This study based on Macinnis and Jaworski’s MOA theory examines the influencing mechanism of the intention of Chinese consumers to consume prepared food. According to this theory motivation, opportunity and ability jointly affect the occurrence of individual or organisational behaviours (Macinnis and Jaworski, 1989). According to this conceptual framework, motivation is considered the direct driving force of action (i.e., ‘whether you want to do it’); opportunity is primarily a restrictive environmental factor affecting motivation and behavioural activity (i.e., ‘whether it is permissible’); and ability refers to the skills, knowledge, resources and other factors required to drive the production of behaviour (i.e., ‘whether it can be done’) (Macinnis et al., 1991). The MOA theory aligns with the logic of consumer psychology probing the intention of consumers to buy prepared food from the micro-subjects perspective. Therefore, this study uses the MOA theory to construct a model of consumer intention to buy prepared food and aims to identify the key influencing factors of the intention of Chinese consumers to purchase prepared food.

This study is primarily grounded in the MOA, relevant literature and preliminary evaluations conducted to ensure the superior content validity of the administered questionnaire. Specific items were designed as closed questions. The research group responsible for this study invited experts to review and modify the contents of the questionnaire, which was further refined based on a preliminary investigation conducted with 20 students from Jiangsu Normal University. The study programme was approved following an ethical review conducted by the Faculty Committee of Jiangsu Normal University (Protocol Ref#: JSNU-H2024CG-001). The questionnaire also incorporated informational prompts to adhere to ethical requirements and minimise social expectation bias. These prompts were positioned in the guidance section of the questionnaire and included statements such as ‘there are no right or wrong answers’, ‘participation is voluntary’, ‘questionnaire responses will be kept confidential’ and ‘participants can withdraw at any time’.

All questionnaire items were evaluated on a five-point Likert-like scale in which 1 indicated complete disagreement and 5 signified complete agreement. Items related to the motivation factor were designed with reference to Han et al.’s (2023) study; statements testing the opportunity factor were adapted from Wang (2018) and queries on the ability factor were based on Malone’s (1990) work. Two aspects of consumer intention to buy prepared food (IN) were measured: readiness to buy and intention to recommend others to buy. Table 1 presents the definitions and descriptive statistics of the variables measuring information sources.

The study survey targeted adult Chinese consumers (18 years and older). From February to March 2024, a simple random sampling method was employed to select participants. A mixed-method approach, combining both online and offline questionnaires, was utilised for data collection. Online surveys were distributed through standardized electronic questionnaires on the SoJump platform, with the survey link disseminated widely. For the offline component, paper questionnaires were administered in key locations, including large shopping malls, communities, and local markets, ensuring a diverse representation of the population. A total of 752 questionnaires were collected for the study.

The simple random sampling method was chosen to ensure that every individual in the target population had an equal probability of selection. This widely used and well-established method is considered reliable in survey research (Erol et al., 2023; Lanfranchi et al., 2016). However, the combined online and offline data collection approach may introduce some biases, particularly in terms of accessibility to digital platforms and the geographic and demographic concentration of the offline survey locations. To mitigate these potential biases, efforts were made to ensure a balanced distribution of the sample across different regions and consumer segments. The representativeness of the sample was further enhanced by selecting a variety of survey locations, thereby capturing a comprehensive range of consumer behaviours and preferences.

The initial data processing was performed after the questionnaires were collected. Questionnaires with short answer times, uniform or duplicated responses and missing values were invalidated and eliminated. Subsequently, the data were imported into SPSS 27.0 software for statistical analysis and thorough examination. The method of replacing anomalous values with their respective average values was employed to address individual data anomalies and ensure comprehensive data cleaning. Eventually, a total of 718 valid data samples were obtained at an effective rate of 95.479%.

In this study, we classified prepared foods according to the NOVA classification system, which includes Unprocessed or Minimally Processed Foods (Group 1), Processed Culinary Ingredients (Group 2), Processed Foods (Group 3), and Ultra-Processed Foods (Group 4) (Monteiro et al., 2019). According to the “Notice on Strengthening the Food Safety Supervision of Prepared Foods” jointly issued by the State Administration for Market Regulation, the Ministry of Education, the Ministry of Industry and Information Technology, the Ministry of Agriculture and Rural Affairs, the Ministry of Commerce, and the National Health Commission in March 2024, prepared foods are clearly defined as products that have been appropriately processed and packaged and can be consumed after heating or simple cooking. These foods are typically produced through industrialized and standardized methods, ensuring a longer shelf life through advanced storage and processing technologies without the use of preservatives.

According to the notice, the scope of prepared foods includes, but is not limited to, prepared dishes, frozen ready-to-cook meat products, frozen rice and noodles, etc. It does not include fresh-cut vegetables (e.g., vegetables that are simply cleaned, peeled, or cut), staple foods (e.g., frozen rice and noodle products, boxed meals, etc.), ready-to-eat foods (e.g., canned foods, sausages, salads, etc.), dishes made in central kitchens, or foods containing preservatives. This study primarily focuses on prepared foods that meet the definition above, which are considered to primarily belong to the Ultra-Processed Foods (Group 4) category in the NOVA classification.

The Structural Equation Model (SEM) is an analytical framework that utilises the covariance matrix of variables to examine causal relationships among them. It effectively combines factor analysis and path analysis into a single quantitative research paradigm. This model allows for simultaneous estimation of both factor structures and relationships, clarifying the causal chains within complex combinations of causal conditions. Additionally, SEM estimates the overall fit between the model and the sample data, enabling verification of the model’s overall suitability. Given the complex path relationships and the potential for subjective measurement errors in latent variables in the theoretical model constructed in this study, SEM is employed for empirical analysis.

A total of 718 valid questionnaires were collected in this study. The distribution characteristics of the samples are shown in Table 2.

We tested the internal consistency of the scale via Cronbach’s α coefficient. The results revealed that the overall Cronbach’s α coefficient of the questionnaire was 0.908, and the Cronbach’s α of each latent variable ranged from 0.805 to 0.923. This outcome indicates that the measurement model fit the data satisfactorily and exhibited good internal consistency.

In addition, we employed the Kaiser–Meyer–Olkin (KMO) and Bartlett sphericity tests to determine whether the study data were suitable for factor analysis. Next, we utilised exploratory factor analysis to determine whether the pre-grouping was reasonable. The KMO statistic for the study was calculated at 0.929, and the significance of the Bartlett sphericity test was 0.000, indicating that the data were suitable for exploratory factor analysis. We performed an exploratory factor analysis on the measurable variables of influencing factors of prepared food purchase using SPSS27.0 to analyse the mechanism of influencing factors of prepared food purchase intentions. We determined the number of factors included in the model statistics using the Oblimin oblique rotation method because of the correlation between the variables.

We verified the rationality of pre-grouping in this study using exploratory factor analysis. The test results of the factor load and reliability of the measurable variables elucidated that the variance contribution of the first effective factor of the dimension formed by each latent variable exceeded 70%. Thus, the hypothesis model displayed good structural validity of the four latent variables and 17 measurable variables.

We utilised the AMOS 26.0 software to construct the SEM to test the hypothesis relationship between the study variables. The overall fit results presented in Table 3 confirm a good fit between the theoretical model and the sample data. Thus, the model constructed for this study was reasonable and reliable.

This study based on the MOA theory and SEM was conducted with survey data obtained from 718 adult consumers in China. It explored the influence mechanism of the constructs of motivation, opportunity and ability on the purchase intentions of consumers apropos prepared foods. The results revealed significant direct effects and confirmed the applicability of our model based on the MOA theory. The factors of motivation, opportunity and ability were also found to exert a positive impact on the purchase intentions of consumers vis-à-vis prepared foods. This outcome aligns with the conclusions derived by Yener et al. (2023) and Jiao and Wang (2024).

Further analysis of the degree to which varied factors influenced the purchase intentions towards prepared food evidenced that opportunity factors represented the cornerstones of consumer intentions to buy prepared foods. This result agrees with the outcomes reported by Furst et al. (1996) and Long et al. (2023). Opportunity factors include policy and institutional support, media publicity and the trust of relatives and friends of consumers, which can significantly increase their likelihood of buying prepared foods. The ability factor substantively supported purchase intentions towards prepared foods, in congruence with the results reported by Arvola et al. (2008) and Arli et al. (2018). The ability primarily entails economic ability, knowledgeability and behavioural accessibility of consumers. Prepared foods satisfy the purchasing needs of consumers because of their simple production and time-saving characteristics. Motivational factors are deemed to catalyse consumer purchase intentions towards prepared foods, and the results of this study align with previous studies. Convenience and health are important motivators in the context of purchasing prepared foods because they echo consumer quests for high-efficiency, time-saving and nutritious products. The combined effects of these two motivators encourage and shape consumer purchase intentions towards prepared foods.

Our comparison of the path coefficients of direct effects revealed that opportunity factors exercised the most influence on purchase intentions vis-à-vis prepared foods, followed by ability factors. Motivation factors least influenced consumer decision-making in this context. Our analysis of motivation factors divulged that convenience features were less important than health aspects in driving consumer decisions to buy prepared foods. This finding differs somewhat from the conclusions reported by Raimondo et al. (2024) that motivational factors most impacted consumer intention to consume recycled foods. Possibly, this study divided motivational factors into the facets of convenience and health, which could clash during actual purchase processes. For example, some high-calorie prepared foods could cause tensions between convenience and health. In such instances, consumers would weigh the two aspects and could prioritise the nutritional value and health impact of the concerned food, resulting in the diminished influence of the convenience motive. This phenomenon could further affect the actual impact of motivational factors.

The following conclusions can be derived from the analyses and comparisons of the total effect size, direct effect size and indirect effect size. The intermediate influence path of opportunity on the purchase intention of prepared food defined as Opportunity → Health → Intention contributed 0.148 indirect effect size and accounted for 47.44% of the total effect size. The direct effect size of Opportunity → Intention was 0.160, explaining 51.28% of the total effect size. Thus, opportunity can affect purchase intentions both directly and indirectly through the two motivational factors of health and convenience. This finding is analogous to the results of previous studies (Long et al., 2023; Finten et al., 2017). However, the mediating path Opportunity → Convenience → Intention was not significant: it explicated only 1.28% of the total effect size. This outcome could suggest that convenience does not pivotally mediate opportunity in influencing purchase intentions towards prepared foods, especially in contexts in which convenience may not represent the primary motivation of consumers contemplating prepared food purchases.

From the perspective of the influence path of ability on purchase intentions towards prepared foods, the intermediary effect of Ability → Convenience → Intention contributed 0.018 indirect effect size and accounted for 2.59% of the total effect size. The intermediate effect of Ability → Health → Intention contributed 0.351 indirect effect size, explaining 50.58% of the total effect size. The direct effect size of Ability → Intention was 0.325 and justified 46.83% of the total effect size. Wei and Meng (2024) and Srimulyani and Hermanto (2021) similarly enhanced the explanatory power of research conclusions by building a causal path of ‘abilities-motivation’ in exploring the relationship between ability and intention. However, some studies in the field of food waste have reported the negative mediating role of motivation vis-à-vis the ability to purchase prepared foods (Jiao et al., 2022). This adverse outcome could be attributed to the fact that the ability factor of their study focused on cooking techniques and similar aspects in consumers. However, this study attends to the knowledge and skill levels, economic abilities and behavioural accessibility of consumers apropos prepared foods. This difference highlights the dynamic and complex nature of the relationships between ability, motivation and purchase intentions in discrete research contexts.

In addressing the challenge of food waste reduction through the promotion of prepared food consumption, several strategies can be adopted by public authorities to support the transition towards sustainable consumption patterns. These strategies not only enhance consumer willingness to adopt prepared foods but also contribute to the broader goal of reducing food waste at the systemic level. This study innovatively proposes that the MOA theory provides a new policy perspective for addressing food waste issues.