Archivio istituzionale della ricerca - Università degli Studi di Venezia Ca' Foscari
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An experimental study on the susceptibility of purchasing managers to greenwashing
Get PDFGreenwashing—the deliberate exaggeration or fabrication of environmental claims—undermines
trust, disrupts transparency, and poses a significant barrier to genuine progress toward sustainability.
This scenario-based experimental study examines whether purchasing managers, key stakeholders in
organizational procurement, can reliably differentiate between greenwashed and certified sustainable
products. Using three carefully designed purchasing scenarios—laptops, safety gloves, and copy
paper—responses were collected from 465 purchasing managers across the EU, a region notable for
its regulatory emphasis on eco-certifications. The findings reveal no statistically significant differences
in willingness to pay (WTP) for products with greenwashed claims versus those backed by stringent
certifications, with average WTP values varying only slightly between groups. These findings highlight
a critical vulnerability to greenwashing, even among experienced professionals, raising concerns about
the credibility of sustainability claims in influencing procurement decisions. The study underscores
the need for systemic reforms, including the standardization of certification systems and enhanced
decision-making tools, to mitigate greenwashing’s pervasive impact and foster authentic corporate
sustainability
«Nada todo es nada»: Quevedo en la poesía de Miguel Hernández (una revisión)
Get PDFLuego de un repaso del stato dell’arte sobre esta relación intertextual, en este trabajo se examina el Quevedo que interesa a Miguel Hernández (una cuestión de canon y recepción), para pasar acto seguido a una revisión de este caso de reescritura (centrado especialmente en El rayo que no cesa)
Reporting on social issues
No full textThe second ESG pillar addresses social issues related to the impacts, risks and opportunities of an organization’s relationships with individuals and groups. Sustainability reporting considers all stakeholders, with a particular focus on employees and the communities surrounding the company. These social issues are recognized as central by different sets of reporting standards (both voluntary and mandatory), which guide sustainability reporting. Despite the wide-ranging nature of social disclosure, two main topics receive more detailed analysis. First, reporting on the organization’s workforce should offer comprehensive information about both direct em-ployees and individuals engaged through other clearly defined relationships, even when these do not involve traditional subordinate roles. Due to the complexity involved, sustainability re-porting also attempts, albeit with less precision, to include information on workers across the value chain, both upstream and downstream of the company. Second, social disclosure in sus-tainability reporting addresses the engagement of stakeholders beyond the workforce. This in-cludes communities that have been or may be affected by the company’s operations, as well as consumers who may experience direct or indirect impacts from its actions
Collaborative Innovation and Governance Structures: A Meta-Analytical Study of Family Firm Performance
No full textThe exchange of knowledge and resources across organizational boundaries is crucial for family firms to facilitate
growth and survival. However, the relationship between collaborative innovation practices and family
firm performance remains contested due to conflicting findings. This meta-analysis synthesizes 65 studies encompassing
173.274 family firms across 21 countries between 1997 and 2021 with the aim of addressing this
debate. The analysis confirms a positive link between collaborative innovation and family firm performance,
moderated by the type of collaboration partner. Specifically, collaborations with R&D partners yield the greatest
benefits by providing access to advanced technologies and external expertise. In addition, governance structures
significantly influence the relationship, with family ownership strengthening the positive effect, while
family management imposes constraints related to control and alignment concerns. These findings underscore
the importance of strategic partner selection and governance alignment to optimize innovation outcomes in
family businesses
Dei rapporti tra i consigli notarili distrettuali
No full textIl commento all'art. 27 dei principi attiene ai rapporti tra i diversi consigli notarili, stabilendo un obbligo di collaborazione agli effetti del promovimento dell'eventuale azione disciplinare, prevista dall'art. 153 della l. n. 89 del 1913, indicando altresì le diverse competenze in ragione del c.d. locus commissi delicti
MQTT Anomalous Behavior Detection in IP Sensor Networks Through Convolutional Neural Networks and Traffic to Image Encoding
No full textThe rapid growth of Internet of Things (IoT) devices in sectors like healthcare, manufacturing, and smart cities has resulted in a substantial increase in data volume and complexity. This requires robust anomaly detection systems to identify critical issues such as system failures, security breaches, external attacks, and inefficiencies. However, traditional anomaly detection methods often struggle with the high-dimensional and dynamic nature of IoT data. In this paper we propose a new and unconventional approach for anomaly detection, cyber-attacks in particular, in IP sensor networks, based on encoding IP packets into image and exploiting the huge and well-known classification strength of Convolutional Neural Networks for malicious behavior recognition. Simulation results show the optimality of the proposed machine learning approach, outperforming the existing tools in terms of accuracy, time and complexity
Compounding geopolitical and energy risks: A clustered stochastic multi-COVOL model
No full textThis paper investigates the relationship between stock returns in the energy sector, energy uncertainty, and geopolitical risk. To this end, we propose a parsimonious and flexible model to extract common volatility factors (COVOL) from panel data. This general nonlinear multi-factor framework organizes panel units into groups based on different exposures to individual and compounding risks to reduce the number of parameters to be estimated. The group membership of the units is unknown, which naturally calls for using stochastic partition models. Random partition and compounding relationships are encoded in the weighted hyper-edges of a random hypergraph where the vertexes are the individual risks. In the empirical analysis, we study the volatility transmission in a multi-country setting and the role of individual and compounding risks
Making the case for studying constructive news across languages and cultures
No full textConstructive news is an alternative to the negativity of if-it-bleeds-it-leads journalism but still unfamiliar to some audiences and still relatively under-researched, particularly by news translation scholars. And yet, it is “done” across cultures and, therefore, languages. This innovative book contributes to filling that research gap and raising awareness of the phenomenon by showcasing cross-cultural research on constructive news, including in the Global South – a region that has traditionally received less scholarly attention than the Global North.
Constructive news is resolutely multimodal, and so a number of chapters analyse it from that perspective. The chapters also tackle such topics as audience attitudes, service to the local community, pedagogy, financial news, and religious news. This book will appeal to journalism studies and translation scholars, applied linguists, lecturers, journalists, editors, and members of the public who consume, study, or teach news but are looking for alternatives
La formazione pre-partenza dei migranti tra mercato del lavoro e integrazione
No full textIl saggio esamina l'istituto della formazione pre-partenza nei paesi di origine per i migranti, contestualizzandolo nelle dinamiche del mercato del lavoro attuale e nel quadro del t.u. sull’immigrazione. Si sofferma poi sull'evoluzione e trasformazione della formazione pre-partenza, esaminando, infine, un caso specifico (il progetto Ghana)
A Comparison of Machine Learning Techniques for Ethereum Smart Contract Vulnerability Detection
No full textVulnerability detection is particularly relevant in smart contracts, where modifying the code after deployment is impossible. Machine learning solutions provide greater efficiency than static analyzers in speed and detection. This study evaluates various classic machine-learning techniques and state-of-the-art neural networks for training a vulnerability detector. We analyze the largest and most reliably labelled dataset of smart contracts currently available, experimenting with six data representations of smart contracts and a multimodal approach. Our experiments show that both deep and traditional machine learning methods excel in different scenarios. Notably, eXtreme Gradient Boosting achieved an F1-score of 0.91 with the multimodal approach, which suggests its potential for more robust classification. At the same time, the results underscore the need for larger datasets to showcase the full potential of the evaluated methods