Consumer behaviour: conceptualisation, scale development and validation of agro-food chain fairness

Although there is broad agreement on the need to transition to a fairer agro-food system, consumer potential in shaping a fair food system has often been overlooked. There is no unique definition of the concept of fairness from the consumer’s perspective. In addition, there are no scales in the academic literature that address fairness in its broad sense, as the existing scales focus on specific and limited aspects that provide a partial picture of the concept. Lack of a true and trustworthy measurement of the notion has been a significant barrier to the knowledge of fairness in agro-food systems from the individual-differences perspective. The individual-differences perspective helps explain why some individuals are more likely than others to put emphasis on the extent to which agro-food chains are fair. Individual consumer perception of an ethical problem is followed by the perception of various alternatives that might lead to a solution. Therefore, the current research intends to make two significant contributions by resolving these constraints. First, advance the literature by providing a new viewpoint to understand fairness in the agro-food chain. Indeed, the research provides a comprehensive conceptualisation of fairness that embraces different aspects of fairness and describes the concept in all its facets and nuances. Second, the research provides a valid, reliable, and invariant measurement of the individual disposition toward fairness in agro-food chains by rooting the items in the theoretical underpinnings of the fairness literature. Overall, this research provides a comprehensive suite of approaches and tools to enhance the resilience, integrity and sustainability of agro-food chains.

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Moduli consensuali nei rapporti tra Stato e autonomie territoriali e ruolo delle Conferenze

Ad oltre un decennio dalla riforma costituzionale del 2001, la non compiuta attuazione della stessa sembra condurre ad una nuova ed assai prossima revisione costituzionale. Nel mutato quadro costituzionale di quest’ultimo periodo l’attenzione e l’interesse sono stati richiamati da una grande quantità di accordi, di intese e di altri moduli consensuali, introdotti ed esitati nei rapporti tra Stato ed autonomie territoriali. Dall’esame del sistema delle Conferenze si è evidenziata la loro indispensabilità ai fini del coordinamento delle azioni politico –amministrative delle autonomie territoriali, ma è anche venuta fuori l’esigenza di ricorrere frequentemente ad altri tipi di moduli consensuali, spesso non tipizzati in ambito legislativo. I principi di sussidiarietà e di leale collaborazione inducono non di rado ad assumere, nella concretezza, forme eterogenee poco chiare e confuse (accordo, intesa, concerto, parere) che, pur considerati i contributi offerti dalla dottrina e dalla giurisprudenza, richiederebbero un intervento da parte del legislatore. L’approfondimento tematico ha rilevato, nel contesto di rapporti tra Stato ed autonomie territoriali, un movimento per così dire ondulatorio tra accese spinte autonomistiche e rimarcate esigenze centralistiche, lasciando ancora nella prospettiva una operativa ed efficiente armonia istituzionale.

Law, Informal Institutions and Trust: an Experimental Perspective

This dissertation has studied how legal and non-legal mechanisms affect the levels of trust and trustworthiness in an economy, and whether and when subtle psychological factors are crucial for establishing trust and even for recovering trust from a breach of contract. The first Chapter has addressed the question of whether formal legal enforcement crowds out or crowds in the amount of trust in a society. We find that formal legal mechanisms, especially formal contracts backed by a powerful authority, normally undermine trust except when they are perceived as legitimate, or when there are no strong social norms of fairness (i.e. the population in a society is considerably heterogeneous), or when the environment in which repeated commercial relationships take place becomes highly uncertain. The second Chapter has examined whether the endogenous adoption of a collective punishment institution can help a society coordinate on an efficient outcome, characterized by high levels of trust and trustworthiness. The experimental results show that the endogenous introduction of collective punishment by means of a majority-voting rule does not significantly improve coordination on the efficient equilibrium. Not all subjects seem to be able to anticipate the change in behavior induced by the introduction of the mechanism, and a majority of them vote against it. The third Chapter has explored whether high-trustors adapt their behavior in response to others’ trustworthiness or untrustworthiness more quickly, which in turn supports them to maintain higher default expectations of others’ trustworthiness relative to low-trustors. Our experimental results reveal that high-trustors are better than low-trustors at predicting others’ trustworthiness because they are less susceptible to the anticipated aversive emotions aroused by the potential betrayal and thereby have a higher willingness to acquire the valuable information about their partner’s actions.

Algorithmic business and EU law on fair trading

This thesis studies how commercial practice is developing with artificial intelligence (AI) technologies and discusses some normative concepts in EU consumer law. The author analyses the phenomenon of 'algorithmic business', which defines the increasing use of data-driven AI in marketing organisations for the optimisation of a range of consumer-related tasks. The phenomenon is orienting business-consumer relations towards some general trends that influence power and behaviors of consumers. These developments are not taking place in a legal vacuum, but against the background of a normative system aimed at maintaining fairness and balance in market transactions. The author assesses current developments in commercial practices in the context of EU consumer law, which is specifically aimed at regulating commercial practices. The analysis is critical by design and without neglecting concrete practices tries to look at the big picture. The thesis consists of nine chapters divided in three thematic parts. The first part discusses the deployment of AI in marketing organisations, a brief history, the technical foundations, and their modes of integration in business organisations. In the second part, a selected number of socio-technical developments in commercial practice are analysed. The following are addressed: the monitoring and analysis of consumers’ behaviour based on data; the personalisation of commercial offers and customer experience; the use of information on consumers’ psychology and emotions, the mediation through marketing conversational applications. The third part assesses these developments in the context of EU consumer law and of the broader policy debate concerning consumer protection in the algorithmic society. In particular, two normative concepts underlying the EU fairness standard are analysed: manipulation, as a substantive regulatory standard that limits commercial behaviours in order to protect consumers’ informed and free choices and vulnerability, as a concept of social policy that portrays people who are more exposed to marketing practices.

Towards Unstructured Knowledge Integration in Natural Language Processing

In the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep learning. In particular, purely data-driven approaches have opened to a wide variety of successful applications due to the large availability of data. Nonetheless, the integration of prior knowledge is still required to compensate for specific issues like lack of generalization from limited data, fairness, robustness, and biases. In this thesis, we analyze the methodology of integrating knowledge into deep learning models in the field of Natural Language Processing (NLP). We start by remarking on the importance of knowledge integration. We highlight the possible shortcomings of these approaches and investigate the implications of integrating unstructured textual knowledge. We introduce Unstructured Knowledge Integration (UKI) as the process of integrating unstructured knowledge into machine learning models. We discuss UKI in the field of NLP, where knowledge is represented in a natural language format. We identify UKI as a complex process comprised of multiple sub-processes, different knowledge types, and knowledge integration properties to guarantee. We remark on the challenges of integrating unstructured textual knowledge and bridge connections with well-known research areas in NLP. We provide a unified vision of structured knowledge extraction (KE) and UKI by identifying KE as a sub-process of UKI. We investigate some challenging scenarios where structured knowledge is not a feasible prior assumption and formulate each task from the point of view of UKI. We adopt simple yet effective neural architectures and discuss the challenges of such an approach. Finally, we identify KE as a form of symbolic representation. From this perspective, we remark on the need of defining sophisticated UKI processes to verify the validity of knowledge integration. To this end, we foresee frameworks capable of combining symbolic and sub-symbolic representations for learning as a solution.

The Financial Services Regime in International Economic Law: on the Difficult Relationship between Trade Liberalization and Prudential Measures

The PhD thesis analyses the financial services regime in international economic law from the perspective of the difficult relationship between trade liberalisation and prudential measures. Financial stability plays a fundamental role for the well-being and well-functioning of the global economy, but, it is at the same time a complex sector to regulate and supervise and, especially after the 2007-08 economic crisis, States have tightened up their regulation of financial services, introducing more severe and protectionist prudential measures. However, in an increasingly interconnected global economy, the harmonization of prudential regulation at the international level is an essential step to guarantee integrity, fairness and stability of financial markets and trade. The research analyses the tools at disposition to achieve this aim, the related problematic issues and the perspectives and possible solutions for the future, starting from the World Trade Organization (WTO) legal framework and its General Agreement on Trade in Services (GATS), devoted to discipline trade in services among the WTO Members. Then, the research moves to a second legal instrument, the Free Trade Agreements (FTAs), which has witnessed a remarkable spread in the last decades. Finally, the research addresses the international standards, developed by supranational entities and implemented by an increasing number of States, as they offer rules and guidelines adequate to update the international financial scenario. Nevertheless, the international standards alone cannot be the solution because, first, they are not mandatory, as governments decide voluntarily to apply them and, second, their decision-making process do not respect the requirements of transparency and representative membership. In light of this analysis, the thesis aims at providing an answer to its research question: how to give more certainty to States and economic operators in the planning of the domestic disciplines and business activities in order to provide a sound and stable international financial system.

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics.

Interfaces between national and EU law: time limits in cross-border civil proceedings and their impact on the free circulation of judgments

The thesis aims at exploring possible legal solutions to remove the obstacles to the free circulation of judgments in the civil justice area that arise from the remarkably diverging national rules on procedural time limits. As shown by the case-law of the CJEU, time limits have recently come under closer scrutiny. The interplay between national and EU law illustrates that time limits raise significant deficiencies connected with the right to a fair trial under Art. 6 ECHR and Art. 47 CFR – e.g. the effective recovery of claims, effective judicial protection, effective cross-border enforcement of judgments – which negatively impact EU cross-border civil litigation. In order to overcome some of the weaknesses of the current legal framework governing the cross-border enforcement of judgments and strengthen the parties’ fundamental procedural rights the PhD thesis intends to determine whether and, to what extent time limits can be harmonised at EU level. EU action on time limits would indeed favour the speed, efficiency and proportionality of cross-border proceedings without sacrificing the fairness of the judicial process and the equality of the parties