Service automation builds on automated technologies such as robotic machines, to assist workers by automating processes and business functions. As customer expectations increase in the digital era, service automation can bring enormous benefits to business operations. Speed of service is a leading customer demand and service automation could be appropriate to meet this expectation and provide a seamless customer experience. Furthermore, service automation removes redundancy and human error while also streamlining the service process. In addition, service automation builds on information systems by providing real-time big data.

The emergence of big data analytics and other technologies has largely changed the landscape of the digital era as well as the operation of enterprises. The effectiveness of big data analytics lies in its ability to find hidden patterns and features which contain valuable information to support real-time decision analytics. Thus, information systems serve as s decision support system for enterprises and address not only the issues of data collection and data management but also big data analytics and knowledge discovery to assist decision making.

This Special Issue aims to collate research focusing on big data analytics and system design to facilitate service automation in the field of decision science. This Special Issue invites submissions focusing on big data analytics and technologies, data-driven modelling in service automation, and decision support systems using various techniques and algorithms. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Big data analytics and technologies for service automation
• Planning, design and control in robotics and automation for service automation
• Information systems including data structures, data management, data mining and knowledge discovery for service automation
• Software design and engineering for service automation
• Data-driven modelling and analysis in service automation
• Intelligent process automation systems
• Decision support systems regarding the use of artificial intelligence techniques and machine learning algorithms
• Practical case studies, theories, technological innovations and programming innovations in service automation