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.

Electoral contestation in recent Indonesian election periods is faced with the challenge of polarization linked to identity politics, where initially assigned identity is leveraged as tools for political competition. This is a qualitative research, using interviews, observations, and direct group discussion methods to collect data from five different regions in Indonesia. The research focused on the presence of governing regulations and how they develop in complex dynamics. The results showed that identity politics was prevalent in all regions due to mobilization through identity manipulation to gain electoral political advantage. Furthermore, electoral characteristics showed a growing tendency toward polarization, primarily in terms of religion and ethnicity, with some issues related to regionalism, gender, religious affiliations, and family history networks. It was also found that weak regulations on identity manipulation led to increasing permissiveness among political actors, the state, and voters. This made identity issues become natural electoral problems, despite weakening the developing democracy in Indonesia. In this context, future contests in Indonesia are expected to consistently intensify identity politics, with the lack of regulations, permissiveness, and social media serving as the main driving factors.

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.

Through Qualitative Comparative Analysis (QCA) on destination attractiveness characteristics at the country level, this study identifies attribute configurations in the pre- and post-pandemic period to analyze the changes and differences generated by an exogenous event (COVID-19). The results suggest that the destination attractiveness attributes work together, in multidimensional configurations, to increase leisure travel volume. We found an important change in pat-terns/configurations of attractiveness between the pre- and post-pandemic scenarios. Our findings suggest that the destination attributes may change in importance and valuation or disappear for some configurations. The conclusion has implications for the stakeholders related to the destination attractiveness development, showing possible patterns of tourism attributes to guide the action to improve the resilience in the tourism sector and recover these activities in a disaster scenario.

This study investigates the influence of government expenditure on the economic growth of the ASEAN-5 countries from 2000 to 2021. The study employs the Pooled Mean Group (PMG) ARDL model and robust least squares method. The importance of the current study lies in its analysis of the short and long-run impact of government expenditure on economic growth in ASEAN-5. The empirical findings demonstrate a positive relationship between government expenditure and economic growth in the long run. These results align with the Keynesian perspective, asserting that government expenditure stimulates economic growth. The study also confirms one-way causality from government expenditure to economic growth, supporting the Keynesian hypothesis. These insights hold significance for policymakers in the ASEAN-5, highlighting the necessity for policies promoting the effective allocation of productive government expenditure. Moreover, it is important to enhance systems that promote economic growth and efficiently allocated economic resources toward productive expenditures while also maintaining effective governance over such expenditures.

Personal data privacy regulation and mitigation are critical in implementing financial technology (fintech). Problems with fintech users’ data might result from data breaches, improper usage, and trade. Issues with personal data will result in financial losses, crimes, and violations of personal information. This legal research used three approaches: conceptual, comparative, and statute-based. In order to implement the statutory method, all laws and regulations pertaining to the legal concerns of information technology, fintech, personal data security, and protection are reviewed. Due to the nature of the sources of data, this study mainly used literature study and document observation to collect the data. Then, legal interpretation, legal reasoning, and legal argumentation are all included in the qualitative juridical analysis. This article recommends two strategies that Indonesia should take to provide personal data protection, including: 1) establishing the Personal Data Protection Commission (PDPC); and 2) improving the financial literacy of consumers.

This paper aims to research the impact of psychological contract fulfilment on employee innovative work behaviour, and the mediating role of work engagement and the moderating role of social support. A quantitative analysis was adopted to address in research. Two-wave data were collected from 332 respondents working in China. Hierarchical regression analyses were conducted to assess the proposed hypotheses. Results revealed that psychological contract fulfilment positively impacted innovative work behaviour. In addition, engagement partially mediated the relationship between psychological contract fulfilment and innovative work behaviour. Furthermore, the findings suggest that social support moderates the relationship between work engagement and innovative work behaviour, and, in turn, moderates the indirect effect of psychological contract fulfilment on innovative work behaviour through work engagement. This research extends the generalizability of findings in the psychological contract literature. The results bear significant implications for the management of employees’ innovative work behaviour.

The study’s purpose is to evaluate the influence of some factors of the model of planned behavior (TPB) and the perceived academic support of the university on the attitude toward entrepreneurship and entrepreneurial intention of students. The results of Structural Equation Modeling (SEM) linear structural model analysis with primary data collected from 1162 students indicated that entrepreneurial intention is influenced by attitude toward entrepreneurship, subjective norm, perceived educational support, and perceived concept development support. In addition, this study also found the positive influence of perceived educational support, concept development support, and business development support on attitude towards entrepreneurship. Interestingly, the influence of perceived business development support on entrepreneurial intention was rejected, and personal innovativeness is demonstrated to promote an attitude toward entrepreneurship. Notably, this study also highlights the moderating role of personal innovativeness on the relationship between attitude toward entrepreneurship and entrepreneurial intention. Based on these findings, several implications were suggested to researchers, universities, and policymakers.