Self-Organizing Mechanisms for Task Allocation in a Knowledge-Based Economy

A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of “Knowledge-based economy” indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (people’s skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a “supervisory problem” (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because ‘the nominal supervisors will not know the best way of doing the job – or even the precise purpose of the specialist job itself – and the worker will know better’ (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that’ why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

Cognitive and affective processes in social actions and decisions

The question of how we make, and how we should make judgments and decisions has occupied thinkers for many centuries. This thesis has the aim to add new evidences to clarify the brain’s mechanisms for decisions. The cognitive and the emotional processes of social actions and decisions are investigated with the aim to understand which brain areas are mostly involved. Four experimental studies are presented. A specific kind of population is involved in the first study (as well as in study III) concerning patients with lesion of ventromedial prefrontal cortex (vmPFC). This region is collocated in the ventral surface of frontal lobe, and it seems have an important role in social and moral decision in forecasting the negative emotional consequences of choice. In study I, it is examined whether emotions, specifically social emotions subserved by the vmPFC, affect people’s willingness to trust others. In study II is observed how incidental emotions could encourage trusting behaviour, especially when individuals are not aware of emotive stimulation. Study III has the aim to gather a direct psychophysiological evidence, both in healthy and neurologically impaired individuals, that emotions are crucially involved in shaping moral judgment, by preventing moral violations. Study IV explores how the moral meaning of a decision and its subsequent action can modulate the basic component of action such as sense of agency.

Social Welfare and Behavioral Public Policies

In this work I discuss several key aspects of welfare economics and policy analysis and I propose two original contributions to the growing field of behavioral public policymaking. After providing a historical perspective of welfare economics and an overview of policy analysis processes in the introductory chapter, in chapter 2 I discuss a debated issue of policymaking, the choice of the social welfare function. I contribute to this debate by proposing an original methodological contribution based on the analysis of the quantitative relationship among different social welfare functional forms commonly used by policy analysts. In chapter 3 I then discuss a behavioral policy to contrast indirect tax evasion based on the use of lotteries. I show that the predictions of my model based on non-expected utility are consistent with observed, and so far unexplained, empirical evidence of the policy success. Finally, in chapter 4 I investigate by mean of a laboratory experiment the effects of social influence on the individual likelihood to engage in altruistic punishment. I show that bystanders’ decision to engage in punishment is influenced by the punishment behavior of their peers and I suggest ways to enact behavioral policies that exploit this finding.

Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

The Role of Multiple Social Categorisation in Promoting the Inclusion in the Human Group of Outgroup Members

Social Housing e Periferie Urbane: Riqualificazione e tecniche Comunicative

Il campo d’interesse della ricerca è stato l’attuale processo di ricentralizzazione del Social Housing nelle periferie urbane in una parte del contesto internazionale, che sembra stia portando le città a ricrearsi e ripensarsi grazie alla presa di coscienza delle differenze esistenti, rispetto al passato, nei nuovi processi di trasformazione nei quali la città è intesa sia come spazio costruito ma anche sociale. In virtù di quest’ultimi due aspetti complementari della città, oggi, il ruolo della periferia contemporanea sembra essere diversamente interpretato, così come gli interventi di riqualificazione di tipo assistenziale - migliorativo tenderebbero a trasformarne i suoi caratteri alla ricerca del “modello di città”. L’interesse alla tematica è inoltre scaturito dalla constatazione che alla base della crisi dei modelli d’intervento pubblico starebbero sia l’insostenibilità economica ma soprattutto l’errata lettura dei bisogni delle famiglie nella loro specificità e diversità e che in tal senso l’eventuale partecipazione della cittadinanza costituirebbe effettivamente una proposta valida, anche per risolvere la crescente domanda abitativa che si pone a livello mondiale. L’obiettivo della ricerca è stato quello d’analizzare, nel contesto internazionale del Social Housing, le caratteristiche di partecipazione e sussidiarietà che connotano particolarmente gli interventi di riqualificazione destinati a famiglie economicamente carenti, nello specifico analizzando i metodi e gli strumenti atti alla comunicazione partecipativa del progetto in aree urbane periferiche italiane e brasiliane. Nella prima e seconda fase della ricerca è stato svolto, rispettivamente, un lavoro di analisi bibliografica sul tema dell’emergenza casa e sulle nuove politiche abitative di sviluppo urbano ed uno specifico sulla tematica della riqualificazione partecipata del Social Housing in aree della periferia urbana, infine nella terza fase sono stati analizzati i casi di studio prescelti dando rilievo all’analisi delle caratteristiche e requisiti prestazionali delle tecniche partecipative di rappresentazione - comunicazione, più idonee ad influenzare positivamente il suddetto processo.

Integration of cognitive and affective processes in perception and decision-making

The relationship between emotion and cognition is a topic that raises great interest in research. Recently, a view of these two processes as interactive and mutually influencing each other has become predominant. This dissertation investigates the reciprocal influences of emotion and cognition, both at behavioral and neural level, in two specific fields, such as attention and decision-making. Experimental evidence on how emotional responses may affect perceptual and attentional processes has been reported. In addition, the impact of three factors, such as personality traits, motivational needs and social context, in modulating the influence that emotion exerts on perception and attention has been investigated. Moreover, the influence of cognition on emotional responses in decision-making has been demonstrated. The current experimental evidence showed that cognitive brain regions such as the dorsolateral prefrontal cortex are causally implicated in regulation of emotional responses and that this has an effect at both pre and post decisional stages. There are two main conclusions of this dissertation: firstly, emotion exerts a strong influence on perceptual and attentional processes but, at the same time, this influence may also be modulated by other factors internal and external to the individuals. Secondly, cognitive processes may modulate emotional prepotent responses, by serving a regulative function critical to driving and shaping human behavior in line with current goals.

The role of proactive coping strategies and perceived health status for Social well-being and life-project in old age.

The latter part of the 20th century was a period characterized by a fundamental demographic transition of western society. This substantial and structural demographic change proposes several challenges to contemporary society and fosters the emergence of new issues and challenges. Among these, none is more crucial than the comprehension of the mechanisms and the processes that lead people to positive aging. Rowe and Kahn’s model of successful aging highlights the interplay between social engagement with life, health, and functioning for a positive aging experience. Other systemic models of successful aging (Kahana et al., 1996; 2003; Stevernik et al., 2006) emphasize the role of internal and external resources for attaining positive aging. Among these, the proactive coping strategies are indicated as important active strategies for avoiding the depletion of resources, counterbalancing the declines and maintaining social and civic involvement. The study has analyzed the role of proactive coping strategies for two facets of positive aging, the experience of a high social well-being and the presence of personal projects in fundamental life domains. As expected, the proactive coping strategies, referred to as the active management of the environment, the accumulation of resources and the actualization of human potentials are confirmed as positive predictors of high level of social well-being and of many personal projects focused on family, culture, leisure time, civic and social participation. Perceived health status give a significant contribution only to the possession of many personal projects. Gender and level of school education give also a significant contribution to these two dimensions of positive aging, highlighting how positive aging is rooted not only in the possession of personal resources, but also in historical models of education and in positive longitudinal chains related to early development.

Social inclusion of vulnerable groups through participatory and emancipatory approaches. Implementing active citizenship and socially innovative actions in the framework of civil & human rights model of disability

The research hypothesis of the thesis is that “an open participation in the co-creation of the services and environments, makes life easier for vulnerable groups”; assuming that the participatory and emancipatory approaches are processes of possible actions and changes aimed at facilitating people’s lives. The adoption of these approaches is put forward as the common denominator of social innovative practices that supporting inclusive processes allow a shift from a medical model to a civil and human rights approach to disability. The theoretical basis of this assumption finds support in many principles of Inclusive Education and the main focus of the hypothesis of research is on participation and emancipation as approaches aimed at facing emerging and existing problems related to inclusion. The framework of reference for the research is represented by the perspectives adopted by several international documents concerning policies and interventions to promote and support the leadership and participation of vulnerable groups. In the first part an in-depth analysis of the main academic publications on the central themes of the thesis has been carried out. After investigating the framework of reference, the analysis focuses on the main tools of participatory and emancipatory approaches, which are able to connect with the concepts of active citizenship and social innovation. In the second part two case studies concerning participatory and emancipatory approaches in the areas of concern are presented and analyzed as example of the improvement of inclusion, through the involvement and participation of persons with disability. The research has been developed using a holistic and interdisciplinary approach, aimed at providing a knowledge-base that fosters a shift from a situation of passivity and care towards a new scenario based on the person’s commitment in the elaboration of his/her own project of life.

Enhancing Workers’ Well-Being. Scientific and social relevance of managing stress in the workplace

Purpose. Despite work-related stress is one of the most studied topic in organizational psychology, many aspects as for example the use of different measures (e.g. subjective and objective, qualitative and quantitative) are still under debate. According to this, in order to enhance knowledge concerning which factors and processes contribute to create healthy workplaces, this thesis is composed by four different studies aiming to understand: a) the role of relevant antecedents (e.g. leadership, job demands, work-family conflict, social support etc.) and outcomes (e.g. workplace phobia, absenteeism etc.) of work-related stress; and b) how to manage psychosocial risk factors in the workplace. The studies. The first study focused on how disagreement between supervisors and their employees on leadership style (transformational and transactional) could affect workers well-being and work team variables. The second and third study used both subjective and objective data in order to increase the quality of the reliability of the results gained. Particularly, the second study focused on job demand and its relationship with objective sickness leave. Findings showed that despite there is no direct relationship between these two variables, job demand affects work-family conflict, which in turn affect exhaustion, which leads to absenteeism. The third study analysed the role of a new concept never studied before in organizational settings (workplace phobia), as a health outcome in the JD-R model, demonstrating also its relationship with absenteeism. The last study highlighted the added value of using the mixed methods research approach in order to detect and analyse context-specific job demands which could affects workers’ health. Conclusion. The findings of this thesis answered both to open questions in the scientific literature and to the social request of managing psychosocial risk factors in the workplace in order to enhance workers well-being.

Assessment and optimization of chemical industrial processes from a life cycle perspective

During the PhD program in chemistry, curriculum in environmental chemistry, at the University of Bologna the sustainability of industry was investigated through the application of the LCA methodology. The efforts were focused on the chemical sector in order to investigate reactions dealing with the Green Chemistry and Green Engineering principles, evaluating their sustainability in comparison with traditional pathways by a life cycle perspective. The environmental benefits associated with a reduction in the synthesis steps and the use of renewable feedstock were assessed through a holistic approach selecting two case studies with high relevance from an industrial point of view: the synthesis of acrylonitrile and the production of acrolein. The current approach wants to represent a standardized application of LCA methodology to the chemical sector, which could be extended to several case studies, and also an improvement of the current databases, since the lack of data to fill the inventories of the chemical productions represent a huge limitation, difficult to overcome and that can affects negatively the results of the studies. Results emerged from the analyses confirms that the sustainability in the chemical sector should be evaluated from a cradle-to-gate approach, considering all the stages and flows involved in each pathways in order to avoid shifting the environmental burdens from a steps to another. Moreover, if possible, LCA should be supported by other tools able to investigate the other two dimensions of sustainability represented by the social and economic issues.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

La convivialità urbana nei quartieri di Milano, Bologna e Roma. Un'analisi mixed-methods sulle Social Streets

Le Social Street sono gruppi di vicini di casa che vogliono ricreare legami di convivialità avendo notato un indebolimento delle relazioni sociali nei loro quartieri. Nascono come gruppi online, tramite la piattaforma Facebook, per materializzarsi in incontri offline andando a costruire legami conviviali grazie pratiche di socialità, inclusività e gratuità. Questa Tesi ha come obiettivo l’analisi dei profili socio-demografici degli Streeter e dei quartieri coinvolti per comprendere come sia possibile creare convivialità e come la variabile urbana intervenga in questi processi. Inoltre, si vuole comprendere le dinamiche di attaccamento al quartiere, gli interessi portati avanti dagli Streeter, il loro profilo civico e il posizionamento di quest’esperienza rispetto all’associazionismo tradizionale. Per perseguire l’obiettivo della ricerca, sono state studiate le tre città che vedono la maggiore presenza di Social Street: Milano, Bologna, Roma. La ricerca ha previsto sia un’analisi degli Streeter grazie a un questionario online replicato in tutti i contesti. Inoltre, sono state realizzate 131 interviste ad amministratori e fondatori di Social Street e condotte osservazioni etnografiche e netnografiche. I risultati mostrano come gli Streeter siano appartenenti alle classi medio-alte, tra trenta e cinquanta anni, che hanno sperimentato la mobilità tra un quartiere e l’altro o tra diversi contesi nazionali ed internazionali e trovano nelle Social Street un modo per creare legami di vicinato che hanno perso nei loro trasferimenti. Gli stessi quartieri dove si diffondono le Social Street sono agiati e vi è una buona corrispondenza tra Streeter e modello della centralità sociale elaborato da Milbrath (1965) per cui anche la partecipazione civica è molto sentita tra gli aderenti alle Social Street. Il contributo di questa Tesi al dibattito sociologico risiede nell’aver offerto un’analisi empirica di un’azione collettiva a livello urbano, quella delle Social Street, mostrando come vi sia circolarità tra azione e contesto grazie all’azione mutualistica conviviale.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Cleavage Politics in Changing Times. Political Realignment Processes in Western European Countries

The dissertation fits the political realignment literature and aims to pro-vide further insights into cleavage politics by investigating voting behaviour in the Western European countries’ national elections. In particular, the dis-sertation focuses on the class and value voting patterns and on the change of these patterns in different countries and over the course of time. Peculiar pro-cesses affected all Western European party systems: whilst the «traditional» cleavage theory accounts for National and Industrial revolutions, those pro-cesses assumed to constitute the «societal modernization» determined chang-es in electoral competitions that questioned the relevance of individuals’ so-cial positions to study electoral preferences. Since the associations between social positions and voting behaviour underpin the so-called political cleav-age, the dealignment perspective assumes them to have been eroding since the second half of the XX century. On the other hand, the realignment perspective argues that the cleavage theory still accounts for individuals’ vote choices: of the four «traditional» cleavages, this perspective hypothesizes new class vot-ing patterns and alignments between electoral preferences and a new line of conflict, that is based on values. The dissertation provides a theoretical ac-count of the realignment of the class cleavage and a new conceptualization of value voting. Then, class and value voting patterns are explored. The analyses employ European Social Survey data and detect general and country-specific patterns. The dissertation adopts a mediation perspective and aims to observe how class voting patterns change when controlling for value orientations. The results are provided with a sensitivity analysis, indeed two versions of the measures computed for value orientations are compared. The findings show that social class continues to affect voting behaviour and that value orienta-tions both mediate this effect and affect electoral preferences.