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Explains the importance of assessing country risk to lenders and investors, outlines previous research on techniques for doing this and describes a classification method: the multi‐group hierarchical discrimination method (MHD). Applies this to 1978‐1995 data for 143 countries, subdivided into four income groups, and compares the results with those from multiple discriminant, logit and probit analyses using jackknife procedures. Finds MHD more accurate overall and for most income groups except the lower‐middle income economies. Briefly considers other applications for MHD and avenues for further research.

This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are presented. Some contrasts and similarities of the different types of portfolio formulations are drawn out. The survey of multi-criteria methods devoted to portfolio optimization such as weighting approach, lexicographic approach, and reference point method is also presented. This survey presents the nature of the multi-objective portfolio problems focuses on a compromise between the construction of objectives, constraints, and decision variables in a portfolio and the problem complexity of the implemented mathematical models. There is always a trade-off between computational time and the size of an input data, as well as the type of mathematical programming formulation with linear and/or mixed integer variables.

This chapter examines the impact of banking competition, bank regulation, and the global financial crisis (GFC) of 2008–2009 on banks’ productivity changes. For the empirical analysis, I apply a semi-parametric two-step approach of Malmquist index estimates and bootstrap regression to a cross-country panel data of 8,451 commercial banks from 82 countries over the period 2004–2012. Empirical results show that (1) banking competition and capital regulation significantly enhance bank productivity, (2) a tighter bank supervision have a positive impact on bank productivity, and (3) bank productivity decreases during the GFC, but starts to increase as the GFC recovers. I also present consistent evidence that commercial banks in countries with better national governance have higher productivity growth before, during and after the GFC.

Supplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.

The concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.

This study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.

This research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.

This work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.

In this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

Purpose: This chapter explores some of the difficult issues in financial regulation for financial stability. Noting the lack of prior academic work in the topic, this chapter presents a discussion of some difficult issues in financial regulation for financial stability.

Methodology: The chapter draws from real-world experiences in financial regulation and draws support from existing literature.

Findings and conclusions: Some of the difficult issues include: the difficulty in breaking too-big-to-fail financial institutions into small insignificant parts; the difficulty in regulating executive compensation in the financial sector without limiting the ability of financial institutions to offer competitive pay for executive talent; difficulty in instilling strict financial regulation and supervision without limiting the ability of financial institutions to exploit emerging profitable opportunities; difficulty in ensuring that financial institutions increase lending in bad times and during recessions; the rarity of having both a female CEO and Chair in a major financial institution; difficulty in making Central Banks independent from the Federal Government; difficulty in making financial institutions relevant in the midst of hostile technological innovation and disruption.

Practical implications: The implication of the findings is that financial regulation for financial stability is not an easy task. There will be issues that financial regulation can address, and there will be issues that financial regulation cannot address. Acknowledging that such difficulties exist on the path to financial stability is the first step to addressing these issues.

This paper aims to present and assess the EU energy policies regarding their dependence on Information and Communication Technology (ICT) implications and the level of complexity of the applied ICT implications using the Technique for Order Preference by Similarity of Ideal Solution (TOPSIS) method. The used criteria have been retrieved from the official “ICT Implication Assessment method of EU Legislation”.

The methodology approach deals with the ranking representation of EU energy policies according to the ICT exploitation. The data for the study were collected from the official website of the European Union (EU) (www.europa.eu). According to these data, the subtopics of the EU energy policies regard the internal energy market, the European energy policy, the energy efficiency, the nuclear energy, the security of energy supply, the external dimension, the enlargement and the renewable energy sources. The EU energy policies were assessed using the TOPSIS multicriteria analysis. The TOPSIS is widely used to solve real-world decision-making problems due to its characteristic to deal with different information types.

According to the results of the research, the EU energy policies achieve a good level of dependence on ICT implications and of complexity of the applied ICT implications but not the optimum. However, EU policy-makers should take into account the ICT factors while updating an existing one or while designing a new energy policy. The results of this research can provide an overview of the current situation regarding the current legislation while moving toward a sustainable eEurope. There is a need for stronger incubation efforts for a wide range of innovations to be ready in due time.

This is the first time that EU energy policies are presented and assessed regarding their dependence on ICT implications and the level of complexity of the applied ICT implications using the TOPSIS method.

This paper aims to review prior studies and presents a synthesis of the takeover prediction literature spanning the period 1968–2018.

The paper adopts a narrative review approach. It explores prior studies on takeover target prediction from a historical perspective, focusing on the evolution and development of the literature over the 50-year period.

From a historical development perspective, prior studies in the area can be partitioned into four distinct eras. Studies in the first era (1968–1985) mainly established that takeover targets share common characteristics which can be captured with financial ratios. Studies in the second era (1986–2002) developed and extended formal target prediction hypotheses. These studies concluded that it was impossible to build a successful investment strategy around takeover target prediction. Studies in the third era (2003–2009) explored similar questions using alternative modelling techniques but arrive at similar results – targets can be predicted with limited accuracy and target prediction is unlikely to lead to abnormal returns. Studies in the fourth era (2010–2018) explore implications of M&A predictability on share valuation, governance and bond prices (amongst others), but most importantly, provide some evidence that takeover prediction can lead to abnormal returns when combined with appropriate screening strategies.

This presents the first in-depth review of the literature on takeover target prediction. It highlights the development of the literature over four distinct eras and identifies several limitations, research gaps and opportunities for future research. Given the recent decline in the literature (i.e. fourth era), this study may stimulate new research in the area.

The purpose of this research is to highlight the financial characteristics of large French targets which were subject to takeovers during the period 2001–2007 and thereafter deduct the implicit motivations of acquirers.

Using a global sample of 128 French listed companies (64 targets and 64 non-targets), the authors carried out Wilcoxon–Mann–Whitney testing and logistic regression in order to test nine hypotheses likely to discriminate between the two categories of companies (targets and non-targets).

According to the results, target firms are more unbalanced in terms of growth resources and less rich in liquidity than their peers. They have unused debt capacity, offer greater opportunities for growth than firms in the control group and present low levels of value creation.

The main limitation of this study is regarding the sample size, limited by the exclusive use of large firms (deals of over $100m). The scope of this research could be broadened in future by including medium-sized companies.

The authors believe that their results have two major implications. First, they enable market investors to achieve abnormal returns by investing in predicted targets through a portfolio of high takeover probability firms. Second, CEO of companies that are potentially targeted can assess their takeover likelihood in order to act and to manage such a situation for the benefit of their shareholders.

This research concerns the last wave of takeover prior to the subprime-mortgage financial crisis (2001–2007), a period that has not been sufficiently covered in empirical studies. This research contributes to the existing literature in two main respects. First, the results of this study improve our understanding of motivations for takeovers, particularly in the French context. Second, the introduction of new accounting and financial variables, not previously tested in the literature, enriches the available information concerning the profile of takeover targets.

This paper aims to assess the topography of financial regulation, supervisory styles and performance of banking systems across the world.

The author gains insights by comparing regulatory and supervisory practices and their impact on banking system performance before and after the global crisis. The study illustrates the differences in regulation/supervision among crisis, non-crisis and BRICS countries. Even as capital ratios increased, bank governance and supervision regimes were strengthened, the private sector incentives to monitor banks deteriorated.

The results show that the crisis-countries had weaker regulatory and supervisory frameworks than those in emerging countries during the crisis period. BRICS countries as a distinct block have demonstrated uniqueness in their regulatory/supervisory styles that are similar neither to those in the crisis-countries nor to those in the non-crisis countries.

The originality of this study lies in its unique approach to assessing the bank regulation and supervision styles around the world and their impact on banking system profitability, as it uses a robust database. Further, this study provides not only a general assessment but also a comparative analysis of the BRICS and emerging economies. Regulatory agencies around the world would greatly benefit from systematic evidence on the relationship between bank performance and regulatory/supervisory systems.