Innovation Ecosystems in Retail: Uncovering Technological Trends and Collaboration Networks Through Patent Mining

Abstract

Retail technology adoption is essential for improving operational efficiency, enhancing customer engagement, and supporting sustainable growth in a highly competitive environment. Despite the growing importance of digital transformation in retail, significant research gaps remain in understanding collaborative innovation networks within this sector. This study addresses these gaps by utilizing Social Network Analysis (SNA) to examine patent registrations in retail technology, analyzing a dataset of 36,411 patents from 1995 to 2024. The methodology includes network construction, community detection, and keyword analysis, mapping out 8,225 entities and 14,805 collaborations. Results reveal IBM, Target Brands, and Procter & Gamble as pivotal entities with high network centrality, highlighting their influence across key technological domains like AI, digital commerce, and retail security. The research categorizes technologies into 15 domains—such as Core Retail Operations, Digital Commerce, and Retail Communication—exposing seven major clusters where innovation efforts are concentrated. These findings offer practical insights for corporations, SMEs, startups, and policymakers aiming to navigate technological change and optimize strategic investments in retail. By detailing the relationships between leading entities and emerging technology clusters, this study provides a comprehensive view of the retail innovation landscape, aiding stakeholders in decision-making around technology adoption, collaborative opportunities, and competitive positioning in an increasingly digital retail ecosystem.

Keywords

• Retail technology
• patent analysis
• social network analysis (SNA)
• digital commerce
• retail industry collaboration
• data-driven decision-making