The growing interconnectedness of the world has led to a rise in cybersecurity risks. Although it is increasingly conventional to use technology to assist business transactions, exposure to these risks must be minimised to allow business owners to do transactions in a secure manner. While a wide range of studies have been undertaken regarding the effects of cyberattacks on several industries and sectors, However, very few studies have focused on the effects of cyberattacks on the educational sector, specifically higher educational institutions (HEIs) in West Africa. Consequently, this study developed a survey and distributed it to HEIs particularly universities in West Africa to examine the data architectures they employed, the cyberattacks they encountered during the COVID-19 pandemic period, and the role of data analysis in decision-making, as well as the countermeasures employed in identifying and preventing cyberattacks. A total of one thousand, one hundred and sixty-four (1164) responses were received from ninety-three (93) HEIs and analysed. According to the study’s findings, data-informed architecture was adopted by 71.8% of HEIs, data-driven architecture by 24.1%, and data-centric architecture by 4.1%, all of which were vulnerable to cyberattacks. In addition, there are further concerns around data analysis techniques, staff training gaps, and countermeasures for cyberattacks. The study’s conclusion includes suggestions for future research topics and recommendations for repelling cyberattacks in HEIs.

This article presents an analysis of Russia’s outward foreign direct investment based on the balance of payments. The country has been affected by the “Dutch disease,” characterized by a heavy reliance on the mining industry and revenues from oil and gas exports. The financial account reveals a consistent outflow of capital from Russia, surpassing inflows. A significant portion of domestic investment goes abroad, often to offshore destinations. This capital outflow has not been fully offset by foreign capital inflows. These findings underscore the challenges faced by Russia in managing its financial position, including the need to address capital outflows, diversify the economy, and reduce dependence on raw material exports. Furthermore, this article aims to identify the presence of Russian capital in OECD countries by comparing data from the Central Bank of Russia and the OECD. The analysis reveals significant discrepancies between the two datasets, primarily due to unavailable or confidential information in the OECD dataset. These variations can also be attributed to differences in methodology and the specific nature of Russian outward direct investments, particularly those involving offshore jurisdictions. As a result, accurately determining the extent of Russian capital in OECD countries based on the available data becomes a challenging task (including for the tourism industry as well).

The advent of the era of big data has brought great changes to accounting work, and vocational colleges and universities, as the main place for cultivating application-oriented new business talents, need to change the way of talent training in time in the face of this change. By describing the impact of the era of big data on the demand for new business talents, this paper analyzes the analysis of the training of new business and scientific and technological talents in vocational colleges and universities in the era of big data from the perspectives of talent training target positioning, professional curriculum setting and teacher quality, accurately locates the talent training goals of new business professional groups in vocational colleges, scientifically sets up the curriculum system, and comprehensively improves the teaching staff.

Strategically managing production systems is crucial for creating value and enhancing the competitive capabilities of companies. However, research on organizational culture within these systems is scarce, particularly in the Colombian context. This research aims to evaluate cultural profiles and their impact on the performance of production systems in Colombian firms. The regional focus is vital as cultural and contextual factors can vary significantly between regions, influencing organizational behavior and performance outcomes. To achieve this, we make a study in a sample of Colombian companies, with participation from working students of the Universidad Nacional Abierta y a Distancia (UNAD). We used a data analytics approach to collected data. The results will be relevant to both the scientific community and business practitioners. This research seeks to determine whether the perception of the work environment within a company influences the perceived performance of the company. The findings will provide a deeper understanding of the relationship between organizational culture and production system performance, offering a foundation for business decision-making and enhancing competitiveness in Latin American context.

Oil spills (OS) in waters can have major consequences for the ecosystem and adjacent natural resources. Therefore, recognizing the OS spread pattern is crucial for supporting decision-making in disaster management. On 31 March 2018, an OS occurred in Balikpapan Bay, Indonesia, due to a ship’s anchor rupturing a seafloor crude oil petroleum pipe. The purpose of this study is to investigate the propagation of crude OS using coupled three-dimensional (3D) model from DHI MIKE software and remote sensing data from Sentinel-1 SAR (Synthetic Aperture Radar). MIKE3 FM predicts and simulates the 3D sea circulation, while MIKE OS models the path of oil’s fate concentration. The OS model could identify the temporal and spatial distribution of OS concentration in subsurface layers. To validate the model, in situ observations were made of oil stranded on the shore. On 1 April 2018, at 21:50 UTC, Sentinel-1 SAR detected an OS on the sea surface covering 203.40 km². The OS model measures 137.52 km². Both methods resulted in a synergistic OS exposure of 314.23 km². Wind dominantly influenced the OS propagation on the sea surface, as detected by the SAR image, while tidal currents primarily affected the oil movement within the subsurface simulated by the OS model. Thus, the two approaches underscored the importance of synergizing the DHI MIKE model with remote sensing data to comprehensively understand OS distribution in semi-enclosed waters like Balikpapan Bay detected by SAR.

Terms and Conditions are always encountered when using social media applications to determine which data can be accessed and what cannot.  However, there are shortcomings in their implementation and communication, often causing users to be unwilling to read them. Therefore, this study aimed to analyze the effectiveness of implementing partial consent in Terms and Conditions concerning user Data Awareness and Data Security in social media. This Paper administered a questionnaire, distributed with a form, to students who use social media to understand their opinions regarding the partial consent concept. This paper analyzed the data using descriptive statistical methods. The results show a positive response from respondents towards implementing the partial consent concept, the users feel the terms and conditions are more effective in increasing user data awareness and security.