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The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.

This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.

A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.

The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.

The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.

Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.

The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.

This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.

The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.

The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.

Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.

The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.

Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.

This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.

This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.

This research aims to conceptualize online shaming discourse in virtual communities and to serve as a practical guide for online community managers and members.

This conceptual study explores the construction of meanings in human interaction in online communities by presenting a conceptual model, “The Triple-Responsibility Model in Online Communities,” that is based on Kantian ethics.

The model includes characterizing the roles of core participants in online communities: writer, reader and group manager; and delineating four ethical principles – truth, necessity, proportionality and caution – that can help society find the golden mean between social change and respecting human dignity and concern for an individual’s public image and provide a theoretical contribution and practical guidelines.

It addresses shaming in virtual communities by suggesting a balance of several key principles, including truth, necessity, proportionality and caution. This is a new conceptualization of online shaming relevant to today's digital arena.

The guidelines can contribute to the ongoing political debate over what constitutes appropriate and justified regulation. Moreover, Facebook community leaders are responsible for formatting the group’s identity, the technical facets of group management and for setting group boundaries and determining the rules of participation. The posited rules may affect social media group managers, as they are called upon to leverage their privileged position and channel their media power into influencing online discourse.

The current study provides insights into how shaming can be used as a legitimate tool in society by implementing an ethical approach, resulting in guidelines that restrict online discourse for participants in virtual communities and affect the work of social media group managers and policymakers.

By presenting a new conceptual model, the authors suggest that ethics are a helpful tool and offer insights into how online communities' participants and managers should use their voice and balance between shaming and maintaining the dignity of the individual.

This study examines academic librarians' perceptions and attitudes toward Internet of Things (IoT) applications in Hong Kong academic libraries and the problems and possible improvements in using IoT technologies to strengthen library services.

This qualitative research used video conferencing software for semi-structured, one-on-one interviews. Participants were given introductory material about the IoT and asked to complete an interview. The data were analyzed using inductive theme clustering for this study.

The analysis identified three themes: perception about applying IoT technology to the library, problems and improvements in using IoT. Participants were generally optimistic about the potential benefits of IoT for improving library operations and providing personalized services. However, they also expressed concerns about privacy and security, errors and extra efforts for information literacy training. They suggested improvements such as incorporating facial recognition technology, advanced RFID technology and collections identification technology to enhance user experience.

Most studies examined users' views rather than librarians' on IoT applications, which few studies cover, especially in East Asia.

The purpose of this paper is to understand the applications of metaverse-related technologies in US urban libraries, explore excellent cases of US urban libraries' practices in using metaverse-related technologies to serve patrons and try to find the factor that may affect the application of metaverse-related technologies in libraries at this stage.

To gather information about how and whether libraries use metaverse-related technologies such as three-dimensional (3D) technology, radio frequency identification (RFID), virtual reality augmented reality (AR) and artificial intelligence (AI) in their services. Firstly, the authors visit 150 US urban library websites that are members of the Urban Libraries Council. Secondly, the authors calculate the proportion of services provided by urban libraries that use metaverse-related technologies and introduce outstanding cases. Lastly, the authors discuss the factors that influence the application of metaverse-related technologies in urban libraries in the United States based on data published by the Institute of Museum and Library Services.

Metaverse-related technologies have been widely used in US urban libraries, but there are differences in the popularity of the applications of different technologies. In all, 84% of libraries use 3D technology, mainly in 3D printing services and 3D model building services; 76% of libraries use virtual and augmented reality technologies in their services, mainly concentrated in head-mounted VR device experiences, AR device experiences, virtual tours and virtual exhibitions; 62% of libraries use Internet of things (IoT) technology, mainly in self-checkout machines and book location services. However, AI technologies are less used in libraries, with 28% of libraries mentioning the applications of AI in their services, mainly focusing on intelligent search, virtual assistants and robot librarians. In addition, this study finds that library operating expenditures and population served do not affect the application of metaverse-related technologies in libraries.

This paper provides updated statistical data on the use of metaverse-related technologies in US urban libraries and aims to help library managers understand the overall applications and best practices. With this as an inspiration, they could formulate corresponding development plans to better serve their communities with metaverse-related technologies.

By a thorough bibliometric examination of the area through time, this paper analyses the research landscape of metaverse in education. It is an effort that is focused on the metaverse research trends, academic production and conceptual focus of scientific publications.

The Web of Science (WoS) database was explored for information containing research articles and associated publications that met the requirements. For a thorough analysis of the trend, thematic focus and scientific output in the subject of metaverse in education, a bibliometric technique was used to analyse the data. The bibliometrix package of R software, specifically the biblioshiny interface of R-studio, was used to conduct the analysis.

The analysis of the metaverse in education spanning from 1995 to the beginning of 2023 reveals a dynamic and evolving landscape. Notably, the field has experienced robust annual growth, with a peak of publications in 2022. Citation analysis highlights seminal works, with Dionisio et al. (2013) leading discussions on the transition of virtual worlds into intricate digital cultures. Thematic mapping identifies dominant themes such as “system,” “augmented reality” and “information technology,” indicating a strong technological focus. Surprisingly, China emerges as a leading contributor with significant citation impact, emphasising the global nature of metaverse research. The thematic map suggests ongoing developments in performance and future aspects, emphasising the essential role of emerging technologies like artificial intelligence and virtual reality. Overall, the findings depict a vibrant and multidimensional metaverse in education, poised for continued exploration and innovation.

The study is among the pioneers that provide a comprehensive bibliometric analysis in the area of metaverse in education which will guide the novice researchers to identify the unexplored areas.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

This research shows how social media has affected learning at present during the COVID-19 pandemic and how it has become the largest and most convenient area of communication. In the current scenario, it seems that social networking sites not only had a profound impact on our social structure and intra-social interaction, but also affected education in general and learning English language in particular. It has been proven that these various social media platforms have created a realm of digital environment in today's new-age learning. Social media platforms are social networking sites through which people interact and communicate with each other easily and conveniently. Undoubtedly and unquestionably, social networking has been proven to be a global phenomenon that has caused a vast paradigm shift in the world of Learning and education during the current pandemic. Therefore, the present study aims to reach the extent of the impact of the various social media platforms on learning English language during the COVID-19 pandemic from the students' point of view.

The study was conducted at the undergraduate level for English language learners. The sample comprised 166 undergraduate students at Najran University. A survey questionnaire was administered to find out the impact of various social media platforms and social networking sites on learning English language in the academic year of 2020 due to the COVID-19 pandemic and to highlight possible suggestions for improving future virtual language learning.

The findings of the study contributed to the area of online learning of English language during the COVID-19 pandemic. Final results confirmed that the utilization of social media has been significantly perceived to have positively impacted learning English language in terms of writing style, reading skills, listening and lexical variation, communication skills and grammar usage.

The findings of the study can serve as fundamental indicators to implement prompt pedagogical reformations, for which a number of pedagogical implications can be proposed. Another equally important pedagogical implication is to design and provide professional development and training sessions to both students and educators on the ultimate utilization of social media as instructional technologies in the context of English language teaching and learning.

This research provides insights in developing policies to assist with the integration and utilization of social media platforms as instructional technologies in the context of English language teaching and learning and how institutions can respond to the advent of advancing technology, especially during and after the COVID-19 era. A model to improve online English language learning process is recommended as a guideline for all educators offering online learning.

This paper aims to provide an overview of South African perspectives on preventing, monitoring and combating hate victimisation, towards informing international understandings.

Using a general review approach, this paper provides a historical examination of measures proposed by the South African Government and civil society since 1994, to prevent, monitor and combat hate crime, hate speech and intentional unfair discrimination.

Regardless of a constitutional commitment to social inclusion, diversity and minority rights, significant progress remains lacking after almost three decades of related advocacy, lobbying and limited government intervention. Findings of the South African Hate Crimes Working Group (HCWG) longitudinal Monitoring Project emphasise the need for decisive legal responses to hate victimisation.

A Bill, recognising hate crime and hate speech as distinct criminal offences, has been in development for almost 15 years and will soon serve before Parliament. Enactment of this legislation will be ground-breaking in Africa.

This paper contributes to the field of hate studies by providing an overview of the journey towards current conceptual understandings of hate in (South) Africa. It sets the stage for evaluating the potential of the redesigned HCWG monitoring tool, which holds promise for early identification and intervention in hate hotspots and targeted sectors. This instrument can establish trends not only in South Africa but also across the African continent.