The purpose of this paper is to analyze the Diversity Management implementation in 005.95(536.8)

The paper analyses the firm-level factors that encourage companies from the Gulf countries to conduct investments in the Middle East and North Africa (MENA) using mergers and acquisitions. Numerous local investors do not seem to be deterred by dissuasive locational variables and ineffective integration in the MENA region. Trade agreements amongst MENA countries, e.g., Arab Maghreb Union, Gulf Cooperation Council (GCC), and the Arab Cooperation Council did not enhance foreign direct investment (FDI) between those nations due to structural gaps and incongruences. Therefore, the aim of this research consists in investigating the extent to which GCC firms' decisions to conduct investments in MENA region are explained by their characteristics (size, age, performance, state ownership, and debt structure). Those factors are assumed to exert an influence on M&A decisions along with other institutional and economic factors. The findings reveal that while firm's size and performance exert a positive effect on a firm's decision to expand within MENA region, state ownership has a negative influence. The study also aligns with the results from more mainstream research

Debt finance, when considered a source of finance, always leads to financial risk; however, it is also considered a source of increased profitability in the normal business scenario. It has always been challenging to find the correct debt equity combination. In the discussed sample of the telecom industry in the USA, an abnormally high total liability-to-total assets ratio was observed. Thus, it is inclined to investigate the capital structure (CapSt) effect on firms’ profitability. By taking annual data of the telecom industry from 2012 to 2020 in the USA, unbalanced cross-sectional data (panel data) comprising 421 firm-year observations for 72 firms were studied using pooled panel regression, univariate analysis, correlation, and descriptive statistics models. We decided to test the impact of CapSt (Total Liabilities to Total Assets (TLsTAs) and Total Equity to Total Assets (TETAs)) on the profitability (Return on Assets (ROA) and Return on Equity (ROE)) of firms in the telecommunication industry in the USA. The results reveal that the ratio of TLsTAs has a significant impact on ROA, and TETAs has a significant impact on ROA. However, TLsTAs and TETAs have no impact on ROE.

This paper analyzes the financial feasibility of an open ocean sea bass farm that employs Innovasea technology in the offshore French Mediterranean Sea. Innovasea technology uses a suite of sensors, enhanced artificial intelligence and other advanced offshore technology to reduce labor costs, increase production, and lower environmental sensitivities related to fish medication and pesticides, fish mortality, excess feed losses, parasitic infections, and lack of monitoring. This study was conducted by employing a spatial analysis to identify the most suitable location, taking into consideration bathymetry, significant wave height, current velocity, distance from shore, and vessel traffic density. 80 cost categories were subsequently identified and populated, as were associated depreciation costs. In the ensuing financial analysis, the farm was projected to produce 5220 tons of sea bass annually (live weight equivalent) with an initial capital investment of $39,924,456, an IRR of 19.43%, and a project NPV of $681,583,178 (cash flow NPV of $113,227,788 and a horizon value NPV of $568,355,390). By approving this farm through existing regulatory parameters that facilitate existing mariculture operations, France stands to meet sustainability and production objectives that it has set for itself. This farm can help advance humanity across many domains including aquaculture, world food supply, upward economic mobility, employment, sustainability, the ocean economy, and maritime engineering. These domains interface strongly with United Nations Sustainable Development Goals 1 (No Poverty), 2 (Zero Hunger), 3 (Good Health and Well-Being), 8 (Decent Work and Economic Growth), 12 (Responsible Consumption and Production), and 14 (Life Below Water).

This article consists a review of the existing literature on artificial intelligence (AI) with respect to financial crimes. The purpose is to notify the unintentional bad impacts and intentional good impacts of AI applications in relation to financial crimes. This article has reinforced the discussions stating AI applications to be considered as a solution for financial crimes instead of being criticized as the cause for financial crime. The public and private sectors both need be alert with the unintentional harm caused by cybercrime. The current behavior of AI is considered as an accelerator or an antidote to financial crimes, specific to cybercrimes. It is advised to apply criminal law to control cybercrimes. However, holding the AI agents responsible is considered to be an inappropriate mechanism. Thus, AI systems are still not deemed to be capable of forming a proper legitimate system in order to curb the financial crimes.