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.

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.

Financial literacy is a key competence for responsible decision-making and entrepreneurial readiness. This study looks at how Generation Z’s entrepreneurial participation is impacted by objective, subjective, and calibrated FL. The alignment of perceived and actual knowledge or calibration is highlighted as an understudied factor that influences entrepreneurial behaviour. A mixed-methods approach was applied, combining a survey of 403 Slovak students with structured interviews with secondary school and university teachers. Quantitative analysis used Chi-square tests, Cramer’s V, sign schemes, and MLR. Qualitative interviews provided contextual insights into educational gaps and perceived barriers to entrepreneurship. The findings confirm that a higher financial literacy is positively related to entrepreneurial interest. Objective literacy has a slightly greater predictive value than self-assessed literacy, while calibration emerged as the strongest predictor: realistically, financially literate individuals displayed the highest entrepreneurial engagement, whereas both over- and underestimation of financial knowledge reduced it. Interviews highlighted insufficient financial education, limited practical experience, and fear of risk as major obstacles. By combining three aspects of financial literacy with business goals and offering fresh data from Slovakia, this study makes a contribution to the literature. In similar situations, it makes suggestions for enhancing financial education to support Generation Z’s entrepreneurial potential.