Hasil untuk "Public relations. Industrial publicity"

Tina Šfiligoj, Renzo Massobrio, Oded Cats

The introduction of network science approaches into public transport research has seen great advances in the past 15 years. However, it has become apparent that monolayer networks are often not sufficient to model and analyse real-world systems in sufficient detail. In the last decade, the theory of multilayer networks has proven to be an invaluable tool in various disciplines, including transport. Multilayer networks consist of layers of networks that are coupled among themselves. This enables modelling of complex systems with heterogeneous elements and relations between them. Although there is a body of work in public transport research that uses multilayer networks, the related literature is scattered, lacking unified terminology and agreed-upon approaches. We posit that there is vast uncovered potential in using multilayer network approaches to public transport modelling, planning, and operations. We first present the basic formalisms of multilayer networks with a focus on how they (may) relate to public transport networks. We then provide a systematic review of the literature on multilayer networks in public transport research. We identify and taxonomise ways in which public transport systems are modelled as multilayer networks. Based on the survey and drawing from the state and history of network science in public transport research as well as multilayer approaches across other application domains, we propose a research agenda for multilayer public transport networks for the upcoming decade(s).

FAEIQUE Azmaine, SAMI Nahin Rahman, SHIKHA Most. Suraia Akter et al.

Police reform in Bangladesh has been constrained by colonial legacies, authoritarian practices, and political patronage, weakening institutional autonomy and public trust. The Police Reform Commission (PRC) 2024, established by the interim government, proposed 108 measures to modernize the police and enhance accountability. This study evaluates these proposals using a convergent mixed-methods approach, combining surveys of 350 citizens and 50 police personnel with key informant interviews and document analysis. Findings indicate limited awareness only 36–45% of respondents demonstrated detailed knowledge but strong support for structural reforms, including an independent police commission (63% of citizens; 94% of police). The study confirms H1, showing that political interference, organizational inertia, and weak monitoring constrain implementation, while validating H2, as stakeholders perceive the reforms as relevant, necessary, and potentially impactful. Factor analysis identified four dimensions Structural Reform & Modernization, Structural Independence, Legal Accountability, and Institutional Challenges highlighting that technical reforms are more attainable than those requiring shifts in political power. The study concludes that meaningful change requires both institutional restructuring and a cultural shift to achieve accountable, democratic policing in Bangladesh.

SABIE Oana Matilda, PURDESCU Florentina, NIȚĂ Elena Maia

The concept of co-production, also known as citizen or beneficiaries’ participation in the delivery of public services, is not a new one, and it has been an established practice for quite some time. As users and institutions from public administration, as well as other types of organisations, work together to improve public services, this concept is gaining more and more recognition. This study aims to determine the key factors influencing the co-production of public services, main opportunities and challenges starting with investigation of specialized literature and continuing with concrete examples of co-production in cultural services provided by museums. The case insights studies presented explores the role of co-production in museums, particularly how involving visitors in the creation and delivery of services enhances diversity and improves quality. Drawing on real-world examples, theoretical frameworks, and scholarly research, this study highlights the benefits and challenges of co-production in general, and in the museum sector in particular.

AGHEORGHIESEI Doina-Monica, SFRIJAN Elena-Mihaela

The implementation of artificial intelligence (AI) in the healthcare sector brings both significant benefits and complex challenges related to ethical, administrative and legal responsibilities. To fully understand the impact of AI on health ethics policies, it is essential to analyze the recommendations of international organizations, national initiatives and recent academic studies. The integration of AI in healthcare is reshaping the responsibilities of professionals and decision-makers alike. In addition to its obvious benefits, AI raises critical concerns related to data privacy, diagnostic accuracy and liability in case of errors. This article examines how AI accountability and governance should be integrated into public health ethics policies, through an interdisciplinary approach that combines applied ethics, administrative sciences and policy analysis. We will argue that effective ethical governance of AI requires new institutional models, transparent policies and a clear distribution of responsibilities between human and technological actors.

BARBIER Lance

This paper is based on the premise that fragmented reform efforts in developing countries fail to deliver sustained public value unless they are unified through an integrated governance model. It presents an in-depth thematic literature review of secondary sources published between 2000 and 2025, examining how Knowledge Management (KM), governance reform, and VUCA (Volatility, Uncertainty, Complexity, Ambiguity) preparedness have evolved and influenced Public Administration practice. The object of research is the development of the 3R Framework, which synthesises three pillars, Reform, Responsiveness, and Resilience, to address the persistent gap between policy intent and operational reality. The investigated problem is the limited success of administrative reforms in resource-constrained environments, where outdated bureaucratic systems, siloed knowledge practices, and low VUCA-readiness undermine service delivery and citizen trust. The most important finding of this literature study is that integrating KM, RBME, and OKRs into multi-tier planning architectures can transform Public Administration from compliance-led to impact-driven governance. The framework positions directorates/business units as central delivery units and introduces Quarterly Performance Reviews (QPRs) as instruments for strategic alignment, learning, and resilience-building. This paper will be useful to Public Administration practitioners and policymakers seeking scalable, citizen-centric reform strategies. The implications are twofold: theoretically, the study contributes a unified model that bridges KM and VUCA preparedness within governance literature; practically, it offers a roadmap for governments, particularly in South Africa, to embed continuous learning, ethical leadership, and adaptive planning into their operations. Further empirical research is encouraged to validate the framework and explore its application across diverse governance contexts. The study asks why reforms fail in resource-constrained contexts and hypothesises that integrating KM, RBME, OKRs, and VUCA tools into a unified framework can enable adaptive, impact-driven governance.

ZAI Paul Vasile, BOJAN Denisa Ioana

This paper evaluates the effects of EU Structural Funds in Romania by comparing ten key indicators across the 2007-2013 (2015 - N+2) and 2014-2020 (2023 - N+3) programming periods. Using national and European data and ratio-based formulas, the study documents significant shifts: a noticeable decline in the digitalization ratio and start-up creation rate, contrasted by strong gains in fund-absorption speed and overall project volume. The findings highlight Romania’s enhanced administrative capacity, yet they reveal persistent challenges in early-stage innovation, SME efficiency and urban-rural equity. The insights offer a data-driven foundation for policy optimization, guiding targeted interventions to promote digital uptake, entrepreneurial activity and balanced regional development.

MONIR Maruf Mohammad Sirajum, GEBEREMESKEL Aula Nerea

The capacity to affect change on a local and global scale about a range of political, social, environmental, and economic challenges is known as social entrepreneurship (SE). Young exposure to theory and practice of social entrepreneurship at postsecondary educational institutions is thought to influence this change. In this study, we examine the intentions of students in social entrepreneurship. This study's objective is to assess the degrees of social and entrepreneurial entrepreneurship. For the study, 150 college students served as the sample. This study examines empathy, moral duty, social support, self-efficacy, social impact, and educational level as principal motivators for social entrepreneurship intentions. The SPSS is a software program used to analyse the data and perform statistical analyses. The findings indicate that the only factors that were statistically correlated with the desire to engage in social entrepreneurship were empathy, self-efficacy, and psychological support. The association between social support and the ambitions for social entrepreneurship was shown to be unfavourable. In conclusion, the study provides insightful information for practitioners and educators who aim to foster a vibrant environment for student social entrepreneurship.

MONIR Maruf Mohammad Sirajum, GEBEREMESKEL Aula Nerea

Through the launch of social innovation projects with the potential to bring about revolutionary change, this study explores the critical function of social entrepreneurship in promoting long-term societal progress. This study set out to do one main thing: shed light on how social innovation fits into entrepreneurial endeavours with a social mission in order to attain long-term social development. Quantitative research was carried out in India through an online survey to examine the proposed links. Organisations across India that are involved in social entrepreneurship and social enterprises were surveyed for this data. The link between social entrepreneurship and long-term social progress can be mediated by social innovation, according to the research. Social innovation in social entrepreneurship projects has a major impact on long-term social progress, according to the research. Government agencies, lawmakers, philanthropists, social entrepreneurs, educators with an entrepreneurial spirit, and Non-Governmental Organizations (NGOs) can all benefit from these discoveries. Policymakers, practitioners, and academics can benefit from this research because it sheds light on the mediating elements and pathways that allow social entrepreneurship to promote transformative social change. This research is important for sustainable development efforts.

Lukas Fuchs

René von Schomberg’s article (von Schomberg, 2024) makes an invigorating case for the co-responsibility of societal actors to give direction to the pursuit of science. In this reply, I wish to endorse his position as a much-needed reconceptualisation in the face of societal challenges and internal scientific developments. At the same time, I urge that there remain theoretical and practical intricacies in attempting to steer science.

SABIE Oana-Matilda, BUNEA Ovidiu-Iulian, POPESCU Ruxandra-Irina

This article undertakes a comprehensive study of worldwide literature gathered from the Web of Science database, using bibliometric analysis. The analysis covers all the years, and most publications are from 1988 to 2024. The primary focus of the inquiry centres on the development of public service concept, public services citizens’ satisfaction, services’ stakeholders, public services’ quality and performance during this period. The assessment of public services quality by citizens has been a prominent subject of scholarly investigation for a considerable period of time. By conducting keyword co-occurrence analysis on pertinent literature, our objective was to uncover dominant themes and track trends over a period of time. Novel insights were obtained by generating density, network, and overlay maps using VOS Viewer software. The keyword co-occurrence analysis performed using VOS Viewer unveiled an intricate and interrelated network of study themes within the literature on stakeholders' perceptions of the quality and performance of public services. The study discovered four main clusters, each reflecting separate yet intersecting research topics. An in-depth analysis of these clusters provides significant insights into the emerging patterns and key areas of interest in this subject. This research provides essential insights for both academic and practical applications in public services, establishing a foundation for future investigations.

NASTACĂ Corina Cristiana

The present research is a pilot study that analyses citizens' perceptions regarding the rail services provided by the Romanian Railways Company - traveller division (CFR Călători SA). The main objectives of the research are: (1) To assess citizens' satisfaction concerning the rail services in Romania; (2) To investigate citizens’ perception regarding the quality of the rail services; (3) To identify the aspects that should be improved in the rail services provided to citizens. The research methodology consists of an opinion survey, conducted among citizens in Bucharest-Ilfov region. The study revealed a rather negative perception regarding the rail services provided by the Romanian Railways Company - travellers division (CFR Călători SA). Respondents were at least satisfied with: trains’ punctuality, the cleanliness in the train wagons, the number of counters for tickets available in the train stations and the food and drinks that can be provided in trains and were satisfied the most with the temperature in the trains wagons, the luggage space and, the attitude of the trains’ personnel. Also, the study showed that on the whole, the respondents considered that the rail company provides services of medium quality.

NASTACĂ Corina Cristiana

The present research explores the concept of gender equality and the main issues faced by female civil servants in the pandemic, with purpose of designing recommendations for the development of an inclusive and fair working environment in the Romanian public administration. The study is an exploratory one and was conducted in the Romanian National Agency for Equal Opportunities for Women and Men, the main institution with prerogatives in developing and implementing the strategy for gender equality. The research methodology consists of a survey based on a questionnaire designed by the author. The main findings of the study are: stereotypes and gender role biases are the main cultural or systemic barriers, indicating an increased awareness, especially among women, of the impact of these stereotypes and prejudices on their career opportunities and progress. In addition, the main difficulties encountered by female civil servants during the pandemic were the necessity to spend more time with their families and doing house chores, as well as to take more often, unexpected leave days.

BURCEA Ștefan Gabriel, REID Catriona, NICA Elvira

This paper is an argue for considering climate change as a security threat, with all the advantages, disadvantages and implications involved in. Our work provides a condensed scientific explanation of how global warming leads to climate change and extreme weather events, and then frame climate change through both a narrow and broad understanding of security. The main research questions addressed in the study are: In what sense might climate change be viewed as a security threat? What are the advantages and disadvantages of viewing climate change as a security threat? What are the funding policy implications in the context of existing climate justice models? With appropriate literature references we argue that climate change can be viewed as a security threat because of its consequences for migration, civil war and interstate conflict, and for human security. Therefore we address the main advantages for considering climate change a security threat (namely the chance for states to prepare for worst-case scenarios) and the main disadvantages (namely the securitisation of climate change). An outline of the components of ‘loss and damage’ policies was made, explaining exactly what sort of measures are required by developing countries and climate-vulnerable countries to respond to climate disasters. Next, four different models for prescribing responsibility onto developed countries for funding climate justice were assessed and critically evaluated. Lastly, concluding remarks covered the overall need for caution when discussing climate change in a security context and the need to ensure a balance is struck between militaristic and humanitarian approaches to climate change.

Carlos Alberto Durigan Junior, André Taue Saito, Daniel Reed Bergmann et al.

The main objective of this paper is to Identify which macroe conomic factors and industrial indexes influenced the total Brazilian banking spread between March 2011 and March 2015. This paper considers subclassification of industrial activities in Brazil. Monthly time series data were used in multivariate linear regression models using Eviews (7.0). Eighteen variables were considered as candidates to be determinants. Variables which positively influenced bank spread are; Default, IPIs (Industrial Production Indexes) for capital goods, intermediate goods, du rable consumer goods, semi-durable and non-durable goods, the Selic, GDP, unemployment rate and EMBI +. Variables which influence negatively are; Consumer and general consumer goods IPIs, IPCA, the balance of the loan portfolio and the retail sales index. A p-value of 05% was considered. The main conclusion of this work is that the progress of industry, job creation and consumption can reduce bank spread. Keywords: Credit. Bank spread. Macroeconomics. Industrial Production Indexes. Finance.

Haiming Yao, Yunkang Cao, Wei Luo et al.

Image anomaly detection plays a pivotal role in industrial inspection. Traditional approaches often demand distinct models for specific categories, resulting in substantial deployment costs. This raises concerns about multi-class anomaly detection, where a unified model is developed for multiple classes. However, applying conventional methods, particularly reconstruction-based models, directly to multi-class scenarios encounters challenges such as identical shortcut learning, hindering effective discrimination between normal and abnormal instances. To tackle this issue, our study introduces the Prior Normality Prompt Transformer (PNPT) method for multi-class image anomaly detection. PNPT strategically incorporates normal semantics prompting to mitigate the "identical mapping" problem. This entails integrating a prior normality prompt into the reconstruction process, yielding a dual-stream model. This innovative architecture combines normal prior semantics with abnormal samples, enabling dual-stream reconstruction grounded in both prior knowledge and intrinsic sample characteristics. PNPT comprises four essential modules: Class-Specific Normality Prompting Pool (CS-NPP), Hierarchical Patch Embedding (HPE), Semantic Alignment Coupling Encoding (SACE), and Contextual Semantic Conditional Decoding (CSCD). Experimental validation on diverse benchmark datasets and real-world industrial applications highlights PNPT's superior performance in multi-class industrial anomaly detection.

Andrew Deas, Hashan Fernando, Heidi A. Hanson et al.

The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates. This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter's predicted rates across the nation's counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5 percent nationally. Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation's most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift. The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.

Mykhailo Koshil, Tilman Wegener, Detlef Mentrup et al.

Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an image, e.g., a missing component on an image of a circuit board, for subsequent manual inspection. While industrial anomaly detection has seen a surge in recent years, most anomaly detection methods still utilize knowledge only from normal samples, failing to leverage the information from the frequently available anomalous samples. Additionally, they heavily rely on very general feature extractors pre-trained on common image classification datasets. In this paper, we address these shortcomings and propose the new anomaly detection system AnomalousPatchCore~(APC) based on a feature extractor fine-tuned with normal and anomalous in-domain samples and a subsequent memory bank for identifying unusual features. To fine-tune the feature extractor in APC, we propose three auxiliary tasks that address the different aspects of anomaly detection~(classification vs. localization) and mitigate the effect of the imbalance between normal and anomalous samples. Our extensive evaluation on the MVTec dataset shows that APC outperforms state-of-the-art systems in detecting anomalies, which is especially important in industrial anomaly detection given the subsequent manual inspection. In detailed ablation studies, we further investigate the properties of our APC.

Thomas Völker, Rasmus Slaattelid, Roger Strand

Since the 1990s, changing ways of producing and circulating knowledge have been accompanied by debates that diagnose and call for change in the relationship between science, society, politics, and innovation. Most recently in Europe, some of these debates emphasize the concept of responsible research and innovation (RRI). In this paper, we present a comparative analysis of different territorial RRI-pilots within the Horizon 2020-funded project TRANSFORM. In these pilots, different translations of RRI become visible. RRI (1) gets translated as participatory and deliberative modes of innovation governance aimed at transformative change, (2) takes the shape of citizen science projects; and (3) is enacted as participatory agenda setting and (plans for a) citizen assembly. We argue that it is the often-invisible work of establishing, nurturing, and caring for relationships within the territorial R&I ecosystems – what can the thought of as ongoing “maintenance work” – that creates the conditions for more responsive modes of innovation governance, and thus a shift towards transformative change in innovation policy. Through describing these translations and the related practices we will direct attention to the potential, challenges, and systemic barriers of this kind of work.

NICA Elvira, SABIE Oana-Matilda

In recent years the interest in emotional intelligence within scientific literature has grown, but too little has been written about the influence of emotional intelligence within educational systems, especially the relation between emotional intelligence and teachers’ job performance, or emotional intelligence and students’ academic achievement. Universities around the world have experiencing changes and reforms, impacting the teachers’ job performance and academic achievement among university students. Emotional intelligence plays an important role in many areas of our lives. The scope of the research is to investigate the impact of emotional intelligence on students’ academic achievement from public administration programs. We choose students from public administration, since they are supposed to work after graduation in public institutions, and get in direct contact with citizens. At the level of Romania, there is no study with predictive value regarding the “impact of emotional intelligence on students’ academic achievements” supported by empirical research. Regarding the methodology, we collected data using the questionnaire which was developed based on the instruments by previous researchers. Respondents were students from public administration programs. The benefits of such a study are to provide a solid basis for understanding the mechanisms of emotional intelligence (EI) and their role in determining or sabotaging academic achievement. The effect of emotional intelligence on students’ academic achievement was established. On the basis of the findings, it is suggested that emotional intelligence should be integrated into university students’ curriculum. The study further advocated for the promulgation of educational policy on emotional intelligence. Also, this research will represent an important contribution to the Romanian and international literature, both in the field of emotional intelligence, as well as in the field of students’ academic achievement and continuous students’ personal development (academic self-efficacy).

Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen et al.

Monitoring and detecting abnormal events in cyber-physical systems is crucial to industrial production. With the prevalent deployment of the Industrial Internet of Things (IIoT), an enormous amount of time series data is collected to facilitate machine learning models for anomaly detection, and it is of the utmost importance to directly deploy the trained models on the IIoT devices. However, it is most challenging to deploy complex deep learning models such as Convolutional Neural Networks (CNNs) on these memory-constrained IIoT devices embedded with microcontrollers (MCUs). To alleviate the memory constraints of MCUs, we propose a novel framework named Tiny Anomaly Detection (TinyAD) to efficiently facilitate onboard inference of CNNs for real-time anomaly detection. First, we conduct a comprehensive analysis of depthwise separable CNNs and regular CNNs for anomaly detection and find that the depthwise separable convolution operation can reduce the model size by 50-90% compared with the traditional CNNs. Then, to reduce the peak memory consumption of CNNs, we explore two complementary strategies, in-place, and patch-by-patch memory rescheduling, and integrate them into a unified framework. The in-place method decreases the peak memory of the depthwise convolution by sparing a temporary buffer to transfer the activation results, while the patch-by-patch method further reduces the peak memory of layer-wise execution by slicing the input data into corresponding receptive fields and executing in order. Furthermore, by adjusting the dimension of convolution filters, these strategies apply to both univariate time series and multidomain time series features. Extensive experiments on real-world industrial datasets show that our framework can reduce peak memory consumption by 2-5x with negligible computation overhead.