An approach to the measurement of the digital economy

The article is devoted to a conceptual approach to the formation of a digital innovation economy based on artificial intelligence technologies. In modern times, the relevance of the development of the economy based on digital technological innovations has been justified. 4.0 It has been shown that increasing the production of science and technology-intensive, highly competitive products in digital economic sectors with the application of industrial components is one of the necessary issues of the current era. The importance of digital transformations has been shown on the basis of socio-economic development strategies. The importance of working out indicators for measuring the intellectual economy included in the structural composition of the information economy was brought to attention. The influence of artificial intelligence technologies in the transition programs from Society 4.0 to 5.0 has been studied. An analysis of the world situation on the economy of artificial intelligence technologies was carried out. Large-scale problems related to artificial intelligence have been mentioned. The characteristics of the formation of the economic sector and development perspectives on artificial intelligence technologies were investigated. The size of the world market for artificial intelligence technologies has been analyzed by various indicators. The global artificial intelligence market size and the revenue in the global artificial intelligence market are shown schematically. Issues of evaluating the innovative perspectives of digital economy sectors related to artificial intelligence technologies were studied. The expert algorithmic stages of the improved Delphi method were proposed for the assessment of innovative perspectives of sub-economic sectors on artificial intelligence. Initial expert evaluations on innovative perspectives have been processed. Evaluation results on the innovative perspective of digital economic sectors related to artificial intelligence technologies were explained. Recommendations on the prospective directions of the formation of a digital innovation economy based on artificial intelligence technologies have been developed.

신남방지역 디지털경제 협력방안 (The Digital Economy in ASEAN and India: Policy Implications for Korea)

Based on the background of artificial intelligence technology, there are different situations in the mutual development of the Internet economy and artificial intelligence technology, which has a relatively large impact on the healthy development of my country’s Internet economy. Whether it is Internet economy or artificial intelligence technology, their ultimate development goal is to achieve the rapid development of our country’s economy. This article will conduct an in-depth analysis of the role of artificial intelligence technology in the development of the Internet economy and study its huge commercial value in the development of the Internet economy. This article first analyzes the relevant concepts and characteristics of artificial intelligence technology in the development of the Internet economy, briefly describes the analysis of the development of my country’s network market economy, and compares the development of artificial intelligence technology in the market Internet economy with the traditional substantive economic development model. Subsequently, it demonstrated the necessity and feasibility of implementing artificial intelligence technology for the development of the Internet economy, and conducted investigations and studies on the way that 10 Internet companies in the east coast of China used artificial intelligence technology to improve economic development. Finally, it puts forward a targeted strategy for accelerating the improvement of Internet companies in the network economy market and future development goals. The experimental research results show that the application of the Internet and artificial intelligence technology has brought us great convenience, and at the same time promoted the growth of our country’s economy, and created huge economic benefits for our country.

The paper examines the difference between the terms “digital economy” and “digitalization of the economy”. Having conducted research, the Author comes to the conclusion that the term “digital economy” cannot be used to denote technologies being used in global economies. Digitalization of the economy is currently underway all over the world. The era of digital economy has not come yet because mankind has not seen a new technological leap as a part of evolution to result in creating artificial intelligence. The introduction of artificial intelligence technology into the economy, which will have been digitalized by then, will lead to a single digital economy in the meaning the term “digital economy” implies. The Author thinks that without integration of these two phenomena, the use of the term “digital economy” is erroneous. Having studied the historical prerequisites for the emergence of the phenomenon of “digitalization of the economy”, the Author comes to the conclusion that the only country in the world that was on the verge of building a state based on digitalization technologies was the USSR. That took place 40 years before the term “digital economy” appeared. The paper goes on to say about the legal regulation of creating artificial intelligence in countries such as the United States of America, England, Germany, France, Italy, Poland, Israel, India, China, South Korea and the Russian Federation. The paper draws the examples of legislation of various countries that regulate the legal status of artificial intelligence, as well as their various approaches to the development of artificial intelligence. Moreover, the study highlights the problems of a non-legal nature that lawyers and users will face when they use artificial intelligence technology. Artificial intelligence is viewed in the context of business security. The Author is certain that administrative and legal institutions have to regulate this area of activity.

PurposeCurrently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.Design/methodology/approachDriven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.FindingsFrom the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.Originality/valueTo overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

PurposeIn the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.Design/methodology/approachTo explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.FindingsThe investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.Originality/valueThis study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and “carbon peaking and carbon neutrality goals.” This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China’s digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development.

Introduction. The digital economy has revolutionized the functioning of businesses, transforming traditional models into innovative ecosystems based on technology. This paper explores the profound role of the digital economy in shaping the modern business environment, with a focus on its implications for fostering innovation. The purpose of the paper is to examine how the digital economy influences the formation of an innovative business environment. By analyzing the key components of the digital economy and their interaction with business practice, the study examines the mechanisms through which digitization promotes innovation. Results. A comprehensive analysis revealed that the digital economy serves as an active driver of innovation in the business environment. Digital technologies enable companies to optimize processes, increase productivity, and leverage data-driven ideas, thereby fostering a culture of innovation. Moreover, the nature of interaction in the digital economy encourages collaboration and knowledge exchange, further stimulating innovation across various sectors. Conclusions. Overall, the digital economy is a complex environment that is constantly evolving and offers numerous opportunities and challenges. Companies that can adapt to changing requirements and harness the potential of digital technologies will be able to achieve progress and gain a competitive advantage. The conclusions drawn from this research highlight the importance of implementing digitization to stimulate innovation in modern businesses. Companies that effectively utilize digital technologies have better opportunities to adapt to the changing dynamics of the market, capitalize on new opportunities, and maintain a competitive edge. However, transitioning to the digital economy also presents challenges, such as cybersecurity risks and digital divides, which need to be addressed for the full realization of innovation potential. Future scientific inquiries could focus on studying specific aspects of the digital economy, such as the impact of artificial intelligence and blockchain technology on innovation. Comparative studies across different industries and regions could provide valuable insights into variations in the intensity of innovation driven by digital technologies.

The impact of digital transformation on the shape of business operations around the world cannot be understated. Yet, the Islamic digital economy era remains in its infancy, and the challenges that it faces are still left unanswered. Nonetheless, Halal entrepreneurs are presented with significant innovative opportunities related to the digital economy. Halal entrepreneurship is an important subject of business research since culture and religion play a significant role in creating business relationships. Cultural entrepreneurship has become a means to use culture and arts for bringing a societal change. This chapter identifies some new opportunities in the digital economy that can be exploited by Halal entrepreneurs. These ventures include the internet of things (IoT), three-dimensional (3D) printing, cloud computing, automation, robotics and artificial intelligence, data analytics, digital platforms, and blockchain technologies. This chapter contributes theoretically and practically to Halal entrepreneurship and the Islamic digital economy. The opportunities identified in this chapter can help Halal entrepreneurs and policy makers to launch products and services and policies to propel the growth of the Islamic digital economy.KeywordsHalal entrepreneurshipIslamic digital economyCultural entrepreneurship

Against the backdrop of deep integration between the digital economy and educational reform, artificial intelligence (AI) technology has opened up new possibilities for enhancing the quality and efficiency of industry-education integration. This paper focuses on the core needs of college students 'career development capabilities, exploring the inherent logic and practical pathways for AI-powered industry-education integration. By analyzing current challenges in resource alignment, teaching adaptation, and evaluation feedback within industry- education integration, the study proposes key solutions from a technology-enabled perspective: establishing intelligent supply-demand matching platforms, developing personalized training systems, and creating dynamic evaluation mechanisms. The research aims to bridge the gap between industrial demands and educational resources through AI technology, achieving precise resource alignment, collaborative teaching process optimization, and targeted vocational skill cultivation. These efforts provide theoretical references and practical guidance for enhancing college students' employability and promoting deeper integration between education and industrial chains.

With the in-depth development of the new round of scientific and technological revolution and industrial change, digital technologies such as big data, Internet, cloud computing, blockchain, artificial intelligence and other digital technologies have a far-reaching impact on the manufacturing industry, and the digital economy has become an important engine for the promotion of high-quality development of the manufacturing industry. Therefore, in order to vigorously promote the digital economy of Lianyungang City to empower the high-quality development of the manufacturing industry, the use of Lianyungang City data from 2011-2021, the establishment of the digital economy and the high-quality development of the manufacturing industry evaluation index system, based on the entropy value method and the coupling coordination model, to explore the degree of coupling and coordination of Lianyungang City's digital economy and the high-quality development of the manufacturing industry. The study found that: from 2011 to 2021, Lianyungang digital economy index and manufacturing high-quality development index are showing an upward trend; from 2011 to 2021, Lianyungang's digital economy and manufacturing high-quality development in the coupling and coordination of the degree of upward trend, to reach the extreme coupling and coordination, but the gap from the developed cities is large, there is a large space for improvement. The conclusions of this study provide a certain reference for the promotion of coupled and coordinated development of digital economy and manufacturing industry in Lianyungang City in the future.

Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored. The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare? A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice. Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships. There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships. In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.

The emergence and presence of Artificial Intelligence (AI) technology has gained popularity in many areas of human lives, including the education system. Since the technology’s inclusion, numerous studies have indicated AI technology through its benefits and positive impact on the teaching and learning process. However, teachers’ perceptions and perspectives on the benefits associated with AI technology are crucial in ensuring its successful integration. Teachers’ pragmatic decisions on how they will benefit from AI technology will influence their willingness to integrate it into their teaching process. This matter becomes more significant looking at the need for AI technology in Visual Art Education (VAE) subject area that emphasizes the development and translation of creative and innovative ideas in the production of works of art. To date, there are limited published studies that address similar issues, especially in the local context of Malaysia and the VAE subject area. Considering the above statements, the present study aims to examine the VAE teachers’ readiness, perception, and attitude toward integrating AI in art classrooms. The study was conducted through the distribution of a survey questionnaire to 253 VAE teachers from 43 public secondary schools in Selangor, Malaysia. Findings from the study informed that the VAE teachers’ current usage and readiness toward integrating AI technology is at a moderate level, although they did post a positive perception and attitude toward its integration into art classrooms. Based on the research findings, this study will suggest several mechanisms that need to be implemented either by the government, school administration, or teachers themselves to ensure that AI technology will be integrated more effectively, creatively, and innovatively.

With the continuous development of the digital economy, artificial intelligence technology is becoming more and more widely used in various fields. This paper mainly discusses the practice and application of artificial intelligence technology in the digital economy, including its application field, technical principle, implementation method, and future development trends. Through analyzing the current application status and existing problems of artificial intelligence technology in the digital economy, this paper puts forward some improvement measures and development suggestions, aiming to provide a reference for promoting the better application of artificial intelligence technology in the digital economy.

Strategic priorities of social production digitalization: world experience