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This study aims to characterize the June 2020 COVID-19 outbreak at San Quentin California State Prison and to describe what made San Quentin so vulnerable to uncontrolled transmission.

Since its onset, the COVID-19 pandemic has exposed and exacerbated the profound health harms of carceral settings, such that nearly half of state prisons reported COVID-19 infection rates that were four or more times (and up to 15 times) the rate found in the state’s general population. Thus, addressing the public health crises and inequities of carceral settings during a respiratory pandemic requires analyzing the myriad factors shaping them. In this study, we reported observations and findings from environmental risk assessments during visits to San Quentin California State Prison. We complemented our assessments with analyses of administrative data.

For future respiratory pathogens that cannot be prevented with effective vaccines, this study argues that outbreaks will no doubt occur again without robust implementation of additional levels of preparedness – improved ventilation, air filtration, decarceration with emergency evacuation planning – alongside addressing the vulnerabilities of carceral settings themselves.

This study addresses two critical aspects that are insufficiently covered in the literature: how to prepare processes to safely implement emergency epidemic measures when needed, such as potential evacuation, and how to address unique challenges throughout an evolving pandemic for each carceral setting.

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best form of variable for this problem. Because of MapReduce’s unsuitability for iteration problems involved in developing CB-FPMs, various BDA initiatives for iteration problems were identified. A BDA framework for developing CB-FPM was proposed. It was validated by using 150,000 datacells of 30,000 construction firms, artificial neural network, Amazon Elastic Compute Cloud, Apache Spark and the R software. The BDA CB-FPM was developed in eight seconds while the same process without BDA was aborted after nine hours without success. This shows the issue of not wanting to use large dataset to develop CB-FPM due to tedious duration is resolvable by applying BDA technique. The BDA CB-FPM largely outperformed an ordinary CB-FPM developed with a dataset of 200 construction firms, proving that use of larger sample size with the aid of BDA, leads to better performing CB-FPMs. The high financial and social cost associated with misclassifications (i.e. model error) thus makes adoption of BDA CB-FPMs very important for, among others, financiers, clients and policy makers.

The unprecedented SARS-CoV-2 (COVID-19) pandemic has further constrained the budgets of governments worldwide for delivering their much-needed infrastructure. Consequently, public-private partnerships (PPPs), with the private sector's investment and ingenuity, would appear to be an increasingly popular alternative. Value for money (VfM) has become the major criterion for evaluating PPPs against the traditional public sector procurement and, however, is plagued with controversy. Hence, it is important that governments compare and contrast their practice with similar and disparate bodies to engender best practice. This paper, therefore, aims to understand governments' assessment context and provide a cross-continental comparison of their VfM assessment.

Faced with different domestic contexts (e.g. aging infrastructure, population growth, and competing demands on finance), governments tend to place different emphases when undertaking the VfM assessment. In line with the theory of boundary spanning, a cross-continental comparison is conducted between three of the most noticeable PPP markets (i.e. the United Kingdom, Australia and China) about their VfM assessment. The institutional level is interpreted by a social, economic and political framework, and the methodological level is elucidated through a qualitative and quantitative VfM assessment.

There are individual institutional characteristics that have shaped the way each country assesses VfM. For the methodological level, we identify that: (1) these global markets use a public sector comparator as the benchmark in VfM assessment; (2) ambiguous qualitative assessment is conducted only against PPPs to strengthen their policy development; (3) Australia's priority is in service provision whereas that of the UK and China is project finance and production; and (4) all markets are seeking an amelioration of existing controversial VfM assessments so that purported VfM relates to project lifecycles. As such, an option framework is proposed to make headway towards a sensible selection of infrastructure procurement approaches in the post COVID-19 era.

This study addresses a current void of enhancing the decision-making process for using PPPs within today's changing environment and then opens up an avenue for future empirical research to examine the option framework and ensuing VfM decisions. Practically, it presents a holistic VfM landscape for public sector procurers that aim to engage with PPPs for their infrastructure interventions.

This paper aims to analyze the ex ante and ex post economic efficiency of the preventive agreement (concordato preventivo) or composition with creditors as defined by the Italian Bankruptcy Law. This study examines four possible outcomes of the procedure: homologation (confirmation); the degree of dissent/consent of creditors; the revocation, admissibility or inadmissibility; the declaration of the company bankruptcy in preventive agreement.

This paper uses data from 728 Italian companies which filed for preventive agreement in 2016. In reference to each of the four possible outcomes, this study applies nine logit regressions to analyze the effects of a series of efficiency variables ex ante (corporate-based drivers) and ex post (procedure-based drivers).

Results show the relevance of the debt structure, ownership structure and virtuous behavior, corporate governance and management systems, as well as effectivity of the court control on the preventive agreement outcome.

This paper draws on original data of bankruptcy in Italy and gives empirical evidence of the ex ante and ex post factors on the outcomes of the preventive agreement.