AI For Sustainability: Consumer Insights On Environmental And Resource Management

As global environmental challenges intensify, Artificial Intelligence (AI) has emerged as a promising tool to enhance environmental sustainability and optimize resource management.However, the effectiveness of AI-driven solutions relies heavily on consumer acceptance and attitudes.This study investigates consumer perceptions toward the use of AI in promoting sustainable environmental practices and efficient resource utilization.This study aims to investigate consumer attitudes toward the use of Artificial Intelligence in environmental sustainability and resource management in Erode District.Employing a quantitative research design, data were collected from residents of Erode District through structured questionnaires and analyzed using multiple regression techniques to examine the influence of socio-demographic, psychological, and informational factors on consumer attitudes.Findings reveal that awareness, trust, perceived benefits, and ethical considerations significantly shape consumer acceptance of AI applications in sustainability.The study highlights the critical need for transparent communication and educational initiatives to foster positive perceptions and facilitate wider adoption of AI technologies in environmental management.These insights can guide policymakers, technology developers, and environmental advocates in designing AI solutions that are socially accepted and environmentally effective.A convenience sampling technique was employed to select a sample of 100 consumers from the Erode District.Data were collected using a structured questionnaire designed to capture relevant information regarding the study variables.To analyze the relationships and effects among these variables, regression analysis was conducted, enabling the identification of significant predictors and the strength of their influence on the outcome measures.

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Publication Details

Journal
IARJSET
Published
2025-10-15
DOI
https://doi.org/10.17148/iarjset.2025.121012
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

AI For Sustainability: Consumer Insights On Environmental And Resource Management

P. Sangeetha
IARJSET
Big Data and Business Intelligence
article

AI For Sustainability: Consumer Insights On Environmental And Resource Management

P. Sangeetha
article en

Abstract

As global environmental challenges intensify, Artificial Intelligence (AI) has emerged as a promising tool to enhance environmental sustainability and optimize resource management.However, the effectiveness of AI-driven solutions relies heavily on consumer acceptance and attitudes.This study investigates consumer perceptions toward the use of AI in promoting sustainable environmental practices and efficient resource utilization.This study aims to investigate consumer attitudes toward the use of Artificial Intelligence in environmental sustainability and resource management in Erode District.Employing a quantitative research design, data were collected from residents of Erode District through structured questionnaires and analyzed using multiple regression techniques to examine the influence of socio-demographic, psychological, and informational factors on consumer attitudes.Findings reveal that awareness, trust, perceived benefits, and ethical considerations significantly shape consumer acceptance of AI applications in sustainability.The study highlights the critical need for transparent communication and educational initiatives to foster positive perceptions and facilitate wider adoption of AI technologies in environmental management.These insights can guide policymakers, technology developers, and environmental advocates in designing AI solutions that are socially accepted and environmentally effective.A convenience sampling technique was employed to select a sample of 100 consumers from the Erode District.Data were collected using a structured questionnaire designed to capture relevant information regarding the study variables.To analyze the relationships and effects among these variables, regression analysis was conducted, enabling the identification of significant predictors and the strength of their influence on the outcome measures.

IARJSETVol. 12(10)
Openalex Percentile: Top 53%
Big Data and Business Intelligence
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