This study examines the psychological drivers influencing the intention to engage alternative proteins as potential substitutes for meat, utilising an extended framework of the norm activation model. Our framework incorporates awareness of meat consumption impacts, personal responsibility, involvement in sustainable and healthy eating and involvement in animal welfare. These factors shape personal norms, which ultimately influence the intention to try new protein sources. The study also considers neophobia (both food neophobia and food technology neophobia) as a determinant of intention. Additionally, it analyses sociodemographic factors associated with previous experience of alternative protein consumption, providing a comprehensive understanding of consumer behaviour.
Data were collected from a representative sample of 500 Italian consumers through a structured questionnaire. The study employed a structural equation model to analyse the intention to engage seitan-based proteins, insect-based proteins and cultured meat. Constructs measured included awareness of impacts, personal responsibility, involvement in healthy eating, involvement in sustainable eating, involvement in animal welfare, food neophobia and food technology neophobia. Additionally, individual scores for the intention to engage with each protein type were calculated, followed by a seemingly unrelated regression analysis (SUR). This model incorporated sociodemographic factors and previous experiences (such as tasting history, frequency of consumption and opinion) as independent variables.
The findings reveal that involvement in sustainable eating and awareness of meat consumption impacts on environmental sustainability are significant predictors of personal norms, which in turn influence the intention to engage alternative proteins. Conversely, health and animal welfare considerations are closely linked to personal responsibility, shaping personal norms that guide engagement intentions. Furthermore, food neophobia and food technology neophobia were found to significantly reduce the intention to consume insect-based foods and cultured meats. SUR analysis also indicates that sociodemographic traits and previous experience are effective predictors of alternative protein consumption frequency.
This study applies an extended version of the norm activation model to explore the engagement of alternative proteins, offering new insights into the psychological drivers behind consumer behaviour in the context of health, environmental sustainability and animal welfare. By integrating these factors with awareness and personal responsibility, the research provides a comprehensive understanding of how personal norms shape intentions to engage alternative proteins. The findings contribute to the literature by highlighting the roles of these factors and offering practical implications for promoting sustainable and ethical food consumption.
Introduction
The increasing interest in alternative proteins as substitutes for conventional meat is driven by the need to address significant global challenges, including public health, environmental sustainability, and animal welfare (Meriggi et al., 2024). As consumers become more sensitive to the impacts of their dietary choices, understanding the psychological factors that influence the intention to engage these alternative proteins becomes essential.
Previous research has shown that consumer behaviour toward alternative proteins is shaped by a variety of factors, including environmental concerns, health motivations, and ethical considerations related to animal welfare. For instance, individuals with strong environmental values are often more inclined to reduce their meat consumption in favour of plant-based or cultured alternatives (Onwezen et al., 2021; Onwezen and Dagevos, 2023; di Santo et al., 2024). Similarly, health-conscious consumers are attracted to alternative proteins due to perceived benefits, such as lower cholesterol levels and a reduced risk of chronic diseases (Weinrich, 2019; de Oliveira Padilha et al., 2022). Ethical concerns, particularly regarding animal welfare, also play a significant role in motivating the choice of meat substitutes (Bryant and Barnett, 2020; Tso et al., 2020). However, much of the existing literature has tended to examine these factors in isolation, without fully exploring how they interact by the use of a comprehensive theoretical framework (Mosikyan et al., 2024).
To provide a blueprint capable of simultaneously considering all the mentioned factors, we based our approach on the Norm Activation Model (NAM) introduced by Schwartz (1977), which has proven useful for understanding the intention to consume plant-based meat alternatives in China (Xueyun et al., 2024) and seaweed in Norway (Govaerts and Olsen, 2022). The Model explains how personal norms are shaped by two key psychological factors: awareness of consequences (AC) and ascription of responsibility (AR). According to this framework, individuals are more likely to engage in pro-social or pro-environmental behaviours when they recognise the negative impacts of their actions on others or the environment and feel personally responsible for addressing these impacts. Once activated, personal norms serve as a guide for behaviour, motivating actions that align with social or environmental responsibility.
Building on this foundation, our approach extends the NAM by incorporating values as fundamental guiding principles (Schwartz, 1992). In particular, values play a crucial role in food-related decisions, where ethical, environmental, and health considerations often intersect with broader societal concerns. In our model, values are directly linked to the activation of personal norms, serving as an independent source of moral obligation. While maintaining AC and AR as essential determinants of personal norms, this perspective highlights the unique role of values in influencing behaviour across these contexts.
By integrating values into the NAM, our framework not only refines the understanding of how moral obligation is shaped but also underscores their centrality in driving ethical and sustainable choices. This contribution is particularly relevant in addressing food-related behaviours, where personal values and societal priorities often converge.
We conceptualise involvement in sustainable eating as an expression of the universalism–nature value, defined as a commitment to preserving the natural environment (Schwartz et al., 2012). Similarly, involvement in healthy eating reflects Schwartz’s conceptualisation of health as a security value, where the focus on personal well-being and dietary health benefits aligns with a sense of safety and stability. Involvement in animal welfare reflects the value of animal welfare, characterised by an empathic motivation to ensure the well-being of all animals (Lee et al., 2019). Together, these value-driven motivations underpin the moral obligations that shape personal norms, emphasising their central role in fostering ethical and sustainable behaviours.
Additionally, we have included food neophobia (FN) and food technology neophobia (FTN) in our model to account for psychological barriers that affect consumer intentions. FN refers to an aversion to trying unfamiliar foods (Pliner and Hobden, 1992), while FTN describes resistance towards foods produced using novel technologies (Cox and Evans, 2008). We hypothesise that FN and FTN act as independent moderating factors between personal norms and behavioural intentions, reflecting stable dispositions that can hinder the adoption of alternative proteins (Fantechi et al., 2024). Their inclusion allows us to better capture the complexity of consumer decision-making, particularly when evaluating novel food options such as alternative proteins. The model described is shown in Figure 1.
The flowchart consists of seven oval text boxes. On the left, three ovals are vertically stacked. The top oval reads, “Value-driven involvement”. The middle oval reads, “Awareness of consequences”. The bottom oval reads, “Ascription of responsibility”. An arrow from “Value-driven involvement” points downward and to the right toward a central oval. An arrow from “Awareness of consequences” points horizontally to the right toward the same central oval. An arrow from “Ascription of responsibility” points upward and to the right toward that central oval. This central oval reads, “Personal Norm”. An arrow points horizontally from “Personal Norm” to the right to another oval that reads, “Intention”. On the far right, two ovals are vertically stacked. The top oval reads, “Food technology neophobia”. The bottom oval reads, “Food neophobia”. An arrow from “Food technology neophobia” points downward and to the left toward “Intention”. An arrow from “Food neophobia” points upward and to the left toward “Intention”.Theoretical framework
The flowchart consists of seven oval text boxes. On the left, three ovals are vertically stacked. The top oval reads, “Value-driven involvement”. The middle oval reads, “Awareness of consequences”. The bottom oval reads, “Ascription of responsibility”. An arrow from “Value-driven involvement” points downward and to the right toward a central oval. An arrow from “Awareness of consequences” points horizontally to the right toward the same central oval. An arrow from “Ascription of responsibility” points upward and to the right toward that central oval. This central oval reads, “Personal Norm”. An arrow points horizontally from “Personal Norm” to the right to another oval that reads, “Intention”. On the far right, two ovals are vertically stacked. The top oval reads, “Food technology neophobia”. The bottom oval reads, “Food neophobia”. An arrow from “Food technology neophobia” points downward and to the left toward “Intention”. An arrow from “Food neophobia” points upward and to the left toward “Intention”.Theoretical framework
This study advances understanding by developing a comprehensive framework that highlights the interplay between psychological drivers, values, and barriers in shaping ethical and sustainable food choices. The findings provide new perspectives for stakeholders, enabling the design of marketing strategies, public policies, and educational initiatives that effectively promote the adoption of alternative proteins and support sustainable dietary practices.
Methodology
To understand the factors influencing the intention to engage with alternative proteins in place of meat, a survey was conducted in August 2024 with a representative sample of 500 Italian consumers, recruited through an international marketing research firm (Toluna, Inc., Wilton, CT, USA). The sample was stratified by gender, age, and region of residence, ensuring that it reflected the demographics of the Italian population, as detailed in Table 1.
Sociodemographic characteristics of our sample (N = 500)
| Variable | Sample (%) | Italian population (%) |
|---|---|---|
| Gender | ||
| Male | 49 | 49 |
| Female | 51 | 51 |
| Age | ||
| 18–34 | 24 | 24 |
| 35–54 | 38 | 38 |
| >54 | 38 | 38 |
| Region | ||
| North | 45 | 45 |
| Central Italy | 20 | 20 |
| South and islands | 35 | 35 |
| Education | ||
| Junior high school or below | 7 | 36 |
| High school diploma | 52 | 43 |
| College education or higher | 41 | 21 |
Note(s): For the Italian population we used ISTAT data
Source(s): Authors’ own work
The questionnaire was structured into four distinct sections. The first section aimed to identify the target sample. It was administered to individuals who reported consuming red and/or white meat beyond the limits recommended by the Mediterranean diet, which is widely recognized as a healthy and balanced dietary pattern (Cavaliere et al., 2018; Gerini et al., 2022). To avoid misunderstandings regarding the types of products considered, examples of the most commonly consumed red and white meats were provided. The final sample included participants who reported consuming red meat more than once a week, white meat more than twice a week, or both.
In the following section, we measured involvement in sustainability, involvement in healthy eating and involvement in animal welfare, as key drivers of meat reduction and engagement of alternative proteins (Califano et al., 2023; Piracci et al., 2024). These constructs along with personal responsibility, awareness, and personal norms were assessed using previously validated Likert scale items, ranging from 1 (completely disagree) to 7 (completely agree) (Table 2).
Items and constructs used in the analysis
| Construct | Code | Item | Source |
|---|---|---|---|
| Involvement in sustainable eating | SUST1 | Sustainable eating is very important to me | Van Loo et al. (2017) |
| SUST2 | I care a lot about sustainable eating | ||
| SUST3 | Sustainable eating means a lot to me | ||
| SUST4 | I am very concerned about the consequences of what I eat in terms of sustainability | ||
| Involvement in animal welfare | AW1 | It is important that the food I eat on a typical day has been produced in a way that animals have not experienced pain | Krystallis et al. (2009) |
| AW2 | It is important that the food I eat on a typical day has been produced in a way that animals’ rights have been respected | ||
| AW3 | In general, humans have too little respect for the quality of life of animals | ||
| AW4 | Increased regulation of the treatment of animals in farming is needed | ||
| AW5 | Animal agriculture raises serious ethical questions about the treatment of animals | ||
| Involvement in healthy eating | H1 | Healthy eating is very important to me | Van Loo et al. (2017) |
| H2 | I care a lot about healthy eating | ||
| H3 | Healthy eating means a lot to me | ||
| H4 | I am very concerned about the health-related consequences of what I eat | ||
| Awareness of meat consumption’s impact on sustainability | SUST_AW1 | Meat consumption causes the exhaustion of natural resources | Zhang et al. (2013) |
| SUST_AW2 | Meat consumption contributes to local ecological damage | ||
| SUST_AW3 | I am aware of the influence meat consumption has on global warming | ||
| SUST_AW4 | Overall, meat consumption can cause some negative environmental consequences | ||
| Awareness of meat consumption’s impact on animal welfare | AW_AW1 | Meat consumption affects the welfare of animals | Zhang et al. (2013) |
| AW_AW2 | Meat consumption contributes to animal suffering | ||
| AW_AW3 | I am aware of the influence meat consumption has on animal welfare | ||
| AW_AW4 | Overall, meat consumption can cause negative consequences for animals | ||
| Awareness of meat consumption’s impact on health | H_AW1 | Meat consumption affects my health | Zhang et al. (2013) |
| H_AW2 | Meat consumption contributes to various health issues | ||
| H_AW3 | I am aware of the influence meat consumption has on my overall health | ||
| H_AW4 | Overall, meat consumption can cause some negative health consequences | ||
| Ascription of responsibility for the sustainability impacts | SUST_RESP1 | I feel jointly responsible for the exhaustion of natural resources due to meat consumption | deGroot and Steg (2009) |
| SUST_RESP2 | I feel joint responsibility for the contribution of meat consumption to global warming | ||
| SUST_RESP3 | I feel joint responsibility for the contribution of meat consumption to local ecological damage | ||
| SUST_RESP4 | I feel joint responsibility for the negative environmental consequences of meat consumption | ||
| Ascription of responsibility for animal welfare impacts | AW_RESP1 | I feel jointly responsible for the impact of meat consumption on animal welfare | deGroot and Steg (2009) |
| AW_RESP2 | I feel joint responsibility for the suffering caused by meat consumption | ||
| AW_RESP3 | I feel joint responsibility for the negative effects of meat consumption on animals | ||
| AW_RESP4 | I feel joint responsibility for the welfare of animals affected by meat consumption | ||
| Ascription of responsibility for health impacts | H_RESP1 | I feel jointly responsible for health impacts of my meat consumption | deGroot and Steg (2009) |
| H_RESP2 | I feel joint responsibility for the health issues caused by meat consumption | ||
| H_RESP3 | I feel joint responsibility for the negative health effects of meat consumption | ||
| H_RESP4 | I feel joint responsibility for maintaining my health through mindful meat consumption | ||
| Personal Norms | PN1 | It would be against my moral principles not to consider the overall impacts of meat consumption | Godin et al. (2005) |
| PN2 | Not considering the consequences of meat consumption would go against my principles | ||
| PN3 | I have a moral obligation to take into account the broader consequences when consuming meat | ||
| PN4 | I would feel guilty about not considering the impacts of meat consumption | ||
| PN5 | I feel obliged to make meat consumption choices that reflect a concern for its overall impacts | ||
| Food technology neophobia | FTN1 | There is no sense trying out high-tech food products because the ones I eat are already good enough | Verneau et al. (2014), Cox and Evans (2008) |
| FTN2 | New food technologies are something I am uncertain about | ||
| FTN3 | New foods are not healthier than traditional foods | ||
| FTN4 | The benefits of new food technologies are often grossly overstated | ||
| FTN5 | There are plenty of tasty foods around, so we do not need to use new food technologies to produce more | ||
| FTN6 | New food technologies decrease the natural quality of food | ||
| FTN7 | It can be risky to switch to new food technologies too quickly | ||
| FTN8 | Society should not depend heavily on technologies to solve its food problems | ||
| Food neophobia | NEO1 | I am constantly sampling new and different foods | Pliner and Hobden (1992) |
| NEO2 | I like foods from different countries | ||
| NEO3 | At dinner, I will try a new food | ||
| NEO4 | I like to try new ethnic restaurants | ||
| Intention to engage new food – insects | INT_INS1 | If I had the opportunity, I plan to include insect-based proteins in my diet | Ajzen and Sheikh (2013), Dunn et al. (2011) |
| INT_INS2 | If given the chance, I intend to add insect-based proteins to my meals | ||
| INT_INS3 | If the option were available, I would make an effort to incorporate insect-based proteins into my diet | ||
| INT_INS4 | It is likely that I would choose to consume insect-based protein foods regularly if they were accessible | ||
| Intention to engage new food – cultured meat | INT_MEAT1 | If I had the opportunity, I plan to include cultured meat in my diet | Ajzen and Sheikh (2013), Dunn et al. (2011) |
| INT_MEAT2 | If given the chance, I intend to add cultured meat to my meals | ||
| INT_MEAT3 | If the option were available, I would make an effort to incorporate cultured meat into my diet | ||
| INT_MEAT4 | It is likely that I would choose to consume cultured meat regularly if it were accessible | ||
| Intention to engage new food – seitan | INT_SEITAN1 | I plan to include or increase seitan in my diet | Ajzen and Sheikh (2013), Dunn et al. (2011) |
| INT_SEITAN2 | I intend to add or increase seitan to my meals | ||
| INT_SEITAN3 | I will make an effort to incorporate or increase seitan into my diet | ||
| INT_SEITAN4 | It is likely that I will consume seitan regularly |
Source(s): Authors’ own work
To evaluate the intention to engage alternative proteins, we focused on three different products: insect-based proteins, seitan-based proteins, and cultured meat. These products were selected to investigate whether the influence of antecedents varies by product type, considering the distinct categories they represent—animal-based, plant-based, and biotechnology-based—and their varying availability on the market. Notably, while seitan is widely available in Italian supermarkets, insect-based proteins are still limited, often found only in specialized or niche markets. In contrast, the purchase of cultured meat is strictly prohibited in Italy, as current national regulations prevent its commercialization. Previous research indicates that consumer attitudes towards these alternatives differ significantly due to cultural, ethical, and psychological factors. Insect-based proteins face cultural resistance in Western countries (Simeone and Scarpato, 2021; Kröger et al., 2022), cultured meat is met with scepticism regarding its unnaturalness and safety (Wilks et al., 2021), and seitan, although more accepted, remains niche due to limited exposure (Andreani et al., 2023). Given the novelty of these products, the study also incorporated measures of food technology neophobia and food neophobia, which are significant barriers to the engagement of novel foods (Fantechi et al., 2024).
Table 2 lists all the constructs and items used in the model, along with their sources.
In the third section, respondents were asked about their previous experience with the three alternative proteins, including whether they had tasted them, the frequency of consumption, and their opinions on taste.
The final section collected demographic data, including gender, age, geographical region (North, Central, or South), and level of education.
For the analysis, we employed a structural equation modelling (SEM) approach, which proved effective for this type of study (Dias et al., 2024; Gastaldello et al., 2022). Within the same SEM framework, the intention to engage with each specific protein alternative was included, resulting in three separate structural equations—one for each product—with intention as the dependent variable.
Following the implementation of the SEM model, we calculated the standardised factor scores from the structural model for all three intentions for each respondent. The aim was to observe which sociodemographic factors (gender, age, education) and familiarity with the products (previous tasting, frequency of consumption, and opinions about them) influence intention. Using these factor scores as dependent variables, we employed a Seemingly Unrelated Regression (SUR) model consisting of three separate equations—one for each protein under investigation. The choice of the SUR model was based on the assumption that the errors across the three equations were correlated, a condition that the methodology explicitly accounts for. This assumption was empirically validated using the Breusch-Pagan test.
Results
Before implementing the SEM model, the constructs used were evaluated. Internal consistency was measured using Cronbach’s alpha, which satisfactorily exceeded the acceptability threshold of 0.7 (George and Mallery, 2003; Cronbach, 1951).
To assess the model, we conducted a confirmatory factor analysis (CFA) to ensure convergent and discriminant validity, using the maximum likelihood estimation method. For convergent validity, we examined the AVE (average variance extracted) values and factor loadings, both of which were above the 0.5 threshold (Cheung and Wang, 2017; Fornell and Larcker, 1981). Discriminant validity was confirmed because the Square Correlation (SC) values were lower than the AVE for the respective constructs. Table 3 presents this comparison between AVE and SC, while Table 4 includes Cronbach’s alpha for each construct and the factor loadings of each item, along with their means and standard deviations.
AVE and SC of the constructs
| Construct | AVE | Squared correlation among latent variables | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13_1 | 13_2 | 13_3 | |||
| 1 | Involvement in sustainable eating | 0.86 | 1 | ||||||||||||||
| 2 | Involvement in animal welfare | 0.62 | 0.29 | 1 | |||||||||||||
| 3 | Involvement in healthy eating | 0.77 | 0.33 | 0.15 | 1 | ||||||||||||
| 4 | Awareness of meat consumption’s impact on sustainability | 0.82 | 0.38 | 0.28 | 0.09 | 1 | |||||||||||
| 5 | Awareness of meat consumption’s impact on animal welfare | 0.76 | 0.29 | 0.37 | 0.09 | 0.61 | 1 | ||||||||||
| 6 | Awareness of meat consumption’s impact on health | 0.77 | 0.29 | 0.19 | 0.09 | 0.52 | 0.52 | 1 | |||||||||
| 7 | Ascription of responsibility for the sustainability impacts | 0.92 | 0.34 | 0.19 | 0.08 | 0.69 | 0.47 | 0.42 | 1 | ||||||||
| 8 | Ascription of responsibility for animal welfare impacts | 0.87 | 0.39 | 0.34 | 0.08 | 0.59 | 0.61 | 0.42 | 0.69 | 1 | |||||||
| 9 | Ascription of responsibility for health impacts | 0.84 | 0.31 | 0.20 | 0.12 | 0.47 | 0.41 | 0.47 | 0.55 | 0.53 | 1 | ||||||
| 10 | Personal norm | 0.82 | 0.59 | 0.33 | 0.20 | 0.55 | 0.48 | 0.44 | 0.52 | 0.59 | 0.50 | 1 | |||||
| 11 | Food technology neophobia | 0.62 | 0.00 | 0.00 | 0.05 | 0.05 | 0.02 | 0.01 | 0.04 | 0.01 | 0.01 | 0.02 | 1 | ||||
| 12 | Food neophobia | 0.69 | 0.15 | 0.09 | 0.03 | 0.14 | 0.09 | 0.11 | 0.16 | 0.11 | 0.12 | 0.15 | 0.10 | 1 | |||
| 13_1 | Intention to engage new food – insects | 0.94 | 0.06 | 0.02 | 0.00 | 0.12 | 0.05 | 0.06 | 0.12 | 0.08 | 0.09 | 0.10 | 0.09 | 0.20 | 1 | ||
| 13_2 | Intention to engage new food – cultured meat | 0.95 | 0.08 | 0.06 | 0.00 | 0.21 | 0.14 | 0.12 | 0.21 | 0.17 | 0.13 | 0.16 | 0.29 | 0.21 | 0.37 | 1 | |
| 13_3 | Intention to engage new food – seitan | 0.91 | 0.16 | 0.10 | 0.04 | 0.25 | 0.18 | 0.19 | 0.27 | 0.23 | 0.20 | 0.25 | 0.08 | 0.24 | 0.27 | 0.32 | 1 |
Source(s): Authors’ own work
Cronbach’s alpha of constructs and factor loadings, mean, and standard deviation of all the items
| Construct | Alpha | Code | Factor loadings | Mean | Standard deviation |
|---|---|---|---|---|---|
| Involvement in sustainable eating | 0.96 | SUST1 | 0.94 | 5.04 | 1.56 |
| SUST2 | 0.94 | 4.79 | 1.67 | ||
| SUST3 | 0.96 | 4.89 | 1.66 | ||
| SUST4 | 0.86 | 4.64 | 1.75 | ||
| Involvement in animal welfare | 0.89 | AW1 | 0.74 | 5.69 | 1.48 |
| AW2 | 0.73 | 5.85 | 1.40 | ||
| AW3 | 0.76 | 5.48 | 1.60 | ||
| AW4 | 0.84 | 5.88 | 1.41 | ||
| AW5 | 0.85 | 5.66 | 1.51 | ||
| Involvement in healthy eating | 0.92 | H1 | 0.91 | 5.77 | 1.23 |
| H2 | 0.94 | 5.51 | 1.39 | ||
| H3 | 0.96 | 5.57 | 1.40 | ||
| H4 | 0.67 | 5.11 | 1.55 | ||
| Awareness of meat consumption’s impact on sustainability | 0.95 | SUST_AW1 | 0.94 | 4.28 | 1.82 |
| SUST_AW2 | 0.94 | 4.27 | 1.84 | ||
| SUST_AW3 | 0.83 | 4.57 | 1.81 | ||
| SUST_AW4 | 0.90 | 4.61 | 1.81 | ||
| Awareness of meat consumption’s impact on animal welfare | 0.93 | AW_AW1 | 0.93 | 4.71 | 1.78 |
| AW_AW2 | 0.93 | 4.89 | 1.79 | ||
| AW_AW3 | 0.72 | 4.95 | 1.67 | ||
| AW_AW4 | 0.90 | 4.88 | 1.73 | ||
| Awareness of meat consumption’s impact on health | 0.93 | H_AW1 | 0.93 | 4.09 | 1.78 |
| H_AW2 | 0.96 | 4.27 | 1.76 | ||
| H_AW3 | 0.70 | 4.91 | 1.59 | ||
| H_AW4 | 0.89 | 4.57 | 1.71 | ||
| Ascription of responsibility for the sustainability impacts | 0.98 | SUST_RESP1 | 0.93 | 3.88 | 1.88 |
| SUST_RESP2 | 0.97 | 3.87 | 1.91 | ||
| SUST_RESP3 | 0.98 | 3.86 | 1.90 | ||
| SUST_RESP4 | 0.97 | 3.84 | 1.93 | ||
| Ascription of responsibility for animal welfare impacts | 0.96 | AW_RESP1 | 0.93 | 4.28 | 1.83 |
| AW_RESP2 | 0.96 | 4.22 | 1.89 | ||
| AW_RESP3 | 0.97 | 4.20 | 1.89 | ||
| AW_RESP4 | 0.86 | 4.28 | 1.87 | ||
| Ascription of responsibility for health impacts | 0.96 | H_RESP1 | 0.91 | 4.48 | 1.80 |
| H_RESP2 | 0.96 | 4.39 | 1.85 | ||
| H_RESP3 | 0.96 | 4.32 | 1.86 | ||
| H_RESP4 | 0.83 | 4.68 | 1.75 | ||
| Personal norm | 0.96 | PN1 | 0.91 | 4.59 | 1.68 |
| PN2 | 0.87 | 4.52 | 1.75 | ||
| PN3 | 0.94 | 4.64 | 1.80 | ||
| PN4 | 0.93 | 4.44 | 1.86 | ||
| PN5 | 0.88 | 4.31 | 1.80 | ||
| Food technology neophobia | 0.93 | FTN1 | 0.79 | 4.98 | 1.71 |
| FTN2 | 0.81 | 5.09 | 1.65 | ||
| FTN3 | 0.70 | 4.84 | 1.72 | ||
| FTN4 | 0.81 | 4.97 | 1.55 | ||
| FTN5 | 0.84 | 4.94 | 1.71 | ||
| FTN6 | 0.84 | 4.89 | 1.75 | ||
| FTN7 | 0.74 | 5.03 | 1.58 | ||
| FTN8 | 0.73 | 4.96 | 1.66 | ||
| Food neophobia | 0.90 | NEO1 | 0.79 | 4.54 | 1.73 |
| NEO2 | 0.85 | 4.84 | 1.74 | ||
| NEO3 | 0.79 | 4.17 | 1.77 | ||
| NEO4 | 0.90 | 4.39 | 1.93 | ||
| Intention to engage new food – insects | 0.98 | INT_INS1 | 0.98 | 2.41 | 1.85 |
| INT_INS2 | 0.99 | 2.39 | 1.89 | ||
| INT_INS3 | 0.95 | 2.44 | 1.87 | ||
| INT_INS4 | 0.96 | 2.30 | 1.81 | ||
| Intention to engage new food – cultured meat | 0.99 | INT_MEAT1 | 0.98 | 3.40 | 2.06 |
| INT_MEAT2 | 0.99 | 3.40 | 2.08 | ||
| INT_MEAT3 | 0.97 | 3.44 | 2.08 | ||
| INT_MEAT4 | 0.96 | 3.35 | 2.06 | ||
| Intention to engage new food – seitan | 0.98 | INT_SEITAN1 | 0.97 | 3.10 | 1.93 |
| INT_SEITAN2 | 0.98 | 3.05 | 1.94 | ||
| INT_SEITAN3 | 0.93 | 3.11 | 1.95 | ||
| INT_SEITAN4 | 0.94 | 3.18 | 2.01 |
Source(s): Authors’ own work
The SEM model demonstrates satisfactory goodness-of-fit statistics, which are essential for the reliability of the results (Hu and Bentler, 1999). We evaluated the RMSEA, which should be less than 0.08; the CFI index, with a minimum threshold of 0.9; the SRMR, with a maximum of 0.08; the TLI, which should be above 0.9; and the χ2 to degrees of freedom ratio, which should be less than 3. Table 5 presents these values, all of which fall within acceptable ranges.
Goodness-of-fit statistics of the SEM model
| Index | |
|---|---|
| RMSEA | 0.05 |
| CFI | 0.95 |
| SRMR | 0.05 |
| TLI | 0.94 |
| χ2/degrees of freedom | 2.21 |
Source(s): Authors’ own work
Table 6 shows the results of the structural model. Among the values, only involvement in sustainable eating has a positive and significant impact. Similarly, sustainability is the only significant factor in the context of awareness. In contrast, within the ascription of responsibility, health and animal welfare emerge as significant factors.
Structural model results
| Construct | Personal Norm | Intention to engage insects | Intention to engage cultured meat | Intention to engage seitan |
|---|---|---|---|---|
| Involvement in sustainable eating | 0.36** | |||
| Involvement in animal welfare | 0.06 | |||
| Involvement in healthy eating | 0.03 | |||
| Awareness of meat consumption’s impact on sustainability | 0.13* | |||
| Awareness of meat consumption’s impact on animal welfare | 0.02 | |||
| Awareness of meat consumption’s impact on health | 0.08 | |||
| Ascription of responsibility for the sustainability impacts | 0.04 | |||
| Ascription of responsibility for animal welfare impacts | 0.20** | |||
| Ascription of responsibility for health impacts | 0.13** | |||
| Personal norm | 0.18** | 0.26** | 0.37** | |
| Food technology neophobia | −0.20** | −0.43** | −0.15** | |
| Food neophobia | −0.34** | −0.26** | −0.32** |
Note(s): ** indicates p < 0.01, * indicates p < 0.05
Source(s): Authors’ own work
All three antecedents to intention are significant across the three alternative proteins. Specifically, stronger personal norms are associated with a greater intention to engage alternative proteins, while higher levels of food neophobia and food technology neophobia correspond to a lower intention. The impact of these constructs varies among the three proteins: for insect-based proteins, food neophobia is the most influential factor; for cultured meat, it is food technology neophobia; and for seitan, personal norms play the most significant role.
Figure 2 shows the model presented in Figure 1, with each construct divided into its various dimensions. It also includes the coefficients derived from the SEM model.
The path diagram displays a complex structural model and its corresponding legend. On the left of the main diagram, nine oval text boxes are arranged in three columns and point toward a central oval. The first column contains “Involvement in sustainable eating” with an arrow reading “0.36 double asterisk” to “Personal Norm”, “Awareness of meat consumption’s impact on sustainability” with an arrow reading “0.13 asterisk” to “Personal Norm”, and “Ascription of responsibility for the sustainability impacts” with an arrow reading “0.04” to “Personal Norm”. The second column contains “Involvement in animal welfare” with an arrow reading “0.06” to “Personal Norm”, “Awareness of meat consumption’s impact on animal welfare” with an arrow reading “0.02” to “Personal Norm”, and “Ascription of responsibility for animal welfare impacts” with an arrow reading “0.20 double asterisk” to “Personal Norm”. The third column contains “Involvement in healthy eating” with an arrow reading “0.03” to “Personal Norm”, “Awareness of meat consumption’s impact on health” with an arrow reading “0.08” to “Personal Norm”, and “Ascription of responsibility for health impacts” with an arrow reading “0.13 double asterisk” to “Personal Norm”. The central oval reads “Personal Norm”. Three arrows lead from “Personal Norm” to three ovals stacked vertically in the center-right. The top arrow reads “0.18 double asterisk” to “Intention to engage new food-insects”. The middle arrow reads “0.26 double asterisk” to “Intention to engage new food – cultured meat”. The bottom arrow reads “0.37 double asterisk” to “Intention to engage new food-seitan”. On the far right, two ovals are stacked vertically. The top reads “Food technology neophobia” and points to “Intention to engage new food-insects” with “negative 0.20 double asterisk”, to “Intention to engage new food – cultured meat” with “negative 0.43 double asterisk”, and to “Intention to engage new food-seitan” with “negative 0.15 double asterisk”. The bottom oval reads “Food neophobia” and points to “Intention to engage new food-insects” with “ negative 0.34 double asterisk”, to “Intention to engage new food – cultured meat” with “ negative 0.26 double asterisk”, and to “Intention to engage new food-seitan” with “negative 0.32 double asterisk”.Theoretical framework with SEM Model results
The path diagram displays a complex structural model and its corresponding legend. On the left of the main diagram, nine oval text boxes are arranged in three columns and point toward a central oval. The first column contains “Involvement in sustainable eating” with an arrow reading “0.36 double asterisk” to “Personal Norm”, “Awareness of meat consumption’s impact on sustainability” with an arrow reading “0.13 asterisk” to “Personal Norm”, and “Ascription of responsibility for the sustainability impacts” with an arrow reading “0.04” to “Personal Norm”. The second column contains “Involvement in animal welfare” with an arrow reading “0.06” to “Personal Norm”, “Awareness of meat consumption’s impact on animal welfare” with an arrow reading “0.02” to “Personal Norm”, and “Ascription of responsibility for animal welfare impacts” with an arrow reading “0.20 double asterisk” to “Personal Norm”. The third column contains “Involvement in healthy eating” with an arrow reading “0.03” to “Personal Norm”, “Awareness of meat consumption’s impact on health” with an arrow reading “0.08” to “Personal Norm”, and “Ascription of responsibility for health impacts” with an arrow reading “0.13 double asterisk” to “Personal Norm”. The central oval reads “Personal Norm”. Three arrows lead from “Personal Norm” to three ovals stacked vertically in the center-right. The top arrow reads “0.18 double asterisk” to “Intention to engage new food-insects”. The middle arrow reads “0.26 double asterisk” to “Intention to engage new food – cultured meat”. The bottom arrow reads “0.37 double asterisk” to “Intention to engage new food-seitan”. On the far right, two ovals are stacked vertically. The top reads “Food technology neophobia” and points to “Intention to engage new food-insects” with “negative 0.20 double asterisk”, to “Intention to engage new food – cultured meat” with “negative 0.43 double asterisk”, and to “Intention to engage new food-seitan” with “negative 0.15 double asterisk”. The bottom oval reads “Food neophobia” and points to “Intention to engage new food-insects” with “ negative 0.34 double asterisk”, to “Intention to engage new food – cultured meat” with “ negative 0.26 double asterisk”, and to “Intention to engage new food-seitan” with “negative 0.32 double asterisk”.Theoretical framework with SEM Model results
Table 7 presents data on our sample’s experiences with the alternative proteins studied. Overall, the three sources of proteins are not widely known among consumers, but seitan is consumed significantly more often than insects and cultured meat. Interestingly, the majority of those who have tried the alternative proteins were satisfied with the taste.
Experience with foods based on insects, cultured meat and seitan
| Foods based on … | Insects | Cultured meat | Seitan |
|---|---|---|---|
| Already tasted | |||
| Yes | 43 | 38 | 164 |
| No | 457 | 480 | 336 |
| Consumption frequency | |||
| I’ve only tasted them | 31 | 35 | 96 |
| I’ve consumed it multiple times in the past year | 12 | 3 | 68 |
| Opinion | |||
| I didn’t like them at all | 9 | 7 | 47 |
| I liked them, but I wouldn’t eat them again | 15 | 16 | 37 |
| I liked them | 19 | 15 | 80 |
Source(s): Authors’ own work
Table 8 presents the results of the three regressions from the SUR model. The Breusch–Pagan test of independence was significant (χ2 = 338.833, p = 0.00), indicating a correlation between the residuals of the three regressions and thus supporting the use of the SUR model. Gender is a significant factor for insect-based proteins, with men showing a greater intention to include them in their diet. Younger individuals express significantly more interest in all three types of proteins compared to older individuals, as do those with higher levels of education. Previous experience with the product, as a positive opinion of the taste, has a positive and significant impact on the intention to engage all products, while a higher frequency of consumption increases the intention only for seitan.
Experience with foods based on insects, cultured meat and seitan
| Variable | Insect | Cultured meat | Seitan |
|---|---|---|---|
| Gender (female = 1) | −0.55** | −0.17 | 0.10 |
| Age | −0.03** | −0.03** | −0.02** |
| Education | 0.26* | 0.40** | 0.38** |
| Previous tested | 2.19** | 1.51* | 1.77** |
| Consumption frequency | 0.27 | 0.18 | 0.58** |
| Opinion | 1.48** | 0.96** | 0.83** |
| Constant | −2.87* | −2.28 | −4.11** |
Note(s): ** indicates p < 0.01, * indicates p < 0.05
Source(s): Authors’ own work
Discussions
Building on an extended version of the Norm Activation Model, this study examines the distinct roles of awareness, personal responsibility, and value-driven motivations—centred on environmental sustainability, health, and animal welfare—in shaping personal norms. These norms, in turn, drive the intention to adopt alternative proteins. The findings shed new light on the psychological mechanisms underlying dietary shifts and offer valuable guidance for designing targeted strategies to encourage the exploration and adoption of alternative protein sources.
Involvement in sustainable eating emerged as the most influential factor in shaping personal norms, which in turn drive the intention to adopt alternative proteins. This suggests that consumers who prioritise environmental sustainability are more inclined to reduce their meat consumption and opt for alternatives such as seitan, cultured meat, or insect-based proteins. The significant impact of sustainability awareness on personal norms indicates that understanding the environmental consequences of meat consumption acts as a catalyst, motivating individuals to develop stronger personal norms and take action to mitigate these impacts. This environmental focus is in line with broader literature, which consistently identifies sustainability as a key driver for reducing meat consumption (Grummon et al., 2023; Kemper et al., 2023; Seffen and Dohle, 2023). For consumers inclined to engage alternative proteins, this shift is primarily motivated by a desire to align their dietary habits with environmental care (Jang and Cho, 2022; Ong et al., 2024). Promoting the benefits of alternative proteins, such as their lower carbon footprints and reduced land use, is likely to be particularly effective in reinforcing personal norms and encouraging dietary changes that reduce meat consumption.
Health is another significant factor influencing personal norms that drive the intention to engage alternative proteins, but it operates through a different mechanism compared to sustainable eating. Here, the influence is more closely tied to individualistic behaviour, which prioritises personal well-being and health. The study found that personal responsibility for health is a key determinant, consistent with the literature indicating that individuals who feel accountable for their well-being are more likely to engage in a balanced diet (Wongprawmas et al., 2021). This sense of responsibility is rooted in the desire to prevent diet-related diseases, maintain a balanced diet, and improve overall quality of life (Marinelli et al., 2015; Vajdi and Farhangi, 2020). However, our study also found that awareness of the health benefits of reducing meat consumption does not significantly influence personal norms or intentions directly, suggesting that simply providing information may not be enough to foster personal norms. Instead, stakeholders—including both public and private entities—should focus on strategies that make healthy eating both achievable and personally meaningful by creating a supportive environment. For example, communication campaigns could emphasise immediate, tangible health outcomes like increased energy levels, improved digestion, or better weight management. Personalised nutrition plans and interactive tools like health tracking apps can also help bridge the gap between general awareness and the development of personal responsibility.
Involvement in animal welfare also emerges as a significant factor influencing personal norms, which drive the intention to engage alternative proteins. This dimension is strongly associated with altruistic principles, which are concerned with the well-being of others, including non-human animals. Similar to healthy eating, personal responsibility plays a leading role in this context. Individuals who perceive themselves as responsible for the ethical treatment of animals are more likely to develop strong personal norms that lead to reducing meat consumption and opting for alternatives that minimise animal suffering. This sense of personal responsibility is often driven by deeply held ethical or moral convictions that go beyond mere awareness of animal welfare issues (Peschel et al., 2024). These findings align with existing research that highlights the ethical dilemmas associated with conventional meat production, such as the poor treatment of animals in industrial farming systems (de Boer and Aiking, 2022). For consumers who experience this dilemma, alternative proteins offer a way to reconcile their dietary habits with their ethical beliefs. Therefore, promoting the ethical advantages of alternative proteins, such as animal-free production methods and the avoidance of animal exploitation, is crucial to resonate with their altruistic perspective. Communication efforts should focus on ethical production practices and the benefits of avoiding animal exploitation associated with products.
The distinction between how environmental sustainability and the other two dimensions—health and animal welfare—influence the intention to engage with alternative proteins may lie in the nature of the motivations themselves. Biospheric concerns associated with sustainability are often linked to global and long-term consequences, relying more on collective awareness and self-transcendent motivations, which then influence the development of personal norms. Consumers motivated by sustainability are thus likely influenced by a broader sense of global responsibility and a desire to contribute to the greater good by reducing their environmental impact. In contrast, health-related motivations often yield immediate and tangible benefits, such as improvements in physical well-being, which directly reinforce personal responsibility. While concerns for animal welfare may not always lead to immediate personal rewards, they can evoke strong emotional responses, such as a reduction in guilt associated with consuming animal products (Lin-Schilstra and Fischer, 2020). This emotional engagement can similarly reinforce personal responsibility as a primary motivator for developing strong personal norms. When it comes to health, individuals are more likely to take action when they can directly observe the benefits or consequences of their dietary choices on their physical well-being. Similarly, concerns about animal welfare, often rooted in strong ethical or moral convictions, make personal responsibility a more immediate and powerful force in shaping behaviour.
The study also examined the impact of neophobia—specifically, food neophobia and food technology neophobia—on the intention to engage alternative proteins. The findings indicate that neophobia significantly reduces the likelihood of consumers engaging novel proteins, particularly insect-based and cultured meats. Consistent with existing literature, food neophobia emerged as the most influential antecedent of the intention to consume insect-based proteins. For cultured meat, food technology neophobia presented the more substantial barrier, reflecting consumer concerns about the perceived unnaturalness and safety of these products (Wilks et al., 2021). In contrast, seitan was less impacted by neophobia, with personal norms playing a more pivotal role in shaping consumers’ intentions to engage it.
The linear regression analysis provided further insights by examining how sociodemographic factors and previous experiences with alternative proteins influence the intention to engage these products. The analysis revealed that younger individuals and those with higher levels of education are more likely to engage alternative proteins, particularly seitan and insect-based proteins. Previous positive experiences with these products, such as tasting and consumption, significantly increased the intention to engage them, suggesting that familiarity and positive experiences are crucial in overcoming initial resistance. Additionally, a favourable opinion of the taste of these proteins was a strong predictor of engagement, underscoring the importance of sensory appeal in driving consumer acceptance.
These findings have implications for stakeholders looking to promote the engagement of novel foods, particularly those like cultured meat and insect-based proteins, which can encounter considerable consumer resistance. To address the challenges posed by neophobia, it is crucial to focus on strategies that enhance consumer familiarity with novel foods through direct, positive experiences. Opportunities for tasting and interacting with these products in environments where they are already available can help build consumer trust and reduce the apprehension associated with engaging new food products.
The study’s sociodemographic insights suggest that targeting younger, more educated consumers could be an effective strategy for facilitating the acceptance of novel foods. Tailored marketing efforts that emphasise the sensory qualities of these products—particularly their taste and texture—are likely to resonate well with these demographic groups. Ensuring that novel foods excel in sensory appeal is essential for their success, as this is a key driver of consumer acceptance.
Conclusion
This study provides a comprehensive analysis of the psychological factors influencing the intention to engage alternative proteins, applying an extended version of the Norm Activation Model to offer novel insights into consumer behaviour. The findings suggest that while involvement in sustainable eating is a key driver for engaging alternative proteins, personal responsibility is crucial in the domains of health and animal welfare, motivating consumers through more immediate and tangible outcomes. Furthermore, this research highlights the critical influence of personal norms, emphasizing how awareness and a sense of responsibility shape intentions to engage with alternative proteins, particularly in the context of health, environmental sustainability, and animal welfare. Neophobia, particularly regarding insect-based and cultured meats, poses a significant barrier to engagement, underscoring the need for strategies that increase familiarity and positive experiences with these products.
However, while the study has limitations, these also offer opportunities for future research. The main limitation is its focus on a single national context, Italy, which may restrict the generalizability of the findings to other cultural settings. This limitation opens up the potential for future studies to conduct cross-cultural comparisons, providing a more comprehensive understanding of how different cultural factors influence engagement with alternative proteins.
Given the significant impact of neophobia, future research should also explore strategies to reduce resistance to novel foods. Understanding how to effectively address neophobia and increase consumer acceptance of alternative proteins will be critical for promoting sustainable dietary shifts. By exploring new avenues of research, future studies can build on the findings of this study and contribute to the development of more effective strategies for encouraging the engagement of alternative proteins, ultimately promoting more sustainable, healthy, and ethical food consumption patterns.
Funding: This study was conducted in the Agritech National Research Center and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)—MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4—D.D. 1032 17/06/2022, CN00000022). This manuscript reflects solely the authors’ views and opinions, not the positions of the European Union or the European Commission.
