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Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

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 study set out to understand how the regional competitiveness index (RCI) in the department of Ancash related to the human development index (HDI) from 2008 to 2021. For a more complete understanding of the findings, each component or dimension of the RCI was analyzed. Ancash's HDI and its competitiveness index over a 14-year period were used as the population for this applied, longitudinal, descriptive-correlational study, which was based on secondary data extracted from the “Instituto Nacional de Estadística e Informática” (INEI) and business school of the Pontificia Universidad Católica del Perú (CENTRUM) statistical databases. Multiple linear regression was used to find the relationship. The research found a strong and positive correlation between regional competitiveness and human development between 2008 and 2021. No correlations were found between the HDI and the health, education, employment, or institutional dimensions of regional competitiveness, but direct and significant correlations were established between the economic environment and the HDI and between the infrastructure dimension and the HDI.

High turnover rates, delay and dissatisfaction among PhD students about the high efforts and low rewards are common problems in doctoral education. Research shows that many different factors are associated with the mental health crisis in graduate education, but these diverse aspects have not often been studied in relation to talent management and human resource management (HRM) strategies. Based on questionnaires and in-depth interviews, this chapter critically assesses the factors that influence doctoral students’ well-being, using as theoretical framework the self-determination theory, concerned with the social and other conditions that facilitate or hinder human well-being and flourishing, and the job demands–resources model, an occupational stress model that suggests strain is a response to imbalance between demands on the individual and the resources he or she has to deal with those demands. These theoretical frameworks help to explore the perceived job demands and resources, and motivations of a sample of 25 PhD students in the Netherlands, in order to recommend adequate talent management strategies to improve PhD work conditions at universities and reduce the increasing levels of ill-being. The study proposes a collegial model, focussing on the enjoyment of work, instead of the current managerial model, which focusses on strengthening knowledge and skills, and stimulating performance-oriented behaviour. A differentiated approach is needed, offering customized talent development for each PhD student in order to respond to his or her specific qualities, improving general well-being. This radical shift in talent management is needed to counter the mental health crisis in doctoral studies.

This chapter examines how innovation and research are essential to the advancement of science, the economy, and society. We examine the current status of scientific research in Saudi Arabia, highlighting issues like financial limitations and a lack of skilled researchers. We emphasize how important it is to develop the next generation of scientists in order to transform existing practices and improve the state of scientific research in the country.

Proficiency in research and innovation is crucial for expanding the frontiers of knowledge, empowering scientists to tackle intricate problems, and advancing scientific rigor. These abilities also support the use of evidence in decision-making, enabling researchers to provide empirical data that inform practices and policies in a variety of industries. Sustained growth requires the formation of future leaders, who promote knowledge exchange and multidisciplinary collaboration.

Despite Saudi Arabia’s significant spending on science, problems still exist. Addressing governance deficiencies is demonstrated by the establishment of the Research, Development, and Innovation Authority in 2021. The nation has grown in the world’s scientific rankings, drawing eminent specialists and fostering cross-border cooperation. Still, there is room for improvement, especially when it comes to fostering a culture of research, improving financing sources, and encouraging international collaboration. It is imperative that these problems are resolved in order to avoid stagnation, guarantee ongoing innovation, and take advantage of chances for society’s progress.

The chapter ends with a call to action that highlights how quickly improvements must be made. Failing to do so runs the risk of stifling the advancement of science, preventing the creation of new technologies, and prolonging complicated issues. To lower risks, seize opportunities, and ensure that research and innovation continue to advance for the good of society, immediate action is necessary.

In academia, assessment is often narrow in its focus on research productivity, its application of a limited number of standardised metrics and its summative approach aimed at selection. This approach, corresponding to an exclusive, subject-oriented concept of talent management, can be thought of as at odds with a broader view of the role of academic institutions as accelerating and improving science and scholarship and its societal impact. In recent years, open science practices as well as research integrity issues have increased awareness of the need for a more inclusive approach to assessment and talent management in academia, broadening assessment to reward the full spectrum of academic activities and, within that spectrum, deepening assessment by critically reflecting on the processes and indicators involved (both qualitative and quantitative). In terms of talent management, this would mean a move from research-focused assessment to assessment including all academic activities (including education, professional performance and leadership), a shift from focus on the individual to a focus on collaboration in teams (recognising contributions of both academic and support staff), increased attention for formative assessment and greater agency for those being evaluated, as well as around the data, tools and platforms used in assessment. Together, this represents a more inclusive, subject-oriented approach to talent management. Implementation of such changes requires involvement from university management, human resource management and academic and support staff at all career levels, and universities would benefit from participation in mutual learning initiatives currently taking shape in various regions of the world.