Contents lists available at ScienceDirect Technological Forecasting & Social Change journal homepage: www.elsevier.com/locate/techfore Understanding business model in the Internet of Things industry Concetta Metallo a, ⁎ , Rocco Agrifoglio b , Francesco Schiavone c,d , Jens Mueller e a Department of Sciences and Technology, University of Naples ‘Parthenope’, Centro Direzionale – Isola C4, 80143 Naples, Italy b Department of Management, Accounting and Economics, University of Naples ‘Parthenope’, Via Generale Parisi, 80132 Naples, Italy c DISAQ, Department of Management and Quantitative Studies, University of Naples ‘Parthenope’, Via Generale Parisi, 80132 Naples, Italy d Paris School of Business, Department of Strategy and Management, 59 Rue Nationale, 75013 Paris, France e Waikato Management School, The University of Waikato, Private Bag 3105, Hamilton, New Zealand ARTICLE INFO Keywords: Business model Canvas Internet of Things ABSTRACT This research presents the results of an exploratory study of how organisations operating in the Internet of Things (IoT) industry are building and innovating their business model (BM). Using an explorative sequential approach through the multiple-case study method, we apply the “Canvas BM” framework to explore the BM of three companies operating in IoT industry, namely Intel, Solair, and Apio. The paper finds the most important building blocks - key activities, key resources, and value proposition - and most critical related factors enabling IoT-oriented organisations to create and capture value. Furthermore, our results also suggest that the main difference in the processes of BM building and innovation depend on the different capabilities and competencies possessed by organisations. This study therefore advances the theoretical understanding of the critical factors for the value creation process in the IoT industry's organisations and offers interesting implications for management theory and practice. 1. Introduction Over the last two decades, the Internet of Things (henceforth: IoT) has been in a constant state of evolution. Some of the most prestigious management-consulting firms, such as Gartner, McKinsey analysis, and ABI Research, forecast that IoT devices would grow from about 5 billion in 2014 to as many as 20 billion devices by 2020. In terms of hardware spending, consumer applications will amount to $1534 billion by 2020, while the use of connected things in the enterprise will rise to $1477 billion in 2020 (Gartner, 2015). Therefore, IoT is included by the US National Intelligence Council in the list of six “Disruptive Civil Tech- nologies” with potential impacts on US national power (NIC, 2008). IoT represents a novel paradigm that is rapidly gaining ground in the modern economics, with a high impact on several aspects of the everyday-life of both private and business users (Atzori et al., 2010). IoT describes “the interconnection of objects or ‘things’ for various purposes including identification, communication, sensing, and data collection” (Oriwoh et al., 2013, p. 122). In particular, it consists of an infrastructure that is able to measure, identify, track, and monitor ob- jects for connecting things, sensors, actuators, and other smart tech- nologies (Uckelmann et al., 2011) as well as simplifying people's lives through tasks automation (Espada et al., 2011). There are several fields of application for IoT technologies, such as the smart industry (or Industry 4.0), transportation and logistics, healthcare, personal life domain and smart cities, emergency management (Atzori et al., 2010; Yang et al., 2013; Kim and Kim, 2016; Suwon and Seongcheol, 2016). Considering the growing importance of the IoT industry in the global economy, academics are also increasing focusing their attention on several issues within a range of research fields. However, prior lit- erature is concentrated mainly on technological aspects, meaning that managerial issues have been lacking compared to technical research (Kiel et al., 2016). According to the traditional technical approach, IoT technologies and overall digital technologies are studied in terms of technical infrastructure or platform (e.g., Eisenmann et al., 2006; Tiwana et al., 2010; Tiwana, 2014; Eaton et al., 2015; Spagnoletti et al., 2015). Thus, IoT technologies are considered as software-based plat- forms that that provides core functionality shared by software sub- systems that connect to the platform and add functionality to it (Tiwana et al., 2010). This IoT technologies' view emphasises features such as interoperability or complementarity for showing these platforms seldom operate in isolation from other technologies, but generally offer functionality for other platforms or complementary technologies (Eisenmann et al., 2006; Eisenmann et al., 2011; Baden-Fuller and Haefliger, 2013; Tiwana, 2014). At the same time, there is emerging a managerial research field for exploring how IoT is changing the way of interpreting the business https://doi.org/10.1016/j.techfore.2018.01.020 Received 21 February 2017; Received in revised form 15 June 2017; Accepted 18 January 2018 ⁎ Corresponding author. E-mail addresses: metallo@uniparthenope.it (C. Metallo), agrifoglio@uniparthenope.it (R. Agrifoglio), schiavone@uniparthenope.it (F. Schiavone), m@usainfo.net (J. Mueller). Technological Forecasting & Social Change xxx (xxxx) xxx–xxx 0040-1625/ © 2018 Elsevier Inc. All rights reserved. Please cite this article as: Metallo, C., Technological Forecasting & Social Change (2018), https://doi.org/10.1016/j.techfore.2018.01.020