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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.

The objective of this paper is to further the understanding of netnography as a research method for supply chain academics. Netnography is a method for gathering and gaining insight from industry-specific online communities. We prescribe that viewing netnography through the lens of the supply chain will permit researchers to explore, discover, understand, describe or report concepts or phenomena that have previously been studied via survey research or quantitative modeling.

To introduce netnography to supply chain research, we propose a framework to guide how netnography can be adopted and used. Definitions and directions are provided, highlighting some of the practices within netnographic research.

Netnography provides the researcher with another avenue to pursue answers to research questions, either alone or in conjunction with the dominant methods of survey research and quantitative modeling. It provides another tool in the researchers’ toolbox to engage practitioners in the field.

The development of netnography as a research method is associated with Robert Kozinets. He developed the method to study online communities in consumer behavior. We justify why this method can be applied to supply chain research, how to collect data and provide research examples of its use. This technique has room to grow as a supply chain research method.

This paper aims to highlight the expanding link between facility management (FM) and building automation and control systems (BACS) through a review of literature. It examines the opportunities and challenges of BACS for facility managers and proposes solutions for mitigating the risks associated with BACS implementation.

This paper reviews various research papers to explore the positive influences of BACS on FM, such as support with strategic decision-making, predictive maintenance, energy efficiency and comfort improvement. It also discusses the challenges of BACS, including obsolescence, interoperability, vendor lock-in, reliability and security risks and suggests potential solutions based on existing literature.

BACS offers numerous opportunities for facility managers, such as improved decision-making, energy efficiency and comfort levels in office buildings. However, there are also risks associated with BACS implementation, including obsolescence, interoperability, vendor lock-in, reliability and security risks. These risks can be mitigated through measures such as hardware and software obsolescence management plans, functional requirement lists, wireless communication protocols, advanced feedback systems and increased awareness about BACS security.

To the best of the authors’ knowledge, no prior academic research has been conducted on the expanding link between FM and BACS. Although some papers have touched upon the opportunities and challenges of BACS for FM, this paper aims to provide a comprehensive overview of these findings by consolidating existing literature.

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.

E-learning has become a polarizing issue. Some say that it enhances accessibility to education and some say that it hinders it. While the literature on the subject underscores the effectiveness of the pedagogical frameworks, strategies and distance learning technologies, the firsthand accounts of students, parents and practitioners challenge the validity of experts’ assessments. There is a gap between theory and practice and between the perceptions of providers and consumers of online learning. Following a period of lockdowns and a transition to online learning during the recent pandemic, the prevailing sentiment toward a distance mode of instruction became one of strong skepticism and negative bias. The aim of the study was to examine why e-learning has struggled to meet stakeholder expectations. Specifically, the study posed two research questions: 1. What are the reasons for dissatisfaction with online learning? 2. What are the implications for future research and practice?

The study used a mixed methods approach to examine the reasons behind negative perceptions of online learning by comparing the firsthand accounts posted on social media with the literature. To this end, n = 62,874 social media comments of secondary and postsecondary students, as well as parents, teachings staff and working professionals, covering the span of over 14 years (2008–2022), were collected and analyzed.

The study identified 28 themes that explain the stakeholder’s discontent with the online learning process and highlighted the importance of user-centric design. The analysis revealed that the perceived ineffectiveness of distance education stems from the failure to identify and address stakeholders’ needs and, more particularly, from the incongruence of instructional strategies, blindness to the cost of decisions related to instructional design, technology selection and insufficient levels of support. The findings also highlight the importance of user-centric design.

To address dissatisfaction with e-learning, it is imperative to remove barriers to learning and ensure alignment between technology and learners’ needs. In other words, the learning experience should be personalized to account for individual differences. Despite its cost-effectiveness, the one-size-fits-all approach hinders the learning process and experience and is likely to be met with resistance.

Drawing from the extensive literature, the study offers an explanation for stakeholders’ discontent with e-learning. Unlike survey research that is prone to social desirability bias, the sample provides a rare opportunity to observe and measure the visceral reactions that provide a more authentic sense of stakeholders’ perceptions toward online learning. The authors offer recommendations and identify areas for future research.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

With the increasing use of social media in operation and supply chain management (OSCM), it is of great importance for managers to consider risks in advance and take precautions against the risks that might arise from social media usage among supply chain members. The aim of this research is to identify and evaluate the risks related to the use of social media in OSCM.

An initial research of the literature revealed that there is no detailed risk categorization in this area. Current taxonomies on the business risks of social media usage were examined and integrated with classifications identified in a Delphi study. The authors empirically demonstrate how the determined risks are prioritized and how decision-makers may decide to manage risks effectively based on the analytical hierarchy process (AHP) method.

The findings of the research showed that reputation-associated risks such as criticism, language and loss of confidence should be prioritized over human, content and technical-associated risks.

To date, a comprehensive approach to determine risks arising from using social media in OSCM is missing. With the Delphi and AHP techniques, the authors provide a novel insight for managers to mitigate risks. The outcomes of this study may assist executives in achieving successful management of social media usage in OSCM. Besides, the proposed AHP model may provide guidelines and direction in this regard.

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.

Although universities have extensive research and initiatives in place that align with the United Nations’ Sustainable Development Goals (SDGs), there is still a significant gap in documenting and assessing these efforts. This paper aims to discuss how academic libraries can apply their information management skills and open-access platforms, to facilitate the discoverability and retrieval of evidence on SDGs.

Introduced by a brief literature review on the role of libraries in contributing to the SDGs in general, the authors draw on their personal experiences as metadata specialists, participating in a project aimed at linking their university’s research output to the SDGs. A case study, from the University of Pretoria’s Veterinary Science Library, is used as an example to demonstrate the benefits of resourceful metadata in organising, communicating and raising awareness about the SDGs in the field of veterinary science.

Through practical examples and recommended workflows, this paper illustrates that metadata specialists are perfectly positioned to apply their information management skills and library platforms to facilitate the discoverability and retrieval of evidence on SDGs.

Although there are increasing reports on the contributions of libraries to support the successful implementation of the SDGs, limited information exists on the role of metadata specialists, as well as those with a practical focus.

This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements.

A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company.

Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively.

Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions.

This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software.