دورية أكاديمية
Classification and Prediction of Food Safety Policy Tools in China Based on Machine Learning.
| العنوان: | Classification and Prediction of Food Safety Policy Tools in China Based on Machine Learning. |
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| المؤلفون: | Sha D; School of Business, Jiangnan University, Wuxi 214122, Jiangsu, China., Du P; School of Business, Jiangnan University, Wuxi 214122, Jiangsu, China; Research Institute for Food Safety Risk Management, School of Business, Jiangnan University, Wuxi 214122, Jiangsu, China., Wu L; School of Business, Jiangnan University, Wuxi 214122, Jiangsu, China; Research Institute for Food Safety Risk Management, School of Business, Jiangnan University, Wuxi 214122, Jiangsu, China. Electronic address: wlh6799@126.com. |
| المصدر: | Journal of food protection [J Food Prot] 2024 Jun; Vol. 87 (6), pp. 100276. Date of Electronic Publication: 2024 Apr 12. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Country of Publication: United States NLM ID: 7703944 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1944-9097 (Electronic) Linking ISSN: 0362028X NLM ISO Abbreviation: J Food Prot Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2023- : [New York, NY] : Elsevier Original Publication: Ames, Iowa, International Association of Milk, Food, and Environmental Sanitarians. |
| مواضيع طبية MeSH: | Food Safety* , Machine Learning*, China ; Humans |
| مستخلص: | Governments use policy interventions to mitigate food safety risks. Despite its crucial role, empirical studies evaluating the effectiveness of China's food safety policy tools are scarce. Drawing on a dataset encompassing 11,236 food safety policy texts from 2005 to 2021 and the incidence of problematic food products in the Eastern, Central, and Western regions of China, this study employs Latent Dirichlet Allocation (LDA) and eXtreme Gradient Boosting (XGBoost) models to facilitate the classification of policy tools and forecast the effectiveness of policy combinations. The study reveals that (1) local governments have gradually become an important supplementary maker of food safety policies, and have issued an increasing number of policy tools year by year. (2) Mandatory policy tools are predominant in number and have the highest legal hierarchy and authority levels, followed successively by guiding policy and voluntary policy tools. (3) Mandatory policy tools demonstrated the most effective intervention results, followed successively by guiding policy and voluntary policy tools. (4) The forecast analysis reveals that combinations of policies within high-growth frameworks and those driven by mandatory regulations emerge as the most effective. Therefore, the balance of policy tools in terms of type, effectiveness, and quantity, as well as their applicability in different situations, should all be taken into account. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Food safety policy; Food safety risk; Policy effectiveness; Policy tools; eXtreme Gradient Boosting |
| تواريخ الأحداث: | Date Created: 20240414 Date Completed: 20240526 Latest Revision: 20240526 |
| رمز التحديث: | 20240527 |
| DOI: | 10.1016/j.jfp.2024.100276 |
| PMID: | 38615993 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1944-9097 |
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| DOI: | 10.1016/j.jfp.2024.100276 |