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This study aims to examine the relationship between information and communication technology (ICT) and economic growth in all organization for economic co-operation and development (OECD) countries.

This paper employs annual panel data together with fixed-effects (FE), random effects (RE), fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and generalized method of moments (GMM) estimators for production function estimation.

The results indicate that ICTs, non-ICT (NICT) capital services and employment significantly and positively affect economic growth.

Information is an important driving force behind economic growth and productivity, and communication technologies have made it more accessable. Also, many countries aimed to invest in ICT to improve their economic growth and productivity. However, these investments failed to produce the expected outcome for some years and countries.

To our knowledge, no study examines the ICT and growth relation in all OECD countries for 2000–2018 period. We intend to fill this gap by examining whether or not the expected returns from ICT investment are achieved in all OECD countries between 2000 and 2018.

We examined the role of technology in employment and work for people with disabilities (PWD). We intended to identify publication trends, key terms, research areas and potential gaps in the topic.

We scrutinized relevant articles from two major databases through bibliometric and systematic review analyses. The bibliometric data involved 256 articles analysed through the VOSviewer software to produce publication trends and network maps. We then scanned article abstracts and selected 114 articles for thematic analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.

The findings revealed a dominance of authors from Western and European countries, particularly the United States of America. Three themes emerged as the crucial factors shaping technology utilization for PWD employment and workplace inclusion. These were identified as individual, environmental and societal, which shed light on the multifaceted influences surrounding PWD’s technology empowerment.

The hybrid review approach enables a thorough examination of the published work. Our study proposes a conceptual model for PWD employment and workplace inclusion. Founded on the theories of Work Adjustment, Human–Computer Interaction and the Social Model of Disability. The model provides a clear visualization to guide further research and relevant initiatives in this area.

This research paper investigates the theoretical frameworks encompassing a nuanced analysis of the digital divide in the Indian educational context, recognising that it is not merely a matter of technology access but also the ability to effectively use the resource for enhancing learning outcomes. This research provides valuable insights for fostering a more equitable and digitally inclusive learning environment by integrating conceptual insights with empirical evidence. The New Education Policy (NEP), India 2020 firmly emphasises the appropriate integration of technology into the teaching-learning process to develop relevant competencies. The pertinent question is, for India to conquer the second digital divide challenge, is the pace of technology accessibility and skill development sufficient?

The paper is a desk research, using secondary data from the Unified District Information System for Education (UDISE+), the Indian Government database of schools. A structured dataset has been created for all years, where states are grouped in descending ranking order of availability of infrastructure and teachers trained. A colour key segregates the States into three zones demonstrating their different levels of performance – high (green), moderate (blue) and low (yellow). The purpose is to identify state/s that have moved from one zone to another and, thereafter, analyse the reasons behind the movement.

Almost all states remained in the same digital resource availability zone for the four years studied, except for a limited few. Despite government interventions through higher budget allocation and targeted policies, growth rates of teacher training in computer usage slowed down post-COVID-19. A high positive correlation between Teachers' training in computer usage and the availability of computer and Internet facilities in schools indicates that an increase in digital infrastructure in schools is highly linked to teachers' training in computer usage and would ultimately translate into better use of digital resources to impart equitable education opportunities.

Primary data collection through interviews might have added to the critical findings. Therefore, researchers are encouraged to test the proposed propositions further on a case-by-case basis for any state under consideration.

Enhancing digital infrastructure in schools and building digital competence in teachers must be understood in the context of the learning organisation and the beneficiaries' attitudes at the meso-level to expand stakeholder motivation towards digital internalisation. This requires continuous engagement with education institutions as professional learning organisations, which will thereby help develop a decentralised context for teacher competency building. Collaboration, continuous monitoring of the outcomes of professional development programs, and sharing best practices are crucial in improving teacher readiness for digital education.

Access to tangible resources, such as computers, Internet connectivity and educational software, and developing intangible resources, such as teacher digital competencies, will play a pivotal role in shaping students' learning experiences. By studying the discrepancies in digital resource accessibility and teacher technology adoption, this research endeavours to add to the efforts towards enhancing the educational landscape.

This paper seeks to address a critical issue in the Indian education system and contribute to the ongoing effort to prevent the widening of the second and third digital divide in schools, and help achieve UN SDG Goals 4 and 10.

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.

The aim of this paper is twofold: to explore the significance and implications of the rise of AI technology for the field of tertiary education in general and, in particular, to answer the question of whether teachers can be replaced by intelligent AI systems such as androids, what that requires in terms of human capabilities and what that might mean for teaching and learning in higher education.

Given the interdisciplinary nature of this conceptual paper, a literature review serves as a methodological tool to access data pertaining to the research question posed in the paper.

This exploratory paper gathers a range of evidence from the philosophy of mind (the mind-body problem), Kahneman’s (2011) System 1 and System 2 models of the mind, Gödel’s (1951) Two Incompleteness Theorems, Polanyi’s (1958, 1966) theory of tacit knowing and Searle’s (1980) Chinese Room thought experiment to the effect that no AI system can ever fully replace a human being because no machine can replicate the human mind and its capacity for intelligence, consciousness and highly developed social skills such as empathy and cooperation.

AI is rising, but there are inherent limits to what machines can achieve when compared to human capabilities. An android can at most attain “weak AI”, that is, it can be smart but lack awareness or empathy. Therefore, an analysis of good teaching at the tertiary level shows that learning, knowledge and understanding go far beyond any quantitative processing that an AI machine does so well, helping us to appreciate the qualitative dimension of education and knowledge acquisition. ChatGPT is robotic, being AI-generated, but human beings thrive on the human-to-human interface – that is, human relationships and meaningful connections – and that is where the true qualitative value of educational attainment will be gauged.

This paper has provided evidence that human beings are irreplaceable due to our unique strengths as meaning-makers and relationship-builders, our capacity for morality and empathy, our creativity, our expertise and adaptability and our capacity to build unity and cooperate in building social structures and civilization for the benefit of all. Furthermore, as society is radically automated, the purpose of human life and its reevaluation will also come into question. For instance, as more and more occupations are replaced by ChatGPT services, more and more people will be freed up to do other things with their time, such as caring for relatives, undertaking creative projects, studying further and having children.

The investigation of the scope and limitations of AI is significant for two reasons. First, the question of the nature and functions of a mind becomes critical to the possibility of replication because if the human mind is like a super-sophisticated computer, then the relationship between a brain and mind is similar (if not identical) to the relationship between a computer as machine hardware and its programme or software (Dreyfus, 1979). [ ] If so, it should be theoretically possible to understand its mechanism and reproduce it, and then it is just a matter of time before AI research and development can replicate the human mind and eventually replace a human teacher, especially if an AI machine can teach just as intelligently yet more efficiently and economically. But if AI has inherent limitations that preclude the possibility of ever having a human-like mind and thought processes, then our investigation can at least clarify in what ways AI/AGI – such as ChatGPT – could support teaching and learning at universities.

South Africa lags significantly in mathematics achievement on international benchmarking tests, which has led to several interventions aimed at improving mathematics attainment in the country. Drawing on the theoretical work of Vygotsky, Leontiev and Engeström, this chapter reports on one such initiative that implemented computer technology into disadvantaged schools in the apple growing district of the Western Cape. Contrary to expectations, the object of the lesson became control over students' actions, rather than a mathematical object aimed at developing students' understanding of the subject. The teacher adopted what I call a defensive position in relation to the novel technology, tightening pace and sequencing in these lessons. I draw on Ratnam's work into ‘excessive entitlement’ to illustrate that this teacher's defensive posture regarding technology emanates from a need to exert complete power over the content taught in a lesson and leads her to reject the novel technology in favour of traditional methods. While interviews with the teacher in this study indicated that she felt she promoted student dialogue and more symmetrical power relations in her classes through group work, this is not seen in the data. This is explained in relation to teachers' excessive entitlement to ‘owning’ the knowledge in their classrooms through maintaining control over the rules of the system. I pull on Cultural-Historical Activity Theory (CHAT) to illuminate how the activity of teaching in a classroom affords and constrains what the teacher is able to achieve, often making them feel excessively entitled to push back reform.

The aim of this study is to investigate the contribution of tangible and intangible investments in driving labour productivity growth in the European Union over the period 2000–2017 and their role in the short and medium run. Additionally, heterogeneity across countries is accounted for by performing estimates separately for Eastern and Western European countries.

The methodology used to conduct the analysis of the determinants of productivity is the two-way fixed-effect and the system generalised method of moments. We also include country-specific dummies in place of our variable on national innovative capacity as a means to further reduce the number of instruments.

The results reveal a long-term relationship of investment in intangible assets with labour productivity growth, more specifically of investment in R&D. This relationship holds both when considering the whole set of European countries and for Western European countries, demonstrating that R&D is key to enhancing labour productivity growth. On the contrary, the effect for Eastern countries is negative, probably due to the lack of capacity to turn this investment into an efficient and effective way to foster productivity.

Besides confirming the well-known role of tangible and intangible assets in productivity, the heterogeneity shown in our analysis highlights the need for improving capabilities in Eastern countries. Diversifying the decisions on the investments in European countries, depending on the specific needs and their heterogeneity, could help bridge the productivity gap and enhance specific capabilities of the country systems.

This paper aims to identify impediments, discuss impediments and make recommendations for the impediments during the execution of a search and seizure warrant for digital evidence in South African criminal cases.

The discussion of this article, the second article of two, focuses on a literature review of international and local impediments identified in case law and published research literature and how it is approached in various jurisdictions.

This study found that impediments identified and addressed internationally during the execution of a search and seizure warrant for digital evidence are relevant to South African criminal cases and still need to be addressed during the execution of a search and seizure warrant for digital evidence in South African criminal cases.

Although searches and seizures for digital evidence are relevant to civil, regulatory and criminal investigations, this study focuses on the search and seizure for digital evidence in criminal matters with an emphasis on the provisions of the Criminal Procedure Act 51 of 1977 and the Cybercrimes Act 19 of 2020.

The originality of this paper lies in the procedures followed during the physical search and seizure of digital information during the execution of search and seizure warrants for digital information in South Africa. If the South African Police Service follows the recommended procedures, it will contribute to the success of the South African Police Service, which would result in the improved quality of investigations and successful prosecution of crime in South Africa.

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

This study aims to test whether a) differences existed in dissent expression between women in management and nonmanagement positions and b) the differences varied between white women and women of color.

Responses from 1,011 employed women in the US were analyzed for the study.

Results revealed that in management vs nonmanagement status, women employees were more likely to express upward dissent and employ dissent strategies that signified both influence and lack of influence in organizations. However, race-based differences existed in the expressions of some forms of dissent.

Research has shown that employees in management vs nonmanagement status express more upward dissent and employ dissent strategies that signify influence in organizations. However, can this be the case for women employees? Although previous research has explored dissent expression extensively in US organizations, women employees' dissent expression has not received much attention in social-scientific studies. In these studies, gender and race were treated as mere demographic variables to describe sample compositions despite these variables being influential factors in organizational life. Through an intersectional approach to identities, this study’s findings call upon organizations to address iniquities that limit dissent expression based on identity hierarchies.