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The purpose of this study is to see the energy relation to economic growth and find a way to solve the energy crisis for Bangladesh. Bangladesh is facing a high rate depletion of traditional energy sources. Renewable energy technology may be an alternative solution to meeting Bangladesh’s rising energy demand. Despite huge potential, Bangladesh fails to use renewable energy sources properly due to insufficient information and technical knowledge. The present research studied the current energy condition and potentiality of renewable energy with its influence on economic growth in Bangladesh.

This study analyzes the relationship between renewable energy consumption and economic growth of Bangladesh for the period of 2001–2016, based on yearly data, by using multiple regression model where augmented Dickey–Fuller unit root test has been chosen for testing the viability.

The result of this study showed that economic growth of Bangladesh is influenced positively by the consumption of renewable energy.

In addition, SWOT analysis has also done to develop a roadmap, and suggest some policies which will be able to accomplish the country’s climbing energy demands for a short- and long-term solution.

This study is an original work for Bangladesh, showing the results of the relationship between renewable energy consumption and economic growth. Therefore, this research will be useful to contribute to the literature review in the near future.

The need for an efficient enterprise risk management (ERM) has never been greater than today when organisations face complex and interconnected risks targeting their business models. Macroeconomics and geopolitical uncertainties, digital transformations of industries and sectors, cybersecurity, and climate change, among other trends, present significant uncertainties. This article aims to analyse the scientific papers on research specific to ERM and review the links between the researched area and market or corporate governance topics. Risk management is underdeveloped in many organisations; the current standard for risk management is a reactive approach. It is usually treated in isolation rather than as a core competency and a strategic asset. As a result, risk management processes are ineffective and seen as adding value to decision-making and responding to uncertainties. Based on the literature, the scope is to set up the framework for future research on ERM by building a bibliometric analysis and examining articles collected from the Web of Science Core Collection database. The study identified the essential research on this topic based on the citations of the papers and the author’s countries with the highest number of publications and citations. VOSviewer software analysed the ERM system based on keywords, citations, geographical distribution, and authorships. The research proves a strong connection between the ERM and corporate governance topics considering the stage where most countries are regarding this subject.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

Owing to the dramatic rise of FinTech credit in the financial sector, this study describes its knowledge and intellectual structure and paves the way for future research.

The study employs citation analysis, keyword analysis, co-author analysis, co-citation analysis and bibliographic coupling on 268 peer-reviewed articles published during 2010–2021 and extracted from the Web of Science database.

Research on FinTech credit has picked up momentum from 2016, with majority contributions from China, followed by UK and USA. International Journal of Bank Marketing is found to be the most productive journal. Co-citation analysis reveals that past studies have focused on three dominant themes, viz. (a) factors that influence user intention to adopt technological products and services (b) borrowers' and lenders' characteristics that impact fund-raising in FinTech credit platforms and (c) evolution of FinTech market over the years. Bibliographic coupling reveals that recent trends in FinTech credit include (a) impact of emerging technologies like blockchain, artificial intelligence, big data on financial system, (b) factors that encourage consumers to adopt the FinTech products and services, (c) mechanisms by which FinTechs have transformed formal credit markets, (d) factors that lead to successful fundraising in FinTech platforms and (e) critical perspectives on digital lending platforms.

To the best of the authors' knowledge, this is a pioneering study undertaking an exhaustive analysis of FinTech credit as a research area. The study offers valuable insights on potential topics of research in FinTech credit domain like investigating Balance Sheet Lending Model, investigating the impact of FinTechs on financial system, and new markets by collaborating with scholars of other regions.

The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends, hotspots, and directions for future research.

The data source for this paper is the Web of Science Core Collection, and 7,154 publications and related information have been derived. We use recognized bibliometric indicators to evaluate publications and visually analyze them through scientific mapping tools (VOS Viewer and CiteSpace).

The analysis results show that China is the most productive and influential country/region. East Asia countries have strong cooperation with each other and also have cooperation with other countries. The study shows that risk management has been involved in various fields such as credit, supply chain, health emergency and disaster especially in the background of COVID-19. We also found that machine learning, especially deep learning, has been playing an increasingly important role in risk management due to its excellent performance.

This paper focuses on studying risk management in East Asia, exploring its publication's fundamental information, citation and cooperation networks, hotspots, and research trends. It provides some reference value for scholars who are interested or further research in this field.