Internet of Things as a ‘rhabdomancy rod’ for smart ecosystems

Purpose – The aim of this paper is to shed some more light on the concept of smart ecosystem. This topic is used in different fields of science (Nam and Pardo, 2012; Petroulakis et al., 2012; Al-Nasrawi et al., 2015) and also business literature, in particular the studies from service science scholars (Spohrer and Maglio, 2008) have put much more emphasis on smart (service) systems (Maglio and Spohrer 2013; Maglio 2014). However, notwithstanding the growing recent interest a definition of what smart ecosystem represents is still missing, as an in-depth analysis about the elements more strictly connected to this notion. Design/methodology/approach – The role of technology in supporting the deployment of activities is the main element emerging in the concept of smart ecosystem. So, we have chosen one of the recent developments in the literature about technology, namely the Internet of Things (IoT) as a magnifier to analyse smart ecosystems (Kwon et al., 2015). We have selected the most relevant elements of IoT by investigating literature contributions on this topic with a bibliometric analysis through Bibexcel (Persson et al., 2009). Furthermore, we have developed a model gathering the emerging elements and we have tested it with the illustration on the DATaBenC ecosystem. Originality/value – The empirical context chosen to deploy our investigation is helpful to test if and how all the elements shaping the most recent contributions on IoT are useful to propose a definition of smart ecosystem. Thanks to this definition we can fill some of the gaps emerging from the analysis of recent scholars contributions on smart ecosystem and to favour a better comparison with the existing notions of ecosystem. Practical implications – The analysis of an empirical context will be useful to favour the adaptability of the concepts of ecosystem and smart ecosystem to the activities carried on by the actors shaping DATaBenC project; due to this the literature on the ecosystem can represent a frame to drive and analyse the deployment of an ongoing project, with mutual benefits for the research and the management in dynamic and evolutionary contexts.