The fashion industry ranks among the most resource-intensive and environment-polluting industries. Circularity has been discussed as a solution to these problems. However, the transition towards a circular economy (CE) requires fundamental changes in the behavior and actions of all market entities. Consumer interest in sustainability and circularity can stimulate businesses to become more responsible and to offer circular solutions, and thus create a significant competitive advantage for these firms in a globalized market. This paper examines consumer attitudes towards the new circular models in the fashion industry (e.g. slow fashion, swapping, clothes rent, etc.). Consumer knowledge of these models, consumer willingness to support them as well as a correlation to selected demographic characteristics will be described along with consumer attitudes towards textile products made of waste and recycled material. Results will be introduced from a questionnaire survey carried out in October and November 2019 using the sample of 468 respondents in Slovakia. The obtained data were evaluated using statistical methods (Pearson Chi-Square, Wilcoxon test, Spearman’s correlation coefficient). While generally a low awareness of Slovak consumers of new models in the fashion industry was confirmed, the willingness of consumers to engage and support circular solutions was shown, especially among the younger generations. These results show that businesses that react to consumer expectations regarding circularity by offering products and services with environmental benefits may increase their competitiveness.

Research background: Generative artificial intelligence (AI) and machine learning algorithms support industrial Internet of Things (IoT)-based big data and enterprise asset management in multiphysics simulation environments by industrial big data processing, modeling, and monitoring, enabling business organizational and managerial practices. Machine learning-based decision support and edge generative AI sensing systems can reduce persistent labor shortages and job vacancies and power productivity growth and labor market dynamics, shaping career pathways and facilitating occupational transitions by skill gap identification and labor-intensive manufacturing job automation by path planning and spatial cognition algorithms, furthering theoretical implications for management sciences. Generative AI fintech, machine learning algorithms, and behavioral analytics can assist multi-layered payment and transaction processing screening with regard to authorized push payment, account takeover, and synthetic identity frauds, flagging suspicious activities and combating economic crimes by rigorous verification processes. Purpose of the article: We show that edge device management functionalities of cloud industrial IoT and virtual robotic simulation technologies configure plant production and route planning processes across cyber-physical production and industrial automation systems in multi-cloud immersive 3D environments, leading to tangible business outcomes by reinforcement learning and convolutional neural networks. Labor-augmenting automation and generative AI technologies can impact employment participation, increase wage and wealth inequality, and lead to potential job displacement and massive labor market disruptions. The deep learning capabilities of generative AI fintech in terms of adaptive behavioral analytics and credit scoring mechanisms can enhance financial transaction behaviors and algorithmic trading returns, identify fraudulent payment transactions swiftly, and improve financial forecasts, leading to customized investment recommendations and well-informed financial decisions. Methods: Machine learning-based study selection process and text mining systematic review management software and tools leveraged include Abstrackr, CADIMA, Colandr, DistillerSR, EPPI-Reviewer, JBI SUMARI, METAGEAR package for R, SluRp, and SWIFT-Active Screener. Such reference management systems are harnessed for methodologically rigorous evidence synthesis, study selection and characteristic extraction, predictive document classification, machine learning-based citation and record screening, bias assessment, article retrieval automation, and document classification and prioritization. Findings & value added: Industrial IoT and 3D augmented reality technologies can create business value by streamlining virtual product and remote asset management across extended reality-based navigation and robotic autonomous systems in smart factory environments by generative AI and machine learning algorithms, articulating business organizational level and theory of management implications. 3D simulation and operational modeling tools can execute and complete complex cognitive task-oriented and knowledge economy jobs, producing first-rate quality outputs swiftly while leading to unemployment spells, labor market disruptions, job displacement losses, and reduced earnings by machine learning clustering and spatial cognition algorithms. Generative AI decentralized finance, interoperable blockchain networks, cash flow management tools, and asset tokenization can mitigate fraud risks, enable digital fund and crypto investing servicing, and automate treasury operations by integrating real-time payment capabilities, routing and configurable workflows, and lending and payment technologies.

Research background: Islamic banks appeared on the world scene as active players over two decades ago. Many of the principles upon which Islamic banking is based have been commonly accepted all over the world. Financial institutions driven by Islamic principles acquire new clientele without excessive marketing, due to preservation of conservative values. Contrary to the conventional investment banks, their value is based on real money, and not on virtual activities from swap and derivative assets. Competition between conventional (or traditional) and Islamic banks is increasing every day, moreover, Islamic financial institutions are more resistant to the crisis. Our study contains analysis and comparison of economic efficiency of the conventional and Islamic banks. Besides the fact that traditional and Islamic banks apply inputs differently, the reason of better efficiency of Islamic banks may be connected with different approach to the risk management and control of the banking operations by the Sharia commission. Purpose of the article: The main aim of the article is to compare the economic efficiency of the conventional and Islamic banks in Europe. Methods: To achieve the aim of the paper, firstly the selected financial indicators of traditional and Islamic banks in Europe were compared. The second, the analysis of the economic efficiency of the selected 1460 conventional and Islamic financial institutions using DEA methods was conducted. Findings & Value added: Research results indicated methodological differences in the economic efficiency measuring in the Islamic banks. At the same time, the higher economic efficiency of Islamic banks was confirmed. The results are motivating for the follow-up investigation into the causes of higher efficiency of Islamic banks compared to traditional banks.

CSR (Corporate Social Responsibility) is an important part of communication with stakeholders and a response to the need for non-fi nancial reports. Regrettably, the rules of non-fi nancial reporting are almost not regulated. CSR reports are drafted using a variety of principles and guidelines, which limits comparisons across enterprises, transparency and assessment of progress. The reasons for reporting non-fi nancial information cited in the specialist literature, and by enterprises preparing CSR reports are examined, and the benefi ts of standardising reports of nonfi nancial information are determined. The literature review and empirical research into the motivations for CSR reporting and the trends in reporting of non-fi nancial information helped to verify the initial hypotheses: 1. Communication with stakeholders is the fundamental reason for reporting non-fi nancial information. This is confi rmed by the literature review, with most authors believing this is the prime reason for preparing CSR reports. Authors indicating other motivations still treat it as the fundamental cause which exists jointly with other motivations. 2. The need to standardise CSR reporting to ensure its transparency and clarity is noted by reporting organisations. This is proven by surveys of organisations drafting CSR reports – approximately 80% of all reports follow the GRI guidelines. This means the reporting enterprises wish their reports to be clear, transparent and comparable and for their stakeholders to be able to fully satisfy their information requirements. This is also evidence of the care for good relations with stakeholders, who receive standardised data although this is not binding on enterprises. A growing tendency for CSR reporting to follow guidelines other than the GRI can be noted in the entire period under analysis. This will not necessarily be a single compulsory standard, yet a model report would need to be followed to assure transparency and comparability. The Regulations of the Directive 2014/95/EU are a step forward since they will help to standardise rules of reporting non-fi nancial information and will improve its transparency and utility.

Research background: The innovation in Shar??ah-compliant banking products has resulted in the rapidly increasing size of assets in Islamic banks worldwide. The assets of such banks have been growing twice as fast as those of conventional banks. Islamic banks do not depend on conventional interest, speculation, or complex derivatives stemming from banking operations. Instead, their actions in respect of profit/risk sharing, and the clarity of the contract are consistent with Islamic Shar??ah principles, which seek to promote a more equal society. Purpose of the article: This research aims to identify and compare factors influencing the liquidity of Islamic and conventional banks in Europe. Candidate factors are sought amongst profitability, credit quality, credit expansion and capital adequacy indicators. Methodology: First, relevant financial ratios for 249 observations on Islamic banks and 2,306 observations on conventional banks are selected and compared for the period 2013?2017. Second, liquidity is explained separately for each type of banks by panel data regression to identify its determinants in a comparative context. Findings & value added: The results indicate that the impact of the net interest margin on the liquidity ratio of Islamic banks is insignificant, which is obviously due to the prohibition of the use of interest (riba). To the contrary, in conventional banking a higher net interest margin results in a reduction in liquidity. Capital adequacy has a positive influence upon liquidity in both types of banks, but in Islamic banking, the influence is 5.4 times greater. The findings strongly suggest that the liquidity of Islamic and conventional banks is affected by different factors.