High-quality implementation of cross-border mergers and acquisitions (cross-border M&As) is an important pathway for emerging-market multinational enterprises (EMNEs) to enhance their international competitiveness. However, in comparison to developed countries, cross-border M&As by EMNEs are often prohibited by the liability of origin caused by negative political coverage. How and why negative political coverage affect the completion of cross-border M&As by EMNEs? What are the contextual constraints that moderate the impact of negative political coverage on cross-border M&As completion? Based on the “liability of origin” theory, this paper addresses these questions using data from the Zephyr database on cross-border M&As by EMNEs in the United States from 2016 to June 2021 and employing a logit model for estimation. The research findings are as follows: (1) Negative political coverage leads to negative perceptions of emerging market countries by host country stakeholders, creating the liability of origin and stigmatizing the corporate nationality, thereby reducing the success rate of cross-border M&As by EMNEs. (2) Increasing geographical distance leads to information asymmetry, reinforcing the negative impact of negative political coverage on the completion of cross-border M&As by EMNEs. (3) Relevant mergers and acquisitions exacerbate the negative effect of negative political coverage on the success rate of cross-border M&As by EMNEs. (4) Being a publicly traded firm and having successful experience in cross-border M&As both intensify the negative impact of negative political coverage on the success rate of cross-border M&As by EMNEs.
Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X1 + 4.276X2, where Y is biomass, X1 is the diameter, and X2 is the tree height. Based on the results of the t-test: variable X1 partially affected Y while variable X2 partially had no effect on Y. The F-test indicated that variables X1 and X2 jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X1, where X1 = tree diameter, Y = Total biomass with R = 0.957, and R2 = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.
The study looks at Ghana’s mining industry’s audit culture and green mining practices about their social responsibility to the communities where their mines are located. Results: According to this study, the economic motivations of mines and green mining are inversely related. Even large mining companies incur significant costs associated with their green mining initiatives because they require a different budget each year, which has an impact on their ability to maximize wealth. Conversely, mines with strong green mining initiatives enjoy positive public perception, and vice versa. Ghanaian mines do not have pre- or during-mining strategies; instead, they only have post-social and post-environmental methods. The best method for evaluating mines’ environmental performance in the community in which they operate is, according to this study, social auditing. This is primarily influenced by the mine’s audit culture, but it is also influenced by the auditor’s compliance with audit processes, audit guidelines, and, ultimately, the audit firm’s experience. The analysis confirms that Ghana’s mine environmental performance is appallingly low since local audit firms are not used in favor of foreign auditors who lack experience or empathy for the problems encountered by these mining communities. Last but not least, corporate social responsibility (CSR) is connected to Ghana’s development of green mining, either directly or indirectly. Whether the mine adopts a technocrat, absolutist, or relativist perspective on mining will determine this. The study discovered that, in contrast to the later approach, the first two views generate work in a mechanistic manner with little to no consideration for CSR.
India’s economic growth is of significant interest due to its expanding Gross Domestic Product (GDP) and global market influence. This study investigates the interplay between production, trade, carbon dioxide (CO2) emissions, and economic growth in India using Granger causality analysis. Also, the data from 1994 to 2023 were analyzed to explore the relationships among these variables. The results reveal strong positive correlations among production, trade, CO2 emissions, and GDP, with production showing significant associations with export, import, and GDP. Co-integration tests confirm the presence of a long-term relationship among the variables, suggesting their interconnectedness in shaping India’s economic landscape. Regression analysis indicates that production, export, import, United States (US)-India trade, manufacturing cost of energy, and CO2 emissions significantly impact GDP. Moreover, the Vector Error Correction Model (VECM) estimation reveals both short-term and long-term dynamics, highlighting the importance of understanding equilibrium and deviations in economic variables. Overall, this study contributes to a better understanding of the complex interactions driving India’s economic growth and sustainability.
This article emphasizes the importance of Small and Medium-Sized Enterprises (SMEs) and large companies in driving economic growth. SMEs are labour-intensive and agile, creating more jobs, while large companies are capital-intensive and rely on technology, having more resources for research and development. In the Gulf Cooperation Council (GCC) region, SMEs contribute significantly to Gross Domestic Product (GDP) and job opportunities, while large companies dominate specific sectors. The research employs a multidisciplinary approach using an extensive literature review to summarize the current literature, highlight the economic impact of SMEs and large companies in GCC, and highlight the importance of large companies in developing local citizens. Policy-makers must consider these differences to integrate these dynamic changes for effective support policies. This study examines the economic impact of SMEs and large companies in the GCC region, providing recommendations to support large businesses. It addresses challenges and opportunities related to employment, household earnings, economic output, and value addition. Promoting the economic impact of SMEs and large companies can lead to sustainable economic growth and development in the GCC region. Also, this article pointed out the importance of large companies and their economic impact in the GCC region; policy recommendations will help the governing bodies in decision-making towards promoting sustainable economic growth.
The intersex person’s social isolation condition is the leading concern in inclusive educational practices. It provides for the relevance of intersex communities with the influence of social isolation on their education and well-being. Given the underlying problem, this paper stresses the isolation-free condition of the intersex community by facilitating inclusive education. The Atkinson and Shiffrin Model and Behaviorism-Based Intersex Theory supports inclusive education by extending the desire to significantly manage stereotypes, quality teaching, parental beliefs, expressions, physique, and intersex attribution. The qualitative research method analyses the reducing role of social isolation for inclusive education. The semi-structured interview research instrument is used for the data collection from the Ministry of Human Rights, Educational Institutions, and inter-sex Representatives. The results show that managing directors and heads of educational institutions frame policy management for the free social isolation of intersex persons, which is relevant through inclusive education. This paper aims to provide a better social condition for intersex persons and promote inclusive education through effective policy management.
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