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Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.

This paper proposes an Information and Communication Technology (ICT) platform to increase the sustainability and resilience of smallholders to face supply chain disruptions in the event of COVID-like crises. The platform facilitates interactions between smallholders and buyers, workers and freight transport companies in agri-food ecosystems. Furthermore, this research work presents the implementation of the freight transport companies’ platform module.

The research work begins with a literature review aiming at analyzing current available ICT solutions supporting smallholders and other actors in the agri-food supply chain. This analysis identifies the research gaps which have to be filled by the platform. Then, the authors proceed with the analysis of the operational scenarios of each platform actor by interacting with experts and operators working in the agri-food sector. The results of such analysis resulted in a comprehensive, unambiguous and consistent set of specification being used to define the platform structure and modules architecture. The platform modules have been developed by using the web-application framework Laravel.

Preliminary tests show that the proposed platform is usable and promises to improve the resilience and economic, social and environmental sustainability of agri-food supply chains, with a focus on smallholders.

The research work allows players in the agri-food supply chain and in particular small local producers to react and mitigate the impact of COVID-like crises through development of a platform in which smallholders, citizens (buyers and workers) and freight transport companies are simultaneously present.

The objective of this chapter is to introduce the reader to Spatial Health Econometrics (SHE). In both micro and macro health economics there are phenomena that are characterised by a strong spatial dimension, from hospitals engaging in local competitions in the delivery of health care services, to the regional concentration of health risk factors and needs. SHE allows health economists to incorporate these spatial effects using simple econometric models that take into account these spillover effects. This improves our understanding of issues such as hospital quality, efficiency and productivity and the sustainability of health expenditure of regional and national health care systems, to mention a few.

The purpose of this paper is to understand the role played by accounting in managing an early nineteenth century lunatic asylum in Palermo, Italy.

The paper is informed by Foucault’s studies of lunatic asylums and his work on governmentality which gave prominence to the role of statistics, the “science of the State”.

This paper identifies a number of roles played by accounting in the management of the lunatic asylum studied. Most importantly, information which formed the basis of accounting reports was used to describe, classify and give visibility and measurability to the “deviance” of the insane. It also legitimated the role played by lunatic asylums, as entrusted to them in post-Napoleonic early nineteenth century society, and was a tool to mediate with the public authorities to provide adequate resources for the institution to operate.

This paper encourages accounting scholars to engage more widely with socio-historical research that will encompass organisations such as lunatic asylums.

This paper provides, for the first time, a case of accounting applied to a lunatic asylum from a socio-historical perspective.

The paper aims to provide a semiotic interpretation of the role played by entanglement in quantum-based models aimed to information retrieval and suggests possible improvements. Actual models are capable of retrieving documents relevant to a query composed of a keyword and its acceptation expressed by a given context. The paper also considers some analogies between this technique and quantum-based approaches in other disciplines to discuss the consequence of this quantum turn, as epistemology and philosophy of language are concerned.

We use quantum geometry to design a formal model for textual semiotics. In particular, the authors refer to Greimas’s work on semantics and information theory, to Eco’s writings on semantic memory and to Lotman’s work on a cybernetic notion of culture.

Quantum approaches imply a particular point of view on meaning. Meaning is not a real, positive quality of a given word. It is a net of relations constructed in the text, whose value is progressively determined during the reading process. Furthermore, reading is not a neutral operation: to read is to determine meaning. If it is said that, from a general semiotic point of view, meaning is stored in quantum semantic memories and is read/written by semantic machines, then the operation of “reading/writing” is analogous to the operation of measuring in quantum theory: in other terms, meaning is a value, and this implies an instance (not necessarily human) according to which values are valuable.

The authors are not proposing a complete quantum semantics. At the present, quantum information retrieval can detect the presence of semantic relations. The authors suggest a way to characterize them, leaving open the problem on how to formalize the document as a vector in four-state semantic space.

A quantum turn shows deep semiotic implications on the approach to language, which shows an immanent semantic organization not reducible to syntax and morphology. This organization is probabilistic and indeterministic and explains to what extent text fixes the meaning of its lexical units.

In the authors’ perspective, signification is not the exclusivity of a human subject. Criticizing Turing test, the great semiotic and cybernetic scholar Jurij Lotman wrote that if we identify “intelligent” and “human”, we raise the failings of an actual form of intelligence to the rank of an essential characteristic. On this line, meaning is considered as a feature of social, artificial and biological systems.

The adoption of quantum formalism seems in line with cybernetic framework, involving a probabilistic, non-cartesian point of view on meaning aimed to critically discuss the human–machine relation. Furthermore, Quantum theory (QT) implies a phenomenological point of view on the conditions of possibility of meaning.

Health is a fundamental populations’ need and an integral part of the socio-economic development of a country. However, it is required to explain the growing role of the private sectors in addressing various health care needs. The purpose of this paper is to analyse potential contribution, criticalities and conditions of success of public-private partnership (PPP) as a strategy to face the complexity of nationally relevant Italian and Indian service systems.

The methodology is built upon the basis of the viable systems approach (VSA) integrated with the fundamental interpretative elements of service science and service-dominant logic to contextualize interpretation to the management of service systems benefitting from recent advances in these research fields.

A VSA-based general framework of reference is built that is useful for analysing any relational context in which different aims and expectations need to be harmonized to make the collaboration effective. On the basis of this framework, first insights on Italian and Indian health care PPPs are proposed, highlighting key elements of analysis and criticalities that may challenge a positive conclusion on health care PPPs.

The implications of the study are both theoretical and practical. From a theoretical perspective, the study contributes to the scholarly understanding of complex health care system in Italy as well as in India with particular reference to the public-private collaboration phenomenon. It also suggests theoretical approaches in the form of a generic VSA-based framework as applicable. From a practical perspective, the study stimulates managers to a critical reflection about current health care management approaches which are reflected in the adoption of PPPs solutions.

The paper discusses relevant worldwide decision-making challenges, such as the equality in the populations’ access to health service, suggesting managers the way to create conditions of consonance among the diverse stakeholders for a successful health care PPPs.

The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective.

A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework.

This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected.

The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases.

This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

Purpose: In this chapter, we examine the National Health Service (NHS) and Adult Social Care (ASC) in England, focussing on policies that have been introduced since 2000 and considering the challenges that providers face in their quest to provide a high standard and affordable health service in the near future.

Methodology/Approach: We discuss recent policy developments and published analysis covering innovations within major aspects of health care (primary, secondary and tertiary) and ASC, before considering future challenges faced by providers in England, highlighted by a 2017 UK Parliament Select Committee.

Findings: The NHS and ASC system have experienced tightening budgets and serious financial pressure, with historically low real-terms growth in health funding from central government and local authorities. Policymakers have tried to overcome these challenges with several policy innovations, but many still remain. With large-scale investment and reform, there is potential for the health and social care system to evolve into a modern service capable of dealing with the needs of an ageing population. However, if these challenges are not met, then it is set to continue struggling with a lack of appropriate facilities, an overstretched staff and a system not entirely appropriate for its patients.

This chapter reviews graphical modeling techniques for estimating large covariance matrices and their inverse. The chapter provides a selective survey of different models and estimators proposed by the graphical modeling literature and offers some practical examples where these methods could be applied in the area of health economics.

Application of operations management in healthcare is particularly promising to improve the overall organisational performance, although the Italian system is behind in introducing related techniques and methods. One of the recent experiments in healthcare is the implementation of “Lean Thinking”. The purpose of this paper is to investigate which exogenous forces are driving knowledge transfer on Lean, both in the private and public healthcare sectors.

Informed by institutional sociology (DiMaggio and Powell, 1983; Powell and DiMaggio, 1991), the paper builds on the case study methodology (Yin, 2013) to elucidate the environmental pressures that are encouraging the adoption of Lean thinking by Italian hospitals and Local Health Authorities.

The study highlights the economic, coercive, mimetic and normative pressures that are triggering the adoption of Lean thinking in the Italian National Health System (INHS). At the same time, the authors reveal the pivotal importance and innovative roles played by diverse prominent key-actors in the different organisations investigated.

Considering that little is known to date regarding which exogenous forces are driving the transfer of knowledge on Lean, especially in the public healthcare sector, the paper allows scholars to focus on patterns of isomorphic change and will facilitate managers and policy makers to understand exogenous factors stimulating the transfer of Lean thinking and the subsequent innovation within health organisations and systems.