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Examining Employee Empowerment within a Jordanian Bank
No full textThis research aims to examine how employee empowerment is enacted and experienced within a Jordanian bank. The study adopts an interactional perspective, viewing empowerment as a phenomenon shaped by everyday social interactions within the broader sociocultural, economic, and political contexts. The research employs a qualitative methodology based on an interpretive phenomenological approach to examine the lived experiences of empowerment. A total of 34 semi-structured interviews were conducted with managers and employees at a bank in Jordan. Among these, 20 employees were direct subordinates of 11 participating managers, facilitating a relational understanding of how empowerment is enacted by managers and experienced by subordinates. The findings show that empowerment within the bank takes the form of making recommendations rather than having decision-making authority, aiming to avoid risk. Employees and managers often prepare tasks or propose actions, but final decisions are reserved for higher levels of the bank. The study also revealed that managers differ in their approach to empowerment: some adopt a participatory style by fostering employee involvement and input, while others take a more directive stance. Consequently, employees experience empowerment differently based on their understanding of empowerment and how their manager interacts with them. These experiences are further shaped by broader cultural factors, where elements such as origin, whether the employee comes from an urban or rural background, gender, religion, socioeconomic status, wasta, and internal politics influence the shaping of empowerment. This study extends structural and psychological empowerment theories by demonstrating that empowerment is shaped through daily relationships, practices, and social context, rather than being defined by formal authority or internal employee cognition. Methodologically, it offers a relational, dual-perspective approach by incorporating both managers and subordinates. Future research could investigate comparative cases, additional sectors, and longitudinal dynamics
Coming in from the cold: Collective European intelligence in the Trump era
No full textTo develop European intelligence independence requires a large financial commitment, changes to laws and regulations, political cooperation and trust, and the coordination of European industry and academia
Advancements of Large Language Models for Enhancing Carbon Capture Technologies: A Comprehensive Review
Get PDFThis paper reviews the current research status, challenges, and prospects of applying large language models (LLMs) in carbon capture technologies. The review emphasizes the importance of interdisciplinary research, integrating AI into chemistry, engineering, and environmental science to address complex challenges in carbon capture. It provides a detailed analysis of how LLMs can be utilized across various stages of carbon capture, from experimental design to industry implementation, showcasing their potential to accelerate innovation. It also reveals the use of LLMs to support gathering and analyzing sustainable information, such as carbon tax, carbon footprint, and social analysis. LLMs not only show great potential in designing and discovering materials for carbon capture technologies but also are promising to accelerate the whole industry's development through their powerful data processing and pattern recognition capabilities. In addition, the review paper also discusses challenges in the application of LLMs for carbon capture technologies and future directions and prospects
Financial investigations of modern slavery offences
No full textBackground:Modern slavery is, in most cases, a financially motivated crime. Offending is often accompanied by financial activity, much of which leaves a trace. This raises the central question of whether financial investigations can offer a means of enabling prosecution without the need to rely so heavily on victim evidence, which can be difficult to secure in cases where victims are traumatised, fearful, or do not identify as victims. Despite the increasing number of potential victims identified, prosecutions, convictions, and sentences under the Modern Slavery Act remain low. This research sought to answer the question: How might financial investigation techniques be a means to improve prosecution and conviction rates in the UK’s Modern Slavery Act 2015? The report is the second in a two-part series. The first focused on identifying and analysing some of the key barriers to successful prosecutions and convictions under the Modern Slavery Act. This second report examines the role and potential of financial investigations as a means of enhancing enforcement outcomes
Fuel cell energy conversion
No full textFuel cells are electrochemical devices that convert the chemical energy of the fuel into electrical energy directly. There are different types of fuel cells, which can be categorized according to their electrolyte type and fuel used. The performance of these fuel cells mainly depends on the materials of their components and the manufacturing method. In this chapter, an introduction to different fuel cell types, the materials and manufacturing methods that can be used for fuel cells, and characterization techniques are first presented. Then, the basic concepts and equations for the thermodynamics and electrochemistry of fuel cells are given. The principles of fuel cell stack design including the calculations of pressure drop within a flow field are discussed. Energy and exergy analyses of integrated fuel cells systems are also presented. This chapter also covers several illustrative examples and a case study on the mathematical modeling of fuel cells
A Novel Approach for Forecasting and Scheduling Building Load through Real-Time Occupant Count Data
No full textThe smart buildings’ load forecasting is necessary for efficient energy management, and it is easily possible because of the data availability based on widespread use of Internet of Things (IoT) devices and automation systems. The information of buildings’ occupancy is directly associated with energy consumption. Therefore, we present a hybrid model consisting of a Long Short-Term Memory (LSTM) network, Extreme Gradient Boosting (XgBoost), Random Forest (RF) and Linear Regression (LR) for commercial and academic buildings’ load forecasting. The correlation between occupants’ count and total load of the building is calculated using Pearson Correlation Coefficient (PCC). The comparative analysis of the proposed approach with LSTM, XgBoost, RF and Gated Recurrent Unit (GRU) is also performed. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Square Error (MSE) and Normalized Root Mean Square Error (NRMSE) are used as performance indicators for evaluating performance. Findings indicate that the proposed hybrid approach outperforms other models. The RMSE and MAE of 2.99 and 2.18, respectively, are recorded by the proposed model for commercial building dataset while for academic building the RMSE and MAE are 4.48 and 2.85, respectively. Occupancy and load consumption have a positive correlation as evident from PCC analysis. Therefore, we have scheduled the forecasted load based on occupancy patterns for two different cases. Cost is reduced by 17.42% and 33.40% in case 1 and case 2, respectively. Moreover, the performance of the proposed hybrid approach is compared with different techniques presented in literature for buildings load forecasting
Embedding Governance and Accountability in Sustainable Forest Management: The Case of REDD+ Implementation in Ghana
Get PDFFrom Executive Summary:The introduction of the Reducing Emissions from Deforestation and Forest Degradation (REDD+) project in 2007 by the United Nations Conference of the Parties in Bali, Indonesia, as part of the Paris Agreement, was aimed at addressing deforestation, reducing greenhouse gas emissions and mitigating climate change by incentivising countries to conserve forests. Under the United Nations Framework Convention on Climate Change (UNFCC), developing countries can receive results-based payments for reducing emissions through REDD+ activities.Over the years, a number of countries have been engaged in this results-based project, with Ghana becoming the second African country, following Mozambique and the first in West Africa, to receive payments from the World Bank’s Forest Carbon Partnership Facility (FCPF). The FCPF disbursed $4,862,280 to Ghana, acknowledging the reduction of 972,456 tons of carbon emissions during the initial monitoring period. In light of project’s success in Ghana, this report, therefore, focuses on exploring and understanding the governance and accountability mechanisms that have made the REDD+ implementation in Ghana successful. The report employs a qualitative research design, utilising semi-structured interviews with stakeholders in the REDD+ space, focus group discussions with four beneficiary Hotspot Intervention Areas (HIAs), and insights from strategic documents on REDD+ from January 2024 to March 2025. These pieces of data are analysed using thematic analysis
Stablecoin as a hedge or a safe haven for international indices
Get PDFPurpose – This paper aims to systematically investigate and compare the hedge and safe-haven properties of stablecoins against international indices. It distinguishes itself from the existing literature by examining how risk-mitigation capabilities differ based on a stablecoin's underlying collateral mechanism. Design/methodology/approach – The authors employ a DCC-GARCH model to analyze the time-varying correlations between a large sample of 44 stablecoins and 30 international indices from October 2022 to September 2024. A core innovation is the systematic classification of stablecoins into five distinct categories (fiat-backed, algorithmic, crypto-collateral, physical gold-backed and synthetic assets-backed) to conduct a granular comparative analysis. Rolling window analysis is also utilized to assess these properties over shorter investment horizons. Findings – The study reveals that hedge and safe-haven properties are highly heterogeneous and depend critically on the stablecoin's design. Synthetic assets-backed stablecoins demonstrate overwhelmingly superior performance, acting as a strong hedge and weak safe haven for 21 of the 30 indices analyzed. In stark contrast, fiat-backed stablecoins, the largest market segment, exhibit very limited risk-mitigation capabilities. Practical implications – The findings provide crucial insights for both investors and policymakers. Investors seeking portfolio diversification should not treat all stablecoins as equal; synthetic asset-backed stablecoins are shown to be far more effective for managing risk against global equity downturns. For regulators, the paper highlights the urgent need for stringent oversight of fiat-backed reserves, while also noting that the effective but complex nature of decentralized synthetic stablecoins presents a different set of regulatory challenges and opportunities. Originality/value – This paper makes a significant contribution by providing the first comprehensive, classification-based analysis of stablecoins' role as potential risk-mitigation assets against a broad array of international stock indices. It challenges the monolithic view of “stablecoins” by empirically demonstrating that the underlying collateral design is the key determinant of their effectiveness as a hedge or safe haven