Industry 4.0 for Thai SMEs: Implementing Open Innovation as Innovation Capability Management

The challenges of cooperation and collaboration faced by small and medium-sized enterprises (SMEs) in Thailand require a specific approach to creating new shared value through innovation—open innovation is extensively applied. The purpose of this research is to shape the psychometric properties of an Open Innovation Implementation scale that supports a four-dimensional factor model incorporating centralization, knowledge management, the technology transfer evaluation process, and networks. A sample of 373 SMEs was used for second-order analysis. The results provided evidence indicating the significant relationship between shaping the concept of Open Innovation Implementation (OII), implying that SMEs should therefore consider the managerial and organizational dimensions of implementing open innovation. In addition, our findings offer manufacturing SMEs the strategic opportunity to innovate via interaction with relevant stakeholders, such as industries, universities, government, and customers/users, to stay competitive.

Centralization; Industry 4.0; Innovation capability management; Open innovation implementation (OII); Technology transfer evaluation process

    The application of science, technology, and innovation is vital to Industry 4.0 in small and medium-sized enterprises (SMEs). The main aim of the cooperation between technology and innovation is to increase firms’ innovativeness and productivity (Masood and Sonntag, 2020). Most SMEs do not have sufficient resources or the knowledge capacity (i.e., in domains such as talent and budgeting) to invest in technological innovation and R&D. This then creates difficulties for SME businesses by preventing them from implementing business innovation models. Consequently, there is a need for innovation. There are two types of innovation: closed and open. The traditional method of achieving innovation—i.e., closed innovation—is through a firm’s own R&D division. It entails the firm strictly keeping the developed intellectual property out of external reach. However, closed innovation requires a huge level of investment and employment to supply the internal R&D. In contrast, the concept that goes against closed innovation is open innovation (Chesbrough, 2003), which is the process by which ideas and knowledge are exchanged between business–industrial partners, universities, users and customers, and public institutions. In its essence, Industry 4.0 refers to the growing trend toward automation and data exchange in manufacturing technology and processes (Xu et al., 2018). Technology helps solve problems and track processes while also improving efficiency and productivity. Therefore, Industry 4.0 is premised on open innovation and digital transformation. Due to innovation capabilities and absorptive capacities to innovative concept, SMEs not only need to adapt and innovate in terms of their products but also improve their manufacturing practices and reduce their environmental footprint across the whole process (Choudhary et al., 2019). This is thus the idea behind integrating open innovation via Industry 4.0. Thailand’s Industry 4.0 policy emphasizes manufacturing and production that uses innovation. This policy initiative has specifically targeted five sections within technology and industry: biotechnology; wellness and medical technology; smart devices and machines; food and agriculture; and digital systems and artificial intelligence. Within Thailand’s 4.0 policy, Industry 4.0 specifically takes on the role of transforming to digital industrial manufacturing systems. It also connects different strategic partners via the Internet of Things (IoT) to meet more diverse needs. However, Industry 4.0 enhances innovation capabilities through the possibilities of new emerging technologies in manufacturing and production. Recently, the National Innovation Agency (NIA) proposed funding programs for Thai SMEs and start-ups through collaborative partnerships to develop a variety of innovations. All of these factors point to Thailand as the location for the current research.

To the best of our knowledge, there are relatively few prior studies regarding the implementation of open innovation in SMEs specifically quantifying how it is implemented—that is, no empirical evidence has yet been obtained demonstrating how firms implement OI internally. Still, there exists a considerable body of literature on the implementation of the emerging management paradigm of open innovation. Chiaroni et al. (2010; 2011) proposed four managerial levers within Lewin’s change model to understand how manufacturing corporations shift from closed innovations: organizational structure, knowledge management, the evaluation process, and networks. These four organizational and managerial systems responded to the Open Innovation Implementation. However, both studies focus on large corporations, the organizational and managerial levers of which may not align with those of SMEs. Gimenez-Fernandez et al. (2021) argued that gamification is an element used to overcome organizational inertia in Open Innovation Implementation, specifically focusing on barriers to open innovation. Naruetharadhol et al. (2020) found that organizational structure, knowledge management, and networks are related to implementing open innovation. They emphasized decentralization, organism, and mechanism; however, centralization appears to be more consistent with the characteristics of Thai SMEs. This is because the majority are family businesses in which top management or business owners oversee the delegation of authority, influence, and decision-making. This justifies the study’s decision to test centralization rather than decentralization, which is supported by Liao et al. (2011). This study specifically aims to explore financial-related decision activities (e.g., capital budgeting, etc.), which tend to be relied on by business owners when developing a new innovation or enhancing an existing one. This is about centralized decisions. According to Huizingh (2011), the processes of open innovation are relevant to two phenomena. First, the processes lead to open innovation; this is the process of opening up innovation practices that were formerly closed. The second process refers to the practices of open innovation (i.e., how to implement open innovation). This paper explores the first process of open innovation, referring to it here as “Open Innovation Implementation”. In doing so, this research undertakes an evaluation of the managerial and organizational dimensions to create a new concept—Open Innovation Implementation (OII)—as a second-order model. Accordingly, we pose the following research question: Does a centralized structure, knowledge management, the technology transfer evaluation process, and networks relate to the emerging implementation of open innovation in small- and medium-sized firms? To answer this, it is assumed that the sub-dimensions of a centralized structure, knowledge management, the technology transfer evaluation process, and networks lead to the occurrence of Open Innovation Implementation (H5). Thus, we define the term Open Innovation Implementation (OII) as the recognition of organizational and managerial components in order to establish an openness to collaboration within an innovation activity. Figure 1 shows the proposed conceptual framework, which consists of the sub-hypotheses (H1–H4), for realizing Open Innovation Implementation.

Figure 1 Proposed conceptual framework and second-order model 

    Open innovation may not be the best-for-all strategic innovation management for SMEs, but it provides an integral dimension to existing innovation approaches and accelerates collaborative learning and value development (i.e., like a wave raises all boats). This study develops and proposes a new theoretical concept of Open Innovation Implementation (OII) for small business practitioners and scholars. Accordingly, this current research answers the holistic question of how centralized structure, knowledge management, technology transfer evaluation, and networks relate to the emerging implementation of open innovation in small- and medium-sized firms. While this paper uses an aggregated data statistical method to empirical model, further research could be conducted based on the manufacturing profile and clustering. Applying the multigroup mean structures model of covariance-based SEM makes the research model more general in terms of smart manufacturing–industrial implementations, expanding the examples of the research model. Furthermore, future studies could also investigate whether this theoretical model of Open Innovation Implementation, as a basic theory, can be applied to the other industry types of the remaining 263 SMEs (e.g., trading, service, etc.) and the effects that it may have on the persistence of SMEs to commit to adopting an open innovation environment.

    This work was financially supported by the International College, Khon Kaen University, Thailand. Also, authors would like to sincerely thank to Ms. Sasichakorn Wongsaichia for her vulnerable support in data collection.

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