Synergy of Consumer Purchasing Behavior Analysis and Return Reason Categorization in Reducing Product Return Rates: A Study at IKEA Indonesia Fulfillment Center

Abstract

The rise of e-commerce has led to a notable escalation in product return rates, presenting a substantial difficulty in the administration of fulfillment centers. This study is to examine the impact of consumer purchasing behavior analysis and the classification of product return causes on return rates at IKEA Indonesia fulfillment centers. A quantitative methodology was employed by gathering data via a questionnaire administered to 150 respondents who had engaged in purchases and product returns within the past six months. Data analysis was performed with SmartPLS by evaluating the measurement model (outer model) and the structural model (inner model). The findings indicated that both independent variables have a positive and significant influence on product return rates. The path coefficient for Consumer Purchasing Behavior Analysis (X1) is 0.574 (T-Statistics 13.299; P-Values 0.000), whereas the path coefficient for Product Return Reason Categorization (X2) is 0.456 (T-Statistics 10.989; P-Values 0.000). Both variables concurrently account for 92.7% of the variance in product return rates (R-Square 0.927), indicating a model with exceptionally robust predictive capability. This discovery underscores the significance of an integrative strategy that combines the analysis of customer behavior patterns with the categorization of product return causes in developing data-driven return management strategies. This study offers theoretical advancements in the supply chain management literature, particularly regarding reverse logistics and consumer behavior analytics, alongside practical implications for IKEA Indonesia in formulating policies aimed at decreasing product return rates by enhancing the accuracy of product information, quality control, and logistics processes.