Abstract
Introduction
New digital paradigms include a vast array of enabling digital technologies (DT), such as the Internet of things (IoTs), additive manufacturing, big data, artificial intelligence, cloud computing and augmented and virtual reality (Rindfleisch et al., 2017; Nambisan, 2017). The large diffusion of these technologies is a pervasive process that is interesting all the industries by causing a radical reconfiguration of firms’ organizational and strategic models (Urbinati et al., 2018); and it is the feature at the basis of emergence of the Industry 4.0 (Frank et al., 2019). Industry 4.0 is a new industrial scenario characterized by the convergence of the DT recalled above into intelligent socio-economic systems in the value creation process of industries (Muller et al., 2018). The pervasiveness and the knowledge intensive nature of these technologies disclose a technology-push innovation approach and open new scenarios for the competitiveness of both innovative and traditional industries.
Despite Industry 4.0 results to be more compliant with the organizational and strategic settings of big corporations, due to the large investments required as well as to the human competencies available, it requires flexibility, decentralization, customer proximity and lean decision-making processes that are affordable more typically by small and medium-sized enterprises (SMEs) (Moeuf et al., 2017). Digital transformation (DT) in SMEs is a topic of great actuality and interest in the agenda of scholars and practitioners (Cha et al., 2015: Li et al., 2018). The increasing use of advanced DT is transforming innovation and production processes (Alcacer et al., 2016; Urbinati et al., 2018). Defined as the result of the introduction of “transformational information technology” (Lucas et al., 2013, p. 372), Industry 4.0 involves fundamental changes in the configuration and execution of business processes (Venkatraman, 1994), operational routines (Chen et al., 2014) and organizational capabilities (Tan et al., 2015). However, the transition towards an Industry 4.0 perspective could be more complex in the context of SMEs where IoT, big data analytics, artificial intelligence and blockchains, generally have implications to design, implement and achieve the full digitalization of their strategic and organizational models. This because SMEs are characterized by limited resources and present gaps in terms of cognitive and organizational assets so necessary to lead the introduction of DT (Li et al., 2018). Furthermore, “the concept of smart technology itself has however been scarcely defined and conceptualized beyond technological fields and perspectives” (Lee, 2012; as cited in Neuhofer et al., 2015, p. 243) and since “there is limited understanding of how organizations need to change to embrace these technological innovations and the business shifts they entail. Even more, the business value and strategic relevance of…technologies still remain largely underexplored” (Mikalef et al., 2017, np). Moving from the above research gaps, the literature highlights the need for a deepened comprehension of business and managerial aspects of DT, mainly in the context of SMEs where the potentiality of DT requires the adoption of models inspired to the principles of collaboration and networking.
Framed in the above premises, this paper aims to contribute at the debate on DT in SMEs through the evidences of Smart District 4.0, a pivotal initiative launched in the Apulia Region (Southern Italy) aimed to sustain the process of DT of SMEs operating in the field of the Agri– Food, Clothing–Footwear and Mechanics–Mechatronics. Accordingly, the paper tries to answer the following research question: How to engage the SMEs in the adoption of DT for achieving a process of digital transformation?
Adopting a qualitative approach based on an extreme case study (Eisenhardt, 1989; Yin, 1984), the paper analyses the Smart District 4.0, a joint project launched by LUM Enterprise (a spin-off of the LUM Jean Monnet University in Casamassima, Bari, Italy) and Noovle, and it aimed to design and realize processes of digitization with a specific target related to SMEs operating in the agri–food, textile, clothing, footwear, mechatronics and mechanics. For its characteristics and features, the case can be classified as an extreme case study (Eisenhardt, 1989; Yin, 1984). The results allowed to comprehend the main limitations and obstacles for the implementation of DT within the Apulian SMEs in the identified industries. The case Smart District 4.0 showed the importance of the adoption of a four levels model for the achievement of DT of SMEs. Despite technology being essential for such a process of digitization, critical success factors for this transition could be identified into the human and social capital of the SMEs.
The remaining of the paper is organised as follows: Section 2 introduces the literature background around the main pillars of DT and digital transformation of SMEs. Section 3 describes the research methodology, Section 4 describes the findings and finally Section 5 discusses and concludes the paper.
