1. Introduction
With the rapid population growth, consumer demand for meat products is steadily increasing [
1]. This rising demand has exerted significant pressure on the environment and grassland ecosystems [
2,
3]. The conventional meat industry is a major contributor to greenhouse gas emissions. To mitigate greenhouse gas emissions from animal husbandry, enhance animal welfare, and conserve energy and water, meat substitutes such as plant-based protein meat and cell-based meat are emerging as potential strategies for future food development across various countries. Cultured meat has already been introduced to dining tables in Singapore [
4]. A survey conducted by Anne Cardin Jacobs and other scholars on German consumers’ attitudes towards artificial meat shows that the majority of respondents believed that the traditional meat industry was currently facing ethical and environmental problems and that reducing meat consumption was likely to be a solution to some of these problems [
5]. The proportion of existing plant-based meat alternatives that meet the needs of Belgian consumers has significantly increased, from 44% in 2019 to 51% in 2020. People’s attention to issues related to animal husbandry, especially environmental issues, has significantly increased [
6]. Chinese consumers’ attitudes towards meat consumption are primarily focused on private interests such as nutrition, safety, and quality, followed by public interests.
Given the constraints of carbon peak and carbon neutrality targets, meat substitutes could serve as supplementary sources of meat supply in China. Consequently, cultured meat and plant-based meat may become viable alternatives for Chinese consumers in the future. In recent years, plant-based protein meat and cultured meat have garnered public attention, becoming a global topic of interest among scientists, media, and consumers [
7]. To meet the growing demand for meat products, major food manufacturing enterprises and research institutions in China are actively investing in research and development of plant-based and cell-based meat substitutes [
8]. Scholars have investigated the acceptance and purchase intentions of Chinese consumers toward meat substitutes, exploring the main influencing factors [
9,
10,
11]. The results showed that Chinese consumers prefer vegetarian and plant-based meat [
12]. Scholars have analyzed how consumer characteristics—such as knowledge, perception, attitudes, and framing—impact consumer acceptance or purchase intentions [
13]. Consumers’ trust in the manufacturing technologies and regulatory processes of meat substitutes may significantly influence their acceptance [
14]. Beyond technological advancements, consumer acceptance remains the most critical factor for the large-scale commercialization of meat substitutes in the Chinese market.
Presently, Chinese consumers are informed about meat substitutes through media platforms such as TikTok, Kwai, and various television programs. Despite media coverage highlighting the environmental benefits [
2], resource conservation, nutritional value [
15], and positive impact on animal welfare of plant-based meat [
16], many consumers still exhibit a cautious or skeptical attitude. This skepticism is due to the relatively short history of meat substitutes, along with underdeveloped manufacturing and regulatory technologies, and concerns related to taste [
17], authenticity [
18], price [
10], and other factors [
7]. Thus, in addition to developing mature manufacturing technologies, achieving high consumer acceptance is essential for the successful integration of meat substitutes into the market.
While plant-based meat has already been commercialized in China, cultured meat remains in the experimental research stage; limited by manufacturing, regulatory, and legislative challenges. Regardless of whether the meat is plant-based or cultured, consumer acceptance is the critical driver for the growth of these novel industries. Understanding consumers’ acceptance of these meat substitutes and the factors influencing their attitudes is vital for diversifying and expanding the future meat market.
Consumer acceptance toward meat substitutes is influenced by their trust in manufacturing companies, regulatory agencies, and media sources. Additionally, perceived benefits and perceived risks, alongside consumer trust, significantly affect purchasing intentions. Consumer knowledge about meat substitutes enhances their perception of benefits and risks, encouraging informed decision-making rather than blind reliance on media. This study explores the intricate relationships among consumer trust, perceived benefits, perceived risks, consumer knowledge, and purchase intentions; synthesizing existing research to construct a theoretical model.
The primary aim of this study is to assess consumer acceptance of meat substitutes and understand the impact of consumer trust on acceptance. Additionally, the study seeks to explore the mediating roles of perceived benefits and perceived risks, as well as the moderating effect of prior consumer knowledge. The structure of this paper is as follows.
Section 2 sorts out the literature and research hypotheses, focusing on the influence of consumer trust in meat substitute technologies and regulatory systems on purchase intentions; alongside the mediating and moderating roles of perceived benefits, perceived risks, and consumer knowledge.
Section 3 details data collection and research methodology.
Section 4 presents data analysis and results.
Section 5 discusses the findings, and
Section 6 concludes the research, highlighting the limitations and future research directions.
4. Results
This study first performs descriptive statistical analysis on consumer demographics and model-related variables, followed by hypothesis testing on the mediating roles of perceived risk and perceived benefit. Subsequently, it examines the moderating model of consumer knowledge. The research primarily employs the Bootstrap method for mediating and moderating effect testing, as recommended by Hayes, using SPSS 27 as the analytical tool.
4.1. Descriptive Analysis
The main control variables include: gender (1288 males and 953 females, representing 57.47% and 42.53%, respectively); age (18–30 years old: 40.96%, 31–40 years old: 20.04%, 41–50 years old: 16.82%, 51–60 years old: 11.33%, over 60 years old: 10.84%); educational background (junior high school or below: 13.16%, high school or technical school: 25.08%, junior college or university degree: 35.03%, bachelor’s degree or above: 26.73%); and annual household income (below ¥20,000: 8.57%, ¥20,000–¥50,000: 18.3%, ¥50,000–¥100,000: 37.62%, ¥100,000–¥200,000: 24.5%, above ¥200,000: 11.02%). Additionally, consumer proportions by residence type are 17.09% from large cities, 30.57% from small and medium-sized cities, 23.34% from small towns, and 29% from rural areas. Regional distribution shows that 54.22% of consumers are from the eastern region, with the remaining 45.78% from central and western regions.
According to statistical analysis results (
Table 2), overall consumer purchase intentions, trust levels, knowledge levels, perceived risks, and perceived benefits are above the median. The mean purchase intention among consumers is 2.85, while perceived risk and perceived benefit scores are relatively high, with means of 3.24 and 3.18, respectively. However, consumer trust and knowledge levels related to meat substitutes are comparatively low, with means of 2.82 and 2.81, respectively.
Table 3 demonstrates that consumer acceptance correlates most strongly with consumer trust (r = 0.635), followed by perceived benefits (r = 0.629), consumer knowledge (r = 0.624), and perceived risks (r = −0.620).
4.2. The Mediating Effect of Perceived Risk and Perceived Benefit
We used Hayes’ PROCESS macro for data analysis, defining consumer purchase intention as the dependent variable, consumer trust as the independent variable, and perceived risk and perceived benefit as mediating variables. The self-sampling frequency was set to 5000, and the detailed results are shown in
Table 4. Findings indicate that consumer trust has a significant positive effect on consumer acceptance (β = 0.3197,
p < 0.001), confirming Hypothesis 1. Trust also significantly reduces perceived risk (β = −0.8005,
p < 0.001) and significantly enhances perceived benefit (β = 1.4736,
p < 0.001). Perceived risk (β = −0.2268,
p < 0.001) negatively affects consumer acceptance, while perceived benefit (β = 0.2577,
p < 0.001) has a significant positive impact on consumer acceptance. These results suggest that perceived risk and perceived benefit partially mediate the relationship between trust and consumer acceptance.
In the bootstrap indirect effect analysis of perceived risk and perceived benefit (
Table 5), the indirect effect of perceived risk on the relationship between trust and consumer acceptance is 0.2041; and for perceived benefit, it is 0.2588. The 95% bootstrap confidence intervals for both variables do not include zero, confirming that perceived risk and perceived benefit mediate the influence of trust on consumer acceptance.
4.3. Moderating Effect of Consumer Knowledge
There is a notable correlation between consumer knowledge and consumer trust, perceived risk, perceived benefit, and consumer acceptance. To further investigate these relationships, a model was developed with consumer acceptance as the dependent variable, consumer trust as the independent variable, perceived risk and perceived benefit as mediators, and consumer knowledge as a moderator. The self-sampling frequency was set to 5000, and the detailed results are provided in
Table 6. According to the regression analysis, consumer trust has a significant negative effect on perceived risk (β = −0.44,
p < 0.001) and a significant positive effect on perceived benefit (β = 0.46,
p < 0.001) and consumer acceptance (β = 0.32,
p < 0.001). Furthermore, knowledge negatively impacts perceived risk (β = −0.40,
p < 0.001) and has a significant positive impact on perceived benefit (β = 0.46,
p < 0.01) and consumer acceptance (β = 0.22,
p < 0.001).
Additional analysis reveals that the interaction term between trust and knowledge significantly affects perceived risk (β = −0.12, p < 0.001) and perceived benefit (β = −0.10, p < 0.001) but does not significantly impact consumer acceptance (β = −0.01, p > 0.05).
Based on the means of the two continuous variables, trust and knowledge, the parts that are more than one standard deviation above the mean value are classified as high trust and high knowledge, and the parts that are more than one standard deviation below the mean are classified as low trust and low knowledge. This study chose to convert the continuous variables of trust and knowledge into binary variables, mainly for the purpose of simplifying the analysis and making the relationships between variables more interpretable in certain analyses. The implications of this binary conversion are two-fold. On the one hand, it provides a clear and easy-to-understand way to present the data, especially for readers who may not be familiar with more complex statistical analyses. For example, in
Figure 2, it becomes immediately apparent how different levels of trust or knowledge are related to other variables. On the other hand, this study found that some information may be lost in the process of converting continuous variables to binary ones. However, we believe that the benefits of simplification and enhanced interpretability in this stage of the analysis outweigh the potential loss of detail.
By categorizing consumer trust into high and low levels based on one standard deviation above and below the mean, the moderating effects of knowledge for both high- and low-knowledge consumers were analyzed separately.
Figure 2 displays the specific moderating effects.
The regression coefficients for consumer knowledge on perceived risk (β = −0.44,
p < 0.001) and perceived benefit (β = 0.46,
p < 0.001) indicate that knowledge moderates the effect of trust on consumer acceptance through perceived risk and perceived benefit. Using the Bootstrap method to further validate this effect, a 95% confidence interval was calculated to determine the significance of knowledge levels on the trust–consumer acceptance relationship (see
Table 7). Analysis shows that for respondents with high knowledge levels, the 95% confidence interval for perceived risk and perceived benefit does not include zero, confirming that trust influences consumer acceptance through perceived risk and perceived benefit. Similarly, for low-knowledge consumers, the confidence interval does not include zero, indicating that trust influences acceptance through perceived risk and benefit for both knowledge groups.
Table 7 shows that perceived benefits among high-knowledge consumers exhibit less variation with increasing trust than among low-knowledge consumers. This outcome illustrates the negative moderating effect of knowledge on the trust–perceived benefit relationship. Regarding the moderating effect of knowledge on trust and perceived risk, high-knowledge consumers experience a greater reduction in perceived risk with increased trust than low-knowledge consumers. In the low-knowledge group, the moderating effect of knowledge on the trust–perceived risk relationship is smaller than in the high-knowledge group.
6. Conclusions
This study utilizes survey data from Chinese consumers and employs a moderated dual mediation model to examine how consumer trust in meat substitutes influences acceptance. It explores the mediating roles of perceived benefits and perceived risks in the relationship between consumer trust and acceptance, and investigates how consumer knowledge moderates the effects of trust on these mediators.
Firstly, consumer trust in meat substitutes positively influences perceived benefits and acceptance, while negatively affecting perceived risks.
Secondly, perceived benefits and perceived risks mediate the effect of consumer trust on acceptance. The indirect effect of trust on acceptance, mediated by these variables, is stronger than the direct effect.
Lastly, consumer knowledge significantly moderates the relationships among trust, perceived benefits, and perceived risks. As consumer knowledge increases, the positive effect of trust on perceived benefits diminishes, whereas its negative effect on perceived risks becomes more pronounced.