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The high frequency of disruption and dislocation of many industries, the migration to low-cost countries of different assets and activities, the increase in systemic risk, the birth of social and ecological constraints, as well as the new worldwide competitors require businesses and the overall society to change. In a so-called Industry 4.0. era, understanding the impact of artificial intelligence (AI) in developed as well as in underdeveloped economies has become increasingly crucial. The purpose of this study is to shed the light on the peculiarities of Chinese AI assessing the state of art of AI in this unique and valuable context.

Through a research based on a qualitative data analysis, the present paper suggests a new way to analyse AI and to support a better understanding of the local Chinese aspects influencing its development and implementation.

The development and implementation of AI in China required tailor solutions which account for the following three main dimensions: the location (i.e. territorial extension, the administrative boundaries); the government approach; and the human capital.

The analysis presents a broad level activity. In addition, the paper focused on Chinese scientific literature and different types of data (i.e. institutional documents, professional reports, websites and speeches in Chinese). The paper used a multi-faceted approach, including also the tacit knowledge of the authors about the context under investigation.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

This chapter discusses the pivotal role of digital technologies, including Information Communication Technologies (ICT) and artificial intelligence (AI), in enhancing inclusivity within higher education organizations. Highlighting the importance of accessible and usable technological tools, the authors argue for the development of digital inclusion to bridge the digital divide and promote digital literacy. Through examples like supporting students with autism spectrum disorder using mobile technologies, this chapter emphasizes the potential of digital tools in creating more inclusive learning environments. The authors advocate for a shift in university culture toward sustainability and inclusiveness, facilitated by technological advancements, to prepare educational institutions for a more integrated and humane society.