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The purpose of this paper is to propose a new MCDM method called ranking based on optimal points (RBOP).

By employing two abstract groups of alternatives as the optimum alternatives and an optimal alternative, in order to offer the most desirable alternative, RBOP imitates human behavior in the decision-making process. RBOP policy is to find the best alternative through measuring alternatives distances from optimum alternatives and optimal alternative, thus, the best alternative must be sitting on the closest distance to its optimum points and the closest distance to the optimal points simultaneously.

In this paper, the author introduced a ten-step gray form of RBOP which is applied in a case of buying running shoes and results compared to the existing MCDM methods. Results showed the considerable differences.

Generally, in order to select the best alternative(s), and to aid decision makers (DMs) to make better decisions for the real-world problems, MCDM methods evaluate a number of alternatives via a number of criteria through the proposed mathematical algorithms. Frequently, for the direct impact of the DMs on the decision-making process, MCDM methods have inflexible algorithms. They only allow DMs to make an impact on the criteria analysis. The inflexibility emerges as a problem when perfect information is available for DMs and MCDM final results are not desirable. The process of the new method completely depends on DMs’ decisions, their interpretation of the periphery and their personal impressions. Hence, the output of RBOP is not necessarily the best alternative, but it offers the most desirable alternative to DM.

This chapter discusses and investigates the sustainability reporting across different sectors. The first section discusses and investigates the relationship between sustainability reporting and primary sector's performance (Agriculture and Food Industries Sector and Energy Sector). The second section discusses and investigates the relationship between sustainability reporting and secondary sector's performance (Manufacturing Sector). The final section discusses and investigates the relationship between sustainability reporting and tertiary sector's performance (Banks and Financial Services Sector, Retail Sector, Telecommunication and Information Technology Sector, and Tourism Sector).

This paper aims to propose an innovative parametric design for artificial neural network (ANN) modeling for the multi-quality function problem to determine the optimal process scenarios.

The innovative hybrid algorithm gray relational analysis (GRA)-ANN and the GRA-Entropy are proposed to effectively solve the multi-response optimization problem.

Both the GRA-ANN and the GRA-Entropy analytical approaches find that the optimal process scenario is a stencil aperture of 57 per cent and immediate processing of the printed circuit board after exposure to a room environment.

A six-week confirmation test indicates that the optimal process has improved quad flat non-lead assembly yield from 99.12 to 99.78 per cent.

Considers why different explanations of the same event can be produced and discusses the characteristics of a good explanation. It identifies and analyses a wide range of different published explanations of a seminal public administration policy‐change. It separates those accounts of that event into families of explanations and describes their common underlying presuppositions. These shared presuppositions are used to construct four models of public policy‐making: sovereign policy‐makers; policy‐makers as relays; policy‐making as the personal; and the discursive construction of policy. Each explanation (and its conceptual model) is challenged by historically grounded counter‐evidence. Based on this analysis the paper suggest ways in which analysis of public management changes might be more fruitfully orientated.

Since 1964 Newcastle University Computing Laboratory has had its own file handling systems for bibliographic records: two systems were developed in parallel for use on an ICL KDF9 computer. In 1967 a third and more sophisticated system compatible with the two KDF9 systems was designed and implemented for use on the newly arrived IBM 360/67. This paper describes the record structure upon which the new system is based. Some of the utilities which make up the file handling system are briefly described, as are some of the projects, both ‘library’ and ‘non‐library’, which have made use of the new system.

German legal historians of nineteenth and twentieth centuries defined the main characteristics of the corporations and believed that one renaissance institution, the Casa di San Giorgio at Genoa (1407–1805), was similar to the corporations of later centuries. This paper proposes to reverse this perspective: did the founders of early modern corporations know the financial model of the fifteenth century Casa di San Giorgio? The research shows the connection between the model of the Casa di San Giorgio and the Mississippi Company of John Law (1720), the famous financial scheme and bubble. The history of the Casa di San Giorgio was mainly transmitted through a passage of Machiavelli’s History of Florence (VIII, 29). The paper offers new biographical evidence that Law had been to Genoa and introduces sources connecting the genesis of Law’s scheme for the Mississippi Company in France with the model of the Casa di San Giorgio.

This paper builds upon the growing research on both privatization and entrepreneurship and provides a model to predict outcomes of privatization of state‐owned enterprises. Previous research has concentrated on the change in ownership as the principal driver of post‐privatization increases in firm performance and wealth creation. We suggest that structural conditions of the state‐owned enterprise and the privatization process, in combination with characteristics of the new owners, lead to performance changes because they determine the firm’s ability to transform from a state agency to an entrepreneurial organization.

A simulation methodology is applied to the loan loss reserve process of an agricultural lender. Weaknesses of the point‐estimate approach to estimating loan loss reserves are addressed with a “bottom‐up” model. Modeling includes consideration of the producer’s and the lender’s diversification efforts. Implementation of this model will provide the lender a better understanding of the institution’s portfolio risk, as well as the credit risk associated with each loan. This study compares the lender’s loan loss estimates to a distribution of losses with associated probabilities. The comparative results could provide the lender a basis for setting probability levels for determining the regulatory required level of loan loss reserve.

The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

After presenting the concepts of grey systems and grey numbers, this paper surveys existing approaches for solving grey linear programming problems and applications. Also, methods and approaches for solving grey linear programming are classified, and its advantages and disadvantages are expressed.

The progress of grey programming has been expressed from past to present. The main methods for solving the grey linear programming problem can be categorized as Best-Worst model, Confidence degree, Whitening parameters, Prediction model, Positioned solution, Genetic algorithm, Covered solution, Multi-objective, Simplex and dual theory methods. This survey investigates the developments of various solving grey programming methods and its applications.

Different methods for solving grey linear programming problems are presented, where each of them has disadvantages and advantages in providing results of grey linear programming problems. This study attempted to review papers published during 35 years (1985–2020) about grey linear programming solving and applications. The review also helps clarify the important advantages, disadvantages and distinctions between different approaches and algorithms such as weakness of solving linear programming with grey numbers in constraints, inappropriate results with the lower bound is greater than upper bound, out of feasible region solutions and so on.