62880 research outputs found
Sort by
Unveiling the potential of digital human avatars in modern marketing strategies
Get PDFPurpose: To develop a theoretical framework that marketing practitioners and scholars can adopt to enhance their understanding of how firms can effectively deploy and use digital human avatars as part of their global digital marketing strategy. By doing so, we inform investors of ongoing digital transformations of marketing practices that will equip marketeers to provide scalable, tailored, reliable, and relevant digital self-service interactions to users, consequently improving the user/customer experience.
Design/methodology/approach: Thematic analysis was used to discover factors to enable the successful implementation of digital human avatars, drawing on in-depth interviews with fourteen executives of digital human avatars developer companies worldwide and analysis of ten podcasts and webinars with artificial intelligence (AI) experts.
Findings: Digital human avatars revitalise the international dynamic marketing capabilities (IDMCs) of firms by integrating advanced technologies that transform user interactions, improve engagement, and facilitate knowledge acquisition, dissemination and usage across various sectors and business units globally. This integration promotes a dynamic approach to international brands, customer relationships, and marketing knowledge management capabilities, offering profound value to users and firms.
Originality/value: The novelty of our study lies in exploring the characteristics of technologies and practical factors that maximize the successful adoption of digital human avatars. We advance and contribute to the emerging theory of avatar marketing, (IDMCs), and absorptive capacity by demonstrating how digital human avatars could be adopted as part of a firm’s global digital marketing strategy. We focus specifically on six dimensions: outcomes and benefits; enhancements and capabilities; applications and domains; future implications; foundational elements; and challenges and considerations. This framework has direct implications for innovators and marketing practitioners who aim to adopt digital human avatars in their marketing practices to enhance the effectiveness of international marketing strategies
Depth constancy and the absolute vergence anomaly
Get PDFBinocular disparity provides information about the depth structure of objects and surfaces in
our environment. Since disparity depends on the distance to objects as well as the depth
separation of points, information about distance is required to estimate depth from disparity.
Our perception of size and shape is biased, such that far objects appear too small and
flattened in depth, and near objects too big and stretched in depth. The current study
assessed the extent to which the failure of depth constancy can be accounted for by the
uncertainty of distance information provided by vergence. We measured individual
differences in vergence noise using a nonius line task, and the degree of depth constancy
using a task in which observers judged the magnitude of a depth interval relative to the
vertical distance between two targets in the image plane. We found no correlation between
the two measures, and show that depth constancy was much poorer than would be expected
from vergence noise measured in this way. This limited ability to take account of vergence in
the perception of depth is, however, consistent with our poor sensitivity to absolute disparity
differences. This absolute disparity anomaly thus also applies to our poor ability to make use
of vergence information for absolute distance judgements
QoE-based assignment of EVs to charging stations in metropolitan environments
Get PDFWith the recent advances in battery technology enabling fast charging, public Charging Stations (CSs) are becoming a viable choice for Electric Vehicles (EVs). However, the distribution of EVs relies on strategic assignment of EVs to CSs. EVs drivers’ Quality of Experience (QoE) is an significant impact factor that should be considered to find the optimal assignment of EVs to CSs. In this context, a novel framework to find the optimal assignment of EVs to CSs has been proposed based on optimization of QoE. Our proposed approach considers the travel time of EVs towards CSs taking into account the distance between EVs and CSs, the impact of congestion level on the roads resulted from the Internal Combustion Engine Vehicles (ICEVs) and EVs, queuing time at the CSs, and the time required to fully charge the EVs battery when connected to any charging slot at a CSs. The adjacency between the different zones in a city environment is also considered in order to minimize the potential number of CSs for each EVs. Specifically, the assignment problem is formulated as Mixed Integer Nonlinear Programming (MINLP), and a heuristic solution is developed using the Genetic Algorithm (GA) technique. The performance evaluation in realistic metropolitan environment attests the benefits of the proposed CSs assignment framework considering range of charging metrics
In‐group versus out‐group preferences in intergroup conflict: an experiment
Get PDFIn group conflicts, individuals often have diverse preferences, such as maximizing personal payoff, maximizing the group's payoff, or defeating rivals. When these preferences coexist, isolating their impact on conflict outcomes becomes challenging. To disentangle in‐group and out‐group preferences, we conduct a group contest experiment in which human in‐group or out‐group players are replaced with historical subjects to maintain strategic similarity. Our study aims to explore (i) the variation in effort in group conflicts due to in‐group and out‐group preferences and group cohesion, and (ii) how the impact of these preferences changes when the two groups have explicitly different categorical identities. Surprisingly, our results indicate an absence of overall treatment effects on effort levels. However, the presence of in‐groups has heightened concerns about individual payoffs. When out‐groups are introduced, these concerns are moderated by an additional focus on the group's payoffs. The negative effect of the in‐group preferences and the positive effect of the out‐group preferences are weaker when group members have a common categorical identity
Climate risk and capital resilience in EU deposit‐taking financial institutions: insights into environmental and cultural dynamics
No full textThis study investigates capital resilience in relevance to the European deposit‐taking financial institutions in response to climate shocks, using the Dynamic Capabilities Theory as the conceptual framework. Employing a panel dataset, spanning the period 2012 to 2021, the analysis documents that climate risk negatively influences the capital position of EU financial institutions, with a more pronounced adverse effect observed on core capital. We integrate cultural dimensions, along with environmental drivers, as moderating variables to provide fresh and comprehensive perspectives on these dynamic ties. While the moderating role of environmental tax exhibits a marginally positive influence, mitigating the adverse impact of climate risk on capital positions, the synergistic effect of per capita greenhouse gas (GHG) emissions weakens the baseline association. National cultural dimensions reveal heterogeneous moderating influences on the relationship between climate risk and capital resilience across EU financial institutions. Given Europe's accelerated warming, which is occurring at twice the global average, this study emphasizes the importance of firms' dynamic capabilities to sense, seize, and transform in response to external shocks, particularly in relation to regulatory capital adequacy, offering both theoretical and managerial insights
Objecting: Sculpture as Counter Evidence
No full textThis research examines how data representations of social, economic, and political
realities sustain systemic power imbalances in today’s contested politics of space and
explores how socially engaged sculptural art practice can challenge representational
norms to support resistance. While the political influence of supposedly objective data
representations used in social housing resident consultations is well-documented,
alternative forms of visualization that contest spatial injustices remain underexplored in
socially engaged art.
The thesis investigates the transformative potential for sculptural art practice in
this area through three core strands of research: 1) evaluating existing artistic protest
and data representation methods; 2) analysing current data practices in resident
consultations; and 3) developing and testing alternative, sculptural data representations
during a resident-led campaign against the demolition of St. Raphael’s social housing
estate in NW London between 2019 and 2022 as a case study.
The research highlights how socially engaged art practice is instrumentalised in
public consultation processes, emphasising the need for an approach to art making that
resists expectations of usefulness. An examination of the origins of the notion of
objectivity in data representations and a study of their role in the case study consultation
process reveal their aesthetic as a political strategy aimed at producing consensus. An
analysis of counter evidence from the fields of art and visual advocacy highlights the need
for a sculptural art practice to represent abstract data in tangible and intuitively
accessible ways. Drawing on Benjamin, Mouffe and Rancière’s interpretations of art’s
power to question and transform naturalised conventions of representation and to foster
critical engagement, the thesis advocates for sculptural data representations to serve
both discursive as well as confrontational functions.
The observations from using sculptural data representations in the case study
demonstrates that they offer new possibilities for challenging injustices in political
decision-making and reaffirming socially engaged art’s capacity for critical agency
With or without you: career capital development as experienced by MBA alumni
Get PDFThis paper focuses on understanding the qualitatively different experiences of career development reported by MBA alumni of a UK business school. Although the potential of the MBA to support career capital development has been previously identified, a thorough investigation into how this is experienced has been lacking. The study contributes to career capital theory in the context of post-experience management education in three ways. Firstly, our findings report the development of career capitals, and we describe how these are manifested within the context of an MBA. Secondly, we identify five different experiences of career capital development, to which we ascribe the following labels: applying; achieving; collaborating; believing; and transforming. These five different experiences contribute to theory by revealing the interrelationships and interdependencies between different forms of capital. Finally, we highlight that whilst it is possible to develop certain forms of career capital either with or without others, this is not the case for those involving personal transformation, which cannot be achieved alone. The paper concludes with reflections on the implication of our findings for management educators, MBA teachers, and researchers
Presence and impact of aldol condensation products as off-notes in plant-based protein sources
Get PDFOff-notes in plant-based sources of protein are mainly formed via the lipid oxidation of unsaturated fatty acids. During gas chromatography–olfactometry analysis of pea protein isolate, previously uncharacterized old soap odors were detected. These were found to arise from a family of α,β-unsaturated aldehydes formed from the aldol condensation of pentanal and hexanal during the protein extraction process. These compounds were synthesized, and it was confirmed that they are highly odor-active and contribute to the old soap odor in pea protein isolates at very low concentrations. Comparison with rice, soy, and hemp protein isolates showed that they all contained at least one such aldol condensate, whereas they were not detected in whey protein. We suggest that the main factor determining the formation of these compounds is the manufacturing process used to isolate and dry the pea protein biomass
Generative adversarial network based on self-attention mechanism for automatic page layout generation
Get PDFAutomatic page layout generation is a challenging and promising research task, which improves the design efficiency and quality of various documents, web pages, etc. However, the current generation of layouts that are both reasonable and aesthetically pleasing still faces many difficulties, such as the shortcomings of existing methods in terms of structural rationality, element alignment, text and image relationship processing, and insufficient consideration of element details and mutual influence within the page. To address these issues, this article proposes a Transformer-based Generative Adversarial Network (TGAN). Generative Adversarial Networks (GANs) innovatively introduce the self-attention mechanism into the network, enabling the model to focus more on key local information that affects page layout. By introducing conditional variables in the generator and discriminator, more accurate sample generation and discrimination can be achieved. The experimental results show that the TGAN outperforms other methods in both subjective and objective ratings when generating page layouts. The generated layouts perform better in element alignment, avoiding overlap, and exhibit higher layout quality and stability, providing a more effective solution for automatic page layout generation
PASCOINFOG/PASFOG: privacy-preserving data deduplication algorithms for fog storage systems
Get PDFThe forthcoming Fog storage system should provide end users with secured and faster
access to cloud services and minimise storage capacity using data deduplication. This method stores
a single copy of data and provides a link to the cloud/fog owners. In client-side data deduplication,
the system can reduce network bandwidth levels by duplicate check. This solution fails to cover user
privacy and optimise the latency of real-time communications.
Motivated by this, this magazine paper develops PrivAcy-preServing data deduplication in Fog
stOraGe system (PASFOG) as a data deduplication protocol implemented between cloud storage and
users to mitigate brute-force and poison attacks. PASFOG is implemented in fog computing to reduce
real-time delay and communication when performing duplicate checks. Also, we propose PrivAcypreServing data dedupliCatiOn in blockchaIN-based Fog stOraGe system (PASCOINFOG) utilised
blockchain techniques to realise a reliable system. In PASCOINFOG, when users want to send chunks
to the cloud/fog nodes, process the duplicate check and create a new block for the blockchain to
reduce real-time latency/communication and protect the cloud from attackers. The proposed protocols
can enhance user privacy and reduce real-time communication delay, crucial for consumer electronics
applications such as cloud storage and IoT devices