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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 examines herd behavior in the cryptocurrency market at the aggregate level and the determinants of herd behavior, such as asymmetric market returns, the coronavirus disease 2019 (COVID-19) pandemic, 2021 cryptocurrency's bear market and the network effect.

The authors applied the Google Search Volume Index (GSVI) as a proxy for the network effect. Since investors who are interested in a particular issue have a common interest, they tend to perform searches using the same keywords in Google and are on the same network. The authors also investigated the daily returns of cryptocurrencies, which are in the top 100 market capitalizations from 2017 to 2022. The authors also examine the association between return dispersion and portfolio return based on aggregate market herding model and employ interactions between herding determinants such as, market direction, market trend, COVID-19 and network effect.

The empirical results indicate that herding behavior in the cryptocurrency market is significantly captured when the market returns of cryptocurrency tend to decline and when the network effect of investors tends to expand (e.g. such as during the COVID-19 pandemic or 2021 Bitcoin crash). However, the results confirm anti-herd behavior in cryptocurrency during the COVID-19 pandemic or 2021 Bitcoin crash, regardless of the network effect.

These findings help investors in the cryptocurrency market make more rational decisions based on their determinants since cryptocurrency is an alternative investment for investors' asset allocation. As imitating trades lead to return comovement, herd behavior in the cryptocurrency has a direct impact on the effectiveness of portfolio diversification. Hence, market participants or investors should consider herd behavior and its underlying factors to fully maximize the benefits of asset allocation, especially during the period of market uncertainty.

Most previous studies have focused on herd behavior in the stock market. Although some researchers have recently begun studying herd behavior in the cryptocurrency market, the empirical results are inconclusive due to an incorrectly specified model or unclear determinants.

The case describes a hypothetical hedge fund manager who is examining whether to invest in bitcoin. The case discusses potential risks and rewards of investing in bitcoin, the role of bitcoin and digital currencies more broadly, and financial innovation in the space, such as ICOs. It can be taught as part of a second-year MBA elective course in investments, financial institutions/capital markets, or fintech.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

This study tests whether environmental awareness affects firm creation by using Google Trends data and a novel region-level data set from Italy.

Forward-looking entrepreneurs drive firm creation. The authors hypothesize that more environmentally conscious entrepreneurs will emerge as environmental awareness rises, increasing the number of green and energy firms. The authors test the prediction using Google Trends data and a novel region-level data set from Italy.

The authors find that not only the number of green and energy-innovative firms but also that of all innovative start-ups increases with rising environmental consciousness. The results imply some “innovation spillover” effects from green sectors to other industries with rising environmental awareness.

The paper hypothesizes that as environmental awareness rises, more environmental-conscious entrepreneurs will emerge, which would increase the number of green and energy firms. Robustness and falsification tests are also offered.

Research concerning the inclusion of individuals with disabilities in tourism activities began long before this field of study was formally named. This has led scholars to use a variety of expressions to refer to what is now known as accessible tourism (AT). Given that this diversity of terms can complicate locating relevant publications, this paper aims to examine the terminology used in the context of AT.

This study conducts an exhaustive literature review and a statistical analysis of 613 documents collected from Scopus, published between 1984 and 2022.

The results suggest that, despite the widespread use of “Accessible Tourism” in recent literature, most papers published before 2010 cannot be retrieved using this term. Additionally, the longitudinal analysis of scientific production revealed four distinct stages based on the number of annual publications.

This paper has limitations that could inspire future studies, such as relying solely on Scopus for data collection, including only academic papers, limiting the number of references and narrowing the search to specific terms. Future investigations could compare these findings using a greater amount of data collected from other databases (e.g. Google Scholar), including non-academic writings (e.g. newspapers and Webpages), exploring the efficiency of different search strategies (e.g. silver market) and delving deeper into the evolution of the AT discourse in society.

Policymakers and tourism stakeholders can leverage the insights of this paper to standardise their vocabulary in communication and operational strategies. Scholars can enhance the efficiency of literature searches and develop new lines of knowledge inspired by terms traditionally used to refer to AT.

This paper encourages continued investigation into AT and underscores the importance of language in developing a more inclusive society.

This research pioneers the analysis of the evolution of AT synonymy by years, nations and authors. It provides evidence of how linguistic choices reflect changes in the social understanding of disability. This study proposes a framework to distinguish AT from other tourism models, facilitating unified communication among stakeholders. It presents strategies to improve efficiency in locating studies in the AT area and advocates for an inclusive society that uses language respectful to all individuals.

本研究对从Scopus收集的1984年至2022年间发表的613篇文献进行了详尽的文献回顾和统计分析。

关于将残疾人纳入旅游活动的研究早在这一研究领域正式命名之前就开始了。这导致学者们使用各种各样的表达来指代现在被称为无障碍旅游(AT)的概念。鉴于这种术语的多样性会使相关出版物的定位复杂化, 本文旨在研究AT语境中使用的术语。

结果表明, 尽管“无障碍旅游”在最近的文献中被广泛使用, 但2010年之前发表的大多数文章都无法使用该术语进行检索。此外, 科学产出的纵向分析显示, 基于年度出版物的数量, 有四个不同的阶段。

这篇论文有一些局限可启发未来的研究, 比如仅仅依靠Scopus进行数据收集, 只包括学术论文, 限制参考文献的数量, 将搜索范围缩小到特定的术语。未来的调查可以使用从其他数据库(如Google Scholar), 包括非学术著作(如报纸、网页), 收集的大量数据来比较这些发现, 探索不同搜索策略(如白银市场)的效率, 并更深入地研究AT话语在社会中的演变。

政策制定者和旅游业利益相关者可以利用本文见解来标准化他们在表达和操作策略中的词汇。学者们可以提高文献检索的效率, 并从传统上用于指AT的术语启发中建立新的知识线。

本文鼓励继续研究无障碍旅游, 并强调语言在发展更具包容性的社会中的重要性。

这项研究是对AT同义词的年代、国家和作者的演变进行分析的开创。它为语言选择如何反映社会对残疾理解的变化提供了证据。本研究提出了一个AT有别于与其他旅游模式的框架, 促进利益相关者之间的统一沟通。它提出了提高AT领域定位效率研究的策略, 并倡导建立一个尊重所有个人的语言的包容的社会。

La investigación relativa a la inclusión de las personas con discapacidad en las actividades turísticas comenzó mucho antes de que se diera un nombre formal a este campo de estudio. Esto ha llevado a los estudiosos a utilizar una gran variedad de expresiones para referirse a lo que ahora se conoce como Turismo Accesible (TA). Dado que esta diversidad de términos puede complicar la localización de publicaciones relevantes, este artículo pretende examinar la terminología utilizada en el contexto del TA.

Este estudio realiza una revisión exhaustiva de la literatura y un análisis estadístico de 613 documentos recopilados de Scopus, publicados entre 1984 y 2022.

Los resultados sugieren que, a pesar del uso generalizado de “Turismo Accesible” en la literatura reciente, la mayoría de los artículos publicados antes de 2010 no pueden recuperarse utilizando este término. Además, el análisis longitudinal de la producción científica reveló cuatro etapas distintas en función del número de publicaciones anuales.

Este trabajo tiene limitaciones que podrían inspirar futuros estudios, como basarse únicamente en Scopus para la recopilación de datos, incluir sólo artículos académicos, limitar el número de referencias y restringir la búsqueda a términos específicos. Futuras investigaciones podrían comparar estos Resultados utilizando una mayor cantidad de datos recogidos en otras bases de datos (por ejemplo, Google Scholar), incluyendo escritos no académicos (por ejemplo, periódicos, páginas web), explorando la eficacia de diferentes estrategias de búsqueda (por ejemplo, el mercado plateado) y profundizando en la evolución del discurso del TA en la sociedad.

Los responsables políticos y las partes interesadas en el turismo pueden aprovechar las ideas de este documento para normalizar su vocabulario en las estrategias de comunicación y operativas. Los estudiosos pueden mejorar la eficacia de las búsquedas bibliográficas y desarrollar nuevas líneas de conocimiento inspiradas en los términos utilizados tradicionalmente para referirse al TA.

Este artículo anima a seguir investigando sobre el turismo accesible y subraya la importancia del lenguaje en el desarrollo de una sociedad más inclusiva.

Esta investigación es pionera en el análisis de la evolución de la sinonimia del TA por años, naciones y autores. Aporta pruebas de cómo las elecciones lingüísticas reflejan los cambios en la comprensión social de la discapacidad. Este estudio propone un marco para distinguir la TA de otros modelos turísticos, facilitando la comunicación unificada entre las partes interesadas. Presenta estrategias para mejorar la eficacia en la localización de estudios en el ámbito de las TA y aboga por una sociedad inclusiva que utilice un lenguaje respetuoso con todas las personas.

It is important to implement artificial intelligence (AI) because it can simplify and solve complex problems faster than humans. Because AI learns about people and their behavior from the first purchase, AI marketing can boost marketing efforts by leveraging data to target extremely precise consumer groups. There is a debate about the efficacy of AI marketing due to the constraints and limits imposed by the system's nature. This chapter presents insights from published studies regarding the relationship of AI with marketing and how AI can affect marketing. A real-world example of Netflix's usage of AI in marketing has been demonstrated. Then, consumer attitudes regarding AI were revealed. Then, several ethical considerations concerning AI were highlighted. Finally, the anticipated future of AI marketing was addressed. This chapter demonstrated the significance of firms implementing AI marketing to get a competitive advantage. Although some of the difficulties mentioned in this study need to be resolved, AI marketing has a bright future. There are ethical concerns about bias and privacy that should be addressed further. This chapter will encourage firms to use AI systems in marketing, and it will open the door to concerns that will need to be investigated academically in the future.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.