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This study aims to investigate the impact of the 2013 privatization of Nigeria’s energy sector on the technical performance of the Benin Electricity Distribution Company (BEDC) and its workforce.

This study used a questionnaire-based approach, and 196 participants were randomly selected. Analytical tools included standard deviation, Spearman rank correlation and regression analysis.

Before privatization, the energy sector, managed by the power holding company of Nigeria, suffered from inefficiencies in fault detection, response and billing. However, privatization improved resource utilization, replaced outdated transformers and increased operational efficiency. However, in spite of these improvements, BEDC faces challenges, including unstable voltage generation and inadequate staff welfare. This study also highlighted a lack of experience among the trained workforce in emerging electricity technologies such as the smart grid.

This study’s focus on BEDC may limit its generalizability to other energy companies. It does not delve into energy sector privatization’s broader economic and policy implications.

The positive outcomes of privatization, such as improved resource utilization and infrastructure investment, emphasize the potential benefits of private ownership and management. However, voltage generation stability and staff welfare challenges call for targeted interventions. Recommendations include investing in voltage generation enhancement, smart grid infrastructure and implementing measures to enhance employee well-being through benefit plans.

Energy sector enhancements hold positive social implications, uplifting living standards and bolstering electricity access for households and businesses.

This study contributes unique insights into privatization’s effects on BEDC, offering perspectives on preprivatization challenges and advancements. Practical recommendations aid BEDC and policymakers in boosting electricity distribution firms’ performance within the privatization context.

An unreliable supply of grid electricity has a strong negative impact on industrial and commercial profitability as well as on household activities and government services that rely on electricity supply. This unreliable grid electricity could be a result of technical and security factors affecting the grid network. Therefore, this study aims to investigate the effects of technical and security factors on the transmission and distribution of grid electricity in Uganda.

This study used the ordinary least squares (OLS) and autoregressive distributed lag (ARDL) models to examine the effects of technical and security factors on grid electricity reliability in Uganda. The study draws upon secondary time series monthly data sourced from the Uganda Electricity Transmission Company Limited (UETCL) government utility, which transmits electricity to both distributors and grid users. Additionally, data from Umeme Limited, the largest power distribution utility in Uganda, were incorporated into the analysis.

The findings revealed that technical faults, failed grid equipment, system overload and theft and vandalism affected grid electricity reliability in the transmission and distribution subsystems of the Ugandan power grid network. The effect was computed both in terms of frequency and duration of power outages. For instance, the number of power outages was 116 and 2,307 for transmission and distribution subsystems, respectively. In terms of duration, the power outages reported on average were 1,248 h and 5,826 h, respectively, for transmission and distribution subsystems.

This paper investigates the effects of technical and security factors on the transmission and distribution grid electricity reliability, specifically focusing on frequency and duration of power outages, in the Ugandan context. It combines both OLS and ARDL models for analysis and adopts the systems reliability theory in the area of grid electricity reliability research.

This paper aims to describe a method for Internet-of-Things-devices to achieve industrial grade reliability for information transfer from wireless sensor systems to production systems using blockchain technologies.

An increased security and reliability of submitted data within the sensor network could be achieved on an application level. Therefore, a lightweight, high-level communication protocol based on blockchain principles was designed.

Blockchain mechanisms can secure the wireless communication of Internet-of-Things-devices in a lightweight and scalable manner.

The innovation of this research is the successful application of general blockchain mechanisms to increase security of a wireless sensor system without binding to a dedicated blockchain technology.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.

This paper aims that privacy research is divided in distinct communities and rarely considered as a singular field, harming its disciplinary identity. The authors collected 119.810 publications and over 3 million references to perform a bibliometric domain analysis as a quantitative approach to uncover the structures within the privacy research field.

The bibliometric domain analysis consists of a combined directed network and topic model of published privacy research. The network contains 83,159 publications and 462,633 internal references. A Latent Dirichlet allocation (LDA) topic model from the same dataset offers an additional lens on structure by classifying each publication on 36 topics with the network data. The combined outcomes of these methods are used to investigate the structural position and topical make-up of the privacy research communities.

The authors identified the research communities as well as categorised their structural positioning. Four communities form the core of privacy research: individual privacy and law, cloud computing, location data and privacy-preserving data publishing. The latter is a macro-community of data mining, anonymity metrics and differential privacy. Surrounding the core are applied communities. Further removed are communities with little influence, most notably the medical communities that make up 14.4% of the network. The topic model shows system design as a potentially latent community. Noteworthy is the absence of a centralised body of knowledge on organisational privacy management.

This is the first in-depth, quantitative mapping study of all privacy research.

Although management scholars have embraced grand challenges research, in many cases, grand challenges have been treated as merely a context for exploring extant theoretical perspectives. By comparison, our approach – robust action – provides a novel theoretical framework for tackling grand challenges. In this invited article, we revisit our 2015 model, clarifying and elaborating its key elements and taking stock of subsequent developments. We then identify three promising directions for future research: scaffolding, future imaginaries, and distributed actorhood. Ultimately, our core message is remarkably simple: robust action strategies – participatory architecture, multivocal inscription and distributed experimentation – jointly provide a means for tackling grand challenges that is well matched to their complexities, uncertainties, and evaluativities.

The purpose of this paper was to assess and determine the impact of the five core technologies of Industry 4.0 (3D Printing, Big Data Analytics, Cloud Computing, Internet of Things (IoT) and Robotics) on the organizational performance of the retail industry in the context of Pakistan.

Pakistan's retail industry was chosen as the target sector, and the target population was composed of senior-level employees, including managers from first-level positions to top-level positions, as well as subordinate employees working under the supervision of first-level managers, possessing the technological know-how of Industry 4.0. The data were collected through a matrix-based survey questionnaire that was based on a five-point Likert scale, ranging from “strongly agree” to “strongly disagree.” The process of data analysis was conducted using IBM SPSS Statistics.

The findings obtained by this research work showed a significant relationship among the five core pillars of Industry 4.0 and the organizational performance of Pakistan's retail industry. Besides, the obtained findings provided preliminary evidence that Industry 4.0's disruptive technologies, particularly, 3D printing, big data analytics, cloud computing, IoT and robotics, could help Pakistan's retail industry solve various problems and challenges, such as meager revenues, increased expenses and unorganized systems.

The present study extended the theoretical body of knowledge through studying and examining Industry 4.0's five crucial factors that significantly contribute to the service sector, particularly, the retail industry, of the big emerging markets (BEM) economies, including Pakistan.

The paper concludes with showing that in the most optimistic scenario, end-of-life (EOL) batteries will account for 86% of energy storage for wind and 36% for solar PV in 2040.

With the growing demand for electric vehicles (EVs), the stock of discarded batteries will increase dramatically if no action is taken for their reuse or recycling. One potential avenue is to reuse them as energy storage systems (ESS) to mitigate the intermittent generation of renewable energy such as solar PV and wind. In a sense, the reliability for solar PV and wind energy can increase if energy storage systems become economically more attractive, making solar and wind systems more attractive through economies of scale.

The paper concludes with showing that in the most optimistic scenario, EOL batteries will account for 86% of energy storage for wind and 36% for solar PV in 2040.

The projection of scenarios can contribute to the information of policies, standards and identification of environmental promotion and promotion related to efficient management for EOL batteries.

This study aims to exploit the abundance of solar energy resources for socioeconomic development in the semi -arid Northeastern Brazil as a potent adaptation tool to global climate change. It points out a set of conjuncture factors that allow us to foresee a new paradigm of sustainable development for the region by transforming the sun’s radiant energy into electricity through distributed photovoltaic generation. The new paradigm, as presented in this essay, has the transformative potential to free the region from past regional development dogma, which was dependent on the scarce water resource, and the marginal and predatory use of its Caatinga Biome.

The research uses a pre ante design, following the procedures of scenario building, as an adaptation mechanism to climate change in the sector of energy generation and socioeconomic inclusion.

The scenarios of socioeconomic resilience to climate change based on the abundance of solar radiation, rather than the scarcity of water, demonstrates its potential as a global adaptation paradigm to climate change.

The developments proposed are dependent on federal legislation changes, allowing the small producer to be remunerated by the energy produced.

The proposed smart grid photovoltaic generation program increases the country's resiliency to the effect of droughts and climate change.

As proposed, the program allows for the reversion of a pattern of long term poverty in semi-arid Northeast Brazil.

The exploitation of the characteristics of abundance of the semiarid climate, i.e. its very condition of semi-aridity with abundant solar radiation, is itself an advantage factor toward adaption to unforeseen drought events. Extensive previous research has focused on weighting and monitoring drought i.e. the paradigm of scarcity. The interplay between exploiting Northeast Brazil’s abundant factors and climate change adaptation, especially at the small farmer levels constitutes a discovery never before contemplated.

India is a fast-growing economy, that has a majority share in the global information technology industry (IT). Rapid urbanisation and modernisation in India have strained its energy sector, which is being reformed to cope. Despite being the global IT heart and having above average research output in the field of artificial intelligence (AI), India has not yet managed to leverage its benefits to the full. This study aims to address the role of AI and information management (IM) in India’s energy transition to highlight the challenges and barriers to its development and use in the energy sector.

The study, through analysis of proposed strategies, current policies, available literature and reports, discusses the role of AI and IM in the energy transition in India, highlighting the current situation and challenges.

The results show dispersed research and development incentives for IT in the Indian energy sector; however, the needed holistic top-down approach is lacking, calling for due attention in this matter. Adaptive and swift actions from policymakers towards AI and IM are warranted in India.

The ongoing transition of the Indian energy sector with the integration of smart technologies would result in increased access to big data. Extracting the maximum benefits from this would require a comprehensive AI and IM policy.

The revolution in AI and robotics must be carried out in line with sustainable development goals, to support climate action and to consider privacy issues – both areas in India must be strengthened.

The paper offers an original discussion on certain applicable solutions regarding the energy transition of AI coming from the Global South; they are based on lessons learned from the Indian case studies presented in this study.