This study addresses the impact of the tourism sector on poverty, poverty depth, and poverty severity in Indonesia, focusing on the micro-level dynamics in the province. Despite numerous tourism destinations, their strategic contribution to regional progress remains underexplored. The motivation stems from the need to comprehend the nuanced relationship between tourism and poverty at both the national and local levels, with specific attention to the untapped potential at the province level in Indonesia. We hypothesize that a higher tourism sector GRDP will be inversely correlated with poverty levels, and the inclusion of a Covid-19 variable will reveal a structural impact on poverty dynamics. Employing a Panel Regression Model, secondary data from the Central Statistics Agency (BPS) spanning 2011–2020 is utilized. A panel data regression equation model, including CEM, FEM, and REM, is employed to analyze the intricate relationship between tourism and poverty. The findings demonstrate a negative correlation between higher tourism sector GRDP and the number of poor people. The Covid-19 variable, considered a structural break, reveals a significant association between increased cases and elevated poverty and severity across Indonesian provinces. This study contributes a micro-level analysis of tourism’s role, emphasizing its impact at the provincial level. The findings underscore the need for strategic initiatives to harness the untapped potential of tourism in alleviating poverty and promoting regional progress.

This study aims to investigate the alignment of emerging skills and competencies with Continuous Professional Development (CPD) programs in the accounting and auditing professions. The research focuses on enhancing the intellectual capital within these sectors, as dictated by the demands of the modern knowledge economy. Employing the World Economic Forum’s (WEF) framework of emerging skills for professional services, a comprehensive content analysis is conducted. This involves reviewing 1009 learning outcomes across 248 CPD courses offered by the global professional accounting body. The analysis reveals that while the existing courses cover all WEF-identified skills, there is an unaddressed requirement for a specialized focus on specific competencies. The study also notes gaps in clearly articulated learning outcomes, highlighting the need for more explicit statements to facilitate effective skills development and knowledge transfer. This research contributes to the ongoing discourse on intellectual capital management strategies, providing actionable recommendations for professional organizations. It fills a critical gap in understanding how CPD offerings can be optimized to better prepare accounting and auditing professionals for the evolving knowledge economy.

This study uses the annual financial data of Chinese A-share listed firms from 2010 to 2020 to investigate the relationship between multiple large shareholders (MLS) and earnings management (EM). After analyzing the samples using the Ordinary Least Squares (OLS) model and endogenous switching regression (ESR) model, the empirical results show that the presence of MLS can increase corporate EM activities and the MLS have a significantly positive effect on EM in both the treatment and control groups. In addition, this conclusion still holds after conducting multiple robustness tests. The cross-section analysis shows that the external audit supervision quality, institutional shareholders, and the uncertainty of the external economic environment have significant impacts on the baseline model results. Lastly, mediation effect analysis shows that the presence of MLS increases the corporate operating risk through EM activities. The conclusions of this paper are critical for policymakers to supervise China’s capital market, improve the level of corporate governance of China’s listed firms, and further promote reform of ownership structure.

The COVID-19 epidemic is a significant humanitarian crisis witnessed in contemporary times, necessitating the exploration of techniques and approaches that might augment the capabilities of individuals within society to mitigate the adverse consequences of this pandemic. Domestic workers have always been an important part of societal structure, and it is essential to ensure their awareness about the perils of the pandemic as well as implement preventive measures. This is crucial in order to effectively address the hazards associated with the ongoing epidemic. The primary objective of this study was to assess the efficacy of infographic technology in augmenting the level of knowledge among foreign domestic workers on the COVID-19 epidemic. The present study employed a quasi-experimental design to examine and compare the effects of infographic technology on the experimental group, while the control group received only public awareness messages disseminated to all citizens and residents. The study sample comprised (16) foreign domestic workers, who were assigned to the two research groups through a random allocation process. The development of the COVID-19 pandemic awareness scale was conducted. The measurement scale consisted of three dimensions: the cognitive awareness dimension, including a set of (12) statements; the performative awareness dimension, comprising a set of (8) statements; and the psychological awareness dimension, comprising a set of (10) statements. The findings demonstrated the superiority of the experimental group, which used the infographic approach, over the control group in fostering awareness of the COVID-19 epidemic throughout its three dimensions among the participants of the study. The study suggested the need of expanding the utilization of infographics in an attempt to enhance knowledge and awareness of the COVID-19 pandemic, alongside the establishment of varied databases for migrant domestic workers. The objective is also to develop an extensive digital awareness strategy about the impacts of the COVID-19 epidemic, so as to include an increased number of informative infographics.

The world has changed to a massive degree in the past thousands of years. Most of the time, the amount of carbon dioxide in the atmosphere remains constant. In the late 18th century, according to the sources of CDIAC and NOOA, the level of carbon dioxide began to rise, and then in the 20th century, it went through the roof, reaching levels that had not been seen in nature for millions of years. The increase in carbon in the atmosphere is the major contributing factor to climate change. The key to reversing the damage is restoring the earth’s delicate, balanced carbon cycle. As carbon cycle depicts the way carbon moves around the earth. It consists of sources that emit the carbon component into the atmosphere. The biological side of the carbon cycle is well balanced due to respiration, where carbon dioxide is released into the atmosphere, then plants, bacteria, and algae take carbon dioxide out of the atmosphere during photosynthesis and the process they use to generate chemical energy. On the other hand, oceans are the best sources and sinks; carbon dioxide is endlessly being absorbed into the ocean and released from the oceans almost exactly at the same rate, which is rapidly influencing the carbon cycle. Similarity is a methodology that has many applications in the real world. The current research article is destined to study how statistics of carbon emission metrics are alike and belong to one cluster. In the current study, the research is destined to derive a similarity analysis of several countries’ carbon emission metrics that are alike and often fall in the range of [0, 1]. And deriving the proximity of the carbon emission metrics leading to similarity or dissimilarity. In the current context of data matrices of numerical data, an Euclidian measure of distance between two data elements will yield a degree of similarity. The current research article is destined to study the similarity analysis of carbon emission metrics through fuzzy entropy clustering.

In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.

Water-based, waterfront tourism has always played an important role in the development of the tourism sector, water has been and still is an important attraction and contributes to regional development. In Hungary, Lake Balaton is the primary destination for waterfront tourism, offering a wide range of opportunities in this sector. Water-based, waterfront tourism is mainly concentrated in the high summer season, but there is an increasing range of opportunities in both the low and high season. In our research, we investigated the development of cruise tourism in Lake Balaton in the off-season, in the months of September-October 2023, by conducting in-depth interviews and questionnaire research. Our research has confirmed that this service is also in demand outside the high season. In the autumn, cruises add a special value to the experience, they can help to reduce seasonal fluctuations in tourism by offering attractive activities and also increase income for local businesses during the off-season.

The focus of the article is the evaluation of the interaction between regional state bodies and business structures in Kazakhstan, specifically in terms of the development of public-private partnerships. The purpose of the research is to enhance the understanding of the theoretical and practical aspects of the mechanism of interaction between the state and business structures. Through an examination of the various structural components of the partnership development strategy, the study aims to identify the elements of the mechanism for the implementation of the state and business development strategy. Additionally, the research seeks to establish the correlation between the outcomes of the joint entrepreneurship mechanism and the criteria used to evaluate the performance of regional state bodies. To assess the effectiveness of the interaction between business and government at the regional level in Kazakhstan, a survey-based evaluation was conducted to measure the satisfaction levels of public utilities, entrepreneurs, and businesses with the activities of local authorities. The survey also evaluated the degree of corruption among local authorities. A matrix of interaction between business and government was created, and various models and algorithms for the interaction between government representatives and business structures were studied. The research findings highlight the importance of enhancing the collaboration between the state and the business sector, promoting the implementation of public-private partnerships, and establishing social partnerships to cultivate mutually beneficial relationships.