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The contrast between the value placed on discriminatory power in discussions of indexing and classification and on the transformation of a query into a set of relevant records dominant in information retrieval research has not yet been fully explored. The value of delivering relevant records in response to a query has been assumed by information retrieval research paradigms otherwise differentiated (the cognitive and the physical). Subsidiary concepts and measures (relevance and precision and recall) have been increasingly subjected to critiques. The founding assumption of the value of delivering relevant records now needs to be questioned. An enhanced capacity for informed choice is advocated as an alternative principle for system evaluation and design. This broadly corresponds to: the exploratory capability discussed in recent information retrieval research; the value of discriminatory power in classification and indexing; Giambattista Vico‘s critique of the unproductivity of Aristotelian methods of categorisation as routes to new knowledge; and, most significantly, to ordinary discourse conceptions of the value of information retrieval systems. The criterion of enhanced choice has a liberating effect, restoring man as an artificer and enabling a continuing dialectic between theory and practice. Techniques developed in classic information retrieval research can be adapted to the new purpose. Finally, the substitution of the principle of enhanced choice exemplifies the development of a true science, in which previous paradigms are absorbed into new as special cases. Ay, in the catalogue ye go for men; As hounds, and greyhounds, mongrels, spaniels, curs, Shoughs, water‐rugs, and demi‐wolves, are clept All by the name of dogs: the valu’d file Distinguishes the swift, the slow, the subtle, The housekeeper, the hunter, every one According to the gift which bounteous Nature Hath in him clos’d; whereby he does receive Particular addition, from the bill That writes them all alike; Shakespeare. Macbeth. c.1606.

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.

The purpose of this paper is to determine whether the original and the revised versions of the existing prediction models are the best tools for assessing the going concern assumption of a firm in the creditor-oriented regime.

The analysis begins from estimating the classification accuracy of the original versions of the bankruptcy, going concern and liquidation prediction models. At the second step, the revised versions of the aforesaid existing prediction models are developed. At the third step, the accounting-based going concern prediction model is proposed by using multiple discriminant analysis for the creditor-oriented regime. The sample contains the financial ratios of manufacturing firms for the period 1997–2014.

The finding indicates that the five discriminatory variables, which belong to “income statement” and “statement of financial position,” of the proposed model are not only useful for evaluating the going concern assumption of a firm, but also give aid for evaluating the financial fraud risk of a firm as compared to the original and revised versions of the prediction models that are developed for the debtor-oriented regime.

The external validity of the proposed prediction model can be tested on the large data sets of the countries where the liquidation provisions are a part of their local corporate law.

The proposed accounting prediction model will be helpful for the internal and external auditors in order to determine the going concern assumption at planning, performing and evaluation stages.

The proposed accounting-based going concern prediction model is based on liquidated firms.

The blue ocean strategy refers to how rebuilding the inputs that customers value in the designing of a new value curve fundamentally requires a four field of action structure: reduce, eliminate, create and raise. However, this does not propose a methodology to identify these fields of action. Hence, the purpose of this study is to present importance-performance analysis (IPA), as a support tool to identify these fields of action given their relevance and utility to managers.

The 101 ex-customers of health club answered a survey to determine the cut-off boundaries for IPA, and therefore, maximising the discriminatory power of the logistical regression model. This correspondingly incorporated the evaluation of both the area below the receiver operating characteristic curve (ROC) and the adoption of coefficients for concordance and correlation.

The research results demonstrate the need to concentrate efforts on the attributes of: price, responses to complaints, emergency procedures, innovative services, changing rooms, support for selecting the activities members choose to undertake and an appropriate number of members per activity. With low levels of performance and importance, are candidates for elimination, specifically, the availability of specialist appointments, member socialisation activities, maintaining memories of members, bar services and services for children.

The contribution: presenting an IPA methodology applicable to identify the fields of action recognised by the blue ocean strategy as the literature currently only covers concrete situations in which organisations achieve success through reducing, eliminating, creating and elevating and does not set out any methodology to identify those same fields of action; the definition of the cut-off points in IPA based on the ROC curve, which is a more rigorous and exact statistical method than that applied in other studies; the study population, the ex-customers, who not only represent a very important source of latent demand but also because ex-customers are likely to return more impartial.

Each production unit is responsible for the protection of the environment. The restricted undesirable production effects lower environmental damage. This paper emphasizes a proportional reduction of the undesirable outputs, and it supports the growth of desirable outputs as much as possible as well. The two-stage proposed model not only considers the viewpoint of the managers to follow the environmental regulations but also it assigns some bounds on producing undesirable factors according to international environmental protocols. Additionally, the restricted bounds on the undesirable outputs, in both stages, enhance the discriminatory ability of the model.

Two-stage network structure based on Data Envelopment Analysis (DEA) is applied as the main methodology for this paper. The advantages of the proposed model are appointed to assess the environmental units.

Comparing with the existing models, the proposed approach presents a new two-stage model to deal with the environmental issues. Furthermore, the discriminatory ability of the efficiency scores is improved. The distribution of this model is greater than the existing ones.

This paper is fully written, submitted and revised during limitations caused by coronavirus .

The proposed method is employed in two different cases. The efficiency scores of 25 power plants and 13 poultry farms are determined. In fact, the undesirable outputs never meet zero in the process of production but they can be reduced. The results of this research support the effect of the undesirable factors' restriction on the reduction scenario. Both of the examples show that imposing the upper bounds for the undesirable products provide low-efficiency results in comparison with the existing model. On the other hand, the results cover the arguments of sustainability in the evaluation of environmental efficiency.

In the production process, desirable outputs and undesirable factors are produced jointly so undesirable factors never meet zero. This paper develops a new two-stage method to reduce the undesirable outputs at each stage. First, the model confirms the reduction of undesirable outputs. Second, this model imposes restrictions on intermediate and final undesirable outputs according to environmental rights and the concerns of the managers. The model increases the discrimination of the efficiency assessment of real-life two-stage environmental systems as well. Then it focuses on the production of desirable outputs. The new objective function is defined according to the aim of the proposed model that not only declares better efficiency decomposition to the individual system but also the efficiency score is evaluated for each stage.

Values have become a subject of growing interest, and are now generally accepted as an important factor in marketing research. However, value research that relies solely on a simple first‐order value paradigm, faces certain conceptual difficulties. By using a radically different formal value theory in a new approach to values, a method for measuring inherent product values directly as perceived by buyer groups is developed. The discriminatory power of this method has been tested on seven small samples of two product classes and two different models of the same brands. Clear discriminatory results were generated between product classes and brands but slight differences only were found between models of the same brand.

The use of risk proxies in internal models remains a popular modelling solution. However, there is some risk that a proxy may not constitute an adequate representation of the underlying asset in terms of capturing tail risk. Therefore, using empirical examples for the financial collateral haircut model, this paper aims to critically review available statistical tools for measuring the adequacy of capturing tail risk by proxies used in the internal risk models of banks. In doing so, this paper advises on the most appropriate solutions for validating risk proxies.

This paper reviews statistical tools used to validate if the equity index/fund benchmark are proxies that adequately represent tail risk in the returns on an individual asset (equity/fund). The following statistical tools for comparing return distributions of the proxies and the portfolio items are discussed: the two-sample Kolmogorov–Smirnov test, the spillover test and the Harrell’s C test.

Upon the empirical review of the available statistical tools, this paper suggests using the two-sample Kolmogorov–Smirnov test to validate the adequacy of capturing tail risk by the assigned proxy and the Harrell’s C test to capture the discriminatory power of the proxy-based collateral haircuts models. This paper also suggests a tool that compares the reactions of risk proxies to tail events to verify possible underestimation of risk in times of significant stress.

The current regulations require banks to prove that the modelled proxies are representative of the real price observations without underestimation of tail risk and asset price volatility. This paper shows how to validate proxy-based financial collateral haircuts models.

As small and medium-size enterprises (SMEs) rely on board heterogeneity to raise capital and establish credit relationships with suppliers, it is crucial to investigate the board heterogeneity effect on their survival. In this study, the first research objective is to provide further insights on the discriminatory power of survival approaches, specifically on semiparametric approaches in survival analysis that take into consideration both fixed and time-varying covariates. The second objective is to examine the relationship between board size and SME liquidation by using resource-based theories that focus on measuring board heterogeneity through board size.

This paper uses survival approaches for modelling SMEs survival by examining the survival of more than 68,000 SMEs in the UK covering the before, onset and post 2008 crisis periods and with firms’ demographic characteristics and financial indicators. Survival analysis is effective to examine multiple causes of default/failure and how do particular circumstances or characteristics increase or decrease the probability of survival. Survival analysis brings more advantages than linear-based regression approaches by effectively handling the censoring of observations.

Motivated by resource-based theories, the authors find that the likelihood of a firm being liquidated robustly increases with a reduction in its board heterogeneity measured through board size. This finding is held under non-parametric, parametric, and semiparametric approaches using survival analysis. The research shows better causal explanation and discriminatory power on using the semiparametric-based survival analysis approach considering both fixed and time-varying covariates.

This study demonstrates the better performance and causal explanation of the survival model using time-varying covariates compared with those using fixed covariates. In addition, the authors delve into board heterogeneity, measuring through the board size to investigate how the number of board directors affects the firm liquidation, it is also a factor worth considering when a small and medium firm is forming its board.

This research investigates the board heterogeneity effect on firm survival using survival analysis approaches. The authors contribute to the knowledge on board heterogeneity of SMEs. Specifically, the size of more than three directors could help reduce SMEs liquidation risk. This result gives a recommendation to firms or start-ups when forming their director board. This research also provides further insights on the applicability of survival models with unique UK SMEs data covering the before, onset and post 2008 crisis periods.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

The purpose of this paper is to present a fresh approach to stimulate individual creativity. It introduces a mathematical representation for creative ideas, six creativity operators and methods of matrix-algebra to evaluate, improve and stimulate creative ideas. Creativity begins with ideas to resolve a problem or tackle an opportunity. By definition, a creative idea must be simultaneously novel and useful. To inject analytic rigor into these concepts of creative ideas, the author introduces a feature-attribute matrix-construct to represent ideas, creativity operators that use ideas as operands and methods of matrix algebra. It is demonstrated that it is now possible to analytically and quantitatively evaluate the intensity of the variables that make an idea more, equal or less, creative than another. The six creativity operators are illustrated with detailed multi-disciplinary real-world examples. The mathematics and working principles of each creativity operator are discussed.

The unit of analysis is ideas, not theory. Ideas are man-made artifacts. They are represented by an original feature-attribute matrix construct. Using matrix algebra, idea matrices can be manipulated to improve their creative intensity, which are now quantitatively measurable. Unlike atoms and cute rabbits, creative ideas, do not occur in nature. Only people can conceive and develop creative ideas for embodiment in physical, non-physical forms, or in a mix of both. For example, as widgets, abstract theorems, business processes, symphonies, organization structures, and so on. The feature-attribute matrix construct is used to represent novelty and usefulness. The multiplicative product of these two matrices forms the creativity matrix. Six creativity operators and matrix algebra are introduced to stimulate and measure creative ideas. Creativity operators use idea matrices as operands. Uses of the six operators are demonstrated using multi-disciplinary real-world examples. Metrics for novelty, usefulness and creativity are in ratio scales, grounded on the Weber–Fechner Law. This law is about persons’ ability to discern differences in the intensity of stimuli.

Ideas are represented using feature-attribute matrices. This construct is used to represent novel, useful and creative ideas with more clarity and precision than before. Using matrices, it is shown how to unambiguously and clearly represent creative ideas endowed with novelty and usefulness. It is shown that using matrix algebra, on idea matrices, makes it possible to analyze multi-disciplinary, real-world cases of creative ideas, with clarity and discriminatory power, to uncover insights about novelty and usefulness. Idea-matrices and the methods of matrix algebra have strong explanatory and predictive power. Using of matrix algebra and eigenvalue analyses, of idea-matrices, it is demonstrated how to quantitatively rank ideas, features and attributes of creative ideas. Matrix methods operationalize and quantitatively measure creativity, novelty and usefulness. The specific elementary variables that characterize creativity, novelty and usefulness factors, can now be quantitatively ranked. Creativity, novelty and usefulness factors are not considered as monolithic, irreducible factors, vague “lumpy” qualitative factors, but as explicit sets of elementary, specific and measurable variables in ratio scales. This significantly improves the acuity and discriminatory power in the analyses of creative ideas. The feature-attribute matrix approach and its matrix operators are conceptually consistent and complementary with key extant theories engineering design and creativity.

First to define and specify ideas as feature-attribute matrices. It is demonstrated that creative ideas, novel ideas and useful ideas can be analytically and unambiguously specified and measured for creativity. It is significant that verbose qualitative narratives will no longer be the exclusive means to specify creative ideas. Rather, qualitative narratives will be used to complement the matrix specifications of creative ideas. First to specify six creativity operators enabling matrix algebra to operate on idea-matrices as operands to generate new ideas. This capability informs and guides a person’s intuition. The myth and dependency, on non-repeatable or non-reproducible serendipity, flashes of “eureka” moments or divine inspiration, can now be vacated. Though their existence cannot be ruled out. First to specify matrix algebra and eigen-value methods of quantitative analyses of feature-attribute matrices to rank the importance of elementary variables that characterize factors of novelty, usefulness and creativity. Use of verbose qualitative narratives of novelty, usefulness and creativity as monolithic “lumpy” factors can now be vacated. Such lumpy narratives risk being ambiguous, imprecise, unreliable and non-reproducible, Analytic and quantitative methods are more reliable and consistent. First to define and specify a method of “attacking the negatives” to systematically pinpoint the improvements of an idea’s novelty, usefulness and creativity. This procedure informs and methodically guides the improvements of deficient ideas.