Una visione sistemica per i silos digitali del PNRR

Il PNRR ha offerto all’Italia un’opportunità di investire nella trasformazione digitale della sanità, individuando e investendo su alcuni sistemi verticali privi di una visione d’insieme. Gli autori propongono lo sviluppo di una visione strategica di ecosistema digitale che si basa innanzitutto su un preciso modello di servizi sanitari costruito con logiche di presa in carico dei pazienti e di comunicazione bidirezionale SSN-cittadini. La visione d’insieme permette di caratterizzare i cinque sistemi digitali verticali supportati dal PNRR: 1) la gestione dei PAI, 2) l’FSE 2.0, 3) l’evoluzione dei CUP, 4) i Clinical Decision Support Systems (CDSS), 5) la telemedicina. Oltre a delineare le caratteristiche di queste componenti e le loro interconnessioni in una visione d’insieme, si propone un percorso di gestione del cambiamento a livello regionale e aziendale

Essays on the Material Origins of Political Change

This dissertation explores how automation, technological change, and economic transformations shape political dynamics in post-industrial societies. It examines how shifts in material conditions influence both the demand and supply sides of politics, with evidence drawn from Western Europe and the United States. The first essay addresses methodological issues in studying the determinants of the globalization backlash, highlighting the bias introduced by post-treatment variables in regressions comparing economic and cultural drivers of voting behavior and providing additional evidence on the culture-economy nexus. The second essay investigates the impact of automation on trade unions in Western Europe, finding that regions more exposed to automation experience a decrease in union density, primarily driven by a broader labor market shift away from unionized industries. The third essay offers a structural explanation for the changing composition of political elites, examining how automation influences the likelihood of different social groups pursuing political office. Drawing on multiple sources of data on political candidates and occupational backgrounds in the US, the analysis reveals that areas with greater exposure to automation experience a decline in candidates from occupations most impacted by technological change. This trend contributes to the underrepresentation of working-class and automatable workers in politics

A quest for knowledge

Is more novel research always desirable? We develop a model in which knowledge shapes society’s policies and guides the search for discoveries. Researchers select a question and how intensely to study it. The novelty of a question determines both the value and difficulty of discovering its answer. We show that the benefits of discoveries are nonmonotone in novelty. Knowledge expands endogenously step-by-step over time. Through a dynamic externality, moonshots—research on questions more novel than what is myopically optimal—can improve the evolution of knowledge. Moonshots induce research cycles in which subsequent researchers connect the moonshot to previous knowledge

Key audit matters as insights into auditors’ professional judgement: evidence from the European Union

The European Union (EU) Regulation 537/2014 introduced the mandatory disclosure of Key Audit Matters (KAMs) within an auditor’s report, with the aim of increasing the informational value of these reports. Extant research, however, shows contrasting results as to whether KAM disclosure is providing relevant information to stakeholders. Moreover, concerns have been raised about unintended consequences from KAM disclosure, with respect to the process that leads to the issuance of the audit report. Using a sample of 6,164 firm-year observations for the period 2017–2021, related to 1,660 unique firms listed in all EU Member States, we find that the number of KAMs is positively associated with audit fees, audit report lags and the probability that an opinion different from the standard unqualified opinion is issued. Moreover, we document that both KAMs related to entity-level and account-level risks are positively associated with audit fees, whereas only entity-level KAMs drive the positive association with audit report lags and the issuance of a modified opinion. Our research speaks directly to EU legislators, the International Auditing and Assurance Standards Board, the US Public Company Accounting Oversight Board, and any other regulators around the globe that have mandated the disclosure of KAMs within audit reports

The impact of account-based marketing approach in shaping impactful narratives on sustainability and resilience

This paper aims to assess the effectiveness of the impact of the Account-Based Marketing (ABM) approach in enhancing stakeholder engagement and communication for sustainability and resilience initiatives in the domain of Operations and Supply Chain Management. We employ exploratory research in assessing the following five key factors: benchmarking, innovation, knowledge sharing, network collaboration, and strategic planning. Our analysis indicates that the ABM approach is a valuable tool that efficiently communicates a core company's main programs with stakeholders by providing benchmarking and knowledge-sharing opportunities. Moreover, ABM enhances innovation capabilities, regardless of the experience level of the target audiences. Additionally, ABM fosters cooperation among the partners in a value chain and helps stakeholders gain a better understanding of the business network’s sustainability and resilience goals, enabling them to align their strategic plans accordingly. Furthermore, sustainability managers found ABM valuable for increasing network collaboration, a crucial factor in successfully implementing sustainability initiatives

Economic evaluations of health service interventions targeting patients with multimorbidities: a scoping literature review

Introduction: Multimorbid patients have been growing, leading to an exponential increase in healthcare costs and patterns of resource utilization. Despite the heightened interest toward integrated care programs as a response to the complex need of multimorbid patients, economic evaluations of these programs remain scarce. This work investigated the economic evaluations of service interventions targeting multimorbid patients, to identify the characteristics of these programs and the methods applied to their evaluation. Methods: We conducted a scoping review of papers published between 2010 and 2021 on PubMed, Science Direct, EconLit and Web Of Science. The search strategy was built around three keyword blocks: service interventions, multimorbidity, economic evaluations. We selected economic evaluations of service interventions delivered through multiple care settings and targeting patients with 2+ chronic conditions. Results: Twenty-five articles were included. Interventions were categorized as organizational-type versus patient-oriented. The selected studies often targeted patients with one chronic disease, associated with a mental disorder, like depression or anxiety. Included studies were mostly cost-utility analyses conducted with the healthcare perspective. Discussions and conclusions: This work confirmed that economic evaluations of service interventions for multimorbid patients are limited in number. This could suggest that decision-making regarding the delivery of healthcare services for multimorbid patients may not always be based on a solid evidence base. More economic analyses are needed to inform evidence-based coverage decision-making

The power of artificial intelligence for managing pandemics: a primer for public health professionals

Artificial intelligence (AI) applications are complex and rapidly evolving, and thus often poorly understood, but have potentially profound implications for public health. We offer a primer for public health professionals that explains some of the key concepts involved and examines how these applications might be used in the response to a future pandemic. They include early outbreak detection, predictive modelling, healthcare management, risk communication, and health surveillance. Artificial intelligence applications, especially predictive algorithms, have the ability to anticipate outbreaks by integrating diverse datasets such as social media, meteorological data, and mobile phone movement data. Artificial intelligence-powered tools can also optimise healthcare delivery by managing the allocation of resources and reducing healthcare workers' exposure to risks. In resource distribution, they can anticipate demand and optimise logistics, while AI-driven robots can minimise physical contact in healthcare settings. Artificial intelligence also shows promise in supporting public health decision-making by simulating the social and economic impacts of different policy interventions. These simulations help policymakers evaluate complex scenarios such as lockdowns and resource allocation. Additionally, it can enhance public health messaging, with AI-generated health communications shown to be more effective than human-generated messages in some cases. However, there are risks, such as privacy concerns, biases in models, and the potential for 'false confirmations', where AI reinforces incorrect decisions. Despite these challenges, we argue that AI will become increasingly important in public health crises, but only if integrated thoughtfully into existing systems and processes

An alternative approach for nonparametric analysis of random utility models

We readdress the problem of nonparametric statistical testing of random utility models proposed in Kitamura and Stoye (2018). Although their test is elegant, it is subject to computational constraints which leaves execution of the test infeasible in many applications. We note that much of the computational burden in Kitamura and Stoye's test is due to their test defining a polyhedral cone through its vertices rather than its faces. We propose an alternative but equivalent hypothesis test for random utility models. This test relies on a series of equality and inequality constraints which defines the faces of the corresponding polyhedral cone. Building on our testing procedure, we develop a novel axiomatization of the random utility model