Russia's Gas Sector: In Need of Liberalization in the Context of the Shale Gas Revolution and Energy Relations with the European Union

Rising gas production from nonconventional deposits in North America and the possibility of growth in the rest of the world pose a serious challenge to Russian energy interests. Although Russia has the largest proven gas reserves and is the number one exporter of fossil fuels, its position as a dominant gas supplier to the European Union (EU) is diminishing. This article examines the main problems of Russia's gas sector in the context of the shale gas revolution and the liberalization of the EU gas market. The article also analyses the perspectives of Russia's energy relations with EU countries and formulates some recommendations for them.     

Selection of a Representative Value Function for Robust Ordinal Regression in Group Decision Making

In this paper, we introduce the concept of a representative value function in a group decision context. We extend recently proposed methods UTA^GMS-GROUP and UTADIS^GMS-GROUP with selection of a compromise and collective preference model which aggregates preferences of several decision makers (DMs) and represents all instances of preference models compatible with preference information elicited from DMs. The representative value function is built on results of robust ordinal regression, so its representativeness can be interpreted in terms of robustness concern. We propose a few procedures designed for multiple criteria ranking, choice, and sorting problems. The use of these procedures is conditioned by both satisfying different degrees of consistency of the preference information provided by all DMs, as well as by some properties of particular decision making situations. The representative value function is intended to help the DMs to understand the robust results, and to provide them with a compromise result in case of conflict between the DMs.     

TOPSIS Based Approach to Scoring Negotiating Offers in Negotiation Support Systems

In this paper we analyze the possibility of applying the technique for order preferences by similarity to ideal solution (TOPSIS) to building the scoring system for negotiating offers. TOPSIS is a multiple criteria decision making method that is based on measuring distances between alternatives under consideration and two bipolar reference alternatives, a positive and negative ideal. Thus the criteria used for the evaluation of alternatives should be described using strong scales. However, in the negotiation, the issues are very often described qualitatively, which results in ordinal or even nominal variables that must be taken into consideration in offers’ evaluation process. What is more, TOPSIS may be applied to solving the discrete decision problems while the negotiation space may be defined by the means of continuous variables too. In this paper we try to modify the TOPSIS algorithm to make it applicable to negotiation support and, moreover, discuss the following methodological issues: using TOPSIS for a negotiation problem with continuous negotiation space; selecting the distance measure for adequate representation of negotiator’s preferences and measuring distances for qualitative issues. Finally, we propose a simple additional mechanism that allows for building the TOPSIS-based scoring system for negotiating offers and does not involve negotiators in time consuming and tiresome preference elicitation process. This mechanism requires from negotiators to construct examples of offers that represent some categories of quality and then by using a goal programming approach it infers all the parameters required by the TOPSIS algorithm. We also show a simple prototype software tool that applies the TOPSIS modified algorithm and may be used in electronic negotiation support.     

Structural equation modeling with ordinal variables: a large sample case study

In the behavioral sciences, response variables are often non-continuous, ordinal variables. Conventional structural equation models (SEMs) have been generalized to accommodate ordinal responses. In this study, three different estimation methods on real data were performed with ordinal variables. Empirical results obtained from the different estimation methods on given real large sample educational data were investigated and compared to recent simulation results. As a result, even very large sample is available, model estimations and fits for ordinal data are affected from inconvenient estimation methods thus it is concluded that asymptotically distribution free estimation method specialized for ordinal variables is more convenient way to model ordinal variables.     

Metrisable assessment of the course of stream-systemic processes in vector form in industry 4.0

Quality & Quantity - The goal of this paper is to present an innovative conception how to use metrisable vector structure of a manufacturing process, based on quantitative relations between the...     

Toward sustainable corporate behavior: The effect of the critical mass of female directors on environmental,social, and governance disclosure

Boards of directors have recently become more attentive to their stakeholders' concerns, providing more transparent information and adopting more sustainable business strategies. This study investigates the influence of a critical mass of women on boards on the environmental, social, and governance (ESG) disclosure score and its three components separately. Using a sample of the FTSE-MIB listed companies in the 2005–2017 period, we show that reaching a critical mass of female board members—going from one or two women to at least three—enhances the level of ESG disclosure. The results also show that the critical mass of female board members has a positive influence on every component of the ESG score, with the highest contribution of women reaching the governance score. These findings provide insights to shareholders and policymakers and suggest that a critical mass of female board members is particularly effective in improving transparency, and it can be seen as a mechanism to transit to stakeholder governance, fostering more sustainable behavior in firms.     

A path model of factors affecting secondary school students’ technological literacy

Technological literacy defines a competitive vision for technology education. Working together with competitive supremacy, technological literacy shapes the actions of technology educators. Rationalised by the dictates of industry, technological literacy was constructed as a product of the marketplace. There are many models that visualise different dimensions of technological literacy, but clear empirical evidence on how these interact is still lacking. A measurement method that comprehensively evaluates technological literacy is missing. Insights into the stem structure and interaction of technological literacy dimensions could be useful for technology education curriculum design and its implementation. In this study, the multifaceted nature of technological literacy was measured using a new assessment method, and dimensions of secondary school students’ technological literacy were empirically investigated. A total of 403 students participated in the quasi-experimental research design. The treatment group consisted of 121 students taught optional subjects relating to technology education. The control group consisted of 282 students. Results from variance analysis showed that optional technology subjects enhance technological literacy, especially students’ technological capacity where a large effect size (η ²  = 0.14) was noted. Results from a path analysis revealed critical thinking and decision-making as the most important dimensions of technological literacy while the predictor of active participation in out-of-school technical activities and technology homework was a key independent influencing factor. A large effect size (R ²  = 0.4) for career path orientation predictors was detected. Technological capacity was revealed as a decisive predictor for a career path in vocational education and technical high school.     

Macroeconomic Effects of an Ageing Population in Mauritius

The economic literature focuses mostly on faster ageing of population among developed countries; however, many developing countries experience even more dramatic pace of this process. Mauritius, with the median age of population higher than the world average since 1990s, represents a prominent example of such a case. In this paper, we analyse demographic developments in Mauritius and discuss their macroeconomic implications using an open-economy OLG model with demographic shocks. We project that a decline in the Mauritian interest rate and net foreign assets to GDP resulting from ageing will be accompanied by a temporary increase in GDP, consumption and investment.     

Depositors Discipline through Interest Costs during Good and Bad Times: the Role of the Guarantor of Last Resort<Superscript>1</Superscript>

We investigate whether the public sector’s ability as the guarantor of last resort (GLR) to help banks or to guarantee banks’ liabilities affects the sensitivity of interest costs to bank fundamentals. We use a global bank sample and find that the sensitivity is an increasing function of GLR risk, regardless of the method applied to describe this risk. Therefore, our results indicate that increased levels of GLR risk might foster market monitoring by depositors.