A meta-analytic review of food safety risk perception

Journal Pre-proof A Meta-Analytic Review Of Food Safety Risk Perception

Vinicius A.M. Nardi, Rafael Teixeira, Wagner Junior Ladeira, Fernando de Oliveira Santini PII:

S0956-7135(20)30005-0

DOI:

https://doi.org/10.1016/j.foodcont.2020.107089

Reference:

JFCO 107089

To appear in:

Food Control

Received Date:

14 September 2019

Accepted Date:

03 January 2020

Please cite this article as: Vinicius A.M. Nardi, Rafael Teixeira, Wagner Junior Ladeira, Fernando de Oliveira Santini, A Meta-Analytic Review Of Food Safety Risk Perception, Food Control (2020), https://doi.org/10.1016/j.foodcont.2020.107089

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Journal Pre-proof 1

A META-ANALYTIC REVIEW OF FOOD SAFETY RISK PERCEPTION First author Vinicius A.M. Nardi a, 1 Second author – Corresponding author Rafael Teixeira b, 1, * Third author Wagner Junior Ladeira c Fourth author Fernando de Oliveira Santini c a

Embrapa , Rua 13 de Maio, 1130 - Bento Gonçalves, RS, 95702-002, Brazil - Email: [email protected] b

Department of Supply Chain and Information Management, School of Business, College of Charleston, 5 Liberty St., Suite 300, Charleston, SC 29424, United States of America - * Email: [email protected] c

Graduate Program of Management, Unisinos Business School, Universidade do Vale do Rio dos Sinos, Av. Dr. Nilo Peçanha, 1600, Porto Alegre, RS 91.330-002, Brazil - Email: [email protected] Email: [email protected] 1 These

authors contributed to the work equally and should be regarded as co-first authors.

This manuscript has not been published and is not under consideration for publication elsewhere. Declarations of interest: none

Journal Pre-proof 1 A META-ANALYTIC REVIEW OF FOOD SAFETY RISK PERCEPTION

ABSTRACT Studies investigating food safety risk perception (FSRP) have substantially increased in recent years, particularly because of recent cases of food contamination. Most studies analysed the effects of FSRP antecedents and their consequences but reported heterogeneous effects. To consolidate these results and provide a more robust and parsimonious picture of FSRP, we conducted a meta-analysis of 128 empirical studies that investigated the key drivers and outcomes of FRSP and potential moderator variables. Our findings reveal the key drivers (trust, knowledge, subjective characteristics, and socio-demographic characteristics) of FSRP and a robust negative consequent effect on the willingness to buy (WTB). Also, we reveal the moderation role of the food origin, risk type, healthiness, shelf life and pleasure in the consequent effect. Our results contribute to the growing literature related to FSRP by consolidating previous results and help establish a foundation for further advancement in this topic. More importantly, our findings provide a more comprehensive picture of the FSRP phenomenon to help in the design of guidelines and rules that shape supplier behaviour to enhance food safety along the food supply chain.

KEYWORDS: food safety, food safety risk perception, willingness to buy, antecedents, meta-analysis

Journal Pre-proof 2 1 INTRODUCTION Food safety risk, defined as the presence of physical, chemical or biological contaminants that are unexpected or unidentified on the product label, is a central issue for global food chains. Recent cases of food contamination, such as adulterated milk (Chen et al., 2014) and melamine in infant formula in China (Gossner et al., 2009; Yang et al., 2009) and the Escherichia coli contamination at Chipotle Mexican Grill restaurants in the United States (2015), have captured the attention of managers and researchers, resulting in a series of studies investigating the subject (Auler et al., 2017; Beske et al., 2014; Dani & Deep, 2010; Marucheck et al., 2011). Food safety is a vital issue for public health and a daily concern for all people. Contaminated food can harm people, increasing demand for health services, insurance, and government expenditures on public health and other social costs. Ultimately, contaminated food can transmit diseases and even kill. Food safety risk perception (FSRP) plays a crucial role in food safety because FSRP indicates how consumers perceive the risk associated with food, thereby influencing consumer choices and willingness to buy (WTB) (Adinolfi et al., 2016; Verbeke et al., 2007). Risk perception represents a person’s view of the risk inherent in a situation (Slovic, 1987), and perceptions of food safety risk reflect an individual’s belief regarding the amount of health risk (Tonsor et al., 2009). From the customer's perspective, safety is an intrinsically non-negotiable attribute of food (Verbeke et al., 2007). This means that consumers who are aware of the potential risk of food contamination can pressure suppliers to provide more information, be more transparent about their practices, and be more proactive in preventing food contamination. Consumer behaviour leads firms to improve their operational processes to mitigate the risks of interruptions in the chain due to contamination events (Schoenherr et al., 2015). Finally, risk perception can be a crucial mechanism for alerting other consumers, suppliers, and policymakers that problems might occur with a specific food supplier or supply chain. Despite its importance, studies related to food risk have not consolidated a unified body of consumer risk perception (Anders & Schmidt, 2011). The lack of integration in these studies may result from the breadth of food safety research since it is a multidisciplinary topic, encompassing marketing,

Journal Pre-proof 3 supply chains, agriculture, and food-related fields. These different research streams explore the same phenomenon using different theoretical approaches, simultaneously resulting in fruitful findings but fragmented literature. For example, what are the key drivers of FSRP? What are their effects on FSRP? What is the effect of FSRP on WTB? To have a more comprehensive understanding of FSRP, another set of variables can play a crucial role in moderating these relationships and set boundary conditions for this phenomenon. To answer these questions, we conducted a meta-analysis to (i) investigate and integrate the results of previous empirical studies on the effects of the antecedents on FSRP, (ii) evaluate the effects of FSRP on WTB, and (iii) analyse possible moderators of the FRSP-WTB relationship. We focus on consumers’ WTB because this variable reflects a crucial consumer outcome for suppliers. As example of the negative consequences of WTB, consumers’ unwillingness to buy a product results in some unrealized sales and affects suppliers’ revenues and inventories. Thus, the purpose of our paper is twofold. First, we examine the effect of key drivers of FSRP and provide a synthesis of the relationships presented in previous empirical studies. More specifically, we review the antecedents constructs of FSRP reported in the literature and conducted a statistical meta-analysis to assess the effect size of these antecedents on FSRP. Second, we analyse the main effect of FSRP on WTB and evaluate potential moderating factors that play a role in increasing or decreasing the effects of FSRP on WTB. In other words, we also performed a meta-analysis to assess the effect of FSRP on WTB and identified constructs used as moderators for this relationship that help explain some of the heterogeneous effects of FSRP on WTB. Our findings contribute to the literature as follows. First, we consolidate previous results and help to show the effects of relevant variables related to FSRP. Revealing the antecedents of FSRP that have the most significant effects and those that have smaller effects can help delineate a course of action for scholars, practitioners, and policymakers. Another contribution is to assess the effect size for the relationship between FSRP and WTB and evaluate how FSRP can impact consumers purchase intention and supplier performance. Finally, we provide a set of moderator variables not previously investigated, adding to the growing literature on this topic.

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2 THEORETICAL BACKGROUND AND RESEARCH PROPOSITIONS

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2.1 Food Safety Risk Perception: Domain and Main Relationships

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FSRP is the individual’s perception of the presence of an attribute (safety) in food and the probability and

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severity of health consequences of its consumption (Schroeder et al., 2007). Studies have applied this

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concept to represent an individual’s belief regarding the amount of health risk related to food (Tonsor et

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al., 2009). In other words, FSRP is a person’s perception of the potential risk associated with food safety

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questions.

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FSRP is vital for food safety because it plays a crucial role in determining consumer attitudes

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(Chen, 2017; Schroeder et al., 2007; Wu et al., 2013). Consumer attitudes refer to the predisposition

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towards a particular object, reflecting behavioural, normative, and control beliefs that are directly related

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to the consumer’s intention and, consequently, his or her behaviour (Ajzen, 1991; Ajzen & Fishbein,

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1973). Because of their attitudes towards food purchase and consumption, consumers play a central role

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in the direction of industrial processes and public and private regulations (Schoenherr et al., 2015). For

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these reasons, there is a significant increase in studies that examine the key drivers of the concept. A

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preliminary literature analysis shows four main categories of predictors: trust, knowledge, subjective

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characteristics and socio-demographic factors. Because of its multidimensional nature, each category has

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sub-categories, hereafter also called variables. These variables link the literature with the methods and

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results sections. The criterion employed to develop these constructs and their sub-dimensions is concept

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similarity; in other words, constructs that share a common meaning are put together. For example, many

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studies investigated the trust of individuals in different actors, such as government or the media, which

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led to the creation of a “trust” construct. Table 1 shows the antecedents, their definition and the expected

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relationship with FSRP.

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TABLE 1 HERE

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The first category is trust, which can be broadly defined as a person’s confidence in or

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expectation that another person or party will behave as expected based on the relationship established

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between them (Cheng et al., 2008; Ireland & Webb, 2007; Kwon & Suh, 2004). The central role of trust

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in FSRP is to reduce the complexity and asymmetry of information in consumer decision making in

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environments of high uncertainty (Stefani et al., 2008). Studies on trust seek to examine how trust in a

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supplier, supply chain or the institutional environment affects the purchase decision-making process

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(Bocker, 2002; Chen, 2013; Chen & Deng, 2013; Wu, 2015). Trust is expected to reduce FSRP because

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the consumer believes that the other party, whether it is the government, experts, suppliers, or the media,

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acts in the market to improve farmers’ compliance to produce safe food. This rationale applies to all sub-

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dimensions of trust; thus, we expect to observe a negative correlation between trust and FSRP.

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The second category is the knowledge dimension with two sub-dimensions: (i) objective

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knowledge, defined as knowledge based on the impartial observation of individual preferences (Klerck &

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Sweeney, 2007; Zhang & Liu, 2015), and (ii) subjective knowledge, which is the knowledge a person

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believes she or he possesses about a product (de Vocht et al., 2015; Zingg et al., 2013). Previous studies

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suggest that knowledge and consumption attitudes are interconnected because a consumer buys products

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he or she knows and has information about (Wilcock et al., 2004), especially when considering new

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technologies such as genetically modified food products (GMF) (Costa-Font et al., 2008; Rodríguez-

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Entrena & Sayadi, 2013; Sjöberg, 2008; Zhang et al., 2016). Consumers who know more about food

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products are more likely to identify potential threats that can contaminate food, improving their

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perception of food safety risks. Thus, we expect to observe a positive relationship between objective and

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subjective knowledge and FSRP.

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The third category is subjective characteristics, which are characteristics related to consumers’

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beliefs and values, such as their food risk control (Feng et al., 2010; Lagerkvist et al., 2015), their

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familiarity with food safety (Li et al., 2016; McComas et al., 2014; Sapp & Bird, 2003), and their risk

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acceptance (Amin et al., 2013). These psychological characteristics are related to risk perception in

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Slovic’s (1993, 1999) psychometric paradigm, helping us understand and predict people’s responses to

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various types of risks. Some sub-categories (perceived control, benefit perception, and initial positive

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attitude) are expected to be negatively related to FSRP because individuals believe that they can avoid

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risk or have a favourable evaluation of some food products (Hilverda et al., 2017). In contrast, individuals

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with more significant concerns related to food, individuals who have a higher preference for natural food

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and individuals who have a negative attitude about the risk of foods perceive lower food safety,

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suggesting that a positive relationship exists between these characteristics and FSRP.

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The last dimension is socio-demographic factors, such as age, education, income, gender, and the

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composition of the family group. We explore the relationship of these characteristics with FSRP. For

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example, we investigate the different perceptions of risk between men and women (Feng et al., 2010;

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Jacobsen et al., 2008; van Dijk et al., 2011; Zingg et al., 2013). Some characteristics are expected to be

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negatively related to FSRP because they provide consumers with more knowledge and access to

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information, as in the case of education level and income, while it is expected that others (such as age or

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presence of children in the household) positively drive FSRP because they make consumers more

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concerned about life threats.

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Finally, presented as a primary outcome of FSRP, WTB refers to a consumer’s disposition to

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accept, buy and consume a given food product (Bearth et al., 2014a). This outcome plays a crucial role in

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consumer behaviour because consumers’ intentions can translate into actions and attitudes, increasing

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consumption of a product. In the case of FSRP, WTB refers to the desire to buy a food product that

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consumers perceive as more or less risky. We expect to observe the negative effect of FSRP on WTB

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because consumers are less likely to buy a food product if they have a perception of a risk associated with

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its safety. Although the previous findings suggest the expected effect, we observe that some contextual

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factors can moderate this relationship. This question will be explained further below.

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2.2 Moderating Effect of Context on the Impact of FSRP on WTB

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From the literature discussion, we identify potential moderator constructs that may change the effects of

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FSRP on WTB. In Table 2, we present the po\ssible moderating elements and their short definitions,

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incorporating this additional analysis as a complement to the analysis of the direct effects. This analysis

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seeks to broaden the understanding of FSRP by considering many studies carried out in different contexts

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and allow for a more robust understanding of the production of effect sizes.

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TABLE 2 HERE

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The first moderator is food origin: vegetal or animal (Coary & Poor, 2016). It is expected that

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FSRP may generate more significant negative effects on WTB for foods with animal origin (milk, meat,

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eggs, etc.) than for food of vegetal origin (cereals, vegetables). Contamination scandals in the food of

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animal origin, such as the case of Melanin in milk in China (Pei et al., 2011), have a persistent effect on

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the perception of the consumer about risk. Consumers relate this food of animal origin with greater

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perishability, greater severity due to possible contamination by antibiotics, hormones and additives

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(Halbrendt et al., 1991). Thus, it is expected that:

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H1: The relationship between FSRP and WTB is higher for food of animal origin than for food of vegetal

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origin.

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The type of risk is our second suggested moderator. Consumers poorly recognize microbiological

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hazards, and the opinions and action of experts are more restricted, which generates optimism bias on the

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topic (Grunert, 2002; Miles et al., 1999). Besides, previous evidence has shown that consumers are

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reluctant to accept the introduction of some kinds of technological improvements in their food (such as

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genetic modification, irradiation or nanotechnology). In this way, the perception of consumers tends to be

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higher in risks of a technological nature due to the adverse effect caused by concerns about innovations in

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food and lower interest with microbiological risks due to lack of information (Chen et al., 2013; Cox &

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Evans, 2008). Based on this evidence, it is hypothesized that:

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H2: The relationship between FSRP and WTB is higher for technological risk than for microbiological

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risk.

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The healthiness moderator refers to essential components of the food experience (processes and

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outcomes) linked to mental symbolism that attribute to food a greater or lesser link with health attributes

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(Muñoz-Vilches et al., 2019). Previous research shows that consumers adopt schemas to classify food and

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make their choices (Blake et al., 2007). In this sense, we classify food in two categories: savory food -

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linked to emotional aspects of immediate retribution related to tasty but unhealthy food (e.g., ice cream,

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chocolate, fast food) - and healthy food - food linked to a healthier diet with benefits to the individual

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(such as fruits, vegetables) (Hausman, 2012; Jakubanecs et al., 2018). We expected that the healthiness of

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some food reduces the negative effects of FSRP on WTB due to the increase in the perception of benefits

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from these foods, while this effect is increased in foods without the same attribute:

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H3: The relationship between FSRP and WTB is higher for savoury food than for healthy food.

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The convenience moderator refers to the level of consumer involvement during the process of

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choosing and preparing a portion of food (Brunner et al., 2010; Warde, 1999). Not convenient foods

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demand more consumer preparatory actions (such as cooking rice and potatoes). Contrarily, convenient

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foods save time and reduce consumer actions (e.g., ready-to-eat meal, chocolates, cereals) (Candel, 2001),

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but they are associated with a perception of being less healthy (Brunner et al., 2010). Thus, the negative

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effects of FSRP on WTB are expected to be higher in convenient foods, since consumers tend to perceive

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less control and bind such foods to an industrialized process that distances them from health:

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H4: The relationship between FSRP and WTB is higher for convenient than for non-convenient food.

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The ethical concern moderator relates to the intrinsic attributes of a product that suggest to the

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consumer belonging to a group or community (Lindeman & Vaananen, 2000). For instance, ethical foods

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are oriented by ecological, political or religious principles and include ethnic and certified food, such as

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fair trade or halal food (Bu et al., 2013; Minton et al., 2019; Schroder & McEachern, 2004). Studies show

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that in choosing foods with ethical concerns, consumers have the notion that they are influencing social

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patterns and contributing to the formation of society closer to their values and attitudes (Schroder &

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McEachern, 2004). Because of that, we expect that consumers are more tolerant of perceived risk when

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consuming food that arouses a strong sense of belonging:

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H5: The relationship between FSRP and WTB is higher for general food than for ethical food.

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The shelf life refers to the time food products remain valid for consumption after it is made

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available to consumers (Holley & Patel, 2005; van Boxstael et al., 2014). Food products with longer life

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cycles (such as processed cereals) increase consumer perception that the food can be exposed to risk

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sources for a longer time. Also, these food products have an image related to the addition of preservatives

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and unnatural additives, creating barriers to consumer acceptance. On the other hand, food products with

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a short cycle (perishables such as fruits and vegetables) can cause the consumer to reduce this impression

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because of its connection with naturalness and control, negatively moderating the effects of FSRP on

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WTB. Thus, we expect that:

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H6: The relationship between FSRP and WTB is higher for long shelf life than for short shelf life food.

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Finally, the pleasure moderator is related to the emotion derived from ingesting a portion of food,

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being an important inducer of the consumption (Epstein et al., 2003). We classify food with hedonic or

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utilitarian motivation (Maehle et al., 2015). Food products with a utilitarian nature have nutrition as their

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main attributes, such as milk, rice, and potatoes. Contrarily, hedonic food products have emotional

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aspects like flavour satisfaction as their main attributes, such as sweets and salty processed food.

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Preliminary research has shown that in choosing hedonic products, consumers decrease their self-control

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about nutritional aspects (Madzharov et al., 2016). Consumers expect to compensate for this effect by

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restricting their acceptance of risky foods. Thus, FSRP is expected to cause a more significant negative

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impact on the WTB of hedonic products:

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H7: The relationship between food safety risk perception and willingness to buy is higher for hedonic

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than for utilitarian foods.

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3 METHODS

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3.1 Protocol of Systematic Review: PRISMA Statement

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This meta-analysis used the PRISMA Statement as a protocol to collect and select the primary data. The

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PRISMA Statement is a protocol that uses systematic and explicit methods to identify, select, and

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critically appraise relevant research, and to collect and analyse data from the studies that are included in

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the meta-analytic review (Moher et al., 2009). The PRISMA Statement involves the following four

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phases: identification, screening, eligibility and inclusion.

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The first phase is the identification. This step prepares the protocol record, which defines the

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characteristics of the study. In this phase, we define the information source, here the databases Web of

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Science Core Collection, JSTOR, Scopus, Proquest, Google Scholar and Ebsco. To perform the search,

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we employed the term “(consum* or custom*) and “food safety” and “risk perception” without

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restrictions on area, time, or location. Additionally, a snowball technique to the references was employed,

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and a manual search of the most cited journals was performed to reduce the possibility of losses. The

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input data (n = 2.476) are obtained from other studies that have been published in scholarly journals or

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unpublished in doctoral dissertations. As a quality control procedure, the citations and reference list of

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each paper were used ina triangulation procedure to inclusion of papers. That is if one paper is cited in

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another paper but missing in the database, then the paper is included.

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The second phase, screening, analyses the number of records and excludes duplicates files

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(n=399). A detailed analysis was carried out. Two researchers did full-text screening by reading each

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manuscript and make decisions based on the criteria described in the next paragraph. In case of

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disagreement, a third researcher did the full-text screening to help the decision-making process. This

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procedure eliminated 951 papers not related to food safety or the risk perception constructs. Then, in the

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third phase of eligibility, the following papers were eliminated: 341 theoretical papers, 287 qualitative

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studies, and 370 studies that had only descriptive statistics since these studies could not provide any

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inferential statistics to be used in the meta-analysis.

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The final step of the PRISMA protocol is the inclusion of papers in the analysis as follows: 128

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studies were retained in the sample for the meta-analysis (Appendix A has the complete list of papers). A

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critical step in the meta-analysis process is to define the inclusion criteria to select the studies to compose

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the analysis. In this study, the following inclusion criteria were used. First, studies must have a

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standardized statistical index used as a measure of effect size that represents the magnitude and direction

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of the relationship involving antecedents and FSRP and FSRP and WTB. The standardized statistical

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indexes used was the correlation coefficient. Thus, theoretical papers, qualitative studies, and studies

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using only descriptive statistics were excluded. Second, studies have to include the FSRP either as a

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construct with antecedents or as the antecedent of WTB. In this sense, the literature about FSRP includes

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studies that analyse the consumer's perception of risk in relation to food safety (absence of chemicals,

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physical, technological and biological components capable of presenting risks to consumer health) (Liu et

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al., 2014), capable of representing physical or psychological damage to consumers (Baker et al., 2016;

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Dholakia, 1997). Thus, studies that evaluated FSRP, especially risk possibility and seriousness but

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attributed another name such as "food hazard concern" (Kendall, 2018) or “level of confidence” (Goddard

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et al., 2013) were included in our analysis. On the other hand, studies that only assess lifestyle risks (e.g.,

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smoking and drinking) were not included. Similarly, studies related to chemistry and biology that analyse

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effective risks and studies that evaluate food quality in terms of nutritional value (Jeffery et al., 2006;

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Witkowski, 2007) and food security - related to the quantitative availability of food for the population

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(Fletcher & Frisvold, 2017; Gaines et al., 2014) - are outside the scope.

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3.2 Estimation Model and Procedure The analysis proceeded in three stages. First, we performed univariate analyses to obtain

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estimates of the mean FSRP. Second, we analysed and calculated 21 direct relationships with FSRP by

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combining study estimates using random-effects Hedges–Olkin-type meta-analysis (HOMA). The

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variables were grouped into five categories defined by the literature analysis (trust, knowledge, subjective

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characteristics and socio-demographic characteristics, willingness to buy).The correlation measure was

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used as the effect-size.

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In this case, we used the correlation as effect-sizes in our study. In case of the studies that did not

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report the correlation effects (standard regression, F or T-test or frequencies) we made conversions as

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suggested by Hedges and Olkin (1985). The effect sizes were corrected by the reliability of the scales and

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sample size (Hedges and Olkin 1985). We used the random-effects models to perform the final analysis of

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HOMA (Hunter and Schmidt, 2004). In this case, we made the correlation transformation by Fisher’s Z-

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distribution. The upper and lower confidence interval index was also analyzed at the 95% level, which

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comprises an estimate of the mean range of corrected weighted correlations (Hunter and Schmidt 2004).

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Also, the level of heterogeneity of the studies was analysed using the Q and Higgin’s I2 tests. The

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first test, known as Cochran's Q, verifies whether the data found in a primary study refute the null

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hypothesis; if so, the studies are considered homogeneous (Lau et al., 1998). The I2 statistic is obtained

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through the Q statistic and can range from 0 to 100%. Studies with a 25% index show low heterogeneity,

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studies with values of 50% showed moderate heterogeneity, and those over 75% show high heterogeneity

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(Higgins et al., 2013). Due to the high heterogeneity of the effect size, we used some variables as

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moderators.

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In the third and final phase, we analysedthe effects of moderators to reduce the heterogeneity.

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The analysis of the moderating effects followed the procedures suggested by You et al. (2015) and Köhler

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et al. (2017) and was performed for constructs that showed a high heterogeneity index (Cochran's Q) and

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a significant number of observations. The effects of moderators on the relationship between FSRP and

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WTB were analysed. These relationships were chosen because of the high heterogeneity indices and the

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number of possible observations with which to perform the calculations. The moderators tested were food

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origin, risk type, healthiness, convenience, ethical concern, shelf life and pleasure. We performed the

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meta-analysis with hierarchical linear modelling (HLM). In this step, the model using the maximum

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likelihood estimation methods was chosen (Köhler et al., 2017; You et al., 2015).

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4 RESULTS

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4.1 Univariate Analysis of Food Safety Risk Perception

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After the inclusion of papers, two independent reviewers (authors 1 and 2) performed the coding

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process, including article titles, journal titles, author(s), year of publication, statistical measures of

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relationships, reliability, sample size, method, type of risk, food analysed, and country of data collection.

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In cases of divergence, the paper was submitted to a third independent reviewer (author 3) to final

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analysis. Figure 1 shows the step-by-step of the search and extraction protocol.

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FIGURE 1 HERE The descriptive analysis reveals that our sample includes studies from 31 countries, with studies

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carried out in the United States (n=33), China (n=17) and the United Kingdom (n=12) representing almost

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half of the total number. The increasing number of publications in the last five years, which accounts for

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41.40% of our sample, reinforces the contemporary relevance of the theme. We did not identify a

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significant relationship between the year of article publication and the sample size (r= -.111; p=0.156).

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Finally, the analysis of the journals shows that multiple sources are present in our sample (67 journals in

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total).

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4.2. Effects of Antecedents on Food Safety Risk Perception

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The overall effects of antecedents on FSRP were computed by combining study estimates using random-

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effects HOMA. The estimated mean effects, the standard error and confidence interval were calculated

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using differences in the precision of the retrieved effect sizes by using weights (Hedges & Olkin, 1985).

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The meta-analysis began with a review of the literature. The study generated 749 observations

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(n=90.238), distributed and classified into 21 variables. The variables were grouped into five categories

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defined through the literature analysis: four antecedents (trust, knowledge, subjective characteristics and

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socio-demographic characteristics) and one consequence (WTB). In our process of coding the results

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from these studies, all these variables demonstrated direct relationships with FSRP.

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The results in Table 3 show that three trust constructs have negative and statistically significant

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effects on FSRP: trust in government (r=-.143; p<.05) and trust in chain members (r=-.226; p<.001).

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Trust in third parties, trust in experts and trust in media do not have a statistically significant relationship

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with FSRP. The effect of the general trust construct on FSRP (r=-.228; p<.05) is higher than any of the

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other trust constructs. General trust is inversely related to FSRP, meaning that higher scores for trust

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decrease the scores for FSRP, as expected.

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TABLE 3 HERE The results show that the effects of subjective knowledge on FSRP are statistically significant

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(r=-.128; p<.05) but that the effects of objective knowledge are non-significant (r=-.004; p=.932). With

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a larger sample size, subjective knowledge has been shown to induce FSRP (Liu, 2014; Martinez-Poveda

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et al., 2009). The results regarding the lack of a significant effect of objective knowledge can be explained

326

by the contextual heterogeneity of the studies that evaluated objective knowledge. Preliminary studies, for

327

example, evaluated objective knowledge in contexts such as GMF (Zhang & Liu, 2015), food additives

Journal Pre-proof 14 328

(Bearth et al., 2014b, 2016), and biological contamination (Bearth et al., 2014a) using different

329

measurement mechanisms. In contrast, studies on subjective knowledge used similar measurement

330

mechanisms, providing more consistency in results and less heterogeneity across studies (Liu et al.,

331

2014).

332

Five subjective characteristics have significant effects on FSRP (perceived control, concern,

333

benefit perception, preference for natural food, and initial negative attitude), while one subjective

334

characteristic (initial positive attitude) does not. Based on a total sample of 2,621 collected from 4 papers,

335

the negative initial attitude has the highest effect on FSRP (r=.377; p<.001). Perceived control (r=-.155;

336

p<.001) and benefit perception (r=-.311; p<.001) are negatively associated with FSRP, suggesting that

337

consumers perceive more food safety risks as they perceive themselves to have less control and fewer

338

benefits. The concern (r=.206; p<.001) and preference for natural food (r=.235; p<.001) constructs are

339

positively associated with FSRP, suggesting that consumers who prefer natural food and those who are

340

more concerned about their food perceive more food safety risks. Five demographic characteristics have

341

significant effects on FSRP: age (r=.06; p<.001), education (r=-.077; p<.05), children in household

342

(r=.144; p<.001), household size (r=.064; p<.001), and gender (r=.259; p<.001).

343

Finally, WTB is significantly and negatively related to FSRP (r=- .28; p<.001). The result

344

supports the arguments presented in our review. In fact, consumers difficulties in recognizing risks just by

345

looking to the physical attributes of food products and the negative effects generated by recurrent

346

contamination scandals worldwide (Lobb et al., 2007) are key drivers of negative attitudes towards food

347

(Chen & Li, 2007), non-acceptance (Kajale & Becker, 2015) and especially non consumption (Zingg et

348

al., 2013).

349 350

4.3 LSTE HLM Regression Estimation Results

351

The heterogeneity indices in the relationship between FSRP and WTB (Q=34,353.3; I2=97.29)

352

demonstrate the need to assess its effect size by testing some moderations, helping the robustness of

353

conclusions (Higgins & Thompson, 2002). We created a percentage of estimates of classified effects with

Journal Pre-proof 15 354

evidence of the reasons for heterogeneity. Additionally, the funnel plot of our data demonstrates the

355

dispersion of horizontally scattered data, which may indicate the presence of systematic heterogeneity

356

(see Fig. 2) (Sterne et al., 2011).

357 358

FIGURE 2 HERE The goal of this phase is to analyse the possible moderating effects of the variables: food origin,

359

risk type, healthiness, convenience, ethical concern, shelf life and pleasure. Also, we focused our analysis

360

only on the relationship between FSRP and WTB because this relationship has larger samples, increasing

361

statistical power, and allowing for higher generalization of the results. Table 4 presents the results of the

362

HLM regression for the meta-analysis.

363

Consistent, with H1, we find that a relationship between FSRP and WTB are greater for animal

364

origin foods than for vegetal origin foods (ß = -.095; r Vegetal Origin =-.19; r Animal Origin =-.36; p<.001).

365

Regarding Hypothesis 2, we find significant differences in the type of risk (ß =-.195; p<.05). The

366

relationship between FSRP and WTB is stronger for technological risk than for microbiological risk (r

367

Microbiological risk =-.18;

368

meta-analytic results demonstrated that there was a significant difference between health food and

369

savoury food (ß =-.087; p<.001). The effects were stronger in the condition of savory food than in health

370

food (r Health food =-.08; r Savory food =-.41).

TABLE 4 HERE

371 372

r Technological risk =-.32). Hypothesis 3 test the moderating effect of healthiness. The

We did not find support for the moderating effect of convenience (Hypothesis 4) (ß =-.24; r

373

Convenient =-.293;

374

no significant differences between the effects of general food and ethical food (ß=-.307; r General food=-

375

.292; r Ethical food=-.288; p=ns). Hypothesis 6, analysing the moderating effect of shelf life, was confirmed

376

(ß=-.25; p<.05). The result implies that long shelf life produces a stronger relationship than short shelf

377

life (r Long=-.432; r Short=-.24). Finally, Hypothesis 7 was confirmed, demonstrating that the pleasure

378

moderator can explain the levels of heterogeneity in the studied relationship (ß=-.178; r Hedonic=-.294; r

r Non-convenient =-.229; p=ns). Nor did Hypothesis 5 show significant differences: here were

Journal Pre-proof 16 379

Utilitarian=

380

products than for utilitarian products.

-.156; p<.05). We found that the relationship between FSRP and WTB are greater for hedonistic

381 382

5 DISCUSSION

383

5.1. Discussion about the antecedents of FSRP

384

We were motivated to conduct this meta-analysis because of the importance of FSRP for food

385

safety and the abundance of empirical findings obtained from many studies. Our objective is to assess the

386

effect of the antecedents on FSRP and its impact on WTB. Consumers’ FSRP and WTB play critical roles

387

in preventing the spread of potentially contaminated food as follows: consumers become suspicious of

388

and do not buy some food products, forcing food producers to review their products and urge authorities

389

to investigate potential food contamination cases. In this section, we discuss our findings and present

390

opportunities for future research. To show how our study distinguishes from previous meta-analysis

391

studies, we present table 5. As shown in this table, our study attempts to provide a more comprehensive

392

analysis of FSRP.

393 394

TABLE 5 HERE Our findings suggest that, in its multiple instances (trust in government, trust in chain members,

395

and general trust), trust is an essential antecedent of FSRP. Trust provides legitimacy for food products

396

and suppliers, reducing the need for other forms of legitimacy. Consumers may view the government as

397

an authority able to monitor and identify potential threats in food producers, even if the government is not

398

efficient performing as such. This argument suggests that the government plays multiple roles by not only

399

enforcing practices, such as traceability (Resende-Filho & Hurley, 2012) but also providing information

400

to consumers. Furthermore, the government must have proper food monitoring operations to increase the

401

likelihood of detecting contaminated food (Rodrigues et al., 2019) and continuously build its reputation.

402

Similar reasoning can be applied to trust in chain members. Consumers might consider firms in

403

the supply chain reputable food producers and distributors that safeguard their products from

404

contamination. Consumers who trust their suppliers reduce the amount of other information they need to

Journal Pre-proof 17 405

believe that a given food supplier or food product is safe. Trust in the supply chain, for example, is related

406

to competence in and knowledge of food safety management because it is a prerequisite for successful

407

food safety management (Costa-Font et al., 2008; van Kleef et al., 2007). These findings reinforce the

408

need for policies developed by different actors (Tonsor et al., 2009; van Kleef et al., 2007) to enhance the

409

quality of information and increase trust among actors in the supply chain. Finally, trust in government

410

and these chain members might work jointly to form general consumer trust. The relationship among

411

these trust instances can be a fruitful research avenue in terms of FSRP since there seem to be a hierarchy

412

in which general trust is at the highest level, trust in the government is at a second level, and trust in chain

413

members is at the lowest level.

414

Future research could explore the mechanisms forming the reputation of the government and

415

chain members. Is this trust in government and chain members related to the number of events and

416

information provided by these actors? How does trust build on particular government and chain member

417

characteristics? Future research could explore whether trust in the government or trust, in general, differs

418

in emerging countries since these countries have issues with reputable institutions. For example, the

419

Brazilian government has been involved in corruption scandals over the past few years; how does this

420

involvement impact trust as a driver of FSRP in the Brazilian population?

421

Another finding shows that the individuals’ perception of knowledge (subjective knowledge) is

422

negatively associated with a decrease in FSRP, suggesting that what individuals think they know about

423

food safety make them safer about their food consumption. Consumers who are more confident about

424

their knowledge tend to perceive less food safety risk. However, individuals might not realize that their

425

understanding may not correspond to the actual risk. Despite this adverse effect, additional information

426

and conclusions must be drawn from future studies to enhance our understanding of how consumers’

427

subjective knowledge is formed and the degree to which this subjectivity corresponds to actual risk. Thus,

428

future studies should determine whether lower levels of FSRP correspond to a real decrease in genuine

429

risk. Subjective knowledge must be placed into context and distinguished depending on consumers’

Journal Pre-proof 18 430

background, history, and personality. Also, future research can focus on possible differences in perception

431

due to the consumption environment (restaurants, markets, houses, and streets).

432

An initial negative attitude (e.g. initial rejection) has a positive effect on FSRP, driving

433

consumers to question many aspects of the food product, including its safety and increasing consumers

434

awareness about food safety. For example, Rodríguez-Entrena & Sayadi (2013) showed that, compared

435

with consumers with a more favourable initial attitude towards GMF, consumers with an initial negative

436

attitude towards GMF had significantly higher FSRP. This finding raises other questions: what does drive

437

an initial negative reaction? What are the main reasons why consumers have an initial negative attitude?

438

Are there events triggering this initial negative attitude? Answer to those questions can illuminate forms

439

of reducing or enhancing its effects on FSRP.

440

Additionally, our findings show that FSRP is influenced by individual characteristics relating to

441

personal preferences and perception/concern of the probabilities and negative severities in food

442

consumption. Some aspects include the consumers’ perceived control, benefit perception, preference for

443

natural food, etc. These subjective characteristics have gained importance in FSRP studies, and future

444

research could explore their role in more depth. Other consumer socio-demographic characteristics also

445

impact FSRP. For instance, FSRP is positively affected by the presence of children in the domestic

446

environment, gender (female), age and the number of people in the household. We speculate that these

447

factors may be related to the perception of the adverse effects of contaminated food within families.

448

Future research might generate fruitful insight by exploring the variability in family structures and

449

consumers FSRP.

450

Both perceive risk control and benefit perception have negative effects on FSRP, suggesting that

451

consumers have control over or favourable evaluation of food. Additionally, the results demonstrate that

452

FSRP is not influenced by information and decisions made at the moment of food choice but derives from

453

cognitive processes formed by individuals throughout their lives. Future research should focus on how

454

and why information about food might interact with perceived risk control and benefit perception.

455

Another direction for research is to explore consumers’ decisions when confronting potential food risks.

Journal Pre-proof 19 456

Finally, our findings are aligned with arguments presented in the literature analysis, especially

457

regarding the presence of children in the family group and the size of the family group (Knight &

458

Warland, 2005). These factors cause consumers to increase the attention they pay to safety aspects in food

459

since their choices will affect not only themselves but also individuals to whom they are closely related.

460

Additionally, a gender difference was identified in the results since surveys regarding the domestic

461

division of labour consistently show that women are primarily responsible for household food preparation

462

(Beagan et al., 2008).

463 464 465

5.2. Discussion about the effect of FSRP on WTB We found that FSRP decreases consumers’ WTB by 28% on average. This finding is expected

466

but simultaneously surprising. We expected a negative relationship because consumers avoid buying food

467

that may be potentially contaminated. However, the magnitude of this relationship is surprising, given its

468

intensity and calls attention to consumer sensitivity to food risk. From one perspective, such avoidance

469

serves as a control mechanism that prevents food contamination from spreading out an achieve many

470

people. From another perspective, this avoidance can lead to financial losses and reputation damage if

471

triggered by a misleading FSRP. For these reasons, other studies must investigate consumers’ WTB in

472

different contexts as well as other consumer and supplier characteristics. For example, the effect of FSRP

473

on WTB might differ for consumption of food at a restaurant or home or even during an event. Similarly,

474

this effect might vary depending on the level of consumer education. Exploring these issues will

475

contribute to clarify the relationship between FSRP and WTB.

476 477

5.3. Discussion about the moderators

478

We found that some conditions strength or weaken the FSRP effects on WTB. One finding shows

479

that consumers become more risk-averse towards the food of an animal origin than vegetable origin. This

480

aversion may be because food from animal sources is more susceptible to contamination than the vegetal

481

counterpart. Future studies could explore mechanisms that trigger those risk aversion behaviour with food

Journal Pre-proof 20 482

from animal source origin. What are the food characteristics associated with risk aversion? How can

483

policymakers make use of this information to mobilize consumers for food safety? For instance, because

484

animal manipulation demands more sanitary control than vegetable manipulation, there are more

485

contamination cases, which, in turn, triggers FSRP in consumers.

486

Another finding demonstrates that the effect of FSRP on WTB tends to be higher for risks of a

487

technological nature than of a microbiological one, corroborating with previous results (Chen et al., 2013;

488

Cox & Evans, 2008). Technological risks, such as genetic modification, have received considerable

489

attention from the media and has been discussed publicly for some time, which might have provoked

490

consumers to think about this issue. Microbiological risks have always been restricted to experts in the

491

field, becoming more difficult for consumers to discuss them. These differences in consumers’ exposition

492

to these risks might be one factor influencing their different impact on consumers. Other authors could

493

develop experiments exposing consumers to various levels of risks and provide a different amount of

494

information and test their effects on FSRP.

495

Our findings show that the healthiness of some food reduces the negative effects of FSRP on

496

WTB due to the increase in the perception of benefits (Jakubanecs et al., 2018). This type of food tends to

497

be associated with health benefits, and therefore, consumers might conclude that this type of food is safer

498

than savoury food. In this case, negative reinforcement is generated by the perception of being unhealthy,

499

which prompts an increase in the control of safety attributes. However, the claim that healthy food is, in

500

fact, healthier than savoury food and less prone to contamination has not been examined yet. Thus, an

501

exciting topic for further investigation is to explore the differences in health and savoury food and

502

differences in consumers’ perceptions. We found similar results in the case of the shelf life moderator.

503

The negative effects of FSRP on WTB are weaker for products with a shorter shelf life than products with

504

a longer shelf life. We speculate that consumers might perceive shorter shelf life food products as having

505

fewer preservatives. This result might be because of the lower perception of naturalness and neophobia.

506

Finally, the negative effects of FSRP on WTB is also strengthening in the case of hedonic food.

507

This finding suggests that pleasure is an essential inducer of consumption (Epstein et al., 2003) because

Journal Pre-proof 21 508

the choice of hedonic products compensates the self-control by restricting their acceptance of risky foods.

509

Thus, consumers seeking for pleasure are more sensitive to potential cases of food risk than consumers of

510

utilitarian food. Future research could investigate the trade-off between pleasure and self-control in

511

consumers of hedonic food and how they respond to information about food risk.

512 513

6 CONCLUSION

514

Using observations from 128 empirical studies, we tested the effect of these antecedents on FSRP and the

515

moderator variables on the effect of FSRP on WTB. Our findings show that trust, subjective knowledge

516

and characteristics have an impact on consumers’ FSRP and that FSRP decreases consumers’ WTB. We

517

also found that the negative effect of FSRP on WTB is more significant for hedonic and animal food and

518

technological risks, while this effect is weaker for healthy food products with a shorter shelf life. These

519

findings provide an overview of the main results involving FSRP and WTB.

520

Our contributions span the empirical and theoretical literature on FSRP. One contribution of our

521

study is its consolidation of previous empirical findings. It also provides a solid foundation for theoretical

522

and practical insights that can shape the advancement of the literature on FSRP. By doing so, we give

523

insights into the drivers and consequences of FSRP. We showed that trust, subjective knowledge, income,

524

and control and benefit perception reduce the FSRP, and in contrast, that an initial negative attitude, food

525

concerns, a preference for natural food, and children increase the FSRP. Furthermore, we showed that

526

FSRP renders people more risk-averse, but people might be willing to pay to obtain information through

527

certificates provided by sources. These insights can serve as a reference point for future research to draw

528

on and advance this topic, helping policymakers to rely on empirically validated findings.

529

Another contribution is our exploration of potential moderators for the effects of the antecedents

530

and consequences of FSRP. Presenting and empirically assessing the impact of these moderators provide

531

a more comprehensive and overall picture of FSRP. We showed that some characteristics of food could

532

alleviate the risk-averse behaviour resulting from the perception of food safety risk. Also, our meta-

533

analysis proposes solutions to other meta-analyses in the area (Bearth & Siegrist, 2014; Frewer, 2012;

Journal Pre-proof 22 534

Patil et al., 2005; Vialette, 2005). Our results become different from these other studies by providing

535

theoretical insight into the FSRP phenomenon through customer perception.

536 537

6.1 Practical Implications

538

We provide some practical implications for firms and policymakers. Firms should work on their

539

reputation because consumers rely on some firms to build their trust. Thus, firms should release accurate

540

information to the press and consumers. Firms could also provide knowledge to consumers to help them

541

build a stronger knowledge base about food and potential risk effects and how to behave in the case of

542

food contamination. For example, firms could use the food product package to provide information about

543

food safety or develop and send booklets with safety food information to consumers. Firms selling food

544

products from an animal origin should exert more effort to clarify and educate consumers since

545

consumers of these type of food are more sensitive to FSRP. For example, slaughterhouse firms selling

546

beef could design communication marketing campaigns to inform consumers about their products and

547

safety practices and the practices that consumers should perform. Firms should work on their supply

548

chains to increase delivery times and reduce inventories to provide products with a shorter life cycle.

549

Finally, firms selling healthy products and products for families should invest in marketing actions to

550

promote safety in their products because consumers are more sensitive to food safety in these products.

551

Policymakers should create and support government institutions that could provide regular

552

information to consumers and become a pillar for knowledge dissemination among consumers. These

553

institutions must be proactive in the monitoring process to detect potential food safety problems and

554

inform consumers before food contamination cases spread. For example, a governmental institution could

555

develop communication actions through online material and print materials. However, these

556

communication actions should aim to build consumers’ trust in government institutions since objective

557

knowledge did not have any effect as an antecedent of FSRP. More specifically, governmental institutions

558

should provide information regarding healthy food because consumers are more sensitive to this type of

559

food. Policymakers could develop regulation giving incentives to grocery stores, restaurants, and other

Journal Pre-proof 23 560

food retailers promoting safety information, especially information about food from animal sources. Laws

561

could be designed to enforce the health system (e.g., hospital, clinics, etc.) to provide information about

562

food safety to consumers. Because contaminated food can result in sickness and hospitalization, it is

563

crucial to work to prevent these cases. Policymakers should target women in families with children

564

because these consumers are more risk-averse than single men. Finally, policymakers should regulate

565

food denominations, such as shorter and longer life cycle products and healthy food. Such regulation can

566

standardize practices that might vary among firms and confuse consumers, creating biased perceptions

567

about food safety.

568 569

6.2 Limitations

570

Our research study has some limitations. First, the meta-analysis does not allow a demonstration of

571

causality in the relationships identified. We did not identify longitudinal studies that examined

572

relationships with FSRP, especially important ones, which prevents causal findings. Second, publication

573

journals focus on specific research fields, which can overweight one research area in detriment of the

574

others. For example, some journals focus on the technicalities of food and publish more papers about this

575

topic, while some journals focus on consumer behaviour. Third, we did not evaluate the quality of the

576

methods employed in each study because we assume that the studies were subjected to a rigorous review

577

process with qualified reviewers that would have captured any methodological problems. If this

578

assumption is incorrect and the results are not valid or biased in some way, we might have amplified

579

effects that should not be considered. Finally, the studies included in our meta-analysis are based on

580

experimental designs in which consumers made decisions in a controlled setting, which may not

581

correspond to their decision-making process in a real situation.

582 583

ACKNOWLEDGMENTS

584

We acknowledge the researchers at the Brazilian Agricultural Research Corporation (EMBRAPA, the

585

acronym in Portuguese) for contributions at the early stages of this study.

Journal Pre-proof 24 586 587

FUNDING

588

This study was financed in part by the Coordination for the Improvement of Higher Education Personnel-

589

Brazil (CAPES) - Finance Code 001.

590 591

APPENDIX A HERE

592 593

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CRediT author statement

Vinicius A.M. Nardi: Conceptualization, Methodology, Data curation, Writing – original draft, Writing – review draft Rafael Teixeira: Supervision, Writing – original draft, Writing – review & editing Wagner J. Ladeira: Formal analysis Fernando O. Santini: Formal analysis

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Declaration of Interest form

We, authors of the manuscript entitled “A meta-analytic review of food safety risk perception”, do not have any conflict of interest to disclose.

Vinicius A.M. Nardi Rafael Teixeira Wagner J. Ladeira Fernando O. Santini

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Appendix A – List of journals used in the meta-analysis. ID

Author

Title

Year

Journal

1

Amin, L; Azad, MA; Samian, AL

Factor influencing risk perception of food additives

2013

Journal of Food Agriculture & Environment

2

Amin, L; Azad, MA; Samian, AL; Jahi, JM

Factors affecting risk perception of culturally sensitive food

2013

Journal of Food Agriculture & Environment

3

Angulo, AM; Gil, JM

Risk perception and consumer willingness to pay for certified beef in Spain

2007

Food Quality and Preference

4

Baker, MA; Shin, JT; Kim, YW

An exploration and investigation of edible insect consumption: the impacts of image and description on risk perceptions and purchase intent

2016

Psychology & Marketing

5

Bearth, A.; Cousin, M. E.; Siegrist, M.

Poultry consumers' behaviour, risk perception and knowledge related to campylobacteriosis and domestic food safety.

2014

Food Control

6

Bearth, A; Cousin, ME; Siegrist, M

The consumer's perception of artificial food additives: Influences on acceptance, risk and benefit perceptions

2014

Food Quality and Preference

7

Bearth, A; Cousin, ME; Siegrist, M

The dose makes the poison: informing consumers about the scientific risk assessment of food additives

2016

Risk Analysis

8

Bocker, A

Consumer response to a food safety incident: exploring the 2002 role of supplier differentiation in an experimental study

European Review of Agricultural Economics

9

Cao, Y; Just, DR; Turvey, C; Wansink, B

Existing food habits and recent choices lead to disregard of 2015 food safety announcements

Canadian Journal of Agricultural Economics-Revue Canadienne D Agroeconomi

10

Cembalo L., Caso D., Carfora The "Land of Fires" toxic waste scandal and its effect on V., Caracciolo F., Lombardi A., consumer food choices Cicia G.

2019

International Journal of Environmental Research and Public Health

11

Chen, MF

Extending the protection motivation theory model to predict public safe food choice behavioural intentions in Taiwan

2016

Food Control

12

Chen, MF

Modeling an extended theory of planned behavior model to predict intention to take precautions to avoid consuming 2017 food with additives

Food Quality and Preference

13

Chen, MF; Li, HL

The consumer's attitude toward genetically modified foods 2007 in Taiwan

Food Quality and Preference

14

Chen, WP

The effects of different types of trust on consumer perceptions of food safety: an empirical study of consumers in Beijing Municipality, China

2013

China Agricultural Economic Review

15

Choi, J; Lee, A; Ok, C

The effects of consumers' perceived risk and benefit on attitude and behavioral intention: a study of street food

2013

Journal of Travel & Tourism Marketing

16

Coppola, A., Verneau, F., & Caracciolo, F.

Neophobia in food consumption: an empirical application of the FTNS scale in Southern Italy

2014

Italian Journal of Food Science

17

Costa-Font, M; Gil, JM

Structural equation modelling of consumer acceptance of genetically modified (GM) food in the Mediterranean Europe: A cross country study

2009

Food Quality and Preference

18

Crowley, OV; Marquette, J; Reddy, D; Fleming, R

Factors predicting likelihood of eating irradiated meat

2013

Journal of Applied Social Psychology

19

Cucchiara, C; Kwon, S; Ha, SJ

Message framing and consumer responses to organic seafood labeling

2015

British Food Journal

Journal Pre-proof

ID

Author

Title

Year

20

Cunha, LM; de Moura, AP; Lopes, Z; Santos, MD; Silva, I

Public perceptions of food-related hazards: an application to Portuguese consumers

2010

British Food Journal

21

David R. Just

Biosecurity, terrorism, and food consumption behavior: using experimental psychology to analyze choices involving fear

2009

Journal of Agricultural And Resource Economics

22

de Jonge, J; van Trijp, H; Goddard, E; Frewer, L

Consumer confidence in the safety of food in Canada and the Netherlands: The validation of a generic framework

2008

Food Quality and Preference

23

de Jonge, J; Van Trijp, H; Renes, RJ; Frewer, LJ

Consumer confidence in the safety of food and newspaper coverage of food safety issues: a longitudinal perspective

2010

Risk Analysis

24

De Steur, H; Gellynck, X; Storozhenko, S; Liqun, G; Lambert, W; Van Der Straeten, D; Viaene, J

Willingness-to-accept and purchase genetically modified rice with high folate content in Shanxi Province, China

2010

Appetite

25

De Steur, H; Odongo, W; Gellynck, X

Applying the food technology neophobia scale in a developing country context. A case-study on processed matooke (cooking banana) flour in Central Uganda

2016

Appetite

26

Dickson-Spillmann, M; Siegrist, M; Keller, C

Attitudes toward chemicals are associated with preference for natural food

2011

Food Quality and Preference

27

Dosman, Donna M

Socioeconomic determinants of health- and food safetyrelated risk perceptions

2001

Risk Analysis

28

Fandos-Herrera, C

Exploring the mediating role of trust in food products with Protected Designation of Origin: the case of "Jamon de Teruel"

2016

Spanish Journal of Agricultural Research

29

Fischer, ARH; Frewer, LJ

Consumer familiarity with foods and the perception of risks and benefits

2009

Food Quality and Preference

30

Fleming, K; Thorson, E; Zhang, YY

Going beyond exposure to local news media: An information-processing examination of public perceptions of food safety

2006

Journal of Health Communication

31

Florkowski, WJ; Elnagheeb, AH; Huang, CL

Risk perception and new food production technologies

1998

Applied Economics Letters

32

Ghasemi, S; Karami, E; Azadi, H

Knowledge, attitudes and behavioral intentions of agricultural professionals toward genetically modified (GM) Foods: a case study in Southwest Iran

2013

Science and Engineering Ethics

33

Grobe, D; Douthitt, R; Zepeda, L

A model of consumers' risk perceptions toward recombinant bovine growth hormone (rhGH): The impact of risk characteristics

1999

Risk Analysis

34

Gupta, V; Khanna, K; Gupta, RK

A study on the street food dimensions and its effects on consumer attitude and behavioural intentions

2018

Tourism Review

35

Harrison R.W., Boccaletti S., House L.

Risk perceptions of urban Italian and United States consumers for genetically modified foods

2005

Agbioforum

36

HF Lee, M Boccalatte

37

Hilverda, F; Kuttschreuter, M; Giebels, E

38

Huang, CL

Food safety in China from North American and European 2018 perspectives Social media mediated interaction with peers, experts and anonymous authors: Conversation partner and message 2017 framing effects on risk perception and sense-making of organic food Simultaneous-equation model for estimating consumer risk perceptions, attitudes, and willingness-to-pay for residue- 1993 free produce

Journal

Asian Geographer

Food Quality and Preference

Journal of Consumer Affairs

Journal Pre-proof

ID

Author

Title

Year

Journal

39

Jakubowska D.; Radzymińska M.

Polish consumer attitudes and behaviour towards meat safety risk

2010

Polish Journal of Food and Nutrition Sciences

40

Jeżewska-Zychowicz M.

Impact of health and nutrition risks perception on the interest in pro-healthy food on the example of bread

2016

Roczniki Państwowego Zakładu Higieny

41

Kajale D.B., Becker T.C.

Factors influencing young consumers’ acceptance of genetically modified food in India

2015

Journal of Food Products Marketing

42

Kim, RB

Consumers' perceptions of food risk management quality: Chinese and Korean evaluations

2012

Agricultural Economics-Zemedelska Ekonomika

43

Klerck, D; Sweeney, JC

The effect of knowledge types on consumer-perceived risk 2007 and adoption of genetically modified foods

Psychology & Marketing

44

Knight, A; Warland, R

The relationship between socio-demographics and concern 2004 about food safety issues

Journal of Consumer Affairs

45

Knight, AJ; Warland, R

Determinants of food safety risks: A multi-disciplinary approach

2005

Rural Sociology

46

Knuth, BA; Connelly, NA; Sheeshka, J; Patterson, J

Weighing health benefit and health risk information when consuming sport-caught fish

2003

Risk Analysis

47

Kuttschreuter, M

Psychological determinants of reactions to food risk messages

2006

Risk Analysis

48

La Barbera, F.; Amato, M.; Sannino, G

Understanding consumers’ intention and behaviour towards functionalised food: The role of knowledge and food technology neophobia

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British Food Journal,

49

Lagerkvist, CJ; Hess, S; Okello, J; Karanja, N

Consumer willingness to pay for safer vegetables in urban markets of a developing country: the case of Kale in Nairobi, Kenya

2013

Journal of Development Studies

50

Lagerkvist, CJ; Okello, J; Karanja, N

Consumers' evaluation of volition, control, anticipated regret, and perceived food health risk. Evidence from a 2015 field experiment in a traditional vegetable market in Kenya

Food Control

51

Lai J; Wang H.H; Ortega D.L; Olynk Widmar N.J.

Factoring Chinese consumers’ risk perceptions into their willingness to pay for pork safety, environmental stewardship, and animal welfare

2018

Food Control

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Li, JJ; Li, N; Luo, L; Ren, YA

Segmentation of Chinese parents based on food risk perception dimensions for risk communication in rural area of Sichuan province

2016

British Food Journal

53

Liao, CH; Zhou, XM; Zhao, DT

An Augmented Risk Information Seeking Model: Perceived Food Safety Risk Related to Food Recalls

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International Journal of Environmental Research And Public Health

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Liu R; Wu L; Shan L; Li H.

Consumer’s risk perception of genetically modified food and its influencing factors: Based on the survey in Jiangsu Province, China

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Open Biotechnology Journal

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American Journal of Agricultural Economics

56 57

Liu, RD; Pieniak, Z; Verbeke, W Lobb, AE; Mazzocchi, M; Traill, WB

58

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Food-related hazards in China: Consumers' perceptions of risk and trust in information sources Modelling risk perception and trust in food safety information within the theory of planned behaviour The impact of abnormally shaped vegetables on consumers' risk perception Risk perceptions, risk preference, and acceptance of risky food

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61 62

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Title Determinants of public phobia about infectious diseases in South Korea: effect of health communication and gender difference

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2015

Asia Pacific Journal of Public Health

2009

Food Policy

2008

Journal of Agricultural Economics

63

McCarthy M; Henson S.

Perceived risk and risk reduction strategies in the choice of 2005 beef by Irish consumers

Food Quality and Preference

64

McComas, KA; Besley, JC; Steinhardt, J

Factors influencing US consumer support for genetic modification to prevent crop disease

2014

Appetite

65

MI Ansari, M Mumtaz, NH Buriro

Determinants of consumer attitude for nutritional drinks: evidences from Pakistan

2017

66

Misra, SK; Huang, CL; Ott, SL

Consumer willingness to pay for pesticide-free fresh produce

1991

67

Mitchell, VW; Bakewell, C; Jackson, P; Heslin, C

How message framing affects consumer attitudes in food crises

2015

British Food Journal

68

Moon, W; Balasubramanian, SK

Public attitudes toward agrobiotechnology: The mediating role of risk perceptions on the impact of trust, awareness, and outrage

2004

Review of Agricultural Economics

69

Moon, W; Balasubramanian, SK; Rimal, A

Willingness to pay (WTP) a premium for non-GM foods versus willingness to accept (WTA) a discount for GM foods

2007

Journal of Agricultural And Resource Economics

70

Murakami M; Suzuki M; Yamaguchi T.

Presenting information on regulation values improves the public’s sense of safety: Perceived mercury risk in fish and 2017 shellfish and its effects on consumption intention

Plos ONE

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2017

Agribusiness

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Muringai, V; Goddard, E

Bovine spongiform encephalopathy, risk perceptions, and beef consumption: differences between Canada and Japan

2011

Journal of Toxicology and Environmental Health-Part A-Current Issues

73

Ortega, DL; Wang, HH; Wu, LP; Olynk, NJ

Modeling heterogeneity in consumer preferences for select 2011 food safety attributes in China

Food Policy

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Jakus, P.M

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Journal of Risk and Uncertainty

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Pieniak, Z; Verbeke, W; Scholderer, J; Brunso, K; Olsen, SO

Impact of consumers' health beliefs, health involvement and risk perception on fish consumption A study in five European countries

2008

British Food Journal

76

Pinto, A; Mascarello, G; Parise, Italian consumers' attitudes towards food risks: selfN; Bonaldo, S; Crovato, S; protective and non-self-protective profiles for effective Ravarotto, L risk communication

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British Food Journal

78

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The prediction of intention to consume genetically modified food: Test of an integrated psychosocial model

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Agro-biotechnology and organic food purchase in the United Kingdom

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Influence of scientific-technical literacy on consumers' behavioural intentions regarding new food

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Rodriguez-Entrena, M; Salazar-Ordonez, M; Sayadi, S

Applying partial least squares to model genetically modified food purchase intentions in southern Spain consumers

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2005

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Pink slimed: media framing of novel food technologies and risk related to ground beef and processed foods in the U.S.

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Determinants of food choice among adults in an urban community: A highlight on risk perception

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Nutrition & Food Science

86

Sapp, SG; Bird, SR

The effects of social trust on consumer perceptions of food 2003 safety

Social Behavior and Personality

87

Sapp, SG; Downing-Matibag, T

Consumer acceptance of food irradiation: a test of the recreancy theorem

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Consumer FSRPs and attitudes: Impacts on beef consumption across countries

2007

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89

Shepherd, Jonathan D

Risk perception and trust interaction in response to food safety events across products and the implications for agribusiness firms.

2015

Journal of Food Distribution Research

90

Shim, M; You, M

Cognitive and affective risk perceptions toward food safety outbreaks: mediating the relation between news use and food consumption intention

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Asian Journal of Communication

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Siegrist M; Stampfli N; Kastenholz H; Keller C.

Perceived risks and perceived benefits of different 2008 nanotechnology foods and nanotechnology food packaging

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An application of the risk perception attitude framework in 2018 food safety behavior

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Sjoberg, L

Genetically modified food in the eyes of the public and experts

2008

Risk Management-An International Journal

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2016

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Acceptance of nanotechnology in food and food packaging: a path model analysis

2010

Journal of Risk Research

94 95

Sodano, V; Gorgitano, MT; Verneau, F; Vitale, CD Stampfli, N; Siegrist, M; Kastenholz, H

96

Stefani, G; Cavicchi, A; Romano, D; Lobb, AE

Determinants of intention to purchase chicken in Italy: the role of consumer risk perception and trust in different information sources

2008

Agribusiness

97

Sun, HH

Research on the influencing factors of consumer FSRP

2017

Proceedings of the 2017 4th Inter. Confer. on Education, Management and Computing Tech. (Icemct 2017)

98

T Terawaki

Can information about genetically modified corn and its oil have significant effects on Japanese consumers' risk perception and their valuation?

2008

Agbioforum

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Author

99

Tanaka, Y; Kitayama, M; Arai, S; Matsushima, Y

Major psychological factors affecting consumer's acceptance of food additives Validity of a new psychological model

2015

British Food Journal

100

Thompson B; Toma L; Barnes A.P; Revoredo-Giha C.

The effect of date labels on willingness to consume dairy products: Implications for food waste reduction

2018

Waste Management

101

Thompson B.M; Ribera K.P; Wingenbach G.J; Vestal T.A.

The relationship between attitudes, knowledge, and demographic variables of high school teachers regarding food irradiation

2007

Journal of Food Science Education

Factors impacting FSRPs

2009

Journal of Agricultural Economics

Determinants of consumers' willingness to accept GM foods

2008

International Journal of Biotechnology

Categories of GM risk-benefit perceptions and their antecedents

2005

Agbioforum

Tonsor, GT; Schroeder, TC; Pennings, JME Traill W.B; Jaeger S.R; Yee W.M.S; Valli C; House L.O; 103 Lusk J.L; Moore M; Morrow Jr. J.L. Traill W.B; Jaeger S.R; Yee W.M.S; Valli C; House L.O; 104 Lusk J.L; Moore M; Morrow Jr. J.L. 102

Title

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Journal

Paper Presented at the 2016 Agricultural & Applied Economics Association Group Processes & Intergroup Relations

105

Tran, V;Yiannaka, A, Giannakas, K.

Consumer perceptions and willingness-to-pay for nanotechnology applications that enhance food safety

2016

106

Vainio, A, Makiniemi, JP;, Paloniemi, R

System justification and the perception of food risks

2014

107

van Dijk, H; Fischer, ARH; Frewer, LJ

Consumer responses to integrated risk-benefit information associated with the consumption of food

2011

Risk Analysis

Consumer responses to communication about food risk management

2008

Appetite

Consumer evaluations of food risk management quality in Europe

2007

Risk Analysis

Contingent valuation and willingness to pay for credence attributes in beef meat

2018

Revista Mexicana de Ciencias Pecuarias

Perceived risks of conventional and organic produce: Pesticides, pathogens, and natural toxins

2001

Risk Analysis

2013

Appetite

van Dijk, H; Houghton, J; van 108 Kleef, E; van der Lans, I; Rowe, G; Frewer, L Van Kleef, E; Houghton, JR; Krystallis, A; Pfenning, U; 109 Rowe, G; Van Dijk, H; Van der Lans, IA; Frewer, LJ Villanueva, JLJ; Lopez, SV; 110 Juarez, LAR 111 Williams, PRD; Hammitt, JK 112

Wu L; Zhong Y; Shan L; Qin W.

113

Wu, LH; Yin, SJ; Xu, YJ; Zhu, DA

114 Xu, LL; Wu, LH Yee W.M.S; Traill W.B; Lusk J.L; Jaeger S.R; House L.O; 115 Moore M; Morrow J.L; Valli C. 116 Yeung, R.M.W.; Yee, W.M.S. 117 Yeung, R. M. W.; Morris, J.

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2014 2010 2008

2005 2006

Canadian Journal of Agricultural Economics-Revue Canadienne D Agroeconomie Journal of The Science of Food and Agriculture International Journal Of Biotechnology Journal of International Food & Agribusiness Marketing International Journal of Consumer Studies

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ID

Author

118 Yeung, R; Yee, W; Morris, J 119 Yormirzoev M; Teuber R. 120 You, M; Ju, Y 121 Yu, HY; Neal, JA; Sirsat, SA

Title

Year

The effects of risk-reducing strategies on consumer perceived risk and on purchase likelihood A modelling 2010 approach Consumers’ response to genetically modified ingredients 2017 in processed food in an emerging economy A comprehensive examination of the determinants for food risk perception: focusing on psychometric factors, 2017 perceivers' characteristics, and media use Consumers' FSRPs and willingness to pay for fresh-cut produce with lower risk of foodborne illness

Journal British Food Journal Food & Agribusiness Marketing Health Communication

2018

Food Control

122

Zepeda, L; Douthitt, R; You, SY

Consumer risk perceptions toward agricultural biotechnology, self-protection, and food demand: The case 2003 of milk in the United States

Risk Analysis

123

Zhang, H; Gao, N; Wang, Y; Han, YX

Modeling risk governance and risk perception in personal prevention with regard to food safety issues

2018

British Food Journal

124 Zhang, M; Liu, GL

2015

International Journal of Food Science and Technology

125

2017

Internet Research

2016

China Economic Review

2015

Risk Analysis

2013

Journal of Risk Research

126 127 128

The effects of consumer's subjective and objective knowledge on perceptions and attitude towards genetically modified foods: objective knowledge as a determinant The impact of reference effects on online purchase Zhao, XF; Deng, SL; Zhou, Y intention of agricultural products: the moderating role of consumers' food safety consciousness Zhou, L; Turvey, CG; Hu, WY; Fear and trust: how risk perceptions of avian influenza Ying, RY affect Chinese consumers' demand for chicken Effects of knowledge on attitude formation and change Zhu, XQ; Xie, XF toward genetically modified foods Zingg, A; Cousin, ME; Connor, Public risk perception in the total meat supply chain M; Siegrist, M

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Fig. 1. PRISMA flow diagram

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Fig. 2. Frequency distribution and funnel plot

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Highlights

-

Consolidation of previous empirical findings regarding the antecedents and consequent of food safety risk perception. Test of effect sizes for consumer behavior antecedents of food safety risk perception. Test of effect size for the effect of food safety risk perception on consumer willingness to buy. Proposal and testing of effect size for factors that potentially moderate the relationship between food safety risk perception and willingness to buy.

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Table 1. Antecedents of food safety risk perception (FSRP). Trust Trust in government Trust in chain Trust in the third part Trust in experts General trust Trust in media Knowledge Subjective knowledge Objective knowledge Subjective characteristics Perceived control Concern Benefit perception Preference for natural food Positive Initial Attitude Negative Initial Attitude Sociodemographic Age Education Income Child household

Definition The individual's confidence in government and its regulations (Chen, 2013). The individual's confidence in companies that are part of the food supply chain (Chen, 2013; van Kleef et al., 2007). Individual confidence in non-governmental organizations and consumer protection entities (Chen, 2013; Kim, 2012). The individual's confidence in researchers, food engineers, physicians, and other food safety experts (Tonsor et al., 2009; van Kleef et al., 2007). Confidence of the individual in the positive behaviour of society in general (Chen & Li, 2007; Chen, 2013). Individual confidence in the media and communication entities (Vainio et al., 2014). Definition Particular knowledge that the individual thinks he knows about a product (Zingg et al., 2013). Knowledge based on impartial and independent observation of individual preferences (Zhang & Liu, 2015).

Expected relationship with estimates Trust in government negatively influences FSRP. Trust in chain negatively influences FSRP. Trust in third part negatively influences FSRP.

Definition

Expected relationship with estimates

Perception of control over risks in food (Feng et al., 2010; Lagerkvist et al., 2015). The concern of the individual with food safety (Zingg et al., 2013). Perception of the benefit of the individual with food (Sodano et al., 2016). Preference of the individual for food of natural origin (Sodano et al., 2016). Favourable preliminary evaluation towards eating a food (…) an essential determinant of consumers’ risk perception (Hilverda et al., 2017). The negative evaluation, similar to values in that it is embedded in our minds to influence our thoughts of a specific product (Chen & Li, 2007).

Perception of control negatively influences FSRP.

Definition

Expected relationship with estimates

Age of individual (Zingg et al., 2013) The educational level of the individual (Williams & Hammitt, 2001) Income level of the individual (Tonsor et al., 2009) Presence of children in the individual's home (Knight & Warland, 2005).

Age positively influences FSRP. Educational level negatively influences FSRP. Income level negatively influences FSRP. Child household positively influences FSRP. Household size positively influences FSRP. Gender (female) positively influences FSRP

Household size

Size of the individual's family group (de Steur et al., 2010).

Gender (female)

Gender of individual (Zingg et al., 2013)

Trust in experts negatively influences FSRP. General trust negatively influences FSRP. Trust in the media negatively influences FSRP. Expected relationship with estimates Subjective knowledge positively influences in the FSRP. Objective knowledge negatively influences FSRP.

Concern positively influences FSRP. Benefit perception negatively influences FSRP. Preference for natural food positively influences safety risk perception. Positive initial attitude negatively influences FSRP. Negative initial attitude positively influences FSRP.

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Table 2. Moderators analysed in the meta-analysis. Moderator Food origin

Description The origin of food (Coary & Poor, 2016; Hess et al., 2016).

Coding 0 = Vegetal Origin 1 = Animal Origin

Risk type

The risk involved in consuming food (Grunert, 2002; McCarthy et al., 2006).

0 = Microbiological Risk 1 = Technological Risk

Healthiness

The perceived healthiness and savoriness of food (Muñoz-Vilches et al., 2019; Xie et al., 2016)

0 = Healthy food 1 = Savory food

Convenience

The convenience involved in purchasing and preparing food (Candel, 2001; Steptoe et al., 1995)

0 = Non-convenient 1 = Convenient

Ethical concern

The environmental and political issues correlated with food (Lindeman & Vaananen, 2000

0 = General food 1 = Ethical food

Shelf Life

The period during which a stored food remains suitable for consumption (van Boxstael et al., 2014

0 = Short 1 = Long

Pleasure

The perception of the tasty and hedonic value of food (Cramer & Antonides, 2011; Maehle et al., 2015)

0 = Utilitarian 1 = Hedonic

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Table 3. Direct relationships with FSRP. Relations Trust Trust in government Trust in chain members Trust in third part Trust in experts General trust Trust in media

Summary of the study characteristics k O k O k O k O k O k O

23 35 17 35 9 12 5 14 11 15 7 11

N 21,542 N 18,393 N 5,458 N 8,834 N 13,659 N 6,137

Knowledge k 18 N Subjective knowledge O 28 11,554 k 12 N Objective knowledge O 20 5,224 Subjective characteristics k 14 N Perceived Control O 20 9,098 k 25 N Concern O 38 22,748 k 18 N Benefit perception O 28 9,908 k 6 N Preference for natural food O 11 3,382 k 9 N Positive Initial Attitude O 14 8,296 k 8 N Negative Initial Attitude O 11 2,621 Socio-demographic characteristics k 24 N Age O 37 29,153 k 23 N Education O 36 32,295 k 19 N Income O 32 25,269 k 14 N Child Household O 22 19,596 k 4 N Household size O 5 3528 k 22 N Gender (female) O 36 29,631 Consequent of FSRP k 67 N Willingness to buy O 94 52,399

Heterogeneity tests

Describing Effect Size Distributions Effect r -.143 Effect r -.226 Effect r .028 Effect r .075 Effect r -.228 Effect r -.028

LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%)

-.270 -.077 -.333 -.113 -.164 .214 -.170 .022 -.393 -.050 -.194 .138

Z p-value Z p-value Z p-value Z p-value Z p-value Z p-value

-2.120 .034 3.881 .000 .286 .775 -1.514 .130 -2.493 .013 -.331 .740

Q I2 Q I2 Q I2 Q I2 Q I2 Q I2

209.656 93.799 3,806.74 99.10 754.71 98.54 355.49 96.34 1,529.47 99.08 688.39 98.54

Effect r -.128 Effect r -.004

LCI (95%) HCI (95%) LCI (95%) HCI (95%)

.026 .226 -.096 .088

Z p-value Z p-value

2.466 .014 -.085 .932

Q I2 Q I2

1,073.15 97.48 356.49 94.67

Effect r -.155 Effect r .206 Effect r -.311 Effect r .235 Effect r -.035 Effect r .377

LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%)

-.255 -.052 .147 .264 -.406 -.209 .115 .348 -.203 .136 .232 .505

Z p-value Z p-value Z p-value Z p-value Z p-value Z p-value

-2.940 .003 6.678 .000 5.773 .000 3.780 .000 -.397 .691 4.858 .000

Q I2 Q I2 Q I2 Q I2 Q I2 Q I2

621.83 96.94 1,260.25 97.06 999.30 97.29 199.38 94.98 924.18 98.59 404.59 97.52

Effect r .060 Effect r -.077 Effect r .027 Effect r .104 Effect r .064 Effect r .259

LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%) LCI (95%) HCI (95%)

.032 .088 -.144 -.009 -.020 .073 .045 .168 .031 .096 .141 .371

Z p-value Z p-value Z p-value Z p-value Z p-value Z p-value

4.205 .000 -2.214 .027 1.131 .258 3.362 .001 3.771 .000 4.213 .000

Q I2 Q I2 Q I2 Q I2 Q I2 Q I2

218.30 83.50 1,448.96 97.58 504.56 93.65 493.88 95.74 1.113 93.31 4,884.65 99.28

Effect r -.280

LCI (95%) HCI (95%)

-.326 -.232

Z p-value

-11.049 .000

Q I2

34,35.33 97.29

Note: (k) number of studies;(o) number of observations taken from the analysis of the studies; (N) number of accumulated samples of the k

assessed studies; (Effect r) average effect and corrected from formula r=Σ = 1Zri. i

ni ― 3 Σki

= 1(ni ― 3); (LCI) lower confidence interval;

(HCI) higher confidence interval; (Q)test of heterogeneity at the individual and the aggregate levels; (I²) significance level of Q;

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Table 4. LSTE HLM estimation results. Hypothesis H1

H2

H3

H4

H5

H6

H7

Variable Intercept Food origin Vegetal origin Animal origin Intercept Risk Type Microbiological risk Technological risk Intercept Healthiness Healthy food Savory food Intercept Convenience No-convenient Convenient Intercept Ethical concern General food Ethical food Intercept Shelf life Short Long Intercept Pleasure Utilitarian Hedonic

N

Estimate

Average LSTE

LCI (95%)

HCI (95%)

-.095 12,113 35,091 16,544 23,389 22,696 18,078 16,087 2,763 45,370 2,054 15,622 3,621 6,866 3,837

1 -.301 -.195

-.190 -.360

1 -.153 -.087

-.180 -.320

1 -.376 -.240

-.080 -.410

1 -.091 -.307

-.229 -.293

1 .151 -.250

-.292 -.288

1 -.157 -.178

-.240 -.432

1 -.194

-.156 -.294

-.311 -.407 -.283 -.367 -.148 -.458 -.333 -.345 -.356 -.453 -.313 -.497 -.194 -.387

-.095 -.195 -.106 -.139 -.025 -.294 -.147 -.062 -.258 -.149 -.187 -.271 -.067 -.037

R2

SE

p-value

.045

.05

19.62%

.054 .045

.001 .001

3.7%

.058 .031

.05 .05

61.01%

.042 .047

.001 .001

14.77%

.078 .024

ns .001

4.59%

.153 .032

ns .01

15.25%

.071 .055

.05 .01

25.05%

.079

.05

Table 5. Characteristics of related food risk meta-analysis studies. Characteristic of the meta-analysis study (1) Focal relation (2) Scope* (3) Antecedents investigated in the metaanalysis

Trust Knowledge Subjective characteristics Socio-demographic

Bearth & Siegrist (2014b) Risk perception and acceptance of food technologies Consumers ‘acceptance

Frewer et al. (2013) Risk perception of genetic modification Public perception of GMF

X X X

√ X √

X √ X

√

X

X

√

X

√ √

√ √

X √

√ X

√ X

Present study Food safety risk perception and willingness to buy Consumer risk perception and decision-making √ √ √

Patil et al. (2005) Food safety knowledge and practices Consumer food safety practices

Vialette (2005) Food safety Information Provision of quality and safety X X X

(4) Risk Perception scope

Microbiological Technological

(5) Contemporariness of observations

Most recent study year in the dataset

2019

2014

2010

2003

2004

(6) Size of the dataset

Total number of articles

128

26

70

20

12

√

√

X

X

X

(7) Moderators

* Based on Grunert (2005)