In our study, we examined 11 designated tourist destinations in Hungary, which can also be interpreted as tourism products including services, infrastructure and attractions. The National Tourism Development Strategy (NTS) also puts a strong emphasis on digitalisation, as it is an unstoppable process with a significant impact on tourism, thanks to globalisation, increasing competition, accelerating information flows and the dominant paradigm shifts on the demand and supply side. We used both qualitative and quantitative methods in our primary research. First, we conducted in-depth interviews with several important tourism service providers in Hungary on the topic of the digitalisation of tourism. A professional questionnaire, addressed to the offices responsible for destination management was distributed in the designated tourist destinations in Hungary in order to get a more comprehensive picture of the attitudes towards digitalisation in the regions under study. In the course of our work, we managed to classify the destinations into three distinctly different clusters. Our hypothesis—that the higher the digitalisation of a tourist destination is, the higher the average length of stay—was partially confirmed by calculating the regional value of the digitalisation, logistic regression analysis, slope and the individual factor categories.

Blockchain technology has increasingly attracted the attention of the financial service sector, customers, and investors because of its distinctive characteristics, such as transparency, security, reliability, and traceability. The paper is based on a Systematic Literature Review (SLR). The study comprehended the literature and the theories. It deployed the technology-organization-environment (TOE) model to consider technological, organizational, and environmental factors as antecedents of blockchain adoption intention. The paper contributes to blockchain literature by providing new insights into the factors that affect the intention to adopt blockchain technology. A theoretical model incorporates antecedents of blockchain adoption intention to direct an agenda for further investigations. Researchers can use the model proposed in this study to test the antecedents of blockchain adoption intention empirically.

Due to the gradual growth of urbanization in cities, urban forests can play an essential role in sequestering atmospheric carbon, trapping pollution, and providing recreational spaces and ecosystem services. However, in many developing countries, the areas of urban forests have sharply been declining due to the lack of conservation incentives. While many green city spaces have been on the decline in Thailand, most university campuses are primarily covered by trees and have been serving as urban forests. In this study, the carbon sequestration of the university campuses in the Bangkok Metropolitan Region was analyzed using geoinformatics technology, Sentinal-2 satellite data, and aerial drone photos. Seventeen campuses were selected as study areas, and the dendrometric parameters in the tree databases of two areas at Chulalongkorn University and Thammasat University were used for validation. The results showed that the weight average carbon stock density of the selected university campuses is 46.77 tons per hectare and that the total carbon stock and sequestration of the study area are 22,546.97 tons and 1402.78 tons per year, respectively. Many universities in Thailand have joined the Green University Initiative (UI) and UI GreenMetric ranking and have implemented several campus improvements while focusing on environmental concerns. Overall, the used methods in this study can be useful for university leaders and policymakers to obtain empirical evidence for developing carbon storage solutions and campus development strategies to realize green universities and urban sustainability.

We analyze Thailand’s projected 2023–2030 energy needs for power generation using a constructed linear programming model and scenario analysis in an attempt to find a formulation for sustainable electricity management. The objective function is modeled to minimize management costs; model constraints include the electricity production capacity of each energy source, imports of electricity and energy sources, storage choices, and customer demand. Future electricity demands are projected based on the trend most closely related to historical data. CO₂ emissions from electricity generation are also investigated. Results show that to keep up with future electricity demands and ensure the country’s energy security, energy from all sources, excluding the use of storage systems, will be necessary under all scenario constraints.

Personality traits refer to enduring patterns of emotions, behaviors, and thoughts that shape an individual’s distinct character, influencing how they perceive and engage with their environment. This quantitative study aims to underscore the influence of personal factors and the role of educational institutions in mapping sustainable green entrepreneurial intentions among university students in Saudia Arabia. To examine the impact of personality traits and entrepreneurship education on students’ green initiatives, the research employs a quantitative research method, collecting data through a structured questionnaire survey from 494 participants who enrolled in the entrepreneurship education at King Faisal University. Structural equation modeling via SmartPLS 3 is employed for data analysis. The study reveals significant associations between the need for achievement, proactiveness, risk-aversion, self-efficacy, and entrepreneurship education with green entrepreneurial intentions. Our research findings demonstrate that the inclusion of entrepreneurship education in the curriculum has a noteworthy and favorable influence on the intention to engage in green entrepreneurship (β = −0.105, t = 3.270, p < 0.001). Additionally, it is worth noting that the desire for achievement remains significantly associated with the intention to engage in green entrepreneurship (β = 0.120, t = 3.588, p < 0.000). Furthermore, the proactive behavior of individuals has a positive and constructive impact on the intention to engage in green entrepreneurship (β = 0.207, t = 4.272, p < 0.000). Similarly, the inclination to avoid risk is found to have a beneficial and significant influence on the intention to engage in green entrepreneurship (β = 0.336, t = 4.594, p < 0.000). Lastly, it is worth highlighting that individuals’ belief in their own abilities, referred to as self-efficacy, is positively and significantly linked to the intention to engage in green entrepreneurship (β = 0.182, t = 2.610, p < 0.009). The research carries social, economic, and academic implications by emphasizing the positive contribution of green entrepreneurs to the future. Practical recommendations for policymakers and decision-makers are provided.

This paper foresees a critical analysis and development of a legislative proposal for the effective implementation of blockchain technology in Civil Mediation in conflicts in condominiums. This paper provides a legal analysis of personal, property rights and condominium disputes, applying blockchain technology for the purpose of self-executing civil mediation. This paper provides several solutions for conflicts in condominiums: Condominium Statute in blockchain, telematic attendance and voting systems, the self-execution of civil mediation agreements in conflicts in condominiums and Tokenization and IoT for property remote control in condominiums. The novelty of this research lies in the fact that, based on the experience of civil mediation in conflicts in condominiums, foreseen in US States and in other States such as Canada, Spain, the regulation is adapted for the correct application of blockchain technology for mediation in conflicts in condominiums.

Decentralized cryptocurrencies, such as bitcoin, use peer-to-peer software protocol, disintermediating the traditional intermediaries that used to be banks and other financial intermediaries, effectuating cross-border transfer. In fact, by removing the requirement for a middleman, the technology has the potential to disrupt current financial transactions that rely on a trusted authority or intermediary operator. Traditional financial regulation, primarily based on the command-and-control approach, is ill-suited to regulating decentralized cryptocurrencies. The present paper aims to investigate the policy option most suitable for regulating decentralized cryptocurrencies. The study employs content analysis method to effectuate the purpose of the study. The paper argues that the combination of both direct and indirect regulatory approaches would be a feasible option for regulating decentralized cryptocurrencies. The absence of centralized authority and the borderless nature of decentralized cryptocurrencies would make them antithetical to centralized direct regulation. Therefore, the findings of the study suggest that regulators should focus on regulating intermediaries bridging the connection between the online world (crypto ecosystem) and the physical world (the point of converting crypto into fiat money). These intermediaries can work as passive actors or surrogate regulators who are indirectly responsible for implementing policy options on behalf of the central authority.

Purpose—In the business sector, reliable and timely data are crucial for business management to formulate a company’s strategy and enhance supply chain efficiency. The main goal of this study is to examine how strong brand strength affects shareholder value with a new Supplier Relationship Management System (SRMS) and to find the specific system qualities that are linked to SRMS adoption. This leads to higher brand strength and stronger shareholder value. Design/Methodology/Approach—This study employed a cross-sectional design with an explanatory survey as a deductive technique to form hypotheses. The primary method of data collection used a drop-off questionnaire that was self-administered to the UAE-based healthcare suppliers. Of the 787 questionnaires sent to the healthcare suppliers, 602 were usable, yielding a response rate of 76.5%. To analyze the data gathered, the study used Partial Least Squares Structural Equation modelling (PLS-SEM) and artificial neural network (ANN) techniques. Findings—The study’s data proved that SRMS adoption and brand strength positively affected and improved healthcare suppliers’ shareholder value. Additionally, it demonstrates that user satisfaction is the most significant predictor of SRMS adoption, while the results show that the mediating role of brand strength is the most significant predictor of shareholder value. The results demonstrated that internally derived constructs were better explained by the ANN technique than by the PLS-SEM approach. Originality/Value—This study demonstrates its practical value by offering decision-makers in the healthcare supplier industry a reference on what to avoid and what elements to take into account when creating plans and implementing strategies and policies.