Social Commerce from Seller and Region Perspective: A Data Mining for Indonesian E-commerce

Abstract

As a subset of e-commerce, social commerce grows fast in many countries. Studies on social commerce primarily focused on consumer behavior, especially purchase intention. This study takes a different perspective by focusing on the e-commerce sellers as an aggregate in regions within a country. The study object is provinces in Indonesia, a country with the most prominent e-commerce and social commerce among Southeast Asian countries. The general objective of this study is to characterize social commerce firms across regions in Indonesia. The specific objectives are (1) to group provinces based on the e-commerce and social commerce-related variables and (2) to specify a group of provinces based on business and e-commerce profiles. This secondary and quantitative research adopts a data mining approach to analyze the official data from the BPS-Statistics Indonesia. The Cross-Industry Standard Process for Data Mining framework was adopted as a methodology and the Knime Analytics Platform as a computational software. The result classifies provinces into two: high and low social commerce. Provinces with high social commerce firms are characterized by younger entrepreneurs, more entrepreneurs with university backgrounds, newer e-commerce establishments, more fashion and beauty products, more resellers, and more revenue from the social media channel. Local governments might consider the finding to understand their province's position in the cluster and make policies to increase social commerce entrepreneurs.