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The latest financial crisis has stressed the need of understanding the world financial system as a network of interconnected institutions, where financial linkages play a fundamental role in the spread of systemic risks. In this paper we propose to enrich the topological perspective of network models with a more structured statistical framework, that of Bayesian Gaussian graphical models. From a statistical viewpoint, we propose a new class of hierarchical Bayesian graphical models that can split correlations between institutions into country specific and idiosyncratic ones, in a way that parallels the decomposition of returns in the well-known Capital Asset Pricing Model. From a financial economics viewpoint, we suggest a way to model systemic risk that can explicitly take into account frictions between different financial markets, particularly suited to study the ongoing banking union process in Europe. From a computational viewpoint, we develop a novel Markov chain Monte Carlo algorithm based on Bayes factor thresholding.

In recent years, companies have started to open up their Research and Development (R&D) and their innovation activities to external partners. They aim to access new resources and capabilities and to gain shorter time-to-markets. However, as several studies have shown, it can be difficult to manage collaborative (open) innovation projects to achieve desired outcomes. Starting from this premise, the paper investigates how project stakeholder management is different in open innovation projects from traditional R&D projects.

The study has a qualitative nature and is based on the interpretative paradigm with an inductive orientation. The paper leverages interviews with experts involved in open innovation projects conducted in two Science and Technology Parks between Sweden and Italy.

The analysis shows how companies manage multiple stakeholders in open innovation projects and the peculiarities project stakeholder management faces in these projects when compared with traditional R&D projects. The paper shows how the relationships with external partners in open innovation projects are regulated by informal identification and analysis frameworks, which reduce the tensions deriving from these multiple collaborations. In addition, it underlines a set of good practices, and project management aspects for developing effective absorptive capacity of know-how, resources, and capabilities from external stakeholders in open innovation projects.

The paper analyzes for the first time how companies manage multiple stakeholders in open innovation projects in a different way from traditional R&D projects. Furthermore, the paper introduces a shift in the focus of the analysis: it focuses on the level of the project conducted through multiple collaborations instead of on the level of the firms involved in the project. Finally, the paper integrates open innovation research with project management research.

The concept of modularity has gained considerable traction in technology studies as a way to conceive, describe, and innovate complex systems, such as product design or organizational structures. In the recent literature, technological modularity has often been intertwined with business model innovation, and scholarship has started investigating how modularity in technology affects changes in business models, both at the cognitive and activity system levels. Yet we still lack a theoretical definition of what modularity is in the business model domain. Business model innovation also encompasses different possibilities of modelling businesses, which are not clearly understood nor classified. We ask when, how, and if modularity theory can be extended to business models in order to enable effective and efficient modelling. We distinguish theoretically between modularity for technology and for business models, and investigate the key processes of modularization and manipulation. We introduce the basic operations of business modelling via modular operators adapted from the technological modularity domain, using iconic examples to develop an analogical reasoning between modularity in technology and in business models. Finally, we discuss opportunities for using modularity theory to foster the understanding of business models and modelling, and develop a challenging research agenda for future investigations.

In this chapter I discuss judicial contributions to Italian penality. I look at the penal incentives produced by interactions between judicial and political classes, and ask whether judges and prosecutors have been forces for punitiveness or moderation. I discuss the relevance of the Italian case for broader analyses of Western penality.

My chapter offers a political-sociological account of judicial contributions to punishment. I analyse the penal incentives created by different national institutional set-ups, specifically addressing judicial contributions to penality using a framework developed by Joachim Savelsberg and Nicola Lacey. The framework examines judicial structure in the institutional context looking at the penal implications of bureaucratisation of the judiciary and the capacity for co-ordination between judges and politicians. I include judicial legitimacy as an additional dimension in this framework.

I conclude that the Italian judiciary have been forces for punitiveness and moderation. Their contributions can be systematised by looking at the waxing and waning of judicial legitimacy, and the consequent expansion and contraction of judicial powers. I claim that judicial legitimacy is also relevant to other (‘non-Italian’) analyses of judicial contributions to contemporary Western penality.

By adding legitimacy to investigations of judicial contributions to penality I provide an organising principle with which to analyse the penal role of Italian judicial actors. I thus allow Italy to be kept in conversation with existing comparative models, without assuming that it either conforms to the models entirely, or that the models should otherwise be eschewed. I use the Italian case to demonstrate the relevance of legitimacy when analysing judicial contributions to Western penality, arguing that changing legitimacy affects the terms and effect of interaction between judicial and political classes.

In this chapter we investigate whether the pricing of IPOs on Europe’s new stock market differs from that of IPOs on main market segments. We report a 22.3 percentage point difference in the average first-day return of new market IPOs (34.3%) and the average first-day return of main market IPOs (12%). We show that reduced incentives to control wealth losses and different firm and offer characteristics partially explain the higher average first-day return on new market segments. We also find that the bundling of IPO deals has been more important to control underpricing costs on new market than on main market segments.

The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017.

The authors use a dynamic spatial Durbin model that enables to explore the direct and indirect effects over the short and long run and the transmission channels of the contagion.

The results show how contagion emerges through physical and financial market links between banks. This finding implies that a bank can fail because people expect other related financial institutions to fail as well (self-fulfilling crisis). The study provides statistically significant evidence of the presence of credit risk spillovers in CDS markets. The findings show that equity market dynamics of “neighbouring” banks are important factors in risk transmission.

The research provides a new contribution to the analysis of EZ banking risk contagion, studying CDS spread determinants both under a temporal and spatial dimension. Considering the cross-dependence of credit spreads, the study allowed to verify the non-linearity between the probability of default of a debtor and the observed credit spreads (credit spread puzzle). The authors provide information on the transmission mechanism of contagion and, on the effects among the largest banks. In fact, through the study of short- and long-term impacts, direct and indirect, the paper classify banks of systemic importance according to their effect on the financial system.

The purpose of this paper is to provide an empirical examination of factors associated with over-education among PhD graduates in Italy.

The investigation is based on recently released data collected by the Italian National Institute of Statistics by means of interviews with a large sample of PhD recipients, carried out a few years after they obtained their PhD degree. The author measured the mismatch between the current job and previous PhD studies using two direct subjective evaluations of over-education, which distinguish between the usefulness of the PhD title to get the current job position and to perform the current work activities. Even if the incidence of over-education varies according to the measurement applied, the author found that it is highly widespread among PhD recipients. The econometric analyses are aimed at identifying factors associated with over-education and are based on the standard probit model and the bivariate probit model with sample selection which allows to control for self selection into employment.

The results show that over-education is significantly correlated with: first, a number of PhD-related variables, such as the scientific field of study, having attended courses or visiting periods abroad; second, some job-related characteristics, such as working in the academia or being mainly involved in research-related activities; third, the channel of access to the job; and fourth, residential location.

This paper contributes to the literature focusing on job-education mismatch by providing, to the best of the author’s knowledge, the first empirical analysis of over-education among PhD recipients in Italy; moreover, it provides some useful insights to evaluate the professional doctoral graduates in Italy.