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Perceptions on how working structures have impacted soft-skills and communication styles among office workers in Ireland: A qualitative study
No full textThis project examines how changes in remote and hybrid work models have influenced the perception of soft skills, with a specific focus on communication in the professional workplace in Ireland. The COVID-19 pandemic accelerated a structural shift in how employees interact, collaborate, and maintain professional relationships. While digital tools have enabled new forms of accessibility and task management, they have also reshaped the emotional and interpersonal dimensions of professional life as interview participants highlighted that digital tools can lead to issues with understanding their colleagues and increase the risk of miscommunication or misinterpretation.
Through qualitative research, including semi-structured interviews and thematic analysis, this study captured the lived experiences of employees navigating post-pandemic work transitions, using interviews with professionals across sectors who experienced shifts from remote to hybrid or in-person environments. The analysis identified five key themes: the evolution of communication methods, the erosion of informal workplace interactions, the burden of emotional labour, generational and cultural differences in communication norms, and the need for structured support in soft skill development. Findings indicate that while technological platforms have allowed for flexible collaboration, they have also disrupted relational dynamics by removing spontaneity, obscuring tone, and reducing opportunities for learning in social and informal scenarios.
This research highlights the growing distance between the recognised importance of soft skills and the limited organisational investment in their development
Artificial Intelligence and government public sector workers
No full textThe integration of Artificial Intelligence (AI) into public services in Ireland is transforming the delivery of government operations, public engagement, and internal administrative processes. While the adoption of AI presents opportunities for increased efficiency, cost savings, and improved citizen services, it also raises critical concerns regarding job security, role displacement, process changes and the need for workforce transformation through disruption caused by the integration of AI. This dissertation explores the central research question:
“How is the adoption of Artificial Intelligence (AI) in the Public Sector impacting job security and employment structures, and what workforce strategies can be implemented to mitigate the risks of workforce displacement?”
The study investigates the dual impact of AI on both the structural aspects of public sector employment and the human implications, using a qualitative research approach. Primary data were collected through in-depth semi-structured interviews with seven professionals currently employed across various departments of the Irish public sector, including health, education, IT, civil service administration, housing, unions, digital transformation and local government. These Interviewee represent a cross-section of operational, managerial, and policy-level roles. The data provide nuanced insights into employee perceptions of AI-driven change, anticipated challenges to employment structures, and proposed strategic responses.
Findings indicate a growing awareness of AI's capabilities, accompanied by concerns over job erosion, skill mismatches, and unclear role evolution. However, there is also a recognition of AI’s potential to augment human tasks rather than replace them outright, provided there are proactive and inclusive workforce strategies in place. Through the integration of AI new skills will be developed and roles. Initiatives and strategies will need to be introduced for the upskilling and reskilling of workers, transparent communication and human involvement, organisational change management, and collaborative policy frameworks between government, unions, and civil society will need to be considered.
This dissertation contributes to the broader literature on AI and public sector workforce planning by offering a grounded perspective on the Irish context. It proposes a multitiered strategic model for mitigating displacement risks and fostering sustainable digital transformation. The research concludes that successful AI integration in public services will depend on inclusive policy design, adaptive leadership, trust, ethical use and continuous engagement with the workforce
Deep Learning based Identification of Deepfake Multimedia
No full textRecent advancements in deep neural networks have progressed innovative approaches for creating digital content and it is getting very difficult to ascertain between which content is real and what is deepfake. Attackers are using these developed technologies for tampering with videos and images and disclosing them into social media. These actions are impacting not only individuals in terms of their reputation, mental health, income, etc. but they are also affecting organizations. This research paper investigates deepfake detection in multimedia clips using Deep Learning. Frames are extracted from multimedia clips. Facial detection techniques like region of interest (ROI) and cascading tools like harasses are applied on the extracted frames. A CNN model is trained using processed video frames and used to classify multimedia content into real or fake. Hyper-parameters like batch normalisation, max pooling, and Sigmoid functions are used for fine-tuning of the model to achieve better accuracy. Results show CNN provides good accuracy for deepfake videos detection
Employee Retention Strategies in Ireland’s Hospitality Industry
No full textThe hospitality industry in Ireland, a vital contributor to the national economy, continues to grapple with high levels of employee turnover and retention challenges. This research investigates the influence of employer branding, employee development, and generational differences on staff retention within Ireland’s hospitality sector. With an increasingly diverse workforce and a competitive labour market, understanding these factors is critical for developing effective and sustainable human resource strategies.
A quantitative research methodology was adopted to explore measurable relationships between key variables. A cross-sectional survey design was employed, utilizing an online questionnaire distributed to a sample of 100 hospitality professionals across international hotel chains, national brands, and independent establishments operating within Ireland. The survey incorporated closed-ended and Likert-scale questions, allowing for statistical analysis and comparison.
Data collection was supported by SPSS software, enabling both descriptive and inferential statistical analysis. Ethical considerations were carefully addressed through informed consent, voluntary participation, and secure, anonymous data handling in compliance with GDPR standards. By examining the practical experiences and perceptions of employees, this study aims to identify which HR practices most significantly influence staff retention.
The study’s results show that strong employer branding, structured training programmes, and generationally tailored retention strategies significantly enhance employee commitment and reduce turnover. Younger staff valued flexibility and rapid growth, while older employees prioritised stability and recognition. Employers aligning strategies with these preferences reported higher satisfaction and loyalty, offering clear, evidence-based guidance for improving retention in Ireland’s hospitality sector
Resilient microservices: an investigation into Istio effectiveness in Kubernetes
No full textMicroservices architecture is widely used for cloud-native applications, offering flexibility but adding complexity in management. Kubernetes helps with scalability and resource efficiency, but resilience depends on individual services and pods. Chaos engineering tests this resilience by simulating failures. Istio, a service mesh, enhances stability and fault tolerance in microservices. This paper examines how chaotic testing evaluates Istio’s impact on microservices resilience in Kubernetes, optimizing its configuration. Performance is measured under heavy load, analyzing response time, errors, resource usage, and requests per second. Findings show Istio improves stability, speeds up responses, and enhances failure resilience over traditional setups
Impact of leadership styles on employee motivation
No full textThe leadership of non-profits has a major impact on the atmosphere that inspires volunteers. There is more to being an administrative executive when you run a non-profit. Its purpose is to inspire and guide those who are ambitious and self-motivated. Leaders and managers in the nonprofit sector may influence employee engagement, retention, work happiness, and performance via their leadership style.
This study aims to fill a critical knowledge gap by investigating the effects of various leadership styles on employee motivation in nonprofits. Although research on the effect of leadership on motivation is abundant in for-profit organizations, nonprofits need a different style of leadership due to their specific problems and incentive systems. An organization's leadership has a critical role to play in encouraging intrinsic as well as extrinsic motivation. Creating a welcoming and inclusive work environment, recognizing and rewarding employees for their contributions, and encouraging them to grow professionally are all examples of what is known as "motivational leadership" in the nonprofit sector. A systematic, closed-ended questionnaire that was supported by a computer was used to collect data from thirty respondents. To give unbiased information on the prevalence and effect of transformational, servant, and democratic leadership styles, quantitative data was descriptively evaluated. Important ethical issues were protecting participants' privacy and getting their informed consent. While the method did have some flaws a small sample size and the fact that the questions were closed-ended it did provide uniformity and clarity in the end.
This research also emphasizes the significance of people management in change management, demonstrating that investment in talent management is closely correlated with the effectiveness of change initiatives. These findings have substantial ramifications for the formulation of change strategies and the comprehension of organizations. Additionally, the data does not support the claim that transformational leadership significantly aids in the process of change management. Servant leadership also increases organizational citizenship behaviours and motivation because it creates a culture of trust and compassion. But if the leadership is too relaxed and hands-off, it may lead to operational messes and low morale. To excite personnel, executives in NPOs should be engaged and focused on the purpose. Transactional leadership works well in the short term but has hidden emotional costs. Democratic leadership boosts morale and creativity, but it can also hurt efficiency
Artificial Intelligence in Recruitment: Understanding the experiences of Human Resource Professionals and Candidates
No full textThe study explores the use of Artificial Intelligence (AI) in recruitment considering the experience and perception of applying AI in recruitment with regard to the Human resource (HR) professionals and job seekers. AI applications such as resume screening algorithm, virtual assistant, and biometric assessment are aiding the hiring process to make better decisions and be more efficient. However, analytical aspects of transparency, justification, and development of human judgment in the process of recruitment take centre stage because of these innovations.
The main research issue aims to question the functionality of AI systems within the context of recruitment jobs and the creation of ethical complications to both the employers and the job candidates. Based on a pragmatic paradigm of research study, the investigation uses a mixed-methods research design, which will include two custom surveys. The two surveys provided quantitative and qualitative data respectively on the prevailing trends on AI usage and qualitative insights about the attitudes and experience of stakeholders on the same.
The results show that the HR practitioners noted greater efficiency and less bias in the early resume-screening stage but both groups see many issues with transparency, algorithmic decisions and the possibility of the loss of human touch. Specifically, the job seekers express the need of having a hybrid model which involves AI-based tools and human practitioners.
The research comes to the conclusion that to ethically and effectively use AI in the recruitment process, organisations are advised to embrace transparent practices, involve various stakeholders in designing AI systems and focus on recruitment decisions made on the basis of fairness and explainability
SMARDY: the CORE of zero-trust FAIR marketplace for research data
No full textSupporting discovery through good and open management of existing datasets is the core of progress in data-rich research environments. Open Data and FAIR (Findable, Accessible, Interoperable, and Reusable) principles drive the exploitation of current results to a better and more trustworthy scientific era, but the wide adoption in Science is hindered by concerns regarding the proper handling of sensitive or extra-valuable copyrighted datasets. We present Smardy, our proposal for extending Open Data Repositories for research datasets with components meant to protect data sovereignty and trust in transfer. Our implementation of a cross-platform is the core of a FAIR Dataset Marketplace, which allows the authors to trade their datasets with the unconditional security of a Zero-Trust environment, and helps them to protect their IP over data using undisputable, Blockchain-based proofs of their authorship. The depicted aspects include application-code design, functional schemes, fingerprinting, and encryption steps for properly handling datasets and generating authorship proofs
Cognitive Stimulation Therapy (CST): Exploring Perspectives of Trained Practitioners on the Barriers and Facilitators to the Implementation of CST for People Living with Dementia
No full textDementia is recognised as a disability under the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD). People with disabilities like dementia have the right to access specialised health and social care services, including interventions that support independence and community participation. Cognitive Stimulation Therapy (CST) is an evidence-based psychosocial intervention that improves cognition, communication, confidence, and quality of life for people living with dementia, but an implementation gap means that CST is often not available. This study examines whether trained CST practitioners implemented CST, their perceptions of the acceptability and efficacy of CST, whether the perceived acceptability and efficacy of CST predicted implementation, and practitioners’ opinions on the barriers and facilitators to CST implementation. A mixed-methods approach was used, with 62 participants (91.9% female). Although 95% of participants were trained to deliver CST, 45.2% did not facilitate CST groups. Statistical analysis showed that perceived efficacy significantly predicted both the likelihood of running CST groups (p = 0.006) and the number of groups delivered (p = 0.01). Thematic analysis of qualitative data identified the three key themes of ‘resources’, ‘awareness and education’, and ‘acceptability of CST’. Overall, the results show that while CST is acceptable and deemed highly effective, resources and staffing often impede implementation. The results are discussed in the context of prioritising the rights of people with disabilities and recommendations are made on improving access to evidence-based support
Using Behavioural Skills Training with Healthcare Staff to Promote Greater Opportunities for Independence for People Living with Dementia: A Randomised Single-Case Experimental Design (Preprint)
No full textApproximately 72% of older adults in residential care have dementia and present with different levels of functioning. People living with dementia (PLwD) may not always be facilitated to independently carry out activities of daily living (ADLs) in care, increasing the likelihood of excess disability. This study incorporated behavioural skills training (BST) to train healthcare staff how to increase opportunities for independence for PLwD by using task analyses and least to most (L-M) prompting procedures during ADLs. Three healthcare staff, two female and one male (mean age = 42.67, SD = 16.82), participated in the intervention. The What Works Clearinghouse (WWC) Single-Case Design Technical Documentation guided the study’s design. A randomised single-case experimental (n-of-1) design was employed, using a multiple-baseline design (MBD) across participants (n=3) for three separate ADLs. The dependent variable (DV) was the percentage of correct staff responses when implementing the L-M prompting procedure for each step during ADLs. Visual and statistical analysis demonstrated an increase in correct use of a task analysis and L-M prompting for all three participants during intervention compared to baseline, for ADL1: assistance to stand (effect sizes, d=5.39; d=9.38; and d=6.79); ADL2: assistance with drinking (effect sizes, d=3.27; d=8.55; and d=3.67); and ADL3 assistance to brush teeth (effect sizes, d=5.99; d=12.93;and d=9.39). Maintenance data ranged from 70% to 100% correct responses at follow-up (Mean=93.11% SD=7.85). Participants successfully generalised skills learned to two new ADLs (PLwD eating a meal and putting on a jumper). BST was demonstrated as an effective training strategy to increase opportunities for independent responding for PLwD in care environments. The influencing contingencies on staff behaviour require attention within the healthcare environment