Contents lists available at ScienceDirect Technological Forecasting & Social Change journal homepage: www.elsevier.com/locate/techfore Business models for developing smart cities. A fuzzy set qualitative comparative analysis of an IoT platform Tindara Abbate a , Fabrizio Cesaroni a, ⁎ , Maria Cristina Cinici a , Massimo Villari b a Department of Economics, University of Messina, Piazza Pugliatti, 1, 98122 Messina, Italy b Department of MIFT, University of Messina, Viale F. Stagno D’Alcontres, 31, 98166 Messina, Italy ARTICLE INFO Keywords: Smart cities Internet of things Technology platform Business model Qualitative comparative analysis ABSTRACT What different configurations of Business Model (BM) exist in an IoT platform that aims at developing smart cities? To address this research question, we build on BM literature and argue that BM configurations have general characteristics beyond the unique traits of individual firms. We empirically investigate 21 projects for smart cities that participate to a European funded Accelerator using fuzzy set qualitative comparative analysis (fsQCA). Our findings reveal the most frequent patters of association among value propositions and BM's building blocks. In so doing, we contribute to explain and analyze the diversity among cases as well as BM's causal complexity. 1. Introduction During the last two decades, the number of projects focusing on smart cities that have been launched worldwide has constantly in- creased, thus attracting the attention of both practitioners, policy ma- kers and management scholars (European Commission, 2016; Lee et al., 2014; Letaifa, 2015). The common trait of such projects is that they exploit the opportunities offered by innovative Information Technology (IT) solutions (and, especially, Internet of Things technology) to pro- vide better and sustainable living conditions to citizens (Albino et al., 2015). As such, most of the attention has been devoted to technological aspects related to them. A smart cities project is usually made of a set of IT devices that exchange information among themselves within a common technology platform. Different actors (both private enterprises and public organizations) participate in this complex ecosystem, and the integration and coordination of their activities represent a major challenge for any project (Lee et al., 2014). Albeit the technological aspects related to the functioning of the system do play a key role, the strategic actions of firms involved in the implementation of smart cities projects have to be properly investigated as well. As in the case of any emerging technology (Anderson and Tushman, 1990; Utterback and Abernathy, 1975), firms struggle to find the best way to exploit the new market opportunities, by seeking the best configuration of resources and capabilities to design products and services that satisfy customer needs. In turn, they need to design and adopt proper and innovative Business Models (BMs), which are suited to the specificities of smart cities projects (European Commission, 2016). The term “business model” has gained popularity in the late 1980s spawning from e-commerce to a variety of empirical contexts (Amit and Zott, 2001, 2012; Osterwalder, 2004). Essentially, it has been conceived as a conceptual tool or model able to figure out how firms generate and deliver value to customers, entice customers to pay for value, and convert those payments into profit(Teece, 2010). Since its original formulation, the body of literature on BM has constantly grown. However, despite the number of research papers directed to exploring BM over the last two decades, structured research on BM associated to smart cities projects remains scarce. Particularly, theory-building work and empirical research beyond single-case studies is lacking. Moving from this theoretical and empirical gap, this study addresses the following research question: What different configurations of BM exist in an Internet of Think (IoT) platform that aims at developing smart cities projects? Indeed, while BM shows path-dependency and is the result of the firms' own history, BM configurations have general characteristics beyond the settings of individual firms. Therefore, the analysis of BMs that firms may adopt to exploit smart cities projects, should focus on the analysis of the best configurations of resources and activities. In order to do so, we use a fuzzy set qualitative comparative analysis (fsQCA), which combines within-case analysis with formalized, sys- tematic cross-case comparisons (Fiss, 2011; Ragin, 1987, 2008). In details, fsQCA has the potential to dig deeper in configurations, such as BM, to understand (1) what different types of cases may occur in a https://doi.org/10.1016/j.techfore.2018.07.031 Received 17 January 2018; Received in revised form 23 April 2018; Accepted 14 July 2018 ⁎ Corresponding author. E-mail addresses: abbatet@unime.it (T. Abbate), fabrizio.cesaroni@unime.it (F. Cesaroni), mcinici@unime.it (M.C. Cinici), mvillari@unime.it (M. Villari). Technological Forecasting & Social Change xxx (xxxx) xxx–xxx 0040-1625/ © 2018 Published by Elsevier Inc. Please cite this article as: Abbate, T., Technological Forecasting & Social Change (2018), https://doi.org/10.1016/j.techfore.2018.07.031