The Role of Management Information Systems in Enhancing AI-Powered Recommendation Systems and Their Impact on Consumer Behaviour in E-Commerce

Introduction: AI recommendations are changing the way people shop online. But how useful they are depends on how much people trust them. If shoppers believe the suggestions are good, they’re more likely to buy. That’s why businesses need to understand consumer trust to make AI work better for them. Objective: The effects of trust in AI recommendation on purchasing intention and customer satisfaction. Methods: We used a quantitative survey of e-commerce users; regressions and moderation analysis using R were used to assess how trust levels influenced consumer engagement. Results: The study's findings indicate that consumers who moderately trust AI recommendations display the greatest engagement and purchase intent. Trust can impair AI reliance at low levels through doubt and at extremely high levels through distrust. Conclusions: This study shows that effectiveness of AI increases when people trust it. Businesses should be open about how AI makes suggestions. They should also make recommendations more personal to keep customers engaged. When consumers feel that AI truly understands their preferences, they develop a stronger sense of control, which fosters trust and enhances engagement.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-24
DOI
https://doi.org/10.52783/jisem.v10i24s.3926
Citations
1
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
2.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Management Information Systems in Enhancing AI-Powered Recommendation Systems and Their Impact on Consumer Behaviour in E-Commerce

Ajit Kumar Singh
1 citations
Journal of Information Systems Engineering & Management
Impact of AI and Big Data on Business and Society
2.11
article

The Role of Management Information Systems in Enhancing AI-Powered Recommendation Systems and Their Impact on Consumer Behaviour in E-Commerce

Ajit Kumar Singh
article en
1 citations

Abstract

Introduction: AI recommendations are changing the way people shop online. But how useful they are depends on how much people trust them. If shoppers believe the suggestions are good, they’re more likely to buy. That’s why businesses need to understand consumer trust to make AI work better for them. Objective: The effects of trust in AI recommendation on purchasing intention and customer satisfaction. Methods: We used a quantitative survey of e-commerce users; regressions and moderation analysis using R were used to assess how trust levels influenced consumer engagement. Results: The study's findings indicate that consumers who moderately trust AI recommendations display the greatest engagement and purchase intent. Trust can impair AI reliance at low levels through doubt and at extremely high levels through distrust. Conclusions: This study shows that effectiveness of AI increases when people trust it. Businesses should be open about how AI makes suggestions. They should also make recommendations more personal to keep customers engaged. When consumers feel that AI truly understands their preferences, they develop a stronger sense of control, which fosters trust and enhances engagement.

Journal of Information Systems Engineering & ManagementVol. 10(24s)
Openalex Percentile: Top 15%
Impact of AI and Big Data on Business and Society
2.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.