Biplot analysis: a study of the change of customer behaviour on e-commerce

Area of Science:

• Business and Economics
• Consumer Behavior Analysis
• Digital Commerce Research

Background:

• The COVID-19 pandemic profoundly impacted global lifestyles, notably accelerating e-commerce adoption and shifting consumer purchasing patterns.
• Pre-pandemic consumption habits were disrupted, leading to increased online shopping across various product categories.
• Understanding these shifts is crucial for businesses operating in the digital marketplace.

Purpose of the Study:

• To determine if significant differences exist in average e-commerce sales before and during the COVID-19 pandemic in Indonesia.
• To identify specific product categories most affected by pandemic-induced changes in consumer behavior.
• To visualize and analyze the transformation of customer behavior in response to the pandemic.

Main Methods:

• Utilized T-Test Paired Samples to compare mean sales data from pre-pandemic and pandemic periods.
• Employed Biplot analysis for visualizing changes in customer behavior.
• Collected data from 63 respondents through questionnaires, using purposive sampling for participant selection.
• Focused on six key variables to assess e-commerce sales performance.

Main Results:

• A statistically significant difference in mean sales was observed between the pre-pandemic and pandemic periods.
• Specific sectors showing significant sales changes include services/online products, food and beverages, electronics, and cosmetics/skincare.
• Biplot analysis visually confirmed shifts in customer purchasing behavior attributed to the pandemic.

Conclusions:

• The COVID-19 pandemic demonstrably altered customer behavior within the Indonesian e-commerce landscape.
• Significant sales increases in essential and convenience-driven categories highlight adaptive consumer strategies.
• The findings provide valuable insights into the lasting effects of the pandemic on online retail.