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Achieving equal treatment of credit applicants has been a legitimate concern of legislators and the credit industry. However, measures taken to date in attempting to comply with anti‐discrimination laws arguably do not allow for the most effective use of credit scoring models, and could run counter‐intuitive to the intention of legislation through indirect discrimination. The purpose of this paper is to offer an alternative interpretation that preserves the intention of legislation and also retains the integrity and effectiveness of credit scoring models.

The paper makes a legal analysis of anti‐discrimination laws in the UK, with US law as a comparison, aiming to demonstrate that concerns in using information protected under anti‐discrimination laws as variables may be misplaced, because nothing in these laws precludes the inclusion of all relevant variables in modelling.

The inclusion of variables representing protected characteristics in credit scoring models may not contradict current anti‐discrimination laws.

Limitations exist from the perspectives of customer relationship and the need for further checks and balances. Conclusive validation of the findings will need to come from the courts. The paper provides a springboard for empirical research on whether the inclusion of variables representing protected characteristics in credit scorecards continues to produce better decision‐making models.

The findings benefit credit risk modelling as a whole in facilitating the development of credit scorecards that are in compliance with anti‐discrimination laws, without sacrificing their effectiveness.

The paper presents a fresh perspective and alternative solution to legal concerns regarding the use of protected characteristics in credit scoring, which will be useful to the credit industry.

The purpose of this paper is to propose a system with the highest discriminatory power by selecting an indicator system based on the K–S test according to the unique circumstances of small enterprises.

The proposed method relies on calculating the K–S test statistical magnitude of D iteratively to reach a system with the maximum discriminatory power.

The empirical results, demonstrated using 3,045 small businesses from a Chinese bank, show that credit rating system should focus on the indicator system’s discriminatory power rather than a single indicator’s discriminatory power, because the interaction between indicators affects the discriminatory power of the system.

The proposed method creates a credit rating system with the highest discriminatory power, rather than its indicators, which is a more reasonable and novel approach to credit rating.

The approach is unique because the final system will have high discriminatory power and has excellent potential for decision support. The authors believe that this contribution is theoretically and practically relevant because credit rating for small business is especially difficult and complicated.

With a newly developed measure of economic freedom across US local government jurisdictions, this paper aims to estimate the relationship between economic freedom and bond ratings.

The author uses a battery of cross-sectional econometric models to identify the impact that economic freedom might have on bond ratings using a sample of US municipal governments.

Overall, the results indicate that relatively more economic freedom within a local jurisdiction is associated with higher bond ratings and thus lower borrowing costs. However, similar to Roychoundhury and Lawson (2010), no specific subcomponent seems to affect bond ratings.

To the author’s knowledge this is the first scholarly work to address this topic at the local level.

This paper aims to survey the credit scoring literature in the past 41 years (1976-2017) and presents a research agenda that addresses the challenges and opportunities Big Data bring to credit scoring.

Content analysis methodology is used to analyze 258 peer-reviewed academic papers from 147 journals from two comprehensive academic research databases to identify their research themes and detect trends and changes in the credit scoring literature according to content characteristics.

The authors find that credit scoring is going through a quantitative transformation, where data-centric underwriting approaches, usage of non-traditional data sources in credit scoring and their regulatory aspects are the up-coming avenues for further research.

The paper’s findings highlight the perils and benefits of using Big Data in credit scoring algorithms for corporates, governments and non-profit actors who develop and use new technologies in credit scoring.

This paper presents greater insight on how Big Data challenges traditional credit scoring models and addresses the need to develop new credit models that identify new and secure data sources and convert them to useful insights that are in compliance with regulations.

Stigma reduction is an important public health challenge because of the large morbidity and mortality associated with some forms of substance use. Extreme stigma can lead to dehumanisation of target groups, who are ascribed with lesser humanity. The authors examined whether there was blatant and subtle dehumanisation of people who use heroin, and if these were associated with levels of support for non-discriminatory drug policy.

A cross-sectional online study using a UK convenience sample (n = 307 [75.2% female, mean age 28.6 ± 12.2 years]) was conducted. Participants completed assessments of blatant (Ascent of Humans [AoH] scale) and subtle (an emotion attribution task) dehumanisation and a bespoke measure assessing support for non-discriminatory drug policies. Other measures controlled for stigma towards people who use drugs (PWUD) and moral disgust.

There was greater blatant dehumanisation of people who used heroin compared to the general population and other potentially stigmatised reference groups, including people who use cannabis. The authors also found evidence of subtle dehumanisation, and people who used heroin were rated as being less likely to feel uniquely human emotions, less likely to feel positive emotions and more likely to feel negative emotions. Blatant dehumanisation was associated with significantly lower probability of support for non-discriminatory drug policy.

Dehumanisation may present significant challenges for stigma reduction initiatives and in fostering public support for drug policy and treatment. Denial of the humanity of this group could be used to justify discriminatory policies or relative deprioritisation of support services in funding decisions. Activities that seek to “rehumanise” PWUD, including social inclusion, and encouraging compassionate media representations that portray the lived experiences of substance use may be useful areas of future work.

This is the first study to investigate blatant and subtle dehumanisation of people who use heroin, and how this relates to public support for drug policy.

Intensive care unit performance evaluation is usually affected by variations in the severity of inpatients' health status. This paper aims, therefore, to standardize two performance measures: intensive care unit survival and length of stay using the Acute Physiology and Chronic Health Evaluation II (APACHE II) severity of illness score.

A records study in three Ain Shams University Hospital intensive care units, from January 1‐December 31, 2003 was carried out to examine illness severity effect using APACHE II, length of stay and survival. Retrospective data were used to model length of stay in days and the survival using the APACHE II score as a predictor. This was followed by a prospective study to monitor the standardized measures in two intensive care units for one year.

APACHE II scores predicted length of stay of those who were discharged and control charts for severity‐adjusted length of stay were drawn up. The APACHE II score predicted survival for those with APACHE II score >16. The model is significant with a specificity of 89.9 percent while sensitivity was 25 percent. Control charts for severity‐adjusted mortality were drawn up to monitor mortality.

Only 60 percent of the files examined in the retrospective part of the study had enough data to calculate APACHE II scores.

Standardized APACHE II severity of illness score can monitor intensive care unit length of stay and mortality.

The paper underlines the need to implement a standardized measurement system to evaluate intensive care patient outcomes.

In pursuit of achieving Education‐For‐All goals of universal primary education and improving quality of education, the Indian Government has been providing substantial resources to Indian states. The responsibility of providing access and quality remains the states' responsibility. Assessment of educational development will therefore become a focal point of the Center for Education Policy & Guidelines Formulation. While educational development indices help in ranking states, they do not help in capturing best practices and assessing the efficient utilization of resources. Assessment of the Educational Development Efficiency can augment educational development indices in vogue. The purpose of this paper is to develop an Educational Development Efficiency (EDE) model to benchmark the Indian states.

This paper uses an input‐process‐output conceptual framework to identify the dimensions of educational development. This paper employs Data Envelopment Analysis (DEA) to compare relative efficiency of 28 states and seven Union territories in India and benchmark them. In order to strengthen the discriminatory power of DEA, cross‐efficiency model was used. Factor analysis was performed to determine the inter‐relationships between variables. The efficiency impacting variables were identified using multiple regression analysis.

This paper benchmarked Indian states on educational development based on their performance. Gross enrolment ratio, students' academic performance and infrastructural investments were identified as the three key variables impacting states' EDE. This paper has shown that the educational administrators can use the EDE model to identify the best practices from efficient states. Insights into utilization of input resources to enhance educational development and consequent improvement of state efficiencies are presented. Four components have been identified to analyze the states' educational development progress – namely, financial adequacy, school resource strength, educational quality and educational access.

Contributions of this paper pertain to evolving a decision support model for national education policy planners, besides providing analytic support to the administrators of the states to benchmark and emulate the efficient educational programs.

This paper is one of the few published studies concerning the evaluation of educational development programs launched in the Indian schools and providing a cross‐comparison of the Indian states for the purposes of performance benchmarking as well as exploring the influencing factors.

This study aims to critically review the research on the phenomenon of discrimination in hospitality and tourism services to identify the key thematic areas, scenarios, antecedents and consequences; to provide theoretical propositions for future research; and to propose practical strategies to reduce discrimination and to improve equality in the field.

This paper adopts the preferred reporting items for systematic reviews and meta-analyses guidelines to collect relevant academic work on discrimination in hospitality and tourism services from 1985 to 2020 and critically reviews and analyses the studies through bibliometric analysis, content analysis and critical analysis.

The findings show that the main sources of discrimination in hospitality and tourism services include sexism, racism, ethnocentrism, lookism and ego-altruism. Discrimination-related research has temporal and geographical variations. A research map is proposed to present existing knowledge of discrimination in hospitality and tourism services, which indicates that while the impacts (at the individual, organizational and institutional levels) of discrimination in hospitality and tourism services have been thoroughly researched, the nature and characteristics of the phenomenon remain context-based and poorly conceptualized.

An anti-discrimination guideline for hospitality and tourism practitioners is designed to cope with and eliminate discriminatory situations. This evidence-based guideline provides useful coping strategies based on the prevent–monitor–manage principle.

This paper is comprehensive in its scope, methodology and wide coverage of discrimination-related research in hospitality and tourism services. It is the first attempt to review this phenomenon in the existing literature and identifies the research gaps and future research agendas.

This chapter analyses the efficiency of African airlines using a two-stage network DEA (Data Envelopment Analysis) model. Network DEA models usually take into account the production process with intermediate inputs derived from the first stage and a second stage that departs from it. This fundamental feature enables one to view the airline production process as a carry-over activity. The analysis covers the 2010–2013 period. The relative efficiency ranks are presented and policy implications are derived.

Success and effectiveness in automated library systems are two related issues that all users are normally looking for when buying or designing a new system. On the basis of the available literature and opinions of automated library systems experts, 26 factors were identified as criteria for the success of automated library systems. Attitudes to these criteria of Australian university librarians and systems managers were examined in a survey conducted in 1993; 23 of these criteria were approved by the survey sample, and the other three were rejected. These criteria should be tested with other groups of experts in library automation to gain more generalisation on the findings.