Green Recommendation Systems for Smart and Sustainable Cities: A Proof-of-Concept on the City of Milan

This work contributes to the study of Green Information Systems (GIS) for the transition to smarter and more sustainable cities, as well as drivers of innovation and entrepreneurship. The literature on GIS has primarily focused on the use of sensory data, neglecting the role of information systems to provide other types of data-driven services, such as knowledge or partnership recommendations. To address this gap, this paper offers a first conceptualization for the use of Green Recommendation Systems (GRS) and a first preliminary application to the Italian city of Milan. This was achieved by reviewing existing literature on GIS and recommendation systems, and particularly on professional social matching. From there, an original framework presenting the functioning of a GRS for Smart and Sustainable Cities (GRS3C) was designed. This was then tested by simulating its usage for the city of Milan, focusing on the recommendation of academic knowledge and actors specialized on air pollution. Preliminary results show that a GRS3C may support policymakers and entrepreneurs in understanding the complexity of current issues, as well as in identifying local actors with relevant expertise. Doing so, this paper expands the concept of GIS and provides a new application of professional social matching concepts, thus contributing to both research areas. As a proof-of-concept, it may motivate the development of actual GRSs which could foster innovation and entrepreneurship for smart and sustainable cities.