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This study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.

The authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.

The authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.

The limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.

This study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.

This paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.

This study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

The connection between digital manufacturing technologies (Industry 4.0) and the environment has sparked discussions on firms' disclosure of negative information on pollutant emissions and the pursuit of positive environmental outcomes. However, very few studies explore how it relates to a firm's robot usage and its mechanism. The purpose of this paper is to investigate the impacts of robot penetration on firms' environmental governance in China.

The ordered probit model (and probit model) are employed and empirically tested with a sample of 1,579 Chinese listed firms from 2010 to 2019.

The study reveals a negative relationship between robot usage and the disclosure of negative indicators and a U-shaped relationship between robot usage and positive environmental outcomes. Among the sample, nonstate-owned enterprises (SOEs) display unsatisfactory performance, while heavily polluting industries disclose more information on pollutant emissions. The robot–environmental governance nexus is conditional on firm size, capital intensity and local economic development.

The study proposes a fresh view of corporate environmental governance to assess the environmental implications of robot adoption. It also contributes to identifying the curvilinear, moderating and heterogenous effects in the robot–environment nexus. The results provide rich policy implications for the development of industrial intelligence and corporate environmental governance in the circular economy (CE) context.

The introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.

A systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.

Based on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.

The findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.

The authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.

By considering the challenges of Industry 5.0, the purpose of this study is to analyze the role of heuristic factors in the technical qualities and emotions of Millennials and Generation Z (Gen Z) to assess their acceptance of the use of artificial intelligence (AI) devices such as robots. For this purpose, this paper uses the innovative AI device use acceptance (AIDUA) framework. This research evaluates the implications of human–machine interactions for the usage of robots and AI in daily life.

The proposed AIDUA model is tested using data collected from Millennials and Gen Z. First, a principal components analysis technique is used to validate each measure. Second, a multiple regression analysis using IBM SPSS 26.0 is conducted.

The results of this study suggest that human–machine interaction is a part of a complex process in which there are different elements determining individuals’ acceptance of the use of AI devices during daily life. This paper outlines both the theoretical and practical implications. This study enriches the AIDUA model by connoting it with features and emotions belonging to the younger generation. Additionally, this research offers technology companies suggestions for addressing future efforts on technical performance and on the alignments of the expectations of young people in Society 5.0.

First, the originality of this paper lies in highlighting the binary role of emotions in triggering the use of AI devices and robots. Second, the focus on Millennials and Gen Z offers a new lens for the interpretation of longitudinal phenomena in the adoption of AI. Finally, the findings of this paper contribute to the development of a new perspective regarding a “heartly collaborative” approach in Society 5.0.

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.

Adopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.

The study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.

Research on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.

The research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.

This study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.

Information infrastructures can enable or constrain how companies pursue their visions of sustainability reporting and help address the urgent need to understand how corporate activity affects sustainability outcomes and how socio-ecological challenges affect corporate activity. The paper examines the relationship between sustainability reporting information infrastructures and sustainability reporting practice.

The paper mobilises a socio-technical perspective and the conception of infrastructure, the socio-technical arrangement of technical artifacts and social routines, to engage with a qualitative dataset comprised of interview and documentary evidence on the development and construction of sustainability reporting information.

The results detail how sustainability reporting information infrastructures are used by companies and depict the difficulties faced in generating reliable sustainability data. The findings illustrate the challenges and measures undertaken by entities to embed automation and integration, and to enhance sustainability data quality. The findings provide insight into how infrastructures constrain and support sustainability reporting practices.

The paper explains how infrastructures shape sustainability reporting practices, and how infrastructures are shaped by regulatory demands and costs. Companies have developed “uneven” infrastructures supporting legislative requirements, whilst infrastructures supporting non-legislative sustainability reporting remain underdeveloped. Consequently, infrastructures supporting specific legislation have developed along unitary pathways and are often poorly integrated with infrastructures supporting other sustainability reporting areas. Infrastructures developed around legislative requirements are not necessarily constrained by financial reporting norms and do not preclude specific sustainability reporting visions. On the contrary, due to regulation, infrastructure supporting disclosures that offer an “inside out” perspective on sustainability reporting is often comparatively well developed.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to examine the impact of extensible business reporting language (XBRL) technology and its functionality on various aspects of financial reporting and its overall quality.

To conduct this study, data was collected from a variety of professionals, including accountants, auditors, tax advisors and others. A structured research instrument was developed, and the collected data were analysed using structural equation modelling and mediation analysis techniques.

The study’s results showed that XBRL technology and its functionality have a noteworthy impact on different aspects of financial reporting. Moreover, the various aspects of financial reporting positively affect the overall quality of financial reporting.

This study solely relied on the opinions of various professionals regarding the current issue under investigation and did not empirically assess the reporting practices of companies by examining their XBRL-based reports. Additionally, it concentrated solely on financial reporting aspects and did not account for non-financial aspects. The main theoretical contributions of this paper to technology in financial reporting, XBRL and accounting literature are that it sheds light on the influence of the use of technologies in the business reporting process and their influence on various aspects of business reporting, which has only received confined focus from earlier studies so far.

This study’s findings could provide valuable insights to the managerial teams of organizations seeking to digitize their business reporting practices, specifically in areas such as regulatory compliance, integrated reporting and timely dissemination of reports in a sustainable way. Furthermore, it could help these teams reap the benefits of technology for various regulatory compliance matters.

This study could assist business organizations and regulatory authorities in adopting and implementing technology such as XBRL for accounting and business reporting. Furthermore, the study’s findings can aid in enhancing financial reporting practices by considering emerging aspects such as ESG and sustainability aspects.