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Overcoming the Trade-Off Effect: Environmental or Economic Prioritization and the Propensity for Green Voting
Full text linkDespite growing environmental awareness, many hesitate to act pro-environmentally. A reason for this is the perceived economic cost of a pro-environmental choice. Such trade-off between environmental and economic prioritization happens through two distinct channels: a pocketbook—sustainability versus personal finances—or a macro-level one—sustainability versus economic growth. Can this trade-off negative effect on pro-environmental behavior be overcome? Facing an electoral choice, when are voters still inclined to opt for a party championing environmental sustainability, even if they are unwilling to prioritize ecological concerns over economic ones? Using survey data representative of the Italian population, we adopt a Propensity for Green Voting measure to assess the likelihood of voting for an environmentally focused party. We find that serious concerns about natural disasters effectively mitigate the trade-off’s negative effect on Propensity for Green Voting (PGV), leading voters holding economic concerns to intend to cast a green vote nonetheless. The same applies to those living with children or having a left-leaning political orientation. However, children in households move the electorate toward a pro-environmental vote only for trade-off evaluations at the macro-level. In contrast, pocketbook evaluations do not hinder voting green for those with a left-leaning orientation
Digital Twin for Sustainable Manufacturing: Integrating Networking and Factory Assets
No full textThe novel Industry 5.0 concept leverages data gathering and communication between the Information Technology (IT) and Operation Technology (OT) segments to drive efficient and sustainable manufacturing processes. However, how to properly integrate IT and OT ecosystems to achieve effective industrial asset management has to be further investigated. We propose an architecture that provides an integrated view and unified control of networking and industrial equipment. This paper describes how the proposed architecture can enable energy-saving decision-making policies and support sustainable predictive maintenance in manufacturing through the Asset Administration Shell concept. Part of the architecture is implemented using the Eclipse BaSyx tool, an Asset Administration Shell-compliant framework, to bridge the IT and OT segments by providing a virtual representation of both network and factory assets and a unified control interface
Essays on selected segments of the US strawberry industry, growers’ behavior and agritourism communication.
No full textAbstract (Italiano)
Questa tesi indaga le intricate dinamiche dell'industria della fragola statunitense e del settore
agrituristico della Virginia, impiegando diverse metodologie per fornire una comprensione completa
delle loro attuali sfide e opportunità. Composto da cinque capitoli, lo studio inizia con un'introduzione
(Capitolo 1) che delinea le motivazioni, gli obiettivi e le strategie della ricerca. La conclusione
(Capitolo 5) sintetizza i risultati, traendone implicazioni pratiche e teoriche e proponendo indicazioni
per la ricerca futura.
Il Capitolo 2, intitolato “Content Analysis of the Breeders’ and Growers’ Segments of the US
Strawberry Industry”, utilizza l'analisi qualitativa del contenuto latente per scoprire i temi chiave che
caratterizzano questi settori. Sulla base di ampie interviste con esperti del settore, lo studio identifica
questioni critiche come lo sviluppo accelerato delle varietà, le sfide della proprietà intellettuale e la
resilienza al clima. I risultati forniscono indicazioni utili per affrontare queste sfide, sottolineando la
collaborazione tra selezionatori, coltivatori e responsabili politici.
Capitolo 3, “How Growers’ Values Affect Decisions in Choosing Strawberry Varieties in the
US: A Higher-Order Construct PLS-SEM Approach”, presenta una nuova integrazione
dell'innovatività specifica del settore nel quadro decisionale dei coltivatori. Utilizzando il Partial
Least Squares Structural Equation Modeling (PLS-SEM), questo capitolo esplora come i valori
percepiti - funzionali, sociali, condizionali ed estetici - plasmino le scelte dei coltivatori di fragole. I
risultati evidenziano il ruolo sfumato di questi valori, offrendo a selezionatori e commercianti un
quadro solido per allineare lo sviluppo dei prodotti alle preferenze dei coltivatori.
Il capitolo 4, “Land Zoning, Permits, and Tax-Related Guidelines for Agritourism Operators
in the Commonwealth of Virginia, USA”, affronta una carenza critica di risorse centralizzate per gli
operatori agrituristici. Attraverso un'analisi sistematica della letteratura, il capitolo consolida le
informazioni normative disperse in una guida pratica, consentendo agli agricoltori di orientarsi
efficacemente tra le complessità legali. I risultati sottolineano l'importanza della conformità
normativa nel promuovere iniziative agrituristiche sostenibili ed evidenziano l'interazione tra i quadri
politici e la crescita imprenditoriale.
I risultati di questa tesi hanno implicazioni significative sia per il mondo accademico che per
quello industriale. Affrontando le dinamiche tra allevatore e coltivatore, la selezione delle cultivar e
la regolamentazione dell'agriturismo, essa colma le lacune critiche della conoscenza e offre soluzioni
praticabili alle sfide più pressanti. L'integrazione di metodologie innovative, tra cui l'analisi del contenuto, il PLS-SEM e la revisione sistematica della letteratura, contribuisce a far progredire i
quadri della ricerca agricola. Lo studio si conclude auspicando ulteriori approfondimenti su studi
comparativi globali, impatti economici e approcci interdisciplinari per garantire la sostenibilità e la
competitività a lungo termine dell'industria statunitense delle fragole e del settore agrituristico della
Virginia.Abstract
This dissertation investigates the intricate dynamics of the US strawberry industry and
Virginia’s agritourism industry, employing diverse methodologies to provide a comprehensive
understanding of their current challenges and opportunities. Comprising five chapters, the study
begins with an introduction (Chapter 1) outlining the research motivations, objectives, and strategies.
The conclusion (Chapter 5) synthesizes the findings, drawing practical and theoretical implications
while proposing future research directions.
Chapter 2, titled "Content Analysis of the Breeders’ and Growers’ Segments of the US
Strawberry Industry," employs qualitative latent content analysis to uncover key themes shaping the
breeders’ and growers’ segments. Based on extensive interviews with industry experts, the study
identifies critical issues such as accelerated variety development, intellectual property challenges, and
climate resilience. The findings provide actionable insights to address these challenges, emphasizing
collaboration between breeders, growers, and policymakers.
Chapter 3, "How Growers’ Values Affect Decisions in Choosing Strawberry Varieties in the
US: A Higher-Order Construct PLS-SEM Approach," presents a novel integration of domain-specific
innovativeness into growers’ decision-making frameworks. Utilizing Partial Least Squares Structural
Equation Modeling (PLS-SEM), this chapter explores how perceived values—functional, social,
conditional, and aesthetic—shape growers' choices of strawberry cultivars. The findings highlight the
nuanced role of these values, offering breeders and marketers a robust framework to align product
development with growers’ preferences.
Chapter 4, "Land Zoning, Permits, and Tax-Related Guidelines for Agritourism Operators in
the Commonwealth of Virginia, USA," addresses a critical gap in centralized resources for
agritourism operators. By conducting a systematic literature review, the chapter consolidates
dispersed regulatory information into a practical guide, enabling farmers to navigate legal
complexities effectively. The findings emphasize the importance of regulatory compliance in
fostering sustainable agritourism ventures and highlight the interplay between policy frameworks and
entrepreneurial growth.
This dissertation’s findings hold significant implications for both academia and industry. By
addressing breeder-grower dynamics, cultivar selection, and agritourism regulation, it bridges critical
knowledge gaps and offers actionable solutions to pressing challenges. The integration of innovative methodologies, including content analysis, PLS-SEM and systematic literature review contributes to
advancing agricultural research frameworks. The study concludes by advocating for further
exploration into global comparative studies, economic impacts, and interdisciplinary approaches to
ensure the long-term sustainability and competitiveness of the US strawberry industry and Virginia's
agritourism industry
Prefazione a J. Pieper, Sulla speranza
No full textPrefazione alla nuova edizione italiana riveduta e ampliat
Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring
No full textIn remote areas or regions with limited access to medical specialists, there is often a high reliance on telemedicine and Artificial Intelligence (AI)-based diagnostic tools. However, misdiagnoses or inadequate care may occur if the AI system lacks domain knowledge, failing to adhere to medical protocols. Despite the incredible research efforts applying AI in medicine, only a few models have been routinely adopted in medicine, due to issues related to trustworthiness. To address these concerns, Symbolic Knowledge Injection (SKI) has been proposed as a solution: it integrates domain-specific expertise into Machine Learning (ML) models, to improve their predictive capabilities. Despite their promising results in other fields, applicability of SKI in healthcare scenarios has not been thoroughly investigated, yet. Accordingly, in this study, we explore the applicability of a SKI method on medical datasets to evaluate: (i) how the predictive capabilities of ML models changes, (ii) their adherence to the medical protocols, and (iii) their robustness w.r.t. data degradation. Results demonstrate the potential of integrating data-driven models with established medical guidelines by improving different clinically relevant metrics