Abstract
Technological innovations are regarded as the tools that can stimulate economic growth and the sustainable development of technology. In recent years, as technologies based on the internet of things (IoT) have rapidly developed, a number of applications based on IoT innovations have emerged and have been widely adopted by various public and private sectors. Applications of IoT in the manufacturing industry, such as manufacturing intelligence, not only play a significant role in the enhancement of industrial competitiveness and sustainability, but also influence the diffusion of innovative applications that are based on IoT innovations. It is crucial for policy makers to understand these potential reasons for stimulating IoT industrial sustainability, as they can facilitate industrial competitiveness and technological innovations using supportive means, such as government procurement and financial incentives. Therefore, there is a need to ascertain different factors that may affect IoT industrial sustainability and further explore the relationship between these factors. However, finding a set of factors that affects IoT industrial sustainability is not easy. Recently, the robustness of a theoretical framework, termed the technological innovation system (TIS), has been verified and has been used to explore and analyze technological and industrial development. Thus, it is suitable for this research to use this theoretical model. In order to find out appropriate factors and accurately analyze the causality among factors that influence IoT industrial sustainability, this research presents a Bayesian rough Multiple Criteria Decision Making (MCDM) model based on TIS functions by integrating random forest (RF), decision making trial and evaluation (DEMATEL), Bayesian theory, and rough interval numbers. The proposed analytical framework is validated by an empirical case of defining the causality between TIS functions to enable the industrial sustainability of IoT in the Taiwanese smart manufacturing industry. Based on the empirical study results, the cause group consists of entrepreneurial activities, knowledge development, market formation, and resource mobilization. The effect group is composed of knowledge diffusion through networks’ guidance of the search, and creation of legitimacy. Moreover, the analytical results also provide several policy suggestions promoting IoT industrial sustainability that can serve as the basis for defining innovation policy tools for Taiwan and late coming economies.
Highlights
In the era of cloud computing, Internet applications have ubiquitously influenced our daily lives
The sustainable development of the internet of things (IoT) industry has become an indispensable task for advanced countries and emerging economies, as it will be capable of influencing industrial competitiveness and national economic growth
This implies that national governments of leading and emerging economies must effectively promote IoT development and enable IoT industrial sustainability by supportive means, such as financial incentives
Summary
In the era of cloud computing, Internet applications have ubiquitously influenced our daily lives. The sustainable development of the IoT industry has become an indispensable task for advanced countries and emerging economies, as it will be capable of influencing industrial competitiveness and national economic growth. Manufacturing industries in Taiwan are facing a problem in which traditional SMEs and parts of large companies have to upgrade existing production infrastructure, such as the use of robotic equipment for human-machine cooperation. Under such situations, the government needs to propose a useful solution that will help industries to upgrade. This implies that the government needs to put more effort into IoT industrial transformation
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