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This study critically examines the transformative impact of the “North Sea TikTok” phenomenon on the marine tourism sector, emphasizing the role of employee training in fostering resilience and adaptability within marine economics and integrated marine systems. It delves into how viral social media trends influence marine tourism destinations, particularly the North Sea, affecting local economies, marine resource management and tourism strategies. By analyzing this trend, the paper seeks to uncover how marine tourism destinations can effectively respond to the challenges and opportunities presented by digital media-driven tourism.

Employing a multidisciplinary framework that merges insights from digital marketing, risk perception in tourism and human resource management, this paper provides a comprehensive qualitative analysis of the “North Sea TikTok” trend. Through a meticulous content analysis of viral videos and an examination of user engagement metrics, alongside a thorough review of contemporary literature in marine tourism and sustainability, the study unpacks the far-reaching implications of social media on marine tourism ecosystems.

The analysis reveals that the “North Sea TikTok” trend has markedly altered public perceptions of the North Sea, catalyzing a shift toward adventure and risk-taking tourism. This pivot promises economic rejuvenation for local tourism sectors and necessitates agile marine management strategies to accommodate the evolving demands. Implementing innovative employee training programs focusing on safety protocols, environmental conservation and digital engagement is central to managing these dynamics. The paper emphasizes integrating sustainable practices to ensure the equitable growth of marine tourism economies and environmental preservation.

This paper pioneers exploring the nexus between social media trends and their operational and strategic impacts on marine tourism management and economics. Synthesizing social media's viral dynamics with marine tourism development introduces groundbreaking insights into adapting marine tourism strategies in the digital age. It emphasizes the critical need for a skilled workforce capable of navigating the complexities of digital trend-driven tourism markets, proposing a novel model for employee training that aligns with the shifting paradigms of marine tourism engagement. This unique contribution advances academic discourse in marine economics and provides practical frameworks for stakeholders aiming to harness social media trends for sustainable tourism development.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

This study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).

Using the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.

The study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.

The novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

This study aims to examine the phenomenon of climate variability and its implications for pastoralists and agro-pastoralists food security in Amibara and Awash Fentale districts of the Afar region, Ethiopia.

The study relied on meteorological records of temperature and rainfall in the study area between 1988 and 2018. Besides, literature on the topic was reviewed to make caveats on the literal picture that comes from quantitative data, and that is the contribution of this study to the existing debate on climate change and variability. The spatiotemporal trend was determined using the Mann–Kendall test and Sen’s slope estimator, while variability was analyzed using the coefficient of variation and standardized anomaly index, and standardized precipitation index/standardized precipitation evapotranspiration index were applied to determine the drought frequency and severity.

The result reveals that the mean seasonal rainfall varies from 111.34 mm to 518.74 mm. Although the maximum and minimum rainfall occurred in the summer and winter seasons, respectively, there has been a decrease in seasonal and annual at the rate of 2.51 mm per season and 4.12 mm per year, respectively. The study sites have been experiencing highly seasonal rainfall variability. The drought analysis result confirms that a total of nine agricultural droughts ranging from moderate to extreme years were observed. Overall, the seasonal and annual rainfall of the Amibara and Awash Fentale districts showed a decreasing trend with highly temporal variations of rainfall and ever-rising temperatures, and frequent drought events means the climate situation of the area could adversely affect pastoral and agro-pastoral households’ food security. However, analysis of data from secondary sources reveals that analyzing precipitation just based on the meteorological records of the study area would be misleading. That explains why flooding, rather than drought, is becoming the main source of catastrophe to pastoral and agro-pastoral livelihoods.

The analysis of temperature and rainfall dynamics in the Afar region, hence the inception of all development interventions, must take the hydrological impact of the neighboring regions which appears to be useful direction to future researchers.

The research is originally conducted using meteorological and existing literature, and hence, it is original. In this research, we utilized a standardized and appropriate methodology, resulting in insights that augment the existing body of knowledge within the field. These insights serve to advance scholarly discourse on the subject matter.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

This article aims to conduct a bibliometric study using structural and relational approaches amongst the extracted documents and investigates the connections between business incubation and entrepreneurship-related papers to describe the field comprehensively.

A total of 259 articles have been retrieved from Scopus database in order to conduct the bibliometric analysis. Performance analysis and science mapping techniques of bibliometrics have been used along with data visualisation software, i.e. VOSviewer and RStudio. The network collaboration and intellectual structures, i.e. bibliographic coupling, co-occurrence analysis, word cloud and trending topics, have been presented to identify the field’s latest trends, themes and development.

The findings highlight annual publication trends, including the most frequently cited articles, the most productive authors, countries and highly influential journals that contribute the most to the said field. The intellectual structures have been developed to identify research themes and trends by running co-occurrence analysis and bibliographic coupling. The findings of this study emphasize the value of technology transfer, mentorship programmes, entrepreneurship education and an emphasis on innovation and creativity through entrepreneurial universities and academia. These findings provide policymakers and administrative officials with crucial guidance for fortifying the pillars of entrepreneurship and education for the comprehensive development of the economy. Further, this article attempts to identify the most influential and relevant publications as well as the newest trends in the area of business incubation in combination with entrepreneurship.

The article contributes not only to broaden the scope of knowledge on the said research discipline but also to comprehend how the field has evolved over a period of time. This study also attracts the interest of scholars/academicians, leading to the significant production of scholarly documents in business incubation and entrepreneurship.

The field of entrepreneurship and business incubation is one of the important pillars for the growth and development of the economy. This piece contributes to this arena by focusing on the areas that must be taken care of by developing the entrepreneurial ecosystem and fostering the progress of startups. The fundamentals of this research highlight the importance of mentorship programs, entrepreneurship education, technology transfer and a focus on innovation and creativity through entrepreneurial education and efforts by universities/academia, giving an important direction to the policymakers and administration for strengthening the pillar of entrepreneurship and education for the holistic development of the economy.

Business incubation is an emerging field of academic research connected to startups, venture formation and entrepreneurship ecosystems, making it a potential scholarly discipline. This study presents a thorough bibliometric analysis over the last three decades, offering comprehensive details on the most significant developments in the field of business incubation. Moreover, the various analytical methods applied to this study make it more attractive.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This paper analyses the impact of the COVID-19 pandemic on Myanmar’s tourism industry, identifying challenges and innovations, and predicting future trends to foster a resilient and sustainable sector.

The study uses a comprehensive analysis of tourism trends, government and private sector responses and changes in tourist behaviour, employing data, case studies and policy reviews.

The pandemic significantly disrupted Myanmar’s tourism, causing economic losses and shifts towards sustainable, outdoor and cultural experiences. Effective strategies by the government and private sector are aiding recovery and suggesting a more diverse and resilient future.

The research is limited by the availability of data during the pandemic, highlighting the need for ongoing strategy adaptation.

The study recommends digitalization, health protocols, domestic tourism focus and sustainable practices for a robust post-pandemic industry.

The study emphasizes the pandemic’s social impact on tourism-dependent communities and the need for inclusive, sustainable tourism practices.

Itprovides unique insights into COVID-19’s multifaceted impact on Myanmar’s tourism, offering valuable information for future sector strategies.

The subject of this paper is the phenomenon of social media aesthetics, which can be perceived as a tool for promoting and building the image of libraries, especially in terms of merchandising. The aim of this paper is to analyse the potential of the dark academia social media trend in the promotion of academic libraries.

The article is based on a review of the social networking sites YouTube and Instagram and an analysis of network resources using the Brand24 tool.

Resources that are described by Internet users as “dark academia” are popular in social media. Dark academia as an aesthetic concept creates potential for the promotion of academic libraries, especially those that are more traditional in terms of their architecture, décor or how they offer their services.

The paper concerns a phenomenon which, although popular socially, has not yet been scientifically analysed in the literature on the subject. Since the topic is new and there is no scientific literature on it, the author had to base the paper on less standard sources of information (e.g. analysis of the content of social media). The article is a review, an introduction, as well as an invitation to further discussion. The author's aim is not to comprehensively cover this topic but only to draw attention to an interesting and rarely discussed issue that has great potential for practical activities.

The topic has great potential for the practical improvement of the promotional activities of libraries, especially older, more traditional libraries, to create a strong and positive image on the basis of characteristics often perceived as weaknesses.

Social media services are powerful social impact tools. Showing the potential role of social media aesthetics for cultural institutions could serve to make the public more aware of the role of the proper use of social media for promotion and image building.

The use of social media aesthetics is very rarely discussed in the subject literature.

This research aims at arriving at a broad scope of the lessons learnt after two years of the coronavirus disease 2019 (COVID-19) pandemic outbreak by analysing the catalyst and inhibiting factors within three aspects of the tourism sector: destination crisis management, tourist behaviour and tourism industry trends.

The methodology of this paper involves semi-structured interviews with high-ranking European travel agents as the agents represent the intermediates between the tourism offer and demand.

Data obtained from travel agents disclosed the factors that catalysed and inhibited the destination, the behaviour of tourists and the tourism industry trends. By contrasting data with previous literature, constructing an overview of the positive and negative outcomes of the pandemic in the tourism sector is possible.

Governments, destination marketing and management organisations and tourism and hospitality organisations could learn from the lessons of COVID-19 outbreak to cope better with future disruptive events affecting the tourism industry.

The paper is novel as it is the first overview that attempts to synthesise the lessons from the COVID-19 pandemic in the tourism sector by analysing tourism sector's three dimensions: the destination, the tourists and the industry.