In June 2023, the Nishan Dialogue on Digital Civilisation of the World Internet Conference was held in China. At this conference, China proposed for the first time, in the era of artificial intelligence (AI), to build a digital world of exchange, mutual appreciation and tolerance, hoping to gather the wisdom of the internet community and seek the governance of digital civilisation. In recent years, with the rapid development and wide recognition of AI technology, how to solve the AI ethical issues generally faced by the international community has become the focus of attention. By analysing the current status of AI ethics and governance in the United States and the European Union, and comparing it with China’s development in recent years, this article further advances the exploration of Chinese solutions to the global ethical governance of AI. On this basis, it responds positively to the call of the United Nations and international organisations to explore solutions to the four main realities of: (a) phenomenon of alienation of labour competition brought about by AI technology; (b) infringement of the subject’s personal privacy and impact on the ethics of responsibility for awareness and undermining of social fairness; (c) justice to seek a path of avoidance for collaborative governance from government supervision, public constraints, technology; and (d) sound mechanisms, which can actively promote global AI ethics.

The study examines the response of the Quad countries (Australia, India, Japan and the United States) to People’s Republic of China (PRC)’s predatory acquisition of foreign technologies. This article looks at PRC’s science and technology (S&T) policy and its relation to the grand strategy of attaining global superpower status. The meteoric rise of the PRC in the last four decades has amazed many. Innovation and technological advancement and their alignment with government policies are important factors in this rise. The study notes that PRC’s S&T policy involves, among others, acquiring foreign technologies through illicit means that include stealing through espionage and sophisticated cyberattacks and forcing overseas companies operating in China to share intellectual property rights with local partners. Alarmed by PRC’s predatory strategy, the Quad countries have taken steps to regulate, and in some cases prohibit, the PRC’s targeted foreign investments and coercive and opportunistic takeovers. The article argues that the Quad countries need to coordinate their efforts to effectively counter PRC’s illicit acquisition of their technologies.

Recently, the defense budget, which includes the cost of purchasing weapons, has continuously and significantly increased in South Korea. This increase, which is entirely financed by the government, has raised the issue of the socioeconomic impacts of spending on the defense industry in areas, such as production, added value and job creation. In this regard, it is necessary to more accurately measure the impact of spending on the defense industry on domestic industry, but the Bank of Korea’s industry inducement coefficient, which measures industrial spillovers, is quite limited in measuring the industry inducement impact caused by weapon production. Therefore, this study explores how to estimate the industry inducement coefficient of the production of a specific weapon by utilising the current Bank of Korea input–output table, which is focused on private industry, and applies this methodology to the estimation of the input–output coefficient of the production of a specific weapon. As a result of the analysis, the input–output coefficient of a specific weapon was estimated to be approximately 1.18 times higher than that of the products of similar industries in the private sector in terms of production, 1.03 times higher in terms of value-added and 1.03 times higher in terms of employment. This suggests that the effect of fostering domestic industry through weapon production is somewhat greater than that of private industry and proves the efficacy of government investment in this sector.

The biopharmaceutical industry in Korea is considered a key strategic industry following the semiconductor industry. However, success in the biopharmaceutical industry depends on the outcome of research and development processes that require long periods and substantial investment, resulting in a success rate of only around 2.5%–4% for new drug development. Consequently, rational strategic choices, such as determining key capabilities to pursue business, deciding where to position within the value chain and identifying collaboration partners and strategies, are more crucial in the biopharmaceutical industry compared to other industries. In this study, we divided Korean biopharmaceutical companies into research and development groups and Integrated groups, which perform both research and production, and compared their productivity using the meta-frontier methodology to verify the significance of technology gap ratio (TGR) values between groups. We also investigated the influence of open innovation activities, including the type, partners and timing, on the TGR of each group with Tobit analysis. The investigation revealed that productivity and its influencing elements varied depending on the business model. This finding suggests that this information can be utilised to develop efficient industrial policies.

The study aims to explore how to measure firms’ open innovation from financial statements. So, our research question is as follows: How can we determine firms’ open innovation signals directly or indirectly from financial statements? This study used data from the US financial statements and patent registration database from 2016 to 2018 to answer this research question. Three manifest signals of open innovation in financial data were found. First, subsidiary or related firm investment in financial data may have a negative relationship with open innovation because open innovation (i.e., the co-application of patents) could decrease subsidiary or related firm investment. But there are differences between the top and bottom twenty firms. Second, internal R&D investment (I R&D) in financial data may have a positive relationship with open innovation because I R&D could trigger inward open innovation. If I R&D combines with an open innovation strategy, it increases the size of subsidiary or related firm investment as a kind of inward open innovation. Third, free cash flow (FCF) in financial data may have a positive relationship with open innovation because high FCF could support outward open innovation.

Since the advent of the fourth industrial revolution, the global economy has been led by big tech companies based on technology startups. In this situation, it is very timely to investigate the antecedent factors for the performance enhancement of technology startups that can play a big role in driving economic growth. We investigate the effect of entrepreneurial orientation and technology acquisition on the financial and non-financial performance of technology startups. In order to achieve these research goals, we collected data from 121 Korean technology startups to examine the effects. Our results support that both entrepreneurial orientation and technology acquisition improve the performance (financial and non-financial) of technology startups. In addition, the entrepreneurial orientation of technology startups has a significant indirect effect on performance (financial and non-financial) through technology acquisition. Overall, our study contributes to improving the understanding of the antecedent factors for the achievement of the performance of technology startups in the field of entrepreneurship research by presenting a new research model of the relationship between entrepreneurial orientation, technology acquisition and the performance of technology startups. In addition, this study provides the basis for the need for technology acquisition support policies for technology startup support institutions to nurture technology startups.

This study examines the factors that influence pro-environmental behaviour intention (PEBI) in manufacturing small- and medium-sized enterprises (SMEs). The data were collected from 517 executives and chief technology officers of Korean SMEs and analysed using a comprehensive research model. The model includes variables such as awareness of consequences (ACs), ascription of responsibility (AR), personal norms (PNs), extrinsic motivation (EM), subjective norms (SNs) and realistic values (RVs). The results show significant relationships between these factors and PEBI. In particular, ACs and AR have positive effects on PNs, with AR having a stronger effect. PNs are the most important predictor of PEBI. EM has a positive impact on behaviour intention, while SNs do not have a significant impact. Interestingly, RVs have a negative impact. These findings have practical implications for encouraging pro-environmental behaviour in manufacturing SMEs. Policymakers and business planners should focus on increasing awareness of environmental consequences and individual responsibility to reinforce PNs. Moreover, offering extrinsic rewards and benefits can motivate pro-environmental behaviour in these firms. Understanding these factors can help design targeted strategies for promoting sustainability practices within manufacturing SMEs. By addressing these aspects, businesses can contribute to environmental innovation and sustainable development.

In the context of knowledge-based economy, an organisation’s ability to create knowledge is the most important factor in maintaining its competitiveness. Collective intelligence is posited as a paramount methodology not only for the generation of knowledge pertaining to multifaceted issues but also as a fundamental pillar within the framework of organizational knowledge management. The use of emerging technologies is an important strategy for improving the organisation’s ability to create knowledge through collective intelligence by adding depth and breadth of knowledge. However, excessive use of technology often has a negative impact on organisational knowledge management. Therefore, this study aims to identify the two-sided effect of using emerging technologies (big data analytics (BDA) and online platforms) on organisational knowledge creation according to the complexity of the task. The results of our study suggest that the use of BDA technology for organisational knowledge creation should be maintained at an appropriate level in general, but it is recommended to increase the use of BDA technology for low-complexity tasks. In addition, using online platform technology is difficult to consider as a strategic way to solve high-complexity tasks, but increasing the use of BDA technology can contribute to improving the organisation’s ability to create knowledge.