IBSS

The development of technology and globalisation have opened wide opportunities even for investors without relevant knowledge or experience to use investment instruments. Although cryptocurrencies have unique features that attract investors, the market is also subject to risks: price fluctuations, operational risks, and the issue of trust. In this context, looking for effective solutions for investment portfolios and being able to understand better and evaluate the cryptocurrency market becomes especially important. Previous studies have highlighted the benefits of cryptocurrencies, such as diversification, hedging, and safe havens, but there is little research that reveals the performance of a cryptocurrency portfolio. Investors seek the highest possible return but generally avoid or underestimate risk. Applying portfolio optimisation in the study aims to identify cryptocurrencies, the inclusion of which in a traditional asset investment portfolio would help to achieve the most effective combination of desired return and risk. The primary purpose of this study is to evaluate the impact of different cryptocurrencies on the efficiency of the investment portfolio. Ten cryptocurrencies included in the B10 BITA CRYPTO 10 INDEX composition are studied. Due to the instability of cryptocurrencies, the composition of this index is constantly changing. The cryptocurrencies analysed in the study, included in the composition of this index, were fixed in August 2023. Traditional assets in the study are represented by stock indices: S&P 500, Euro Stoxx 50, DAX and CAC 40. After identifying efficient portfolios in the study, it can be concluded that the inclusion of different cryptocurrencies in an investment portfolio consisting of stock indices does not always allow efficient portfolio results to be achieved.

The selection of appropriate solution strategies to deal with the disruption in project management has become an essential topic. The evaluation of the ranking of solution strategies for dealing with disruption as a complex multi-criteria decision-making (MCDM) problem includes several alternatives with conflicting criteria in the implementation phase of the project. This paper introduces a new MCDM method by a novel integration of grey relational analysis (GRA) and measurement alternatives and ranking according to the compromise solution (MARCOS) approaches under interval-valued fuzzy sets (IVFSs). The contribution of this paper is not only to extend the MARCOS method with both GRA techniques and IVFSs but also to propose a method for weighting the criteria that considers both the subjective and the objective weight based on entropy in an integrated manner. In this proposed method, the subjective weights assigned by decision makers (DM) and the objective weights are based on interval Shannon’s entropy theory. Subsequently, the proposed method is evaluated through an empirical example, which demonstrates its applicability and validity in prioritising solution strategies for managing project disruption. The paper also provides managerial insights.

The establishment of the circular economy contributes to the development of sustainable consumption and creates new consumer habits, changes the market of goods and promotes innovations and ecological principles in the daily life of the population. The increasing consumption of eco-friendly goods is closely related to the environmental responsibility of the individual, which is formed over time and affects the results of social production and the technological level of production. The article examines the problem of adjusting public demand that would increase the rate of adoption of the circular economy, analyses factors affecting public demand and determines the price of changing public targets for different groups of the population. The mathematical function of public utility in the introduction of the circular economy changes the determining factors of consumer satisfaction, tending to reduce risks to the ecosystem and the health of consumers. It is concluded that when carrying out certain educational activities, 22% of surveyed consumers on average are ready to change their preferences in favour of eco-friendly goods. If a systematic approach is used and the market for environmentally friendly products is balanced, the main hazardous environmental products and their alternatives that can adjust public demand and change consumer habits are analysed.

In the article, we examine the promotion of hate and autocracy in the environment of liberal democracy and market economy, comparing economic values with social capital, as well as the relationship between ideology and authoritarian populism. We use the method of critical analysis, together with a synthetic method to describe the integrated socio-politico-economic phenomena. We develop the theses as follows. 1. The free market is inseparable from the freedom of speech and press. 2. Freedom of speech and economic activities has many limitations including the responsibility of actors, social state politics, and ideology. 3. The biggest threat to freedom lies in very democracy which tends to evolve into populist autocracy. 4. The constitution guarantees both freedom of speech and economic activities but it is effective only when the majority is convinced of the value of constitutional democracy.

The article examines the politico-economic ethos as it relates to the idea of solidarity and contrasts it with social chaos. The politico-economic ethos is defined as the ethos of collective responsibility, confirming not only the pragmatic interests of governments but also testifying to common normative values in the cooperation of regional political and economic actors. Instrumental (economic, managerial, consumerist, or other) attitudes expose politics without any ethos. Systems based on knowledge, control, and predictability are particularly fragile. The sources of solidarity of the European Union as a politico-economic entity are examined. European solidarity, which began as economic cooperation, is associated with hegemonic and perspective-imposing tendencies, that is, with the “European/non-European” variant of the “barbarian/non-barbarian” distinction. Solidarity is an aspect of sociality in the world of political and economic speaking beings (Aristotle), and it is necessary for economic activity.

Algorithmic trading models are now widely used in investment decision-making. By grounding these models in scientific knowledge, investors can obtain efficient results in financial markets. During the COVID-19 outbreak, the drug manufacturing industry has received substantial attention from investors. The purpose of our research is to form an investment portfolio using an algorithmic trading model in the drug manufacturing industry. The model covers the entire process of portfolio formation: market analysis, selection of industry, selection of particular stocks, data mining, forecasting and investment decision-making. Three portfolios – maximum return, minimum risk and maximum Sharpe ratio – are constructed and compared across two periods. Portfolios formed using deep learning forecasting outperformed the index in more cases than did portfolios created using the Monte Carlo simulation. Portfolio formation using algorithmic trading models is suitable for individual investors, can be easily automated using the computer application and can not only be applied to one industry but diversified across various sectors.

The paper deals with (dis)advantages of gamification in such fields as management, politics, communication, education, and technologies through the comparative analysis of English, German, French, Spanish, Russian, and Ukrainian literature. Gamification is a relevant issue in business. The results of gamification are the commercialisation of education, pseudo-scientific approach, and fragmentation of knowledge. However, making learning more engaging can also lead to more enjoyable learning and better academic performance. Game technologies are used by the media to manipulate people, nevertheless, they introduce innovations into the public sphere. Gamification could deny real life, on the other hand, it is a kind of socialisation and protective mechanism. In communication, gamification develops self-virtualisation, trains communication skills. Gamification creates the illusion of easy action without moral consequence and legitimises violence on the computer screen, however, it presupposes responsibility for implemented phantasies and develops direct aggressive energy.

Research background: Stochastic information in finance and economics results from various unexpected and uncertain processes and fluctuations of financial and economic activity. It is necessary to make investment decisions in capital and exchange markets adequately. Thus stochastic models in investment are widely used. Investment decision-making problems are successfully being solved by applying artificial intelligence or similar methods. However, artificial intelligence can solve significantly broader groups of problems and tasks. To solve such kinds of problems, the focusing of artificial neurons into the effectively functioning stochastic pseudo-neural network is oriented in the proposed research. Purpose of the article: The research objective is to form an efficient investment portfolio using the historical data of financial markets and assess its results. Methods: To reach the aim of the research, the stochastic investment system based on artificial intelligence and methodology of stochastic expertise is developed. It is capable of solving the investment problems in financial markets. The system is backed up by the authors’ previously developed adequate portfolio model, which solves investment problems concerning the stochastic nature of investment return and analyses three investment parameters: return, reliability, and risk. Findings & value added: The paper presents investment results in the USA stock market during the 2019-2020 time period. Based on the historical data, the investment portfolio is proposed, highlighting its generated return and reliability. The possibilities to invest in portfolios with different risk levels are disclosed, attention to the investor’s risk resistance level is paid. Also, an experiment in the exchange market has been conducted. After performing experiments in capital and exchange markets, the traditional technique of investment portfolio optimal solution search has been diversified and broadened. The results of the research are useful for researchers in the field of investment, as well as for individual and institutional investors.

Disasters such as the COVID-19 pandemic outbreak can bring challenges to trades all over the world. How to enhance the supply chain resilience and strengthen the competitiveness of enterprises in emergency situations has become a significant topic. To improve the emergency response capability of supply chains, this study aims at establishing a novel decision-making method to deal with the supplier selection problem during the COVID-19 pandemic outbreak based on a novel preference information represent tool, the hesitant fuzzy linguistic preference relation (HFLPR). To achieve this goal, we first introduce the alpha-cut of hesitant fuzzy linguistic elements and transform each hesitant fuzzy linguistic element in an HFLPR into the corresponding semantic considering the degree of confidence of the decision-makers regarding the evaluation values. Then, the utility matrix of an HFLPR is proposed. Afterwards, we construct two dual linear programming models to obtain interval weights from an HFLPR based on the concept of the least upper and the greatest lower bounds. An approach to ranking the obtained interval weights is introduced based on the concept of possibility degree between intervals. The procedure is summarised for the facility of implementation and we apply it to a case study about the resilient supplier selection during the COVID-19 pandemic outbreak. Some comparative analyses are presented to demonstrate the advantages of our method.

Information and communications technologies promote change in the service sector, and the banking sector is not an exception. Finding what factors impact consumer satisfaction with service and lead to loyalty is invariably important for business. However, it is important to begin with evaluating the aspects that are specific to the market and service. The purpose of this study was to investigate the factors affecting customer loyalty in Mobile Banking. Following the model designed by the researchers, consideration was given to mediator variables of satisfaction, trust, and customer service to examine how factors such as perceived risk, relative advantages, and usability affect customer loyalty. In this study, customers of an Iranian bank (Shahr Bank) based in the city of Tehran constituted the statistical population. The descriptive survey method was used on a sample that was selected through a cluster-convenience method and included 411 Shahr Bank's customers resident in the east, west, north, south, and centre of the city of Tehran. Structural Equation Modelling (SEM) test and the LISREL 8.8 software were used to analyse the data and to determine what role each factor plays on loyalty. The results showed that such factors as relative advantages, satisfaction, and trust have the most significant impact on customer loyalty. However, the effect of usability on customer service was not confirmed. Furthermore, it was identified that perceived risk has a negative impact on loyalty.