Application of Big Data in a Multicategory Product-Service System for Global Logistics Support

This article conducts a case study with a global logistics service value-added (GLSV) system using big data analytics (BDA), which is implemented in a machinery equipment manufacturing company to provide a multicategory product-service system (PSS) intended to enhance firm performance. Drawing on the product-service system (PSS) concept, application of big data analytics, and strategic information systems planning (SISP), the plan do check action (PDCA) concept is used to develop a research framework in order to achieve the target company's objectives through the use of a global logistics system. The current article considers a machinery and equipment company located in a developing country as the case study. Through the case study, it is ascertained how the case company develops a GLSV system with BDA applications that leads to achieving multicategory PSS applications. The results indicate that a successful multicategory PSS should consider customer demands in the system framework and construct innovative assisting functions to support customer requirements. The proposed model not only demonstrates that a firm's business models should apply big data to align product providers with multicategory product-and-service providers for the PSS in global supply chains but also proves that this approach will enhance competitive advantage.