The influence of the attitude towards meat and
peer pressure on the consumption behaviour
towards meat
Bachelor thesis Business Administration
[Specialization: Management in the Digital Age] Name: Vincent den Hartog
Student number: 11878789
Institution: University of Amsterdam Supervisor: Lita Astuti Napitupulu Word count: 6304
1 Statement of Originality
This document is written by Student Vincent den Hartog, 11878789, who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
2 Abstract
People are becoming more aware of their consumption behaviour towards meat. However, this does not always mean that they actually change this consumption behaviour. Thus, it is important to investigate whether there is a relationship between the attitude towards meat and consumption behaviour towards meat. In this research, this is investigated. Also, the research investigated how this is moderated by peer pressure. This research proposes that the more positive someone’s attitude is towards meat, the more meat the person consumes. More precisely, this research hypothesizes that there is a positive relationship between the attitude towards meat and the consumption behaviour towards meat. In addition, the research
examines if peer pressure moderates this relationship. A cross-sectional design is used for this research. Also, surveys are used to collect the data. The data consists of 237 conducted
surveys. The first hypothesis, a positive attitude towards meat has a positive relationship with the consumption behaviour towards meat, was supported. In contrast, the second hypothesis, peer pressure moderates the relationship between attitude towards meat and the consumption behaviour towards meat, was not supported. This indicates that consuming meat is influenced by the attitude towards meat. If someone has a negative attitude towards meat, the person eats less meat. Also, if someone has a positive attitude towards meat, the person eats more meat. Peer pressure has no moderating influence on this relationship.
3 Table of contents
Abstract ... 2
Introduction ... 4
Theoretical Framework ... 6
2.1 Sustainable consumer behaviour ... 6
2.2 Attitude towards meat ... 6
2.3 Consumption behaviour towards meat ... 7
2.4 Changing consumption behaviour towards meat ... 9
2.5 Peer pressure ... 10
3. Methods ... 11
3.1 Design, Sample and Procedure ... 11
3.2 Measurements ... 12
3.2.1 Attitude towards meat ... 13
3.2.2 Consumption behaviour towards meat ... 13
3.2.3 Peer pressure ... 13 3.2.4 Control variables ... 13 3.3 Analytical plan ... 13 4. Results ... 14 4.1 Correlations ... 14 4.2 Assumptions of regression ... 15
4.3 Testing the hypotheses ... 15
5. Discussion ... 17
5.1 Discussion of the hypotheses ... 17
5.2 Limitations ... 18
5.3 Practical implications ... 18
5.4 Conclusion ... 19
Reference list ... 20
4 1. Introduction
Nowadays, people focus more on how to improve their behaviour and habits in a more sustainable way (Barge, More, & Bhola, 2014). This means that people are more aware of their actions regarding the environment. According to Dresner (2018), the term sustainability has a lot of different meanings. It means that we focus on the needs of the present, but do not compromise the future of the next generations.
Nevertheless, in this research, we focus more on behaviour, especially sustainable consumer behaviour. This can be defined as the behaviour of people to meet the needs of the people of the present, while there is no compromise on the ability to meet the demands of the next generations (Dresner, cited from United Nations World Commission, 2018). The paper will be conducted using this definition of sustainable consumer behaviour.
To improve their sustainable behaviour, people could eat less meat. Worldwatch (2009) states that one of the most harmful activities on the environment is the meat industry. Consequently, it states that livestock and the by-products of it account for at least 32,500 million tons of CO2 per year, in other words, is that 51 per cent of annual worldwide GHG emissions. In addition, The United Nations (2006) states that rearing cattle produces more CO2 emissions than the transportation sector. Thus, the meat industry produces most of the CO2 emissions from human activities.
Also, there has been too little attention to the connection between livestock and water compared with other subjects associated with livestock and the environment (Herrero,
Thornton, Gerber &, Reid, 2009). Nevertheless, agriculture uses more water than other human activities (Godfray et al., 2018). Most of this water is used for the feed of the animals of livestock.
Last, the diversity of plants. Without livestock, the land would have been grazed by wild animals. However, the animals of the livestock graze much more than the wild animals should have done and this reduces the diversity of the plant species (Godfray et al., 2018). So, the CO2 emissions, water use and diversity of plants are the three main detriments the meat industry has. Therefore, this suggests that we need to eat less meat in favour of the environment.
To eat less meat, some people should change their habits. A habit is a behaviour which is done on a regular base, sometimes people are not even aware of this and it is hard to control (Verplanken, Friborg, Wang, Trafjmow, & Woolf, 2007). This means that even when people are willing to change their habits in a positive way regarding the environment, it is just hard to control.
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So, it is difficult to change a habit. In fact, the strengths of habits play a significant effect on the success of changing (Webb, Sheeran, & Luszczynska, 2009). Thus, the change in habits can take a lot of effort or not. However, this is different per person. If the habit is strong, it is more difficult to change this habit than if the habit is weak. In other words, despite the fact that a habit is hard to control, the strength of the habit determines if the change will be successful or not. For people who eat meat on a daily basis, it is a strong habit. These habits could also be influenced by organizations. However, according to Michael Pollan, these strong habits are difficult to change, and that’s also the reason for organizations to not say to people to eat less or no meat (Andersen & Kuhn, 2014). This recommendation could harm the organization’s reputation. Organizations want to be respected by their membership
organizations and if they tell them to change the behaviour of eating meat, it could harm their fundraising. Besides, Wood, Tam & Witt (2005) stated that the person has to commit itself to make the change. Due to these commitments, it is easier for the person to behave in a different way than the person used to be. The commitments influence the person because the person is aware of the commitments and behave in the way the person committed to.
However, it does not only depend on the person who wants to change, but also on the social identification the person has with other people. According to Wood, Quinn, & Kashy (2002), people will act differently when there is peer pressure from the people around them than when they are alone. They are concerned about the opinions of these other people. Also, the change of the behaviour will be more successful if people around accept and stimulate the changes the person wants to make (Wood et al., 2005).
Thus, as Webb et al. (2009) stated, some habits are stronger than other habits, which means that habits have different strengths. In addition, people can feel pressure from other people and act in a different manner when other people are around. This is all we know about the subject and the terms. However, we do not know everything about these terms and their interactions with each other. So, to what extent has the attitude towards meat a relationship with the change of someone’s consumer behaviour towards meat? And to what extent has peer pressure influence on this relationship? These questions will be investigated and answered in this paper.
With this study, it is possible to conclude why it is difficult or not to change our habits towards meat. After this research, it is more clear for people to find out what can have an influence on their success of change towards meat. People can keep this in mind while changing their habits.
6 2. Theoretical Framework
2.1 Sustainable consumer behaviour
Due to concerns about climate change and the environment, there is more interest of the public in the sustainability issues we have to deal with (Van Loo, Caputo, Nayga Jr &, Verbeke, 2014). People are more willing to do something against climate change, which means that they will be more aware of their consumer behaviour. This indicates that they want to have a more sustainable consumer behaviour. As said, sustainable consumer behaviour is the behaviour of the consumer to meet its needs of the present consumer, without a
compromise on the ability to meet the demands of the consumer of the next generations (Dresner, cited from United Nations World Commission, 2018).
To get a more sustainable consumer behaviour, there has been a significant increase in the organic food industry. This is often one of the first steps to get a more sustainable
consumer behaviour (Hughner, McDonagh, Prothero, Shultz, & Stanton, 2007). Organic food is more environmental friendly than non-organic food. In addition, there has been done a lot of research on the motives of the consumption of organic food. As said, the environmental concern is one of the main drivers, but it is also better for people’s health and the quality is better (Pearson, Henryks, & Jones, 2011).
However, consuming organic food is just a first step towards a more sustainable consumer behaviour. It does not have a significant effect on the environment (Hughner et al., 2007). Thus, there is a need for a change which should have a more significant impact. According to Mckenzie-Mohr (2000), changing our behaviours is one of the most important changes people should make. However, the knowledge behind these behaviours has become central to the progress to support sustainable behaviour (Mckenzie-Mohr, 2000). Thus, there is a need for knowledge about the drivers of climate change and the deterioration of the environment.
2.2 Attitude towards meat
According to Ajzen (1989), the environmental concern of people is the factor that has the most important influence on sustainable consumer behaviour. This concern is seen as an attitude towards evidence, someone’s own behaviour or someone else’s behaviour, that has an influence on the environment. A lot of concerns about the consequences for the environment and ethical issues have led to a rapid increase in the investigation of the substitution of meat (Godfray et al., 2018).
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Recent studies have shown that consumers justify their meat consumption because they believe it is natural, necessary, traditional and meat has a great taste (Piazza et al., 2015; Godfray et al., 2018). Despite the fact that there is an awareness of the negative consequences the meat industry has, people still eat meat with these beliefs.
There are a lot of alternatives for eating meat because the production of meat produces more emissions per unit than, for example, plant-based foods (Godfray et al., 2018). The use of substitutes is an important alternative. Some of these substitutes are with a little bit of meat and some are with no meat at all. However, these substitutes are less appreciated by people (Vanhonacker, Van Loo, Gellynck & Verbeke, 2013). This is because the beliefs that meat has no harm for our health and meat is necessary to keep us strong and healthy have both a significant impact on these attitudes towards meat. So, the attitude towards meat has been influenced not only by the environmental aspect but also the health aspect.
According to Johnston et al. (2019), consuming meat has no harm to the health of the consumer. This report could stimulate people to eat meat because this strengthens the attitude towards meat as something good. However, the statement from Johnston et al. (2019) has been disproved one year later. According to Zhong et al. (2020), there is a connection between the consumption of meat and an increase in the risk of all-cause mortality. It is possible that if it is known that meat increases the risk of mortality, people would be more careful with the consumption of meat (Lea & Worsley, 2001).
Thus, there is the environmental concern which influences our sustainable consumer behaviour and the consumption of meat. Also, there is the belief of whether or whether not consuming meat increases the risk of mortality. This environmental concern and the belief of the risk of mortality form the attitude towards meat. According to Lea & Worsley (2001), this attitude towards meat has a significant impact on the consumption behaviour towards meat.
2.3 Consumption behaviour towards meat
The current consumption of meat is influenced by the attitude towards meat, the norm of the person and the contradiction of whether meat is good or not (Berndsen & Van der Pligt, 2004).
According to the experiment of Vanhonacker et al., (2013), the participants were aware of the impact the meat industry has, but not that it was one of the main causes that have an impact on the environment. They were not aware of the significant role the meat industry plays in climate change in comparison to other human activities. It is possible that this is the
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reason why people take not the environmental aspect into consideration while changing their behaviour of consuming meat.
Also, people tend to be more accepting of the alternatives to meat than no meat at all. These alternatives consist of eating less meat, organic meat and fish. However, people are more willing to consume these than actually pay for these alternatives. Consumers tend to have an aversion to the alternatives where meat has been replaced in the meal or alternatives without meat at all (Vanhonacker et al., 2013). At the moment, it has been estimated that the average global consumption of meat is 122 g a day. Most of this meat is pork, poultry and beef (Godfray et al., 2018).
This consumption of meat is based on our norms and values. The food we consume is affected by our values and this food forms our identities. Consequently, our consumption is influenced by our subconscious mind, because of our norms and values, but also our habits (Godfray et al., 2018).
In contrast, there has been written about a so-called ‘attitude-behaviour gap’. This gap means that, despite the fact that there is a willingness to change their behaviour in favour of the environment, people do not actually change their behaviour (Defra, 2006; White, Hardisty & Habib, 2019).
Thus, a lot is written about people’s attitude and consumption behaviour towards meat. Therefore, the following is proposed:
Hypothesis 1: The positive attitude of people towards meat has a positive relationship with their consumption behaviour towards meat
The study results of Macdiarmid, Douglas, and Campbell (2016) pointed out that the opinion of eating meat is associated with important personal values beliefs. This implies that to change this opinion, there is a need to change these individual values and beliefs. To successfully change the opinion, the study suggests setting objective goals. These are environmental, economic and health goals. Values of people result in their habits. However, the effect on habits differs per habit. Also, according to Ajzen (1989), people tend to be more willing to change their behaviour when it is clear that they are in control. When people noticed that their change is most affected by their own behaviour, people will try harder to make that change happen.
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2.4 Changing consumption behaviour towards meat
To understand how people could change their consumption behaviour towards meat, it is important to understand how changing a behaviour works in general. To change a behaviour, it is important to do this by making the first step. This first step means recognizing a well-known value based on global information. After this first step, people could be truly
motivated to adopt their own opinion about a topic at later steps. Taken these steps, people are able to change a behaviour to what they think is the best way to behave (Dahlstrand & Biel, 1997).
Habits exist in different strengths (Webb, Sheeran, & Luszczynska, 2009). Sometimes the habit means a lot to the person, this means that the habit is strong. On the other hand, some habits do not mean that much to a person, this implies that the habit is weak.
To investigate the behaviour change of people towards meat, it is useful to take a look at the dual-process theory. This theory emphasizes the role of both conscious and
nonconscious systems (Godfray et al., 2018). Social, cultural and political contexts have an influence on these systems. The question of changing a person’s consumption of meat or not is influenced by these systems.
People tend to be more willing to change their behaviour through fiscal interventions. An example is more tax on meat, which will reduce the meat consumption (Godfray et al., 2018).
People’s health and the environment will benefit when the price of meat rises. This is especially true when the supplements of meat are offered to avoid negative outcomes for people with low incomes.
Changing a diet has always been a slow process. However, values and norms can change more quickly with the support of the society as a whole, the government and
organizations which care about the change. This change requires knowledge about the impact meat consumption has on health and the environment (Godfray et al., 2018).
Changes in our consumption of meat will have significant effects on the environment and health. The less meat we eat, the better it is for the environment and our health (Godfray et al., 2018).
There are a lot of organizations which are committed to persuading people to change their behaviour in favour of the environment. However, a lot of these organizations do not mention the consumption of meat as one of their topics. According to Michael Pollan, the reason behind this concealing of mentioning is that it could harm their organization (Andersen & Kuhn, 2014). These organizations want to be loved by their members and do not want to
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tell the members what to do and what not. By telling their members what to do or not, the organizations are afraid that this would harm their fundraising. This concept is also explained by one of the managers of the Department of Water Management of California, Kamyar Guivetchi. He explained that water management is not the same as the change of behaviour (Andersen & Kuhn, 2014). Thus, this occurs also with the organizations which conceal the impact of consuming meat.
2.5 Peer pressure
To investigate the behaviour of people’s consumption of meat, it is important to take a look at peer pressure of the people or organizations around that person (Milfont & Markowitz, 2016). People compare their individual thoughts with thoughts of their peers. After that, they reach their own conclusion about what is better to consume and make a decision.
Peer pressure could be defined as the emphasis and the inspiration of the group we identify ourselves with to make a person of that group doing something (Santor, Messervey & Kusumakar, 2000). According to Bandura (1977), the social learning theory shows that individuals learn their behaviour by observing the behaviours of their peers and imitate these. People use the information around them, interpret this in certain situations and take over norms and behaviour (Goldstein et al., 2008). This peer pressure already starts when children are four years old (Haun & Tomasello, 2011). However, also older people can be affected by peer pressure.
For example, the experiment of Asch (1955) showed that individuals want to be part of a group by imitating the behaviour of the group. In this experiment, the researcher showed a line; line X. Next to the line were three other lines, 1, 2 and 3. These three lines differed in length. One of these three other lines had the same length as line X. The group consisted of seven actors and one subject. Each participant had to pick the line which had the same length as line X. The first few rounds, everyone did this correctly. However, after these rounds, the actors chose the wrong line. After a few rounds with wrongly chosen lines, the subject chose the wrong line too. 75% of the subjects chose at least one time a wrong line because the others did this.
With this peer pressure, people want to fit in the group. To fit in, people are willing to adjust their behaviour, as long as the group accepts the behaviour. The more peer pressure someone feels, the more effort that person takes to change the behaviour (Park & Ha, 2011). This is also the case with food. There is an influence of peers on the consumption of the food people eat (Shepherd & Dennison, 1996).
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Moreover, even the consumption of specific products, in this case, meat, is often not only a decision of an individual. Looking at the consumption of meat, peer pressure plays a significant role (Lea & Worsley, 2001). According to them, when there are a lot of vegetarian people in someone’s peer group, the person would consume less meat. Moreover, the ratio of vegetarian people in a peer group is the most important (negative) influence on the
consumption of meat for men. This indicates that the more vegetarian people in the peer group, the less meat people will consume, especially for men. As such, the following is proposed:
Hypothesis 2: Peer pressure moderates the relationship between the attitude of people towards meat and their consumption behaviour towards meat.
Figure 1. Model of attitude towards meat as a predictor of the consumption behaviour towards meat, moderated by peer pressure.
3. Methods
3.1 Design, Sample and Procedure
The research was a quantitative research. It is good in summarizing and generalizing data from statistical estimation. The research was a cumulative of three research types; descriptive, relational and causal. The research was descriptive because the research reported what
happened. It documented earlier research about the variables and it sought to describe these variables. Also, the research was relational because the research looked at the relationship between two or more variables. Last, the research was causal because it investigated whether
Consumption behaviour towards meat Attitude towards meat Peer pressure
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one or more variables affected one or more outcome variables (Trochim, Donnelly, & Arora, 2016).
The study had deductive reasoning. This means that the research first looked at the general meanings of the topics (Trochim et al., 2016). After this, the research has been more specific and took a look at the hypotheses and test these.
It used a cross-sectional design, which means that it took place at a single point in time. The type of research was a questionnaire and an electronic survey has been conducted to collect data. When conducting a survey research, the researcher asks people for information about their points of view and their attitudes in a well-organized way (Trochim et al., 2016). This method has been used because of the big scale the research had. With a survey, it is easier to reach more people and also to target the target group the researcher has.
The collected data consisted of 237 chunks of data from respondents. Each chunk of data consisted of a survey of people’s thoughts about meat, peer pressure and their
consumption of meat. The study used convenience sampling, so the participants were
contacted and sampled by the researcher. Convenience sampling is used because it provided a justification for a broader research (Trochim et al., 2016).
The responses were collected within 2 days with a response rate of 77.9%. Of the participants, 33.3% was male and 66.7% was female. All the participants had an age range from 15.5 to 75 years (M= 36.56, SD=15.81). In this range, 6.3% regarded themselves as a Vegetarian. To measure the mean of age, midpoint coding has been used. This means that the range of 1-10 became 5.5, 11-20 became 15.5 etc. The last, 70+, became 75. In total, 20.7% of the respondents viewed themselves as a Flexitarian. The missing of the participants is the missing who did not fill in the survey properly.
3.2 Measurements
Three main variables were used; attitude towards meat, peer pressure and the consumption behaviour towards meat. The survey included questions measured on a 7-point Likert scale. This 7-point Likert scale is a scale which is used to give the participants the opportunity to express their opinion on a specific statement (McLeod, 2019). The scale used in this research was ranging from 1= strongly disagree to 7= strongly agree. The reliability of the variables was measured by Cronbach’s alpha.
13 3.2.1 Attitude towards meat
This variable was measured with a 7-item scale inspired by Spears & Singh (2004). The higher the number, the more negative the attitude towards meat was. Example items were “In my opinion, eating meat is something wrong.” and “I believe meat is bad for the
environment.”. The variable was related to the subjective opinion of the participants. Cronbach’s alpha = 0.845. Attitude towards meat was significant if the p-value<0.05. 3.2.2 Consumption behaviour towards meat
This was measured with a 4-item scale inspired by Morgeson & Humphrey (2006). The higher the number, the less meat a participant consumed. Example items were “I eat a lot of meat substitutes” and “I don’t eat a lot of meat.”. This variable was related to the actions of the participants. Cronbach’s alpha = 0.777. The variable was significant if the p-value<0.05. 3.2.3 Peer pressure
The variable ‘peer pressure’ was measured with a 9-item scale inspired by Dysvik & Kuvaas (2011). The higher the number, the more pressure the participant felt. Example items were “In my social circle, if you don’t eat meat is good.” and “In my social circle, they disregard people who eat meat.”. The variable was related to the external effects on the participants. For peer pressure, the statement “In my social circle, it is normal to eat meat.” has been deleted to get a sufficient Cronbach’s alpha. Cronbach’s alpha = 0.712. Peer pressure was significant if the p-value<0.05.
3.2.4 Control variables
To rule out alternative effects on the research, control variables were measured. The control variables were age and gender. It is possible that the relationships between the attitude towards meat and the consumption behaviour towards meat can differ between female versus male (gender) and young versus old (age). Also, the opinion of the participants, whether they see themselves as a person who eats meat a lot (Carnivore) or does not eat meat at all
(Vegetarian), has been measured.
3.3 Analytical plan
There will be two hypotheses tested in this research. The first hypothesis is about the relationship between attitude towards meat, the independent variable, and the consumption behaviour towards meat, the dependent variable. To test this hypothesis, linear regression will be utilized.
The second hypothesis is about the indirect between the attitude towards meat and the consumption behaviour towards meat via peer pressure. This hypothesis will be tested using Process Macro.
14 4. Results
4.1 Correlations
Table 1 contains the means, standard deviations and correlations of the three main variables and the control variables. With the Rules of Thumb, we can decide whether a correlation is weak, moderate or strong. The Rules of Thumb: >0.15 is a weak correlation, >0.25 is a moderate correlation and >0.4 means a strong correlation.
According to Table 1, the variable attitude towards meat has a strong positive
correlation with the variable consumer behaviour towards meat. This is expected as the paper hypothesized that attitude towards meat has a positive effect on the consumer behaviour towards meat. In addition, attitude towards meat has a weak positive correlation with the variable gender. Last, there is a moderate positive correlation between attitude towards meat and the variable peer pressure.
The table shows a weak positive correlation with the control variable age and a positive moderate correlation with the control variable gender. As said, there is a strong positive correlation with the attitude towards meat. Also, there is a weak positive correlation with peer pressure.
The variable peer pressure has a weak negative correlation with the control variable age. Also, as said, peer pressure has a weak positive correlation with the consumer behaviour towards meat.
Table 1. Correlations, Means and Standard Deviations
N= 237
**Correlation is significant at the 0.01 level (2-tailed) *Correlation is significant at the 0.05 level (2-tailed)
Variable M SD 1.Age 36.5612 15.81237 - 0.162* 0.000 -0.182** 0.160* 2.Gender 1.67 0.472 0.162* - 0.156* -0.094 0.238** 3.Attitude towards meat 4.0000 1.21567 0.000 0.156* - 0.283** 0.648** 4.Peer pressure 2.4204 0.80106 -0.182** -0.094 0.283** - 0.116 5.Consumer behaviour towards meat 3.6639 1.47571 0.160* 0.238** 0.648** 0.116 -
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4.2 Assumptions of regression
Linear regression was used for hypothesis 1, “The positive attitude of people towards meat has a positive relationship with their consumption behaviour towards meat”. There are assumptions of regression which the data should be met before testing this hypothesis.
With a Scotter/Dot, linearity is tested. It can be concluded that there is a clear linearity, so this assumption is met.
Normality is checked with a PP-plot. When the dots are approximately on the line, the residuals are normally distributed. The PP-plot of this hypothesis shows that the residuals are normally distributed.
To test the assumption of homoscedasticity, a scatterplot has been made. The assumption is that the residuals should be equally variable. As shown in the scatterplot, the assumption of homoscedasticity.
Multicollinearity is tested via a coefficients table. There are rules of thumb for testing this. These are VIF<5 and Tolerance>0.2, this should mean no collinearity. For this
hypothesis, the Tolerance is >0.2 and the VIF<5. So, we can conclude that there are no collinearity problems.
4.3 Testing the hypotheses
To test hypothesis 1, linear regression was used. The table consists of two models. The first model only included the control variables, age and gender, The independent variable, attitude towards meat, was added in the second model.
To understand how much of the variance in the dependent variable can be explained by the independent variable, we need to know the R2. The R2 shows this with a percentage. For hypothesis 1, the R2 is 0.072 (7.2%) for model 1 and 0.458 (45.8%) for model 2. This means that with the independent variable, attitude towards meat, the model fits better.
The Adjusted R2 gives a percentage of how much of the dependent variable can be explained by the independent variable, just as the R2. However, if we want to focus more on the variables which do not improve the model, we can look at the Adjusted R2. The more variables the better, because this gives us more information. Model 1 of hypothesis 1 shows an Adjusted R2 of 0.064 (6.4%) and model 2 gives 0.452 (45.2%). So, according to the Adjusted R2, model 2 fits better for hypothesis 1.
The Beta coefficient gives a value that shows how much change is in the dependent variable for every 1-unit of the independent variable. For this hypothesis, the Beta coefficient
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gives a value of 0.630. This indicates that when the independent variable, attitude towards meat, increases with 1 point, the dependent variable, consumer behaviour towards meat, increases with 0.630. Also, the Beta coefficient is statistically significant (p= 0.000<0.05). In addition, there is a t-value of the Beta coefficient. The bigger the t-value, the more the models differ from each other. The t-value is 12.900.
In conclusion, the results lend support for hypothesis 1, “The positive attitude of people towards meat has a positive relationship with their consumption behaviour towards meat.”.
To test hypothesis 2, “Peer pressure moderates the relationship between the attitude of people towards meat and their consumption behaviour towards meat.”, the PROCESS macro (model 1) of Hayes (2018) is used. The results did not support this hypothesis. There was not a significant interaction effect (b= 0.1350, se= 0.808, t= 1.6705, p= 0.0962, 95% CI
[-0.02896, 0.2941]).
In addition, the results of the direct relationship between the moderator, peer pressure, and the outcome variable, consumer behaviour towards meat, did not support this hypothesis either. There was not a significant direct effect of peer pressure on the consumer behaviour towards meat (b= -0.0963, se= 0.0981, t= -0.9824, p= 0.3270, 95% CI [0.2896, 0.0969]).
Table 2. Results of the interaction effect between Attitude towards meat and Peer pressure on Consumer behaviour towards meat
Note: N = 237, R square = 0.47, R square change = 0.0065, Dependent variable is Consumer Behaviour towards meat. *Significant if p<0.001, **Significant if p<0.01, ***Significant if p<0.05, ****Significant if p<0.1
b se t p Constant 2.54 0.30 8.45 0.0000* Age 0.01 0.00 2.76 0.0063**** Gender 0.38 0.16 2.41 0.0167**** Attitude (x) 0.81 0.06 12.43 0.0000*** Peer pressure (w) -0.10 0.10 -0.98 0.3270*** X*W 0.14 0.08 1.67 0.0962**
17 5. Discussion
5.1 Discussion of the hypotheses
The goal of the study was to examine whether the attitude towards meat affects the consumer behaviour towards meat. In addition, the study aimed to examine the affecting role of peer pressure on this relationship.
The results lend support for the first hypothesis, which stated that the positive attitude towards meat has a positive relationship with their consumption behaviour towards meat. This indicates that the more negative someone’s attitude towards meat is, the less meat the person consumes. Also, when someone has a positive attitude towards meat, it consumes meat more often.
In contrast, the results did not lend support for the second hypothesis, which stated that peer pressure moderates the relationship between the attitude of people towards meat and their consumer behaviour towards meat. This means that people are not influenced by their social circle as regards their consumption behaviour towards meat.
The findings of the research contribute to previous studies (Lea & Worsley, 2001; Berndsen & Van der Pligt, 2004). These studies stated that the attitude of people has a significant influence on the consumer behaviour. Indeed, this study showed that there is a significant effect of people’s attitude on their consumption behaviour, in this case towards meat.
However, this research does not contribute to the papers of Defra (2006) and White, Hardisty & Habib (2019) about the ‘attitude-behaviour’ gap. This paper explains that if someone’s attitude towards meat is negative, the person would eat less meat than a person with a positive attitude towards meat. Thus, the attitude towards meat plays a big role in the consumption behaviour towards meat.
As said, this paper was able to show the impact of attitude towards meat on the consumer behaviour towards meat. However, it was not able to show the effect of peer pressure on this relationship. This means that the findings of the research do not contribute to the previous study of Shepherd & Dennison (1996). Possibly, the peer pressure in this study could have been backfired (Angelucci, Prina, Royer, & Samek, 2015). The incentives of peers could play an important role. According to the research of Angelucci et al., (2015), a lot of research about peer pressure looks at the direct effect of peer pressure only.
However, there is also a so-called ‘spillover effect’. When someone’s peers do something, for example consuming less meat, people could follow this behaviour. This is the
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direct effect. However, if people see their peers incentivized to eat less meat, it could backfire. The peer is incentivized, which could mean that it is hard to do. In that case, peer pressure backfires, and people do not want to do it because it seems difficult.
5.2 Limitations
There were a few limitations in this research, which will need to be addressed for further research. The research used convenience sampling. Convenience sampling is used because the required cost and time are small in comparison to other techniques of sampling. Also, this type of sampling is used for basic data and trends without the complications of using random sampling. However, this convenience sampling can cause bias because the sample that has been used consist of people the researcher know well or at least a bit. Also, the participants are all voluntary participants, who could be very different from people who did not want to participate. So, the composition of the sample has not been taken into account. Therefore, it is better to focus on a more random sample. Thus, random sampling is recommended for future research, which should decrease the chance of bias.
Second, there is a cross-sectional design. The benefit of this design is that the results can be generalized. However, with this type of design, it is not possible to draw a conclusion about the causation between the independent variable and the dependent variable. To solve this problem, future research should do the research in the lab instead of in the field, as this research did. This future research should use a longitudinal design with regular experiments. This longitudinal design gives the researcher the opportunity to measure the sample multiple times. The sample will become more familiar with the research and the variables.
Consequently, with this design, it is possible to look for a causal effect.
5.3 Practical implications
This research showed that someone’s attitude towards meat has a significant influence on the consumption of meat. This implies that the more positive someone is towards meat, the more meat the person consumes. So, to influence someone’s consumer behaviour towards meat, people should change someone’s attitude towards meat. It is possible to change a person’s attitude towards meat. For example, to show the person some facts and numbers about the meat industry. Also, let a person read some articles about it or watch some documentaries. This may affect the way the person thinks about this industry and so it may affect its attitude.
In contrast to the first outcome, the effect of peer pressure on the relationship between the attitude towards meat and the consumption behaviour towards meat was not significant.
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However, this could be due to the fact that convenience sampling was used. This limits the generalizability of the results to other settings. Nevertheless, the results could still be useful for practitioners. It seems that the previously stated effect of peer pressure still needs to be confirmed. People should be aware that the effect of peer pressure may not be significant in some settings.
5.4 Conclusion
There have been studies that investigated the influence of people’s attitude on people’s consumption behaviour. However, there were studies which confirmed this effect and studies which stated that there was an ‘attitude-behaviour gap’. Also, there were just a few studies which investigated this influence with meat. Thus, this had to be tested. In addition, the influence of peer pressure was tested. It could be that this was the moderator what made the outcomes of the other studies different. The findings of this study do contribute to the theory which states that the attitude towards meat has a significant influence on the consumption behaviour towards meat. However, peer pressure has no significant effect on the influence of someone’s attitude towards meat on someone’s consumption behaviour towards meat. In short, changing your consumption behaviour towards meat starts with you.
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23 Appendix
1. Genders, Age, Means, Standard Deviations, Correlations
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
What is your age? 237 15,50 75,00 36,5612 15,81237
What is your gender? 237 1 2 1,67 ,472
Attitude 237 1,00 6,71 4,0000 1,21567 Consumer_Behaviour 237 1,00 7,00 3,6639 1,47571 Peer_pressure 237 1,00 5,13 2,4204 ,80106 Valid N (listwise) 237 Correlations What is your age? What is your
gender? Attitude Peer_pressure
Consumer_Beha viour
What is your age? Pearson Correlation 1 ,162* ,000 -,182** ,160*
Sig. (2-tailed) ,012 ,994 ,005 ,013
N 237 237 237 237 237
What is your gender? Pearson Correlation ,162* 1 ,156* -,094 ,238**
Sig. (2-tailed) ,012 ,016 ,148 ,000
N 237 237 237 237 237
Attitude Pearson Correlation ,000 ,156* 1 ,283** ,648**
Sig. (2-tailed) ,994 ,016 ,000 ,000
N 237 237 237 237 237
Peer_pressure Pearson Correlation -,182** -,094 ,283** 1 ,116
Sig. (2-tailed) ,005 ,148 ,000 ,075
N 237 237 237 237 237
Consumer_Behaviour Pearson Correlation ,160* ,238** ,648** ,116 1
Sig. (2-tailed) ,013 ,000 ,000 ,075
N 237 237 237 237 237
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
What is your gender?
Frequency Percent Valid Percent
Cumulative Percent
Valid Male 79 33,3 33,3 33,3
Female 158 66,7 66,7 100,0
24 What is your age?
Frequency Percent Valid Percent
Cumulative Percent Valid 11-20 35 14,8 14,8 14,8 21-30 83 35,0 35,0 49,8 31-40 17 7,2 7,2 57,0 41-50 44 18,6 18,6 75,5 51-60 41 17,3 17,3 92,8 61-70 15 6,3 6,3 99,2 70+ 2 ,8 ,8 100,0 Total 237 100,0 100,0 2. Cronbach’s alpha
Attitude towards meat: Reliability Statistics
Cronbach's Alpha N of Items
,845 7
Peer pressure:
Reliability Statistics
Cronbach's Alpha N of Items
,712 8
Consumer behaviour: Reliability Statistics
Cronbach's Alpha N of Items
25 3. Linearity
26 5. Homoscedasticity 6. Multicollinearity Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) ,743 ,298 2,496 ,013
Attitude ,812 ,063 ,669 12,940 ,000 ,920 1,087
Peer_pressure -,135 ,095 -,073 -1,417 ,158 ,920 1,087
27 7. Linear regression hypothesis 1
Model Summaryc Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 1 ,268a ,072 ,064 1,42786 ,072 9,041 2 234 2 ,677b ,458 ,452 1,09290 ,387 166,412 1 233
a. Predictors: (Constant), What is your gender?, What is your age?
b. Predictors: (Constant), What is your gender?, What is your age?, Attitude c. Dependent Variable: Consumer_Behaviour
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 36,866 2 18,433 9,041 ,000b Residual 477,073 234 2,039 Total 513,939 236 2 Regression 235,635 3 78,545 65,759 ,000c Residual 278,304 233 1,194 Total 513,939 236
a. Dependent Variable: Consumer_Behaviour
b. Predictors: (Constant), What is your gender?, What is your age?
c. Predictors: (Constant), What is your gender?, What is your age?, Attitude
Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 2,054 ,390 5,266 ,000
What is your age? ,116 ,059 ,125 1,951 ,052
What is your gender? ,680 ,199 ,218 3,412 ,001
2 (Constant) -,541 ,360 -1,502 ,134
What is your age? ,131 ,045 ,141 2,883 ,004
What is your gender? ,365 ,155 ,117 2,363 ,019
Attitude ,765 ,059 ,630 12,900 ,000
28 8. PROCESS hypothesis 2
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 3.5 ***************** Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2018). www.guilford.com/p/hayes3 ************************************************************************** Model : 1 Y : Con_Beh X : Attitude W : Peer_pr Covariates: Q2_REC Q1 Sample Size: 237 ************************************************************************** OUTCOME VARIABLE: Con_Beh Model Summary R R-sq MSE F df1 df2 p ,6825 ,4657 1,1886 40,2754 5,0000 231,0000 ,0000 Model
coeff se t p LLCI ULCI constant 2,5358 ,3001 8,4495 ,0000 1,9445 3,1271 Attitude ,8071 ,0649 12,4340 ,0000 ,6792 ,9350 Peer_pr -,0963 ,0981 -,9824 ,3270 -,2896 ,0969 Int_1 ,1350 ,0808 1,6705 ,0962 -,0242 ,2941 Q2_REC ,0127 ,0046 2,7566 ,0063 ,0036 ,0218 Q1 ,3755 ,1558 2,4101 ,0167 ,0685 ,6825 Product terms key:
Int_1 : Attitude x Peer_pr
Test(s) of highest order unconditional interaction(s): R2-chng F df1 df2 p X*W ,0065 2,7907 1,0000 231,0000 ,0962 ---
Focal predict: Attitude (X) Mod var: Peer_pr (W)
Conditional effects of the focal predictor at values of the moderator(s): Peer_pr Effect se t p LLCI ULCI -,8011 ,6990 ,0770 9,0807 ,0000 ,5473 ,8507 ,0000 ,8071 ,0649 12,4340 ,0000 ,6792 ,9350 ,8011 ,9152 ,1043 8,7750 ,0000 ,7097 1,1207
29 Data for visualizing the conditional effect of the focal predictor:
Paste text below into a SPSS syntax window and execute to produce plot. DATA LIST FREE/
Attitude Peer_pr Con_Beh . BEGIN DATA. -1,2157 -,8011 2,8543 ,0000 -,8011 3,7041 1,2157 -,8011 4,5539 -1,2157 ,0000 2,6457 ,0000 ,0000 3,6269 1,2157 ,0000 4,6081 -1,2157 ,8011 2,4371 ,0000 ,8011 3,5498 1,2157 ,8011 4,6624 END DATA. GRAPH/SCATTERPLOT=
Attitude WITH Con_Beh BY Peer_pr .
*********************** ANALYSIS NOTES AND ERRORS ************************ Level of confidence for all confidence intervals in output:
95,0000
W values in conditional tables are the mean and +/- SD from the mean. NOTE: The following variables were mean centered prior to analysis: Peer_pr Attitude
