Leveraging in-store technology and AI: Increasing customer and employee efficiency and enhancing their experiences

• Main Authors: GREWAL, Dhruv, BENOIT, Sabine, NOBLE, Stephanie, GUHA, Abhijit, AHLBOM, Carl-Philip, NORDFALT, Jens
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: In-store technology; AI; Retail employees; In-store; Retail strategy; Efficiency; Enhancements; Marketing; Sales and Merchandising; Technology and Innovation
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/7570; https://ink.library.smu.edu.sg/context/lkcsb_research/article/8569/viewcontent/1_s2.0_S0022435923000507_pvoa_nc_nd.pdf
• Institution: Singapore Management University

Due to digital innovations, retailing is undergoing radical changes. Scholars have proposed frameworks to address outcomes of implementing technology e.g., an increased customer experience, efficiency gains, consumer or employee acceptance. Existing frameworks concentrate primarily on the consumer perspective, focus on specific technologies (e.g., AI) and covering the customer journey. In contrast, this paper also focuses on the employee perspective, and how technology influences the employee journey. Since the convenience offered by online retailers puts offline retailers under pressure, this research focuses on in-store technology. Based on a comprehensive review of managerial and academic literature and expert interviews, we propose a framework covering customers and employees, and technology's function (increasing efficiency or experience), as also including more traditional and newer technologies, such as robots and AI. We identify and showcase technologies increasing efficiency for customers (quadrant 1, e.g., checkout options or autonomous stores) or for employees (quadrant 2, e.g., in-store robots), and enhancing the experience for customers (quadrant 3, e.g., retailer apps or communication) or for employees (quadrant 4, e.g., exoskeletons or smart wearables). Finally, for each of these quadrants, we identify future research opportunities.