Towards the eco-design of Artificial Intelligence and Big Data applications: a bibliometric analysis of related research

Abstract

Given the impacts of information and communications technologies on the planet and people, researchers from all disciplines need to pay attention to the environmental footprints and sustainable opportunities associated with the Artificial Intelligence (AI) and Big Data applications. In order to provide a preliminary discussion on the eco-design of AI and Big Data applications, the paper aims to map out the sources and topics to explore (1) the intersections of eco-design with AI and Big Data, and (2) the sustainable and eco-friendly design. Based on a bibliometric analysis of 236 articles gathered from the Web of Science (WoS) database, the paper has identified main research topics, publication outlets, research fronts, and intellectual bases and explored their inter-relationship and grouping. The leading application disciplines include construction & building technology, automation & control system, computer & information science, and business & economics. Multi-disciplinary and inter-disciplinary journals such as Sustainability, Journal of Cleaner Production, and Sustainable Cities and Society have been proven to be more receptive to such eco-design research outputs. As the notion of eco-design of AI and Big Data applications is expected to be pertinent and relevant for designing greener strategies, products and services for green digital transformation, we argue that more concerted efforts must be made to advance both the theoretical and empirical research on the nascent topic among researchers, funding bodies, policy-makers and industry professionals.