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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.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The aims of the current study were twofold: first, to rank the world’s emerging economies based on a novel National Intellectual Capital Index (NICI) and its components; and second, to examine the impact of NICI and its components on economic growth, measured in terms of real GDP per capita.

We employed principal component analysis (PCA) to construct the novel NICI based on five key socio-economic indicators including (1) national human capital, (2) national structural capital, (3) national relational capital, (4) national informational capital and (5) national innovational capital. These indicators are publicly available for many countries. The index was generated by considering the most appropriate socio-economic indicators as precise measures of NIC from the Penn world table (version 10.0), the World Bank’s database of world governance and development indicators and the KOF globalization across the selected emerging economies.

The empirical findings revealed that national human capital is a significant driver of NIC, corresponding to higher economic growth. This is followed by national informational capital, national relational capital, national innovation capital and national structural capital. Furthermore, results indicate that the contribution of national structural capital is marginal compared to other critical strands of NIC.

NIC is generally considered the most valuable strategic resource for driving knowledge economies, especially in the Industry 5.0 revolution. Ranking emerging economies based on the NICI sheds light on the accumulated stock of NIC and how it contributes to and improves the economic growth of these economies. The stock of NIC is considered a critical success factor for measuring both current and future economic prosperity. Therefore, using the socio-economic indicators of KOFGI as accurate measures of NICI will assist policymakers in formulating and implementing relevant policies to enhance the accumulation of knowledge-based capital, which are critical components of NIC.

To the best of the authors' knowledge, this is the first study of its kind, both theoretically and empirically, to measure the National Intellectual Capital Index (NICI) using the most nascent socio-economic indicators of NIC. Moving forward, this study evaluates the impact of NICI and its components on economic growth, which is a relatively sparse area of research in the context of emerging knowledge economies.

The author examines the impact these efficient factors have on factor model comparison tests in US returns using the Bayesian model scan approach of Chib et al. (2020), and Chib et al.(2022).

Ehsani and Linnainmaa (2022) show that time-series efficient investment factors in US stock returns span and earn 40% higher Sharpe ratios than the original factors.

The author shows that the optimal asset pricing model is an eight-factor model which contains efficient versions of the market factor, value factor (HML) and long-horizon behavioral factor (FIN). The findings show that efficient factors enhance the performance of US factor model performance. The top performing asset pricing model does not change in recent data.

The author is the only one to examine if the efficient factors developed by Ehsani and Linnainmaa (2022) have an impact on model comparison tests in US stock returns.

This study aims to investigate the factors affecting technological innovation intentions at banks listed in Vietnam, a developing country, to develop business activities and accounting benefits according to the trend of the 4th Industrial Revolution.

To collect and analyze the data for this study, qualitative and quantitative methods were used. Specifically, 20 finance and banking experts and 45 managers in the field of information technology were interviewed in qualitative research over a period of three months. Then, 1,000 questionnaires were sent to banks within six months, with the final sample for quantitative research being 324 respondents. Finally, the structural equation modeling (SEM) was used to check the hypotheses. Regarding the tools used, the qualitative study used a semistructured questionnaire to collect information. Meanwhile, SPSS software was used to analyze quantitative research information, including checking common method bias, nonresponse bias, evaluating scale quality and checking SEM.

The findings show that the usefulness, ease of application, credibility, innovation and efficiency of technology have certain impacts on technological innovation intentions at banks listed in Vietnam. Using the SEM analysis, the results showed that the five factors had a favorable influence on the technological innovation intentions. More specifically, this study proposed adding an efficiency factor, and the results showed that it has the greatest impact on technological innovation intentions.

This study would be considered a continuation of prior studies because it provides empirical evidence for business models at banks listed in developing countries (for example, Vietnam) and so provides useful advice for bank management not only in Vietnam but across Asia. In fact, bank managers should consider introducing new technology as appropriate to make their reports more clear and up-to-date, therefore improving their performance. Banking managers, in particular, should focus on enhancing the bank’s application technology indicators to obtain a competitive edge.

This is a pioneering study that uses a combination of the reasoned action theory, planned behavior theory, transaction cost theory and unified theory of acceptance and use of technology to expand knowledge about technological innovation intentions at listed banks in the context of a developing country. The study also discovered and added the efficiency factor as a key factor affecting the intention to innovate technology at listed banks. These contribute to improving the literature of technological innovation intentions.

This study examines how the introduction of mobile money transfers, while making it efficient and convenient to access funds, has affected rural households’ savings behavior and the banking sector.

This study utilizes Fiji’s most recent agricultural census data to model the agricultural household’s saving decision. The study estimates an probit model to examine rural households' savings behavior. Furthermore, it utilizes time series secondary data to examine how funds transfer has been channeled to rural households in Fiji.

Firstly, the results demonstrate that with the mobile money transfer platform launch, the banking sector has lost substantial money previously used to pass through its system, thus losing service fees and interest income. Furthermore, the findings demonstrate that those using mobile wallet platforms to receive money are more likely not to have a savings account with the bank. Noting the cultural systems and social settings of the native households and the ease of payments via the mobile platform, they tend to spend more on consumption rather than saving, thus making these households more vulnerable during shocks such as natural disasters.

While mobile money transfer is hailed as a revolution, no research has yet picked up the downside to it, that of undermining the very effort by policymakers to get low-income rural households to save. Secondly, this study also highlights how mobile money transfer deprives the banking system of a significant transfer fee income and a source of funds to pool and lend to earn interest income. Furthermore, this study brings to the forefront a dichotomy about how a rural indigenous community sees the welfare and prosperity of their community much differently than what economics textbooks portray.

This study aims to provide a systemic and integrated view of how Industry 4.0 and its enabling technologies affect companies' internal and external environments. It offers a comprehensive view of the contribution about ten years after the start of the Fourth Industrial Revolution.

The study performs a systematic literature review based on Industry 4.0 management literature. Analyzing the results of the 308 final papers in the sample made it possible to build a theoretical model to explain the contribution of Industry 4.0 to the internal and external environment of the company.

The results highlight the contribution of Industry 4.0 to the processes and environment of the company by providing a systemic and integrated view, highlighting the most applied enabling technologies and their internal, external, and combined usefulness in business processes.

Finally, the paper provides a broad view of the Industry 4.0 topic ten years after its origin through an extensive literature analysis that allows us to highlight the significant studies and the areas still under-researched by researchers and opens the debate on the Industry 5.0 scenario.

The model makes it possible to appreciate the role of Industry 4.0 and its enabling technologies in companies in a broad and systemic view and to understand, from a managerial point of view, the interactions, synergies, and possibilities within processes and the reflection on the external environment.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

This paper finds the returns from soil conservation practices and examines whether the welfare implications of adopting the conservation practices are heterogeneous across the farming groups in Indian agriculture.

The study uses an endogenous switching regression (ESR) method on the data collected from the 77th round of National Sample Survey (2019–21) to quantify the returns from adopting soil conservation practices.

It finds that farmers adopting soil health conservation practices would have reduced their crop yield by 13% if they did not implement them. Similarly, smallholders who have not adopted soil health management practices would have increased crop yield by 16% if they had adopted the practices. The authors also observed that the returns from adopting soil health management practices vary across farming groups, where marginal and large farms tend to gain higher yields. Finally, the authors find that regardless of farm size, smallholders who did not adopt soil health management practices would benefit from adopting these with increased crop yields of 29%–31%.

More data could have been better for drawing policy implications, since the number of soil card users are relatively less.

This research work uses nationally representative data, which is first in nature on this very aspect.

Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.

The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.

This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.

This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.