The soundscape studied has gained increasingly frequent attention across multiple disciplines, especially in tourism and leisure domain. While it has already indicated a unique soundscape provides dynamic and memorable tourism experiences, a clearly mapped perspective across different segmentations of soundscapes, both natural and acoustically created, remains missing. Therefore, a comprehensive mapping and review of soundscape studies is imperative to understand its implications for potential inbound tourism research in future. This article aimed to explore potential soundscape studies by assessing trends and developments in recent decades (2013–2023). We applied a bibliometric approach, using a PRISMA framework and under NVivo 12 Plus, VOSViewer, and Biblioshiny-R-Studio software as analytical tools. Significant yield discoveries showed that tourism soundscape research is undergoing steady growth, as evidenced by quantity of publications and citation trends. Single and multi-country international collaborations characterized by soundscape outreach research playing an influential role were highlighted. We identified multiple research themes, such as anthropogenic noise and music heritage, and pointed out how we approached this research from two perspectives: environmental/natural and manufacturing/acoustics. In our review, several keywords and predominant themes were identified, which suggested soundscape studies have recently become an increasingly popular topic in tourism research. The broad spectrum of key themes, such a tourism, tourists, sustainability, areas, and development perspectives, are evidence points of significant diversity in these topics. Most importantly, our research offers significant theoretical and conceptual implications for future direction of soundscape studies. We identified three originality main focus domains in soundscape tourism research: urban and natural environments, technological advancements, and tourists’ perceptions and behaviors.

In this regard the key factor determining the success of the mining industry is the cost of electricity. By understanding the risks associated with crypto mining industry. The method is based on systemic literature review and bibliometric analysis exploring keyword “bitcoin mining”. This review paper studies 50 papers for the period of 2019–2023. The results propose recommendations for crypto miners. Currently, the results confirm that bitcoin mainly depends on the consumption of inexpensive electricity. Consequently, the bitcoin network predominantly uses energy in regions where it is abundant and cannot be stored or exported. Most miners rely on electricity generated from hydroelectric power plants, geysers and geothermal sources, which are not easy to transport or store. Bitcoin will continue to look for such cost-effective and underutilized energy sources, as mining in urban areas or industrial centers will remain financially unviable. If the price of bitcoin stabilizes and a sufficient number of miners enter the market, it is quite possible that in the near future we may witness a fivefold increase in their energy consumption.

This study systematically examines the literature of electric vehicle (EV) purchase intention and consumer behavior using a bibliometric method to unveil three main research questions: 1) identifying influential publications, authors, and journals; 2) analyzing the thematic evolution of research over time; and 3) identifying emerging research directions. The main objective is to provide a comprehensive understanding of the current state of knowledge and to guide future research in this evolving field. A comprehensive bibliometric analysis was conducted, using Scopus statistics analysis, R-Studio Biblioshiny and VOSviewer, comprising 687 publications authored by 1743 researchers representing 34 different countries with the dataset sourced from the Scopus database from 2010 to 2023. To achieve a nuanced understanding of the research landscape, a multifaceted approach was adopted, including detailed citation analysis, author co-citation analysis, keyword analysis, and thematic mapping. Through meticulous analysis, this study identifies the most influential publications, authors, and journals in the domain of EV purchase intentions and consumer behaviors. It also traces the evolution of themes over time and identifies emerging research directions, providing valuable insights into the trajectory and future avenues of inquiry within this field. The findings contribute to a deeper understanding of the dynamics shaping research in the realm of EVs. The insights gained contribute significantly to advancing knowledge in this crucial domain, offering theoretical insights and practical implications for policymakers, businesses, manufacturers, and academics.

This study provides an evaluation of the environmental impact and economic benefits associated with the disposal of mango waste in Thailand, utilizing the methodologies of life cycle assessment (LCA) and cost-benefit analysis (CBA) in accordance with internationally recognized standards such as ISO 14046 and ISO 14067. The study aimed to assess the environmental impact of mango production in Thailand, with a specific focus on its contribution to global warming. This was achieved through the application of a life cycle assessment methodology, which enabled the determination of the cradle-to-grave environmental impact, including the estimation of the mango production’s global warming potential (GWP). Based on the findings of the feasibility analysis, mango production is identified as a novel opportunity for mango farmers and environmentally conscious consumers. This is due to the fact that the production of mangoes of the highest quality is associated with a carbon footprint and other environmental considerations.  Based on the life cycle assessment conducted on conventional mangoes, taking into account greenhouse gas (GHG) emissions, it has been determined that the disposal of 1 kg of mango waste per 1 rai through landfilling results in an annual emission of 8.669 tons of carbon. This conclusion is based on comprehensive data collected throughout the entire life cycle of the mangoes. Based on the available data, it can be observed that the quantity of gas released through the landfilling process of mango waste exhibits an annual increase in the absence of any intervening measures. The cost benefit analysis conducted on the life cycle assessment (LCA) of traditional mango waste has demonstrated that the potential benefits derived from its utilization are numerous. The utilization of the life cycle assessment (LCA) methodology and the adoption of a sustainable business model exemplify the potential for developing novel eco-sustainable products derived from mango waste in forthcoming time.

The research utilizes a comprehensive dataset from MENA-listed companies, capturing data from 2013 to 2022 to scrutinize the influence of capital structure (CapSt) level on corporate performance across 11 distinct countries. This study analyzed 6870 firm-year observations using a quantitative research method through static and dynamic panel data analysis. The primary analysis reveals a positive correlation between the CapSt ratio and company performance using fixed effects (FE) techniques. Hence, the preliminary results were re-examined and affirmed using a two-step system generalized method of moment (GMM) estimator to address potential endogeneity concerns. This finding aligns with most studies conducted in advanced countries, indicating a positive correlation between CapSt and corporate performance. Furthermore, it is also consistent with some research conducted in less-developed markets. This research argues that, in the MENA region, the advantages of debt, such as tax saving, may outweigh the potential financial distress cost. Furthermore, it offers insights into the monitoring role of CapSt in MENA-listed companies. We strengthen our research results by employing various methodologies and using alternative measures of accounting performance and controlling size, notably panel quantile regression analysis.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.