We write emails, listen to music online, pay an invoice through internet banking, and have an eID. These all are e-services. But how can we define an e-service? Numerous definitions of e-services generalize their essence, reflect the specific characteristics and certain elements of their production process. They are important for economic theory and practice, but none of them have acquired general acceptance. Supranational institutions, scientists and researchers attempt to seek one definition. A lot of definitions explain e-services only as e-government, e-learning and e-commerce. It is insufficient for further classification. We pay attention to classification of e-services in this chapter. Some of them divided e-services according to the branch, processes etc. Classification as e-co model, e-ladder, E-Diamond model, classification of service and product to the dimensions in a 2 * 2 matrix, and fulfilment-product classification have been introduced. The main goal of our study is to provide an extensive review of e-service definitions and classifications. Based on the findings we propose our own classification of e-services. The result of our work is a new 3D model. The 3D model is constructed according to bases of stages models and Diamond model, but we respect also user's needs and their fulfilment in process. In this empirical analysis of e-service definitions and classifications, we have compared known definitions and classifications and proposed a new model. Most models and schemes only deal with public e-services. We bring a new perspective, the classification is intended for all known e-services

This article explores the significance of Bitcoin halving events within the cryptocurrency ecosystem and their impact on market dynamics. While the existing literature addresses the periods before and after Bitcoin halving, as well as financial bubbles, there is an absence of forecasting regarding Bitcoin price in the time after halving. To address this gap and provide predictions of Bitcoin price development, we conducted a rigorous analysis of past halving events in 2012, 2016, and 2020, focusing on Bitcoin price behaviour before and after each occurrence. What interests us is not only the change in the price level of Bitcoins (top and bottom), but also when this turn occurs. Through synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, the peaks reached, and price troughs. Our approach involved employing methods such as RSI, MACD, and regression analysis. We looked for the relationship between the price of Bitcoin (top and bottom) and the number of days after the halving. We have uncovered a mathematical model, according to which the next peak will be reached 19 months (in November 2025) and the trough 31 months after Bitcoin halving 2024 (in November 2026). Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. These discoveries significantly enhance our understanding of Bitcoin’s trajectory and its implications for the finance cryptocurrency market. By offering novel insights into cryptocurrency market dynamics, this study contributes to advancing knowledge in the field and provides valuable information for cryptocurrency markets, investors, and stakeholders.

Taxing Bitcoin and other cryptocurrencies presents a significant challenge due to their decentralised and pseudonymous nature, complicating enforcement and fostering regulatory inconsistencies across jurisdictions. This study systematically reviews the existing literature on cryptocurrency taxation, critically analysing 38 academic studies to identify key themes, challenges, and gaps in global regulatory frameworks. Using a structured seven-step methodology, it examines how jurisdictions approach cryptocurrency taxation, highlighting ten thematic categories, including jurisdictional comparisons, taxable events, and compliance mechanisms. The findings reveal persistent regulatory fragmentation and a lack of harmonisation, underscoring the need for international cooperation to establish coherent tax policies. By synthesising existing research and identifying unresolved issues, this study contributes to the discourse on balancing technological innovation with fiscal accountability, ultimately advocating for a unified, cross-border approach to cryptocurrency taxation.

This study conceptualizes how artificial intelligence (AI)-based customer engagement strategies can shape consumers’ green purchasing intentions, focusing on the theorized roles of attitude and perceived risk toward green products as articulated in prior literature. Building on contemporary research in sustainable marketing and consumer psychology, the article proposes a conceptual framework in which AI-enabled engagement influences green purchase intention via attitudes, with perceived risk operating as a boundary condition that moderates these effects. To qualitatively substantiate the salience and practical relevance of these constructs, an exploratory sentiment analysis of Amazon reviews for green products was conducted to surface emotional responses, perceived value drivers, and behavioral cues. The review corpus predominantly reflects positive sentiment alongside mixed subjectivity and factual commentary, highlighting recurring decision factors such as product quality, packaging, sustainability claims, and price sensitivity. Consistent with literature, the evidence aligns with the view that personalization and transparency can bolster trust and more favorable attitudes, while perceived risks—spanning greenwashing concerns, cost, and performance doubts—remain obstacles to adoption. Crucially, the sentiment analysis is presented as illustrative and does not statistically test the proposed mediation or moderation pathways; rather, it offers qualitative support that complements the literature-based conceptual model. The study contributes by integrating insights from digital technologies, consumer psychology, and sustainable marketing to guide authentic, strategic engagement practices that can encourage eco-conscious behavior.

Websites, nowadays, are used not only as a sales method and information tool, but also as a communication tool. Almost every company has a website. Universities and colleges understand their strength, too. In this article, we describe theory of usability of university website and one of the usability testing methods—eye tracking. We use eye tracking to assess the usability of University of Žilina website. We present and use different analysis: Scan Path and Focus map. We identify many usability problems whose removal will help to create new pages and, thus, increasing their effectiveness.

This paper describes an investigation of the brain activity during browsing websites. The study was carried out at the University of Žilina in Slovakia. Data, in the form of scan path from eye tracking and signal from Electroencephalograph, were collected and analysed. The researchers found higher brain activity only during decision making processes. During browsing websites there was no clearly increased brain activity. The findings suggested that visual stimuli of website might have had a bearing on the human active thinking, but it could not be clearly identified. The results also supported the notion that the internet users do not read the websites.