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利用机器学习方法揭示益生菌补充剂市场格局:市场产品、销售模式及未来预测——以黑山为例

Uncovering the Probiotic Supplement Landscape: Market Offerings, Sales Patterns, and Future Forecasts Using Machine Learning Approach - A Case Study of Montenegro.

作者信息

Anđela Martinović, Ivan Martinović, Mora Diego, Arioli Stefania

机构信息

Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Via Celoria 2, 20133, Milan, Italy.

Faculty of Electrical Engineering, University of Montenegro, Džordža Vašingtona Bb, 81000, Podgorica, Montenegro.

出版信息

Probiotics Antimicrob Proteins. 2024 Nov 25. doi: 10.1007/s12602-024-10400-6.

Abstract

Global increasing awareness about the health benefits of probiotics resulted to explorational growth in probiotic food supplement market. However, in some countries such as Montenegro, specific probiotic supplement regulation and comprehensive market analysis are absent, hampering the understanding of consumer preferences, market trends, and potential economic impacts of this industry. This article aims to delve into the Montenegrin market of probiotic food supplements, thoroughly examining various product types and their key characteristics. Using the case study of a pharmacy chain, as an example of organizational level, the sales, sale patterns, and trends are examined. Furthermore, we developed and employed a machine learning model for forecasting future sales. The market analysis highlighted the importance of setting national probiotic supplement regulations to enhance Montenegrin consumer understanding and trust, ensuring product efficacy and safety. Our study clearly showed increased interest in probiotic supplements as well as a constant positive trend in probiotic supplement sales. Furthermore, we found the correlation between foreign tourist visits in Montenegro and the yearly seasonality of probiotic supplement sales. Developed support vector regression machine learning model on time series data showed a good forecasting accuracy, clearly indicating that the same could be used for national sales forecasting. The insights from this study could promote the establishment of national probiotic supplement regulations, enhancing consumer protection and market credibility. Additionally, developed machine learning model provides the industry with valuable predictive tool, enabling companies to optimize their supply chains, effectively meet demand, and make data-driven decisions that could support sustainable market growth.

摘要

全球对益生菌健康益处的认识不断提高,导致益生菌食品补充剂市场呈探索性增长。然而,在黑山等一些国家,缺乏具体的益生菌补充剂监管和全面的市场分析,这阻碍了对该行业消费者偏好、市场趋势和潜在经济影响的了解。本文旨在深入研究黑山的益生菌食品补充剂市场,全面考察各种产品类型及其关键特性。以一家连锁药店为例,从组织层面考察其销售情况、销售模式和趋势。此外,我们开发并应用了一种机器学习模型来预测未来的销售情况。市场分析强调了制定国家益生菌补充剂法规对于增强黑山消费者的理解和信任、确保产品功效和安全性的重要性。我们的研究清楚地表明,消费者对益生菌补充剂的兴趣增加,以及益生菌补充剂销售持续呈积极趋势。此外,我们发现黑山外国游客访问量与益生菌补充剂销售的年度季节性之间存在关联。基于时间序列数据开发的支持向量回归机器学习模型显示出良好的预测准确性,清楚地表明该模型可用于全国销售预测。这项研究的见解可以促进国家益生菌补充剂法规的建立,加强消费者保护和市场信誉。此外,开发的机器学习模型为该行业提供了有价值的预测工具,使公司能够优化其供应链,有效满足需求,并做出数据驱动的决策,以支持市场的可持续增长。

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