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Quite often than not, a new industry can be created, thanks to the countless entrepreneurs and innovative activities across the globe. Smart city (SC) is one such industry and a living lab using the key roles of the digital platform that enable a seamless flow of information and knowledge for innovation within the SC. The purpose of this paper is to illustrate how SC can be a new regional industry engine through an “open collective innovation system” as its new concept. In particular, SC provides efficient transaction costs and knowledge flows. Eventually, SC can be an innovation hub for entrepreneurship through openness.

To frame the research goals, the authors used qualitative research methodologies based on grounded theory. In particular, the author used inductive reasoning to generate arguments and conclusions about the future of an SC as a new growth engine in the era of the fourth industrial revolution. Numerous documents and prior literature were used for the preliminary conceptualization of an SC. Interview data were then coded for reasoning in an open collective innovation system based on “openness”.

SC maximizes efficiency in practicing innovation. In the perspective of innovation costs, SC can minimize transaction costs, specifically the information processing costs, through data openness. In this context, transaction costs can be considered an economic equivalent of friction in a physical system. So, as the friction is low, some movements of an object on the surface are likely to be easy. SC is optimized for innovation activities through an “open collective innovation system”. In terms of innovation networks, an SC results in an innovation efficiency derived from both the network and the spatial agglomerations in physical and cyberspace. The efficiency-based SC itself overlaps knowledge creation, dissemination and absorption, providing an open innovation (OI) ecosystem.

This paper remarkably extends that SC can be an “open collective innovation system model” and a new conceptualization. Eventually, SC will play a crucial role in developing regional industries as a new growth engine. To operate as a new growth engine fully-fledged, the SC is needed to accumulate innovative assets such as the critical mass of residents, numerous firms, etc. However, this study has some limitations. First, difficulties in any analytic approach to SC resulted from their many interdependent facets, such as social, economic, infrastructural and spatial complex systems, which exist in similar but changing forms over a huge range of scales. Also, this research is at a quite an early stage. Thus, its theoretical stability is weak. So, this paper used the qualitative methodology with a grounded theory. Another limitation is in the research methodology. The limitation of using grounded theory adapted by this work is that the results of this study may not be generalizable beyond the context of this study. This non-generalizability occurs because ours is an inductive approach to research, meaning that the findings are based on data collected and analyzed. As such, the results of this study may not be applicable to other contexts or situations. In addition, the analysis of data in the grounded theory is based on researcher’s subjective interpretations. This means that the researcher’s own biases, preferences and assumptions may influence the results of the study. The quality of the data collected is another potential limitation. If the data is incomplete or of poor quality, it can cause researcher’s own subjective interpretations.

Findings of this study have some practical implications for enterprises, practitioners and governors. First, firms should use value networks instead of value chains. Notably, the firms that pursue new products or services or startups that try to find a new venture business should take full advantage of SC. This taking advantage is possible because SC not only adapts state-of-the-art information technology (e.g. sensor devices, open data analytics, IoT and fiber optic networks) but also facilitates knowledge flow (e.g. between universities, research centers, knowledge-based partner firms and public agencies). More importantly, with globalized market competition in recent years, sustainability for firms is a challenging issue. In this respect, managers can take the benefits of SC into consideration for strategic decisions for sustainability. Specifically, industrial practitioners who engage in innovation activities have capabilities of network-related technologies (e.g. data analysis, AI, IoT and sensor networks). By using these technologies in an SC, enterprises can keep existing customers as well as attract potential customers. Lastly, the findings of this study contribute to policy implementation in many aspects. At first, for SC to become a growth engine at regional or natural levels, strong policy implementation is crucial because SC is widely regarded as a means of entrepreneurship and an innovation plaza (Kraus et al., 2015). To facilitate entrepreneurship, maker spaces used for making the prototypes to support entrepreneurial process were setup within universities. The reason for establishing maker spaces in universities is to expand networking between entrepreneurs and experts and lead to innovation through a value network. One of the policy instruments that can be adapted is the “Data Basic Income Scheme” suggested by this research to boost the usage of data, providing content and information for doing business. Also, a governor in SC as an intermediator for the process of the knowledge flow should initiate soft configuration for SC.

This work makes two theoretical contributions to OI aspects: (1) it explores dynamic model archetypes; and (2) it articulates and highlights how SC with digital technology (i.e. in the AI, IoT and big data context) can be used to create collective knowledge flow efficiently. First, the findings of this study shed light on the OI dynamic model. It reveals important archetypes of new sub-clustering creation, namely, a system that underpins the holistic process of innovation by categorization in amongst the participating value network (Aguilar-Gallegos et al., 2015). In innovation studies, scholars have particularly paid attention to a cluster’s evolution model. In the process of innovation, the “open innovation dynamic model” suggested by this study illustrates sub-clustering that happens in value networks by taking the benefits of SC. Eventually, the evolution or development of sub-clusters can bring in a new system, namely, an OI system. Second, the findings of this study contribute to the understanding of the role of digital technologies in promoting knowledge flow. The usage and deployment of digital technologies in SC may enormously and positively influence innovative activities for participants. Furthermore, the rising of digital economy, in the so-called platform business, may occur depending on advanced technologies and OI. In doing so, the findings can further tow innovation research through juxtaposition between SC and innovation research (Mehra et al., 2021).

This paper shows that the function of an SC not only improves the quality of life but also acts as an engine of new industry through an open collective innovation setting using dynamic and ecological models.