Herd Forecasting and Acceptance Analysis of Sustainable Meat Production through 3D-Bioprinted Meat from Fish Stem Cell
DOI:
https://doi.org/10.32871/rmrj1302si.i2501Keywords:
3D-bioprinted fish meat, consumption intention, long short-term memory, neural network, sustainable production and consumptionAbstract
Background: Sustainable production and consumption have been targeted in this study through the lens of 3D bioprinted fish meat using their stem cell. Adopting recent developments from Steakholder Foods Ltd., the cruelty-free and slaughter-free process has been seen as promising for future meat sources.
Methods: This study employed a consumption intention analysis to assess acceptance and forecast the general population using an integrated machine learning algorithm comprising a neural network and long short-term memory, implemented in MATLAB R2021a. Using an established integrated framework of the health belief model and values, beliefs, and norms theory, combined with the theory of planned behavior, the researcher employed a purposive sampling approach among 738 valid respondents.
Results: It was seen that self-efficacy, perception of environmental concern, perceived values, personal beliefs, ecological worldview, health beliefs, and norms affected the positive consumption intention.
Conclusion: It was implied that high positive pro-environmental impact and perceived value were dominant variables affecting the herd acceptance of 3D bioprinted fish meat. This further implicated the need for slaughter-free and cruelty-free alternative food sources. Further policy and implications on sustainable production and consumption were developed.
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