基于机器学习的泰米尔纳德邦绿色产品购买模式评估

IF 0.6 Q4 BUSINESS, FINANCE
C. Nithya Devi, B. Subatra
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引用次数: 0

摘要

冠状病毒大流行对供应链产生了深远影响,从原材料到成品。饮食、卫生和总体幸福感都受到了这些变化的影响。鉴于目前的环境状况在全球范围内对人类健康和福祉有害,消费者对环保和绿色产品的偏好增加了,这是出于对食品安全的担忧。因此,消费者的态度、观念、品味和购买都变得更加环保。绿色环保营销的目的是在满足顾客需求的同时保护环境和提高社会效益。本研究的目的是找出消费者购买环保产品行为的主要驱动因素。由于社交媒体是最广泛使用的观点、参考和产品信息,本研究提出了一个基于社交媒体数据的系统,称为机器学习方案,用于评估激励消费者的因素(MLS-AFMC)。本研究使用回归分析和机器学习技术来检验印度绿色产品。此外,本研究的发现验证了客户的偏好和行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A machine learning-based assessments of green product purchase patterns in Tamilnadu
The pandemic Corona epidemic has had profound implications on supply chains, from raw materials to finished items. Diets, hygiene and general well-being have all been impacted by these changes. Customers’ preferences for eco-friendly and green products have increased as a consequence of food safety concerns, given that the current state of the environment is so detrimental to human health and well-being on a worldwide scale. As a result, customers’ attitudes, perceptions, tastes and purchases are becoming more environmentally conscious. The purpose of green/eco-friendly marketing is to meet customers’ wants and needs while simultaneously conserving the environment and boosting social benefits. This study’s goal is to identify the primary drivers of consumer behavior in the purchase of environmentally friendly goods. Since social media is the most widely used for views, references and product information, this study effort suggests a system based on social media data called machine learning scheme for assessments of factors motivating consumers (MLS-AFMC). Regression analysis and machine learning techniques were used in this study to examine Indian green goods. Furthermore, client preferences and behavior are verified by this study’s findings.
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