{"title":"A machine learning-based assessments of green product purchase patterns in Tamilnadu","authors":"C. Nithya Devi, B. Subatra","doi":"10.1142/s2424786323500317","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.6000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Financial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s2424786323500317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
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.