reports of unsafe food products in consumer product reviews from Amazon.com. Materials and Methods We linked Amazon.com food product reviews to Food and Drug Administration (FDA) food recalls from 2012 to 2014 using text matching approaches in a PostGres relational database. We applied machine learning methods and over- and under-sampling methods to the linked data to automate the detection of reports of unsafe food products. Results Our data consisted of 1 297 156 product reviews from Amazon.com. Only 5149 (0.4%) were linked to recalled food products. Bidirectional Encoder Representation from Transformations performed best in identifying unsafe food reviews, achieving an F1 score, precision and recall of 0.74, 0.78, and 0.71, respectively. We also identified synonyms for terms associated with FDA recalls in more than 20 000 reviews, most of which were associated with nonrecalled products. This might suggest that many more products should have been recalled or investigated. Discussion and Conclusion Challenges to improving food safety include, urbanization which has led to a longer food chain, underreporting of illness and difficulty in linking contaminated food to illness. Our approach can improve food safety by enabling early identification of unsafe foods which can lead to timely recall thereby limiting the health and economic impact on the public.

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