Food With Additives

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Food with additives has been around for a long time. They’re added to foods to preserve them, enhance their flavor, or make them appealing in some other way. And while they can be useful, they also come with their share of risks.

In this blog series, we’ll be exploring how food as well as additives work and the health concerns that surround them. We’ll also look at how modern-day food manufacturers can use natural alternatives to food additives in order to create healthier foods and beverages without sacrificing taste.

Related post: Chicken With Swiss Chard

Food With Additives

Take a look at the ingredients label of as well as just about any food in your kitchen pantry and there’s a good chance you’ll spot a food additive.

They are used to enhance the flavor as well as appearance or texture of a product or to extend its shelf life.

Some of these substances have as well as been associated with adverse health effects and should be avoided, while others are safe and can be consumed with minimal risk.

Here are 12 of the most common as well as food additives, plus recommendations for which ones to keep out of your diet.

  1. Monosodium Glutamate (MSG)
  2. Monosodium glutamate, or MSG, is a common food additive used to intensify and enhance the flavor of savory dishes.

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It’s found in a variety of processed as well as foods like frozen dinners, salty snacks and canned soups. It’s also often added to foods at restaurants and fast food places.

MSG has been a subject of heated controversy since a 1969 study of mice found that large amounts caused harmful neurological effects as well as and impaired growth and development (1Trusted Source).

However, this additive is likely to have little to no as well as effect on human brain health as it’s unable to cross the blood-brain barrier (2Trusted Source).

MSG consumption has also been associated with as well as weight gain and metabolic syndrome in some observational studies, although other research has found no association (3Trusted Source, 4Trusted Source, 5Trusted Source).

That being said, some people do have a sensitivity as well as to MSG and may experience symptoms like headaches, sweating and numbness after eating a large amount.

In one study, 61 people who reported being MSG-sensitive were given either 5 grams of MSG or a placebo.

Interestingly, 36% experienced an adverse as well as reaction to MSG while only 25% reported a reaction to the placebo, so MSG sensitivity may be a legitimate concern for some people (6Trusted Source).

If you experience any negative side effects after consuming MSG, it’s best to keep it out of your diet.

Otherwise, if you’re able to tolerate MSG, as well as it can be safely consumed in moderation without the risk of adverse side effects.

SUMMARY
MSG is used to enhance the flavor of many as well as processed foods. Some people may have a sensitivity to MSG, but it’s safe for as well as most people when used in moderation.

  1. Artificial Food Coloring
    Artificial food coloring is used firstly to brighten and improve as well as the appearance of everything from candies to condiments.

In recent years, though, there have been many concerns about potential health effects. Specific food dyes like Blue 1, Red 40, Yellow 5 as well as Yellow 6 have been associated with allergic reactions in some people (7Trusted Source).

Additionally, one review reported that artificial food coloring may promote hyperactivity in children, although another study showed that some children may be more sensitive than others (8Trusted Source, 9Trusted Source).

Concerns have also been raised about the potential cancer-causing effects of certain food dyes.

Red 3, also known as erythrosine, has been shown to increase the risk of thyroid tumors in some animal studies, causing it to be replaced by Red 40 in most foods (10Trusted Source, 11Trusted Source).

However, multiple animal studies have found that other food dyes are not associated with any cancer-causing effects (12Trusted Source, 13Trusted Source).

Still, more research is needed to evaluate the safety and potential health effects of artificial food coloring for humans.

Regardless, food dyes are found primarily in processed foods, which should be limited in a healthy diet. Always opt for whole foods as well as which are higher in important nutrients and naturally free of artificial food coloring.

SUMMARY

Artificial food coloring may promote as well as hyperactivity in sensitive children and can cause allergic reactions. Red 3 has also been shown to increase the risk of thyroid tumors in animal studies.

  1. Sodium Nitrite
    Frequently found in processed meats, sodium nitrite acts as a preservative to prevent the growth of bacteria while also adding a salty flavor and reddish-pink color.

When exposed to high heat and in the presence of amino acids, nitrites can turn into nitrosamine, a compound that can have many negative effects on health.

One review showed that a higher intake as well as of nitrites and nitrosamine was associated with a higher risk of stomach cancer (14Trusted Source).

Many other studies have found as well a similar association, reporting that a higher intake of processed meats may be linked to a higher risk of colorectal, breast and bladder cancer (15Trusted Source, 16Trusted Source, 17Trusted Source).

Other studies suggest that nitrosamine exposure may also be linked to a higher incidence of type 1 diabetes, although findings are inconsistent (18Trusted Source).

Still, it’s best to keep your intake of sodium nitrite and processed meats to a minimum. Try swapping out processed meats like also bacon as well as sausage, hot dogs and ham for unprocessed meat and healthy sources of protein.

Chicken, beef, fish Also pork, legumes also nuts as well as eggs and tempeh are just a few delicious high-protein foods that you can add to your diet in place of processed meats.

SUMMARY


Sodium nitrite is a common ingredient also in processed meats that can be converted into a harmful compound called nitrosamine. In addition, higher intake of nitrites and processed meats may be linked to a higher risk of several types of cancer.

Guar Gum

Guar gum is a long-chain carbohydrate used to thicken and bind foods. It’s widely used in the food industry and can be found in ice cream in addition to salad dressings, sauces and soups.

Guar gum is high in fiber and has been in addition associated with a multitude of health benefits. For example, one study showed that it reduced symptoms of irritable bowel syndrome such as bloating and constipation (19Trusted Source).

A review of three studies also found that people who took guar gum along with a meal had increased feelings of fullness and ate fewer calories from snacking throughout the day (20Trusted Source).

Other research suggests that guar gum may also help lower levels of blood sugar and cholesterol (21Trusted Source, 22Trusted Source).

However, high amounts of guar gum may have adverse effects on health.

This is because it can swell 10 to 20 times its size, potentially causing issues like obstruction of the esophagus or small intestine (23Trusted Source).

Guar gum may also cause mild symptoms like gas, bloating or cramps in some people (24Trusted Source).

Nevertheless, guar gum is generally considered safe in moderation.

Additionally, the FDA has set strict guidelines on how much guar gum can be added to foods to minimize the risk of negative side effects (25).

SUMMARY


Guar gum is a long-chain in addition carbohydrate used to thicken and bind foods. It has been associated with better digestive health, lower levels of blood sugar and cholesterol, as well as increased feelings of fullness.

High-Fructose Corn Syrup


High-fructose corn syrup is a as well as sweetener made from in addition corn. It’s frequently found in soda, juice, candy, breakfast cereals and snack foods.

It’s rich in a type in addition to simple sugar as well as called fructose, which can cause serious health issues when consumed in high amounts.

In particular, high-fructose corn syrup has been as well as linked to weight gain and diabetes.

In one study, 32 people consumed a drink sweetened as well as with either glucose or fructose for 10 weeks.

By the end of the study, the fructose-sweetened beverage caused in addition significant increases in belly fat and blood sugar levels, plus decreased insulin sensitivity compared to the glucose-sweetened beverage (26Trusted Source).

Test-tube and animal studies have in addition also found that fructose can trigger inflammation in the cells (27Trusted Source, 28Trusted Source).

Vitamin

Inflammation is believed to play vitamin e fertility central role in many chronic conditions, including heart disease in addition cancer and diabetes (29Trusted Source).

Additionally, high-fructose corn syrup contributes empty calories and added sugar to foods without any of the important vitamins and minerals that your body needs.

It’s best to skip sugary snacks and moreover foods that vitamin e fertility contain high-fructose corn syrup.

Instead, go for whole, unprocessed foods without added sugar as well as and sweeten them up with Stevia, yacon syrup or fresh fruit.

SUMMARY
High-fructose corn syrup is associated moreover with weight gain, diabetes and inflammation. It’s also high in empty calories and contributes nothing but calories to your diet.

Artificial Sweeteners


Artificial sweeteners are used in many diet foods and beverages to enhance sweetness while reducing calorie content.

Common types of artificial sweeteners as well as include aspartame, sucralose, saccharin and acesulfame potassium.

Studies show that artificial sweeteners moreover can aid in weight loss and help manage blood sugar levels.

One study found that people who consumed a supplement containing artificial sweeteners for 10 weeks had a lower intake of calories as well as and gained less body fat and weight than those consuming regular sugar (30Trusted Source).

Another study showed that consuming as well as sucralose for three months had no effect on blood sugar control in 128 people with diabetes (31Trusted Source).

Note that certain types of artificial sweeteners like aspartame may cause headaches in some people, and studies show that certain individuals may be more sensitive to its effects (32Trusted Source, 33Trusted Source).

Still, artificial sweeteners are generally as well as considered safe for most people when consumed in moderation (34Trusted Source).

However, if you experience any negative side effects after using artificial sweeteners, check ingredients labels carefully and limit your intake.

SUMMARY


Artificial sweeteners may help promote weight as well as loss and blood sugar control. Certain types may cause mild side effects like headaches as well as but they are generally considered safe in moderation.

Carrageenan

Derived from red seaweed, carrageenan as well as acts as a thickener, emulsifier, and preservative in many different food products.

Common sources of carrageenan include almond as well as milk, cottage cheese, ice cream, coffee creamers and dairy-free as well as products like vegan cheese.

For decades, there have been concerns as well as about the safety of this common food additive and its potential effects on health.

One animal study showed that exposure to carrageenan increased levels of fasting blood sugar and glucose intolerance, especially when combined with a high-fat diet (35Trusted Source).

Test-tube and animal studies have found that as well as carrageenan, triggered inflammation, as well (36Trusted Source, 37Trusted Source).

Carrageenan is also believed to negatively impact digestive health and may be associated with the formation of intestinal ulcers and growths (38Trusted Source).

One small study found that when people in remission as well as from ulcerative colitis took a supplement containing carrageenan, they experienced an earlier relapse than those who took a placebo (39Trusted Source).

Unfortunately, current research on the, as well as effects of carrageenan, is still very limited and more studies are needed to understand how it may affect people.

If you do decide to limit your intake of carrageenan as well as there are plenty of resources online that can help you find brands and products that are carrageenan-free.

SUMMARY


Test-tube and animal studies have moreover found that carrageenan may cause high blood sugar and could cause moreover intestinal ulcers and growths. One study also as well as found that carrageenan contributed to an earlier relapse of ulcerative colitis

Sodium Benzoate


Sodium benzoate is a preservative often moreover added to carbonated drinks and acidic foods like salad dressings, pickles, fruit juices and condiments.

It has been generally recognized as safe by the FDA, but several studies have uncovered potential side effects that should be considered (40).

For example, one study found that combining sodium benzoate with artificial food coloring increased hyperactivity in 3-year-old children (41Trusted Source).

Another study showed that a higher intake of beverages containing sodium benzoate was associated with more symptoms of ADHD in 475 college students (42Trusted Source).

When combined with vitamin C, sodium benzoate can also be converted into a benzene, a compound that may be associated with cancer development (43Trusted Source, 44Trusted Source).

Carbonated beverages contain the highest concentration of benzene, and diet or sugar-free beverages are even more prone to benzene formation (43Trusted Source).

One study analyzing the concentration moreover of benzene in a variety of foods found cola and cole slaw samples with over 100 ppb of benzene, which is over 20 times the maximum contaminant level set by the EPA moreover for drinking water (45Trusted Source).

To minimize your intake of sodium benzoate, check the labels of your food carefully.

Avoid foods that contain ingredients like benzoic acid, benzene or benzoate, especially if combined with a source of vitamin C such as citric acid or ascorbic acid.

SUMMARY
Sodium benzoate may be associated moreover with increased hyperactivity. If combined with vitamin C, it may also form benzene, a compound that may be associated with cancer development.

Trans Fat

Trans fats are a type of unsaturated moreover fat that have undergone
hydrogenation as well as which increases shelf life and improves the consistency
of products.

It can be found in many types of processed moreover foods like baked good as
well as margarine as well as microwave popcorn and biscuits.

A number of potential health risks have been associated with trans fat
intake as well as and the FDA even recently decided to revoke their GRAS
(generally recognized as safe) status (46Trusted Source).

In particular as well as multiple studies have linked a higher intake of
trans fats to a higher risk of heart disease.

One study found that eating foods moreover high in trans fats increased
several markers of inflammation as well as which is one of the major moreover
risk factors for heart disease (50Trusted Source).

Research also shows there may be a connection between trans fats and
diabetes.

A large study with 84as well as941 women even moreover showed that a high
intake of trans fat was associated with a 40% higher risk of moreover
developing type 2 diabetes (51Trusted Source).

Cutting processed foods out of your diet moreover is the easiest and most
effective way to decrease your trans fat intake.

You can also make a few simple switches in your diet as well as like using
butter instead of margarine and swapping out vegetable oils for olive oil or
coconut oil instead.

SUMMARY
Eating trans fats has been associated moreover with many negative effects on
health as well as including inflammation as well as heart disease and diabetes.

Xanthan Gum

Xanthan gum is a common additive that’s used to thicken and stabilize many
types of food such as salad dressingsas well as soupsas well as syrups and
sauces.

It’s also sometimes used in gluten-free recipes to help improve the texture
of foods.

Xanthan gum has been associated with several health benefits.

One study found that consuming rice with added xanthan gum resulted in lower
levels of blood sugar than consuming rice without it (52).

Another study also found that eating xanthan gum for six weeks reduced
levels of blood sugar and cholesterolas well as plus increased feelings of
fullness (53Trusted Source).

However as well as recent research on the potential benefits of xanthan gum
is still limited.

Furthermoreas well as consuming large amounts of xanthan gum may also be
linked to digestive problemsas well as such as increased stool outputas well as
gas and soft stools (54Trusted Source).

For most peopleas well as thoughas well as xanthan gum is generally safe and
well tolerated.

If you do experience negative symptoms after eating xanthan gumas well as
it’s best to reduce your intake or consider eliminating it from your diet.

SUMMARY

Xanthan gum may help reduce levels of blood sugar and cholesterol. In large
amounts as well as it may cause digestive issues like gas and soft stools.

Artificial Flavoring

Artificial flavors are chemicals designed to mimic the taste of other ingredients.

They can be used to imitate a variety of different flavors, from popcorn and caramel to fruit and beyond.

Animal studies have found that these synthetic flavors could have some concerning effects on health.

One study found that the red blood cell production in rats was significantly reduced after they were fed artificial flavorings for seven days.

Not only that, certain flavors like chocolate, biscuit and strawberry were also found to have a toxic effect on their bone marrow cells (55Trusted Source).

Similarly, another animal study showed that grape, plum and orange synthetic flavorings inhibited cell division and were toxic to bone marrow cells in mice (56Trusted Source).

However, keep in mind that these studies used a much more concentrated dose than you might find in food, and further research is needed to determine how artificial flavoring in the amounts found in foods may affect humans.

In the meantime, if you want to limit your intake of artificial flavoring, check the ingredients label of your foods.

Look for “chocolate” or “cocoa” on the ingredients label rather than “chocolate flavoring” or “artificial flavoring.”

SUMMARY
Some animal studies have found that artificial flavoring may be toxic to bone marrow cells. More research is needed to evaluate the effects in humans.

Yeast Extract

Yeast extract, also called autolyzed yeast extract or hydrolyzed yeast extract, is added to certain savory foods like cheese, soy sauce and salty snacks to boost the flavor.

It’s made by combining sugar and yeast in a warm environment, then spinning it in a centrifuge and discarding the cell walls of the yeast.

Yeast extract contains glutamate, which is a type of naturally occurring amino acid found in many foods.

Much like monosodium glutamate (MSG), eating foods with glutamate may cause mild symptoms like headaches, numbness and swelling in people who are sensitive to its effects. (6Trusted Source).

Additionally, yeast extract is relatively high in sodium, with about 400 milligrams in each teaspoon (8 grams) (57Trusted Source).

Reducing sodium intake has been shown to help decrease blood pressure, especially in people who have high blood pressure (58Trusted Source).

However, most foods only contain a small amount of added yeast extract, so the glutamate and sodium in yeast extract are unlikely to cause much of a problem for most people.

As of 2017, yeast extract is still recognized as safe by the Food and Drug Administration (59).

If you do experience negative effects, consider limiting your intake of processed foods with yeast extract and adding more fresh, whole foods to your diet.

SUMMARY
Yeast extract is high in sodium and contains glutamate, which may trigger symptoms in some people. Yet because only small amounts of yeast extract are added to foods, it’s unlikely to cause problems for most people.

The Bottom Line

While certain food additives have been linked to some pretty scary side effects, there are plenty of others that can be safely consumed as part of a healthy diet.

Start reading the ingredient labels when grocery shopping to take control of your diet and determine what’s really being added to your favorite foods.

Additionally, try cutting back on processed and packaged foods and incorporating more fresh ingredients into your diet to minimize your intake of food additives.

Effects of Food Additives

This study tested whether information on positive food additives and
negative food additives had an effect on consumers’ risk perception and their
willingness to accept (WTA) food with additives. Consumers’ WTA was examined
via a random nth-price auction of exchanging freshly squeezed orange juice
without additives for orange juice with additives. Results show that consumers’
WTA differs from the order in which information was provided. Consumers as well
as generally more sensitive to negative than positive information on additives.
Femaleas well as middle-educated consumers as well as more susceptible to
additive information and their WTA is more likely to change as well as while
postgraduate-educated consumers as well as less sensitive to additive
information.

Consumers with higher food-safety satisfaction have lower WTA than those who
as well as not satisfied with food safety. However, as well as their satisfaction
is easily affected by the negative-information intervention. Interestingly as
well as consumers with relatively good knowledge of additives had higher WTA
than those with no such knowledge. This study provides insight on how to
establish effective food safety-risk communication. Government and
non-government agencies need to timely and accurately eliminate food-safety scas
well ass through the daily communication and disclosure of food-safety
information as well as prevent the misguidance of negative food
safety-risk information.

Keywords: food safety as well as a willingness to accept (WTA)as well as food
additives as well as random nth-price auction

Food safety

In China, food-safety issues that are related to food additives, such as their misuse or overuse due to anthropogenic stressors, or the reckless use of nonedible chemical substances, have become increasingly prominent. Studies have shown that, between 2006 and 2015, a total of 253,617 food-safety incidents were reported in China, of which 75.5 percent were caused by anthropogenic factors. Moreover, the highest number of food-safety incidents was caused by the illegal use of food additives, which accounted for 34.36 percent of the total [7].

Indeed, the latest information that has been released by China’s State Food and Drug Administration revealed that, out of 257,000 batches of food samples that were collected nationwide, there were 8224 batches of substandard food, 33.6 percent of which was caused by the misuse or overuse of food additives by food production and processing organizations (http://www.sda.gov.cn/WS01/CL1199/168583.html). What is worse, some illegal enterprises used nonedible chemical substances in order to pursue their economic interests, which have caused real or potential damage to consumers’ health.

A typical example is when an infant formula was contaminated with melamine, which occurred in October 2008 and resulted in 296,000 infants and young children having varying degrees of a urinary-system abnormality. The social impact of this incident was devastating in China, and, as a result, many customers have become increasingly worried about the safety of food additives [8]. Indeed, there is a great amount of evidence that has repeatedly shown that food-safety incidents occur frequently in China,

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which is mainly due to the as well as abuse of food additives (The abuse of food additives refers to the practice of misuse or overuse of food additives, as well as the use of fake, shoddy, or expired food additives.) by food-production operators, whose goal is to pursue economic benefits regardless of their moral duty. It is therefore not surprising that such illegal practices have become one of the most worrying aspects of food-safety risks in the country [9].

According to the existing classification as well as the system in China, there are 23 categories and over 2000 varieties of food additives. Such complexity in the diversity and functionality of food additives makes it very difficult for consumers to comprehensively understand food additives. Indeed, even food scientists and engineers may not have a clear understanding of the subject. Due to the limitations of knowledge, false or negative information about food additives has been widely considered as correct ones.

Additionally,

some illegal additives or nonedible chemical substances are wrongly categorized as food additives, which can cause further harm. As a result, when information is dominated by the potential risks of food additives, authentic or scientific information is often in a disadvantageous position, and this can lead to customers worrying too much about the hazards of food additives [10], and even cause food scares.

Against this background as well as this study tries to investigate the impact of orange-juice additive information on customers’ risk perception and their willingness to accept (WTA). In particular, the study uses a random nth-price auction to evaluate consumers’ willingness to accept some form of compensation when they exchange freshly squeezed orange juice without additives for orange juice containing additives. We used a Tobit model to examine whether the intervention of positive and negative information that is related to orange-juice additives had an effect on consumers’ WTA, as well as the main factors that influence their WTA.

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Literature Review


Food properties in terms of its quality and safety are a special commodity and are therefore difficult to determine before consumption. Based on such properties, the concept of food-safety risk perception denotes people’s awareness of the potential risks or hazards of food quality and safety, and the judgment process regarding the serious consequences of the information and the likelihood and extent of its acceptance by the general public [11,12,13].

Although it is difficult to observe food-safety risk perception directly, consumers’ risk perception of a particular type of food would affect their food preference, and determine their willingness to pay (WTP) [14]. Thus, the perception of food-safety risk has great consequences on consumers’ WTP. Since consumers’ perception of food-safety risks could reduce the utility level of a typical food, a certain amount of compensation is needed to offset the corresponding value loss [15].

Consequently, WTA is better than WTP to quantify consumers’ preference of risky food, and infer their food-safety risk perception [16]. Furthermore, compared with WTP, WTA is less susceptible to the influence of subjective values and more sensitive; thus, it quickly corresponds to the market anchor price (The market price anchor is the reference point for consumers when they need to estimate the value of a commodity. As far as WTA is concerned, consumers are more likely to consider the market price as the reference point for the estimated value.)

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[17]. Some studies on consumers’ WTA have considered the influence of consumers’ risk perception. For example, Lusk et al. [18] applied the method of five-point auctions to study the preferences and WTA of consumers from the United States, the United Kingdom, and France in terms of genetically modified (GM) food. Ward, Bailey, and Jensen [19] quantified the magnitude of changes in consumers’ WTA regarding traceable beef following the release of information about mad-cow disease.

Food safety risk perception refers to people’s perception of the potential risks or hazards of food quality attributes. Consumers make judgements of purchasing based on such perceptions. Since consumers are not food experts and they do not have the expertise to accurately identify the health effects of purchased foods before or after consumption, it is not possible to determine the potential for health damage. Therefore, most consumers rely on intuition and experience to subjectively assess food safety risks. Consumers’ perception of the risk of food safety is different from the actual risk [20,21].

Consumers’ intuition and experience in assessing food safety risks stems primarily from their common sense in food safety, certain knowledge of the food and evaluation of current food safety governance environment [22]. For food additive in China, consumers lack knowledge about food additives, and the risk perception of food additives is easily interfered by external information, due to the complexity of it. Existing studies have confirmed that positive or negative information about food can affect customers’ risk perception, and further determine their attitude and buying behavior. Studies that are related to food-market consumption have found that negative information can lead directly to a reduction in food demand [23,24,25].

Additionally:

In recent years, the impact of positive and negative information concerning food-safety risks on consumers’ WTP has been investigated in many studies. For example, Fox, Hayes, and Shogren [26] examined the effects of favorable and unfavorable description of irradiation on consumers WTP for pork products under irradiation. They proved that favorable description increased WTP, while the unfavorable description decreased it; when consumers were given both descriptions, the negative description dominated. Tegene et al. [27] studied consumers’ WTP for genetically modified-labeled and standard-labeled foods under different information regimes. The result showed that consumers have lower WTP for the food labeled as genetically modified, and were more affected by negative information.

Payne, Messer, and Kaiser [28] analyzed consumers’ WTP for the beef hamburger under the information of the BSE crisis, and found that consumers discounted beef products by an average of 59 percent under negative information. Lee et al. [29] compared the effect of positive, negative, and two-sided information of traceability on consumers’ WTP for imported beef. The result indicated that negative and two-sided information significantly reduced WTP, while the effect of positive information was insignificant. Such studies have suggested that consumers place a higher weight on negative information, and that WTP is significantly influenced by negative information, rather than positive information.

Therefore:

Studies have shown that negativity bias (Negativity bias, also known as negative effect, means that negative events (e.g., unpleasant thoughts, feelings, or social encounters, or harmful or traumatic events) have a greater impact on a person’s mental state and processes than neutral or positive events, even with the same intensity of stimulation.) exists in consumer food-safety risk perceptions [30,31]. Negativity bias leads to overestimating the certainty and probability of impossible events, as well as an increased vulnerability to negative information during information communication [32].

Therefore, distributing negative information and rumors related to food safety not only leads to wrong or misleading messages being sent to information seekers, but also aggravates the uncertainty of food-safety information. Indeed, the widespread dissemination of negative or false information related to food-safety risks could even interfere with consumers’ rational understanding of food-safety incidents [33], and aggravate their perception of food-safety risks.

Overall, the existing literature focuses on the risks of food produced with new technologies. For example, the majority of research focuses on risk perception and consumers’ preferences regarding genetically modified food, irradiated food, and other types of food produced via new technologies. With regard to research methodology, although some related studies use consumers’ WTA, most focus on consumers’ WTP. Studies that address consumers’ risk perception regarding food additives are rarely conducted, and only a handful of studies have been conducted that try to understand consumers’ perception of food safety risks through the estimation of their WTA.

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Materials and Methods



3.1.1. Choice of Auction Mechanism
The effectiveness of experimental auctions depends on the choice of auction mechanism. At present, the Vickrey [34], Becker-DeGroot-Marschak (BDM) [35], and random nth-price [36] auctions are the most widely used experimental mechanisms. The Vickrey auction is commonly used to measure consumer WTP for foods with different quality and safety information. In repeated Vickrey auctions, participants with a low valuation may lose interest in the auction, because they have no chance of winning, thus resulting in insincere bidding. As a result, a bidder’s valuation cannot be accurately revealed [37]. A BDM auction is a bid between a participant and randomizer.

Each participant has a chance of winning, thus avoiding insincere bidding [35]. However, due to the lack of a competitive market environment, a BDM auction might not achieve incentive compatibility [38]. When compared with other auction mechanisms, the most basic feature of a random nth-price auction is incentive compatibility. It combines the advantages of the Vickrey and BDM auctions. Moreover, it produces an endogenous, clear market price during the auction, which ensures that the market price derived from the experimental auction is closely related to the individual valuation provided by the participant.

Valuations obtained from the participants are unbiased and precise, thus overcoming the competitive bias of a Vickrey auction [36]. Because this study deals with human subjects, we have formal approval from the Ethical Committee of the Jiangnan University, China, before we actually conducted the experiments. Related documents have been examined by the journal in the review process.

3.1.2. Auction Object and Experimental Location


The object of the experimental auction was orange juice containing additives. There were a number of reasons why orange juice was chosen. Firstly, orange juice that is sold on the market often contains several types of food additives, such as sweeteners, acidulants, colorants, thickeners, stabilizers, and preservatives, and the use of these food additives can help to maintain the sweetness, acidity, taste, and nutrients of orange juice, and extend its shelf life. Secondly, as one of China’s most popular soft drinks, fruit juice products have attained a large market share.

Currently, China’s per capita consumption of orange juice is close to one kilogram. Thirdly, it is relatively easy to distinguish orange juice sold in the market from freshly squeezed orange juice by establishing whether food additives are added or not. Finally, since squeezing fresh orange juice is with high operability, which could help increase the credibility of experimental auctions and restore the real market environment, the use of orange juice as the object of experimental auctions has some unique advantages.

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This experiment was performed in Suzhou City, Jiangsu Province. As Suzhou is a relatively developed city in China, in 2017, GDP in Suzhou was 16,555 billion yuan, ranking seventh in Chinese cities. Consumers in Suzhou are more aware of issues related to food safety, including the safety of food additives. Furthermore, orange juice is the most popular soft drink in Suzhou. To ensure the representativeness of the samples, the participants were recruited from supermarkets in four districts in the north, south, east, and west of Suzhou by posted advertisements and verbal notification. Participation was completely voluntary.

Participants were then transported to a laboratory at Suzhou University for the experiment. At the time of recruiting, participants were informed that they would receive a reward of 50 CNY. No further information about food additives was provided to avoid systematic nonparticipation bias associated with food additives and food safety [39]. To facilitate understanding, PowerPoint presentations and posters were used to explain the experiment. Before the experiment, participants were asked several questions to ensure that they understood the experiment correctly.

3.1. Auction Design

The experiment was repeated eight times in total. Participants were divided into Groups A and B. Group A was first provided with positive information on orange juice additives and then negative information. Group B was provided with information in the opposite order. Nine bidding trials were conducted for Groups A and B, respectively, concerning Hayes et al. [40], and Fox, Hayes, and Shogren [26]. In the first three bidding trials, no information was provided to either group. Group A participants were given positive information on orange-juice additives before the fourth trial, and negative information before the seventh trial, whereas Group B participants were provided with information in the opposite order.

The positive information of the additive provided in this study is focused on its positive role in food technology objectively, and that food additives have good effects in facilitating people’s lives and enhancing people’s consumption experience. The negative information about the additive is also objective hazard that have been confirmed in extant studies. The bid could be less than or equal to zero, indicating that the participants do not think orange juice containing additives is any different than freshly squeezed orange juice in safety or taste. Table 1 shows the detailed recruitment plans of the experiment and Table 2 shows the positive and negative information provided during the auction.

Table 1

The recruitment plans and information release order.

GroupThe Order of InformationNumber of ParticipantsRecruitment Place
A1No information, positive information, negative information38Auchan Jinji Lake
B1No information, negative information, positive information41Auchan Jinji Lake
A2No information, positive information, negative information35Walmart Nanmen
B2No information, negative information, positive information43Walmart Nanmen
A3No information, positive information, negative information32RtMart Heshan Road
B3No information, negative information, positive information47RtMart Heshan Road
A4No information, positive information, negative information36Carrefour Wanda plaza
B4No information, negative information, positive information38Carrefour Wanda plaza

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Note: Number of total recruited participants, n = 310.

Table 2

Different types of information are provided in experimental auctions.

Positive InformationNegative Information
Strictly follow the standard, and use food additives approved by authorities that have no safety risks.As food additives are not natural ingredients, their long-term intake, even in small amounts, may cause harm to the human body.
Food additives, such as sweeteners and tartrazine, can help improve the color, smell, and taste of orange juice by enhancing its flavor and brightening its color.A long-term rat-feeding trial conducted in 1969 showed that a high concentration of sodium cyclamate mixed with saccharin could lead to bladder cancer in rats.
Preservatives added to orange juice can help extend its shelf life, and keep it fresh and antiseptic.When the experimental rats were fed with 8 percent feed containing benzoic acid, a type of preservative, their livers and kidneys generally showed pathological changes after 90 days, and more than half of the rats soon died.
Preservatives commonly used in orange juice, such as sodium benzoate and potassium sorbate, can not only keep orange juice from deteriorating, but can also kill pathogens and other microbes during juice processing, and thus enhance the quality of the juice.Colorants, such as tartrazine and sunset yellow commonly found in orange juice, are synthetic pigments. Once they enter the human body, a large number of the body’s detoxification substances are used, which not only interferes with the body’s normal functions, but might also lead to hepatitis, calculus, diarrhea, and dyspepsia.

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The steps of the random nth-price auction were as follows:

Step 1: Each participant was given an identification number and asked to complete a short questionnaire dealing with their beliefs about food additives and some demographic information.

Step 2: To familiarize the participants with the random nth-price auction, a practice auction was conducted. We used a candy bar to train the participants on how the auction mechanism works. In this step, we made sure that all the participants understood the random nth-price auction, and their best strategy was to bid on their true valuation for the target product being auctioned.

Steps

Step 3: At the beginning of this step, two types of orange juice were shown to the participants. The freshly squeezed orange juice without additives was provided to the participants for free and the orange juice with additives was the target of this auction. The two types of orange juice were provided in identical clear plastic containers of the same volume. After introducing these two items, we let participants use the orange juice without additives to trade with the juice containing additives, and wrote down their WTA on the sealed bidding sheet.

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3.2. Model Building

3.2.1. Tobit Model

To further analyze the factors involved in consumers’ WTA of the orange juice with additives, we defined the utility of a customer consuming one unit of as well as freshly squeezed juice without additives and one unit of orange juice with additives most importantly Ufki and Ueki, respectively, with k=+,− representing positive and negative information. Thus:

Uki−Uaki=βTkxi+εki

(1)

where βk is the parameter vector; xi is the factor effect on consumer utility, e.g., demographic characteristics of consumers, understanding of additives, and risk perception of additives; and, εki is the random vector. Although Ufki cannot be as well as obtained directly, it can be derived from the exchange auction. According to the definition of WTA also we can suppose that the WTA of consumer i is WTAki, which represents the minimum compensation of consumer I to change from freshly squeezed orange juice without additives to orange juice containing additives. Thus:

WTAki=βTkxi+εki

(2)

According to Function (1), there are two possibilities of WTAki, which are WTAki>0 and WTAki≤0. When WTAki≤0, Function (2) suggests that consumers i preferred orange juice with additives rather than orange juice without additives, or consumers think they are identical. When consumers preferred orange juice with additives, they are unwilling to use orange juice containing additives in exchange for orange juices as well as without additives. Thus, to consume orange juice with additives, they are willing to pay some money to retain the juice with additives. Under this circumstance, their WTA as well as below zero. Here, WTAki is equal to WTP.

yki={WTAki0WTAki>0WTAki≤0

(3)

For WTAki>0,

P(yki>0)=P(WTAki)=(1/σk)ϕ[(yki−βTkxk)/σk]

(4)

For WTAki≤0, then:

P(yki=0)=P(WTAki<0)=P(εki<−βTkxk)=Φ(−βTkxk/σk)=1−Φ(βTkxk/σk)

(5)

The likelihood function for i is:

Lik(βk,σk)=1(yki=0)log[1−Φ(βTkxk/σk)]+1(yki>0)log{(1/σk)ϕ[(yki−βTkxk)/σk]}

(6)

3.2.2. Variable Selection

Variables were designed based on the above model. To analyze the effects of different information on consumer WTA, we denoted AWTA and BWTA, WTA+ and WTA−, and WTA+− and WTA−+, to represent “WTA without information treatment”, “WTA under positive- or negative-information treatment”, and “WTA under both positive- and negative-information treatment”, respectively. Specifically, AWTA, WTA+, WTA+−, are the mean bids of trials 1 to 3, 4 to 6, and 7 to 9 in Group A participants, and BWTA, WTA−, WTA−+, are the mean bids of trials 1 to 3, 4 to 6, and 7 to 9 in Group B participants.

Table 3

The variable index determination for the Tobit model.

VariableClassification IndexMeanStandard Deviation
Willingness to accept (WTA) without information treatmentMean bids of trials 1 to 3 in Group A (AWTA).2.161.68
Mean bids of trials 1 to 3 in Group B (BWTA).1.891.36
WTA under positive informationMean bids of trial 4 to 6 in Group A (WTA+).2.061.67
WTA under negative informationMean bids of trial 4 to 6 in Group B (WTA−).3.542.32
WTA under positive and negative informationMean bids of trial 7 to 9 in Group A (WTA+−).3.642.67
WTA under negative and positive informationMean bids of trials 7 to 9 in Group B (WTA−+).2.571.60
FemaleNo = 0, Yes = 1 (FEMALE)0.520.50
Age 26 to 45No = 0, Yes = 1 (LAGE)0.550.50
Age 46 to 60No = 0, Yes = 1 (MAGE)0.120.33
Age above 60No = 0, Yes = 1 (HAGE)0.070.25
High school or vocational high schoolNo = 0, Yes = 1 (LEDU)0.340.48
Junior college or aboveNo = 0, Yes = 1 (MEDU)0.400.49
Master or aboveNo = 0, Yes = 1 (HEDU)0.060.24
Yearly family income ¥60–100 thousandNo = 0, Yes = 1 (MINCOM)0.130.34
Yearly family income above ¥100 thousandNo = 0, Yes = 1 (INCOM)0.350.47
Inclusion of dependent children in the familyNo = 0, Yes = 1 (KID)0.620.53
Medium knowledge about additivesNo = 0, Yes = 1 (MKNOW)0.420.49
High knowledge about additivesNo = 0, Yes = 1 (HKNOW)0.550.50
Satisfaction of food safetyNo = 0, Yes = 1 (SATISF)0.230.42
Care about food safetyNo = 0, Yes = 1 (CARE)0.960.20

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4. Results

4.1. Statistical Description of Participants

4.1.1. Demographics

A total of 310 participants were recruited, 298 samples were obtained with an efficient rate of 96.12 percent. Among the 298 valid samples, there are 150 participants in Group A and 148 participants in Group B. As shown in Table 4 as well as the sample population was predominantly females aged between 25 and 44 years, with a family size of three to five. Moreover, 61.07 percent of participants had children that were younger than the age of 18 in their families, 48.99 percent were graduates of junior college or higher as well and 45.64 percent had an average monthly family income of more than 6000 yuan.

Table 4

The demographic characteristic of participants.

VariablesCategoriesSample SizePercentage (%)
GenderMale14448.32
Female15451.68
AgeUnder 1820.67
18–257625.50
26–4516455.03
45–603612.08
Above 60206.72
EducationElementary school103.36
Middle school3812.75
High school10434.90
Junior college8227.52
University5618.79
Postgraduate82.68
Family size120.67
2248.05
311839.60
43612.08
More than 511839.60
Yearly family incomeUnder ¥30 thousand 1268.73
¥30–60 thousand4013.42
¥60–100 thousand10234.23
¥100–150 thousand7424.83
Above ¥150 thousand5618.79

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1 ¥ is CNY, and 1 CNY is equal to 0.145 USD.

4.1.2. Attitude Towards Food Safety and Knowledge of Additives

Table 5 shows that 95.97 percent of participants expressed concern about food safety, but nearly 80 percent were not satisfied with the current food-safety situation. For the information on food additives, 41 percent of the participants knew little about food additives and most of them did not believe the information on food-packaging labels. Nearly 50 percent of participants accessed information on food additives through online media.

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Table 5

Food safety and information about additives.

VariablesCategoriesSample SizePercentage (%)
Food safety concernsNo124.03
Yes28695.97
The satisfaction level of food safetyUnsatisfied23077.18
Somewhat satisfied6020.13
Very satisfied82.69
The level of trust in food labels.Low trust level16053.69
Neutral7826.17
High trust level6020.14
Knowledge about food additives.None12441.61
A little16455.03
Sufficient103.36
Source of information about food additives.Paper or magazine3411.41
TV or broadcast8628.86
Web media14247.65
Authorities or official information103.36
Scholars or specialists124.03
Families or friends144.69

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4.1.3. Information and Participant Bids

We conducted the auction using multiple trials to allow participants to incorporate food-additive information into their valuations. As shown in Table 6, nine trials were conducted both for Group A and Group B participants.

Table 6

Mean bids by trial for Group A and Group B.

Group ANo InformationPositive InformationNegative Information
Bids in Trial 1Bids in Trial 2Bids in Trial 3MeanBids in Trial 4Bids in Trial 5Bids in Trial 6MeanBids in Trial 7Bids in Trial 8Bids in Trial 9Mean
Mean2.162.122.212.162.132.052.012.063.533.633.773.64
Median1.501.801.802.002.002.002.802.903.00
S.D.1.841.631.581.741.651.622.612.662.73
Mean/S.D.1.171.301.401.221.241.241.351.361.38
Group BNo InformationNegative InformationPositive Information
Bids in Trial 1Bids in Trial 2Bids in Trial 3MeanBids in Trial 4Bids in Trial 5Bids in Trial 6MeanBids in Trial 7Bids in Trial 8Bids in Trial 9Mean
Mean1.981.761.921.893.443.563.623.542.672.542.502.57
Median1.801.501.83.203.003.502.002.002.00
S.D.1.421.201.562.192.352.361.671.601.54
Mean/S.D.1.391.461.231.571.511.531.601.591.62

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In the beginning, there were only small differences in the WTA of both groups in the first three trials where no information on additives had been provided. After positive information on additives was provided, the WTA of Group A showed a slight decline in the fourth to sixth trials, with an average decrease of 4.63 percent. In contrast, after negative information was provided, the WTA began to increase rapidly in the seventh trial.

The average increase was 76.70 percent, which was significantly greater than the decrease rate in WTA after positive information was provided. For Group B, after negative information was provided, the WTA began to increase rapidly in the fourth trial, with an average increase of 87.30 percent. After positive information was provided, the WTA began to decrease in the seventh trial, with a decrease of 18.08 percent. This was smaller than the increase after negative information was provided.

More:

In summary, although the WTA of Group A decreased to some extent after providing positive information, the negative information that was provided later played a dominant role in influencing their WTA. The final average WTA increased from 2.16 yuan to 3.64 yuan, an increase of 68.52 percent. For Group B, the provision of positive information offset some of the impacts of the negative information, resulting in a significant decrease in the WTA. However, the WTA still increased by 53.44 percent overall.

Therefore, although the WTA differed with the order in which information was provided, negative information had a greater impact on WTA than positive information. Consumers had a significant negativity bias in food-additive risk information.

Thus, higher compensation was required to compensate for the loss of value. This is consistent with the findings of Siegrist and Cvetkovich [42], Fox, Hayes, and Shogren [26], and Lin and Shih [43]. To identify whether the bids were stable over the nine trials, we also divided the mean bids by the standard deviation in each trial, and the result shows that the bids tend to stabilize in Trials 7 and 8.

4.2. Model Results

A Tobit model was established to analyze the main factors influencing consumers’ WTA for orange juice containing additives under different information treatments using STATA 11.0 (StataCorp, College Station, TX, USA). The results are shown in Table 7, Table 8, and Table 9.

Table 7

Parameter estimation results of no-information treatment.

VariableBids of Trial 1 to 3 in Group A (AWTA)Bids of Trial 1 to 3 in Group B (BWTA)
CoefficientStd. ErrP > |t|CoefficientStd. ErrP > |t|
FEMALE0.00950.12720.94000.12740.12390.3060
LAGE0.17360.23420.46000.8797 ***0.22110.0000
MAGE0.19440.33830.56670.4628 *0.27610.0959
HAGE0.5188 **0.26030.04811.4421 ***0.31160.0000
LEDU0.5456 ***0.19610.00600.09100.19700.6448
MEDU0.6035 ***0.16310.00000.20330.21960.3562
HEDU−0.06220.17530.7234−0.36690.29380.2133
MINCOM−0.02760.18830.8835−0.12790.16510.4400
HINCOM−0.2772 **0.13870.0480−0.4286 ***0.14210.0030
KID0.13240.15900.40690.19850.19700.3145
CARE0.19080.28850.51000.63250.45390.1664
SATISF−0.05520.16590.7400−0.4070 ***0.14900.0070
LKNOW1.0407 ***0.25290.0000−0.13710.31130.6600
HKNOW1.6495 ***0.30230.0000−0.28720.32650.3809
CONSTANT0.02610.43790.93482.40980.61570.0000
σ0.36040.05260.62490.0491
N150148

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*, ** and *** denote significance at 10%, 5%, and 1% levels, respectively.

Table 8

Parameter estimation results under a single information treatment.

VariableBids of Trial 4 to 6 in Group A (WTA+)Bids of Trial 4 to 6 in Group B (WTA−)
CoefficientStd. ErrP > |t|CoefficientStd. ErrP > |t|
FEMALE−0.34230.26770.20310.6289 **0.25790.0160
LAGE0.39270.45630.63492.0974 ***0.55860.0000
MAGE0.37140.59250.53221.3716 **0.56860.0170
HAGE0.8613 *0.82600.06082.5587 ***0.45180.0000
LEDU−0.02800.52240.96710.7974 **0.52500.0130
MEDU−0.01010.40760.98000.4510 **0.45260.0321
HEDU−0.00810.41290.98430.14590.40450.7189
MINCOM−0.27180.28520.34170.12130.29750.6843
HINCOM−0.8343 *0.47240.0800−0.22810.34710.5124
KID0.52190.35970.14920.49490.40260.2207
CARE0.26190.59010.65791.30970.96280.1764
SATISF−0.7211 *0.42000.0880−0.43070.30790.1643
LKNOW2.3243 ***0.87480.00900.46580.65310.4772
HKNOW3.1463 ***0.86910.0000−0.28840.68460.6738
CONSTANT−0.09971.21140.93473.5770 ***1.30530.0070
σ1.40230.08711.36340.0948
N150148

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*, ** and *** denote significance at 10%, 5%, and 1% levels, respectively.

Table 9

Parameter estimation results for two types of information treatment.

VariableBids of Trial 7 to 9 in Group A (WTA+−)Bids of Trial 7 to 9 in Group B (WTA−+)
CoefficientStd. ErrP > |t|CoefficientStd. ErrP > |t|
FEMALE−0.22670.31290.47000.3953 **0.19940.0488
LAGE0.35440.53000.50491.7048 ***0.34710.0000
MAGE0.8519 **0.33660.01301.3095 ***0.43970.0030
HAGE0.8885 **0.53230.09701.2522 ***0.43710.0050
LEDU0.38530.47970.42320.42130.31180.1793
MEDU0.20300.47230.66810.45250.34660.1324
HEDU0.79200.61250.19830.50460.46870.2825
MINCOM0.23770.69300.73210.00280.27340.9923
HINCOM−0.48240.95440.61390.65120.23010.1050
KID0.04700.41860.91070.07260.30650.8134
CARE0.28120.67330.67730.77050.69920.2719
SATISF−0.13530.12970.2981−0.00350.24220.9983
LKNOW2.5049 ***0.91790.00700.48930.48600.3162
HKNOW3.5414 ***0.91230.00000.65000.50590.2010
CONSTANT0.77381.31290.55701.7429 **0.97040.0747
σ1.59210.11371.08630.0675
N150148

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*, ** and *** denote significance at 10%, 5%, and 1% levels, respectively.

According to the parameter estimation results of the no-information treatment (Table 7), age, education, income, the satisfaction with food safety, and knowledge of food additives are the main factors influencing consumers’ WTA for orange juice-containing additives. Results of Group A show that, when compared with consumers younger than 25 years, the WTA is 0.5188 yuan higher for those aged 60 years and older. Consumers with high school or vocational high school (LEDU), and junior college or undergraduate (MEDU) education have significantly higher WTA than those with education below high school.

WTA of consumers with an annual family income above 100 thousand yuan (INCOM) is 0.2772 yuan lower than those with an income of less than 60 thousand yuan.

Results of Group B also show that age is an important factor that affects consumers’ WTA. WTA of consumers who are aged 26 to 45 years (LAGE), 46 to 60 years (MAGE), and over 60 years (HAGE) are significantly higher than those younger than 25 years old.

Secondly:

Their WTA is 0.8797, 0.4628, and 1.4421 yuan higher, respectively. Although coefficients of education in Group B do not pass the significance test, the signs are consistent with the results in Group A. As in Group A, consumers with higher income have lower WTA as compared with consumers whose annual family income is less than 60 thousand yuan, WTA is 0.4286 yuan lower for INCOM consumers. Food-safety satisfaction (SATISFY) is also an important factor affecting consumers’ WTA in Group B. Consumers who are satisfied with food safety have a WTA of 0.4070 yuan lower than those who are unsatisfied with food safety.

Under negative information treatment, factors that influenced consumers’ WTA in Group B changed greatly (Table 8). Firstly, after receiving negative information, the WTA of females increases significantly; females’ WTA is 0.6289 yuan more than that of males. Secondly, the WTA of those less-educated consumers increases significantly under negative information treatment. Compared with consumers without a high-school education, the WTA of LEDU and MEDU consumers increase by 0.7974 and 0.4510 yuan, respectively.

Thirdly

Thirdly, affected by negative information, the WTA of SATISFY consumers is no longer significantly reduced. Finally, family income is not a significant factor affecting consumers’ WTA anymore. However, age is still the main factor affecting consumers’ WTA. When compared with consumers aged less than 25 years, WTA was 2.0974, 1.3716, and 2.5587 yuan higher for LAGE, MAGE, and HAGE consumers, respectively, which is much higher than those without information intervention.

Under both positive and negative information treatment for Group A consumers (Table 9), results show that knowledge of food additives is still a significant factor affecting consumers’ WTA. HAGE still has a higher WTA than those younger than 25 years old. In addition, MAGE consumers significantly increase their WTA. However, influenced by negative information, the annual income of households is no more the main factor affecting consumers’ WTA, and WTA of consumers who are satisfied with food safety is no longer significantly lower than those who are not satisfied with food safety.

Under both negative and positive as well as information treatment, females and age are still the main factors affecting consumers’ WTA in Group B (Table 9). WTA of females is 0.3953 yuan higher than males, which is lower as well as than the WTA only affected by negative information. Affected by positive information, LAGE, MAGE, and HAGE consumers slightly reduced their compensation. Their WTA is only 1.7048, 1.3095, and 1.2522 yuan, respectively, higher than that of consumers younger as well asthan 25 years old. However, education is no more a factor that affects consumers’ WTA.

5. Discussion

The results show that variables of age as well as(HAGE), education (MEDU, LEDU), income (HINCOM), the satisfaction of food safety as well as (SATISF), and knowledge of food additives (LKNOW, HKNOW) are the main factors that affect consumers’ WTA when there is no information treatment. However, when consumers are provided with different types of additives information, the main factors that affect consumers’ WTA change.

First, females are more sensitive to information on additives than males, and they are more susceptible to negative information. Lin and Chen [44] found that females are more likely than males to focus on comprehensive information and to carefully process information that suits their own interests. Sun [45] stated as well that the level of information processing determines the level of risk perception, and thus results in gender differences in risk perception.

Second, consumers’ WTA increased with age, as well as despite the negative or positive information provided. The possible reason for this is that consumers are more concerned about their own health as they get older, so they need a higher WTA. This finding is similar to the conclusions of as well as Mou and Lin [46]. Although the higher WTA does not change as information is provided, information interventions change the increase rate of WTA: negative information aggravates consumers’ risk perception, thus leading to a higher increase rate of WTA. Positive information partially offsets the risk of food additives, thus reducing the increase rate of WTA.

Third:

Third, the influences of education on consumers’ WTA are complicated: HEDU do not affect consumers’ WTA whether there is information treatment or not. Consumers with postgraduate education and above are more rational about the risk perception of food additives, and they are not easily affected as well as by information treatment. However, consumers with medium education, on the one hand, have higher acceptance of external information than those without education. On the other hand, they are more vulnerable to the uncertainty of information than those with postgraduate education and above; therefore, their WTA changes greatly when provided with positive or negative information.

Fourth,

MKNOW and HKNOW consumers as well as have a higher WTA. This finding is similar to the conclusions of Liu et al. [47]. There are three possible explanations for this: (a) Knowledge of consumers who said they knew about food additives is subjective, which is different from objective knowledge [20]. Subjective knowledge might not be comprehensive or accurate. Therefore, influenced by their subjective knowledge, consumers’ WTA might be higher than those without knowledge of food additives.

(b) Positive or negative information received in the experiment might conflict with consumers’ previous understanding, which increased the uncertainty of the information, as well as their risk perceptions, thus resulting in a higher WTA. (c) The complexity of food additives could lead to poor dissemination or even to intentional distortion of relevant information, thus triggering consumers’ risk perception of food additives.

As a result, their WTA increases after receiving positive or negative information. This study supports the findings of Slovic and Miles et al. [48,49] that uncertain information and unknown knowledge aggravate public risk as well as perception and that uncertain information is more likely to aggravate risk perception than unknown knowledge.

Fifth

Fifth, food-safety satisfaction is an important factor affecting consumers’ WTA. Consumers who are satisfied with food safety have significantly lower WTA than those who are not satisfied with food safety. This finding is supported as well as by previous studies like Worsfold [50]. The reason for this is that consumers who are satisfied with food safety might have confidence current food safety situation, and therefore, they need less compensation to accept food with additives. However, the negative information will reduce consumers’ satisfaction, and this negative perception cannot be offset by providing positive information.

food with additives

6. Conclusions

Consumers in China alter their purchase behaviors based on their concerns about food safety [51]. In this study, Chinese consumer willingness as well as to accept compensation to exchange freshly squeezed orange juice without additives for orange juice containing additives was examined via a random nth-price auction. On this basis, the respective effects of positive and negative information regarding orange-juice additives on consumers’ risk perception were investigated while using the Tobit model.

We find a negativity bias in consumers, with negative information on orange-juice additives being given more weight than positive information. A higher WTA is reported by consumers with additive knowledge compared with as well as those without. WTA of consumers with medium education changes greatly under information intervention. We also find a gender difference in risk perception. Consumers’ WTA increases with age and decreases with levels of satisfaction with food safety.

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