2821 research outputs found
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Exploring the influence of information sharing on cybersecurity via social media platforms
Full text linkThe internet has revolutionized the way people communicate, access data, and engage with one another, and has led to online information sharing on social media platforms which has a huge impact on our society. Over the years, there have been numerous concerns about the impact that sharing of information has on user, data and information security. This research work investigates user’s perception of security in terms of information sharing on various social media platforms. A quantitative analysis was carried out amongst the post-graduate students of Glasgow Caledonian University, Glasgow. Data was collected using a questionnaire with eight (8) sections, which was administered online to capture information about users’ behaviours related to their information sharing, perception of the sensitivity of data they share, control over privacy settings, and their trust level in social media platforms. Findings from this research has shown that Postgraduate students of Glasgow Caledonian University exchange all sort of personal and general information over social media platforms. However, they do not perceive these platforms to be highly secured, as there are concerns emerging regarding the security and trustworthiness of these platforms. This conclusively shows there is a high level of awareness amongst these social media users regarding privacy settings and security features provided by social media platforms
AI and IoT for Proactive Disaster Management
No full textIn our rapidly evolving digital landscape, the threat of natural disasters looms large, necessitating innovative solutions for effective disaster management. Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) presents a transformative approach to addressing these challenges. However, despite the potential benefits, the field needs more comprehensive resources that explore the full extent of AI and IoT applications in disaster management.
AI and IoT for Proactive Disaster Management fills that gap by examining how AI and IoT can revolutionize disaster preparedness, response, and recovery. It offers a deep dive into AI frameworks, IoT infrastructures, and the synergy of these technologies in predicting and managing natural disasters. By showcasing cutting-edge research and practical applications, this book equips readers with the knowledge and tools to harness AI and IoT for more efficient and effective disaster management strategies.
Targeted at undergraduate and postgraduate students, academicians, research scholars, industry professionals, and technology enthusiasts, this book serves as a comprehensive guide to understanding the intersection of AI, IoT, and disaster management. It offers insights into emerging trends, ethical considerations, and best practices, making it an essential resource for anyone interested in leveraging technology to mitigate the impact of natural disasters
Leadership During a Crisis: A Focus on Leadership Development
No full textWe live in uncertain times propelled by complex systems, climate change and the use of technology which possess various threats. At times of crisis, leadership that permits quick reactions to the changing organisational environment becomes necessary. However, there has been limited studies that provide a road map of leading during a crisis. What is required of leaders during a crisis? How can you develop the required leadership expertise during such turbulent periods? What are the challenges leaders will have to combat? Through this book, these questions are answered.
It is no exaggeration therefore to claim that this book opens a new chapter as it seeks to advance discussions about how to lead during crisis. Drawing on empirical and conceptual evidence from the perspective of renowned authors in leadership research, it offers a robust and engaging overview of the field of leadership and leadership development in turbulent and dynamic environments. The chapters in the book support the personal and professional development of aspiring and experienced leaders and managers. The readers will be able to display critical awareness of current developments in both the theory and practice of leadership and leadership development and its importance in modern organisations
Fictions of maternity: reading and re-writing the mother in three narratives of the abandoned wife
No full textWhat is it to be a mother when you have been forsaken as a wife? Surprisingly, this question
is largely absent from analysis of the “abandoned” woman in both literary texts and the
cultural narratives that inform them. Taking Simone de Beauvoir’s The Woman Destroyed
(1967) as the classic account of the abandoned wife, this chapter will argue that the mother is
missing from the dominant patriarchal discourse of marriage. Too frequently critical attention
is devoted to the plight of the failed wife at the expense of any acknowledgment of her
successful mothering, an omission that attests to the invisibility of “motherwork” within the
ideological construction of motherhood as natural, normative and apolitical. Situating Patricia
Highsmith’s Edith’s Diary (1977) and Elena Ferrante’s The Days of Abandonment (2002) in
dialogue with Beauvoir’s text, this discussion will show how each text renders visible the
labour of mothering, revealing not only how the literary protagonists “read” their respective
maternal scripts but also how motherhood might be re-written once divested of patriarchal
assumptions. Significantly, each character uses writing in order to process her changed
circumstances, revealing the power of narrative to shape the material conditions of
experience
Assessing the capabilities of ChatGPT in recognising customer intent in a small training data scenario
Full text linkThis study addresses the issue of recognising customer intent when
only limited training data is available. The performance of ChatGPT was evaluated in this scenario, and it was found to be better than traditional machine learning algorithms and the Bidirectional Encoder Representations from Transformers (BERT) model,
which performed the worst in this case. While Random Forest with
PCA was objectively the best among traditional models when the
training examples were randomly selected, a qualitative evaluation
showed that ChatGPT had better generalisation ability and could
produce contextually correct outputs. Our research found that to
improve ChatGPT’s performance on small data classification tasks, it
is essential to utilise stratified sampling to select representative examples for few-shot learning. This research provides valuable insights
into using ChatGPT in customer-facing applications with limited
training data. Knowing the strengths and limitations of ChatGPT
can enhance response accuracy, customer satisfaction, and loyalt
Co-designing pilot games with citizens and policy stakeholders to increase climate action
Full text linkThis paper presents an initial report on the codesign processes between researchers and policy stakeholders in the GREAT (Games Realising Effective and Affective Transformation) project applied in the context of the climate emergency. The objective of piloting these co-design processes is to develop a methodology to support policy stakeholders in identifying and determining an urgent climate issue. We engage stakeholders in co-design of games-based activities, which can be instantiated for citizens and simultaneously be used to collect their attitudes towards climate policies. By piloting these codesign processes, we aim to support policy stakeholders in identifying an urgent climate issue they want to address. Based on this climate issue, we co-design games-based interventions which provide the opportunity for citizens to engage with policy issues, and to represent their attitudes and preferences relating to climate policies. We develop two types of game-based methods - a short quiz format embedded in a mobile game, and longer, collaborative serious games - for collecting, analyzing, and presenting data on citizens’ attitudes to policymakers for improving climate policies. In this paper, we describe the pilot studies undertaken and discuss the lessons learnt
Empowering marketing management and gaming consumer interaction through AI and citizen science
Full text linkThere has been a significant revolution seen by
AI getting incorporated into the management and customer
relations of companies. The research of the present Artificial
Intelligence (AI) Revolution that influences a variety of fields i.e.
video games are the topic of the article. AI systems such as
machine learning and data analytics can help brands
understand consumer behaviour in much greater detail; hence,
companies can better reach and interest potential consumers
through personalized marketing plans and campaigns. What is
more, this is another case of citizen science projects that can host
a large number of artisanal anglers who can together provide
data that can make the research wider-reaching. This is when
the conclusion is reached, which means, for gaming neither
marketing nor game-play is the energy source. The proposed
scheme improves the level of customer accuracy and tackles
trends timely as well as creates slight space for real-time
communication by applying neighbour-based recommendation
techniques, neural networks, and sentiment analysis. Its
supremacy over the conventional methods of statistical
significance is highlighted through the advent of predictive
analytics and dynamic pricing approaches. The advantage of
deploying natural language processing (NLP) is that it helps to
understand what the customers mean with how they write.
Measuring the key performance indicators at the end of this
approach can be called the method of adaptation and flexibility
which makes digital marketing not just refer only the success
but also turn to the happiness of customers
A critical analysis of state and on-state actor approaches to climate change interventions in Zambia
Full text linkThe study aims at critically analysing approaches of state and non-state actors to climate
change interventions in Zambia, with a view to determine climate change coordination
and propose improvements to the coordination framework or efforts. By doing so, the
study proposes solutions to traditionally identified challenges of climate change
coordination. It is argued that a robust climate change coordination model would bolster
sustainable climate change action.
Deriving from a theoretical multiplicity framework, this study employed the use of semi-structured questionnaires and interviews through purposive sampling of survey
respondents and key informants. A total of 147 respondents completed the questionnaire,
while 18 interviews were held with key informants. The use of semi-structured
questionnaires and interviews aided in triangulation. Primary data was analysed by
means of Exploratory Data Analysis (EDA), descriptive statistical analysis and thematic
analysis. Deep dive analysis and systematic reviews were utilised for the secondary data.
The study found the following: politics was a major factor at domestic level and has a
significant influence on climate change policy, as well as on the extent of inclusion of
actors and the consequent effectiveness of climate actor actions. For non-state actors
and sub-national entities, the politics is compounded by: limited incentives; failure to
access climate financing and benefits from international instruments; fragmented climate
information systems; limited technical and institutional capacities; unclear climate action
roles and responsibilities; limited decision making power; and limited participation in the
formulation process of climate change legislation, which for Zambia is currently narrow in
scope to effectively address the complexity of climate change. The study therefore
proposes a Climate Action Coordination (CAC) Model which ensures all critical elements
of climate change coordination are embraced.
This study contributes to the body of knowledge in terms of theory, practice and
assessment methodologies: Firstly, it deepens our understanding of climate action
practices prevailing in the climate change sector in Zambia and the possible reasoning behind such phenomena. Secondly, the study also gave rise to a Model that promotes
robust coordination and collaboration of climate change actors. The expectation is that
the operationalisation of the proposed interventions outlined in the CAC Model would
improve effectiveness of climate change interventions. In addition to the Model, the study
also highlights policy measures in the areas of climate financing, legislation, policy,
information systems, capacity building and institutional arrangements, among others.
Thirdly, the research processes and tools employed in undertaking this study provide a
valuable approach for similar assessments, evaluations, reviews, studies or research
projects. This study therefore contributes practical and tested methods and processes for
climate action and climate actor institutional assessments
Introduction to leadership during a crisis
No full textWe live in uncertain times propelled by complex systems, climate change and the use of technology which possess various threats. Leaders are put to test, and people continue to look up to their leaders for solutions. Under this deep uncertainty conditions, timely, legitimate and effective response is expected from leaders.
Leadership during crisis is a distinct area from daily leadership activities. At times of crisis, leadership that permits quick reactions to the changing business environment becomes necessary. Leaders provide a series of actions to effect immediate change in peoples’ attitudes, beliefs, behaviour and in accomplishing a set outcome. They are expected to rapidly recognise the impending danger and put in place the required procedures and infrastructure to manage the crisis. However, there have been limited studies that provide a road map of leading during a crisis. What is required of leaders during a crisis? How can you develop the required leadership expertise during such turbulent periods? What are the challenges leaders will have to combat? Through this book, these questions will be answered
Big Data innovation and implementation in projects teams: towards a SEM approach to conflict prevention
Full text linkPurpose: Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.
Design/methodology/ Approach: This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship, and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.
Findings: Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by Power-Conflict prevention, prevention of relationship disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflict interact on the one hand, while Task and relationship conflict prevention on the other hand, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.
Research Limitations: The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.
Practical Implications: The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. We urge organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.
Social Implications: The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.
Originality/Value: The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power, process, relationship & task conflicts; to encourage Big Data implementation