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Science and religion around the world: Compatibility between belief systems predicts increased wellbeing
Get PDFPrevious research, conducted mainly in Western societies, indicates that religious/spiritual (R/S) and pro-science belief systems each relate positively to believer well-being, but are perceived as being highly incompatible with each other. This perception would presumably undermine one's ability to benefit fully from both systems, leading to the research questions examined here: does the perceived incompatibility between religion and science vary cross-culturally, and is this level of incompatibility itself related to group member well-being? Our data set included 55,230 participants from 54 countries, organized for analytical purposes into 13 global regions and 11 belief groups. We found that perceived incompatibility between R/S and pro-science beliefs was indeed characteristic of the West but was not the norm cross-culturally. We also found that higher levels of belief system compatibility related positively to well-being, and especially to the strength of positive associations between well-being and each type of belief system. That is, in regions and belief groups that perceived higher compatibility, well-being's positive relationships with R/S and pro-science beliefs were both also higher. We speculate about compatibility's potential causal effects on these relationships, noting that as compatibility increases, so does the possibility of benefiting from one system without forgoing the benefits of the other.The Issachar Fund and the Templeton Religion Trust [grant number TRT0207]
Outbound Profit Shifting and the Propensity to Engage in Cross‐Border Acquisitions
Get PDFAccountability-avoiding foreign direct investment (FDI) is a category of financial motives explaining where firms invest and how, yet our grasp of this phenomenon is incomplete. In contrast with tax-haven FDI, where multinational enterprises (MNEs) invest in a host country to pursue inbound profit shifting, we consider a novel motive – FDI attracted by low host country financial transparency that enables outbound profit shifting (OPS). Cross-border acquisitions (CBAs) are a takeover route to achieving OPS and global tax optimization. Our empirical context is 39,951 CBAs by 315 acquirers from 26 countries in the 1996–2015 period. We hypothesize and empirically show a positive relationship between OPS and CBAs and the probability that equity ownership of CBAs will be high. We find that the relationship between OPS and CBAs is stronger the more attractive or income unequal the host market, or when the multinational's industry is vertically or horizontally integrated. We attribute the lack of support for our hypothesis that MNEs require in-house capability to conduct OPS to tax planning consultancies’ services. These findings highlight the role of low financial transparency as a novel locational determinant of OPS-pursuing FDI and emphasize the distinction between inbound and outbound profit shifting as manifestations of accountability-avoiding FDI
Farmers’ perceived effect of the COVID-19 pandemic and its relationship to preparedness and risk perception
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The authors do not have permission to share data.The impact of the COVID-19 pandemic across the agri-food sector was significant and pervasive, challenging farmers' resilience through multiple disruptions to the supply chain. To support forward planning in face to future shocks, this research examines the perceived impacts of the COVID-19 pandemic by farmers themselves, providing insights from the UK. Using a nation-wide online survey carried out during two distinct waves of the pandemic in 2021, the study reveals changing perceptions and the relationship between preparedness and perceived impacts. Results indicate that perceptions of both the severity of the COVID-19 impacts and preparedness for such impacts in the future, were scaled down as the pandemic evolved. Findings suggest that a farmer feeling more prepared in the present to withstand shocks is positively influenced by them perceiving the impact of COVID-19's in their business as severe. This effect is reinforced for farmers that felt more prepared to withstand COVID-19's impacts when the pandemic unfolded, as well as for those that perceive the impact of COVID-19 as long-term. Farmers in our sample appear to have adapted to the shocks to their businesses through supply-side interventions, focusing on having higher flexibility in delivery of products and diversifying their supply networks. Doing so requires them to absorb an increase in both fixed and variable costs, which can end-up been transferred to the consumer. Government support moving forward should focus on strengthening and, perhaps, re-imagining the whole supply industry and re-defining the role of farmers as more than food producers, but also as stewards of climate and food resilience.RePhoKUs project, funded by the Global Food Security's ‘Resilience of the UK Food System Programme’ with the UK's Biotechnology and Biological Science Research Council (BBSRC), the Economic and Social Research Council (ESRC), the Natural Environment Research Council (NERC) and the Scottish Government (Grant No. BB/R005842/1); as well as the CONSOLE project, funded by the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 817949)
Intelligent Immersion: The current landscape of AI tools in the Mixed Reality development pipeline for creative experiences
Get PDFAmong the technologies that hold immense potential to revolutionize how we interact with information and digital content, Mixed Reality (MR) offers unique immersive experiences that seamlessly integrate virtual objects into the user's physical environment. This groundbreaking fusion of the physical and digital worlds has a complex development process which is a fertile ground for applications of Artificial Intelligence (AI). This article aims to provide a comprehensive overview of AI tools and their applications, in all stages of the development of MR experiences for the creative sector. It also discusses the challenges and opportunities of incorporating them in the development pipeline and offer some use guidelines as a compass to navigate this rapidly changing landscape.Arts and Humanities Research Council (UK, AH/W005530/1) and National Endowment For the Humanities (US, HND-284975-22
Joint MIMO Transceiver and Reflector Design for Reconfigurable Intelligent Surface-Assisted Communication
Get PDFA preprint version of this article is available at: arXiv:2405.17329v1 [cs.IT], https://arxiv.org/abs/2405.17329 . It may not have been certified by peer review. Please consult the peer reviewed version published by IEEE at https://doi.org/10.1109/TVT.2024.3406199 .In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output communication system with multiple antennas at both the base station (BS) and the user. We plan to maximize the achievable rate through jointly optimizing the transmit precoding matrix, the receive combining matrix, and the RIS reflection matrix under the constraints of the transmit power at the BS and the unit-modulus reflection at the RIS. Regarding the non-trivial problem form, we initially reformulate it into an considerable problem to make it tractable by utilizing the relationship between the achievable rate and the weighted minimum mean squared error. Next, the transmit precoding matrix, the receive combining matrix, and the RIS reflection matrix are alternately optimized. In particular, the optimal transmit precoding matrix and receive combining matrix are obtained in closed forms. Furthermore, a pair of computationally efficient methods are proposed for the RIS reflection matrix, namely the semi-definite relaxation (SDR) method and the successive closed form (SCF) method. We theoretically prove that both methods are ensured to converge, and the SCF-based algorithm is able to converges to a Karush-Kuhn-Tucker point of the problem
Time-varying parameters in monetary policy rules: a GMM approach
Get PDFThe supplementary material for this article can be found online at: https://www.emerald.com/insight/content/doi/10.1108/JES-06-2023-0289/full/html#supplementary-tab .JEL Classification: C14; C52; E52; E58Purpose:
The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.
Design/methodology/approach:
This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.
Findings:
Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.
Originality/value:
It provides new evidence on changes over time in monetary policy rules
Democratic Deficit and Underdevelopment in Nigeria: A Qualitative Study of the 2023 Presidential Elections
Get PDFDiscontentment with democracy in West Africa centres on abuse of power and political corruption. In Nigeria, dissatisfaction lies not just with these but also with insecurity, economic recession and the electoral process – a system fraught with complications, controversies and contradictions. Using the political economy of elections as its theoretical framework together with mixed research methods, this paper interrogates the relationship between Nigeria’s democratic culture and the 2023 presidential elections. Here I present a politicised electoral management institution, the Independent National Electoral Commission (INEC). Its performance is shaped, not by legislative instruments and constitutional guidelines, but by a dysfunctional democratic culture that reflects the extent to which ethnicised politics, class, institutionalised loyalty and money politics determine election results and Nigeria’s version of democracy. Although fragile and prebendal, democracy continues to consolidate amidst delayed development. The paper recommends increased media advocacy for reform
Evaluation of Pothole Detection Performance Using Deep Learning Models Under Low-Light Conditions
Get PDFData Availability Statement:
The data supporting the findings of this study are derived from publicly available datasets. Specifically, the dataset utilized in this research was compiled based on data from the following sources: The “Pothole detection Computer Vision Project” dataset supporting the findings of this study is openly available at https://universe.roboflow.com/arthana-p-n/pothole-detection-th8es/ (accessed on 1 September 2024) [34]. The “Potholes YOLO-NAS” dataset supporting the findings of this study is openly available at https://www.kaggle.com/code/stpeteishii/potholes-yolo-nas-train-predict (accessed on 1 September 2024) [35]. The “Pothole Dataset” provided by Roboflow supporting the findings of this study is openly available at https://public.roboflow.com/object-detection/pothole/1 (accessed on 1 September 2024) [36]. The “Pothole-detection” project by Jay on GitHub supporting the findings of this study is openly available at https://github.com/jaygala24/pothole-detection (accessed on 1 September 2024) [37]. Additionally, our primary dataset was created based on these public resources and further detailed in the “Pothole Detection Computer Vision Project” hosted on Roboflow Universe, available at https://universe.roboflow.com/lviv-polytehnic-national-university/potholedetection-0coqc (accessed on 1 September 2024) [38]. No new data were created as part of this study beyond the compilation and adjustment of these existing datasets. Due to the nature of this research, all datasets utilized are publicly available and accessible through the provided links. For further information on the data and resources used in this study, readers are encouraged to refer to the sources listed above.In our interconnected society, prioritizing the resilience and sustainability of road infrastructure has never been more critical, especially in light of growing environmental and climatic challenges. By harnessing data from various sources, we can proactively enhance our ability to detect road damage. This approach will enable us to make well-informed decisions for timely maintenance and implement effective mitigation strategies, ultimately leading to safer and more durable road systems. This paper presents a new method for detecting road potholes during low-light conditions, particularly at night when influenced by street and traffic lighting. We examined and assessed various advanced machine learning and computer vision models, placing a strong emphasis on deep learning algorithms such as YOLO, as well as the combination of Grad-CAM++ with feature pyramid networks for feature extraction. Our approach utilized innovative data augmentation techniques, which enhanced the diversity and robustness of the training dataset, ultimately leading to significant improvements in model performance. The study results reveal that the proposed YOLOv11+FPN+Grad-CAM model achieved a mean average precision (mAP) score of 0.72 for the 50–95 IoU thresholds, outperforming other tested models, including YOLOv8 Medium with a score of 0.611. The proposed model also demonstrated notable improvements in key metrics, with mAP50 and mAP75 values of 0.88 and 0.791, reflecting enhancements of 1.5% and 5.7%, respectively, compared to YOLOv11. These results highlight the model’s superior performance in detecting potholes under low-light conditions. By leveraging a specialized dataset for nighttime scenarios, the approach offers significant advancements in hazard detection, paving the way for more effective and timely driver alerts and ultimately contributing to improved road safety. This paper makes several key contributions, including implementing advanced data augmentation methods and a thorough comparative analysis of various YOLO-based models. Future plans involve developing a real-time driver warning application, introducing enhanced evaluation metrics, and demonstrating the model’s adaptability in diverse environmental conditions, such as snow and rain. The contributions significantly advance the field of road maintenance and safety by offering a robust and scalable solution for pothole detection, particularly in developing countries.The fourth author would like to acknowledge the financial support from the British Academy for this research (RaR\100727)
Past, present and future of AI in marketing and knowledge management
Get PDFPurpose:
This paper aims to explore the intersection of artificial intelligence (AI) and marketing within the context of knowledge management (KM). It investigates how AI technologies facilitate data-driven decision-making, enhance business communication, improve customer personalization, optimize marketing campaigns and boost overall marketing effectiveness.
Design/methodology/approach:
This study uses a quantitative and systematic approach, integrating citation analysis, text mining and co-citation analysis to examine foundational research areas and the evolution of AI in marketing. This comprehensive analysis addresses the current gap in empirical investigations of AI’s influence on marketing and its future developments.
Findings:
This study identifies three main perspectives that have shaped the foundation of AI in marketing: proxy, tool and ensemble views. It develops a managerially relevant conceptual framework that outlines future research directions and expands the boundaries of AI and marketing literature within the KM landscape.
Originality/value:
This research proposes a conceptual model that integrates AI and marketing within the KM context, offering new research trajectories. This study provides a holistic view of how AI can enhance knowledge sharing, strategic planning and decision-making in marketing
Noise Sources of Closely Installed Subsonic Jets
Get PDFEmitted noise of an installed jet is significantly louder, compared to an isolated jet. When the jet is installed closely under a solid surface, nonlinear jet-surface interactions occur and modify the jet turbulence in addition to the linear potential field interactions. In this paper, the noise sources are decomposed into quadrupole sources due to turbulent mixing and dipole sources due to the unsteady loadings on the surface. The change of the two sources due to the close installation is first characterised in the near-field and their contribution to the far-field noise is then quantified. The quadrupole source and noise are examined using Goldstein’s acoustic analogy, while the dipole noise is studied with the Amiet approach to model trailing edge scattering of evanescent hydrodynamic waves. The methods are first validated in a plate-jet configuration and then applied to analyze the noise sources of a closely installed jet-wing configuration. The results show that the increased quadrupole source primarily contributes to the installation noise at the polar angle of 30 degrees, while the dipole source is responsible for the installation noise at the higher polar angles.The ARCHER computing time is provided by the UK Turbulence Consortium under EPSRC grant EP/L000261/1 and PRACE Distributed European Computing Initiative. The simulation of jet-wing configuration was performed in the EU-funded project “JERONIMO” (ACP2-GA-2012-314692-JERONIMO). The authors would like to thank Drs Jack Lawerence and Anderson Proneca for providing the experimental measurement to validate the simulation of jet-plate configuration
Data sources:
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