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This paper aims to unveil the darker side of cryptocurrencies by delving into its role as an obstacle to investments in Middle East and African (MEAs) countries, unravelling the challenges involved. Indeed, despite the rise of blockchain-related technologies, specifically cryptocurrencies, having undeniably unlocked new avenues for business and society, crypto for venture funding purposes may exhibit a “dark side” due to their use for unethical purposes, for example, money laundering or terrorism financing, largely diffused in certain areas of MEA countries.

Through an explorative research design, using a mix of techniques based on both qualitative and interpretive methods, we conducted in-depth interviews among 33 European managers of companies engaged in MEA markets or aspiring to invest in such foreign markets, to analyse their thoughts, perceptions and possible strategies concerning the management of the “dark side” of cryptocurrencies in MEAs.

Our investigation unearthed seven pivotal issues, which manifest as significant barriers related to the ambivalent use of crypto for funding projects, encompassing seven important consequential elements: (1) lack of knowledge about the technology’s potentialities; (2) perceptions of crypto technology’s ambivalence; (3) reputation and image consequences; (4) uncertainty about the destination of the invested funds; (5) decreased attractiveness of MEAs; (6) competition and market; and (7) lack of control and regulation. We grouped these into technology-related, business-related and legal- and policy-related barriers. Such findings underline the probable decrease in attractiveness of MEAs in terms of investments, together with the triggering factors and potential strategic solutions to mitigate such circumstances.

Future studies could explore a broader sample of managers since we only considered the perception of European managers operating in companies that invest (or are intending to invest) in MEAs. Moreover, future research may extend the analysis to MEA-native companies or those engaging in reciprocal exchanges with Western countries.

Practically, our findings suggest several elements in which to intervene to mitigate managers’ negative perception of the unethical use of cryptocurrencies in MEAs and to support CEOs’ and CFOs’ strategies, together with requirements to ensure the unaltered attractiveness of investments in an otherwise thriving region of the world, without overlooking the protection and safeguarding of investments and the health of the market and competition. Furthermore, a call for future research in this domain, along with at least minimal regulatory mechanisms, clearly emerges.

Our findings underline the social challenges associated with the perception and acceptance of cryptocurrencies in these contexts, influencing cultural and social dynamics. Moreover, the identification of these barriers could underscore the significance of awareness of and education on blockchain technology and cryptocurrencies within society, including implications for policymakers.

Despite prior investigations into the negative effects of cryptocurrencies as a form of venture funding, no studies to date have examined managers’ perceptions by focusing on possible barriers to investment in MEA countries due to the unethical usage of crypto. Importantly, this paper unravels the unexplored complexities of crypto’s impact on ethical investments in MEAs, showcasing an original perspective.

High-nitrogen steel is a common material for the manufacture of drilling equipment such as drill collars. However, its poor surface properties often limit its applications. The purpose of this paper is to find a way to enhance the surface performance of high-nitrogen steel, which is expected to improve the wear resistance of high-nitrogen steel.

The CoCrNi and CoCrFeNi medium-entropy alloy (MEA) coatings were prepared on high-nitrogen steel substrate by laser cladding technology. The microstructure, phase composition and element distribution of the fabricated coatings were investigated using scanning electronic microscopy, electron backscatter diffraction and X-ray diffraction. The phase structure, phase stability and structural stability of the CoCrNi and CoCrFeNi MEAs were investigated in combination with phase diagram calculation and molecular dynamics. Then the wear tests were carried out for coatings.

The results show that both prepared MEA coatings have good quality and contain a single face-centered cubic phase. The wear performance of MEA coatings is improved by the refinement of grain size and the increase of dislocation density. Due to the addition of Fe atoms, the lattice distortion of the CoCrFeNi system increased, resulting in a higher dislocation density of the coating. Cr atoms in the CoCrFeNi system are the largest, and the local lattice distortions induced by them are greater. Through this study, MEA coatings with high hardness can be expanded to drilling field applications.

CoCrFeNi and CoCrNi MEA coatings were successfully prepared on the surface of high-nitrogen steel for the first time without obvious defects. The micromorphology and grain orientation of the different kinds of coatings were discussed in detail. The hardness-strengthening mechanism and structure stability of the coatings were illustrated by experiments and molecular dynamics simulations.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0116/

Performing accurate numerical simulations of electrical drives, the precise knowledge of the local magnetic material properties is of utmost importance. Due to the various manufacturing steps, e.g. heat treatment or cutting techniques, the magnetic material properties can strongly vary locally, and the assumption of homogenized global material parameters is no longer feasible. This paper aims to present the general methodology and two different solution strategies for determining the local magnetic material properties using reference and simulation data.

The general methodology combines methods based on measurement, numerical simulation and solving an inverse problem. Therefore, a sensor-actuator system is used to characterize electrical steel sheets locally. Based on the measurement data and results from the finite element simulation, the inverse problem is solved with two different solution strategies. The first one is a quasi Newton method (QNM) using Broyden's update formula to approximate the Jacobian and the second is an adjoint method. For comparison of both methods regarding convergence and efficiency, an artificial example with a linear material model is considered.

The QNM and the adjoint method show similar convergence behavior for two different cutting-edge effects. Furthermore, considering a priori information improved the convergence rate. However, no impact on the stability and the remaining error is observed.

The presented methodology enables a fast and simple determination of the local magnetic material properties of electrical steel sheets without the need for a large number of samples or special preparation procedures.

This study aims to identify the reasons for unmet health-care needs and related barriers among the Roma population with chronic diseases in Jordan.

A descriptive survey with a cross-sectional design was conducted, involving a sample of 347 Jordanian Roma participants. Data collection was performed using a structured questionnaire based on the Canadian Community Health Survey.

The analysis revealed that within the three categories of reasons for unmet health-care needs (accessibility, availability and acceptability), “Transportation issues” under the accessibility category constitute the most reported reasons: (mean = 90.4%, SD = 22.6%), followed by “Cost” (mean = 89.0%, SD = 26.2%) and “Care not available in the area” (mean = 85.8%, SD = 23.6%). Predictors of unmet health-care needs were being married, having health insurance and self-perception of mental health (OR = 0.215, p = 0.044), (OR = 0.391, p = 0.008) and (OR = 0.302, p = 0.002) respectively.

Unmet health-care needs are highly prevalent among Jordanian Roma, rendering them a vulnerable group susceptible to other diseases. To address this pressing issue, concerted and comprehensive efforts should be made to improve the utilization and accessibility of health-care services within this community. Furthermore, efforts should be made to elevate their social standing and status. facilitate their integration into the broader community.

The purpose of this study was to ascertain the relationship between EFL teachers' perception of the intended and unintended consequences of formative assessment (FA) decisions and their sense of self-efficacy and anxiety toward data-driven decision-making (DDDM).

A correlational research design and correlational/regression analysis was utilized to conduct this study. In addition, a thematic analysis was conducted of participants' responses to the open-ended questions.

Descriptive statistics suggest that most EFL teachers perceived both intended and unintended consequential validity of their FA decisions with a moderate level of DDDM self-efficacy and a low level of anxiety. The results of the correlational analysis indicated a strong positive relationship indicating that those with higher teachers' perceptions of consequential validity of formative assessment (TPCVFA) scores tended to report higher DDDM efficacy. The results of the correlational analysis also indicated that a significant relationship did not exist between TPCVFA scores and DDDM anxiety. Finally, multiple regression analyses revealed that TPCVFA was a significant predictor of DDDM efficacy; however, TPCVFA was not a significant predictor of DDDM anxiety.

Data collected from 114 Iranian EFL teachers using the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA, Dunn et al. 2013a) and the TPCVFA questionnaire, which was self-developed and validated for the current study.

This study investigates if and how the board size, the board independence, the CEO duality and the board-specific skills are associated with higher-quality Sustainable Development Goals (SDGs) disclosure in European State-Owned Enterprises (SOEs).

We measured SDGs disclosure through a content analysis of SOE's reports from 2017 to 2022. The characteristics of the boards analyzed are board size, board independence, CEO duality and board-specific skills. We performed multiple regression models to test the association between the SDGs disclosure and the characteristics of the boards.

The results show that board size, independent directors and board-specific skills are positively associated with higher-quality SDGs disclosure, while CEO duality is negatively associated with higher-quality SDGs disclosure.

This study provides several practical implications. Shareholders could equip their firms with larger boards, more independent and highly skilled directors, while avoiding a CEO duality for improving the SDGs disclosure; capital providers could examine the characteristics of a firm's board before allocating financial resources to verify which firms are accountable in reaching the SDGs. Also, standard-setters and policymakers could use the results of this research to define new standards or regulatory pathways to push firms to put more efforts in preparing a comprehensive and high-quality SDGs disclosure.

While prior studies mostly focused on sustainability reporting overall, this study adds a specific insight about SDGs disclosure employing an investigation which has not been previously analyzed.

This study aims investigate in-service teachers’ perspectives on the integration of ChatGPT, an artificial intelligence (AI)-driven chatbot, into United Arab Emirates (UAE) private schools. As the UAE progresses towards a knowledge-based economy, aligning with the goals of the UAE 2030 vision, this research assesses the capacity of ChatGPT to enhance the educational experience within the framework of technological pedagogical content knowledge.

A mixed-methods approach is used, combining a survey assessing teachers’ attitudes and a thematic analysis of open-ended responses, to explore the effectiveness, challenges and pedagogical implications of ChatGPT’s use in the classroom.

Findings reveal that teachers value ChatGPT for its potential to individualize learning and streamline the creation of educational materials, aligning with the shift towards student-centred approaches and the demands of 21st-century skills. However, significant challenges are noted, including ethical concerns, the need for reliable content and a necessity for extensive professional development to fully realize ChatGPT’s benefits.

While ChatGPT transforms teaching and learning practices, realizing this potential requires addressing critical issues through adaptive policy-making, continuous educator training and thoughtful integration into the curriculum.

The study highlights the importance of a collaborative approach to dealing with the details of AI in education, ensuring that advancements like ChatGPT align with the evolving educational paradigms of the UAE.

Sacred forests are biocultural landscapes deeply rooted in centuries-old traditions of spiritual veneration. These sacred sites, including shrines, temple forests churches and graveyards, have historically been significant reservoirs of traditional resource management practices underpinned by spiritual reverence. However, despite their cultural and ecological importance, the cultural ecosystem services inherent to these sacred forests remain unexplored, particularly in urban settings.

This study focused on six sacred sites within Kanazawa City, Japan, using a meticulous face-to-face survey with 342 participants. We collected data on the extent of forest utilisation, the breadth of activities engaged in by visitors and their holistic appraisal of the rendered cultural ecosystem services. The findings illustrate the multifaceted benefits of urban sacred forests, encompassing participation in religious ceremonies, cultural events and festivals, complemented by educational programming that elucidates the historical and traditional underpinnings of the shrines and their surrounding communities.

It has been observed that urban forests have a crucial role in providing spiritual and communal connectivity, preserving traditional heritage, offering vital aesthetic values as green spaces and making visitors connected with nature while they are in the urban landscape. However, a concerning trend has emerged, as the younger demographic appears to lack interest in participating in the stewardship and cultural activities associated with these biocultural landscapes. Community engagement strategies must be strengthened, conservation measures should be implemented and cultural awareness programs need to be established to ensure the perpetuation and appreciation of these valuable urban sacred forests.

This study provides original perspectives on the measurable cultural ecosystem services and intangible values associated with urban sacred forests using the sacred forests in Kanazawa City, Japan. Our research illuminates the various advantages that visitors derive by examining the intersection of spiritual traditions, resource management practices and cultural significance, which has been relatively unexplored. The present study provides a significant basis for establishing initiatives that seek to promote the cultivation of respect and responsibility towards urban sacred forests.

Drawing on the dynamic capability view, this study aims to examine the relationships between big data analytics capability (BDAC) and sustainable supply chain performance (SSCP) by exploring the mediating effects of knowledge development (KD) in terms of knowledge acquisition, information distribution, shared meaning and achieved memory.

Data were collected by questionnaire survey from 300 manufacturing organizations. Structural equation modeling was used to test the research hypotheses.

It was found that all the dimensions of KD were positively related to BDAC and SSCP. Although no direct association was established between BDAC and SSCP, the empirical findings indicated that all the dimensions of KD fully mediated the relationship between BDAC and SSCP. This highlights that organizations need to harness KD because developing BDAC alone may not be sufficient.

No previous research has explored how KD dimensions such as knowledge acquisition, information distribution, shared meaning and achieved memory mediate the relationship between BDAC and SSCP. This paper addresses this gap in the literature and contributes to the existing debate to better understand the conditions in which BDAC affects SSCP. Pointers for future research are also identified.

This study aims to evaluate the usability of Google Drive (GD) in addition to measuring the effectiveness of GD and the challenges faced while using this cloud storage application among public library users of Lahore.

The study adopted a sequential explanatory mixed method design comprising the quantitative (QUAN) and qualitative (QUAL) parts. For the QUAN phase, a questionnaire survey was conducted among 384 users of public libraries through purposive sampling. For the QUAL phase, the think aloud technique was performed on several tasks during experiments and verbalized their thoughts and experiences while interacting with the system. The cloud usability model (CUM) was used to measure the “usability” of GD.

Findings indicated that most users were satisfied with GD's obvious features and inherent functions. QUAL results indicated that respondents did most tasks easily, whereas only some could complete the task.

The study is valuable as it is the first time used CUM to measure the perceived usability of GD. Second, the study used a mixed method study to get insights into perceived usability, effectiveness and challenges while using GD. The findings might be helpful for cloud support teams, including GD, as they can enhance certain features of usability, which lead to increased usage among users.

This research work is based on MPhil thesis.