Search results

Inter-municipal cooperation (IMC) has been increasingly adopted worldwide to tackle issues of size and cost reduction in the provision of public services. Although the determinants of cooperation among municipalities have been widely investigated in the prior literature, little is known about the link between a municipality's financial health and that of the supra-municipal entity formed under IMC. The purpose of this study is to fill this research gap by analyzing the case of municipal unions (MUs) in Italy.

A quantitative approach has been used, applying OLS and quantile regression on financial information and other variables of municipalities and their MUs.

The study finds that the most important condition of operation for IMC, that is, financial sustainability, is directly linked to the financial health of member municipalities and the functional integration reached with the supra-municipal entity.

The study analyses all MUs in Italy, focusing on the factors affecting their financial sustainability. In doing so, it sheds light on the factors that influence the financial sustainability of second-tier governments, which rely on external funding.

This paper explores how global pandemic crises affect the financial vulnerability of municipalities.

This paper is developed from the relevant literature an analytical framework to examine municipal financial vulnerability before a global pandemic crisis and in its immediate aftermath by mapping and systematizing its dimensions and sources. To illustrate how it can be used and evaluate its robustness and flexibility, such a tool was applied to Portugal and Italy, two countries that particularly suffered from the Covid-19 crisis.

The application of the analytical framework has shown how financially vulnerable municipalities are to global pandemic crises. Financial vulnerability relates to issues ranging from institutional design to internal financial conditions and the perception of the capacity to cope with a crisis. Results further reveal that vulnerability has an inherent contingent nature in time and space and can lead to paradoxical outcomes.

This paper provides a tool that can be useful for both academic and public policy purposes, to further appreciate municipal financial vulnerability, especially during crises.

Municipalities can use the framework to better manage their financial vulnerability, strengthening their anticipatory and copying capacities, while oversight authorities can use it to help municipalities become less financially vulnerable or, at least, more aware of their financial vulnerability.

Municipal financial vulnerability to global shocks has not been explored extensively. Also, the Covid-19 pandemic is different from previous global crises as it affected society overnight with the implementation of lockdown and social distancing measures.

Many public sector organizations use outsourcing in an effort to take advantage of a private contractor’s experience and economies of scale, thereby allowing them to provide high quality public services at a low cost. Although it has received considerable attention in the public policy and management literature for almost three decades, outsourcing has not always achieved a municipality’s goals. To address the strategic and managerial issues of outsourcing, we combine a literature review with data obtained from a field study of three Italian municipalities. The resulting framework can assist public sector managers to determine both the services that are the best candidates for outsourcing, and the issues that must be considered in managing the chosen vendors to guarantee high quality and cost-effective results.

The purpose of this paper is to explain how public sector accounting has changed and is changing due to public governance development.

This paper conducts a traditional literature review based on selected studies in the fields of accounting, public administration and management. The aim of the review is to explain how diverse forms of public governance influence the fate of public sector accounting, including accountability, performance measurement, budgeting and reporting practices.

Public governance is developing into more inclusive but also complex forms, resulting in network, collaborative and digital governance. Consequently, the focus and practices of public sector accounting have changed, as reflected in new types of accountability, performance measurement, budgeting and reporting practices.

Drawing upon literature from different fields enables a deeper understanding of the changes in public sector accounting. Nevertheless, the intention is not to execute a systematic literature review but to provide an overview and resolve the scattered body of knowledge generated by previous contributions. The areas of risk management and auditing were not included and deserve further attention.

This paper discusses the need to continually redefine and reassess public sector accounting practices, by recognising the interdependencies between different actors, citizens and digital technologies.

This study aimed to assess the potential of the Clinical Dementia Rating (CDR) Scale in the prognosis of dementia in elderly subjects.

Dementia staging severity is clinically an essential task, so the authors used machine learning (ML) on the magnetic resonance imaging (MRI) features to locate and study the impact of various MR readings onto the classification of demented and nondemented patients. The authors used cross-sectional MRI data in this study. The designed ML approach established the role of CDR in the prognosis of inflicted and normal patients. Moreover, the pattern analysis indicated CDR as a strong cohort amongst the various attributes, with CDR to have a significant value of p < 0.01. The authors employed 20 ML classifiers.

The mean prediction accuracy varied with the various ML classifier used, with the bagging classifier (random forest as a base estimator) achieving the highest (93.67%). A series of ML analyses demonstrated that the model including the CDR score had better prediction accuracy and other related performance metrics.

The results suggest that the CDR score, a simple clinical measure, can be used in real community settings. It can be used to predict dementia progression with ML modeling.