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This paper reviews recent research on the expected economic effects of developing artificial intelligence (AI) through a survey of the latest publications, in particular papers and reports issued by academics, consulting companies and think tanks.

Our paper represents a point of view on AI and its impact on the global economy. It represents a descriptive analysis of the AI phenomenon.

AI represents a driver of productivity and economic growth. It can increase efficiency and significantly improve the decision-making process by analyzing large amounts of data, yet at the same time it creates equally serious risks of job market polarization, rising inequality, structural unemployment and the emergence of new undesirable industrial structures.

This paper presents itself as a building block for further research by introducing the two main factors in the production function (Cobb-Douglas): labor and capital. Indeed, Zeira (1998) and Aghion, Jones and Jones (2017) suggested that AI can stimulate growth by replacing labor, which is a limited resource, with capital, an unlimited resource, both for the production of goods, services and ideas.

Our study contributes to the previous literature and presents a descriptive analysis of the impact of AI on technological development, economic growth and employment.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.

The growth of the internet has transformed digital infrastructure in Thailand over the past two decades, with the widespread use of e-commerce, digital money and online services becoming a daily norm for all ages. The COVID-19 restrictions, which limited in-person business operations, boosted demand for takeout and delivery services and fueled the expected steady growth of the online food delivery market in Thailand. The pandemic also resulted in a shift towards online ordering and delivery, reflecting changes in customer behavior. This study focuses on exploring the factors that have driven Bangkokians to use online food delivery services after the COVID-19 restrictions were lifted in June 2022.

Data were collected from 398 participants who had ordered food delivery services after the announcement.

The findings showed that perceived usefulness, time saving benefit and price saving benefit have a significant impact on the intention of customers to use online food delivery services, while food safety risk perception had no effect.

Bangkokians favor online food delivery services due to convenience and time-saving, indicating high demand post-pandemic. Businesses should invest in improving their platforms to meet evolving consumer behavior.

The result of this study offers valuable insights into the attitudes and behaviors of Bangkokians towards online food delivery services and could be beneficial for businesses in the industry to improve their services, enhance customer satisfaction as well as increase their competitiveness.

This paper is one of the first studies to examine specificities, including limits of mindfulness at work in an African organisational context, whilst dealing with the ongoing COVID-19 pandemic. It specifically addresses the role of organisational and managerial support systems in restoring employee wellbeing, social connectedness and attachment to their organisations, in order to overcome the exclusion caused by the ongoing pandemic.

The study uses a qualitative research methodology that includes interviews as the main data source. The sample comprises of 20 entrepreneurs (organisational leaders) from Ghana and Nigeria.

The authors found that COVID-19-induced worries restricted the practice of mindfulness, and this was prevalent at the peak of the pandemic, particularly due to very tough economic conditions caused by reduction in salaries, and intensified by pre-existing general economic and social insecurities, and institutional voids in Africa. This aspect further resulted in lack of engagement and lack of commitment, which affected overall team performance and restricted employees’ mindfulness at work. Hence, quietness by employees even though can be linked to mindfulness was linked to larger psychological stress that they were facing. The authors also found leaders/manager’s emotional intelligence, social skills and organisational support systems to be helpful in such circumstances. However, their effectiveness varied among the cases.

This paper is one of the first studies to establish a link between the COVID-19 pandemic and mindfulness limitations. Moreover, it is a pioneering study specifically highlighting the damaging impact of COVID-19-induced concerns on leader–member exchange (LMX) and team–member exchange (TMX) relationships, particularly in the African context. It further brings in a unique discussion on the mitigating mechanisms of such COVID-19-induced concerns in organisations and highlights the roles of manager’s/leader’s emotional intelligence, social skills and supportive intervention patterns. Finally, the authors offer an in-depth assessment of the effectiveness of organisational interventions and supportive relational systems in restoring social connectedness following a social exclusion caused by COVID-19-induced worries.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.