The influencing factors of consumers purchase behaviour preference in the internet market based on joint analysis

This study employs conjoint analysis to examine the determinants of consumer purchase behaviour preferences in digital market environments. The research methodology involves decomposing products into key attributes and collecting corresponding consumer preference data, followed by determining full-profile preferences and calculating attribute importance weights. Subsequently, conjoint analysis is applied to estimate simulated product market shares, thereby quantifying the influence of different attributes on consumer purchase decisions. The Bradley-Terry-Ross model is then implemented to compute attribute utility values and validate the findings. The analysis reveals that logistics distribution systems and e-commerce platform features constitute the primary factors influencing purchase behaviour preferences. Through iterative recommendation processes, the proposed method achieves a peak purchase prediction accuracy of 88.1%, demonstrating its efficacy in forecasting consumer preferences with substantial precision.

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Publication Details

Journal
International Journal of Business Intelligence and Data Mining
Published
2025-01-01
DOI
https://doi.org/10.1504/ijbidm.2025.10072624
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

The influencing factors of consumers purchase behaviour preference in the internet market based on joint analysis

Meijuan Li
International Journal of Business Intelligence and Data Mining
Customer churn and segmentation
article

The influencing factors of consumers purchase behaviour preference in the internet market based on joint analysis

Meijuan Li
article en

Abstract

This study employs conjoint analysis to examine the determinants of consumer purchase behaviour preferences in digital market environments. The research methodology involves decomposing products into key attributes and collecting corresponding consumer preference data, followed by determining full-profile preferences and calculating attribute importance weights. Subsequently, conjoint analysis is applied to estimate simulated product market shares, thereby quantifying the influence of different attributes on consumer purchase decisions. The Bradley-Terry-Ross model is then implemented to compute attribute utility values and validate the findings. The analysis reveals that logistics distribution systems and e-commerce platform features constitute the primary factors influencing purchase behaviour preferences. Through iterative recommendation processes, the proposed method achieves a peak purchase prediction accuracy of 88.1%, demonstrating its efficacy in forecasting consumer preferences with substantial precision.

International Journal of Business Intelligence and Data MiningVol. 1(1)
Luoyang Institute of Science and Technology (CN)
Openalex Percentile: Top 75%
Customer churn and segmentation
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The influencing factors of consumers purchase behaviour preference in the internet market based on joint analysis — Meijuan Li · International Journal of Business Intelligence and Data Mining (2025) | TGRS Research Map | TGRS