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This paper seeks to analyse the characteristics of performance measurement and management systems in public organizations and to highlight the main factors driving performance in this sector.

A literature review is carried out in order to outline the main issues related to the adoption and implementation of performance measurement and management systems in public organizations.

The paper provides better information on the performance measurement and management systems in public organizations, by analyzing the performance dimensions, the use of performance measures and the factors influencing the implementation of the performance management process.

The paper presents a model for driving the implementation of a performance measurement system within public organizations and identifies the main factors influencing this process. The paper is conceptual in its nature and will be further developed through an empirical research investigating the role played by the identified factors.

The paper identifies the factors driving the performance management process in public organizations.

The purpose of this paper is to investigate the main challenges related to the use of performance measures in public organisations in order to identify the factors affecting the adoption and implementation of performance measurement systems. The empirical analysis is focused on the Italian Institutions.

This paper is based on a two‐stage research process. First a systematic literature review has been carried out with the aim of identifying the factors enabling and hampering the adoption of performance measures in public organisations. Second on the basis of the results of the desk analysis a survey‐based investigation has been implemented involving Italian public institutions.

The paper provides a twofold contribution. It analyses the factors affecting the adoption and implementation of performance measures in public organisations. On the other hand it presents the descriptive statistical results of the survey highlighting the position of Italian institutions with regard to the use of performance measures. This allows an assessment of the cultural, political and rational factors influencing the deployment of measures in Italian institutions.

The conceptual analysis has a general validity, whilst the empirical investigation is focused on the Italian context. The framework proposed in this paper allows the identification of the factors affecting the exploitation of performance measures in public organisations. It can be applied in any public organisational context. The empirical evidence is context‐specific and related, in particular, to the Italian local governments. Some main managerial implications are addressed that can support managers to apply performance measurement systems in public organisations.

The paper sheds light on a fundamental issue related to the implementation of performance measurement systems in public organisations. It addresses what are the factors that matter in order to make sure that performance measures are effectively employed to run everyday working activities. Indeed in many public organisations PMSs are something nice to have, but with little practical application.

Unilever‐Sagit is the main Italian competitor in the Italian frozen food market. The company has very recently innovated its distribution channel by creating a private Electronic Data Interchange (EDI) network. Examines the effects generated by the implementation of EDI technology on supply chain management. Discusses the theoretical aspects of the impact of EDI on strategic management of logistics and examines the Unilever‐Sagit EDI network in detail.

The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

Smart manufacturing (SM) lies at the core of Industry 4.0. Uniform adoption of SM across business partners is crucial to exploit its value creation potential. However, firms' willingness to invest in SM is limited by insufficient or inconclusive evidence on its performance-related benefits. To close this gap, this paper develops and tests a model linking SM adoption to firms' financial performance. Improvements along the four dimensions of operational performance (i.e. cost quality, delivery and flexibility) mediate this relation.

This study follows an empirical research approach. In particular, survey data from 234 automotive component suppliers are analyzed via covariance-based structural equation modeling to explore the link between SM adoption and operational performance. Survey data are then matched with secondary data from balance sheets of 81 firms to investigate the impact of SM on financial performance via partial least square structural equation modeling.

Findings highlight that adoption of SM results in improvements in cost, quality, delivery performance, thus suggesting that SM is a mean to overcome performance trade-offs. Improvements in operational performance enabled by SM do not give rise to superior financial performance, thus implying that SM might support firms in maintaining the competitive position in the market, but could be insufficient to generate higher margin.

Results have implications for SM research and for manufacturing executives engaged in the adoption of SM, as they provide a detailed analysis of the impact of SM on operational performance and clarify the effect that SM adoption has on financial performance.

As unemployment rises across the European Union (EU), it is important to understand the extent to which the incomes of the new unemployed are protected by tax–benefit systems and to assess the cost pressures on the social protection systems of this increase in unemployment. This chapter uses the EU tax–benefit model EUROMOD to explore these issues, comparing effects in five EU countries. It provides evidence on the differing degrees of resilience of the household incomes of the newly unemployed due to the variations in the protection offered by the tax–benefit systems, according to whether unemployment benefit is payable, the household situation of the unemployed person and across countries.

Analysis of the guidelines on investment recommendations (“Guidelines”) issued by the Italian Securities and Exchange Commission (“CONSOB”) on the application of the EU Regulation No. 596/2014, the Market Abuse Regulation (“MAR”).

This article focuses on the Guidelines issued with the aim to facilitate the identification of unlawful conducts of firms and individuals disseminating investment recommendations on financial instruments or issuers. In particular, the definition of investment recommendations as per MAR, the duties of persons providing such information and also the investigative powers conferred to CONSOB in order to prevent the dissemination of false or misleading information to the public are examined in detail.

The Guidelines are an important interpretative tool for firms and individuals providing investment recommendations on financial instruments or issuers. They further determine the duties deriving from MAR and the investigative powers attributed to CONSOB.

This article provides useful information on MAR and practical guidance on the applicability of this regulation to persons and firms providing investment recommendations on financial instruments or issuers.

The expectations surrounding innovation as the principal mean by which firms gain a sustainable advantage while simultaneously alleviating social problems are tremendous. However, in the process of developing innovation, many small entrepreneurs, SMEs, as well as large firms struggle to access the necessary finances in order to further develop their innovative projects. The purpose of this paper is to underline some of the most recent tools and practices used to finance novelty.

This paper synthetizes some thoughts about the financing of novelty and proposes a research agenda based on trends highlighted in the recent literature.

This paper pinpoints recent advances in finance applied to the field of innovation. In particular, this paper highlights both promising developments as well as the need for more research in this area in order to untangle the links between creativity and financial support, the financing of innovation in developing countries, accounting and evaluation of ideas.

The importance of developing innovation and easing access to resources has societal implications. The development of education around finance and entrepreneurship, as well as improving literacy of citizens in these fields could yield a more open view on innovation and financial supports in the future.

Financing novelty, evaluating projects and facing uncertainty are among the most difficult decisions investors take. This paper combines many dimensions of innovation and finance to construct an overview of current and future practices within both domains.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.