Perceived behavioural control and animal-welfare ethics predict cultured meat acceptance in India: An extended Theory of Planned Behaviour analysis

This record contains the supplementary materials and the complete reproducibility package accompanying the research article "Perceived behavioural control and animal-welfare ethics predict cultured meat acceptance in India: An extended Theory of Planned Behaviour analysis" by Nematullah Farooqui and Anna Kaczmarek (submitted to Foods, MDPI, 2026). The study applied an extended Theory of Planned Behaviour to identify the psychological predictors of intention to try cultured meat among English-speaking Indian consumers (N = 255). Data were collected through an anonymous, self-administered online questionnaire in December 2025 using non-probability convenience and snowball sampling. The analysis combined covariance-based latent-variable structural equation modelling (with a common-method-variance check) with a pre-specified package of robustness and triangulation analyses, including Holm–Bonferroni multiplicity correction, sensitivity power analysis, bootstrap robust standard errors, Bayesian path modelling, partial least squares SEM, and regularised machine-learning triangulation. Contents Supplementary_Materials.docx — the full survey questionnaire (Appendix A) and Supplementary Tables S1–S10.Reproducibility_Package.zip — the complete analytic pipeline: 24 Python scripts (Steps 01–23 and a correlation analysis), the anonymised dataset (the raw questionnaire export and the cleaned analytic dataset with computed construct scores, in CSV and Excel, N = 255), a pinned requirements file, and a README with full setup and execution instructions.All results reported in the article and its supplementary materials can be regenerated from these files. The pipeline was developed in Python 3.13 and is deterministic given the pinned package versions and a fixed random seed (20260525); the README documents the exact execution order and the mapping of each script to the corresponding tables and figures. Ethics and privacy. Participation was voluntary and anonymous, and implied informed consent was obtained electronically. The dataset contains no identifiable or sensitive personal data. When using these materials, please cite the associated journal article.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-29
DOI
https://doi.org/10.5281/zenodo.20444748
Primary Topic
Agriculture Sustainability and Environmental Impact
Type
article
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article

Perceived behavioural control and animal-welfare ethics predict cultured meat acceptance in India: An extended Theory of Planned Behaviour analysis

Nematullah Farooqui
Zenodo (CERN European Organization for Nuclear Research)
Agriculture Sustainability and Environmental Impact
article

Perceived behavioural control and animal-welfare ethics predict cultured meat acceptance in India: An extended Theory of Planned Behaviour analysis

Nematullah Farooqui
article en

Abstract

This record contains the supplementary materials and the complete reproducibility package accompanying the research article "Perceived behavioural control and animal-welfare ethics predict cultured meat acceptance in India: An extended Theory of Planned Behaviour analysis" by Nematullah Farooqui and Anna Kaczmarek (submitted to Foods, MDPI, 2026). The study applied an extended Theory of Planned Behaviour to identify the psychological predictors of intention to try cultured meat among English-speaking Indian consumers (N = 255). Data were collected through an anonymous, self-administered online questionnaire in December 2025 using non-probability convenience and snowball sampling. The analysis combined covariance-based latent-variable structural equation modelling (with a common-method-variance check) with a pre-specified package of robustness and triangulation analyses, including Holm–Bonferroni multiplicity correction, sensitivity power analysis, bootstrap robust standard errors, Bayesian path modelling, partial least squares SEM, and regularised machine-learning triangulation. Contents Supplementary_Materials.docx — the full survey questionnaire (Appendix A) and Supplementary Tables S1–S10.Reproducibility_Package.zip — the complete analytic pipeline: 24 Python scripts (Steps 01–23 and a correlation analysis), the anonymised dataset (the raw questionnaire export and the cleaned analytic dataset with computed construct scores, in CSV and Excel, N = 255), a pinned requirements file, and a README with full setup and execution instructions.All results reported in the article and its supplementary materials can be regenerated from these files. The pipeline was developed in Python 3.13 and is deterministic given the pinned package versions and a fixed random seed (20260525); the README documents the exact execution order and the mapping of each script to the corresponding tables and figures. Ethics and privacy. Participation was voluntary and anonymous, and implied informed consent was obtained electronically. The dataset contains no identifiable or sensitive personal data. When using these materials, please cite the associated journal article.

Zenodo (CERN European Organization for Nuclear Research)
University of Life Sciences in Poznań (PL)
Openalex Percentile: Top 6%
Agriculture Sustainability and Environmental Impact
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