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This study aims at evaluating the technical efficiency (TE) of healthcare systems in the Arab region and exploring the key factors that affect the efficiency performance.

The study applies a two-stage Data Envelopment Analysis (DEA) approach to a sample of 20 Arab countries. In the first stage, a DEA model is used to calculate the TE scores of the examined healthcare systems in 2019 and 2010, following both the output and input orientations of efficiency. In the second stage, a censored Tobit model is estimated to investigate the determinants of healthcare efficiency.

DEA results of 2019 indicate that achievable efficiency gains of the Arab countries range from 0.4% to 16% under the output and input orientations, respectively. Six countries are efficient under both orientations. Although the average efficiency scores of the Arab countries have deteriorated between 2010 and 2019, Djibouti and Sudan had the greatest efficiency improvements between the two years. Bahrain, Mauritania, Morocco and Qatar proved to be efficient in 2010 and 2019 under the two orientations of efficiency and according to the two DEA specifications followed. The Tobit model reveals that corruption and government health expenditure tend to have an adverse impact on healthcare efficiency.

The author evaluates healthcare efficiency and healthcare's efficiency determinants in the Arab countries. Regardless Arab countries' diversity, these countries are facing common health challenges, including diminishing role of governments in healthcare financing; increased out-of-pocket healthcare spending; poor healthcare outputs and prevalence of health inequities resulting from weak governance institutions. Comparing the efficiency of healthcare systems between 2010 and 2019 gives insights on the potential impact of the Arab spring uprisings on healthcare efficiency. Moreover, examining the determinants of healthcare efficiency allows for better understanding of how to improve the efficiency of healthcare systems in the region.

This article investigates the dynamic implication of healthcare expenditure on economic growth in the selected ten Sub-Saharan African countries over the period 2000–2018.

The study methodology included dynamic heterogenous panel, using mean group and pooled mean group estimators. The investigation of the healthcare expenditure and economic growth nexus was achieved while controlling the effects of investment, savings, labor force and life expectancy via interaction terms.

The results from linear healthcare expenditure have a significant positive impact on economic growth, while the nonlinear estimates through the interaction terms between healthcare expenditure and investment have a negative statistically significant impact on growth. The marginal effect of healthcare expenditure evaluated at the minimum and maximum level of investment is positive, suggesting the impact of health expenditure on growth does not vary with the level of investments. This result responds to the primary objective of the article.

In policy terms, the impact of investment on healthcare is essential to addressing future health crises. The impact of coronavirus disease 2019 (COVID-19) can never be separated from the shortages or low prioritization of health against other sectors of the economy. The article also provides an insight to policymakers on the demand for policy reform that will boost and make the health sector attractive to both domestic and foreign direct investment.

Given the vulnerability of SSA to the health crisis, there are limited studies to examine this phenomenon and first to address the needed investment priorities to the health sector infrastructure in SSA.

Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.

In this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.

This paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.

This paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.

Good health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.

This paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

The recent increase in the number of infections and mortality rates in many regions has emphasized the cyclical nature of this pandemic, with new variants emerging constantly. Understanding what has been done by efficient administrations to contain the outbreak is essential while new immunization developments for the new variants are not available.

This work adapts the traditional Banker, Charnes and Cooper (BCC) Variable Returns to Scale model for including panel data on the Brazilian Federal Government spending over the first pandemic months in Pernambuco to identify efficient municipalities and conduct a benchmark on the best practices, reactions and implications that can serve as a guide for the post-Covid recurrence era.

The results provide an interesting panorama of municipal response to the pandemic and some quantitative and qualitative prospects on potentials for improvements from the perspective of efficient and inefficient cities. Only one administration (São Bento do Una) was identified as efficient for the entire period. The authors’ benchmark and discussion are focused on this municipality.

The authors believe this work has two innovative components. The first is a robust and systematic methodology integrating the advances in testing convexity and returns to scale in the construction of a production frontier based on panel data. The second is a discussion on what drives efficiency (benchmarking of best practices) in addition to how to quantitatively attain such efficiency prospects. To the best of the authors’ knowledge, both methodological and empirical implications are original to the present manuscript.

This paper addresses the under-explored collateral damage of economic sanctions, shedding light on the disproportionate harm endured by the most vulnerable segments of societies, which at the same time lack political influence to effect the ruling government into change. The primary objective is to review the literature on humanitarian repercussions associated with sanctions, concluding if they really are a comparably human way of international interference.

Employing a systematic literature review, adhering to the PRISMA approach, and incorporating key term definitions and clear selection criteria, this review analyses 52 studies sourced from Scopus and EconBiz.

The surveyed literature reveals profound adverse impacts of sanctions on health, economic well-being, inequality, and education. Critical gaps in the literature such as disproportional focus on extreme cases like Iran and Iraq, scarce literature on effects on education and inequality, and predominantly inadequate control groups are identified, limiting the generalizability of existing findings.

This paper is the first systematic and replicable review of the literature on the effects of sanctions using a capabilistic approach to define poverty. Highlighting gaps in the current research landscape underscores the limited generalizability of reviewed results. Providing a well-structured summary of existing literature, this work serves as a foundation for future research.

For a successful search, all members of the client–headhunter–candidate trio need to step up to the plate. How can clients better prepare for and engage in the search process? What are the current limits of client engagement and their rights vis-á-vis the headhunter? We explain why headhunting is different from recruitment, and why procuring executive search is as serious as other assets. We reveal the depth of questioning and bias management that it takes to reveal and attract the right candidate. We propose five points to build into the profile of the leader of the future. We next take a look at the clients of executive search firms – who come in all shapes and sizes. Van Eijck distinguishes four groups: multinationals, family businesses, private equity firms and public institutions. A tour signals points of attention for each group regarding a search process and some key points that apply across the spectrum – for example, how wildcard candidates can compromise a search process, the persistent problem of “no pay no cure” and why an appointment doesn’t always guarantee success. Finally, we move to the world of the executive candidate. Many make errors (also of judgment) when building their CVs. A seasoned headhunter can easily spot these. We present the keys to forging a robust story, working effectively with an executive search consultant and conclude with the features of the modern educational and work environment that can get in the way of a career.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018).

This chapter pays tribute to Andrew Jones' research in health programme evaluation, health-risky behaviour and income-related health inequalities by reviewing policy-relevant empirical studies in these domains using Italian data. In the first section, We discuss the impact of reimbursement systems on healthcare behaviour, particularly the transition from incurred-cost-based to prospective systems in hospitals. We explore incentive-driven practices like up-coding and cream skimming, while also considering the potential advantages of primary care incentives and the mixed outcomes associated with cost-sharing schemes. The second section delves into health-risk behaviours in Italy, encompassing substance use, preventive healthcare and responses to health information. The last section presents some evidence on socioeconomic status (SES)-related health disparities and discusses the necessity of accounting for these factors in the Italian National Health Service (NHS)'s resource allocation formula in line with British NHS experience.

John Kenneth Galbraith’s social balance theory is an important theme in many of his books, particularly The Affluent Society, The New Industrial State, and Economics and the Public Purpose. Galbraith’s social balance theory states that forces driving private consumption in an industrial society will outpace the development and provision of public goods and services with consequences on the well-being of society (Stanfield, 1996, p. 49). The theory leads to several questions: (1) What is the specific relationship between private and public goods and consumption? (2) What is optimized with social balancing? (3) Does the relationship between private and public goods change over time? and (4) How do we evaluate the types of public goods we need? This chapter explores these questions and examines the type of public goods we need today to serve our communities better. For example, police presence and activities in many minority communities are now viewed negatively, as evidenced by the “defund the police” movement. Conversely, some have advocated for greater public spending on community mental health programs and new initiatives to deal with racism in communities.