Parthenope University of Naples
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Productivity, Growth and Labour Market Dynamics in Italy (1960-2023)
No full textThis article aims to examine the evolution of the Italian economy from the 1960s to the present focusing on wage and labour productivity dynamics. Throughout this period, the issue of containing labour costs emerged. On one hand, it provided a competitive advantage, but on the other exerted downward pressure on employment, aggregate demand, productivity, and economic growth. These contradictions and vulnerabilities began to emerge clearly since the 1980s with the intensification of the processes of economic tertiarization, international market integration and a general reduction in workers' bargaining power, further aggravated by the lack of policy manoeuvrability due to European constraints and austerity. Within a context characterized by small businesses, factors such as outsourcing, the adoption of a two-tier bargaining system, and increasing labour flexibility have been discouraging investments and productivity, thus locking Italy into a development model that risks further decline
Flood Mud Index (FMI): A Rapid and Effective Tool for Mapping Muddy Areas After Floods—The Valencia Case
No full textPSInSAR-Based Time-Series Coastal Deformation Estimation Using Sentinel-1 Data
No full textCoastal areas are highly dynamic regions where surface deformation due to natural and anthropogenic activities poses significant challenges. Synthetic Aperture Radar (SAR) interferometry techniques, such as Persistent Scatterer Interferometry (PSInSAR), provide advanced capabilities to monitor surface deformation with high precision. This study applies PSInSAR techniques to estimate surface deformation along coastal zones from 2017 to 2020 using Sentinel-1 data. In the densely populated areas of Pasni, an annual subsidence rate of 130 mm is observed, while the northern, less populated region experiences an uplift of 70 mm per year. Seawater intrusion is an emerging issue causing surface deformation in Pasni’s coastal areas. It infiltrates freshwater aquifers, primarily due to excessive groundwater extraction and rising sea levels. Over time, seawater intrusion destabilizes the underlying soil and rock structures, leading to subsidence or gradual sinking of the ground surface. This form of surface deformation poses significant risks to infrastructure, agriculture, and the local ecosystem. Land deformation varies along the study area’s coastline. The eastern region, which is highly reclaimed, is particularly affected by erosion. The results derived from Sentinel-1 SAR data indicate significant subsidence in major urban districts. This information is crucial for coastal management, hazard assessment, and planning sustainable development in the region
Artificial Intelligence and Digital Data in Recruitment. Exploring Business and Engineering Candidates’ Perceptions of Organizational Attractiveness
No full textArtificial intelligence (AI) is increasingly used in Human Resource Management (HRM), particularly within recruitment. However, the candidate perspective on AI usage remains underexplored, as existing research predominantly focuses on the employer’s viewpoint. Addressing this gap, we conducted a vignette survey experiment to examine how the combination of AI with professional and personal digital data influences the perceptions of business and engineering candidates regarding organizational attractiveness (OA) and their likelihood to apply for a job. The study was conducted in two large European Union (EU) countries, providing insights specific to the EU context, where regulations like the General Data Protection Regulation and the AI Act lead global efforts on responsible AI use. Our findings indicate that candidates generally view AI positively, particularly valuing its role in fostering innovation and development. Nevertheless, the combination of AI with professional and personal data prompts a more cautious perspective among candidates, with some opting not to apply. Notably, engineering candidates displayed more significant reservations towards AI than their business counterparts, contrasting to prior research. This investigation enriches theoretical, methodological, and practical discussions concerning AI in recruitment, elucidating factors influencing candidate perceptions and suggesting avenues for future research
Exploring the Effectiveness of Slot Attention-Based Classifier in Detecting Underwater Marine Litter: A Study
No full textThe increase in marine litter is slowly becoming a significant problem, for which various recognition techniques have been proposed and are still being. Artificial Intelligence (AI) based methodologies have emerged as a promising tool to address this challenge. However, adopting AI in marine litter search and monitoring requires high performance and accuracy, interpretability, and explainability, which are essential for building trust in the decision-making process. Explainable AI (XAI) is an emerging research area that aims to make AI models transparent and interpretable, enabling human experts to understand and trust the model’s decisions. In this context, XAI can play a crucial role in improving the effectiveness and efficiency of marine litter search and monitoring by providing insight into the model’s decision-making process and identifying areas for improvement. This paper aims to evaluate using a pre-processing methodology for removing water from underwater image interoperability on a slot attention-based classifier for explainable image recognition using a dataset based on marine debris for searching underwater litter. Experimental results show that the application of the above-mentioned pre-processing technique brings about a significant improvement in underwater image classification
Carbon Accounting for Cultural Change: An Ethnographic Case Study of an Italian Municipally Owned Corporation
No full textClimate change, as a pressing global challenge, compels organizations to address environmental issues by innovating their management and accounting models to align with sustainability goals. Carbon accounting has become essential for quantifying and reducing greenhouse gas emissions. However, research on how organizations leverage carbon accounting to drive cultural and organizational change remains limited. This study examines the potential of carbon footprint analysis to drive organizational changes necessary for a sustainable transition within a municipally owned corporation in Italy, responsible for urban waste collection and management. Municipally owned corporations, established and operated by local governments to manage public services, often face resistance to change as they navigate the balance between public accountability and operational efficiency. Using an integrated research framework, this study explores how carbon footprint analysis
serves as a practical tool for embedding sustainability practices and fostering cultural change. Employing an ethnographic case study methodology, findings reveal that carbon footprint measurement extends beyond its technical function, acting as a cultural and social mechanism that reshapes organizational dynamics and individual behavior. Furthermore, while carbon accounting raises environmental awareness, its effectiveness in driving cultural transformation depends on top management commitment, active employee participation, and targeted training programs to enhance environmental knowledge
Aspetti innovativi e problematici della nuova Direttiva (UE) 2024/1260 sul recupero e confisca di beni
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