BMF CP38: How social classes and health considerations in food consumption affect food price concerns
March 18, 2023
1. Project description
1.1. Main objectives
This study will examine food price concerns among urban residents across different income-based social classes. Here, health considerations in food consumption are a potential moderator.
In this research project, we use a dataset of 710 Indonesian urban residents . The research project follows the Bayesian Mindsponge Framework (BMF) [2-4]. The bayesvl R package will be employed for statistical analyses . Data and code snippets for this initial analysis were deposited at https://osf.io/cwpf9/
1.3. Main findings
The analysis results show that people from a higher income-based social class are less likely to think that food price is a main consideration regarding their family’s food consumption, which is rather intuitive. Health considerations about food have a negative moderating effect. Figure 2 shows that while the “upper class” line is the lowest, it is also the steepest. Upper-class people who are more concerned about the health aspect of their food also have a relatively high level of food price consideration.
Figure 1. Pairwise posterior distributions SocialClass and Health*SocialClass
In Figure 2, the y-axis represents food price considerations, the x-axis represents health considerations about food, and the line color represents income-based social classes.
Figure 2. Estimated probabilities of food price concerns based on social classes and health considerations
2. Collaboration procedure
Portal users should follow these steps to register to participate in this research project:
- Create an account on the website (preferably using an institution’s email).
- Comment your name, affiliation, and desired project role below this post.
- Patiently wait for the formal agreement on the project from the AISDL mentor.
If you have further inquiries, please contact us at email@example.com
If you have been invited to join the project by an AISDL member, you are still encouraged to follow the above formal steps.
All the resources for conducting and writing the research manuscript will be distributed upon project participation.
AISDL mentor for this project: Tam-Tri Le.
AISDL members who have joined this project: Quan-Hoang Vuong, Minh-Hoang Nguyen.
The research project strictly adheres to scientific integrity standards, including authorship rights and obligations , without incurring an economic burden at participants’ expenses .
 Seda FS, et al. (2020). Dataset on The Cultural Dimension of Urban Society Food Consumption in Indonesia. Data in Brief, 31, 105681.
 Vuong QH, Nguyen MH, La VP. (2022). The mindsponge and BMF analytics for innovative thinking in social sciences and humanities. De Gruyter.
 Vuong QH. (2023). Mindsponge Theory. De Gruyter.
 Vuong QH, et al. (2023). Near-Suicide Phenomenon: An Investigation into the Psychology of Patients with Serious Illnesses Withdrawing from Treatment. International Journal of Environmental Research and Public Health, 20(6), 5173.
 La VP, Vuong QH. (2019). bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with ‘Stan’. The Comprehensive R Archive Network.
 Vuong QH. (2020). Reform retractions to make them more transparent. Nature, 582(7811), 149.
 Vuong QH. (2018). The (ir)rational consideration of the cost of science in transition economies. Nature Human Behaviour, 2(1), 5.