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Abstract: This paper examines normality in time series econometrics for a sustainable energy transition. By analysing data from January 1997 to December 2021, this study integrates macroeconomic, environmental, and energy data to gain insights into the potential changes in daily commuting patterns among Slovenians. Various methods, including unit root tests such as the augmented Dickey–Fuller (ADF), Kwiatkowski–Phillips–Schmidt–Shin (KPSS), and Zivot–Andrews (Z-A), as well as other tests, are employed. Additionally, the vector autoregressive (VAR) model, Granger Causality and regression analysis determine the impact. This paper contributes to uncovering valuable information within data from macrovariables using macroeconometric techniques. It also provides insights that can support evidence-based decision-making for sustainable energy transition policies in Slovenia. The results of the normality tests indicate that most macro variables are integrated; there is a need for a careful analysis of integration levels and appropriate testing methods. These findings have implications for policymakers, researchers, and practitioners in economics, the environment, and energy supply. At the same time, this research highlights that gross domestic product, unemployment, inflation, and carbon dioxide positively impact car usage among Slovenians, while gasoline prices and commuters have a negative one. While the recently investigated development of sustainable commuting does not work, the study highlights an innovation: the connection of time series econometrics, which offers a better understanding of future commuting patterns on energy consumption and their causalities.
Found in: osebi
Keywords: case study, commuting, energy-saving, VAR model
Published: 16.10.2023; Views: 544; Downloads: 17
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Abstract: With the emergence of the metaverse, countries’ digital efforts to create tourism opportunities have given rise to the possibility of capitalising on digital content which, along with physical tourism experiences, can generate further income and enhance a country’s reputation. Non-fungible tokens (NFTs), a unique application of blockchain technology, offer an enabling technology in several sectors, including tourism. Therefore, this study aims to explore the official tourism websites of Croatia and Slovenia and analyse current NFT applications in tourism economics. The methodology focuses explicitly on sentiment analysis, blockchain and machine learning. The paper introduces various applications currently in place, including Slovenia’s “I Feel Nft” project. The research shows that the main benefits of using NFT and sentiment analysis in the tourism economy are the promotion and presentation of major tourist destinations, exhibitions, works of art, and companies’ products in tokens, digital content and souvenirs. The adoption of sentiment analysis and NFTs in the tourism economy is still open to proposals for implementing public quantitative data metrics. Therefore, the scientific contribution of this research is essential in terms of operational recommendations and defining metrics for measuring the effectiveness of those methodologies and their applications in the tourism economy. On top of that, the practical contribution lies in monitoring the influx of tourists, and highlighting their increase over time and the significance of new technology in time series tourism research.
Found in: osebi
Published: 04.01.2024; Views: 36855; Downloads: 17
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