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The study aims to assess the effectiveness of prevailing methods for quantifying physical climate risks. Its goal is to evaluate their utility in guiding financial decision-making within the real estate industry. Whilst climate risk has become a pivotal consideration in transaction and regulatory compliance, the existing tools for risk quantification frequently encounter criticism for their perceived lack of transparency and comparability.

We utilise a sequential exploratory mixed-methods analysis to integrate qualitative aspects of underlying tool characteristics with quantitative result divergence. In our qualitative analysis, we conduct interviews with companies providing risk quantification tools. We task these providers with quantifying the physical risk of a fictive pan-European real estate portfolio. Our approach involves an in-depth comparative analysis, hypothesis tests and regression to discern patterns in the variability of the results.

We observe significant variations in the quantification of physical risk for the pan-European portfolio, indicating limited utility for decision-making. The results highlight that variability is influenced by both the location of assets and the hazard. Identified reasons for discrepancies include differences in regional databases and models, variations in downscaling and corresponding scope, disparities in the definition of scores and systematic uncertainties.

The study assists market participants in comprehending both the quantification process and the implications associated with using tools for financial decision-making.

To our knowledge, this study presents the initial robust empirical evidence of variability in quantification outputs for physical risk within the real estate industry, coupled with an exploration of their underlying reasons.

This study aims to evaluate the service and crime prevention performance of law enforcement agencies in Taiwan’s municipalities. By analyzing these performances, the study seeks to improve the efficiency of police services through appropriate resource allocation, ultimately achieving enhanced crime prevention.

The study utilized a two-stage data envelopment analysis (DEA) to construct performance metrics. In the first stage, the service performance of the police force was measured using the number of police officers and police stations as inputs and the number of patrols and temporary patrol boxes as outputs. In the second stage, crime prevention performance was assessed with the number of patrols and temporary patrol boxes as inputs and cases of violence, injury, intimidation and theft as outputs. Additionally, a truncated regression model was employed to analyze the impact of environmental variables such as per capita income, population density, proportion of the population with higher education and the unemployment rate on crime prevention performance.

The study found significant variations in both service and crime prevention performance across different municipalities. By identifying the most efficient and inefficient units, the analysis revealed critical insights into resource utilization and areas needing improvement. The regression analysis indicated that environmental factors such as higher per capita income, population density, education level and unemployment rate significantly affect crime prevention performance.

This research provides a novel approach to assessing police service efficiency and crime prevention effectiveness using a two-stage DEA model. By incorporating environmental variables through truncated regression, the study offers a comprehensive evaluation framework that can inform policy decisions and resource allocation strategies. This methodology not only highlights the performance metrics of law enforcement agencies but also underscores the influence of socioeconomic factors on crime prevention, contributing to the broader literature on public safety and resource management.

The purpose of this paper is to explore the dynamic relationship between formal and non-formal processes of accountability in a public services context.

The paper presents a case study of the impact of the Health and Social Care Act (2012) on the practices of Health and Wellbeing Board (HWB) members. It draws upon multiple data sources, including in-depth interviews with the members, comprehensive archival data published by the HWB (2011–2019), and observations of HWB public meetings. We utilise the concept of dynamic duality (Li, 2008) to further theorise the relationship between formal and non-formal processes of accountability and how they mutually transform one another.

The case illustrates the role of formal and non-formal processes of accountability at a HWB in England. Moreover, the case study reveals the relationship and interaction between the formal and non-formal accountability processes and how they change and transform each other over time. We find that whilst non-formal accountability processes were strengthened by a historical legacy of partnership working, over time the dynamics at play led to the development of formal accountability processes through more sophisticated performance systems, which in turn transformed non-formal accountability processes.

The paper presents a more holistic conceptualisation than articulated in prior accountability literature, dynamic duality, on the relationship between formal and non-formal accountability processes. Through application of this conceptualisation to a HWB in England, the paper spotlights the inter-relationship between formal and non-formal processes of accountability, and how they have the potential to transform each over an extended time-period.

The question of “what works?” for organizational diversity and inclusion (D&I) has captivated practitioners and researchers for some time, but there is a lack of unifying knowledge on what interventions are effective. The purpose of this study was to investigate the impact, outcomes and quality of evidence relating to interventions used by organizations for workplace D&I to inform what works in practice and where there are still evidence gaps.

This multidisciplinary meta-review – a systematic review of reviews – summarized the effects of various practices, policies, programs and initiatives across dimensions of diversity and disciplines.

From 37 reviews over 13 years, we identified 12 categories of interventions (e.g. diversity training, de-biasing selection procedures and workplace accommodations) mapped to 22 outcomes. Workplace accommodations and job training were linked with positive outcomes in the age and disability dimensions of diversity. Diversity training was associated with comparatively higher-quality evidence, albeit its effects were largely limited to awareness and learning outcomes. The literature on recruitment, leave and compensation policies reported some mixed effects on D&I.

This meta-review provides a synthesis of the current state of evidence across multiple disciplines and diversity dimensions to guide future research and practical D&I actions. It has implications for research (e.g. greater attention needed for interventions to improve inclusion) and practice (e.g. setting realistic expectations about what change organizations can expect to achieve).

This paper aims to design, develop and validate an instrument to measure employer branding by considering existing employee perceptions.

In this systematic research, the predominant factors of employer branding are identified through Pareto analysis; using structured questionnaire information and data collected from 423 employees. The number of items and dimensions was reduced by conducting exploratory factor analysis (EFA) and validated extracted dimensions using confirmatory factor analysis (CFA) using statistical software (SPSS-21). The designed scale was verified by applying relevant statistical techniques, including a multicollinearity test, construct validity, content validity, divergent validity, convergent validity and reliability test. Structural equation modeling (SEM) was performed using AMOS, to explore the interrelationship between the dimensions of the scale.

Considering the perception of existing employees, seven factors along with 24 items scale were designed and developed to measure the employer branding. The identified seven factors are; career development opportunities; compensation and benefits; corporate social responsibility; training and development; work environment; organizational culture; and work-life balance. The proposed model explains a total variance of 70.35% and the model fit indices are within the acceptable range, validity and statistical reliability are established for seven dimensions of employer branding.

Employer branding is studied from existing employee perspective by collecting responses from the employees of the IT sector only.

This validated scale is valuable for practitioners and academicians. The proposed dimensions in the scale may help practitioners explore the impact on the outcomes of organizations such as employee commitment, employee retention, employee satisfaction and total productivity. This novel instrument helps to measure employees' perception of their employers. Further, the authors identify the gaps and accordingly plan strategies to attract and retain the talented workforce.

The authors believe that this novel measuring instrument is comprehensive and the first of its kind. Employer branding has been modeled using SEM analysis by considering the perceptions of the present employees.

This study examines the moderating role of female directors on the relationship between the firms’ characteristics and tax avoidance in an emerging economy.

This study employs the second-generation unit root test and the generalised method of moments (GMM) techniques. The Kao residual cointegration test corroborates a long-run cointegration among variables.

Female directors demonstrate mixed and unusual findings. No significant impact of female directors on tax avoidance is found. In addition, the presence of female directors does not show any negative or significant moderating impacts on the relationship between leverage, firm age, board size and tax avoidance. However, having more female directors can negatively and significantly moderate the relationship between more profitable firms, larger firms and tax avoidance. These findings show that the board of directors could use the presence of female directors to maximise their opportunistic behaviour, such as to avoid tax.

Research limitations – The study is limited by considering only 62 listed firms. The scope could be extended to include non-listed firms.

Research implications – There is increasing pressure for female directors on boards from diverse stakeholders, such as the European Commission, national governments, politicians, employer lobby groups, shareholders, and Fortune and Financial Times Stock Exchange (FTSE) rankings. This study provides input to decision-makers putting gender quota laws into practice. Our findings can help policy-makers adopt regulatory reforms to control tax avoidance practices and enhance organisational legitimacy. Policymakers can change their policy to include female directors up to the threshold suggested by the critical mass theory.

This is the first attempt in Bangladesh to explore the role of female directors in the relationship between the firms' characteristics and tax avoidance. The current study has significant ramifications for bringing gender diversity into practice as a component of good corporate governance.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.

This chapter shifts focus from the underlying causes of offending to current rehabilitation approaches and models. It begins with an overview of the rehabilitation movement, emphasising the principle of ‘what works’ in offender reform. The discussion then moves on to explore two major frameworks: the Risk-Need-Responsivity (RNR) model and the Good Lives Model (GLM). Each model will be briefly outlined and critically evaluated for its effectiveness in preventing re-offending and supporting desistance. The chapter concludes with a rationale for introducing a new approach to rehabilitation, the Compassionate Positive Applied Strengths-based Solutions (COMPASS) model, summarising its potential benefits for enhancing desistance support.